INFECTION RESISTANT CATHETER SYSTEM

Abstract

This invention is for a catheter apparatus that greatly reduces microbial infections resulting from catheterization of dialysis, semi-mobile, or hospitalized patients. The apparatus applies light in the ultraviolet and near ultraviolet band to multiple catheter lumens for both detection and inactivation of biofilm microorganisms. It uses real-time automated techniques for the selection of wavelength, power level and exposure time regimes that are used for irradiating the biofilm in vivo. Artificial intelligence is incorporated to adjust the UV irradiation regimes to maximize the microorganism inactivation efficacy while minimizing the destruction of keratinocytes. The biofilm inactivation efficacy of this infection resistant catheter apparatus is at least 99%. The apparatus allows for minimal deviation from conventional catheter insertion procedures and can remain in vivo for long periods of time without the risk of microorganism contamination.

Claims

1. An apparatus comprising: An infection resistant catheter system that provides UVA and UVB wavelength light to fluoresce biofilm bacteria on the exterior and interior walls of an in-vivo catheter to produce a spectral pattern of the biofilm bacteria and UVC wavelength light irradiation to inactivate the biofilm bacteria while minimizing keratinocyte destruction. Further, two concentric liquid jackets deliver the UVC irradiation and fluoresced UVA and UVB light to all internal, external walls and hub elements of the catheter. Further, a Deep Learning Neural Network and associated bacteria spectral pattern training data automatically manage the biofilm spectral pattern detection, wavelength selection, power level and irradiation source protocol. The apparatus components include: a plurality of lumens flexible tube structure surrounded by two liquid filled concentric jackets; a UVA, UVB, and UVC band optical transmit liquid coupler; a UVA, UVB, and UVC band optical receive liquid coupler; a fiber optic transmit cable; a fiber optic receive cable; a plurality of UVA, UVB, and UVC band light sources; a plurality of UVA, UVB, and UVC band optical filters; a plurality of UVA, UVB, and UVC band photo sensors; a high speed graphic processing unit a eight layer Deep Learning Neural Network with a plurality of input and output nodes; a Deep Learning Neural Network training data set for 63 fluoresced bacteria spectral patterns; a bacteria inactivation irradiation protocol algorithm; a bacteria type and state detection Deep Learning Neural Network directed protocol algorithm; a irradiation protocol control algorithm; a battery power source; a rechargeable power source unit; a set of multi-lumen hubs and a injectate or drain port distal tip.

2. The apparatus of claim 1 wherein a plurality of fluid carrying lumens are used as a dialysis central venous catheter (CVC).

3. The apparatus of claim 1 wherein a single fluid carrying lumen is used as an intravascular catheter (IVC).

4. The apparatus of claim 1 wherein a single fluid carrying lumen is used as a urinary catheter (UC).

5. The apparatus of claim 1 wherein a plurality of fluid and gas carrying lumens are used as an inflatable tip urinary catheter (ITUC).

6. The apparatus of claim 1 wherein a plurality of fluid and gas carrying lumens are used as a pulmonary indwelling catheter (PIDC).

7. The apparatus of claim 1 wherein a Deep Learning Neural Network directed irradiation wavelength is automatically adjusted to suppress microorganism adaptation to the UVC inactivation light.

8. The apparatus of claim 1 wherein a Deep Learning Neural Network directed detection algorithm is used to signal the presence of fluoresced microorganisms on any of the catheter walls.

9. The apparatus of claim 1 wherein a plurality of fluid carrying lumens are used as an indwelling fluid delivery or drain catheter (IDC).

10. (canceled)

11. The apparatus of claim 1 wherein two liquid jackets are used to carry UVA, UVB and UVC band light to all lumens and associated hubs.

12. The apparatus of claim 1 wherein a liquid jacket is used to carry UVA and UVB band light from fluoresced microorganisms from all associated catheter internal and exterior walls.

13. The apparatus of claim 1 wherein the irradiation ON TIME is automatically adjusted by a Deep Learning Neural Network to minimize keratinocyte destruction while insuring up to 99.9% inactivation of the catheter internal and exterior walls biofilm microorganisms.

14. The apparatus of claim 1 wherein the irradiation POWER LEVEL is automatically adjusted by a Deep Learning Neural Network to minimize keratinocyte destruction while insuring up to 99.9% inactivation of the catheter internal and exterior walls biofilm microorganisms.

15. The apparatus of claim 1 wherein the irradiation WAVELENGTH is automatically adjusted by a Deep Learning Neural Network to prevent viability adaptation of the target bacteria or virus on the catheter internal and exterior walls biofilm microorganisms.

16. The apparatus of claim 1 wherein the irradiation regime (i.e. wavelength, ON TIME, POWER LEVEL, detection protocol, and pulse rate) is controlled by a Deep Learning Neural Network executed on an embedded graphic processor in the catheter control unit.

17. The apparatus of claim 1 wherein Deep Learning Neural Net algorithms are executed on the embedded graphic processor.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The invention is illustrated by way of example and not by way of limitation in the figures of the accompanying drawings in which like references indicate similar elements. It should be noted that references to an or one embodiment in this disclosure are not necessarily to the same embodiment, and such references mean at least one.

[0030] FIG. 1 illustrates the pathways that are subject to microorganism contamination that can lead to infection.

[0031] FIG. 2 illustrates one embodiment of the invention having all the elements of the lumen structure associated with a single injectate infection resistant catheter.

[0032] FIG. 3 illustrates one embodiment of the invention having all the elements of the multiple lumen structure associated with a multi injectate or injectate/drain infection resistant catheter.

[0033] FIG. 4 illustrates the fluid filled jacket used to irradiate or receive light to and from the full length of the surface of the infection resistant catheter.

[0034] FIG. 5 illustrates a block diagram of the infection resistant catheter light source and control unit.

[0035] FIG. 6 illustrates the Deep Learning Neural Net employed by the AI algorithms associated with this invention.

[0036] FIG. 7 illustrates one embodiment of this invention having all the elements of the multi-lumen infection resistant catheter and its associated AI control unit.

DETAILED DESCRIPTION AND CLAIMS

[0037] There are four distinct pathways that lead to catheter-related infection (FIG. 1.0). [0038] 1. First, colonization of the outer surface may start by the migration of skin resident microorganisms from the insertion site, and microbial cells may progressively move through the transcutaneous part of the dermal tunnel surrounding the catheter 103. [0039] 2. Second, colonization of the internal surface may occur by colonization of the hub and intraluminal surface of the catheter during utilization, and frequent opening of the hub is now viewed as an important source of microbial colonization 101. [0040] 3. Hematogenous seeding of the catheter during bloodstream infection of any origin represents a third pathway 104, and [0041] 4. Fourth, contamination of the fluids or drugs intravenously administered is sometimes responsible for outbreaks 102.

[0042] The apparatus described in this enclosure is resistant to all four contamination sources. It uses UVC light to damage the genetic material in the nucleus of the microorganism cell.sup.(1). UVC light in the range of 180 to 270 nm is strongly absorbed by the nucleic acids of an organism. The light induced damage to the DNA and RNA of an organism often results from the dimerization of pyrimidine molecules. In particular, thymine (which is only found in DNA) produces cyclobutane pyrimidine dimers. When these molecules are dimerized, it becomes very difficult for the nucleic acids to replicate and if replication does occur it often produces a defect which prevents the microorganisms from being viable.

[0043] Previous studies have shown that 254 nm is near optimum for germicidal effects on microorganisms. In 1878, Arthur Downes and Thomas P. Blunt published a paper describing the sterilization of bacteria exposed to ultraviolet UV light.sup.[2] in the 250 nm to 280 nm range. At these wavelengths, UV light is mutagenic to bacteria, viruses and other microorganisms. This process is similar to the effect of UV wavelengths that produce sunburns in humans. Microorganisms have less protection from UV light and cannot survive prolonged exposure to it.

[0044] The embodiment of this disclosure is the multi-lumen mechanical structure, the fiber optics AI based UV light irradiation delivery and detection system, and the control algorithms that maximize the infection resistance of the catheter while minimizing the UV destruction of keratinocytes by exploiting the mutagenic behavior of UV light on microorganisms.

[0045] With reference to FIG. 2, a single fluid flow example of the disclosed apparatus operates as follows: There are three catheter lumens in this example, a UV light transmitter jacket 207, a UV light receiver jacket 209, and a fluid transfer lumen 203. The UV light transmit lumen 207 irradiates the entire length of the catheter with 240 to 280 nm light to inactivate microorganisms at the intraluminal surface 209, hub, hematogenous distant tip and in the fluid 208 flowing through the catheter. Alternately, this same UV light transmit lumen 209 irradiates the entire length of the apparatus with wavelengths in the UVC band for the purpose of fluorescing microorganisms that may be present at any of the catheter sites subject to infection. The light from the fluoresced microorganisms is detected by sensors linked to the received light catheter lumen 209. This alternating process continues until no fluoresced microorganisms are detected. The alternating detection and irradiation cycle is controlled by AI algorithms running on a processor located in an external control unit attached to the catheter by fiber optic links 201, 202. The specific wavelength, power level, and on-time cycle are also controlled by AI algorithms running on the external control unit. The continuous changing of irradiation wavelength controlled by the AI algorithms, suppresses the ability for adaptation to inactivation by the microorganisms. The light sent and received by the transmit and receive lumens is coupled to the sources and sensors using optical couplers 205, 206 placed at the catheter entry sites. When the presence of microorganisms is not detected, the irradiation algorithm applies maintenance doses only of UV which also inactivate microorganisms that do not fluoresce but are still harmful to the patient. This single fluid flow example of the disclosed apparatus forms the baseline operational structure for other examples of the infection resistant catheter apparatus.

[0046] With reference to FIG. 3, a multi-flow multi-lumen example of the disclosed apparatus operates as follows: There are five catheter lumens in this example, a UV light transmit 308, UV light receive 312, and two fluid transfer lumens (304, 303) respectively. The UV light transmit lumen 308 irradiates the entire length of the catheter with 240 to 280 nm light to inactivate microorganisms at the intraluminal surface 312, hub, hematogenous distant tip 313, and in the fluid (303, 304) flowing through the catheter. This example of the apparatus is identical to the single flow version and operates the same with the exception of having two fluid flow lumens. The two lumens are generally used in central venous catheter applications to carry blood to and from the right atrium heart chamber.

[0047] With reference to FIG. 4, a fluid filled UV light transport lumen example of the disclosed apparatus follows: Each catheter type has a UV light transmit lumen and a UV light receive lumen. These lumens consist of distilled water filled jackets 402 due to the extreme attenuation of UV light in the 240 to 280 nm wavelengths encountered when the jackets are solely implemented with polyethylene plastic (a plastic having the least amount of UV attenuation). Instead, a very thin polyethylene fluid filled jacket is used. An optical coupler 401, also fluid filled, connects a fiber optics cable 404 that delivers the light to the coupler from an LED source in a control unit through an optical hub 405. The single or multi-flow fluid transfer lumens are inserted in the light carrying jackets 403 to complete the catheter implementation.

[0048] With reference to FIG. 5, a functional block diagram of the control unit of the disclosed apparatus is provided. The purpose of the control unit is to execute an AI directed protocol that selects the ON-OFF-SWITCHING, PULSE DURATION, IRRADIATION WAVELENGTH SELECTION, FLORECENSE WAVELENGTH SELECTION, and POWER LEVEL required to inactivate bacteria or virus microorganisms present on the catheter external surface. A deep learning neural net AI algorithm implemented in software running on an embedded processor 503 within the control unit executes this operation.

[0049] The components of the control unit include: [0050] a source of UV light when connected to the lumen fiber optic hub (510); [0051] a source for providing the ON TIME for UV irradiation (508); [0052] a source for providing irradiation wavelength (508,509); [0053] a source for providing the irradiation power level (507); [0054] a sensor for detecting presence of fluoresced microorganisms (505); [0055] a embedded micro-processor 503 for executing artificial intelligence software that automatically determines the power level, irradiation wavelength, and irradiation ON TIME that maximizes the efficiency of deactivating the biofilm microorganisms while minimizing the destruction of keratinocytes associated with the insertion site; [0056] an interface to an external device via USB (cell phone, laptop computer, online connected device (517); [0057] an optical filter unit for separating irradiation wavelengths from fluoresced wavelengths (516); [0058] an internal interface bus (504); [0059] a fiber optics hub connecting the irradiating sources to catheter fiber optics cables (511, 514); [0060] a manual operating switch and associated display panel (501).

[0061] The control unit has an embedded internal microchip PC 503 which executes the algorithms and protocols associated with the MMC system. The ON TIME algorithm running on the embedded PC signals 506 the LED drivers 507 turn-on times for the UV light LED array 509. The specific wavelength is also controlled by the embedded PC such that individual or concurrent LEDs 508 are turned on based on the type of microorganism that is to be inactivated or detected.

[0062] The operational sequence starts with the control unit in the detection mode whereby the LED array outputs a 300 to 780 nm light to the catheter fiber optic transmit hub 511. This near UV light energy is used to florescenced microorganisms that may be present along the outer walls, insertion site, or inner fluid of the catheter. The specific type of biofilm is determined by the wavelength of the fluoresced microorganisms which is determined by the optical filter bank 516 and sent 515 to a photodiode detector sensor 505 in the control unit. The level of the detected fluoresce is transferred 504 to the microchip PC 503 where the AI algorithm determines what wavelength, ON TIME, and power level should be used to inactivate the biofilm. The microchip PC 503 then enables the appropriate LED drivers 507 to deliver UV light in the 180 to 270 nm band at the fiber optics transmit hub 511. The switch and display panel 501 allows the operator to power on the unit, select the inactivation protocol, select the automatic mode algorithm, and select the reporting action through local alarm, through a smartphone via USB interface 517, or an external PC. The smartphone interface enables contamination status to be reported to healthcare personnel remotely.

[0063] FIG. 6 illustrates the layers of the deep learning neural net that identifies the microorganism patterns present on the catheter surface. This identification is based on sixteen samples 601 of surface biofilm fluoresced by sixteen different wavelengths. Based on the florescence pattern detected, the deep learning neural net 602, 603, 604 creates an irradiation regime 605 that completely inactivates the biofilm microorganisms while causing minimum damage to keratinocytes. A bank of eight different irradiation sources is controlled by the deep learning neural net.

[0064] FIG. 7 illustrates one embodiment of this invention as a complete dual lumen catheter system. The catheter is connected to the control unit 702 with an attached fiber optics cable 708, thus alleviating the possibility of electrical shock to the patient. The control unit is reusable with any MMC type catheter while the actual catheter unit 703, 704, 705, 706, and 707 is disposable. The disposable portion of the catheter has the usual elements of a traditional dual lumen catheter. A power cable 701 is included to recharge batteries during mobile use or connect to A/C source during long term use.