There is provided a microparticle composition suitable for molecular imaging, the composition comprising microparticles, wherein the microparticles comprise: a core microparticle structure having a central area and a shell, and wherein the core microparticle structure comprises (i) a phosphatidylcholine lipid: (ii) a phosphatidylethanolamine lipid comprising at least one maleimide moiety; and (iii) an alkoxylated fatty acid.

In some examples, a method includes receiving a signal indicative of a blood pressure of a patient and identifying at least one first portion of the signal comprising a first characteristic of the signal exceeding a first threshold. The method also includes identifying at least one first portion of the signal comprising a second characteristic of the signal exceeding a second threshold, the first characteristic being different than the second characteristic. The method further includes determining a filtered signal indicative of the blood pressure of the patient by excluding the at least one first portion and the at least one second portion from the signal. The method includes determining a set of mean arterial pressure values based on the filtered signal and determining an autoregulation status of the patient based on the set of mean arterial pressure values.

A system and a method for identifying a patient with a threshold number of distinct ECG abnormalities. The system and the method include an ECG monitoring device; a server; a database; a network; a memory containing machine readable medium comprising a machine executable code having stored thereon instructions for identifying patients with a threshold number of distinct ECG abnormalities; and a processor coupled to the memory, the processor configured to execute the machine executable code to cause the processor to: receive an ECG data output from the ECG monitoring device; process the ECG data output to identify abnormalities in the ECG data; and analyze the abnormalities in the ECG data in order to output an indication of whether the patient has depressed LVEF, wherein the ECG monitoring device, the server, the database, the memory, and the processor are coupled to the network via communication links.

Apparatus for the diagnostics and treatment of conditions presenting as intracranial circulation maladies in reliance upon segmental intracranial compartment pressure, which is established from the interdynamics between intra-cranial and extra-cranial circulation, and which relies upon compression of the extra-cranial vascular network in order to: measure cranial inflow and outflow pressure in the intra-extra cranial collateral (e.g., in the network supplied by the supraorbital artery), to estimate intracranial compartment segmental perfusion pressure; temporarily augment intracranial inflow pressure during a period of the compromise (e.g., common carotid cross-clamp during carotid endarterectomy or extracranial stenosis with low-flow state) and redirect extracranial blood-flow intracranially to augment cerebral circulation and/or introduce therapeutic agents or cold blood to the intracranial compartment.

Systems and methods are disclosed for to determining a blood supply and blood demand. One method includes receiving a patient-specific model of vessel geometry of at least a portion of a coronary artery, wherein the model is based on patient-specific image data of at least a portion of a patient's heart having myocardium; determining a coronary blood supply based on the patient-specific model; determining at least a portion of the myocardium corresponding to the coronary artery; determining a myocardial blood demand based on either a mass or a volume of the portion of the myocardium, or based on perfusion imaging of the portion of the myocardium; and determining a relationship between the coronary blood supply and the myocardial blood demand.

A vital signs monitoring system includes a peak pattern detection module configured to output a peak prediction signal from sensor signals based on a peak prediction algorithm; a vital sign estimating module configured to estimate a vital sign based on the peak prediction signal; an activity and context detector module configured to output a context signal based on at least one environmental condition and/or activity level of the person; and a concept drift detection module configured to output a drift signal based on drift detected in the estimated vital sign. The peak pattern prediction module is configured to update the peak prediction algorithm based on the context signal and the drift signal.

A method for monitoring autoregulation includes, using a processor, using a processor to execute one or more routines on a memory. The one or more routines include receiving one or more physiological signals from a patient, determining a correlation-based measure indicative of the patient's autoregulation based on the one or more physiological signals, and generating an autoregulation profile of the patient based on autoregulation index values of the correlation-based measure. The autoregulation profile includes the autoregulation index values sorted into bins corresponding to different blood pressure ranges. The one or more routines also include designating a blood pressure range encompassing one or more of the bins as a blood pressure safe zone indicative of intact regulation and providing a signal to a display to display the autoregulation profile and a first indicator of the blood pressure safe zone.

A method and apparatus for monitoring a subject's autoregulation function state is provided. The method includes: a) continuously sensing a tissue region of the subject with a tissue oximeter, the sensing producing first signals, and determining frequency domain tissue oxygen parameter values; b) continuously measuring a blood pressure level of the subject using a blood pressure sensing device, the measuring producing second signals, and determining frequency domain blood pressure values; c) determining a coherence value indicative of the subject's autoregulation state in each of a plurality of different frequency bands; and d) determining a peak coherence value indicative of the subject's autoregulation state based on the determined coherence value from each of the plurality of different frequency bands.

Tools and techniques for estimating a probability that a patient is bleeding or has sustained intravascular volume loss (e.g., due to hemodialysis or dehydration) and/or to estimate a patient’s current hemodynamic reserve index, track the patient’s hemodynamic reserve index over time, and/or predict a patient’s hemodynamic reserve index in the future. Tools and techniques for estimating and/or predicting a patient’s dehydration state. Tools and techniques for controlling a hemodialysis machine based on the patient’s estimated and/or predicted hemodynamic reserve index.

Systems and methods for monitoring and display of a hemodynamic status of a patient. Hemodynamic status may be monitored using, for example, a transducer, an adapter and one or more monitor devices. The adapter may be in communication with the transducer and the one or more monitor devices. The adapter can be configured to receive and process data from the transducer such as unprocessed physiological data. The adapter can be configured to transmit data to the monitor device(s) such as processed and/or unprocessed physiological data. The adapter can be configured to generate, and transmit to the monitor devices(s), user interface data for rendering interactive graphical user interfaces to display information such as physiological information relating to a hemodynamic status of the patient. The adapter can be configured to receive and process, from the monitor device(s) user commands or instructions to control an operation of the system or its components.