In vivo endoscopic tissue identification tool

Abstract

An apparatus is disclosed including a tool comprising a first device for generating aerosol from a target, the first device being deployed through an opening in a tubing of the tool, wherein the tubing is provided with aspiration ports or fenestrations such that the generated aerosol is aspirated into the tubing via the aspiration ports or fenestrations. The aspirated aerosol is then transferred to a mass spectrometer for subsequent mass analysis.

Claims

1. An apparatus for analysis comprising: a tool comprising an ambient ion source located within a tubing or a housing, wherein said tubing or said housing comprises a tool deployment opening and one or more aspiration ports separate to the tool deployment opening; a suction device arranged and adapted to aspirate aerosol, smoke or vapour generated using said ambient ion source through said one or more aspiration ports providing in the tubing or housing; a mass spectrometer and/or ion mobility spectrometer; tubing which is arranged and adapted to pass said aerosol, smoke or vapour into a vacuum chamber of said mass spectrometer and/or ion mobility spectrometer; and a collision surface located within a vacuum chamber of said mass spectrometer and/or ion mobility spectrometer arranged such that the aerosol, smoke or vapour passed into the vacuum chamber can then be ionised by colliding with the collision surface; wherein, through an inlet of the mass spectrometer and/or ion mobility spectrometer, the mass spectrometer and/or ion mobility spectrometer is operative to add a matrix to said aerosol, smoke or vapour prior to said aerosol, smoke or vapour impacting upon said collision surface, wherein said matrix comprises a matrix selected from the group consisting of: (i) an organic solvent; (ii) one or more alcohols; (iii) methanol; (iv) ethanol; (v) isopropanol; (vi) acetone; and (vii) acetonitrile.

2. The apparatus as claimed in claim 1, wherein said ambient ion source comprises a laser device.

3. The apparatus as claimed in claim 1, wherein said ambient ion source is selected from the group consisting of: (i) a rapid evaporative ionisation mass spectrometry (“REIMS”) ion source; (ii) a desorption electrospray ionisation (“DESI”) ion source; (iii) a laser desorption ionisation (“LDI”) ion source; (iv) a thermal desorption ion source; (v) a laser diode thermal desorption (“LDTD”) ion source; (vi) a desorption electro-flow focusing (“DEFFI”) ion source; (vii) a dielectric barrier discharge (“DBD”) plasma ion source; (viii) an Atmospheric Solids Analysis Probe (“ASAP”) ion source; (ix) an ultrasonic assisted spray ionisation ion source; (x) an easy ambient sonic-spray ionisation (“EASI”) ion source; (xi) a desorption atmospheric pressure photoionisation (“DAPPI”) ion source; (xii) a paperspray (“PS”) ion source; (xiii) a jet desorption ionisation (“JeDI”) ion source; (xiv) a touch spray (“TS”) ion source; (xv) a nano-DESI ion source; (xvi) a laser ablation electrospray (“LAESI”) ion source; (xvii) a direct analysis in real time (“DART”) ion source; (xviii) a probe electrospray ionisation (“PESI”) ion source; (xix) a solid-probe assisted electrospray ionisation (“SPA-ESI”) ion source; (xx) a cavitron ultrasonic surgical aspirator (“CUSA”) device; (xxi) a focussed or unfocussed ultrasonic ablation device; (xxii) a microwave resonance device; and (xxiii) a pulsed plasma RF dissection device.

4. The apparatus as claimed in claim 1, wherein said ambient ion source comprises one or more electrodes.

5. The apparatus as claimed in claim 1, wherein said tool comprises either: (i) an electrode which is extendable from and/or retractable within said tubing or housing; (ii) an optical fibre for directing laser radiation on to tissue or another surface, wherein said optical fibre is extendable from and/or retractable within said tubing or housing; (iii) an argon plasma coagulation device or a hybrid argon plasma coagulation device; or (iv) a water jet device or a hydrosurgical or surgical water jet device.

6. The apparatus as claimed in claim 1, further comprising an endoscope.

7. The apparatus as claimed in claim 6, wherein said endoscope comprises a port, wherein said tool configured to be deployed through said port.

8. The apparatus as claimed in claim 1, wherein said suction device is arranged and adapted to aspirate said aerosol, smoke or vapour through said one or more aspiration ports in a substantially continuous manner.

9. The apparatus as claimed in claim 1, wherein said suction device is arranged and adapted to aspirate said aerosol, smoke or vapour through said one or more aspiration ports in a substantially pulsed, discontinuous or irregular manner.

10. The apparatus as claimed in claim 1, further comprising a heating device which is arranged and adapted to heat said collision surface.

11. The apparatus as claimed in claim 1, further comprising an alarm which is arranged and adapted to: receive an indication of a type of tissue being analyzed by the mass spectrometer and/or ion mobility spectrometer, and generate feedback responsive to the tissue being from an undesired target region or area.

12. The apparatus as claimed in claim 1, further comprising an analysis device for analysing one or more sample spectra so as to classify said aerosol, smoke or vapour sample using one or more of: (i) univariate analysis; (ii) multivariate analysis; (iii) principal component analysis (PCA); (iv) linear discriminant analysis (LDA); (v) maximum margin criteria (MMC); (vi) library-based analysis; (vii) soft independent modelling of class analogy (SIMCA); (viii) factor analysis (FA); (ix) recursive partitioning (decision trees); (x) random forests; (xi) independent component analysis (ICA); (xii) partial least squares discriminant analysis (PLS-DA); (xiii) orthogonal (partial least squares) projections to latent structures (OPLS); (xiv) OPLS discriminant analysis (OPLS-DA); (xv) support vector machines (SVM); (xvi) (artificial) neural networks; (xvii) multilayer perceptron; (xviii) radial basis function (RBF) networks; (xix) Bayesian analysis; (xx) cluster analysis; (xxi) a kernelized method; and (xxii) subspace discriminant analysis.

13. The apparatus as claimed in claim 1, wherein the matrix comprises isopropanol.

14. An apparatus for analysis comprising: a tool comprising an ambient ion source located within a tubing or a housing, wherein said tubing or said housing comprises a tool deployment opening and one or more aspiration ports separate to the tool deployment opening; a suction device arranged and adapted to aspirate aerosol, smoke or vapour generated using said ambient ion source through said one or more aspiration ports providing in the tubing or housing; and a mass spectrometer and/or ion mobility spectrometer; the apparatus further comprising: tubing which is arranged and adapted to pass said aerosol, smoke or vapour into a vacuum chamber of said mass spectrometer and/or ion mobility spectrometer; a collision surface located within a vacuum chamber of said mass spectrometer and/or ion mobility spectrometer arranged such that the aerosol, smoke or vapour passed into the vacuum chamber can then be ionised by colliding with the collision surface; and an interface to a matrix for adding the matrix to said aerosol, smoke or vapour, wherein said matrix is added, in use, to said aerosol, smoke or vapour prior to said aerosol, smoke or vapour impacting upon said collision surface, wherein said matrix comprises a matrix selected from the group consisting of: (i) an organic solvent; (ii) one or more alcohols; (iii) methanol; (iv) ethanol; (v) isopropanol; (vi) acetone; and (vii) acetonitrile.

15. An apparatus for analysis comprising: a tool comprising an ambient ion source located within a tubing or a housing, wherein said tubing or said housing comprises a tool deployment opening and one or more aspiration ports separate to the tool deployment opening; a suction device arranged and adapted to aspirate aerosol, smoke or vapour generated using said ambient ion source through said one or more aspiration ports providing in the tubing or housing; and a mass spectrometer and/or ion mobility spectrometer; tubing which is arranged and adapted to pass said aerosol, smoke or vapour into a vacuum chamber of said mass spectrometer and/or ion mobility spectrometer; and a collision surface located within a vacuum chamber of said mass spectrometer and/or ion mobility spectrometer arranged such that the aerosol, smoke or vapour passed into the vacuum chamber can then be ionised by colliding with a collision surface; wherein, through an inlet of the mass spectrometer and/or ion mobility spectrometer, the mass spectrometer and/or ion mobility spectrometer is operative to add a matrix to form a mixture with said aerosol, smoke or vapour to dissolve analyte molecules within said aerosol, smoke or vapour, prior to causing the mixture to impact upon said collision surface, wherein said matrix comprises a matrix selected from the group consisting of: (i) an organic solvent; (ii) one or more alcohols; (iii) methanol; (iv) ethanol; (v) isopropanol; (vi) acetone; and (vii) acetonitrile.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) Various embodiments will now be described, by way of example only, and with reference to the accompanying drawings, in which:

(2) FIG. 1 illustrates a method of rapid evaporative ionisation mass spectrometry (“REIMS”) wherein an RF voltage is applied to bipolar forceps resulting in the generation of an aerosol or surgical plume which is captured through an irrigation port of the bipolar forceps and is then transferred to a mass spectrometer for ionisation and mass analysis;

(3) FIG. 2 shows a polypectomy snare according to an embodiment;

(4) FIG. 3A shows an endoscopic experimental setup wherein endoscopic tubing is equipped with an additional T-piece in order to establish a direct connection between an electrosurgical electrode tip and a mass spectrometer for the transfer of electrosurgical aerosol and FIG. 3B shows a resection of a GI polyp according to an embodiment wherein an electrosurgical snare is used to capture a polyp using the snare loop so that the polyp is securely fastened around its base and then electrosurgical dissection is performed and the resulting surgical smoke or aerosol is aspirated through fenestrations provided in the plastic sheath of the electrosurgical tool;

(5) FIG. 4A shows mass spectra of gastric mucosa, gastric submucosa and adenocarcinoma tissue which was recorded using a modified Xevo G2-S® Q-Tof mass spectrometer (Waters®), wherein cancerous and healthy mucosa tissue feature mainly phospholipids in the 600-900 m/z range whilst submucosa feature triglyceride and phosphatidyl-inositol species in the 800-1000 m/z range and FIG. 4B shows a comparison of the abundance of selected peaks showing significant differences between cancerous and healthy tissue in the 600-900 m/z range using Kruskal-Wallis ANOVA wherein all peaks above m/z 800 are significantly different when comparing submucosa to the other two tissue types;

(6) FIG. 5A shows a 3-dimensional PCA plot of human colon adenocarcinoma (n=43) and healthy colon mucosal data (n=45) acquired from seven patients using an LTQ Velos® mass spectrometer wherein the adenomatous polyps (n=5) collected from two patients were sampled ex vivo after their removal and wherein a significant difference can be observed in the PCA space between all three groups and FIG. 5B shows a 3-dimensional PCA plot of healthy gastric mucosa (n=32), gastric submucosa (n=10) and adenocarcinoma of the stomach (n=29) acquired from three patients ex vivo using a Xevo G2-S® Q-Tof mass spectrometer (Waters®) wherein significant differences between submucosa and the other two layers may be used to provide a perforation risk alert system for interventional endoscopy according to an embodiment;

(7) FIG. 6A shows in vivo utilization of a rapid evaporative ionisation mass spectrometry compatible endoscope system according to an embodiment and sampling points taken from three patients undergoing colonoscopy and FIG. 6B shows the sampling points depicted on a 3-dimensional PCA plot wherein the spectra acquired in vivo when the polyps were removed localize in a different part of space whilst all other mucosal spectra are quasi uniformly independent from the sampling location;

(8) FIG. 7 shows three different configurations of fenestrations on a snare tubing that were tested according to an embodiment;

(9) FIG. 8 illustrates an ex vivo testing method which was arranged to simulate an endoscopic environment;

(10) FIG. 9 shows a linear discriminant analysis plot comparing the testing for the three different configurations of fenestration illustrated in FIG. 7;

(11) FIG. 10 shows a linear discriminant analysis plot comparing the testing of two different wire snare types;

(12) FIG. 11 shows a method of analysis that comprises building a classification model according to various embodiments;

(13) FIG. 12 shows a set of reference sample spectra obtained from two classes of known reference samples;

(14) FIG. 13 shows a multivariate space having three dimensions defined by intensity axes, wherein the multivariate space comprises plural reference points, each reference point corresponding to a set of three peak intensity values derived from a reference sample spectrum;

(15) FIG. 14 shows a general relationship between cumulative variance and number of components of a PCA model;

(16) FIG. 15 shows a PCA space having two dimensions defined by principal component axes, wherein the PCA space comprises plural transformed reference points or scores, each transformed reference point or score corresponding to a reference point of FIG. 13;

(17) FIG. 16 shows a PCA-LDA space having a single dimension or axis, wherein the LDA is performed based on the PCA space of FIG. 15, the PCA-LDA space comprising plural further transformed reference points or class scores, each further transformed reference point or class score corresponding to a transformed reference point or score of FIG. 15;

(18) FIG. 17 shows a method of analysis that comprises using a classification model according to various embodiments;

(19) FIG. 18 shows a sample spectrum obtained from an unknown sample;

(20) FIG. 19 shows the PCA-LDA space of FIG. 16, wherein the PCA-LDA space further comprises a PCA-LDA projected sample point derived from the peak intensity values of the sample spectrum of FIG. 18;

(21) FIG. 20 shows a method of analysis that comprises building a classification library according to various embodiments; and

(22) FIG. 21 shows a method of analysis that comprises using a classification library according to various embodiments.

DETAILED DESCRIPTION

(23) Various embodiments will now be described in more detail below which in general relate to an endoscope coupled with an ambient ionisation ion source.

(24) Aerosol, surgical smoke or vapour is aspirated via one or more aspirations ports or fenestrations into a sheath which may surround a portion of the tool. The aerosol, surgical smoke or vapour may then be passed into tubing which may transfer the aerosol, surgical smoke or vapour to the inlet of a mass spectrometer. The aerosol, surgical smoke or vapour may pass into a vacuum chamber of the mass spectrometer and may be caused to impact upon a collision surface causing the aerosol, smoke or vapour to be ionised by impact ionisation and resulting in the generation of analyte ions.

(25) The resulting analyte ions (or fragment or product ions derived from the analyte ions) may then be mass analysed and the resulting mass spectrometric data may then be subjected to multivariate analysis in order to determine one or more properties of the target (e.g. tissue) in real time.

(26) For example, the multivariate analysis may enable a determination to be made as to whether or not a portion of tissue which is currently being resected is cancerous or not.

(27) Ambient Ionisation Ion Sources

(28) According to various embodiments a device is used to generate an aerosol, smoke or vapour from one or more regions of a target (e.g., in vivo tissue). The device may comprise an ambient ionisation ion source which is characterised by the ability to generate analyte aerosol, smoke or vapour from a native or unmodified target. For example, other types of ionisation ion sources such as Matrix Assisted Laser Desorption Ionisation (“MALDI”) ion sources require a matrix or reagent to be added to the sample prior to ionisation.

(29) It will be apparent that the requirement to add a matrix or a reagent to a sample prevents the ability to perform in vivo analysis of tissue and also, more generally, prevents the ability to provide a rapid simple analysis of target material.

(30) In contrast, therefore, ambient ionisation techniques are particularly advantageous since firstly they do not require the addition of a matrix or a reagent (and hence are suitable for the analysis of in vivo tissue) and since secondly they enable a rapid simple analysis of target material to be performed.

(31) A number of different ambient ionisation techniques are known and are intended to fall within the scope of the present invention. As a matter of historical record, Desorption Electrospray Ionisation (“DESI”) was the first ambient ionisation technique to be developed and was disclosed in 2004. Since 2004, a number of other ambient ionisation techniques have been developed. These ambient ionisation techniques differ in their precise ionisation method but they share the same general capability of generating gas-phase ions directly from native (i.e. untreated or unmodified) samples. A particular advantage of the various ambient ionisation techniques which are intended to fall within the scope of the present invention is that the various ambient ionisation techniques do not require any prior sample preparation. As a result, the various ambient ionisation techniques enable both in vivo tissue and ex vivo tissue samples to be analysed without necessitating the time and expense of adding a matrix or reagent to the tissue sample or other target material.

(32) A list of ambient ionisation techniques which are intended to fall within the scope of the present invention are given in the following table:

(33) TABLE-US-00001 Acronym Ionisation technique DESI Desorption electrospray ionization DeSSI Desorption sonic spray ionization DAPPI Desorption atmospheric pressure photoionization EASI Easy ambient sonic-spray ionization JeDI Jet desorption electrospray ionization TM-DESI Transmission mode desorption electrospray ionization LMJ-SSP Liquid microjunction-surface sampling probe DICE Desorption ionization by charge exchange Nano-DESI Nanospray desorption electrospray ionization EADESI Electrode-assisted desorption electrospray ionization APTDCI Atmospheric pressure thermal desorption chemical ionization V-EASI Venturi easy ambient sonic-spray ionization AFAI Air flow-assisted ionization LESA Liquid extraction surface analysis PTC-ESI Pipette tip column electrospray ionization AFADESI Air flow-assisted desorption electrospray ionization DEFFI Desorption electro-flow focusing ionization ESTASI Electrostatic spray ionization PASIT Plasma-based ambient sampling ionization transmission DAPCI Desorption atmospheric pressure chemical ionization DART Direct analysis in real time ASAP Atmospheric pressure solid analysis probe APTDI Atmospheric pressure thermal desorption ionization PADI Plasma assisted desorption ionization DBDI Dielectric barrier discharge ionization FAPA Flowing atmospheric pressure afterglow HAPGDI Helium atmospheric pressure glow discharge ionization APGDDI Atmospheric pressure glow discharge desorption ionization LTP Low temperature plasma LS-APGD Liquid sampling-atmospheric pressure glow discharge MIPDI Microwave induced plasma desorption ionization MFGDP Microfabricated glow discharge plasma RoPPI Robotic plasma probe ionization PLASI Plasma spray ionization MALDESI Matrix assisted laser desorption electrospray ionization ELDI Electrospray laser desorption ionization LDTD Laser diode thermal desorption LAESI Laser ablation electrospray ionization CALDI Charge assisted laser desorption ionization LA-FAPA Laser ablation flowing atmospheric pressure afterglow LADESI Laser assisted desorption electrospray ionization LDESI Laser desorption electrospray ionization LEMS Laser electrospray mass spectrometry LSI Laser spray ionization IR-LAMICI Infrared laser ablation metastable induced chemical ionization LDSPI Laser desorption spray post-ionization PAMLDI Plasma assisted multiwavelength laser desorption ionization HALDI High voltage-assisted laser desorption ionization PALDI Plasma assisted laser desorption ionization ESSI Extractive electrospray ionization PESI Probe electrospray ionization ND-ESSI Neutral desorption extractive electrospray ionization PS Paper spray DIP-APCI Direct inlet probe-atmospheric pressure chemical ionization TS Touch spray Wooden-tip Wooden-tip electrospray CBS-SPME Coated blade spray solid phase microextraction TSI Tissue spray ionization RADIO Radiofrequency acoustic desorption ionization LIAD-ESI Laser induced acoustic desorption electrospray ionization SAWN Surface acoustic wave nebulization UASI Ultrasonication-assisted spray ionization SPA-nanoESI Solid probe assisted nanoelectrospray ionization PAUSI Paper assisted ultrasonic spray ionization DPESI Direct probe electrospray ionization ESA-Py Electrospray assisted pyrolysis ionization APPIS Ambient pressure pyroelectric ion source RASTIR Remote analyte sampling transport and ionization relay SACI Surface activated chemical ionization DEMI Desorption electrospray metastable-induced ionization REIMS Rapid evaporative ionization mass spectrometry SPAM Single particle aerosol mass spectrometry TDAMS Thermal desorption-based ambient mass spectrometry MAII Matrix assisted inlet ionization SAII Solvent assisted inlet ionization SwiFERR Switched ferroelectric plasma ionizer LPTD Leidenfrost phenomenon assisted thermal desorption

(34) According to an embodiment the ambient ionisation ion source may comprise a rapid evaporative ionisation mass spectrometry (“REIMS”) ion source wherein a RF voltage is applied to one or more electrodes in order to generate an aerosol or plume of surgical smoke by Joule heating.

(35) However, it will be appreciated that other ambient ion sources including those referred to above may also be utilised. For example, according to another embodiment the ambient ionisation ion source may comprise a laser ionisation ion source. According to an embodiment the laser ionisation ion source may comprise a mid-IR laser ablation ion source. For example, there are several lasers which emit radiation close to or at 2.94 μm which corresponds with the peak in the water absorption spectrum. According to various embodiments the ambient ionisation ion source may comprise a laser ablation ion source having a wavelength close to 2.94 μm on the basis of the high absorption coefficient of water at 2.94 μm. According to an embodiment the laser ablation ion source may comprise a Er:YAG laser which emits radiation at 2.94 μm.

(36) Other embodiments are contemplated wherein a mid-infrared optical parametric oscillator (“OPO”) may be used to produce a laser ablation ion source having a longer wavelength than 2.94 μm. For example, an Er:YAG pumped ZGP-OPO may be used to produce laser radiation having a wavelength of e.g. 6.1 μm, 6.45 μm or 6.73 μm. In some situations it may be advantageous to use a laser ablation ion source having a shorter or longer wavelength than 2.94 μm since only the surface layers will be ablated and less thermal damage may result. According to an embodiment a Co:MgF.sub.2 laser may be used as a laser ablation ion source wherein the laser may be tuned from 1.75-2.5 μm. According to another embodiment an optical parametric oscillator (“OPO”) system pumped by a Nd:YAG laser may be used to produce a laser ablation ion source having a wavelength between 2.9-3.1 μm. According to another embodiment a CO.sub.2 laser having a wavelength of 10.6 μm may be used to generate the aerosol, smoke or vapour.

(37) According to other embodiments the ambient ionisation ion source may comprise an ultrasonic ablation ion source which generates a liquid sample which is then aspirated as an aerosol. The ultrasonic ablation ion source may comprise a focused or unfocussed source.

(38) According to an embodiment the first device for generating aerosol, smoke or vapour from one or more regions of a target may comprise an electrosurgical tool which utilises a continuous RF waveform. According to other embodiments a radiofrequency tissue dissection system may be used which is arranged to supply pulsed plasma RF energy to a tool. The tool may comprise, for example, a PlasmaBlade®. Pulsed plasma RF tools operate at lower temperatures than conventional electrosurgical tools (e.g. 40-170° C. c.f. 200-350° C.) thereby reducing thermal injury depth. Pulsed waveforms and duty cycles may be used for both cut and coagulation modes of operation by inducing electrical plasma along the cutting edge(s) of a thin insulated electrode.

(39) Rapid Evaporative Ionisation Mass Spectrometry (“REIMS”)

(40) FIG. 1 illustrates a method of rapid evaporative ionisation mass spectrometry (“REIMS”) wherein bipolar forceps 1 may be brought into contact with in vivo tissue 2 of a patient 3. In the example shown in FIG. 1, the bipolar forceps 1 may be brought into contact with brain tissue 2 of a patient 3 during the course of a surgical operation on the patient's brain. An RF voltage from an RF voltage generator 4 may be applied to the bipolar forceps 1 which causes localised Joule or diathermy heating of the tissue 2. As a result, an aerosol or surgical plume 5 is generated. The aerosol or surgical plume 5 may then be captured or otherwise aspirated through an irrigation port of the bipolar forceps 1. The irrigation port of the bipolar forceps 1 is therefore reutilised as an aspiration port. The aerosol or surgical plume 5 may then be passed from the irrigation (aspiration) port of the bipolar forceps 1 to tubing 6 (e.g. ⅛″ or 3.2 mm diameter Teflon® tubing). The tubing 6 is arranged to transfer the aerosol or surgical plume 5 to an atmospheric pressure interface 7 of a mass spectrometer 8 and/or ion mobility spectrometer.

(41) According to various embodiments a matrix comprising an organic solvent such as isopropanol may be added to the aerosol or surgical plume 5 at the atmospheric pressure interface 7. The mixture of aerosol 3 and organic solvent may then be arranged to impact upon a collision surface within a vacuum chamber of the mass spectrometer 8. According to one embodiment the collision surface may be heated. The aerosol is caused to ionise upon impacting the collision surface resulting in the generation of analyte ions. The ionisation efficiency of generating the analyte ions may be improved by the addition of the organic solvent. However, the addition of an organic solvent is not essential.

(42) Analyte ions which are generated by causing the aerosol, smoke or vapour 5 to impact upon the collision surface are then passed through subsequent stages of the mass spectrometer (and/or ion mobility spectrometer) and are subjected to mass analysis in a mass analyser (and/or ion mobility analysis). The mass analyser may, for example, comprise a quadrupole mass analyser or a Time of Flight mass analyser.

(43) Endoscope

(44) Gastro-intestinal (“GI”) cancers account for 23% of cancer-related deaths globally. Despite an increasing incidence, mortality from cancer has been decreasing over the last four decades. However, it is nonetheless estimated that a further 30-40% of these deaths can potentially be prevented. Accurate disease diagnosis and early treatment are key factors in improving cancer outcomes.

(45) Early stage cancers and pre-malignant conditions can be successfully treated using electrocautery-based endoscopic techniques while the gold standard method for diagnosis remains white light endoscopic investigation of the GI tract with tissue biopsy.

(46) It has been recently reported that GI cancer may be missed at endoscopy in up to 7.8% of patients who are subsequently diagnosed with cancer. A major advantage of current endoscopic procedures is that patients avoid the need for major surgery if their lesions are completely excised. However, re-intervention is necessary in up to 41% of patients due to incomplete excision.

(47) As will become further apparent, a particular advantage of a rapid evaporative ionisation mass spectrometry endoscope and snare arrangement according to various embodiments and which will be described in more detail below is that the rapid evaporative ionisation mass spectrometry endoscope and snare arrangement enables accurate real time mass spectral data to be obtained and utilised in order to reduce mis-diagnosis rates and to improve complete resection rates.

(48) Enhanced imaging techniques may also be used to improve diagnostic accuracy within the GI tract with particular emphasis upon spectroscopic characterization using elastic scattering spectroscopy, optical coherence tomography, multimodal imaging combining Raman spectroscopy, autofluorescence and narrow band imaging. However, none of these approaches are currently used in mainstream clinical practice.

(49) Mass spectrometry (“MS”) based identification of tissues is known using imaging techniques, sampling probe/electrospray systems and the direct ambient ionization mass spectrometry investigation of tissues.

(50) Rapid evaporative ionization mass spectrometry (“REIMS”) has emerged from this latter group as a key technology allowing in-situ real-time analysis by the utilization of electrosurgical tools as a mass spectrometry ion source.

(51) The rapid evaporative ionisation mass spectrometry fingerprint of human tissues shows high histological specificity with 90-100% concordance with standard histology.

(52) An embodiment relates to a real-time, robust endoscopic tissue characterisation tool which utilises rapid evaporative ionisation mass spectrometry technology.

(53) FIG. 2 shows a polypectomy snare 20 according to an embodiment. The snare comprises a wire loop 21 which runs through a length of tubing 22. The wire loop 21 is attached to a manipulator 23 which allows a user to close the snare around a polyp. The wire snare is connected to an RF voltage generator. The wire snare acts as an electrosurgical tool and may be used to resect polyps located e.g. in the stomach or colon. As the polypectomy snare is deployed and tightened around a polyp, the polyp effectively restricts or seals the end of the tubing which houses the wire snare.

(54) It will be appreciated that the wire loop 21 may take any suitable form. In particular, standard commercially available snare wires may be employed within the polypectomy snares described herein. For instance, the wire loop 21 may comprise a commercially available oval braided or convex compact wire snare. It has been found that oval braided wire snares may provide a slightly more robust signal transfer and/or higher signal intensity.

(55) When an RF voltage is applied to the wire snare, the wire snare acts as an electrosurgical tool and effectively cuts and removes the polyp. At the same time, surgical smoke or aerosol is generated which is substantially unable to pass into the end of the tubing which houses the wire snare. A particular aspect is that the tubing 22 which houses the wire snare is additionally provided with fenestrations or one or more aspiration ports 30 (as shown in FIG. 3B) which enables the surgical smoke or aerosol to be aspirated into the tubing 22 which houses the wire snare 21. The surgical smoke or aerosol is then aspirated along the length of the tubing 22 and via a connector (not shown in FIG. 2) and is passed to a vacuum chamber of a mass spectrometer 8 whereupon the surgical smoke or aerosol is ionised upon impacting a collision surface which may heated.

(56) The resulting analyte ions are then mass analysed and real time information relating to the tissue which is being resected may be provided to a user (who may comprise a surgeon or specialist nurse). In addition to cutting the polyp away from the lining of the stomach or colon, the snare 21 may also be used to hold on to the polyp so that the polyp can be removed from the stomach, optionally analysed and then disposed of.

(57) According to other embodiments the electrosurgical tool and optionally an associated endoscope (if provided) may be used in other body cavities and organs including the lung, nose and urethra. In particular, the endoscope may comprise a bronchoscope, a cystoscope, a rhinoscope or a nasoscope.

(58) According to an embodiment the snare 21 may comprise a monopolar device and a relatively large pad acting as a return electrode may be placed underneath the patient so that electrical current flows from the snare electrode 21, through the patient, to the return electrode. Other embodiments are also contemplated wherein the snare electrode 21 may comprise a bipolar device such that electrical current does not flow through the patient's body. A bipolar device may be used, for example, in very sensitive operations such as brain surgery wherein it is clearly undesirable for an electrical current to flow through surrounding tissue.

(59) According to an embodiment the snare 21 may comprise a monopolar device probe or needle probe and a relatively large pad acting as a return electrode may be placed underneath the patient so that electrical current flows from the probe electrode, through the patient, to the return electrode. Alternatively, the probe may comprise a bipolar device.

(60) Although a monopolar or a bipolar electrode arrangement is particularly advantageous, other embodiments are also contemplated wherein the electrosurgical tool may comprise a multi-phase or 3-phase device and may comprise, for example, three or more separate electrodes or probes.

(61) According to another embodiment a pulsed plasma RF tool such as a PlasmaBlade® tool may be used to generate the surgical smoke, aerosol or vapour.

(62) According to another embodiment an optical fibre coupled to a laser source may be used to generate the surgical smoke, aerosol or vapour.

(63) According to an embodiment surgical smoke or aerosol which is aspirated via the electrosurgical tool may be passed via a liquid separator or liquid trap in order to remove or reduce the amount of liquid which is onwardly transmitted to the mass spectrometer and/or ion mobility spectrometer.

(64) A matrix may added or mixed with the analyte, smoke, fumes, liquid, gas, surgical smoke, aerosol or vapour may prior to the analyte, smoke, fumes, liquid, gas, surgical smoke, aerosol or vapour impacting upon the collision surface.

(65) The matrix may comprise a solvent for the analyte, smoke, fumes, liquid, gas, surgical smoke, aerosol or vapour and may comprise an organic solvent and/or a volatile compound.

(66) According to an embodiment the matrix may comprise polar molecules, water, one or more alcohols, methanol, ethanol, isopropanol, acetone or acetonitrile. Isopropanol is particularly advantageous to use.

(67) The matrix which is added may additionally or alternatively comprise a lockmass or calibration compound.

(68) The addition of a matrix is particularly advantageous in that dissolving analyte in the matrix eliminates intermolecular bonding between the analyte molecules. As such, when the dissolved analyte is collided with the collision surface, the dissolved analyte will fragment into droplets and any given droplet is likely to contain fewer analyte molecules than it would if the matrix were not present. This in turn leads to a more efficient generation of ions when the matrix in each droplet is evaporated.

(69) FIG. 3A shows in more detail an embodiment and shows an endoscopic polypectomy snare which is equipped with an additional T-piece connector 32 in order to establish a direct transfer line 6 between the tissue evaporation point and the atmospheric inlet 7 of a mass spectrometer 8 and/or ion mobility spectrometer (in addition to the transfer line from the endoscope 38 to an endoscopic stack 39).

(70) The T-piece connector 32 may include a valve which only allows surgical smoke, aerosol or vapour to be transferred to the inlet 7 of the mass spectrometer 8 and/or ion mobility spectrometer when the snare (or other tool) is energised. If the snare (or other tool) is not being energised then the tube 6 in fluid communication with the snare (or other tool) may be diverted to atmosphere. The valve can thereby help to stop deflation of the bowel or gastrointestinal (“GI”) tract.

(71) According to an embodiment the endoscopic tool may be equipped with a fluid detection device 40 which may be arranged to detect fluid (e.g. mucus, bile or other bodily fluid) or saline solution travelling up the sampling tube 6. The fluid detection device 40 may be positioned at the T-piece connector 32 or at a different position along the sampling tube e.g. upstream of the T-piece connector 32 as shown in FIG. 3A.

(72) The fluid detection device 40 may effectively form a diverter which is arranged to divert fluid or liquid to waste or suction 42 via a tube 41 in the event that fluid is detected. As a result, fluid is prevented from reaching the inlet 7 of the mass spectrometer 8 and/or ion mobility spectrometer.

(73) The rapid evaporative ionisation mass spectrometry based endoscopic setup according to various embodiments addresses various potential problems if a conventional endoscope were attempted to be used.

(74) In particular, the various embodiments are designed to address the problem of there being a short signal capture window (typically 1-2 seconds) coupled with the problem of seeking to aspirate aerosol from a closed cavity.

(75) A yet further problem which the various embodiments seek to address is the problem of potential exogenous contamination from the GI tract and the need for a long sampling line 6 (>4 m) through the working channel of the endoscope 38.

(76) The rapid evaporative ionisation mass spectrometry endoscopic setup was initially optimized and its reproducibility was assessed using a porcine stomach model. Artificial polyps were created within porcine stomach mucosa and resections were undertaken using a polypectomy snare 21 as shown in FIG. 3B. This set-up allowed for an exact simulation of a standard endoscopic resection. Since the polyp 35 completely blocks the opening or tool deployment opening 37 of the plastic sheath 22 of the snare during resection (as can be seen from FIG. 3B), the aerosol 5 produced by the resection is aspirated through fenestrations 30 which are provided on the plastic sheath 22 of the snare 21.

(77) The provision of fenestrations 30 on the plastic sheath 22 of the rapid evaporative ionisation mass spectrometry snare 21 and which are distal from the tool deployment opening 37 of the snare are particularly advantageous since the fenestrations or aspiration ports 30 allow surgical smoke and/or aerosol to be aspirated when the tool deployment opening 37 is at least partially or totally blocked.

(78) The aerosol particles which enter the rapid evaporative ionisation mass spectrometry sheath 22 via the fenestrations or aspiration ports 30 may then be transferred to a mass spectrometer 8 via PFTE tubing 6 which may connected to a port of the snare. The snare 21 may be connected to or extend from the proximal end of an endoscope 38. The tubing 6 may be connected directly to an inlet capillary or ion sampling orifice 7 of the mass spectrometer 8. It will be understood that the mass spectrometer 8 is distal to the point of evaporation.

(79) Aspiration of the aerosols may be facilitated using a Venturi pump driven by standard medical air or nitrogen.

(80) The mass spectrometer may include a modified atmospheric interface which may include a collision surface which may positioned along and adjacent to the central axis of the large opening of a StepWave® ion guide. As will be understood by those skilled in the art, a StepWave® ion guide comprises two conjoined ion tunnel ion guides. Each ion guide comprises a plurality of ring or other electrodes wherein ions pass through the central aperture provided by the ring or other electrodes. Transient DC voltages or potentials are applied to the electrodes. The StepWave® ion guide is based on stacked ring ion guide technology and is designed to maximise ion transmission from the source to the mass analyser. The device allows for the active removal of neutral contaminants thereby providing an enhancement to overall signal to noise. The design enables the efficient capture of the diffuse ion cloud entering a first lower stage which is then may focused into an upper ion guide for transfer to the mass analyser.

(81) The collision surface located within a vacuum chamber of the mass spectrometer 8 may facilitate efficient fragmentation of molecular clusters formed in the free jet region of the atmospheric interface due to the adiabatic expansion of gas entering the vacuum chamber and the resulting drop of temperature. Other means for facilitating efficient fragmentation of molecular clusters may additionally or alternatively be provided within the vacuum chamber, for example, a collision gas may be provided in this region wherein collisions with the collision gas helps to break up the molecular clusters.

(82) The surface-induced dissociation of supramolecular clusters may improve the signal intensity and may also alleviate the problems associated with the contamination of ion optics.

(83) Rapid evaporative ionisation mass spectrometry spectra recorded from the porcine stomach model in the m/z range 600-1000 feature predominantly phospholipids which have been observed for all mammalian tissue types in previous rapid evaporative ionisation mass spectrometry experiments.

(84) Various experiments were performed in order to optimise the snare tip geometry and also to optimise the number and relative positions of the fenestrations 30 on the plastic sheath 22 of the snare. An assessment of the repeatability of the analysis was also performed.

(85) Following optimization of the sampling geometry, the rapid evaporative ionisation mass spectrometry endoscopic setup was tested on ex vivo human samples including gastric adenocarcinoma, healthy gastric mucosa and healthy gastric submucosa.

(86) The samples were acquired from three individual patients, all of whom provided written informed consent.

(87) Previous studies demonstrated marked differences in the rapid evaporative ionisation mass spectrometry fingerprint of healthy mucosa and cancers of the GI tract. However, for the first time healthy submucosa and GI polyps were investigated.

(88) Significant spectral differences were observed between healthy gastric mucosa, healthy gastric submucosa and gastric cancer tissue. Spectra of healthy gastric mucosa (n=32) and gastric adenocarcinoma (n=29) featured phospholipids in the range m/z 600-900 while the gastric submucosa (n=10) featured intensive triglyceride (“TG”) and phosphatidyl-inositol (“PI”) species in the m/z 900-1000 range as shown in FIG. 4A.

(89) The submucosa in the GI tract represents a connective tissue layer containing arterioles, venules and lymphatic vessels. It is made up of mostly collagenous and elastic fibers with varying amounts of adipose elements. It is hypothesised that the PI and triglycerides species observed in the m/z 900-1000 mass range are associated with these histological features present within the submucosa.

(90) An interesting feature was observed regarding the abundance of phosphatidyl-ethanolamines and corresponding plasmalogen species. While the PEs show higher abundance, the plasmalogens are depleted in the tumour tissue, probably due to the impaired peroxisomal function of the cancer cells.

(91) FIG. 4B shows a number of selected peaks which are significantly different between the healthy tissue layers and cancer tissue in the mass range 600-900. All peaks between m/z 900 to 1000 show significant differences when comparing the gastric submucosa to either adenocarcinoma or gastric mucosa.

(92) The clear differences observed between the rapid evaporative ionisation mass spectrometry fingerprints of the submucosa and mucosal layer may according to an embodiment be exploited as a potential safety function for interventional endoscopy.

(93) Colonoscopic procedures involving electrocautery are associated with a 9× increase in perforation risk compared to a purely diagnostic procedure. It has also been reported that endomucosal resection (“EMR”) of ulcerated lesions are at higher risk of perforation. According to an embodiment the rapid evaporative ionisation mass spectrometry endoscopic method may include an alert feature such that any diathermy device is immediately stopped if there is a breach of the submucosal layer during polypectomy or endomucosal resection.

(94) Real time and/or delayed information may be provided to a user of the electrosurgical tool that may comprise mass spectral information and/or tissue classification information. A feedback device and/or an alarm and/or an alert may also may be provided to provide a user of the electrosurgical tool with feedback and/or an alarm and/or an alert that analyte from an undesired target region or area is being analysed by the analyser or that the electrosurgical tool is operating in and/or is located in an undesired target region or area.

(95) Electrical power to the electrosurgical tool may be reduced and/or stopped in the event that analyte from an undesired target region or area is being analysed by the analyser and/or the electrosurgical tool is operating in and/or is located in an undesired target region or area.

(96) Development of the rapid evaporative ionisation mass spectrometry technology for this purpose advantageously helps in decreasing perforation rates and the significant morbidity associated with this complication.

(97) Analysis of ex vivo human colonic adenocarcinoma (n=43) and healthy colonic mucosa (n=45) acquired from seven patients was conducted using a LTQ Velos® mass spectrometer at the University of Debrecen, Hungary.

(98) Adenomatous polyps (n=5) from two patients were also sampled ex vivo and the resulting rapid evaporative ionisation mass spectrometry data was analysed using multivariate statistical tools as shown in FIGS. 5A and 5B. In agreement with previously published rapid evaporative ionisation mass spectrometry studies, the spectra acquired from healthy mucosa and adenocarcinoma of both the stomach and colon were discovered to separate well in 3-dimensional PCA space as can be seen from FIGS. 5A and 5B. The sampled adenomatous polyps also demonstrate good separation from both healthy mucosa and malignant tissue from the colon as shown in FIG. 5A.

(99) Following the proof of concept analysis of ex vivo samples, the rapid evaporative ionisation mass spectrometry endoscopic method was also tested in vivo on three consecutive patients referred for colonoscopy. FIG. 6A shows in vivo utilization of a rapid evaporative ionisation mass spectrometry compatible endoscope system according to an embodiment and sampling points taken from three patients undergoing colonoscopy and FIG. 6B shows the sampling points depicted on a 3-dimensional PCA plot wherein the spectra acquired in vivo when the polyps were removed localize in a different part of space whilst all other mucosal spectra are quasi uniformly independent from the sampling location.

(100) Different regions of the colon and rectum were sampled during the colonoscopy procedures. The first and third patients had evidence of colonic polyps and these were confirmed to be benign. The second patient had evidence of a normal colon with no visible polyps. The mucosal layer showed uniform spectral pattern independently from anatomical location. However, colonic polyps showed marked differences from the healthy mucosal layer as shown in FIG. 6B. This is in agreement with the findings of previous ex vivo studies.

(101) The data presented herewith demonstrates the significant advantages in using the rapid evaporative ionisation mass spectrometry technique as a real-time diagnostic tool in endoscopy in accordance with an embodiment.

(102) The rapid evaporative ionisation mass spectrometry compatible endoscope and snare has been tested in both ex vivo and in vivo settings without the need for major modification of standard approved clinical equipment. The method has been optimised to account for the short signal capture window that occurs with endoscopic resectional procedures and also to address technical challenges associated with long ion transfer distances and potential aspiration of gastric/intestinal content.

(103) The rapid evaporative ionisation mass spectrometry compatible endoscope 38 and snare 21 has successfully been shown to be capable of differentiating between healthy mucosa, adenomae and GI cancer based on their individual lipodomic spectral profiles. Furthermore, the significant differences demonstrated between healthy mucosal and submucosal layers of the GI tract indicate that rapid evaporative ionisation mass spectrometry can also be utilized to avoid the damaging of smooth muscle layer and consequent perforation in course of interventional endoscopy.

(104) Rapid evaporative ionisation mass spectrometry technology has also been demonstrated to be able to identify microorganisms. Accordingly the rapid evaporative ionisation mass spectrometry endoscope may be used to analyser in situ bacteria. This is of particular interest since the composition and metabolic activity of gut microbiota has been associated with the pathogenesis of cancer, diabetes, obesity, hypertension and autism.

(105) The rapid evaporative ionisation mass spectrometry endoscope 38 and snare 21 may be used as a general screening tool in order to help the assessment of the risk of developing a wide variety of diseases and also to enable preventive measures to be taken in a timely manner. The rapid evaporative ionisation mass spectrometry endoscope 38 and snare 21 may also be used, for example, for testing of faecal or mucal material.

(106) The techniques described above are presented in the context of an embodiment utilising rapid evaporative ionisation mass spectrometry. However, it will be appreciated that the techniques and apparatus described herein are not limited to rapid evaporative ionisation mass spectrometry devices and may also be extended to other ambient ion sources. For example, a tool having fenestrations or aspiration ports may be provided as part of a laser surgery probe for aspirating aerosol, smoke or vapour generated using the laser. Further details of known ambient ion sources that may be suitable for use with the techniques and apparatus described herein are presented below.

(107) The endoscopic tool may be used to help distinguish between healthy, potentially cancerous, cancerous, potentially diseased or diseased biological tissue or the margins or bounds of a tumour.

(108) The cancerous biological tissue or the tumour may comprise: (i) grade I, grade II, grade III or grade IV cancerous tissue; (ii) metastatic cancerous tissue; (iii) mixed grade cancerous tissue; or (iv) a sub-grade cancerous tissue.

(109) The endoscopic tool may also be used to identify whether or not a patient is suffering from irritable bowel syndrome (“IBS”), inflammatory bowel disease (“IBD”), Chron's disease or ulcerative colitis (“UC”).

Experimental

(110) For the experiments described above, a commercially available polypectomy snare (Olympus® Model No. SD-210U-15) having a working length of about 2300 mm, minimum channel size about 2.8 mm, opening diameter about 15 mm and wire thickness about 0.47 mm was equipped with an additional T-piece 32 in order to establish connection with a ⅛″ OD 2 mm ID PFTE tubing 6 between the tissue evaporation point and the atmospheric inlet 7 of a mass spectrometer 8 (Xevo G2-S® Q-TOF, Waters®, Manchester, UK, and a LTQ Velos® linear ion trap mass spectrometer, Thermo Fischer Scientific®, Bremen, Germany).

(111) The snare 21 was used with a commercially available endoscope 38 (Olympus®, Tokyo, Japan) and the associated endoscopic stack 39 was coupled with an electrosurgical generator (Valleylab Surgistat II®).

(112) The endoscopic plume 5 generated during the removal of polyps was captured through the fenestrations 30 on the rapid evaporative ionisation mass spectrometry snare 21. The endoscopic plume 5 was then transferred to the mass spectrometer 8 through the endoscope housing and via PFTE tubing 6 which was coupled directly to the inlet capillary 7 of a mass spectrometer 8 using the internal vacuum of the mass spectrometer for plume capturing.

(113) High resolution mass spectrometry was performed in negative ion mode between m/z 150-1500 range.

(114) Written, informed consent was obtained from all patients who provided tissue samples. Ethical approval was obtained from the Hungarian National Scientific Research Ethical Committee (Ref number 182/PI/10) and the National Research Ethics Service, UK (Ref number: 11/LO/0686).

(115) The data analysis workflow for the separation of healthy, cancerous and adenomatous polyps of the gastrointestinal tract included the construction of a tissue specific spectral database followed by multivariate classification and spectral identification algorithms in a known manner.

(116) The test studies described above using an Olympus disposable snare 21 on ex vivo oesophageal gastric and colorectal samples provided good quality signals with reasonable intensities; particularly for relatively large samples. The effect of the snare 21 and/or fenestration geometry was investigated to attempt to optimize the signal transfer. Three different configurations of fenestrations 30 (shown in FIG. 7) were tested in combination with two different types of commercially available snare wire 21 (oval braided and convex compact) to give a total of six different snare configurations.

(117) Systematic experiments were carried out for each of the six snare configurations on porcine muscle tissue and normal human colorectal mucosa tissue. To mimic the conditions of the endoscope environment a long funnel-tube was held over the tissue with the snare threaded through it as shown in FIG. 8. An isopropanol matrix was added to the aerosol/smoke at the mass spectrometer inlet 7. In order to optimize the signal, the experimental set-up was altered by not using a Venturi gas flow. This increased signal intensity but resulted in approximately a six second delay from snare use to spectral signal received due to the relatively slow transit of the aerosol/smoke through the tubing 6. High-resolution mass spectrometry was performed in negative-ion mode in the m/z 150-1500 range.

(118) With the isopropanol matrix and no Venturi gas flow, phospholipid peaks of sufficiently high intensity (of the order of 10.sup.3) were seen for each of the snare configurations tested. There was no apparent difference in the spectra obtained with any of the different hole configurations shown in FIG. 7, with robust signals being obtained for all three hole configurations, and this was confirmed by linear discriminant analysis (see the plot in FIG. 9). The different wire snare types also produced very similar results but a slightly higher signal intensity was obtained for the phospholipid peaks of interest in the 600-1000 m/z region using the oval braided wire snare compared to the convex compact wire snare (see the linear discriminant analysis plot in FIG. 10).

(119) Analysing Sample Spectra

(120) A list of analysis techniques which are intended to fall within the scope of the present invention are given in the following table:

(121) TABLE-US-00002 Analysis Techniques Univariate Analysis Multivariate Analysis Principal Component Analysis (PCA) Linear Discriminant Analysis (LDA) Maximum Margin Criteria (MMC) Library Based Analysis Soft Independent Modelling Of Class Analogy (SIMCA) Factor Analysis (FA) Recursive Partitioning (Decision Trees) Random Forests Independent Component Analysis (ICA) Partial Least Squares Discriminant Analysis (PLS-DA) Orthogonal (Partial Least Squares) Projections To Latent Structures (OPLS) OPLS Discriminant Analysis (OPLS-DA) Support Vector Machines (SVM) (Artificial) Neural Networks Multilayer Perceptron Radial Basis Function (RBF) Networks Bayesian Analysis Cluster Analysis Kernelized Methods Subspace Discriminant Analysis K-Nearest Neighbours (KNN) Quadratic Discriminant Analysis (QDA) Probabilistic Principal Component Analysis (PPCA) Non negative matrix factorisation K-means factorisation Fuzzy c-means factorisation Discriminant Analysis (DA)

(122) Combinations of the foregoing analysis approaches can also be used, such as PCA-LDA, PCA-MMC, PLS-LDA, etc.

(123) Analysing the sample spectra can comprise unsupervised analysis for dimensionality reduction followed by supervised analysis for classification.

(124) By way of example, a number of different analysis techniques will now be described in more detail.

(125) Multivariate Analysis—Developing a Model for Classification

(126) By way of example, a method of building a classification model using multivariate analysis of plural reference sample spectra will now be described.

(127) FIG. 11 shows a method 1500 of building a classification model using multivariate analysis. In this example, the method comprises a step 1502 of obtaining plural sets of intensity values for reference sample spectra. The method then comprises a step 1504 of unsupervised principal component analysis (PCA) followed by a step 1506 of supervised linear discriminant analysis (LDA). This approach may be referred to herein as PCA-LDA. Other multivariate analysis approaches may be used, such as PCA-MMC. The PCA-LDA model is then output, for example to storage, in step 1508.

(128) The multivariate analysis such as this can provide a classification model that allows an aerosol, smoke or vapour sample to be classified using one or more sample spectra obtained from the aerosol, smoke or vapour sample. The multivariate analysis will now be described in more detail with reference to a simple example.

(129) FIG. 12 shows a set of reference sample spectra obtained from two classes of known reference samples. The classes may be any one or more of the classes of target described herein. However, for simplicity, in this example the two classes will be referred as a left-hand class and a right-hand class.

(130) Each of the reference sample spectra has been pre-processed in order to derive a set of three reference peak-intensity values for respective mass to charge ratios in that reference sample spectrum. Although only three reference peak-intensity values are shown, it will be appreciated that many more reference peak-intensity values (e.g., ˜100 reference peak-intensity values) may be derived for a corresponding number of mass to charge ratios in each of the reference sample spectra. In other embodiments, the reference peak-intensity values may correspond to: masses; mass to charge ratios; ion mobilities (drift times); and/or operational parameters.

(131) FIG. 13 shows a multivariate space having three dimensions defined by intensity axes. Each of the dimensions or intensity axes corresponds to the peak-intensity at a particular mass to charge ratio. Again, it will be appreciated that there may be many more dimensions or intensity axes (e.g., ˜100 dimensions or intensity axes) in the multivariate space. The multivariate space comprises plural reference points, with each reference point corresponding to a reference sample spectrum, i.e., the peak-intensity values of each reference sample spectrum provide the co-ordinates for the reference points in the multivariate space.

(132) The set of reference sample spectra may be represented by a reference matrix D having rows associated with respective reference sample spectra, columns associated with respective mass to charge ratios, and the elements of the matrix being the peak-intensity values for the respective mass to charge ratios of the respective reference sample spectra.

(133) In many cases, the large number of dimensions in the multivariate space and matrix D can make it difficult to group the reference sample spectra into classes. PCA may accordingly be carried out on the matrix D in order to calculate a PCA model that defines a PCA space having a reduced number of one or more dimensions defined by principal component axes. The principal components may be selected to be those that comprise or “explain” the largest variance in the matrix D and that cumulatively explain a threshold amount of the variance in the matrix D.

(134) FIG. 14 shows how the cumulative variance may increase as a function of the number n of principal components in the PCA model. The threshold amount of the variance may be selected as desired.

(135) The PCA model may be calculated from the matrix D using a non-linear iterative partial least squares (NIPALS) algorithm or singular value decomposition, the details of which are known to the skilled person and so will not be described herein in detail. Other methods of calculating the PCA model may be used.

(136) The resultant PCA model may be defined by a PCA scores matrix S and a PCA loadings matrix L. The PCA may also produce an error matrix E, which contains the variance not explained by the PCA model. The relationship between D, S, L and E may be:
D=SL.sup.T+E  (1)

(137) FIG. 15 shows the resultant PCA space for the reference sample spectra of FIGS. 12 and 13. In this example, the PCA model has two principal components PC.sub.0 and PC.sub.1 and the PCA space therefore has two dimensions defined by two principal component axes. However, a lesser or greater number of principal components may be included in the PCA model as desired. It is generally desired that the number of principal components is at least one less than the number of dimensions in the multivariate space.

(138) The PCA space comprises plural transformed reference points or PCA scores, with each transformed reference point or PCA score corresponding to a reference sample spectrum of FIG. 12 and therefore to a reference point of FIG. 13.

(139) As is shown in FIG. 15, the reduced dimensionality of the PCA space makes it easier to group the reference sample spectra into the two classes. Any outliers may also be identified and removed from the classification model at this stage.

(140) Further supervised multivariate analysis, such as multi-class LDA or maximum margin criteria (MMC), in the PCA space may then be performed so as to define classes and, optionally, further reduce the dimensionality.

(141) As will be appreciated by the skilled person, multi-class LDA seeks to maximise the ratio of the variance between classes to the variance within classes (i.e., so as to give the largest possible distance between the most compact classes possible). The details of LDA are known to the skilled person and so will not be described herein in detail.

(142) The resultant PCA-LDA model may be defined by a transformation matrix U, which may be derived from the PCA scores matrix S and class assignments for each of the transformed spectra contained therein by solving a generalised eigenvalue problem.

(143) The transformation of the scores S from the original PCA space into the new LDA space may then be given by:
Z=SU  (2)
wherein the matrix Z contains the scores transformed into the LDA space.

(144) FIG. 16 shows a PCA-LDA space having a single dimension or axis, wherein the LDA is performed in the PCA space of FIG. 15. As is shown in FIG. 16, the LDA space comprises plural further transformed reference points or PCA-LDA scores, with each further transformed reference point corresponding to a transformed reference point or PCA score of FIG. 15.

(145) In this example, the further reduced dimensionality of the PCA-LDA space makes it even easier to group the reference sample spectra into the two classes. Each class in the PCA-LDA model may be defined by its transformed class average and covariance matrix or one or more hyperplanes (including points, lines, planes or higher order hyperplanes) or hypersurfaces or Voronoi cells in the PCA-LDA space.

(146) The PCA loadings matrix L, the LDA matrix U and transformed class averages and covariance matrices or hyperplanes or hypersurfaces or Voronoi cells may be output to a database for later use in classifying an aerosol, smoke or vapour sample.

(147) The transformed covariance matrix in the LDA space V′.sub.g for class g may be given by:
V′.sub.g=U.sup.TV.sub.gU  (3)
wherein V.sub.g are the class covariance matrices in the PCA space.

(148) The transformed class average position z.sub.g for class g may be given by:
s.sub.gU=z.sub.g  (4)
wherein s.sub.g is the class average position in the PCA space.
Multivariate Analysis—Using a Model for Classification

(149) By way of example, a method of using a classification model to classify an aerosol, smoke or vapour sample will now be described.

(150) FIG. 17 shows a method 2100 of using a classification model. In this example, the method comprises a step 2102 of obtaining a set of intensity values for a sample spectrum. The method then comprises a step 2104 of projecting the set of intensity values for the sample spectrum into PCA-LDA model space. Other classification model spaces may be used, such as PCA-MMC. The sample spectrum is then classified at step 2106 based on the project position and the classification is then output in step 2108.

(151) Classification of an aerosol, smoke or vapour sample will now be described in more detail with reference to the simple PCA-LDA model described above.

(152) FIG. 18 shows a sample spectrum obtained from an unknown aerosol, smoke or vapour sample. The sample spectrum has been pre-processed in order to derive a set of three sample peak-intensity values for respective mass to charge ratios. As mentioned above, although only three sample peak-intensity values are shown, it will be appreciated that many more sample peak-intensity values (e.g., ˜100 sample peak-intensity values) may be derived at many more corresponding mass to charge ratios for the sample spectrum. Also, as mentioned above, in other embodiments, the sample peak-intensity values may correspond to: masses; mass to charge ratios; ion mobilities (drift times); and/or operational parameters.

(153) The sample spectrum may be represented by a sample vector d.sub.x, with the elements of the vector being the peak-intensity values for the respective mass to charge ratios. A transformed PCA vector s.sub.x for the sample spectrum can be obtained as follows:
d.sub.xL=s.sub.x  (5)

(154) Then, a transformed PCA-LDA vector z.sub.x for the sample spectrum can be obtained as follows:
s.sub.xU=z.sub.x  (6)

(155) FIG. 19 again shows the PCA-LDA space of FIG. 16. However, the PCA-LDA space of FIG. 19 further comprises the projected sample point, corresponding to the transformed PCA-LDA vector z.sub.x, derived from the peak intensity values of the sample spectrum of FIG. 18.

(156) In this example, the projected sample point is to one side of a hyperplane between the classes that relates to the right-hand class, and so the aerosol, smoke or vapour sample may be classified as belonging to the right-hand class.

(157) Alternatively, the Mahalanobis distance from the class centres in the LDA space may be used, where the Mahalanobis distance of the point z.sub.x from the centre of class g may be given by the square root of:
(z.sub.x−z.sub.g).sup.T(V′.sub.g).sup.−1(z.sub.x−z.sub.g)  (7)
and the data vector d.sub.x may be assigned to the class for which this distance is smallest.

(158) In addition, treating each class as a multivariate Gaussian, a probability of membership of the data vector to each class may be calculated.

(159) Library Based Analysis—Developing a Library for Classification

(160) By way of example, a method of building a classification library using plural input reference sample spectra will now be described.

(161) FIG. 20 shows a method 2400 of building a classification library. In this example, the method comprises a step 2402 of obtaining plural input reference sample spectra and a step 2404 of deriving metadata from the plural input reference sample spectra for each class of sample. The method then comprises a step 2406 of storing the metadata for each class of sample as a separate library entry. The classification library is then output, for example to electronic storage, in step 2408.

(162) A classification library such as this allows an aerosol, smoke or vapour sample to be classified using one or more sample spectra obtained from the aerosol, smoke or vapour sample. The library based analysis will now be described in more detail with reference to an example.

(163) In this example, each entry in the classification library is created from plural pre-processed reference sample spectra that are representative of a class. In this example, the reference sample spectra for a class are pre-processed according to the following procedure:

(164) First, a re-binning process is performed. In this embodiment, the data are resampled onto a logarithmic grid with abscissae:

(165) $\begin{array}{cc}{x}_i=.Math.N_{\mathrm{chan}}\log \frac{m}{M_{\min }}/\log \frac{M_{\max }}{M_{\min }}.Math.& \left(8\right)\end{array}$
wherein N.sub.chan is a selected value and └x┘ denotes the nearest integer below x. In one example, N.sub.chan is 2.sup.12 or 4096.

(166) Then, a background subtraction process is performed. In this embodiment, a cubic spline with k knots is then constructed such that p % of the data between each pair of knots lies below the curve. This curve is then subtracted from the data. In one example, k is 32. In one example, p is 5. A constant value corresponding to the q % quantile of the intensity subtracted data is then subtracted from each intensity. Positive and negative values are retained. In one example, q is 45.

(167) Then, a normalisation process is performed. In this embodiment, the data are normalised to have mean y.sub.i. In one example, y.sub.i=1.

(168) An entry in the library then consists of metadata in the form of a median spectrum value μ.sub.i and a deviation value D.sub.i for each of the N.sub.chan points in the spectrum.

(169) The likelihood for the i'th channel is given by:

(170) $\begin{array}{cc}\mathrm{Pr}\left(y_i.Math.{\mu }_i,D_i\right)=\frac{1}{D_i}\frac{C^{C-1/2}\Gamma \left(C\right)}{\sqrt{\pi }\Gamma \left(C-1/2\right)}\frac{1}{{\left(C+\frac{{\left(y_i-{\mu }_i\right)}^2}{D_i^2}\right)}^C}& \left(9\right)\end{array}$
where ½≤C<∞ and where Γ(C) is the gamma function.

(171) The above equation is a generalised Cauchy distribution which reduces to a standard Cauchy distribution for C=1 and becomes a Gaussian (normal) distribution as C.fwdarw.∞. The parameter D.sub.i controls the width of the distribution (in the Gaussian limit D.sub.i=σ.sub.i is simply the standard deviation) while the global value C controls the size of the tails.

(172) In one example, C is 3/2, which lies between Cauchy and Gaussian, so that the likelihood becomes:

(173) $\begin{array}{cc}\mathrm{Pr}\left(y_i.Math.{\mu }_i,D_i\right)=\frac{3}{4}\frac{1}{D_i}\frac{1}{{\left(3/2+{\left(y_i-{\mu }_i\right)}^2/D_i^2\right)}^{3/2}}& \left(10\right)\end{array}$

(174) For each library entry, the parameters μ.sub.i are set to the median of the list of values in the i'th channel of the input reference sample spectra while the deviation D.sub.i is taken to be the interquartile range of these values divided by √2. This choice can ensure that the likelihood for the i'th channel has the same interquartile range as the input data, with the use of quantiles providing some protection against outlying data.

(175) Library Based Analysis—Using a Library for Classification

(176) By way of example, a method of using a classification library to classify an aerosol, smoke or vapour sample will now be described.

(177) FIG. 21 shows a method 2500 of using a classification library. In this example, the method comprises a step 2502 of obtaining a set of plural sample spectra. The method then comprises a step 2504 of calculating a probability or classification score for the set of plural sample spectra for each class of sample using metadata for the class entry in the classification library. The sample spectra are then classified at step 2506 and the classification is then output in step 2508.

(178) Classification of an aerosol, smoke or vapour sample will now be described in more detail with reference to the classification library described above.

(179) In this example, an unknown sample spectrum y is the median spectrum of a set of plural sample spectra. Taking the median spectrum y can protect against outlying data on a channel by channel basis.

(180) The likelihood L.sub.s for the input data given the library entry s is then given by:
L.sub.s=Pr(y|μ,D)=Π.sub.i=1.sup.N.sup.chanPr(y.sub.i|μ.sub.i,D.sub.i)  (11)
wherein μ.sub.i and D.sub.i are, respectively, the library median values and deviation values for channel i. The likelihoods L.sub.s may be calculated as log likelihoods for numerical safety.

(181) The likelihoods L.sub.s are then normalised over all candidate classes ‘s’ to give probabilities, assuming a uniform prior probability over the classes. The resulting probability for the class {tilde over (s)} is given by:

(182) $\begin{array}{cc}\mathrm{Pr}\left(\tilde{s}.Math.y\right)=\frac{L_{\tilde{s}}^{\left(1/F\right)}}{{.Math.}_s{L}_s^{\left(1/F\right)}}& \left(12\right)\end{array}$

(183) The exponent (1/F) can soften the probabilities which may otherwise be too definitive. In one example, F=100. These probabilities may be expressed as percentages, e.g., in a user interface.

(184) Alternatively, RMS classification scores R.sub.s may be calculated using the same median sample values and derivation values from the library:

(185) $\begin{array}{cc}{R}_s\left(y,\mu ,D\right)=\sqrt{\frac{1}{N_{\mathrm{chan}}}\underset{i=1}{\overset{N_{\mathrm{chan}}}{.Math.}}\frac{{\left(y_i-{\mu }_i\right)}^2}{D_i^2}}& \left(13\right)\end{array}$

(186) Again, the scores R.sub.s are normalised over all candidate classes ‘s’.

(187) The aerosol, smoke or vapour sample may then be classified as belonging to the class having the highest probability and/or highest RMS classification score.

(188) Non-Surgical Applications

(189) It has also been recognised that a tool comprising a relatively extended and miniaturised probe comprising an ambient ion source for generating aerosol, smoke or vapour from a sample, i.e. similarly to the endoscope described above, may find application outside of the surgical or medical environments.

(190) For instance, such a tool may be used for minimally invasive analysis of fully packed containers e.g. at customs or airport security. The tool may be inserted into a relatively small hole formed in the container, with the ambient ion source then deployed through the tool deployment opening and activated to generate gaseous, smoke or vapour analyte material from within the container, with the gaseous, smoke or vapour material then being aspirated through fenestrations in the tool tubing and transported to an analyser for mass spectrometric analysis. It will be apparent that the endoscope arrangement may be used to detect narcotics or other illegal substances hidden in concealed places.

(191) Similarly, such a tool may find applications for analysis of closed pipe heating or cooling systems. It is known that organic growth such as fungi, bacteria, biofilms and/or algae may clog the heating or cooling pipes, but it is generally difficult to identify the organic material within such systems and hence difficult to ascertain how to treat it. This can be a particular problem in the cooling systems of a nuclear reactor, where disassembly of the cooling system for cleaning is prohibitively time consuming and expensive. By passing the tool through the pipework and deploying the ambient ion source into contact with the obstruction to generate gaseous, smoke or vapour analyte material which can then be aspirated into the tool housing and transported to a mass spectrometer for analysis, it may be possible to identify the nature of the organic growth and hence help determine how best to remove it.

(192) In the same manner, such a tool may find application in the fields of pest/parasite control, or structural testing/surveying. For instance, current methods for analysing fungal growth in the foundations or walls of a house tend to rely on optical imaging methods which can be inconclusive. By probing the growth and then mass analysing the generated gaseous, smoke or vapour analyte material it is possible to more accurately determine the nature of the fungal growth.

(193) The endoscopic tool arrangement may, for example, also be used to probe for asbestos or other potentially hazardous materials in buildings.

(194) Methods of Medical Treatment, Surgery and Diagnosis and Non-Medical Methods

(195) Various different embodiments are contemplated. According to some embodiments the methods disclosed above may be performed on in vivo, ex vivo or in vitro tissue. The tissue may comprise human or non-human animal tissue. Embodiments are contemplated wherein the target may comprise biological tissue, a bacterial or fungal colony or more generally an organic target such as a plastic).

(196) Various embodiments are contemplated wherein analyte ions generated by an ambient ionisation ion source are then subjected either to: (i) mass analysis by a mass analyser such as a quadrupole mass analyser or a Time of Flight mass analyser; (ii) ion mobility analysis (IMS) and/or differential ion mobility analysis (DMA) and/or Field Asymmetric Ion Mobility Spectrometry (FAIMS) analysis; and/or (iii) a combination of firstly (or vice versa) ion mobility analysis (IMS) and/or differential ion mobility analysis (DMA) and/or Field Asymmetric Ion Mobility Spectrometry (FAIMS) analysis followed by secondly (or vice versa) mass analysis by a mass analyser such as a quadrupole mass analyser or a Time of Flight mass analyser. Various embodiments also relate to an ion mobility spectrometer and/or mass analyser and a method of ion mobility spectrometry and/or method of mass analysis. Ion mobility analysis may be performed prior to mass to charge ratio analysis or vice versa.

(197) Various references are made in the present application to mass analysis, mass analysers, mass analysing, mass spectrometric data, mass spectrometers and other related terms referring to apparatus and methods for determining the mass or mass to charge of analyte ions. It should be understood that it is equally contemplated that the present invention may extend to ion mobility analysis, ion mobility analysers, ion mobility analysing, ion mobility data, ion mobility spectrometers, ion mobility separators and other related terms referring to apparatus and methods for determining the ion mobility, differential ion mobility, collision cross section or interaction cross section of analyte ions. Furthermore, it should also be understood that embodiments are contemplated wherein analyte ions may be subjected to a combination of both ion mobility analysis and mass analysis i.e. that both (a) the ion mobility, differential ion mobility, collision cross section or interaction cross section of analyte ions together with (b) the mass to charge of analyte ions is determined. Accordingly, hybrid ion mobility-mass spectrometry (IMS-MS) and mass spectrometry-ion mobility (MS-IMS) embodiments are contemplated wherein both the ion mobility and mass to charge ratio of analyte ions generated e.g. by an ambient ionisation ion source are determined. Ion mobility analysis may be performed prior to mass to charge ratio analysis or vice versa. Furthermore, it should be understood that embodiments are contemplated wherein references to mass spectrometric data and databases comprising mass spectrometric data should also be understood as encompassing ion mobility data and differential ion mobility data etc. and databases comprising ion mobility data and differential ion mobility data etc. (either in isolation or in combination with mass spectrometric data).

(198) Various surgical, therapeutic, medical treatment and diagnostic methods are contemplated.

(199) However, other embodiments are contemplated which relate to non-surgical and non-therapeutic methods of mass spectrometry which are not performed on in vivo tissue. Other related embodiments are contemplated which are performed in an extracorporeal manner such that they are performed outside of the human or animal body.

(200) Further embodiments are contemplated wherein the methods are performed on a non-living human or animal, for example, as part of an autopsy procedure.

(201) Although the present invention has been described with reference to preferred embodiments, it will be understood by those skilled in the art that various changes in form and detail may be made without departing from the scope of the invention as set forth in the accompanying claims.