Ultrasound system for organ recognition

Abstract

An organ blood flow monitor includes an ultrasound transducer probe and an adhesive patch connected to the ultrasound transducer probe for attaching the ultrasound transducer probe to a patient. The organ blood flow monitor also includes a system memory storing monitoring software code with an organ recognition module. A processor of the organ blood flow monitor is configured to execute the organ recognition module to scan a Doppler flow signal sensed in an abdomen of the patient by the ultrasound transducer probe for at least two cardiac cycles of the patient. The processor also executes the organ recognition module to process the scanned Doppler flow signal through a renal heuristic algorithm, a portal vein heuristic algorithm, and / or a hepatic vein heuristic algorithm of the organ recognition module to identify whether the scanned Doppler flow signal represents renal blood flow, portal vein flow, or hepatic vein flow of the patient.

Description

[0001] ULTRASOUND SYSTEM FOR ORGAN RECOGNITION

[0002] CROSS-REFERENCE TO RELATED APPLICATION^ )

[0003] This application claims the benefit of U.S. Provisional Application No. 63 / 666,586, filed July 1, 2024, and entitled “ULTRASOUND SYSTEM FOR ORGAN RECOGNITION,” the disclosure of which is hereby incorporated by reference in its entirety.

[0004] BACKGROUND

[0005] Acute kidney injury (AKI) occurs when a kidney experiences a sudden decrease in function. AKI can be a complication from major abdominal surgery and may increase a risk of chronic kidney disease in a patient if AKI is not detected and treated at an early stage. Decreased perfusion to the kidney(s) during surgery is one cause of AKI. Detecting AKI in a patient is traditionally done by viewing two biomarkers in the patient. The first biomarker is analyzing urine output of the patient and the second biomarker is measuring serum creatinine from a blood sample of the patient. These biomarkers generally do not show up in the patient until about eight hours to forty-eight hours after the injury has occurred to the kidney(s). Due to the late onset of these biomarkers, physicians can only use these biomarkers to detect whether AKI has occurred a relatively long time after the kidney has been damaged, and cannot use these biomarkers to monitor health of the kidneys in real time during a surgery. The ability to monitor the health of the kidneys and other organs during surgery would not only allow physicians the ability of early detection of AKI, but possibly the ability to prevent AKI in the patient.

[0006] SUMMARY

[0007] A method for monitoring an organ blood flow of a patient is disclosed. The method includes performing a finding phase. The finding phase includes scanning, by an ultrasound transducer probe and a beamformer driving the ultrasound transducer probe, a volume within an abdomen of the patient under a field of view of the ultrasound transducer probe. The finding phase also includes detecting, by a processor in communication with the ultrasound transducer probe and the beamformer, a Doppler flow signal of the organ blood flow. The method also includes performing an organ identification phase. The organ identification phase includes scanning a data segment, by the ultrasound transducer probe, the beamformer, and the processor, of the Doppler flow signal for at least two cardiac cycles of the patient. The data segment is processed by the processor through a portal vein heuristic algorithm to determine a portal vein score of the Doppler flow signal. The data segment is also processed by the processor through a hepatic vein heuristic algorithm to determine a hepatic vein score of the Doppler flow signal. The processor also processes the data segment through a renal heuristic algorithm to determine a renal blood flow score of the Doppler flow signal. The Doppler flow signal is identified by the processor as a portal vein flow, as a renal blood flow, or as a hepatic vein flow of the patient based on the portal vein score, the hepatic vein score, and the renal artery score. The ultrasound transducer probe is affixed on the abdomen of the patient with an adhesive patch based on the portal vein score, the hepatic vein score, or the renal artery score. The processor commands the beamformer and the ultrasound transducer probe to track scan the Doppler flow signal based on the portal vein score, the hepatic vein score, or the renal artery score. The Doppler flow signal is track-scanned by the beamformer and the ultrasound transducer probe to continuously sense the Doppler flow signal of the organ blood flow of the patient during a surgery, medical procedure, or medical observation without an ultrasound operator.

[0008] A method for monitoring a patient during a surgery, medical procedure, or medical observation is disclosed. The method includes performing a finding phase. The finding phase includes scanning three-dimensionally, by an ultrasound transducer probe and a beamformer driving the ultrasound transducer probe, a volume within an abdomen of the patient under a field of view of the ultrasound transducer probe. The finding phase also includes detecting, by a processor in communication with the ultrasound transducer probe and the beamformer, a first Doppler flow signal of the organ blood flow. The finding phase also includes detecting, by the processor, a second Doppler flow signal of the organ blood flow. The method also includes performing an organ identification phase. The organ identification phase includes scanning a first data segment, by the ultrasound transducer probe, the beamformer, and the processor, of the first Doppler flow signal for at least two cardiac cycles of the patient. A second data segment is also scanned by the ultrasound transducer probe, the beamformer, and the processor, of the second Doppler flow signal for at least two cardiac cycles of the patient. The organ identification phase also includes processing, by the processor, the first data segment through a portal vein heuristic algorithm to determine a portal vein score of the first Doppler flow signal. The first data segment is also processed by the processor through a hepatic vein heuristic algorithm to determine a hepatic vein score of the first Doppler flow signal. The processor also processes the first data segment through a renal heuristic algorithm to determine a renal blood flow score of the first Doppler flow signal. The processor identifies the first Doppler flow signal as a portal vein flow, as a renal blood flow, or as a hepatic vein flow of the patient based on the portal vein score, the hepatic vein score, and the renal artery score of the first Doppler flow signal. The processor processes the second data segment through the portal vein heuristic algorithm to determine a portal vein score of the second Doppler flow signal. The second data segment is also processed by the processor through the hepatic vein heuristic algorithm to determine a hepatic vein score of the second Doppler flow signal. The processor also processes the second data segment through the renal heuristic algorithm to determine a renal blood flow score of the second Doppler flow signal. The processor identifies the second Doppler flow signal as the portal vein flow, as the renal blood flow, or as the hepatic vein flow of the patient based on the portal vein score, the hepatic vein score, and the renal artery score of the second Doppler flow signal. The method also includes affixing the ultrasound transducer probe on the abdomen of the patient with an adhesive patch based on the portal vein score, the hepatic vein score, or the renal artery score of the first Doppler flow signal or the second Doppler flow signal. The processor commands the beamformer and the ultrasound transducer probe to track scan at least one of the first Doppler flow signal and the second Doppler flow signal based on the portal vein score, the hepatic vein score, or the renal artery score of the first Doppler flow signal or the second Doppler flow signal.

[0009] A system includes an ultrasound transducer probe configured to continuously measure a Doppler flow signal of an organ blood flow of a patient during a surgery, a medical procedure, or a medical observation. An adhesive patch is connected to the ultrasound transducer probe and is configured to attach the ultrasound transducer probe to the patient and maintain contact between the patient and the ultrasound transducer probe without an operator. The system also includes a beamformer configured to drive the ultrasound transducer probe to track the Doppler flow signal. A blood flow monitor is in communication with the ultrasound transducer probe and includes a system memory and a processor. The system memory stores monitoring software code and the processor is configured to execute the monitoring software code to track into a data segment, by the ultrasound transducer probe, the beamformer, and the processor, the Doppler flow signal for at least two cardiac cycles of the patient. The processor is configured to execute the monitoring software code to process, by the processor, the data segment through a portal vein heuristic algorithm to determine a portal vein score of the Doppler flow signal. The processor is configured to execute the monitoring software code to process, by the processor, the data segment through a hepatic vein heuristic algorithm to determine a hepatic vein score of the Doppler flow signal. The processor is also configured to execute the monitoring software code to process, by the processor, the data segment through a renal heuristic algorithm to determine a renal artery score of the Doppler flow signal. The processor is also configured to execute the monitoring software code to identify, by the processor, the Doppler flow signal as a portal vein flow, as a renal artery flow, or as a hepatic vein flow of the patient based on the portal vein score, the hepatic vein score, and the renal artery score.

[0010] A method is disclosed for monitoring an organ blood flow of a patient during a surgery, a medical procedure, or a medical observation. The method includes performing a finding phase. The finding phase includes scanning, by an array of transducer elements of an ultrasound probe and a beamformer driving the array of transducer elements, a volume within an abdomen of the patient under a field of view of the array of transducer elements. The finding phase also includes detecting, by a processor in communication with the ultrasound transducer probe and the beamformer, a Doppler flow signal of the organ blood flow. The method also includes performing an organ identification phase. The organ identification phase includes scanning a data segment, by the array of transducer elements, the beamformer, and the processor, of the Doppler flow signal for at least two cardiac cycles of the patient. The organ identification phase also includes processing, by the processor, the data segment through a renal heuristic algorithm to determine a renal blood flow score of the Doppler flow signal. The processor identifies the Doppler flow signal as a renal blood flow or as a non-renal blood flow of the patient based on the renal blood flow score. The method also includes affixing the ultrasound transducer probe in a stationary position to the abdomen of the patient with an adhesive patch after the processor identifies the Doppler flow signal as the renal blood flow of the patient. The Doppler flow signal is continuously measured with the ultrasound transducer probe attached in the stationary position to the abdomen of the patient during the surgery, the medical procedure, or the medical observation.

[0011] An organ blood flow monitor includes an ultrasound transducer probe and an adhesive patch connected to the ultrasound transducer probe for attaching the ultrasound transducer probe to a patient. The organ blood flow monitor also includes system memory that stores monitoring software code. The monitoring software code includes an organ recognition module. The organ blood flow monitor also includes a processor configured to execute the organ recognition module to scan a Doppler flow signal sensed in an abdomen of the patient by the ultrasound transducer probe for at least two cardiac cycles of the patient. The processor is also configured to execute the organ recognition module to process the scanned Doppler flow signal through a renal heuristic algorithm of the organ recognition module to identify whether the scanned Doppler flow signal is from a renal blood flow of the patient.

[0012] An organ blood flow monitor includes an ultrasound transducer probe and an adhesive patch connected to the ultrasound transducer probe for attaching the ultrasound transducer probe to a patient. The organ blood flow monitor also includes a system memory that stores monitoring software code. The monitoring software code includes an organ recognition module. The organ blood flow monitor also includes a processor configured to execute the organ recognition module to track a Doppler flow signal sensed in an abdomen of the patient by the ultrasound transducer probe for at least two cardiac cycles of the patient. The processor is also configured to execute the organ recognition module to process the tracked Doppler flow signal through a portal vein heuristic algorithm of the organ recognition module to identify whether the tracked Doppler flow signal is from a portal vein blood flow of the patient.

[0013] An organ blood flow monitor includes an ultrasound transducer probe and an adhesive patch connected to the ultrasound transducer probe for attaching the ultrasound transducer probe to a patient. The organ blood flow monitor also includes a system memory that stores monitoring software code. The monitoring software code includes an organ recognition module. The organ blood flow monitor also includes a processor configured to execute the organ recognition module to track a Doppler flow signal sensed in an abdomen of the patient by the ultrasound transducer probe for at least two cardiac cycles of the patient. The processor is also configured to execute the organ recognition module to process the tracked Doppler flow signal through a hepatic vein heuristic algorithm of the organ recognition module to identify whether the tracked Doppler flow signal is from a hepatic vein blood flow of the patient.

[0014] BRIEF DESCRIPTION OF THE DRAWINGS

[0015] FIG. 1 is a schematic diagram illustrating an example monitoring system with a blood flow monitor, an ultrasound transducer probe attached to an abdomen of a patient by an adhesive patch, and a hemodynamic pressure sensor connected to the patient for sensing hemodynamic data and a cardiac cycle of the patient.

[0016] FIG. 2 is another schematic diagram illustrating the blood flow monitor of FIG. 1 connected a breathing monitor and to an ultrasound transducer probe with a two- dimensional array of transducer elements. FIG. 3 is a schematic diagram of an ultrasound transducer probe attached to an abdomen of a patient by an adhesive patch to monitor a kidney of the patient.

[0017] FIG. 4A is another schematic diagram of an ultrasound transducer probe attached to an abdomen of a patient by an adhesive patch to monitor a kidney of the patient.

[0018] FIG. 4B is another schematic diagram of an ultrasound transducer probe attached to an abdomen of a patient by an adhesive patch to monitor a kidney of the patient.

[0019] FIG. 5 is a schematic diagram of an ultrasound transducer probe with an array of transducer elements.

[0020] FIG. 6 is a block diagram of a method for continuously monitoring a blood flow of an organ of a patient.

[0021] FIG. 7 is a block diagram of another method for continuously monitoring a blood flow of an organ of a patient.

[0022] FIG. 8 is a block diagram of a method for verifying an identity of a blood flow signal from an organ blood flow of the patient.

[0023] FIG. 9 is a plot and block diagram representing a portal vein heuristic algorithm.

[0024] FIG. 10 is a plot and block diagram representing a hepatic vein heuristic algorithm.

[0025] FIG. 11 is a plot and block diagram representing a renal heuristic algorithm.

[0026] FIG. 12 is a plot and block diagram representing another example of the renal heuristic algorithm.

[0027] FIG. 13 is a plot and block diagram representing another example of the renal heuristic algorithm.

[0028] FIG. 14 is a block diagram of another method for verifying an identity of a blood flow signal from an organ blood flow of the patient.

[0029] DETAILED DESCRIPTION

[0030] The present disclosure is directed to a system and a method to monitor in real time a blood flow of an abdominal organ, such as a kidney, of a patient during a surgery, medical procedure, or medical observation of the patient. The system includes a blood flow monitor with an ultrasound transducer probe. The system also includes an adhesive patch that can attach the ultrasound transducer probe to a patient and keep the ultrasound transducer probe attached to the patient throughout a surgery, medical procedure, or medical observation of the patient without assistance from an ultrasound operator. The blood flow monitor also includes a beamformer and ultrasound front-end (UFE) circuitry in communication with the ultrasound transducer probe to drive an array of transducer elements of the ultrasound transducer probe to find and track a target vessel.

[0031] In this disclosure, a Doppler flow signal is defined as comprising an ultrasound pulse-echo signal received from tissue, filtered to only contain those spectral components with a large enough Doppler shift to be reliably identified as having been generated by flowing blood cells. An instantaneous spectrum is defined as a power spectrum of a windowed portion of the Doppler flow signal with a window centered at a particular moment in time. Tn this disclosure, a Doppler spectrogram is defined as a timefrequency representation of the Doppler flow signal in which instantaneous spectrum is calculated for many timepoints to characterize how the instantaneous spectrum changes over time. The Doppler spectrogram is often visualized as a heat-map plot with frequency along one axis and time along a second axis. Relative intensity of the Doppler spectrogram can be interpreted as an indication of a fraction of scatterers (i.e., blood cells) with a particular velocity (i.e., a particular Doppler shift) at a particular moment in time. Negative frequency components of the Doppler spectrogram arise from scatterers that move away from the ultrasound transducer probe while the positive frequency components arise from scatterers moving towards the ultrasound transducer probe. Integrated power spectrum is defined as comprising the integral of the Doppler spectrogram along the frequency dimension. The integral of the Doppler spectrogram may be taken over all frequencies, over only the positive frequencies, over only the negative frequencies or over some other subset of frequencies. In cases where a signal from a particular vessel is sought, the integrated power spectrum will be calculated over a range of frequencies appropriate to isolate the Doppler flow signal from that vessel from interfering signals of nearby vessels. In particular, since blood flow in the renal artery is directed towards the ultrasound transducer probe and blood flow in the renal vein is directed away from the ultrasound transducer probe, the integrated power spectrum calculated in relation to the renal artery can comprise an integral over only positive frequencies while the integrated power spectrum calculated in relation to the renal vein can be calculated only over negative frequencies.

[0032] Depending on the application, the system may be configured to measure flow in many multiple different arteries or veins in various organs using the same techniques described in this disclosure for scanning, tracking and measuring Doppler signals. When methods are not specific to a particular vessel, the vessel that is being tracked will be referred to as the target vessel or the target organ blood flow. The beamformer is configured to continuously track a Doppler flow signal of an organ blood flow, such as renal blood flow, of the patient by emitting a set of sequential beams from the array of transducer elements and steering them to track the Doppler flow signal of the organ blood flow relative to the array of transducer elements focused on different locations. By beam steering to track the Doppler flow signal of the organ blood flow, the beamformer allows continuous sensing of the Doppler flow signal of the organ blood flow throughout the surgery, medical procedure, or medical observation without moving or readjusting the position of the ultrasound transducer probe on the patient. Even if the organ shifts position in the abdomen of the patient, beam steering by the beamformer enables the ultrasound transducer probe to continue sensing the organ blood flow without moving or readjusting the position of the ultrasound transducer probe on the patient. The ultrasound transducer probe sends the sensed measurements of the Doppler flow signal to the beamformer and the UFE circuitry where the sensed measurements are converted into a real time continuous reading of the organ blood flow. The beamformer and the UFE circuitry send the real time continuous reading of the organ blood flow to the blood flow monitor for health monitoring and perfusion of the organ throughout the duration of the surgery, medical procedure, or medical observation. The blood flow monitoring system is described in detail below with reference to FIGS. 1-14.

[0033] FIG. 1 is a schematic diagram of patient 10 and monitoring system 11 that continuously monitors an organ blood flow of patient 10 during a surgery, medical procedure, or medical observation. As shown in the example of FIG. 1 , monitoring system 11 can include blood flow monitor 12, ultrasound transducer probe 14, adhesive patch 15, ultrasound front-end (UFE) circuitry 16, hemodynamic pressure sensor 17, system processor 19, system memory 20 with software code 22, probe cables 24, first analog-to- digital converter (ADC) 26, second ADC 27, and display 28. Software code 22 can include transducer probe control module 30, injury monitoring module 32, and organ recognition module 33. Display 28 can include user interface 34, plot 35, injury score indicator 36, and identity determination score 37. Monitoring system 11 can also include input device(s) 38 and output device(s) 39. FIG. 1 also shows abdomen 40 of patient 10 along with kidneys 42E and 42R, liver 44, and spleen 45. In the example of FIG. 1, monitoring system 1 1 is monitoring a renal blood flow of kidney 42R of patient 10. In other examples, monitoring system 11 can be used to monitor hepatic blood flow of liver 44, to monitor celiac blood flow of spleen 45, the pancreas (not shown), and / or the stomach (not shown) of patient 10. In other examples, monitoring system 11 can be used to monitor mesenteric blood flow of the intestines and / or to monitor portal blood flow from the stomach of patient 10. Thus, blood flow monitor 12 can be adapted as an organ blood flow monitor for any organ in abdomen 40 of patient 10.

[0034] Blood flow monitor 12, can be, e.g., an integrated hardware unit that includes system processor 19, system memory 20, display 28, UFE circuitry 16, first ADC 26, and second ADC 27. In other examples, any one or more components and / or described functionality of blood flow monitor 12 can be distributed among multiple hardware units. For instance, in some examples, display 28 can be a separate display device that is remote from and operatively coupled with blood flow monitor 12 as an output device 39. In general, though illustrated and described in the example of FIG. 1 as an integrated hardware unit, it should be understood that blood flow monitor 12 can include any combination of devices and components that are electrically, communicatively, or otherwise operatively connected to perform functionality attributed herein to blood flow monitor 12. Input device(s) 38 can be connected to blood flow monitor 12 such that a user may input data and / or commands into blood flow monitor 12. Non- limiting examples of input device(s) 38 includes a keyboard, a touchpad, and / or other devices whereby a user may input data and / or commands into blood flow monitor 12. Input device(s) 38 can also include a port configured for communication with an external input device via hardwire or wireless connection.

[0035] Ultrasound transducer probe 14 can be attached or secured to patient 10 by adhesive patch 15. In the example of FIG. 1, ultrasound transducer probe 14 is positioned on abdomen 40 of patient 10 over at least a portion of kidney 42R. Adhesive patch 15 can include a sheet of structural material, such as fabric or flexible plastic, with a layer of bonding adhesive deposited on a face of the sheet. Adhesive patch 15 can be bonded to or mechanically connected to ultrasound transducer probe 14, or to a frame (not shown) connected to a base of ultrasound transducer probe 14, and can extend outward from ultrasound transducer probe 14 along a surface of abdomen 40 of patient 10. In other examples, adhesive patch 15 can be placed over ultrasound transducer probe 14 to attach ultrasound transducer probe 14 to abdomen 40 of patient 10. Adhesive patch 15 keeps ultrasound transducer probe 14 attached to patient 10 and secured in place throughout a duration of the surgery, medical procedure, or medical observation of patient 10. Since adhesive patch 15 keeps ultrasound transducer probe 14 immobile and in contact with patient 10, an ultrasound operator or technician is not needed during the surgery, medical procedure, or medical observation to keep ultrasound transducer probe 14 in position. A coupling layer (not shown) with a couplant material can be positioned between a skin of patient 10 and ultrasound transducer probe 14. The coupling layer enables ultrasonic energy transmission between the skin of patient 10 and ultrasound transducer probe 14.

[0036] In the example of FIG. 1, the ultrasound transducer probe 14 detects and senses a Doppler flow signal DF of the renal blood flow of kidney 42R. Ultrasound transducer probe 14 can be operatively connected to blood flow monitor 12 by cables 24. Via cables 24, ultrasound transducer probe 14 can receive electrical signals from the ultrasound front-end circuitry 16 of the blood flow monitor 12 and can relay the received ultrasound signals from patient 10 to blood flow monitor 12 for extraction of the Doppler flow signal DF of the renal blood flow of kidney 42R. In other examples, UFE circuitry 16 is combined with ultrasound transducer probe 14, can be battery powered and can include a receiver to wirelessly receive commands from blood flow monitor 12. The combined ultrasound front-end circuitry 16 and ultrasound transducer probe 14 can also include a transmitter to wirelessly communicate the Doppler flow signal DF of the renal blood flow of kidney 42R to blood flow monitor 12 for analysis. In some examples, the combined ultrasound transducer probe 14 and UFE circuitry 16 provide the Doppler flow signal DF to blood flow monitor 12 as analog signal 25, which is converted by first ADC 26 to digital hemodynamic data representative of the renal blood flow of kidney 42R. In other examples, the combined ultrasound transducer probe 14 and UFE circuitry 16 can provide the sensed Doppler flow signal DF to blood flow monitor 12 in digital form, in which case blood flow monitor 12 may not include or utilize first ADC 26. In yet other examples, ultrasound transducer probe 14 can provide the Doppler flow signal DF of the renal blood flow of kidney 42R to blood flow monitor 12 as analog signal 25, which is analyzed in its analog form by blood flow monitor 12.

[0037] Hemodynamic pressure sensor 17 is a second sensor of monitoring system 11. In the example of FIG. 1, hemodynamic pressure sensor 17 is a non-invasive hemodynamic pressure sensor attached to patient 10 non-invasively on an extremity of patient 10, such as a wrist, an arm, a finger, an ankle, a toe, or other extremity of patient 10. In other examples, hemodynamic pressure sensor 17 can attached non-invasively to a chest of patient 10.

[0038] Hemodynamic pressure sensor 17 continuously senses hemodynamic data representative of an arterial pressure and a cardiac cycle of patient 10 during the surgery, the medical procedure, or the medical observation of patient 10. The term “continuously” as used herein means that hemodynamic pressure sensor 17 senses and collects patient data on a periodic basis during the monitoring time period, which periodic basis is sufficiently frequent that the periodic basis may be considered to be clinically continuous. For example, hemodynamic pressure sensor 17 can sample a waveform of the hemodynamic data representative of the arterial pressure of patient 10 at a rate of at least 10Hz, at least 20Hz, at least 60Hz, at least 100Hz, or at least 200Hz. In other examples, hemodynamic pressure sensor 17 can sample an average of the signal of the hemodynamic data representative of the arterial pressure of patient 10 over a window of time, such as every ten seconds or less (<10 seconds). Hemodynamic pressure sensor 17 can sample an average of the signal of the hemodynamic data representative of the arterial pressure of patient 10 more frequently, such as every two seconds or less. In other examples, can sample an average of the signal of the hemodynamic data representative of the arterial pressure of patient 10 over a rolling window of time. The present disclosure is not limited to any particular device settings or sampling rate.

[0039] Hemodynamic pressure sensor 17 is operatively connected to blood flow monitor 12 (e.g., electrically and / or communicatively connected via wired or wireless connection, or both) to provide the sensed hemodynamic data to blood flow monitor 12. Hemodynamic pressure sensor 17 can provide the sensed hemodynamic data to blood flow monitor 12 as an electrocardiograph (ECG or EKG), a photoplethysmogram (PPG), an oxygen saturation (SpO2) measurement, and / or a blood pressure waveform. In some examples, hemodynamic pressure sensor 17 provides the sensed hemodynamic data representative of the arterial pressure and the cardiac cycle of patient 10 to blood flow monitor 12 as an analog signal, which is converted by second ADC 27 to digital hemodynamic data representative of the arterial pressure of patient 10. In other examples, hemodynamic pressure sensor 17 can provide the sensed hemodynamic data representative of the arterial pressure of patient 10 to blood flow monitor 12 in digital form, in which case blood flow monitor 12 may not include or utilize second ADC 27. In yet other examples, hemodynamic pressure sensor 17 can provide the hemodynamic data representative of the arterial pressure of patient 10 to blood flow monitor 12 as an analog signal, which is analyzed in its analog form by blood flow monitor 12.

[0040] System memory 20 can be configured to store information within blood flow monitor 12 during operation. System memory 20, in some examples, is described as computer-readable storage media. In some examples, a computer-readable storage medium can include a non-transitory medium. The term “non-transitory” can indicate that the storage medium is not embodied in a carrier wave or a propagated signal. In certain examples, a non-transitory storage medium can store data that can, over time, change (e.g., in RAM or cache). System memory 20 can include volatile and non-volatile computer- readable memories. Examples of volatile memories can include random access memories (RAM), dynamic random access memories (DRAM), static random access memories (SRAM), and other forms of volatile memories. Examples of non-volatile memories can include, e.g., magnetic hard discs, optical discs, flash memories, or forms of electrically programmable memories (EPROM) or electrically erasable and programmable (EEPROM) memories.

[0041] As shown in FIG. 1, system memory 20 of blood flow monitor 12 can store software code 22 which forms a monitoring model of blood flow monitor 12. Software code 22 can include transducer probe control module 30 for controlling and commanding ultrasound transducer probe 14. Transducer probe control module 30, as discussed in greater detail below with reference to FIG. 2, includes a beamformer that keeps ultrasound transducer probe 14 aimed at the renal blood flow of kidney 42R so that ultrasound transducer probe 14 continuously senses and communicates the Doppler flow signal DF of the renal blood flow to blood flow monitor 12 throughout the surgery, medical procedure, or medical observation of patient 10.

[0042] Software code 22 can also include injury monitoring module 32 which includes acute kidney injury (AKI) monitoring software code and / or specific organ injury (SOI) monitoring software code. This code is monitoring software code that allows injury monitoring module 32 to determine, in real time, a characteristic of the renal blood flow of patient 10, monitor the characteristic of the renal blood flow over time, and determine an AKI risk score of patient 10 from the characteristic and the Doppler flow signal DF of the renal blood flow of kidney 42R. The AKI risk score represents the probability that kidney 42R is experiencing or approaching an AKI. When monitoring system 11 is used to monitor an organ other than kidneys 42R and 42L of patient 10, injury monitoring module 32 can be adapted to determine a real-time organ injury risk score from the Doppler flow signal of the organ blood flow of the organ that is being monitored, such as liver 44.

[0043] Organ recognition module 33 is a software module stored in system memory 20 as part of software code 22. As discussed in greater detail below with reference to FIGS. 2 and 6-14, organ recognition module 33 includes a flow identification algorithm that identifies flow signals from non-flow signals and artifacts, and includes organ blood flow heuristic algorithms that can identify specific kinds of organ blood flow signals. When executed by system processor 19, organ recognition module 33 can recognize and distinguish a targeted organ blood flow signal of patient 10 from non- targeted blood flow signals based upon heuristics that quickly analyze waveform characteristics of the targeted organ blood flow signal. In the example of FIG. 1 , the targeted organ blood flow signal is the Doppler flow signal DF of the renal blood flow of kidney 42R, and organ recognition module 33 recognizes the Doppler flow signal DF of the renal blood flow from other non- renal blood flow signals based upon waveform characteristics of the Doppler flow signal DF. Organ recognition module 33 can aid blood flow monitor 12 in monitoring the renal blood flow of kidney 42R by verifying that system processor 19 and transducer probe control module 30 are continually aiming ultrasound transducer probe 14 electronically at the Doppler flow signal DF of the renal blood flow and not mistakenly aiming at some other organ blood flow. This feature can be very useful as monitoring system 11 monitors patient 10 over time as kidney 42R and other organs can shift and move within abdomen 40, causing the Doppler flow signal DF to drift relative to ultrasound transducer probe 14 or cause other organ blood flow signals to appear within a sensing window of ultrasound transducer probe 14.

[0044] System processor 19 is a hardware processor configured to execute software code 22, which implements transducer probe control module 30, organ recognition module 33, and injury monitoring module 32, to continuously sense the Doppler flow signal DF, to identify the organ generating Doppler flow signal DF, and monitor the Doppler flow signal DF for AKI of kidney 42R when the organ recognition module 33 identifies the Doppler flow signal DF as a signal of renal blood flow. Examples of system processor 19 can include any one or more of a microprocessor, a controller, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other equivalent discrete or integrated logic circuitry.

[0045] Display 28 provides user interface 34, which includes control elements that enable user interaction with blood flow monitor 12 and / or other components of monitoring system 11. Display 28 is in communication with system processor 19 and is configured to provide plot 35 in real time of the Doppler flow signal DF of the renal blood flow of kidney 42R. In addition to showing plot 35 of Doppler flow signal DF, display 28 can also provide an audible representation of Doppler flow signal DF via a speaker. Display 28, as shown in FIG. 1, also shows identity determination score 37, or a representation of identity determination score 37, to display 28. Identity determination score 37 indicates whether the Doppler flow signal DF is from the renal blood flow or from a non-renal blood flow (such as portal vein flow or hepatic vein flow). For example, as shown in FIG. 1, identity determination score 37 can state “Renal” when the Doppler flow signal DF is from the renal blood flow. If monitoring system 11 is being used to monitor hepatic vein flow from liver 44, identity determination score 37 can state “Hepatic” when monitoring system 11 finds a Doppler flow signal for the hepatic vein flow. If monitoring system 11 is being used to monitor portal vein flow to liver 44, identity determination score 37 can state “Portal” when monitoring system 11 finds a Doppler flow signal for the portal vein flow. In other examples, identity determination score 37 can use numerical indicators or acronyms. In yet another example, identity determination score 37 can include a quality grade or index of the signal of interest that is assessed from the waveform characteristics of the Doppler flow signal DF.

[0046] Display 28, as shown in FIG. 1, also shows an injury score indicator 36, which is a representation of the real-time AKI risk score of patient 10 determined from the Doppler flow signal DF by system processor 19 and injury monitoring module 32. Display 28 can also include a sensory alarm to alert medical personnel when the real-time AKI risk score of patient 10 is approaching or exceeding a predetermined threshold. The sensory alarm can be implemented as one or more of a visual alarm, an audible alarm, a haptic alarm, or other type of sensory alarm. For instance, the sensory alarm can be invoked as any combination of flashing and / or colored graphics shown by user interface 34 on display 28, a warning sound such as a siren or repeated tone, and a haptic alarm configured to cause blood flow monitor 12 to vibrate or otherwise deliver a physical impulse perceptible to medical personnel.

[0047] Display 28 can be a liquid crystal display (LCD), a light-emitting diode (LED) display, an organic light-emitting diode (OLED) display, or other display device suitable for providing information to users in graphical form. User interface 34 can include graphical and / or physical control elements that enable user input to interact with blood flow monitor 12 and / or other components of monitoring system 11. In some examples, user interface 34 can take the form of a graphical user interface (GUI) that presents graphical control elements presented at, e.g., a touch-sensitive and / or pressure sensitive display screen of display 28. In such examples, user input can be received in the form of gesture input, such as touch gestures, scroll gestures, zoom gestures, or other gesture input. In certain examples, user interface 34 can take the form of and / or include physical control elements, such as a physical buttons, keys, knobs, or other physical control elements configured to receive user input to interact with components of monitoring system 11. User interface 34 can include a speaker that allows blood flow monitor 12 the ability to generate an audible alarm.

[0048] In operation of monitoring system 11 , before a surgery, medical procedure, or medical observation begins, a medical worker places ultrasound transducer probe 14 on abdomen 40 of patient 10. The medical worker uses ultrasound transducer probe 14 in a finding mode to locate the Doppler flow signal DF of the renal blood flow of kidney 42R. In the example of FIGS. 1—14, ultrasound transducer probe 14 can operate in a pulsed-wave Doppler mode while in the finding mode. Ultrasound transducer probe 14 can generate an audible representation of the Doppler flow signal DF to assist the medical worker in locating the Doppler flow signal DF of the renal blood flow of kidney 42R. System processor 19 of blood flow monitor 12 can execute organ recognition module 33 to assist the medical worker in finding and verifying the identity of the Doppler flow signal DF of the renal blood flow of kidney 42R. After organ recognition module 33 identifies the Doppler flow signal DF as a signal of the renal blood flow of kidney 42R, organ recognition module 33 can command system processor 19 to output identity determination score 37 to display 28, thereby alerting and informing the medical worker that the Doppler flow signal DF of the renal blood flow of kidney 42R has been found.

[0049] Once the medical worker finds the Doppler flow signal DF of the renal blood flow of kidney 42R, the medical worker attaches and secures ultrasound transducer probe 14 to patient 10 with adhesive patch 15. Adhesive patch 15 keeps ultrasound transducer probe 14 in constant contact with patient 10 such that ultrasound transducer probe 14 does not shift positions on patient 10 during the surgery, medical procedure, or medical observation and lose the Doppler flow signal DF of the renal blood flow of kidney 42R. Ultrasound transducer probe 14 relays the received ultrasound signals to blood flow monitor 12 via cable(s) 24 or wirelessly. In the case of wireless transmission, the ultrasound transducer probe 14 includes UFE circuitry 16. System processor 19 of blood flow monitor 12 receives the Doppler flow signal DF and processes the Doppler flow signal DF sequentially or simultaneously through transducer probe control module 30 and injury monitoring module 32.

[0050] System processor 19 can execute the AKI monitoring software code of injury monitoring module 32 to establish a baseline value for the renal blood flow of kidney 42R of patient 10 from the Doppler flow signal DF sensed by ultrasound transducer probe 14. Deviations from the baseline value for the renal blood flow can be used as factors by system processor 19 and injury monitoring module 32 to calculate the real-time AKI risk score of kidney 42R. System processor 19 can further execute the AKI monitoring software code of injury monitoring module 32 to continuously monitor the Doppler flow signal DF of the renal blood flow sensed by ultrasound transducer probe 14 throughout a duration of the surgery, medical procedure, or medical observation of patient 10 and to estimate the AKI risk score of kidney 42R of patient 10 from the Doppler flow signal DF. System processor 19 outputs the Doppler flow signal DF and the real-time AKI risk score of kidney 42R to display 28. Display 28 produces plot 35 showing the Doppler flow signal DF of the renal blood flow of kidney 42R plotted over time. Display 28 also produces injury score indicator 36 which represents the real-time AKI risk score of kidney 42R in injury score indicator 36.

[0051] As the surgery, medical procedure, or medical observation of patient 10 progresses, system processor 19 continues to receive the Doppler flow signal DF from ultrasound transducer probe 14 and continues to output both the Doppler flow signal DF and the real-time AKI risk score of kidney 42R to display 28. System processor 19 can also periodically execute organ recognition module 33 to reanalyze the Doppler flow signal DF to verify that ultrasound transducer probe 14 is still sensing the renal blood flow of kidney 42R. System processor 19 can refresh identity determination score 37 on display 28 every time system processor 19 executes organ recognition module 33. If organ recognition module 33 determines that ultrasound transducer probe 14 is no longer sensing the Doppler flow signal DF of the target organ blood flow (the renal blood flow in the case of FIG. 1), organ recognition module 33 can generate an alert to display 28 and a command to system processor 19 to reinitiate the finding mode to locate the Doppler flow signal DF of the renal blood flow of kidney 42R.

[0052] If the real-time AKI risk score of kidney 42R changes toward an undesired threshold, or changes at an undesired rate, system processor 19 and display 28 can alert the medical personnel so that the medical personnel can possibly take action to increase kidney perfusion and prevent AKI to kidney 42R, or minimize AKI to kidney 42R. For example, medical personnel can administer medication or fluids that increases the renal blood flow and perfusion to kidney 42R or improves autoregulation of the renal blood flow to kidney 42R. At the end of the surgery, medical procedure, or medical observation, system processor 19 and injury monitoring module 32 can estimate a final AKI risk score for kidney 42R and output the final AKI risk score to display 28. If the final AKI risk score for kidney 42R indicates that kidney 42R has a high risk of AKI, medical personnel can take immediate action to treat kidney 42R without having to wait for biomarkers to appear in blood and urine samples of patient 10. Biomarkers that indicate AKI can take several hours or days to appear in blood and urine samples of patient 10. With monitoring system 11, the medical personnel can determine quickly whether patient 10 needs to be treated for AKI of kidney 42R.

[0053] When the location of kidney 42R changes relative to ultrasound transducer probe 14 due to breathing or movement of patient 10 during the surgery, medical procedure, or medical observation, transducer probe control module 30 will detect a change in the Doppler flow signal DF and will respond by adjusting the focusing location of the set of beams to scan abdomen 40 of patient 10 to relocate the Doppler flow signal DF and aim the beams from ultrasound transducer probe 14 at the new location of the Doppler flow signal DF of the renal blood flow of kidney 42R. As discussed below with reference to FIGS. 2-5, blood flow monitor 12 can include a beamformer that can steer beam signals produced by an array of transducer elements of ultrasound transducer probe 14.

[0054] FIG. 2 is another schematic diagram of blood flow monitor 12. As shown in FIG. 2, blood flow monitor 12 can include beamformer 46 with predictive filter 47. Ultrasound transducer probe 14 can include array 50 of transducer elements 52. Each transducer element 52 of array 50 can comprise a piezoelectric material, such as lead zirconate titanate, capable of transmitting ultrasound pulses and detecting ultrasound pulses. Array 50 of transducer elements 52 of ultrasound transducer probe 14 can form a two-dimensional phased array with probe length PL and probe width PW. As a phased array, each transducer element 52 in array 50 can pulse individually relative the other transducer elements 52 in array 50. Monitoring system 11 can also include breathing monitor 51 or can be in communication with breathing monitor 51. Organ recognition module 33 can include flow identification algorithm 48 that identifies flow signals from non-flow signals and artifacts. Organ recognition module 33 can also include heuristic algorithms 49 that can recognize and identify specific kinds of organ blood flow signals. Identity determination score 37 can also include quality grade 53. Quality grade 53 can be a grade or index that indicates a confidence level of identity determination score 37 distinguishing the Doppler flow signal (DF) of the renal blood flow (or another targeted organ blood flow) from other organ blood flow signals. Quality grade 53 is discussed below in greater detail with reference to FIG. 8.

[0055] In the example of FIG. 2, beamformer 46 drives array 50 of transducer elements 52 via system processor 19 and UFE circuitry 16. Beamformer 46 functions as a transducer probe controller with flow signal tracking software code that controls the timing that each transducer element 52 in array 50 emits an ultrasound pulse. Beamformer 46 can time and pattern when each transducer element 52 emits a pulse such that array 50 can form one or more ultrasonic beams and can sweep or steer the one or more ultrasonic beams without physically moving the position of ultrasound transducer probe 14 on patient 10. Beamformer 46 can be a software sub-module of transformer probe control module 30 that can be executed by system processor 19 to control activation of transducer elements 52 of array 50. Predictive filter 47 can be a software sub-module of beamformer 46 and / or transformer probe control module 30 that can be executed by system processor 19 to predict an expected trajectory of a target vessel based on measured inputs from beamformer 46 and / or from inputs from other external sensors, such as breathing monitor 51. In other examples, beamformer 46 can be a separate hardware component from system processor 19 and system memory 20 with separate memory and software from software code 22 that coordinates with system processor 19 to control activation of transducer elements 52 of array 50. In the example of FIG. 2, beamformer 46 is housed within blood flow monitor 12 as part of transducer probe control module 30 of software code 22 that is executed by system processor 19. In other examples, beamformer 46 can be fully or partially housed within a casing of ultrasound transducer probe 14 as a separate hardware and software unit that coordinates with system processor 19. Housing beamformer 46 in the same unit as blood flow monitor 12 (whether as part of software code 22 or as an add-on hardware component) can decrease the overall size and thickness of ultrasound transducer probe 14. Ultrasound transducer probe 14 can be relatively thin and flat in profile, with a thickness that is smaller than a width or diameter of ultrasound transducer probe 14. Attaching ultrasound transducer probe 14 to patient 10 by adhesive patch 15 is easier and more secure when ultrasound transducer probe 14 has a thin and flat profile.

[0056] FIG. 3 is another schematic diagram of ultrasound transducer probe 14 attached to abdomen 40 of patient 10 by adhesive patch 15 over kidney 42R. The Doppler flow signal DF of kidney 42R can be measured from either the renal artery RA as blood enters kidney 42R from the aorta of patient 10 via the renal artery or from the renal vein RV as blood exits kidney 42R to the vena cava of patient 10 via the renal vein RV. Ultrasound transducer probe 14 generates originating signals OW that move into abdomen 40 of patient 10. Due to Doppler physics, a Doppler signal BW of the blood flow in the renal artery RA is “blue shifted” as the blood flow in the renal artery RA is moving toward the ultrasound transducer probe 14. A Doppler signal RW of the blood flow in the renal vein RV is “red shifted” as the blood flow in the renal vein RV is moving away from the ultrasound transducer. Since the Doppler signal BW is blue shifted and the Doppler signal RW is red shifted, blood flow monitor 12 can easily distinguish renal artery blood flow from renal vein blood flow. In human subjects the renal artery RA and renal vein RV are close and aligned parallel such that beamformer 46 can position the beam(s) to capture both arterial and venous flow of kidney 42R simultaneously in the same beam / voxel.

[0057] FIGS. 4A, 4B and 5 will be discussed concurrently. FIG. 4A is another schematic diagram of ultrasound transducer probe 14 attached to abdomen 40 of patient 10 by adhesive patch 15 over kidney 42R. FIG. 4B is also a schematic diagram of ultrasound transducer probe 14 attached to abdomen 40 of patient 10 by adhesive patch 15 over kidney 42R at a position slightly higher on abdomen 40 than the position of FIG. 4A. FIG. 5 is another schematic diagram of ultrasound transducer probe 14. In the example of FIGS. 4A and 4B, ultrasound transducer probe 14 is attached by adhesive patch 15 to a surface of abdomen 40 over kidney 42R and over at least some of ribs 54a, 54b, and 54c of patient 10.

[0058] Ultrasound transducer probe 14 can have a probe length PL, probe width PW (shown in FIG. 2), or diameter that is large enough that array 50 of transducer elements 52 of ultrasound transducer probe 14 can cover one or more acoustic windows in patient 10. An acoustic window of patient 10 is defined as an area of patient 10 where transmission of ultrasonic waves is not substantially attenuated in comparison to immediate surroundings. For example, array 50 of transducer elements 52 of ultrasound transducer probe 14 can be sized in length or width to extend over at least two intercostal spaces of patient 10. For example, in FIG. 4A, array 50 of transducer elements 52 of ultrasound transducer probe 14 is positioned over first acoustic window W1 (formed by the intercostal space between rib 54a and rib 54b) and over second acoustic window W2 (formed by the intercostal space between rib 54b and rib 54c). In the example of FIG. 4 A, beamformer 46 (shown in FIG. 2) can selectively activate transducer elements 52 in array 50 to steer signal beams 56a, 56b, and 56c (not visible) into abdomen 40 through the first acoustic window W1 and / or second acoustic window W2 to avoid ribs 54a, 54b, and 54c. In the example of FIG. 4B, ultrasound transducer probe 14 is positioned slightly higher on abdomen 40 of patient 10 in comparison to the example of FIG. 4A. However, the probe length PL or probe width PW of ultrasound transducer probe 14 is long enough that ultrasound transducer probe 14 still has access to first acoustic window W1 and can still scan and steer signal beams 56a, 56b, and 56c (not visible) into abdomen 40 through the first acoustic window Wl. Regardless of where ultrasound transducer probe 14 is placed over ribs 54a, 54b, and 54c, ribs 54a, 54b, and 54c will not block the direct view of kidney 42R from array 50 of ultrasound transducer probe 14.

[0059] Beamformer 46 controls transducer elements 52 in array 50 to beam scan abdomen 40 during a finding phase or a finding mode to locate a target vessel when ultrasound transducer probe 14 is first placed on patient 10. To find the target vessel, beamformer 46 divides the entirety of a volume in the field of view of array 50 into multiple sub-volumes and uses a predefined set of beams (such as beams 56a, 56b, and 56c) to probe each sub-volume. To reduce the search time, the search can be performed in two steps. In a first step the sub-volumes can be made larger in a depth dimension into abdomen 40 while a two-dimensional scan is performed in the other two dimensions only. Once the location of the signal in the other two dimensions is determined by the two-dimension scan, the next step is to reduce the size of the sub-volume in the depth dimension and perform a search along the depth dimension at the previously determined location in the other two dimensions. The sub-volumes can be made larger in the depth dimension by increasing the duration of the driving pulses used to form the firing beams. The sub- volumes can also be made larger in the depth dimension by extracting the Doppler signal at all depths from the received signal from a single firing beam by adjusting the time delay and selecting the one with the highest intensity or an average of the stronger ones.

[0060] Beamformer 46 also controls transducer elements 52 in array 50 to track scan abdomen 40 to track the target vessel over time. Beamformer 46 beam scans and / or track scans the Doppler flow signal DF of the renal blood flow of kidney 42R of patient 10 by sequentially emitting signal beams 56a, 56b, and 56c from array 50 of transducer elements 52 and focusing each of beams 56a, 56b, and 56c in different locations. To track in both the azimuth dimension and the elevation dimension (sometimes referred to as altitude dimension), at least three beams are required. Using more beams will result in more accurate target vessel position estimation at the cost of a lower Nyquist frequency for the Doppler shift and hence the possibility of aliasing of the instantaneous spectrogram. Thus, beamformer 46 is not limited to three beams and can include more than three beams. The beam locations of beams 56a, 56b, and 56c are selected to have a sufficient degree of overlap of beams 56a, 56b, and 56c, such that when a target vessel is located at the center of the three beams the signal-to-noise ratio of the Doppler flow signal in each of the beams is acceptably large (e.g. >20dB). For example, the beam locations may be selected so that the center between beams 56a, 56b, and 56c lies at a point where the pressure is 3dB below its peak value for each of beams 56a, 56b, and 56c. By comparing integrated spectral power measured along multiple signal beams (e.g. beams 56a, 56b, and 56c), beamformer 46 and / or blood flow monitor 12 can estimate a bearing (i.e. the azimuthal and elevation angles) of the target vessel relative to array 50 of transducer elements 52. As a target vessel (e.g., the renal artery RA, and / or the renal vein RV) moves within abdomen 40, or as ultrasound transducer probe 14 moves relative to the target vessel due to breathing of patient 10, the target vessel will move closer to the focus of some of signal beams 56a, 56b, and 56c, which increases the integrated spectral power measured along those beams, and will move further away from the focus of some other(s) of signal beams 56a, 56b, and 56c, which decreases the integrated spectral power measured along those beams. As the target vessel moves, beamformer 46 can redirect signal beams 56a, 56b, and 56c (and possibly more signal beams) in the direction of those beams for which the measured integrated power spectrum is higher and away from those beams for which the integrated power spectrum is lower, thereby tracking the target vessel whose scatterers generate the Doppler flow signal DF. In one example incorporating this tracking methodology, beamformer 46 computes an estimated location for the target vessel as a vector sum of unit vectors along the signal beam directions weighted by the integrated spectral power measured along each of signal beams 56a, 56b, and 56c. The weighting by the integrated spectral power ensures that as beamformer 46 redirects signal beams 56a, 56b, and 56c to the estimated target vessel location, the centroid of the beams 56a, 56b, and 56c will move towards those beams that have the largest integrated spectral power and therefore lie closest to the target vessel.

[0061] In some examples, beamformer 46 and / or blood flow monitor 12 can use estimates of the target vessel location as an input to predictive filter 47, shown in FIG. 2, that contains a model of the expected trajectory of the target vessel. The model of predictive filter 47 can make tracking more stable and accurate by allowing beamformer 46 and / or blood flow monitor 12 to infer in advance a new location for the signal beams that maximizes the signal or signals that correspond to the signature of interest of the target vessel. The model of predictive filter 47 can include Kalman filters. For example, in cases where the main source of target vessel motion is from breathing, predictive filter 47 may contain a periodic trajectory model describing the motion as periodic at the breathing frequency. In some examples, the periodic trajectory model may be implemented as a partial Fourier sum in each direction with the breathing frequency as the fundamental frequency. In such examples, model parameters may include some or all of the amplitude and phase (or equivalently, the amplitudes of the in-phase and quadrature components) of each Fourier component in each direction and the location of the origin about which the periodic motion occurs. In some examples, predictive filter 47 allows the model parameters to be updated in response to a target vessel position estimate obtained from the integrated power spectrum along a plurality of signal beams so that drift in the model parameters over time or the failure of the model to fully describe the trajectory may be accommodated.

[0062] In some examples, predictive filter 47 may incorporate an estimate of uncertainty in the estimate of the target vessel position obtained from the integrated power spectrum measurements. This uncertainty estimate may be used to adjust the degree to which the model parameters are affected by new measurements during parameter updates. In some examples, this uncertainty estimate may be used to force monitoring system 11 to ignore measurements that are invalid, due, for example, to a transient event that corrupts measurements over a period of time. In some examples, this uncertainty estimate may be used to reduce the degree to which measurements affect model parameters when the signal- to-noise ratio of the integrated power spectrum is low and to increase the degree to which measurements affect model parameters when the integrated power spectrum signal-to-noise ratio is high. In some examples, the uncertainty estimate may be adjusted in response to changes in the moments of the instantaneous spectrum of the Doppler flow signal DF (e.g. the mean velocity, the spectral bandwidth), or the maximum velocity envelope of the Doppler spectrogram. In some examples, the uncertainty estimate may be adjusted based on the total integrated power spectrum, including both the negative and positive frequencies, or based on an integrated power spectrum in a different range of Doppler shifts than the range used to estimate target vessel position. For example, the integrated power spectrum over the negative frequencies may be used to estimate the uncertainty in a position estimate arrived at using the integrated power spectrum over the positive frequencies.

[0063] The integrated spectral power is an inherently noisy signal as the Doppler spectrogram contains speckle arising from constructive and destructive interference between large numbers of scatterers distributed randomly through the insonified volume of abdomen 40 and from statistical noise due to variance in the number and orientation of scatterers in the beam(s) over time. Additionally, the integrated power spectrum is modulated by the cardiac cycle because a larger fraction of scatterers will have Doppler shifts large enough to pass through the filter that defines the Doppler flow signal during systole than during diastole. If unmitigated, the variability in the integrated power spectrum due to speckle and the cardiac cycle will lead to a noisy estimate of target vessel location and to inaccurate tracking. In some examples, the noise on the integrated power spectrum is reduced by applying a filter to the integrated power spectrum signal prior to using the integrated power spectrum signal to estimate the target vessel location. Making a kernel duration of the filter longer will make the filter more effective at removing noise, but if the kernel duration of the filter becomes comparable to a timescale of target vessel motion of the target vessel, then the filter will begin to degrade tracking accuracy. Since the fastest source of the target vessel motion is breathing, a filter kernel size shorter than the breathing frequency duration advantageously reduces modulation from cardiac cycle and speckle when maintaining target vessel location estimation accuracy. Statistical noise and speckle noise produce long-tailed intensity distributions with a high probability of producing very large values. While monitoring system 11 can apply linear filters to the integrated power spectrum signal prior to using the integrated power spectrum signal to estimate the target vessel location, linear filters can sometimes be ineffective at smoothing the integrated power spectrum due to these occasional very large intensities. Median filters are advantageously insensitive to outliers and provide a smoother output than is possible with linear filters. Consequently, in some examples, a median filter is used to filter the integrated power spectrum. In some examples the median filter kernel size is selected to be larger than the cardiac cycle duration of patient 10 but less than the breathing frequency duration.

[0064] In some examples, information obtained from other sensors separate from ultrasound transducer probe 14 or a priori information may also be provided to predictive filter 47 estimating the target vessel location. Predictive filter 47 may be configured to incorporate this additional information when adjusting the model parameters as well as adjusting the estimate of target vessel position obtained from the integrated power spectrum. For example, predictive filter 47 may receive input from breathing monitor 51 connected to patient 10 and may use measurements from breathing monitor 51 to update model parameters that capture a breathing frequency of patient 10. In some examples, predictive filter 47 can incorporate both measurements made with external sensors (such as breathing monitor 51) and the estimate of target vessel position obtained from the integrated power spectrum to adjust model parameters. In some examples, predictive filter 47 may use information obtained from integrated power spectrum measurements taken at an earlier point in time. For example, in some examples, tracking of the target vessel may be halted and the directions of signal beams 56a, 56b, and 56c may be fixed in order to observe and identify the periodicity in the integrated power spectrum as the target vessel moves due to breathing. This observation may be used to estimate breathing frequency so that the breathing frequency may be incorporated into predictive filter 47 when tracking resumes. In some examples, predictive filter 47 is implemented as a Linear Kalman Filter. In some examples, predictive filter 47 is implemented as an Unscented Kalman Filter. In some examples, predictive filter 47 is implemented as an Extended Kalman Filter. An input to the Kalman filter can be a centroid of the estimated location of the target vessel in all three dimensions with the Kalman filter based on a periodic movement model with one or more frequency components. Alternatively, the input can be a centroid of the estimated location of the target vessel in only two dimensions while the depth tracking is achieved by extracting the Doppler signal for all depths from the received signal from a single firing beam using the all-depths approach previously described. In yet another alternative approach, a different Kalman filter can use the integrated power spectrum from all firing beams and be based on a different model that estimates position as a byproduct of predicting the integrated power spectrum.

[0065] In some examples, predictive filter 47 may be configured to produce an estimate of the integrated power spectrum signal along each of a plurality of signal beams (such as signal beams 56a, 56b, and 56c) based on an internal parametric model of target vessel position, beam shape and target vessel shape and orientation. The estimate of the integrated power spectrum by predictive filter 47 for each of the plurality of signal beams may be compared to measurements of the integrated power spectrum along each signal beam, and the difference between the prediction and measurement can be used to update the model parameters including those describing the target vessel location. In calculating the integrated power spectrum along the plurality of signal beams, predictive filter 47 may make use of a physical model of the integrated power spectrum that calculates an overlap integral between the target vessel and the ultrasound beam profile. In some examples the physical model may include a description of how the beam profile changes with depth. In some examples the physical model may include an asymmetric beam profile such as would be produced by an asymmetric transducer array.

[0066] In some examples, differences in integrated power spectrum between the different signal beams 56a, 56b, and 56c are used by beamformer 46 and / or blood flow monitor 12 to estimate the bearing (azimuthal and elevation angles) of the target vessel, while the range (distance from the transducer) of the target vessel is estimated by beamformer 46 and / or blood flow monitor 12 by calculating the integrated power spectrum at a plurality of range samples, assigning a likelihood of containing the target vessel to each range sample, and calculating an estimate of the center of the target vessel from the plurality of range samples. In some examples, the likelihood that a range sample contains the target vessel is made proportional, or is assigned a proportional relationship, to the integrated power spectrum at that range so that the estimate of the location of the target vessel range may be estimated, for example, by beamformer 46 and / or blood flow monitor 12 by selecting the range sample with the largest integrated power spectrum or calculating the location of the centroid over the range samples. In other examples, beamformer 46 and / or blood flow monitor 12 can use a likelihood function to take into account integrated power spectrum, spectral moments, Doppler spectrogram shape, and / or integrated power in spectral ranges other than the range where the integrated power spectrum is calculated. Tn many cases, the target vessel may extend over a plurality of range samples, in which case, the accuracy of the integrated power spectrum may be improved by averaging over the plurality of range samples likely to contain the target vessel.

[0067] In some examples, an estimate of target vessel range incorporates the integrated power spectrum calculated for each of a plurality of signal beams (e.g. beams 56a, 56b, 56c). In some examples, beamformer 46 and / or blood flow monitor 12 can arrive at this estimate by first averaging the integrated power spectrum across the plurality of beams at each range sample and then calculating a likelihood of each range sample containing the target on this averaged signal.

[0068] Separating the estimate of the bearing of the target vessel from the estimate of the range of the target vessel in this way is advantageous as the beamformer 46 and / or blood flow monitor 12 can calculate the range estimations more frequently than the bearing estimations over time. Beamformer 46 and / or blood flow monitor 12 can obtain a range estimate on every ultrasound transmit event, while a bearing estimate requires that beamformer 46 move an ultrasound beam to a plurality of locations and that the measurements made at the different locations be compared by beamformer 46 and / or blood flow monitor 12. Having a reliable estimate of range associated with each transmit event ensures that when beamformer 46 and / or blood flow monitor 12 uses the integrated power spectrum to estimate bearing across a plurality of signal beams, the integrated power spectrum from the range or ranges closest to the target vessel are used by beamformer 46 and / or blood flow monitor 12 in the bearing calculation. The separation of range from bearing estimation also simplifies the predictive model used to estimate bearing thereby making the predictive model more robust and reliable.

[0069] In order for ultrasound transducer probe 14 to measure the Doppler flow signal DF of the renal blood flow of kidney 42R, ultrasound transducer probe 14 can have a low center frequency between 0.5 MHz and 4.0 MHz. With a center frequency between 0.5 MHz and 4.0 MHz, ultrasound transducer probe 14 can penetrate more than 15 cm into patient 10, which is a sufficient depth to measure the renal blood flow. This depth also allows ultrasound transducer probe 14 the ability to measure hepatic vein blood flow, celiac artery blood flow, portal vein blood flow, and mesenteric blood flow, for example.

[0070] As shown best in the example of FIG. 5, each transducer element 52 in array 50 comprises an element width EW and element length EL that are both larger than one wavelength in soft tissue of an ultrasonic wave emitted by array 50 of transducer elements 52. Array 50 of transducer elements 52 also includes a pitch EP defining an inter-element spacing between centers of adjacent transducer elements 52. In the example of FIG. 5, the pitch EP is larger than the one wavelength in soft tissue of the ultrasonic wave emitted by array 50 of transducer elements 52. The element width EW, the element length EL, and the pitch EP are all larger than the one wavelength in soft tissue of the ultrasonic wave emitted by array 50 of transducer elements 52 to reduce an element count for the selected aperture of ultrasound transducer probe 14. In a traditional phased array imaging transducer, use of a pitch of greater than one wavelength would result in significant image degradation due to grating lobes. However, for ultrasound transducer probe 14, grating lobes do not degrade the Doppler spectrogram because large blood vessels are sparsely distributed in the body and it is highly unlikely that an interfering Doppler signal source would be located at a grating lobe location when a main lobe is focused on a target vessel. Monitoring system 11 does not use ultrasound transducer probe 14 for high resolution imaging of kidney 42R, thus ultrasound transducer probe 14 does not need to have as high a transducer element count as an ultrasound transducer probe used for ultrasound imaging.

[0071] During the finding phase, system processor 19 divides the entirety of the field of view of array 50 into multiple subsections or sub-volumes of the volume under the field of view of ultrasound transducer probe 14. Each sub-volume of the multiple subvolumes can overlap in area with adjacent sub-volumes to ensure no gaps are inadvertently formed between sub-volumes. For example, each sub-volume of the multiple sub-volumes can overlap in area by 25% to 33% with adjacent sub-volumes. Beamformer 46 then drives array 50 to focus a beam 56 successively on each sub- volume of the multiple sub- volumes for a period until the beam 56 has scanned the entire volume under the field of view of array 50. The period that beam 56 focuses on each subsection can be longer than the breathing frequency of patient 10 to take into account movement within the volume of abdomen 40 that is caused by breathing of patient 10. The entire volume can be scanned multiple times by beam 56 until an observation period is completed. In some examples, the observation period spans multiple cycles of the breathing frequency of patient 10. In other examples, the observation period can span multiple cardiac cycles of patient 10.

[0072] To identify the Doppler flow signal DF in the finding phase, system processor 19 searches in the scans of the volume for a signature of interest of the Doppler flow signal DF that corresponds to the renal blood flow of patient 10. System processor 19 can execute flow identification algorithm 48 of organ recognition module 33 (shown in FIG. 2) to analyze the scans of the volume for the signature of interest of the Doppler flow signal DF that distinguishes the Doppler flow signal DF from non-flow signals and artifacts. The signature of interest of the Doppler flow signal DF can be at least one of, or any combination of, but not limited to, signal intensity of the Doppler flow signal DF, signal velocity of the Doppler flow signal DF, spectral shift of the Doppler flow signal DF, signal direction of the Doppler flow signal DF, spectral shift of signals surrounding the Doppler flow signal DF, and signal direction of the signals surrounding the Doppler flow signal DF. In some examples, system processor 19 can use the maximum intensity signature of the Doppler flow signal DF as the signature of interest to identify the renal blood flow of kidney 42R in the volume. The maximum intensity signature is the portion of the Doppler flow signal DF that has the highest Doppler intensity. The maximum intensity signature of the Doppler flow signal DF has a Doppler intensity that rises above a preset threshold, criterium, criteria, and / or heuristic that is characteristic of renal blood flow. Once system processor 19 finds Doppler flow signal DF with a Doppler intensity that rises above the preset threshold, criterium, criteria, and / or heuristic that is characteristic of renal blood flow (or of another targeted organ blood flow), system processor 19 can execute heuristic algorithms 49 of organ recognition module 33 quickly confirm the identity of the Doppler flow signal DF is from the renal blood flow of kidney 42R, or from another targeted organ blood flow (such as in the case where monitoring system 11 is being used to monitor portal vein flow or hepatic vein flow).

[0073] If system processor 19 cannot find any Doppler flow signals in the scans of the volume that rise above the preset threshold, criterium, criteria, and / or heuristic that is characteristic of a renal blood flow, system processor 19 can send a signal to display 28 indicating that the renal blood flow of kidney 42R is not within the field of view of the ultrasound transducer probe 14 and that ultrasound transducer probe 14 needs to be repositioned on abdomen 40 of patient 10 and the finding phase repeated.

[0074] Once system processor 19 identifies the location of the signature of interest in the scans of the volume, system processor 19 identifies a sub-volume that encloses the signature of interest. In one example, system processor 19 can select dimensions for the sub-volume such that the maximum intensity signature has an intensity decay of 3dB to 12dB at edges of the sub-volume. System processor 19 can output a map of the volume with the sub- volume marked on the map to display 28 so that an operator can verify during the finding phase that system processor 19 has correctly located and identified the Doppler flow signal DF of the renal blood flow of kidney 42R of patient 10. After system processor 19 has identified the location of the maximum intensity signature, has verified the identity of the Doppler flow signal DF as being from the targeted organ blood flow (such as renal blood flow), and has defined the sub-volume that contains the location of the maximum intensity signature, the finding phase ends and system processor 19 can begin a tracking phase of the Doppler flow signal DF.

[0075] In the tracking phase, beamformer 46 drives array 50 to periodically fire a set of beams 56 over the sub-volume containing the maximum intensity signature of the Doppler flow signal DF. Beamformer 46 can also direct array 50 to center the set of beams 56 on the location or point of the maximum intensity signature of Doppler flow signal DF. Beamformer 46 can direct array 50 to limit scanning during the tracking phase to the subvolume containing the maximum intensity signature of the Doppler flow signal DF such the array 50 is only firing beams 56 at the sub-volume containing the maximum intensity signature of the Doppler flow signal DF, instead of the whole volume. Limiting scanning to the sub-volume containing the maximum intensity signature of the Doppler flow signal DF will increase the SNR, thereby allowing ultrasound transducer probe 14 to get a strong Doppler flow signal DF of the renal blood flow while still tracking the position of the Doppler flow signal DF of the renal blood flow.

[0076] If the maximum intensity signature of the Doppler flow signal DF decreases and falls to a level that is below the preset threshold, criterium, criteria, and / or heuristic that is characteristic of renal blood flow during the tracking phase, the system processor 19 can stop the tracking phase. The system processor 19, beamformer 46, and array 50 of ultrasound transducer probe 14 will then repeat the finding phase to relocate the Doppler flow signal DF of the renal blood flow and determine a new sub-volume that contains the maximum intensity signature of the Doppler flow signal DF. If the system processor 19, beamformer 46, and array 50 do not relocate the Doppler flow signal DF after repeating the finding phase, the system processor 19 will send a signal to display 28 indicating that the renal blood flow of kidney 42R is no longer within the field of view of the ultrasound transducer probe 14, ultrasound transducer probe 14 needs to be repositioned on abdomen 40 of patient 10, and the finding phase repeated.

[0077] FIG. 6 is a block diagram of one method 58 for operating monitoring system 11 shown in FIGS. 1 and 2 to continuously monitor a targeted organ blood flow of patient 10. First step 60 of method 58 includes positioning ultrasound transducer probe 14 on abdomen 40 of patient 10. Next, in second step 62, system processor 19 executes transducer probe control module 30 with beamformer 46 to beam scan patient 10 with ultrasound transducer probe 14 to find a Doppler flow signal DF of the targeted organ blood flow in abdomen 40 of patient 10. If the Doppler flow signal DF is not found, blood flow monitor 12 can alert and instruct the medical personnel to reposition ultrasound transducer probe 14 on patient 10 and repeat second step 62. In third step 64, system processor 19 executes transducer probe control module 30 with beamformer 46 to scan the Doppler flow signal DF of the targeted organ blood flow with ultrasound transducer probe 14 for at least two cardiac cycles of patient 10. The scan of the Doppler flow signal DF of the targeted organ blood flow for at least two cardiac cycles can be recorded into a data segment and saved to system memory 20. In fourth step 66, system processor 19 executes organ recognition module 33 to analyze the data segment generated in third step 64 to verify that the Doppler flow signal DF is in fact a signal of the targeted organ blood flow. For example, if the renal blood flow of kidney 42R is the blood flow intended for monitoring by monitoring system 11 during a medical procedure or observation of patient 10, organ recognition module 33 can verify that the Doppler flow signal DF being scanned by ultrasound transducer probe 14 is in fact a signal from the renal blood flow of kidney 42R and not some other blood flow or signal artifact in abdomen 40 of patient 10.

[0078] With the Doppler flow signal DF found and verified, fifth step 68 of method 58 can be performed by attaching and securing ultrasound transducer probe 14 to patient 10 by adhesive patch 15. Adhesive patch 15 keeps ultrasound transducer probe 14 in place on patient 10 and maintains contact between abdomen 40 and ultrasound transducer probe 14 so that monitoring system 11 can continue to sense and analyze the Doppler flow signal DF over an extended time period, such as a surgery or a stay in an intensive care unit (ICU) or an emergency ward. In sixth step 70 of method 58, system processor 19 continuously outputs a plot of the Doppler flow signal DF of the targeted organ blood flow to display 28. As part of sixth step 70, system processor 19 can also execute injury monitoring module 32 to estimate a real-time organ injury risk score of patient 10 from the Doppler flow signal DF of the targeted organ blood flow and output a representation of the real-time organ injury risk score to display 28 as injury score indicator 38. While blood flow monitor 12 continues to read and analyze the organ blood flow signal of the targeted organ, system processor 19 performs seventh step 72 by executing transducer probe control module 30 to track scan the Doppler flow signal DF of the targeted organ blood flow as described above with reference to FIGS. 2-5. If the Doppler flow signal DF of the targeted organ blood flow begins to shift and drift relative to ultrasound transducer probe 14, system processor 19 can perform eighth step 74 by executing transducer probe control module 30 to adjust a position or angle of a beam scan of ultrasound transducer probe 14 to follow the Doppler flow signal DF of the targeted organ blood flow.

[0079] As the surgery or medical procedure of patient 10 progresses, or as the stay of patient 10 in the ICU or emergency ward passes in time, system processor 19 continues to receive the Doppler flow signal DF from ultrasound transducer probe 14 and continues to output both the Doppler flow signal DF and the real-time organ injury risk score of the targeted organ to display 28. If the real-time organ injury risk score changes toward an undesired threshold, or changes at an undesired rate, system processor 19 and display 28 can alert medical personnel so that the medical personnel can possibly take action to increase perfusion to the targeted organ and prevent or minimize injury to the targeted organ. For example, in the case where kidney 42R is the targeted organ, medical personnel can administer medication or fluids that increases the renal blood flow and perfusion to kidney 42R to improve autoregulation of the renal blood flow to kidney 42R. Monitoring system 11 allows medical personnel to take immediate action to treat kidney 42R and other abdominal organs without having to wait for biomarkers to appear in blood and urine samples of patient 10. Biomarkers that indicate acute kidney injury (AKI) can take several hours or days to appear in blood and urine samples of patient 10. With monitoring system 11, the medical personnel can determine quickly whether patient 10 needs to be treated for AKI of kidney 42R.

[0080] FIG. 7 is a block diagram of another method 76 for operating monitoring system 11 shown in FIGS. 1 and 2 to continuously monitor an organ blood flow of a targeted organ of patient 10 and help maintain proper perfusion of the targeted organ. The targeted organ of patient 10 can be kidney 42R or kidney 42L, or any other organ of patient 10, such as liver 44, spleen 46, the pancreas, the stomach, and the intestines. First step 78 of method 76 includes positioning ultrasound transducer probe 14 on patient 10. Next, in second step 80, a technician manually scans patient 10 with ultrasound transducer probe 14 of monitoring system 11 (or another ultrasound probe) to find an organ blood flow signal of the targeted organ.

[0081] Once the technician finds the organ blood flow signal of the targeted organ, the technician performs third step 82 by attaching and securing ultrasound transducer probe 14 to patient 10 by adhesive patch 15 at the location where the organ blood flow signal was found in second step 80. Adhesive patch 15 keeps ultrasound transducer probe 14 in place on patient 10 and maintains contact between abdomen 40 and ultrasound transducer probe 14 so that monitoring system 1 1 can continue to sense and analyze the organ blood flow signal over an extended time period, such as a surgery or a stay in an ICU or an emergency department. With ultrasound transducer probe 14 secured to patient 10 by adhesive patch 15, system processor 19 can proceed with fourth step 84 by executing transducer probe control module 30 with beamformer 46 to command ultrasound transducer probe 14 to beam scan patient 10 to re-find the organ blood flow signal of the targeted organ.

[0082] In fifth step 86, system processor 19 executes transducer probe control module 30 with beamformer 46 to scan the organ blood flow signal of the targeted organ with ultrasound transducer probe 14 for at least two cardiac cycles of patient 10. The scan of the organ blood flow signal of the targeted organ for at least two cardiac cycles can be recorded into a data segment and saved to system memory 20. In sixth step 88, system processor 19 executes organ recognition module 33 to analyze the data segment generated in fifth step 86 to verify that the organ blood flow signal sensed by ultrasound transducer probe 14 is in fact a blood flow signal of the targeted organ. For example, if the portal vein flow of liver 44 is the blood flow intended for monitoring by monitoring system 11 during a medical procedure or observation of patient 10, organ recognition module 33 can verify that the organ blood flow signal being scanned by ultrasound transducer probe 14 is in fact a signal from the portal vein flow of liver 44 and not some other blood flow or signal artifact in abdomen 40 of patient 10.

[0083] With the organ blood flow signal of the targeted organ found and verified, system processor 19 performs seventh step 90 of method 76 by continuously outputting a plot of the organ blood flow signal of the targeted organ to display 28. As part of seventh step 90, system processor 19 can also execute injury monitoring module 32 to estimate a real-time organ injury risk score of patient 10 from the organ blood flow signal and output a representation of the real-time organ injury risk score to display 28 as injury score indicator 38. While blood flow monitor 12 continues to read and analyze the organ blood flow signal of the targeted organ, system processor 19 performs eighth step 92 by executing transducer probe control module 30 to track scan the organ blood flow signal of the targeted organ as described above with reference to FIGS. 2-5. If the organ blood flow signal of the targeted organ begins to shift and drift relative to ultrasound transducer probe 14, system processor 19 can perform ninth step 94 by executing transducer probe control module 30 to adjust a position or angle of a beam scan of ultrasound transducer probe 14 to follow the organ blood flow signal of the targeted organ.

[0084] As the surgery or medical procedure of patient 10 progresses, or as the stay of patient 10 in the ICU or emergency ward passes in time, system processor 19 continues to receive the organ blood flow signal of the targeted organ from ultrasound transducer probe 14 and continues to output both the plot of the organ blood flow signal and the realtime organ injury risk score of the targeted organ to display 28. If the real-time organ injury risk score of the targeted organ changes toward an undesired threshold, or changes at an undesired rate, system processor 19 and display 28 can alert medical personnel so that the medical personnel can possibly take action to increase perfusion (or decrease perfusion) to the targeted organ to prevent or minimize injury to the targeted organ. For example, medical personnel can administer medication or fluids that increases blood flow to the targeted organ to improve autoregulation of the targeted organ. Monitoring system 11 allows medical personnel to take immediate action to care for the targeted organ without having to wait for biomarkers to appear in blood and urine samples of patient 10.

[0085] FIG. 8 is a block diagram of method 95 for verifying the identity of an organ blood flow signal through organ recognition module 33 (shown in FIGS. 1 and 2). In the example of FIG. 8, the organ blood flow signal is a Doppler flow signal sensed by ultrasound transducer probe 14 and suspected as being a blood flow signal of the targeted organ. In first step 96 of method 95, system processor 19 can execute organ recognition module 33 to process the organ blood flow signal through the flow identification algorithm 48 (shown in FIG. 2). The flow identification algorithm 48 is an algorithm that identifies the organ blood flow signal from non-flow signals and signal artifacts in abdomen 40 of patient 10.

[0086] In some examples, the flow identification algorithm 48 can include waveform analyzer 97 that employs a machine learning based classifier. System processor 19 can execute waveform analyzer 97 to calculate signal features such as the Signal-to- Noise Ratio (SNR), integrated power spectrum, spectral envelope, pulsatility, and spectral bandwidth from the organ blood flow signal. The machine learning based classifier can be trained on labelled training datasets of Doppler flow signals that use the signal features outputted by waveform analyzer 97 (for example, SNR, integrated power spectrum, spectral envelope, pulsatility, and spectral bandwidth) as input features. Waveform analyzer 97 can use various classifier models to classify Doppler flow signals including Random Forest Classifiers and Support Vector Machine (SVM) classifiers. One example of this classification system was trained on a dataset of 5,756 samples, each sample including a 0.25s segment of a Doppler signal taken from one of four healthy subjects. The dataset was 17 minutes in total time, with some of the samples of the dataset overlapping one another. Each sample was labeled as either “renal arterial flow”, “non-blood artifact”, or “noise”. Following training, the model was able to correctly classify renal arterial flow with 93% accuracy on a testing set of 2,467 samples.

[0087] In some examples, waveform analyzer 97 employs machine learning -based classifiers that not only provide a predicted class label but also provide an estimate of the confidence in the classification in terms of a probability of correct classification, as represented in FIG. 8 by flow quality grade / index 98. For example, in examples of waveform analyzer 97 employing a Random Forest classifier model, the proportion of trees voting for a particular classification may be interpreted as a confidence score ranging from 0 to 1. In examples of waveform analyzer 97 employing an SVM classifier, each of the SVM scores gives the distance of a sample to decision hyperplanes in feature space. Waveform analyzer 97 can use a logistic regression model to convert these SVM scores into probabilities for various binary classifications. Waveform analyzer 97 can use any other machine learning or classification algorithm that can produce a probability of correct classification.

[0088] In some examples, the classification of the organ blood flow signal as a blood flow signal, non-flow signal, or signal artifact and the flow quality grade / index 98 (the probability of correct classification of the organ blood flow signal) are used to establish a measurement uncertainty that is passed into predictive filter 47 being used by beamformer 46 and / or renal blood flow monitor 12 to track a target vessel location. In some examples the classifier is configured as a binary classifier that classifies the organ blood flow signal into “blood flow” and “not blood flow” along with an estimate of the probability that the classification is correct. A function maps the probability range [0,1] of the organ blood flow signal being blood flow to an uncertainty range | / ,0| where an uncertainty of » indicates complete certainty that the organ blood flow signal is not blood flow and an uncertainty of 0 indicates complete certainty that the organ blood flow signal is blood flow. In various examples the function mapping probability of correct classification to measurement uncertainty may be a rational polynomial function, a logit, a logarithm, or an exponential function or another function that maps from [0,1] to [oo,0].

[0089] Once the flow identification algorithm 48 of organ recognition module 33 has completed first step 96 of method 95 and has determined that the organ blood flow signal is a blood flow signal and not a non-flow signal or a signal artifact, method 95 proceeds to second step 100 which commences an organ identification phase where the organ blood flow signal is identified as being from portal vein flow, hepatic vein flow, or renal blood flow (renal artery flow and / or renal vein flow). In second step 100, organ recognition module 33 can instruct system processor 19 to execute transducer probe control module 30 and beamformer 46 (shown in FIGS. 1 and 2) to scan the organ blood flow signal with ultrasound transducer probe 14 for at least two cardiac cycles of patient 10. Patient 10 can perform a breath hold during second step 100 to ensure ultrasound transducer probe 14 maintains reception of the organ blood flow signal during the at least two cardiac cycles of patient 10. Alternatively, system processor 19 can command beamformer 46 and ultrasound transducer probe 14 to track the organ blood flow signal during the at least two cardiac cycles of patient 10 to ensure ultrasound transducer probe 14 maintains reception of the organ blood flow signal during the at least two cardiac cycles of patient 10. As transducer probe control module 30 and beamformer 46 scan the organ blood flow signal for the at least two cardiac cycles, system processor 19 can record the scan into a data segment and can save the data segment to system memory 12 of blood flow monitor 12. System processor 19 can use hemodynamic data communicated from hemodynamic pressure sensor 17 (shown in FIGS. 1 and 2) to measure the at least two cardiac cycles of patient 10 concurrently with the scan of the organ blood flow into the data segment and to determine when the data segment is complete. In other examples, system processor 19 can record the scan into the data segment for a time period known through clinical data sufficient to cover at least two cardiac cycles of patient 10.

[0090] In third step 102, system processor 19 executes organ recognition module 33 to process the data segment of the organ blood flow signal through a portal vein heuristic algorithm. The portal vein heuristic algorithm is one of heuristic algorithms 49 (shown in FIG. 2) of organ recognition module 33 and is configured to search the data segment of the organ blood flow signal to determine whether the data segment includes Doppler flow signal features indicative of a portal vein blood flow. The portal vein heuristic algorithm is discussed in greater detail below with reference to FIG. 9. After system processor 19 processes the data segment of the organ blood flow signal through the portal vein heuristic algorithm, the portal vein heuristic algorithm determines a portal vein score of the organ blood flow signal. The portal vein score represents a probability of the organ blood flow signal sensed by ultrasound transducer probe 14 being from a portal vein blood flow of patient 10. System processor 19 can save the portal vein score to system memory 20 of blood flow monitor 12.

[0091] In fourth step 104, system processor 19 executes organ recognition module 33 to process the data segment of the organ blood flow signal through a hepatic vein heuristic algorithm. The hepatic vein heuristic algorithm is one of heuristic algorithms 49 (shown in FIG. 2) of organ recognition module 33 and is configured to search the data segment of the organ blood flow signal to determine whether the data segment includes Doppler flow signal features indicative of a hepatic vein blood flow. The hepatic vein heuristic algorithm is discussed in greater detail below with reference to FIG. 10. After system processor 19 processes the data segment of the organ blood flow signal through the hepatic vein heuristic algorithm, the hepatic vein heuristic algorithm determines a hepatic vein score of the organ blood flow signal. The hepatic vein score represents a probability of the organ blood flow signal sensed by ultrasound transducer probe 14 being from a hepatic vein blood flow of patient 10. System processor 19 can save the hepatic vein score to system memory 20 of blood flow monitor 12.

[0092] In fifth step 106, system processor 19 executes organ recognition module 33 to process the data segment of the organ blood flow signal through a renal heuristic algorithm. The renal heuristic algorithm is one of heuristic algorithms 49 (shown in FIG. 2) of organ recognition module 33 that searches the data segment of the organ blood flow signal to determine whether the data segment includes Doppler flow signal features indicative of a renal artery blood flow and / or a renal vein blood flow. The renal heuristic algorithm is discussed in greater detail below with reference to FIGS. 11-13. After system processor 19 processes the data segment of the organ blood flow signal through the renal heuristic algorithm, the renal heuristic algorithm determines a renal blood flow score of the organ blood flow signal. The renal blood flow score represents a probability of the organ blood flow signal sensed by ultrasound transducer probe 14 being from a renal artery blood flow and / or a renal vein blood flow of patient 10. System processor 19 can save the renal blood flow score to system memory 20 of blood flow monitor 12.

[0093] System processor 19 can execute organ recognition module 33 to perform all of third step 102, fourth step 104, and fifth step 106 of method 95 concurrently. In other words, system processor 19 can execute organ recognition module 33 to process the data segment of the organ blood flow signal concurrently through the portal vein heuristic algorithm, the hepatic vein heuristic algorithm, and the renal heuristic algorithm. In other examples, system processor 19 can execute organ recognition module 33 to perform all of third step 102, fourth step 104, and fifth step 106 of method 95 consecutively.

[0094] In sixth step 108 of method 95, system processor 19 can execute organ recognition module 33 to compare the portal vein score, the hepatic vein score, and the renal blood flow score to determine whether the organ blood flow signal is from the portal vein flow, the hepatic vein blood flow, or from the renal blood flow of patient 10. Organ recognition module 33 can include a score threshold that must be exceeded by one of the portal vein score, the hepatic vein score, and the renal blood flow score to determine the identity of the organ blood flow signal. The score that exceeds the score threshold is selected as the identity determination score 37 of the organ blood flow signal by system processor 19 and is outputted to display 28.

[0095] If none of the portal vein score, the hepatic vein score, and the renal blood flow score exceeds the score threshold, system processor 19 can send an alert to display 28 of monitoring system 11 that the organ blood flow of the targeted organ was not found and can reinitiate the finding phase. If the organ blood flow of the targeted organ still cannot be found after the reinitiating the finding phase, system processor 19 can send an alert to display 28 indicating that ultrasound transducer probe 14 needs to be moved to another position on abdomen 40 of patient 10.

[0096] If one of the portal vein score, the hepatic vein score, and the renal blood flow score exceeds the score threshold but indicates that the organ blood flow signal is from a non-targeted organ, system processor 19 can send an alert to display 28 of monitoring system 11 that the organ blood flow of the targeted organ was not found and can reinitiate the finding phase. For example, if the renal blood flow of kidney 42R is being targeted for observation by monitoring system 1 1 , and ultrasound transducer probe 14 and blood flow monitor 12 have found an organ blood flow signal, but organ recognition module 33 has been executed and generates a hepatic vein score that exceeds the score threshold while renal blood flow score does not exceed the score threshold, system processor 19 can send an identity determination score 37 to display 28 indicating that the organ blood flow signal is a hepatic vein flow of patient 10 and an alert that the finding phase is reinitiating to find the renal blood flow.

[0097] Organ recognition module 33 can also generate organ quality grade 53 as part of identity determination score 37. Organ quality grade 53 can be a grade or index that indicates a confidence level of identity determination score 37. Organ quality grade 53 can indicate how much identity determination score 37 exceeds the score threshold and / or how much the identity determination score 37 exceeds those scores of the portal vein score, the hepatic vein score, and the renal blood flow score that did not exceed the score threshold. In seventh step 110 of method 95, system processor 19 can output identity determination score 37 and organ quality grade 53 to display 110, or a representation of identity determination score 37 and organ quality grade 53 to display 28. In examples where organ recognition module 33 determined that the organ blood flow signal is from the hepatic vein flow of patient 10, identity determination score 37 can state “Hepatic” on display 28 along with organ quality grade 53 indicating the confidence of identity determination score 37. In examples where organ recognition module 33 determined that the organ blood flow signal is from the portal vein flow of patient 10, identity determination score 37 can state “Portal” on display 28 along with organ quality grade 53 indicating the confidence of identity determination score 37. In examples where organ recognition module 33 determined that the organ blood flow signal is from the renal blood flow of patient 10, identity determination score 37 can state “Renal” on display 28 along with organ quality grade 53 indicating the confidence of identity determination score 37. In other examples, identity determination score 37 can use numerical indicators or acronyms. Organ quality grade 53 can be shown on display 28 as a numerical grade (such as a scale between 1 and 10), a percentage grade, as a verbal grade (such as “High Confidence” or “Adequate Confidence”), as a color grade, and / or a combination thereof. In other examples, system processor 10 can also output all three of the portal vein score, the hepatic vein score, and the renal blood flow score to display 28 so that a medical professional can directly compare the three scores.

[0098] Once system processor 19 has executed organ recognition module 33 and has outputted identity determination score 37 to display 28, the medical professional can choose to affix the ultrasound transducer probe 14 to abdomen 40 of patient 10 based on identity determination score 37, such that ultrasound transducer probe 14 is in a stationary position on abdomen 40. With ultrasound transducer probe 14 affixed to patient 10 based on identity determination score 37, system processor 19 can command beamformer 46 and ultrasound transducer probe 14 to track scan the organ blood flow signal to continuously sense the organ blood flow signal of the targeted organ during the surgery, medical procedure, or medical observation without an ultrasound operator having to be present throughout the surgery, medical procedure, or medical observation. FIG. 9 shows a simplified representation of portal vein heuristic algorithm 112 through plot 114 and block diagram 116. Plot 114 shows a data segment of a Doppler flow signal PV of a portal vein flow, with a y-axis representing velocity and an x-axis representing time. Positive velocity in plot 114 indicates flow toward ultrasound transducer probe 14 and negative velocity in plot 114 indicates flow away from ultrasound transducer probe 14. A cardiac cycle plot CC is overlayed on plot 114 to show correlation between the Doppler flow signal PV of the portal vein flow and the cardiac cycle plot CC. As shown in plot 1 14, the data segment of the Doppler flow signal PV recorded in plot 1 14 is at least two cardiac cycles in length. The data segment of the Doppler flow signal PV of the portal vein flow shown in plot 114 can be generated by ultrasound transducer probe 14 and organ recognition module 33 as described above with reference to FIGS. 6-8.

[0099] As shown in plot 1 14, the Doppler flow signal PV of the portal vein flow includes three significant features: first feature A, second feature B, and third feature C. First feature A of the Doppler flow signal PV of the portal vein flow is that the Doppler flow signal PV always has a positive velocity indicative of flow toward ultrasound transducer probe 14 and never has a negative velocity indicative of flow away from ultrasound transducer probe 14. Second feature B of the Doppler flow signal PV of the portal vein flow is that the Doppler flow signal PV may be pulsatile with a heartbeat of patient 10 with a sawtooth-shaped velocity profile with inclined segments and declined segments that are approximately symmetrical in length of time. Third feature C of the Doppler flow signal PV of the portal vein flow is that the inclined segments and the declined segments of the sawtooth-shaped velocity profile are approximately symmetrical in slope.

[0100] As shown in the block diagram 116, portal vein heuristic algorithm 112 includes four heuristics to analyze the data segment of plot 114 (and any other data segment inputted into portal vein heuristic algorithm 112 by system processor 19) and determine portal vein score 122: first portal heuristic 118, second portal heuristic 119, third portal heuristic 120, and fourth portal heuristic 121. First portal heuristic 118, second portal heuristic 119, third portal heuristic 120, and fourth portal heuristic 121 are coded logic steps of heuristic algorithm 112 that system process 19 can execute to rapidly process the data segment and determine portal vein score 122. In some examples, portal vein heuristic algorithm 112 can be complimented with a machine learning trained regression that places different weights on first portal heuristic 118, second portal heuristic 119, third portal heuristic 120, and fourth portal heuristic 121. Portal vein heuristic algorithm 112 can also be machine trained to recognize all of first portal heuristic 118, second portal heuristic 1 19, third portal heuristic 120, and fourth portal heuristic 121 simultaneously as a whole and in addition to additional heuristics and features. When system processor 19 executes first portal heuristic 118 of portal vein heuristic algorithm 112, first portal heuristic 118 analyzes the data segment for an organ blood flow signal that is always flowing toward ultrasound transducer probe 14, such as shown in first feature A of plot 114. If first portal heuristic 120 determines that a data segment does not include an organ blood flow signal that is always flowing toward ultrasound transducer probe 14, portal vein heuristic algorithm 112 can stop system processor from proceeding with second portal heuristic 1 19, third portal heuristic 120, and fourth portal heuristic 121, and can output a value for portal vein score 122 that indicates a very low probability that the data segment contains a Doppler flow signal PV from a portal vein flow. If first portal heuristic 118 determines that the data segment does include an organ blood flow signal that is always flowing toward ultrasound transducer probe 14, portal vein heuristic algorithm 112 can proceed with processing the data segment through second portal heuristic 119, third portal heuristic 120, and fourth portal heuristic 121.

[0101] When system processor 19 executes second portal heuristic 119 of portal vein heuristic algorithm 112, second portal heuristic 119 analyzes the data segment to determine whether the organ blood flow signal is pulsatile with each heartbeat of cardiac cycle CC, such as shown in second feature B of plot 114. If second portal heuristic 119 determines that the organ blood flow signal in the data segment is not pulsatile, portal vein heuristic algorithm 112 can stop system processor from proceeding with third portal heuristic 120 and fourth portal heuristic 121, and can output a value for portal vein score 122 that indicates a relatively low confidence that the data segment contains a Doppler flow signal PV from the portal vein flow. If second portal heuristic 119 determines that the organ blood flow in the data segment includes pulsatility with the heartbeat of patient 10, portal vein heuristic algorithm 112 can proceed with processing the data segment through third portal heuristic 120 and fourth portal heuristic 121.

[0102] When system processor 19 executes third portal heuristic 120 of portal vein heuristic algorithm 112, third portal heuristic 120 analyzes the organ blood flow signal of the data segment for a sawtooth-shaped velocity profile, such as shown in second feature B of plot 114. If third portal heuristic 120 determines that the organ blood flow signal in the data segment does not include a sawtooth-shaped velocity profile, portal vein heuristic algorithm 112 can stop system processor from proceeding with fourth portal heuristic 121, and can output a value for portal vein score 122 that indicates a relatively low confidence that the data segment contains a Doppler flow signal PV from the portal vein flow. If third portal heuristic 120 determines that the organ blood flow in the data segment includes a sawtooth-shaped velocity profile, portal vein heuristic algorithm 112 can proceed with processing the data segment through fourth portal heuristic 121.

[0103] Fourth portal heuristic 121, when executed by system processor 19, analyzes the sawtooth-shaped velocity profile for inclined segments and declined segments that are approximately symmetrical in slope and length of time, such as shown in second feature B and third feature C of plot 1 14. If fourth portal heuristic 121 determines that the sawtoothshaped velocity profile of the organ blood flow signal in the data segment does not include inclined segments and declined segments that are approximately symmetrical in slope and length of time, portal vein heuristic algorithm 112 can output a value for portal vein score 122 that indicates the data segment might possibly contain a Doppler flow signal PV from the portal vein flow. If fourth portal heuristic 121 determines that the that the sawtoothshaped velocity profile of the organ blood flow signal in the data segment does include inclined segments and declined segments that are approximately symmetrical in slope and length of time, portal vein heuristic algorithm 112 can output a value for portal vein score 122 indicating with high certainty that the organ blood flow signal in the data segment is from the portal vein blood flow.

[0104] FIG. 10 shows a simplified representation of hepatic vein heuristic algorithm 124 through plot 126 and block diagram 128. Plot 126 shows a data segment of a Doppler flow signal HV of a hepatic vein flow, with a y-axis representing velocity and an x-axis representing time. Positive velocity in plot 126 indicates flow toward ultrasound transducer probe 14 and negative velocity in plot 126 indicates flow away from ultrasound transducer probe 14. A cardiac cycle plot CC is overlayed on plot 126 to show correlation between the Doppler flow signal HV of the hepatic vein flow and the cardiac cycle plot CC. As shown in plot 126, the data segment of the Doppler flow signal HV recorded in plot 126 is at least two cardiac cycles in length. The data segment of the Doppler flow signal HV of the hepatic vein flow shown in plot 126 can be generated by ultrasound transducer probe 14 and organ recognition module 33 as described above with reference to FIGS. 6-8.

[0105] As shown in plot 126, the Doppler flow signal HV of the hepatic vein flow includes four significant features: first feature D, second feature E, third feature F, and fourth feature G. First feature D of the Doppler flow signal HV of the hepatic vein flow is that the Doppler flow signal HV is always pulsatile with a heartbeat of patient 10. Second feature E of the Doppler flow signal HV of the hepatic vein flow is that the flow direction of the Doppler flow signal HV reverses direction within each heartbeat of patient 10 (i.e., the Doppler flow signal HV shows flow toward and away from ultrasound transducer probe 14 during each heartbeat). Third feature F of the Doppler flow signal HV of the hepatic vein flow is that a larger portion of the Doppler flow signal HV has a flow direction away from ultrasound transducer probe 14 (i.e., a larger flow velocity, time, and volume away from ultrasound transducer probe 14). Fourth feature G of the Doppler flow signal HV of the hepatic vein flow is that a smaller portion of the Doppler flow signal HV has a flow direction toward ultrasound transducer probe 14 (i.e., a smaller flow velocity, time, and volume toward ultrasound transducer probe 14).

[0106] As shown in the block diagram 128, hepatic vein heuristic algorithm 124 includes four heuristics to analyze the data segment of plot 126 (and any other data segment inputted into hepatic vein heuristic algorithm 124 by system processor 19) and determine hepatic vein score 135: first hepatic heuristic 130, second hepatic heuristic 131, third hepatic heuristic 132, and fourth hepatic heuristic 134. First hepatic heuristic 130, second hepatic heuristic 131, third hepatic heuristic 132, and fourth hepatic heuristic 134 are coded logic steps of heuristic algorithm 1 12 that system process 19 can execute to rapidly process the data segment and determine hepatic vein score 135. In some examples, hepatic vein heuristic algorithm 124 can be complimented with a machine learning trained regression that places different weights on first hepatic heuristic 130, second hepatic heuristic 131, third hepatic heuristic 132, and fourth hepatic heuristic 134. Hepatic vein heuristic algorithm 124 can also be machine trained to recognize all of first hepatic heuristic 130, second hepatic heuristic 131, third hepatic heuristic 132, and fourth hepatic heuristic 134 simultaneously as a whole and in addition to additional heuristics and features.

[0107] When system processor 19 executes first hepatic heuristic 130 of hepatic vein heuristic algorithm 124, first hepatic heuristic 130 analyzes the data segment for an organ blood flow signal that is always pulsatile with a heartbeat of patient 10, such as shown in first feature D of plot 126. If first hepatic heuristic 120 determines that a data segment does not include an organ blood flow signal that is always pulsatile with the heartbeat of patient 10, hepatic vein heuristic algorithm 124 can stop system processor from proceeding with second hepatic heuristic 131, third hepatic heuristic 132, and fourth hepatic heuristic 134, and can output a value for hepatic vein score 135 that indicates a very low probability that the data segment contains a Doppler flow signal HV from a hepatic vein flow. If first hepatic heuristic 130 determines that the data segment does include an organ blood flow signal that is always pulsatile with the heartbeat of patient 10, hepatic vein heuristic algorithm 124 can proceed with processing the data segment through second hepatic heuristic 131, third hepatic heuristic 132, and fourth hepatic heuristic 134.

[0108] When system processor 19 executes second hepatic heuristic 131 of hepatic vein heuristic algorithm 124, second hepatic heuristic 131 analyzes the data segment to determine whether the organ blood flow signal includes a flow direction reversal in the organ blood flow signal relative to ultrasound transducer probe 14 during each heartbeat of patient 10, such as shown in second feature E of plot 126. If second hepatic heuristic 131 determines that the organ blood flow signal in the data segment does not include a flow direction reversal in the organ blood flow signal relative to ultrasound transducer probe 14 during each heartbeat of patient 10, hepatic vein heuristic algorithm 124 can stop system processor 19 from proceeding with third hepatic heuristic 132 and fourth hepatic heuristic 134, and can output a value for hepatic vein score 135 that indicates that the data segment does not contain a Doppler flow signal HV from the hepatic vein flow. If second hepatic heuristic 131 determines that the organ blood flow in the data segment does include a flow direction reversal in the organ blood flow signal relative to ultrasound transducer probe 14 during each heartbeat of patient 10, hepatic vein heuristic algorithm 124 can proceed with processing the data segment through third hepatic heuristic 132 and fourth hepatic heuristic 134.

[0109] When system processor 19 executes third hepatic heuristic 132 of hepatic vein heuristic algorithm 124, third hepatic heuristic 132 analyzes the flow direction reversal of the organ blood flow signal for non-symmetry in time, velocity, and volume within a cardiac cycle of patient 10, such as shown in third feature F and fourth feature G of plot 126. If third hepatic heuristic 132 determines that the flow direction reversal of the organ blood flow signal does not include non-symmetry in time, velocity, and volume within a cardiac cycle of patient 10, hepatic vein heuristic algorithm 124 can stop system processor from proceeding with fourth hepatic heuristic 134, and can output a value for hepatic vein score 135 that indicates that the data segment does not contain a Doppler flow signal HV from the hepatic vein flow. If third hepatic heuristic 132 determines that the flow direction reversal of the organ blood flow signal does include non-symmetry in time, velocity, and volume within a cardiac cycle of patient 10, hepatic vein heuristic algorithm 124 can proceed with processing the data segment through fourth hepatic heuristic 134.

[0110] Fourth hepatic heuristic 134, when executed by system processor 19, analyzes the organ blood flow signal in the data segment for more flow volume and flow velocity away from the ultrasound transducer probe than toward the ultrasound transducer probe within each cardiac cycle of patient 10, such as shown in third feature F and fourth feature G of plot 126. If fourth hepatic heuristic 134 determines that the organ blood flow signal in the data segment does not include more flow volume and flow velocity away from the ultrasound transducer probe than toward the ultrasound transducer probe within each cardiac cycle of patient 10, hepatic vein heuristic algorithm 124 can output a value for hepatic vein score 135 that indicates a very low confidence that the data segment contains a Doppler flow signal HV from the hepatic vein flow. If fourth hepatic heuristic 134 determines that the organ blood flow signal in the data segment does include more flow volume and flow velocity away from the ultrasound transducer probe than toward the ultrasound transducer probe within each cardiac cycle of patient 10, hepatic vein heuristic algorithm 124 can output a value for hepatic vein score 135 indicating with high certainty that the organ blood flow signal in the data segment is from the hepatic vein blood flow.

[0111] FIG. 11 shows a simplified representation of renal heuristic algorithm 136 through plot 138 and block diagram 140. Due to the proximity of the renal artery to the renal vein, both the renal artery and the renal vein can be present under the field of view ultrasound transducer probe 14 at the same time and can be sensed by ultrasound transducer probe 14 at the same time by the same beam / voxel. Plot 138 shows a data segment of both a Doppler flow signal RV of a renal vein flow and a Doppler flow signal RA of a renal artery flow, with a y-axis representing velocity and an x-axis representing time. Positive velocity in plot 138 indicates flow toward ultrasound transducer probe 14 and negative velocity in plot 138 indicates flow away from ultrasound transducer probe 14. A cardiac cycle plot CC is overlay ed on plot 138 to show correlation between the cardiac cycle plot CC and both the Doppler flow signal RV of the renal vein flow and the Doppler flow signal RA of the renal artery flow. As shown in plot 138, the data segment containing both the Doppler flow signal RV of the renal vein flow and the Doppler flow signal RA of the renal artery flow is at least two cardiac cycles in length. The data segment of the Doppler flow signal HV of the hepatic vein flow shown in plot 138 can be generated by ultrasound transducer probe 14 and organ recognition module 33 as described above with reference to FIGS. 6-8.

[0112] As shown in plot 138, the Doppler flow signal RV of the renal vein flow and the Doppler flow signal RA of the renal artery flow together include four significant features: first feature H, second feature I, third feature J, and fourth feature K. First feature H of plot 138 is that the Doppler flow signal RA of the renal artery flow has a flow direction that is always toward ultrasound transducer probe 14, the Doppler flow signal RV has a flow direction that is always away from ultrasound transducer probe 14, and that the Doppler flow signal RV is always lower in flow velocity than the Doppler flow signal RA. Second feature I of plot 138 is that the Doppler flow signal RA of the renal artery flow is pulsatile with the heartbeat of patient 10 and has a higher flow velocity than the Doppler flow signal RV of the renal vein. Third feature J of plot 138 is that the Doppler flow signal RV of the renal vein may or may not be pulsatile and is always lower in flow velocity than the Doppler flow signal RA of the renal artery for any given point of time within the data segment. Fourth feature K of plot 138 is that the Doppler flow signal RA of the renal artery flow has a velocity profile that is biphasic with a pulse segment (associated with a systole of the cardiac cycle CC) followed in time by a steady segment (associated with a diastole of the cardiac cycle CC), the pulse segment being higher in velocity than the steady, the pulse segment being shorter in time than the steady segment, and the steady segment decreasing in velocity with time.

[0113] As shown in the block diagram 140, renal heuristic algorithm 136 includes five heuristics to analyze the data segment of plot 138 (and any other data segment inputted into renal heuristic algorithm 136 by system processor 19) and determine renal blood flow score 146: first renal heuristic 141, second renal heuristic 142, third renal heuristic 143, fourth renal heuristic 144, and fifth renal heuristic 145. First renal heuristic 141, second renal heuristic 142, third renal heuristic 143, fourth renal heuristic 144, and fifth renal heuristic 145 are coded logic steps of heuristic algorithm 112 that system process 19 can execute to rapidly process the data segment and determine renal blood flow score 146. In some examples, renal heuristic algorithm 136 can be complimented with a machine learning trained regression that places different weights on first renal heuristic 141, second renal heuristic 142, third renal heuristic 143, fourth renal heuristic 144, and fifth renal heuristic 145. Renal heuristic algorithm 136 can also be machine trained to recognize all of first renal heuristic 141 , second renal heuristic 142, third renal heuristic 143, fourth renal heuristic 144, and fifth renal heuristic 145 simultaneously as a whole and in addition to additional heuristics and features. When system processor 19 executes first renal heuristic 141 of renal heuristic algorithm 136, first renal heuristic 141 analyzes the data segment for a first organ blood flow signal with a flow direction that is always toward ultrasound transducer probe 14, such as shown in first feature H of plot 138. If first hepatic heuristic 120 determines that a data segment does not include a first organ blood flow signal with a flow direction that is always toward ultrasound transducer probe 14, renal heuristic algorithm 136 can stop system processor from proceeding with second renal heuristic 142, third renal heuristic 143, fourth renal heuristic 144, and fifth renal heuristic 145, and can output a value for renal blood flow score 146 that indicates a very low probability that the data segment contains a Doppler flow signal RA from a renal artery flow. If first renal heuristic 141 determines that the data segment does include a first organ blood flow signal with a flow direction that is always toward ultrasound transducer probe 14, renal heuristic algorithm 136 can proceed with processing the data segment through second renal heuristic

[0114] 142, third renal heuristic 143, fourth renal heuristic 144, and fifth renal heuristic 145.

[0115] When system processor 19 executes second renal heuristic 142 of renal heuristic algorithm 136, second renal heuristic 142 analyzes the data segment to determine whether the first organ blood flow signal in the data segment is always pulsatile with the heartbeat of patient 10, such as shown in second feature I of plot 138. If second renal heuristic 142 determines that the first organ blood flow signal in the data segment is not always pulsatile with the heartbeat of patient 10, renal heuristic algorithm 136 can stop system processor 19 from proceeding with third renal heuristic 143, fourth renal heuristic 144, and fifth renal heuristic 145, and can output a value for renal blood flow score 146 that indicates that the data segment does not contain a Doppler flow signal RA from the renal artery flow. If second renal heuristic 142 determines that the first organ blood flow signal in the data segment is always pulsatile with the heartbeat of patient 10, renal heuristic algorithm 136 can proceed with processing the data segment through third renal heuristic

[0116] 143, fourth renal heuristic 144, and fifth renal heuristic 145.

[0117] When system processor 19 executes third renal heuristic 143 of renal heuristic algorithm 136, third renal heuristic 143 analyzes the first organ blood flow signal in the data segment for a velocity profile that is biphasic with a pulse segment followed in time by a steady segment, the pulse segment being higher in velocity than the steady segment, the pulse segment being shorter in time than the steady segment, and the steady segment decreasing in velocity with time, such as shown in fourth feature K of plot 138. If third renal heuristic 143 determines that the first organ blood flow signal in the data segment does not include a velocity profile that is biphasic with a pulse segment followed in time by a steady segment, the pulse segment being higher in velocity than the steady segment, the pulse segment being shorter in time than the steady segment, and the steady segment decreasing in velocity with time, renal heuristic algorithm 136 can stop system processor 19 from proceeding with fourth renal heuristic 144 and fifth renal heuristic 145, and can output a value for renal blood flow score 146 that indicates that the data segment does not contain a Doppler flow signal RA from the renal artery flow. If third renal heuristic 143 determines that the first organ blood flow signal in the data segment does include a velocity profile that is biphasic with a pulse segment followed in time by a steady segment, the pulse segment being higher in velocity than the steady segment, the pulse segment being shorter in time than the steady segment, and the steady segment decreasing in velocity with time, renal heuristic algorithm 136 can output a value for renal blood flow score 146 that indicates with high confidence that the data segment does contain a Doppler flow signal RA from the renal artery flow, and can proceed with processing the data segment through fourth renal heuristic 144 and fifth renal heuristic 145.

[0118] Fourth renal heuristic 144, when executed by system processor 19, analyzes the data segment for the presence of a second organ blood flow signal within 1cm to 2cm of the first organ blood flow signal, such as shown in first feature H of plot 138. If fourth renal heuristic 144 determines that the data segment does not include a second organ blood flow signal within 1cm to 2cm of the first organ blood flow signal, renal heuristic algorithm 136 can output a value for renal blood flow score 146 that indicates a very low confidence that the data segment contains a Doppler flow signal RV from the renal vein flow. If fourth renal heuristic 144 determines that the data segment does include a second organ blood flow signal within 1cm to 2cm of the first organ blood flow signal, renal heuristic algorithm 136 can proceed with processing the data segment through fifth renal heuristic 145.

[0119] Fifth renal heuristic 145, when executed by system processor 19, analyzes the second organ blood flow signal in the data segment to determine whether the second organ blood flow signal includes a flow direction that is always away from ultrasound transducer probe 14, such as shown in first feature H of plot 138. If fifth renal heuristic 145 determines that the second organ blood flow signal does not include a flow direction that is always away from ultrasound transducer probe 14, renal heuristic algorithm 136 can output a value for renal blood flow score 146 that indicates a very low confidence that the data segment contains a Doppler flow signal RV from the renal vein flow. If fifth renal heuristic 145 determines that the second organ blood flow signal does include a flow direction that is always away from ultrasound transducer probe 14, renal heuristic algorithm 136 can output a value for renal blood flow score 146 indicating with high confidence that the data segment does contain a Doppler flow signal RV from the renal vein flow.

[0120] In some examples, renal heuristic algorithm 136 can analyze an organ blood flow signal for renal artery flow separate from renal vein flow. FIG. 12 shows an example of renal heuristic algorithm 136 where the organ blood flow signal is only being analyzed by first renal heuristic 141, second renal heuristic 142, and third renal heuristic 143 to determine whether organ blood flow signal is from a renal artery flow. FIG. 13 shows an example of renal heuristic algorithm 136 where the organ blood flow signal is only being analyzed by fifth renal heuristic 145 to determine whether organ blood flow signal is from a renal vein flow.

[0121] In the examples of FIGS. 1-13, monitoring system 11 is described as using ultrasound transducer probe 14 to perform a series of two-dimensional scans on abdomen 40 of patient 10 to find, identify, and track the Doppler flow signal of an organ blood flow. In other examples, as discussed below with reference to FIG. 14, ultrasound transducer probe 14 and blood flow monitor 12 can perform a three-dimensional scan of abdomen 40 to find, identify, track, and monitor Doppler flow signals of multiple organ blood flows in abdomen 40. Alternatively, ultrasound transducer probe 14 and blood flow monitor 12 can perform a three-dimensional scan of abdomen 40 to find and identify Doppler flow signals of multiple organ blood flows in abdomen 40, and then select one of the Doppler flow signals of the multiple organ blood flows for tracking and monitoring.

[0122] FIG. 14 is a block diagram of method 148 for finding multiple organ blood flow signals in abdomen 40 and verifying the identity of each organ blood flow signal through organ recognition module 33. In the example of FIG. 14, each organ blood flow signal of the multiple organ blood flow signals is a Doppler flow signal sensed by ultrasound transducer probe 14 and suspected as being a blood flow signal of an organ in abdomen 40.

[0123] In first step 150 of method 148, system processor 19 can execute transducer probe control module 30 to three-dimensionally scan patient 10 with ultrasound transducer probe 14 to sense multiple organ blood flow signals (or what possibly could be multiple organ blood flow signals) in a volume within abdomen 40 under a field of view of ultrasound transducer probe 14. In second step 152 of method 148, system processor 19 can execute organ recognition module 33 to process each organ blood flow signal of the multiple organ blood flow signals sensed by ultrasound transducer probe 14 through the flow identification algorithm 48. As discussed above with reference to FIG. 8, the flow identification algorithm 48 is an algorithm that can identify an organ blood flow signal from non-flow signals and signal artifacts in abdomen 40 of patient 10. The description of flow identification algorithm 48 provided in reference to FIG. 8 can also apply to the flow identification algorithm 48 discussed here with reference to FIG. 14. However, in the example of FIG. 14, system processor 19 is executing flow identification algorithm 48 to analyze multiple possible organ blood flow signals in the same volume as opposed to a single organ blood flow signal. System processor 19 can process the multiple possible organ blood flow signals through flow identification algorithm 48 concurrently or consecutively. As flow identification algorithm 48 processes each possible organ blood flow signal, the flow identification algorithm 48 can classify whether the sensed organ blood flow signal is actually from an organ blood flow, is a non-flow signal, or is a signal artifact. Along with classifying each possible organ blood flow signal of the multiple sensed by ultrasound transducer probe 14, flow identification algorithm 48 can also determine the flow quality grade / index 98 (the probability of correct classification) for each of multiple possible organ blood flow signals. The flow quality grade / index 98 is described above in greater detail with reference to FIG. 8.

[0124] After flow identification algorithm 48 of organ recognition module 33 has completed second step 152 of method 148 and has determined which signals being sensed by ultrasound transducer probe 14 are actually organ blood flow signals not a non-flow signal or a signal artifact, method 148 proceeds to third step 154 which commences an organ identification phase where each of the organ blood flow signals is identified as being from portal vein flow, hepatic vein flow, or renal blood flow (renal artery flow and / or renal vein flow). In third step 154, organ recognition module 33 can instruct system processor 19 to execute transducer probe control module 30 and beamformer 46 (shown in FIGS. 1 and 2) to scan each of the organ blood flow signals with ultrasound transducer probe 14 for at least two cardiac cycles of patient 10. Patient 10 can perform a breath hold during second step 100 to ensure ultrasound transducer probe 14 maintains reception of each of the organ blood flow signals during the at least two cardiac cycles of patient 10. Alternatively, system processor 19 can command beamformer 46 and ultrasound transducer probe 14 to track each of the organ blood flow signals during the at least two cardiac cycles of patient 10 to ensure ultrasound transducer probe 14 maintains reception of the organ blood flow signals during the at least two cardiac cycles of patient 10. As transducer probe control module 30 and beamformer 46 scan each of the organ blood flow signals for the at least two cardiac cycles, system processor 19 can record each scan into a data segment and can save each data segment to system memory 12 of blood flow monitor 12. System processor 19 can use hemodynamic data communicated from hemodynamic pressure sensor 17 (shown in FIGS. 1 and 2) to measure the at least two cardiac cycles of patient 10 concurrently with the scan of the organ blood flow signals into the data segments and to determine when the data segments are complete. In other examples, system processor 19 can record each scan into a data segment for a time period known through clinical data sufficient to cover at least two cardiac cycles of patient 10.

[0125] In fourth step 156, system processor 19 executes organ recognition module 33 to process each of the data segments of the organ blood flow signals through the portal vein heuristic algorithm 112. The portal vein heuristic algorithm 112 is discussed in greater detail above with reference to FIG. 9. After system processor 19 processes each data segment of the organ blood flow signals through the portal vein heuristic algorithm 112, the portal vein heuristic algorithm 112 determines the portal vein score 122 for each of the organ blood flow signals. The portal vein score 122 represents a probability of an organ blood flow signal sensed by ultrasound transducer probe 14 being from a portal vein blood flow of patient 10. System processor 19 can save each of the portal vein scores 122 to system memory 20 of blood flow monitor 12.

[0126] In fifth step 158, system processor 19 executes organ recognition module 33 to process each of the data segments of the organ blood flow signals through the hepatic vein heuristic algorithm 124. The hepatic vein heuristic algorithm 124 is discussed in greater detail above with reference to FIG. 10. After system processor 19 processes each of the data segments of the organ blood flow signals through the hepatic vein heuristic algorithm 124, the hepatic vein heuristic algorithm 124 determines the hepatic vein score 135 for each of the organ blood flow signals. The hepatic vein score 135 represents a probability of the organ blood flow signal sensed by ultrasound transducer probe 14 being from a hepatic vein blood flow of patient 10. System processor 19 can save each of the hepatic vein scores 135 to system memory 20 of blood flow monitor 12.

[0127] In sixth step 160, system processor 19 executes organ recognition module 33 to process each of the data segments of the organ blood flow signals through the renal heuristic algorithm 136. The renal heuristic algorithm 136 is discussed in greater detail above with reference to FIGS. 11-13. After system processor 19 processes each of the data segments of the organ blood flow signals through the renal heuristic algorithm 136, the renal heuristic algorithm 136 determines the renal blood flow score 146 for each of the organ blood flow signals. The renal blood flow score 146 represents a probability of an organ blood flow signal sensed by ultrasound transducer probe 14 being from a renal artery blood flow and / or a renal vein blood flow of patient 10. System processor 19 can save each of the renal blood flow scores 146 to system memory 20 of blood flow monitor 12.

[0128] System processor 19 can execute organ recognition module 33 to perform all of fourth step 156, fifth step 158, and sixth step 160 of method 148 concurrently. In other words, system processor 19 can execute organ recognition module 33 to process all of the respective data segments of the organ blood flow signals concurrently through the portal vein heuristic algorithm 112, the hepatic vein heuristic algorithm 124, and the renal heuristic algorithm 136. In other examples, system processor 19 can execute organ recognition module 33 to perform all of fourth step 156, fifth step 158, and sixth step 160 of method 148 consecutively.

[0129] In seventh step 162 of method 148, system processor 19 can execute organ recognition module 33 to compare the portal vein score 122, the hepatic vein score 135, and the renal blood flow score 146 for each of the organ blood flow signals to determine for each of the organ blood flow signals if that organ blood flow signal is from the portal vein flow, the hepatic vein blood flow, or from the renal blood flow of patient 10. Organ recognition module 33 can include a score threshold that must be exceeded by one of the portal vein score 122, the hepatic vein score 135, and the renal blood flow score 146 to determine the identity of that organ blood flow signal. The score that exceeds the score threshold is selected as the identity determination score 37 of that organ blood flow signal by system processor 19 and is outputted to display 28. The identity determination score 37 of each of the organ blood flow signals can be outputted to display 28. Organ recognition module 33 can also generate organ quality grade 53 as part of the identity determination score 37 for each of the organ blood flow signals. Organ quality grade 53 is described above in detail with reference to FIG. 8.

[0130] Once system processor 19 has executed organ recognition module 33 and has outputted the identity determination scores 37 to display 28 for each of the organ blood flow signals, the medical professional can choose to affix the ultrasound transducer probe 14 to abdomen 40 of patient 10 based on the identity determination scores 37, such that ultrasound transducer probe 14 is in a stationary position on abdomen 40. With ultrasound transducer probe 14 affixed to patient 10 based on the identity determination scores 37 of the organ blood flow signals, system processor 19 can command beamformer 46 and ultrasound transducer probe 14 to track scan those organ blood flow signals that the medical professional desires monitoring system 11 to continuously sense and monitor during the surgery, medical procedure, or medical observation without an ultrasound operator having to be present throughout the surgery, medical procedure, or medical observation.

[0131] Discussion of Possible Embodiments

[0132] The following are non-exclusive descriptions of possible examples of the present invention. In one example of the disclosure, a method for monitoring an organ blood flow of a patient is disclosed. The method includes performing a finding phase. The finding phase includes scanning, by an ultrasound transducer probe and a beamformer driving the ultrasound transducer probe, a volume within an abdomen of the patient under a field of view of the ultrasound transducer probe. The finding phase also includes detecting, by a processor in communication with the ultrasound transducer probe and the beamformer, a Doppler flow signal of the organ blood flow. The method also includes performing an organ identification phase. The organ identification phase includes scanning a data segment, by the ultrasound transducer probe, the beamformer, and the processor, of the Doppler flow signal for at least two cardiac cycles of the patient. The data segment is processed by the processor through a portal vein heuristic algorithm to determine a portal vein score of the Doppler flow signal. The data segment is also processed by the processor through a hepatic vein heuristic algorithm to determine a hepatic vein score of the Doppler flow signal. The processor also processes the data segment through a renal heuristic algorithm to determine a renal blood flow score of the Doppler flow signal. The Doppler flow signal is identified by the processor as a portal vein flow, as a renal blood flow, or as a hepatic vein flow of the patient based on the portal vein score, the hepatic vein score, and the renal artery score. The ultrasound transducer probe is affixed on the abdomen of the patient with an adhesive patch based on the portal vein score, the hepatic vein score, or the renal artery score. The processor commands the beamformer and the ultrasound transducer probe to track scan the Doppler flow signal based on the portal vein score, the hepatic vein score, or the renal artery score. The Doppler flow signal is track-scanned by the beamformer and the ultrasound transducer probe to continuously sense the Doppler flow signal of the organ blood flow of the patient during a surgery, medical procedure, or medical observation without an ultrasound operator.

[0133] The method of the preceding paragraph can optionally include, additionally and / or alternatively, any one or more of the following features, configurations and / or additional components in the paragraphs below.

[0134] In an embodiment of the foregoing method, the processor processes the data segment concurrently through the portal vein heuristic algorithm, the hepatic vein heuristic algorithm, and the renal heuristic algorithm.

[0135] In an embodiment of the foregoing method, processing, by the processor, the data segment through the hepatic vein heuristic algorithm to determine the hepatic vein score of the Doppler flow signal comprises: determining, by the processor, whether the data segment of the Doppler flow signal is always pulsatile with a heartbeat of the patient; determining, by the processor, whether the data segment of the Doppler flow signal shows flow direction reversal in the organ blood flow relative to the ultrasound transducer probe during each heartbeat of the patient recorded in the data segment; determining, by the processor, whether the data segment of the Doppler flow signal shows the flow direction reversal as nonsymmetrical in time, velocity, or volume; and determining, by the processor whether the data segment of the Doppler flow signal shows more flow volume and flow velocity of the organ blood flow away from the ultrasound transducer probe than toward the ultrasound transducer probe.

[0136] In an embodiment of the foregoing method, processing, by the processor, the data segment through the portal vein heuristic algorithm to determine the portal vein score of the Doppler flow signal comprises: determining, by the processor, whether the data segment of the Doppler flow signal shows the organ blood flow always flowing toward the ultrasound transducer probe; determining, by the processor, whether the data segment of the Doppler flow signal shows the organ blood flow to be pulsatile with the heartbeat of the patient; and determining, by the processor, whether the data segment of the Doppler flow signal shows the organ blood flow as having pulsatility with a sawtooth-shaped velocity profile with inclined segments and declined segments that are approximately symmetrical in slope and time.

[0137] In an embodiment of the foregoing method, processing, by the processor, the data segment through the renal heuristic algorithm to determine the renal blood flow score of the Doppler flow signal comprises: determining, by the processor, whether the data segment of the Doppler flow signal includes a first organ blood flow signal with a flow direction that is always toward the ultrasound transducer probe; determining, by the processor, whether the first organ blood flow signal in the data segment is always pulsatile with the heartbeat of the patient; and determining, by the processor, whether the first organ blood flow signal in the data segment includes a velocity profile that is biphasic with a pulse segment followed in time by a steady segment, wherein the pulse segment is higher in velocity than the steady segment, the pulse segment is shorter in time than the steady segment, and the steady segment decreases in velocity with time.

[0138] In an embodiment of the foregoing method, processing, by the processor, the data segment through the renal heuristic algorithm to determine the renal blood flow score of the Doppler flow signal comprises: determining, by the processor, whether the data segment of the Doppler flow signal includes a second organ blood flow signal; and determining, by the processor, whether the second organ blood flow signal of the Doppler flow signal in the data segment includes a flow direction that is always away from the ultrasound transducer probe.

[0139] In an embodiment of the foregoing method, the method further comprises: outputting, by the processor, a plot of the data segment of the Doppler flow signal and to a display in communication with the processor; outputting, by the processor, the hepatic vein score, the portal vein score, and / or the renal blood flow score to the display; and outputting, by the processor, an identity determination score that indicates on the display that the Doppler flow signal is from the portal vein flow, the renal blood flow, or the hepatic vein flow of the patient.

[0140] In an embodiment of the foregoing method, the method further comprises: determining, by the processor, a first quality grade / index that indicates a probability of the Doppler flow signal being from the portal vein flow, the renal blood flow, or the hepatic vein flow of the patient; and outputting to the display the quality grade / index.

[0141] In an embodiment of the foregoing method, the method further comprises: sensing the at least two cardiac cycles of the patient with a hemodynamic sensor connected to the patient and in electrical communication with the processor concurrently with the ultrasound transducer probe, the beamformer, and the processor scanning the data segment of the Doppler flow signal.

[0142] In an embodiment of the foregoing method, track-scanning the Doppler flow signal of the organ blood flow of the patient by the beamformer and the ultrasound transducer probe comprises: emitting a set of sequential beams from an array of transducer elements of the ultrasound transducer probe to track a center of the organ blood flow relative to the array of transducer elements; focusing each beam from the set of beams in different locations; and adjusting the position of the set of beams onto the center of the organ blood flow by the beamformer to maintain the Doppler flow signal of the organ blood flow of the patient.

[0143] In an embodiment of the foregoing method, track-scanning the Doppler flow signal of the organ blood flow of the patient by the beamformer and the ultrasound transducer probe comprises: measuring estimates of a location of the organ blood flow by the beamformer; inputting the estimates of the location of the organ blood flow into a predictive filter; and determining an expected trajectory of the location of the organ blood flow based on the estimates of the location of the organ blood flow and based on a breathing frequency of the patient. In an embodiment of the foregoing method, the method further comprises: determining, by the processor, a second quality grade / index that indicates a probability of the Doppler flow signal being from the organ blood flow versus noise, artifacts, or other physiologically irrelevant blood flow signals in the abdomen of the patient; and continuously communicating the second quality grade / index as an input into the predictive filter during the operation, medical procedure, or medical observation.

[0144] In an embodiment of the foregoing method, the method further comprises: measuring the breathing frequency of the patient with a breathing monitor connected to the patient and in communication with the processor; and inputting the breathing frequency of the patient into the predictive filter from the breathing monitor.

[0145] In an embodiment of the foregoing method, the predictive filter comprises a Kalman Filter.

[0146] In an embodiment of the foregoing method, the method further comprises: repeating the finding phase if a signature of interest of the Doppler flow signal falls below a preset threshold, criterium, criteria, and / or heuristic while track-scanning the Doppler flow signal; and repeating the organ identification phase after repeating the finding phase.

[0147] In another example of the disclosure, a method is disclosed for monitoring a patient during a surgery, medical procedure, or medical observation. The method includes performing a finding phase. The finding phase includes scanning three- dimensionally, by an ultrasound transducer probe and a beamformer driving the ultrasound transducer probe, a volume within an abdomen of the patient under a field of view of the ultrasound transducer probe. The finding phase also includes detecting, by a processor in communication with the ultrasound transducer probe and the beamformer, a first Doppler flow signal of the organ blood flow. The finding phase also includes detecting, by the processor, a second Doppler flow signal of the organ blood flow. The method also includes performing an organ identification phase. The organ identification phase includes scanning a first data segment, by the ultrasound transducer probe, the beamformer, and the processor, of the first Doppler flow signal for at least two cardiac cycles of the patient. A second data segment is also scanned by the ultrasound transducer probe, the beamformer, and the processor, of the second Doppler flow signal for at least two cardiac cycles of the patient. The organ identification phase also includes processing, by the processor, the first data segment through a portal vein heuristic algorithm to determine a portal vein score of the first Doppler flow signal. The first data segment is also processed by the processor through a hepatic vein heuristic algorithm to determine a hepatic vein score of the first Doppler flow signal. The processor also processes the first data segment through a renal heuristic algorithm to determine a renal blood flow score of the first Doppler flow signal. The processor identifies the first Doppler flow signal as a portal vein flow, as a renal blood flow, or as a hepatic vein flow of the patient based on the portal vein score, the hepatic vein score, and the renal artery score of the first Doppler flow signal. The processor processes the second data segment through the portal vein heuristic algorithm to determine a portal vein score of the second Doppler flow signal. The second data segment is also processed by the processor through the hepatic vein heuristic algorithm to determine a hepatic vein score of the second Doppler flow signal. The processor also processes the second data segment through the renal heuristic algorithm to determine a renal blood flow score of the second Doppler flow signal. The processor identifies the second Doppler flow signal as the portal vein flow, as the renal blood flow, or as the hepatic vein flow of the patient based on the portal vein score, the hepatic vein score, and the renal artery score of the second Doppler flow signal. The method also includes affixing the ultrasound transducer probe on the abdomen of the patient with an adhesive patch based on the portal vein score, the hepatic vein score, or the renal artery score of the first Doppler flow signal or the second Doppler flow signal. The processor commands the beamformer and the ultrasound transducer probe to track scan at least one of the first Doppler flow signal and the second Doppler flow signal based on the portal vein score, the hepatic vein score, or the renal artery score of the first Doppler flow signal or the second Doppler flow signal.

[0148] In yet another example of the disclosure, a system includes an ultrasound transducer probe configured to continuously measure a Doppler flow signal of an organ blood flow of a patient during a surgery, a medical procedure, or a medical observation. An adhesive patch is connected to the ultrasound transducer probe and is configured to attach the ultrasound transducer probe to the patient and maintain contact between the patient and the ultrasound transducer probe without an operator. The system also includes a beamformer configured to drive the ultrasound transducer probe to track the Doppler flow signal. A blood flow monitor is in communication with the ultrasound transducer probe and includes a system memory and a processor. The system memory stores monitoring software code and the processor is configured to execute the monitoring software code to track into a data segment, by the ultrasound transducer probe, the beamformer, and the processor, the Doppler flow signal for at least two cardiac cycles of the patient. The processor is configured to execute the monitoring software code to process, by the processor, the data segment through a portal vein heuristic algorithm to determine a portal vein score of the Doppler flow signal. The processor is configured to execute the monitoring software code to process, by the processor, the data segment through a hepatic vein heuristic algorithm to determine a hepatic vein score of the Doppler flow signal. The processor is also configured to execute the monitoring software code to process, by the processor, the data segment through a renal heuristic algorithm to determine a renal artery score of the Doppler flow signal. The processor is also configured to execute the monitoring software code to identify, by the processor, the Doppler flow signal as a portal vein flow, as a renal artery flow, or as a hepatic vein flow of the patient based on the portal vein score, the hepatic vein score, and the renal artery score.

[0149] The system of the preceding paragraph can optionally include, additionally and / or alternatively, any one or more of the following features, configurations and / or additional components in the paragraphs below.

[0150] In an embodiment of the foregoing system, the renal heuristic algorithm comprises: a first renal heuristic that is configured to be executed by the processor to analyze the data segment for a first organ blood flow signal with a flow direction that is always toward the ultrasound transducer probe; a second renal heuristic that is configured to be executed by the processor to analyze the first organ blood flow signal in the data segment and determine whether first organ blood flow signal is always pulsatile with a heartbeat of the patient; and a third renal heuristic that is configured to be executed by the processor to analyze the first organ blood flow signal for a velocity profile that is biphasic with a pulse segment followed in time by a steady segment, wherein the pulse segment is higher in velocity than the steady segment, the pulse segment is shorter in time than the steady segment, and the steady segment decreases in velocity with time.

[0151] In an embodiment of the foregoing system, the renal heuristic algorithm comprises: a fourth renal heuristic that is configured to be executed by the processor to analyze the data segment for a second organ blood flow signal; and a fifth renal heuristic that is configured to be executed by the processor to analyze the second organ blood flow signal for a flow direction that is always away from the ultrasound transducer probe.

[0152] In an embodiment of the foregoing system, the hepatic vein heuristic algorithm comprises: a first hepatic heuristic that is configured to be executed by the processor to analyze the data segment for an organ blood flow signal that is always pulsatile with a heartbeat of the patient; a second hepatic heuristic that is configured to be executed by the processor to analyze the organ blood flow signal for a flow direction reversal in the organ blood flow signal relative to the ultrasound transducer probe during each heartbeat of the patient recorded in the data segment; a third hepatic heuristic that is configured to be executed by the processor to analyze the flow direction reversal of the organ blood flow signal for non-symmetry in time, velocity, and volume within a cardiac cycle of the patient; and a fourth hepatic heuristic that is configured to be executed by the processor to analyze the organ blood flow signal for more flow volume and flow velocity away from the ultrasound transducer probe than toward the ultrasound transducer probe within the cardiac cycle of the patient.

[0153] In an embodiment of the foregoing system, the portal vein heuristic algorithm comprises: a first portal heuristic that is configured to be executed by the processor to analyze the data segment for a blood flow signal flowing toward the ultrasound transducer probe; a second portal heuristic that is configured to be executed by the processor to analyze the blood flow signal for pulsatility with the heartbeat of the patient; and a third portal heuristic that is configured to be executed by the processor to analyze the pulsatility of the blood flow signal for a sawtooth-shaped velocity profile with inclined segments and declined segments that are approximately symmetrical in slope and time.

[0154] In an embodiment of the foregoing system, the processor is configured to execute the monitoring software code to process the data segment concurrently through the renal heuristic algorithm, the portal vein heuristic algorithm, and the hepatic vein heuristic algorithm to identify whether the Doppler flow signal is from the renal artery flow, the portal vein blood flow, or the hepatic vein blood flow of the patient.

[0155] In an embodiment of the foregoing system, the ultrasound transducer probe comprises a two-dimensional array of transducer elements.

[0156] In an embodiment of the foregoing system, the ultrasound transducer probe is configured to operate at a center frequency between 0.5 MHz and 4.0 MHz to penetrate more than 15 cm into the patient.

[0157] In an embodiment of the foregoing system, the ultrasound transducer probe is configured to perform three-dimensional scanning.

[0158] In an embodiment of the foregoing system, the system further comprises a hemodynamic sensor configured to measure cardiac cycles of the patient during the surgery, the medical procedure, or the medical observation, and wherein the hemodynamic sensor is in electric communication with the processor of the blood flow monitor to deliver cardiac cycle measurements to the processor.

[0159] In another example of the disclosure, a method is disclosed for monitoring an organ blood flow of a patient during a surgery, a medical procedure, or a medical observation. The method includes performing a finding phase. The finding phase includes scanning, by an array of transducer elements of an ultrasound probe and a beamformer driving the array of transducer elements, a volume within an abdomen of the patient under a field of view of the array of transducer elements. The finding phase also includes detecting, by a processor in communication with the ultrasound transducer probe and the beamformer, a Doppler flow signal of the organ blood flow. The method also includes performing an organ identification phase. The organ identification phase includes scanning a data segment, by the array of transducer elements, the beamformer, and the processor, of the Doppler flow signal for at least two cardiac cycles of the patient. The organ identification phase also includes processing, by the processor, the data segment through a renal heuristic algorithm to determine a renal blood flow score of the Doppler flow signal. The processor identifies the Doppler flow signal as a renal blood flow or as a non-renal blood flow of the patient based on the renal blood flow score. The method also includes affixing the ultrasound transducer probe in a stationary position to the abdomen of the patient with an adhesive patch after the processor identifies the Doppler flow signal as the renal blood flow of the patient. The Doppler flow signal is continuously measured with the ultrasound transducer probe attached in the stationary position to the abdomen of the patient during the surgery, the medical procedure, or the medical observation.

[0160] The method of the preceding paragraph can optionally include, additionally and / or alternatively, any one or more of the following features, configurations and / or additional components in the paragraphs below.

[0161] In an embodiment of the foregoing method, processing, by the processor, the data segment through the renal heuristic algorithm to determine the renal blood flow score of the Doppler flow signal comprises: determining, by the processor, whether the data segment of the Doppler flow signal includes a first organ blood flow signal with a flow direction that is always toward the ultrasound transducer probe; determining, by the processor, whether the first organ blood flow signal in the data segment is always pulsatile with a heartbeat of the patient; and determining, by the processor, whether the first organ blood flow signal in the data segment includes a velocity profile that is biphasic with a pulse segment followed in time by a steady segment, wherein the pulse segment is higher in velocity than the steady segment, the pulse segment is shorter in time than the steady segment, and the steady segment decreases in velocity with time.

[0162] In an embodiment of the foregoing method, processing, by the processor, the data segment through the renal heuristic algorithm to determine the renal blood flow score of the Doppler flow signal comprises: determining, by the processor, whether the data segment of the Doppler flow signal includes a second organ blood flow signal; and determining, by the processor, whether the second organ blood flow signal of the Doppler flow signal in the data segment includes a flow direction that is always away from the ultrasound transducer probe.

[0163] In an embodiment of the foregoing method, the method further comprises: outputting, by the processor, a plot of the data segment of the Doppler flow signal to a display in communication with the processor; outputting, by the processor, the renal blood flow score to the display; and outputting, by the processor, an identity determination score that indicates on the display that the Doppler flow signal is from the renal blood flow of the patient or is not from the renal blood flow of the patient.

[0164] In an embodiment of the foregoing method, the organ identification phase further comprises: processing, by the processor, the data segment through a portal vein heuristic algorithm to determine a portal vein score of the Doppler flow signal; processing, by the processor, the data segment through a hepatic vein heuristic algorithm to determine a hepatic vein score of the Doppler flow signal; and identifying, by the processor, the Doppler flow signal as a portal vein flow, as the renal blood flow, or as a hepatic vein flow of the patient based on the portal vein score, the hepatic vein score, and the renal blood flow score.

[0165] In an embodiment of the foregoing method, the method further comprises affixing the ultrasound transducer probe in a stationary position to the abdomen of the patient with an adhesive patch after the processor identifies the Doppler flow signal as the portal vein flow, as the renal blood flow, or as the hepatic vein flow of the patient.

[0166] In an embodiment of the foregoing method, the processor processes the data segment concurrently through the portal vein heuristic algorithm, the hepatic vein heuristic algorithm, and the renal heuristic algorithm.

[0167] In an embodiment of the foregoing method, processing, by the processor, the data segment through the hepatic vein heuristic algorithm to determine the hepatic vein score of the Doppler flow signal comprises: determining, by the processor, whether the data segment of the Doppler flow signal is always pulsatile with a heartbeat of the patient; determining, by the processor, whether the data segment of the Doppler flow signal shows flow direction reversal in the organ blood flow relative to the ultrasound transducer probe during each heartbeat of the patient recorded in the data segment; determining, by the processor, whether the data segment of the Doppler flow signal shows the flow direction reversal as nonsymmetrical in time, velocity, or volume; and determining, by the processor whether the data segment of the Doppler flow signal shows more flow volume and flow velocity of the organ blood flow away from the ultrasound transducer probe than toward the ultrasound transducer probe.

[0168] In an embodiment of the foregoing method, processing, by the processor, the data segment through the portal vein heuristic algorithm to determine the portal vein score of the Doppler flow signal comprises: determining, by the processor, whether the data segment of the Doppler flow signal shows the organ blood flow always flowing toward the ultrasound transducer probe; determining, by the processor, whether the data segment of the Doppler flow signal shows the organ blood flow to be pulsatile with the heartbeat of the patient; and determining, by the processor, whether the data segment of the Doppler flow signal shows the organ blood flow as having pulsatility with a sawtooth-shaped velocity profile with inclined segments and declined segments that are approximately symmetrical in slope and time.

[0169] In an embodiment of the foregoing method, the method further comprises: outputting, by the processor, the hepatic vein score, the portal vein score, and the renal blood flow score to the display; and outputting, by the processor, the identity determination score, wherein the identity determination score indicates on the display that the Doppler flow signal is from the portal vein flow, the renal blood flow, or the hepatic vein flow of the patient.

[0170] In an embodiment of the foregoing method, the method further comprises: determining, by the processor, a first quality grade / index that indicates a probability of the Doppler flow signal being from the portal vein flow, the renal blood flow, or the hepatic vein flow of the patient; and outputting to the display the quality grade / index.

[0171] In an embodiment of the foregoing method, the method further comprises sensing the at least two cardiac cycles of the patient with a hemodynamic sensor connected to the patient and in electrical communication with the processor concurrently with the ultrasound transducer probe, the beamformer, and the processor scanning the data segment of the Doppler flow signal.

[0172] In an embodiment of the foregoing method, continuously measuring the Doppler flow signal with the ultrasound transducer probe attached in the stationary position to the abdomen of the patient during the surgery, the medical procedure, or the medical observation comprises: track-scanning the Doppler flow signal of the organ blood flow of the patient by the beamformer and the ultrasound transducer probe. In an embodiment of the foregoing method, track-scanning the Doppler flow signal of the organ blood flow of the patient by the beamformer and the ultrasound transducer probe comprises: emitting a set of sequential beams from an array of transducer elements of the ultrasound transducer probe to track a center of the organ blood flow relative to the array of transducer elements; focusing each beam from the set of beams in different locations; and adjusting the position of the set of beams onto the center of the organ blood flow by the beamformer to maintain the Doppler flow signal of the organ blood flow of the patient.

[0173] In an embodiment of the foregoing method, track-scanning the Doppler flow signal of the organ blood flow of the patient by the beamformer and the ultrasound transducer probe further comprises: measuring estimates of a location of the organ blood flow by the beamformer; inputting the estimates of the location of the organ blood flow into a predictive filter; and determining an expected trajectory of the location of the organ blood flow based on the estimates of the location of the organ blood flow and based on a breathing frequency of the patient.

[0174] In an embodiment of the foregoing method, measuring estimates of the location of the organ blood flow by the beamformer comprises: measuring, by the beamformer, differences in integrated power spectrum between individual beams of the set of sequential beams to estimate an azimuthal angle and an elevation angle of the location of the organ blood flow relative to the array of transducer elements; and estimating, by the beamformer, a distance of the organ blood flow from the array of transducer elements in a distance dimension by: gathering, by the array of transducer elements and the beamformer, a plurality of distance samples along a distance dimension; calculating, by the beamformer, integrated power spectrum for each distance sample of the plurality of distance samples; assigning, by the beamformer, a likelihood of containing the organ blood flow to each distance sample of the plurality of distance samples; and calculating, by the beamformer, an estimate of a center of the organ blood flow from the plurality of distance samples.

[0175] In an embodiment of the foregoing method, the method further comprises: making, by the beamformer, proportional the likelihood of containing the organ blood flow to the integrated power spectrum for each distance sample of the plurality of distance samples; and calculating, by the beamformer, the estimate of the center of the organ blood flow from the plurality of distance samples by selecting a distance sample of the plurality of distance samples with the largest integrated power spectrum. In an embodiment of the foregoing method, the method further comprises: determining, by the processor, a second quality grade / index that indicates a probability of the Doppler flow signal being from the organ blood flow versus noise, artifacts, or other physiologically irrelevant blood flow signals in the abdomen of the patient; and continuously communicating the second quality grade / index as an input into the predictive filter during the operation, medical procedure, or medical observation.

[0176] In an embodiment of the foregoing method, the method further comprises: measuring the breathing frequency of the patient with a breathing monitor connected to the patient and in communication with the processor; and inputting the breathing frequency of the patient into the predictive filter from the breathing monitor.

[0177] In an embodiment of the foregoing method, the predictive filter comprises a Kalman Filter.

[0178] In an embodiment of the foregoing method, the method further comprises: repeating the finding phase if a signature of interest of the Doppler flow signal falls below a preset threshold, cri terium, criteria, and / or heuristic; and repeating the organ identification phase after repeating the finding phase.

[0179] In yet another example of the disclosure, an organ blood flow monitor includes an ultrasound transducer probe and an adhesive patch connected to the ultrasound transducer probe for attaching the ultrasound transducer probe to a patient. The organ blood flow monitor also includes system memory that stores monitoring software code. The monitoring software code includes an organ recognition module. The organ blood flow monitor also includes a processor configured to execute the organ recognition module to scan a Doppler flow signal sensed in an abdomen of the patient by the ultrasound transducer probe for at least two cardiac cycles of the patient. The processor is also configured to execute the organ recognition module to process the scanned Doppler flow signal through a renal heuristic algorithm of the organ recognition module to identify whether the scanned Doppler flow signal is from a renal blood flow of the patient.

[0180] The organ blood flow monitor of the preceding paragraph can optionally include, additionally and / or alternatively, any one or more of the following features, configurations and / or additional components in the paragraphs below.

[0181] In an embodiment of the foregoing organ blood flow monitor, the ultrasound transducer probe comprises a two-dimensional array of transducer elements.

[0182] In an embodiment of the foregoing organ blood flow monitor, the organ blood flow monitor further comprises a beamformer configured to drive the two- dimensional array of transducer elements of the ultrasound transducer probe to track the Doppler flow signal.

[0183] In an embodiment of the foregoing organ blood flow monitor, the ultrasound transducer probe is configured to perform three-dimensional scans.

[0184] In an embodiment of the foregoing organ blood flow monitor, the renal heuristic algorithm comprises: a first renal heuristic that is configured to be executed by the processor to analyze the data segment for a first organ blood flow signal with a flow direction that is always toward the ultrasound transducer probe; a second renal heuristic that is configured to be executed by the processor to analyze the first organ blood flow signal in the data segment and determine whether first organ blood flow signal is always pulsatile with a heartbeat of the patient; and a third renal heuristic that is configured to be executed by the processor to analyze the first organ blood flow signal for a velocity profile that is biphasic with a pulse segment followed in time by a steady segment, wherein the pulse segment is higher in velocity than the steady segment, the pulse segment is shorter in time than the steady segment, and the steady segment decreases in velocity with time.

[0185] In an embodiment of the foregoing organ blood flow monitor, the renal heuristic algorithm comprises: a fourth renal heuristic that is configured to be executed by the processor to analyze the data segment for a second organ blood flow signal; and a fifth renal heuristic that is configured to be executed by the processor to analyze the second organ blood flow signal for a flow direction that is always away from the ultrasound transducer probe.

[0186] In an embodiment of the foregoing organ blood flow monitor, the organ recognition module further comprises: a portal vein heuristic algorithm that is configured to be executed by the processor to identify whether the scanned Doppler flow signal is from a portal vein blood flow of the patient; and a hepatic vein heuristic algorithm that is configured to be executed by the processor to identify whether the scanned Doppler flow signal is from a hepatic vein blood flow of the patient.

[0187] In an embodiment of the foregoing organ blood flow monitor, the hepatic vein heuristic algorithm comprises: a first hepatic heuristic that is configured to be executed by the processor to determine whether the scanned Doppler flow signal is always pulsatile with a heartbeat of the patient; a second hepatic heuristic that is configured to be executed by the processor to determine whether the scanned Doppler flow signal shows flow direction reversal in the organ blood flow relative to the ultrasound transducer probe during each heartbeat of the patient recorded in the scanned Doppler flow signal; a third hepatic heuristic that is configured to be executed by the processor to determine whether the scanned Doppler flow signal shows the flow direction reversal as nonsymmetrical in time, velocity, or volume; and a fourth hepatic heuristic that is configured to be executed by the processor to determine whether the scanned Doppler flow signal shows more flow volume and flow velocity of the organ blood flow away from the ultrasound transducer probe than toward the ultrasound transducer probe.

[0188] In an embodiment of the foregoing organ blood flow monitor, the portal vein heuristic algorithm comprises: a first portal heuristic that is configured to be executed by the processor to determine whether the scanned Doppler flow signal shows the organ blood flow always flowing toward the ultrasound transducer probe; a second portal heuristic that is configured to be executed by the processor to determine whether the scanned Doppler flow signal shows the organ blood flow to be pulsatile with the heartbeat of the patient; and a third portal heuristic that is configured to be executed by the processor to determine whether the scanned Doppler flow signal shows the organ blood flow as having pulsatility with a sawtooth-shaped velocity profile with inclined segments and declined segments that are approximately symmetrical in slope and time.

[0189] In an embodiment of the foregoing organ blood flow monitor, the processor is configured to execute the organ recognition module to process the scanned Doppler flow signal concurrently through the renal heuristic algorithm, the portal vein heuristic algorithm, and the hepatic vein heuristic algorithm to identify whether the scanned Doppler flow signal is from the renal blood flow, the portal vein blood flow, or the hepatic vein blood flow of the patient.

[0190] In an embodiment of the foregoing organ blood flow monitor, the organ blood flow monitor further comprises a display in communication with the ultrasound transducer probe, the beamformer, and the processor to receive and show the Doppler flow signal from the ultrasound transducer probe and an identity determination score of the Doppler flow signal generated by the organ recognition module.

[0191] In an embodiment of the foregoing organ blood flow monitor, the ultrasound transducer probe is configured to operate at a center frequency between 0.5 MHz and 4.0 MHz to penetrate more than 15 cm into the patient.

[0192] In an embodiment of the foregoing organ blood flow monitor, the organ blood flow monitor further comprises a hemodynamic sensor configured to measure cardiac cycles of the patient, and wherein the hemodynamic sensor is in electric communication with the processor to deliver cardiac cycle measurements to the processor. In another example of the disclosure, an organ blood flow monitor includes an ultrasound transducer probe and an adhesive patch connected to the ultrasound transducer probe for attaching the ultrasound transducer probe to a patient. The organ blood flow monitor also includes a system memory that stores monitoring software code. The monitoring software code includes an organ recognition module. The organ blood flow monitor also includes a processor configured to execute the organ recognition module to track a Doppler flow signal sensed in an abdomen of the patient by the ultrasound transducer probe for at least two cardiac cycles of the patient. The processor is also configured to execute the organ recognition module to process the tracked Doppler flow signal through a portal vein heuristic algorithm of the organ recognition module to identify whether the tracked Doppler flow signal is from a portal vein blood flow of the patient.

[0193] The organ blood flow monitor of the preceding paragraph can optionally include, additionally and / or alternatively, any one or more of the following features, configurations and / or additional components in the paragraphs below.

[0194] In an embodiment of the foregoing organ blood flow monitor, the ultrasound transducer probe comprises a two-dimensional array of transducer elements.

[0195] In an embodiment of the foregoing organ blood flow monitor, the organ blood flow monitor further comprises: a beamformer configured to drive the two- dimensional array of transducer elements of the ultrasound transducer probe to track the Doppler flow signal.

[0196] In an embodiment of the foregoing organ blood flow monitor, the ultrasound transducer probe is configured to perform three-dimensional scanning.

[0197] In an embodiment of the foregoing organ blood flow monitor, the portal vein heuristic algorithm comprises: a first portal heuristic that is configured to be executed by the processor to determine whether the tracked Doppler flow signal shows the organ blood flow always flowing toward the ultrasound transducer probe; a second portal heuristic that is configured to be executed by the processor to determine whether the tracked Doppler flow signal shows the organ blood flow to be pulsatile with the heartbeat of the patient; and a third portal heuristic that is configured to be executed by the processor to determine whether the tracked Doppler flow signal shows the organ blood flow as having pulsatility with a sawtooth-shaped velocity profile with inclined segments and declined segments that are approximately symmetrical in slope and time.

[0198] In an embodiment of the foregoing organ blood flow monitor, the organ recognition module further comprises: a hepatic vein heuristic algorithm that is configured to be executed by the processor to identify whether the tracked Doppler flow signal is from a hepatic vein blood flow of the patient; and a renal heuristic algorithm that is configured to be executed by the processor to identify whether the tracked Doppler flow signal is from a renal blood flow of the patient.

[0199] In an embodiment of the foregoing organ blood flow monitor, the hepatic vein heuristic algorithm comprises: a first hepatic heuristic that is configured to be executed by the processor to determine whether the tracked Doppler flow signal is always pulsatile with a heartbeat of the patient; a second hepatic heuristic that is configured to be executed by the processor to determine whether the tracked Doppler flow signal shows flow direction reversal in the organ blood flow relative to the ultrasound transducer probe during each heartbeat of the patient recorded in the tracked Doppler flow signal; a third hepatic heuristic that is configured to be executed by the processor to determine whether the tracked Doppler flow signal shows the flow direction reversal as nonsymmetrical in time, velocity, or volume; and a fourth hepatic heuristic that is configured to be executed by the processor to determine whether the tracked Doppler flow signal shows more flow volume and flow velocity of the organ blood flow away from the ultrasound transducer probe than toward the ultrasound transducer probe.

[0200] In an embodiment of the foregoing organ blood flow monitor, the renal heuristic algorithm comprises: a first renal heuristic that is configured to be executed by the processor to analyze the data segment for a first organ blood flow signal with a flow direction that is always toward the ultrasound transducer probe; a second renal heuristic that is configured to be executed by the processor to analyze the first organ blood flow signal in the data segment and determine whether first organ blood flow signal is always pulsatile with a heartbeat of the patient; and a third renal heuristic that is configured to be executed by the processor to analyze the first organ blood flow signal for a velocity profile that is biphasic with a pulse segment followed in time by a steady segment, wherein the pulse segment is higher in velocity than the steady segment, the pulse segment is shorter in time than the steady segment, and the steady segment decreases in velocity with time.

[0201] In an embodiment of the foregoing organ blood flow monitor, the renal heuristic algorithm comprises: a fourth renal heuristic that is configured to be executed by the processor to analyze the data segment for a second organ blood flow signal; and a fifth renal heuristic that is configured to be executed by the processor to analyze the second organ blood flow signal for a flow direction that is always away from the ultrasound transducer probe. In an embodiment of the foregoing organ blood flow monitor, the processor is configured to execute the organ recognition module to process the tracked Doppler flow signal concurrently through the renal heuristic algorithm, the portal vein heuristic algorithm, and the hepatic vein heuristic algorithm to identify whether the tracked Doppler flow signal is from the renal blood flow, the portal vein blood flow, or the hepatic vein blood flow of the patient.

[0202] In an embodiment of the foregoing organ blood flow monitor, the organ blood flow monitor further comprises a display in communication with the ultrasound transducer probe, the beamformer, and the processor to receive and show the Doppler flow signal from the ultrasound transducer probe and an identity determination score of the Doppler flow signal generated by the organ recognition module.

[0203] In an embodiment of the foregoing organ blood flow monitor, the ultrasound transducer probe is configured to operate at a center frequency between 0.5 MHz and 4.0 MHz to penetrate more than 15 cm into the patient.

[0204] In an embodiment of the foregoing organ blood flow monitor, the organ blood flow monitor further comprises a hemodynamic sensor configured to measure cardiac cycles of the patient, and wherein the hemodynamic sensor is in electric communication with the processor to deliver cardiac cycle measurements to the processor.

[0205] In another example of the disclosure, an organ blood flow monitor includes an ultrasound transducer probe and an adhesive patch connected to the ultrasound transducer probe for attaching the ultrasound transducer probe to a patient. The organ blood flow monitor also includes a system memory that stores monitoring software code. The monitoring software code includes an organ recognition module. The organ blood flow monitor also includes a processor configured to execute the organ recognition module to track a Doppler flow signal sensed in an abdomen of the patient by the ultrasound transducer probe for at least two cardiac cycles of the patient. The processor is also configured to execute the organ recognition module to process the tracked Doppler flow signal through a hepatic vein heuristic algorithm of the organ recognition module to identify whether the tracked Doppler flow signal is from a hepatic vein blood flow of the patient.

[0206] The organ blood flow monitor of the preceding paragraph can optionally include, additionally and / or alternatively, any one or more of the following features, configurations and / or additional components in the paragraphs below.

[0207] In an embodiment of the foregoing organ blood flow monitor, the ultrasound transducer probe comprises a two-dimensional array of transducer elements. In an embodiment of the foregoing organ blood flow monitor, the organ blood flow monitor further comprises a beamformer configured to drive the two- dimensional array of transducer elements of the ultrasound transducer probe to track the Doppler flow signal.

[0208] In an embodiment of the foregoing organ blood flow monitor, the ultrasound transducer probe is configured to perform three-dimensional scanning.

[0209] In an embodiment of the foregoing organ blood flow monitor, the hepatic vein heuristic algorithm comprises: a first hepatic heuristic that is configured to he executed by the processor to determine whether the tracked Doppler flow signal is always pulsatile with a heartbeat of the patient; a second hepatic heuristic that is configured to be executed by the processor to determine whether the tracked Doppler flow signal shows flow direction reversal in the organ blood flow relative to the ultrasound transducer probe during each heartbeat of the patient recorded in the tracked Doppler flow signal; a third hepatic heuristic that is configured to be executed by the processor to determine whether the tracked Doppler flow signal shows the flow direction reversal as nonsymmetrical in time, velocity, or volume; and a fourth hepatic heuristic that is configured to be executed by the processor to determine whether the tracked Doppler flow signal shows more flow volume and flow velocity of the organ blood flow away from the ultrasound transducer probe than toward the ultrasound transducer probe.

[0210] In an embodiment of the foregoing organ blood flow monitor, the organ recognition module further comprises: a portal vein heuristic algorithm that is configured to be executed by the processor to identify whether the tracked Doppler flow signal is from a portal vein blood flow of the patient; and a renal heuristic algorithm that is configured to be executed by the processor to identify whether the tracked Doppler flow signal is from a renal blood flow of the patient.

[0211] In an embodiment of the foregoing organ blood flow monitor, the portal vein heuristic algorithm comprises: a first portal heuristic that is configured to be executed by the processor to determine whether the tracked Doppler flow signal shows the organ blood flow always flowing toward the ultrasound transducer probe; a second portal heuristic that is configured to be executed by the processor to determine whether the tracked Doppler flow signal shows the organ blood flow to be pulsatile with the heartbeat of the patient; and a third portal heuristic that is configured to be executed by the processor to determine whether the tracked Doppler flow signal shows the organ blood flow as having pulsatility with a sawtooth-shaped velocity profile with inclined segments and declined segments that are approximately symmetrical in slope and time.

[0212] In an embodiment of the foregoing organ blood flow monitor, the renal heuristic algorithm comprises: a first renal heuristic that is configured to be executed by the processor to analyze the data segment for a first organ blood flow signal with a flow direction that is always toward the ultrasound transducer probe; a second renal heuristic that is configured to be executed by the processor to analyze the first organ blood flow signal in the data segment and determine whether first organ blood flow signal is always pulsatile with a heartbeat of the patient; and a third renal heuristic that is configured to be executed by the processor to analyze the first organ blood flow signal for a velocity profile that is biphasic with a pulse segment followed in time by a steady segment, wherein the pulse segment is higher in velocity than the steady segment, the pulse segment is shorter in time than the steady segment, and the steady segment decreases in velocity with time.

[0213] In an embodiment of the foregoing organ blood flow monitor, the renal heuristic algorithm comprises: a fourth renal heuristic that is configured to be executed by the processor to analyze the data segment for a second organ blood flow signal; and a fifth renal heuristic that is configured to be executed by the processor to analyze the second organ blood flow signal for a flow direction that is always away from the ultrasound transducer probe.

[0214] In an embodiment of the foregoing organ blood flow monitor, the processor is configured to execute the organ recognition module to process the tracked Doppler flow signal concurrently through the renal heuristic algorithm, the portal vein heuristic algorithm, and the hepatic vein heuristic algorithm to identify whether the tracked Doppler flow signal is from the renal blood flow, the portal vein blood flow, or the hepatic vein blood flow of the patient.

[0215] In an embodiment of the foregoing organ blood flow monitor, the organ blood flow monitor further comprises a display in communication with the ultrasound transducer probe, the beamformer, and the processor to receive and show the Doppler flow signal from the ultrasound transducer probe and an identity determination score of the Doppler flow signal generated by the organ recognition module.

[0216] In an embodiment of the foregoing organ blood flow monitor, the ultrasound transducer probe is configured to operate at a center frequency between 0.5 MHz and 4.0 MHz to penetrate more than 15 cm into the patient. In an embodiment of the foregoing organ blood flow monitor, the organ blood flow monitor further comprises a hemodynamic sensor configured to measure cardiac cycles of the patient, and wherein the hemodynamic sensor is in electric communication with the processor to deliver the cardiac cycle measurements to the processor. While the invention has been described with reference to an exemplary embodiment(s), it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiment(s) disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.

Claims

CLAIMS:

1. A method for monitoring an organ blood flow of a patient, the method comprising: performing a finding phase, wherein the finding phase comprises: scanning, by an ultrasound transducer probe and a beamformer driving the ultrasound transducer probe, a volume within an abdomen of the patient under a field of view of the ultrasound transducer probe; and detecting, by a processor in communication with the ultrasound transducer probe and the beamformer, a Doppler flow signal of the organ blood flow; performing an organ identification phase, wherein the organ identification phase comprises: scanning a data segment, by the ultrasound transducer probe, the beamformer, and the processor, of the Doppler flow signal for at least two cardiac cycles of the patient; processing, by the processor, the data segment through a portal vein heuristic algorithm to determine a portal vein score of the Doppler flow signal; processing, by the processor, the data segment through a hepatic vein heuristic algorithm to determine a hepatic vein score of the Doppler flow signal; processing, by the processor, the data segment through a renal heuristic algorithm to determine a renal blood flow score of the Doppler flow signal; and identifying, by the processor, the Doppler flow signal as a portal vein flow, as a renal blood flow, or as a hepatic vein flow of the patient based on the portal vein score, the hepatic vein score, and the renal blood flow score; affixing the ultrasound transducer probe on the abdomen of the patient with an adhesive patch based on the portal vein score, the hepatic vein score, or the renal blood flow score; commanding, by the processor, the beamformer and the ultrasound transducer probe to track scan the Doppler flow signal based on the portal vein score, the hepatic vein score, or the renal blood flow score; andtrack-scanning the Doppler flow signal by the beamformer and the ultrasound transducer probe to continuously sense the Doppler flow signal of the organ blood flow of the patient during a surgery, medical procedure, or medical observation without an ultrasound operator.

2. The method of claim 1, wherein the processor processes the data segment concurrently through the portal vein heuristic algorithm, the hepatic vein heuristic algorithm, and the renal heuristic algorithm.

3. The method of claim 2, wherein processing, by the processor, the data segment through the hepatic vein heuristic algorithm to determine the hepatic vein score of the Doppler flow signal comprises: determining, by the processor, whether the data segment of the Doppler flow signal is always pulsatile with a heartbeat of the patient; determining, by the processor, whether the data segment of the Doppler flow signal shows flow direction reversal in the organ blood flow relative to the ultrasound transducer probe during each heartbeat of the patient recorded in the data segment; determining, by the processor, whether the data segment of the Doppler flow signal shows the flow direction reversal as nonsymmetrical in time, velocity, or volume; and determining, by the processor whether the data segment of the Doppler flow signal shows more flow volume and flow velocity of the organ blood flow away from the ultrasound transducer probe than toward the ultrasound transducer probe.

4. The method of claim 2, wherein processing, by the processor, the data segment through the portal vein heuristic algorithm to determine the portal vein score of the Doppler flow signal comprises: determining, by the processor, whether the data segment of the Doppler flow signal shows the organ blood flow always flowing toward the ultrasound transducer probe; determining, by the processor, whether the data segment of the Doppler flow signal shows the organ blood flow to be pulsatile with the heartbeat of the patient; and determining, by the processor, whether the data segment of the Doppler flow signal shows the organ blood flow as having pulsatility with a sawtooth-shapedvelocity profile with inclined segments and declined segments that are approximately symmetrical in slope and time.

5. The method of claim 2, wherein processing, by the processor, the data segment through the renal heuristic algorithm to determine the renal blood flow score of the Doppler flow signal comprises: determining, by the processor, whether the data segment of the Doppler flow signal includes a first organ blood flow signal with a flow direction that is always toward the ultrasound transducer probe; determining, by the processor, whether the first organ blood flow signal in the data segment is always pulsatile with the heartbeat of the patient; and determining, by the processor, whether the first organ blood flow signal in the data segment includes a velocity profile that is biphasic with a pulse segment followed in time by a steady segment, wherein the pulse segment is higher in velocity than the steady segment, the pulse segment is shorter in time than the steady segment, and the steady segment decreases in velocity with time.

6. The method of claim 5, wherein processing, by the processor, the data segment through the renal heuristic algorithm to determine the renal blood flow score of the Doppler flow signal comprises: determining, by the processor, whether the data segment of the Doppler flow signal includes a second organ blood flow signal; and determining, by the processor, whether the second organ blood flow signal of the Doppler flow signal in the data segment includes a flow direction that is always away from the ultrasound transducer probe.

7. The method of claim 1 , further comprising: outputting, by the processor, a plot of the data segment of the Doppler flow signal and to a display in communication with the processor; outputting, by the processor, the hepatic vein score, the portal vein score, and / or the renal blood flow score to the display; and outputting, by the processor, an identity determination score that indicates on the display that the Doppler flow signal is from the portal vein flow, the renal blood flow, or the hepatic vein flow of the patient.

8. The method of claim 1 , further comprising:determining, by the processor, a first quality grade / index that indicates a probability of the Doppler flow signal being from the portal vein flow, the renal blood flow, or the hepatic vein flow of the patient; and outputting to the display the quality grade / index.

9. The method of claim 1 , further comprising: sensing the at least two cardiac cycles of the patient with a hemodynamic sensor connected to the patient and in electrical communication with the processor concurrently with the ultrasound transducer probe, the beamformer, and the processor scanning the data segment of the Doppler flow signal.

10. The method of claim 1 , wherein track-scanning the Doppler flow signal of the organ blood flow of the patient by the beamformer and the ultrasound transducer probe comprises: emitting a set of sequential beams from an array of transducer elements of the ultrasound transducer probe to track a center of the organ blood flow relative to the array of transducer elements; focusing each beam from the set of beams in different locations; and adjusting the position of the set of beams onto the center of the organ blood flow by the beamformer to maintain the Doppler flow signal of the organ blood flow of the patient.

11. The method of claim 10, wherein track-scanning the Doppler flow signal of the organ blood flow of the patient by the beamformer and the ultrasound transducer probe comprises: measuring estimates of a location of the organ blood flow by the beamformer; inputting the estimates of the location of the organ blood flow into a predictive filter; and determining an expected trajectory of the location of the organ blood flow based on the estimates of the location of the organ blood flow and based on a breathing frequency of the patient.

12. The method of claim 11, further comprising: determining, by the processor, a second quality grade / index that indicates a probability of the Doppler flow signal being from the organ blood flow versus noise, artifacts, or other physiologically irrelevant blood flow signals in the abdomen of the patient; andcontinuously communicating the second quality grade / index as an input into the predictive filter during the operation, medical procedure, or medical observation.

13. The method of claim 12, further comprising: measuring the breathing frequency of the patient with a breathing monitor connected to the patient and in communication with the processor; and inputting the breathing frequency of the patient into the predictive filter from the breathing monitor.

14. The method of claim 13, wherein the predictive filter comprises a Kalman Filter.

15. The method of claim 1 , further comprising: repeating the finding phase if a signature of interest of the Doppler flow signal falls below a preset threshold, criterium, criteria, and / or heuristic while trackscanning the Doppler flow signal; and repeating the organ identification phase after repeating the finding phase.

16. A system comprising: an ultrasound transducer probe configured to continuously measure a Doppler flow signal of an organ blood flow of a patient during a surgery, a medical procedure, or a medical observation; an adhesive patch connected to the ultrasound transducer probe and configured to attach the ultrasound transducer probe to the patient and maintain contact between the patient and the ultrasound transducer probe without an operator; a beamformer configured to drive the ultrasound transducer probe to track the Doppler flow signal; and a blood flow monitor in communication with the ultrasound transducer probe, wherein the blood flow monitor comprises: a system memory that stores monitoring software code; and a processor configured to execute the monitoring software code to: track into a data segment, by the ultrasound transducer probe, the beamformer, and the processor, the Doppler flow signal for at least two cardiac cycles of the patient; process, by the processor, the data segment through a portal vein heuristic algorithm to determine a portal vein score of the Doppler flow signal;process, by the processor, the data segment through a hepatic vein heuristic algorithm to determine a hepatic vein score of the Doppler flow signal; process, by the processor, the data segment through a renal heuristic algorithm to determine a renal artery score of the Doppler flow signal; and identify, by the processor, the Doppler flow signal as a portal vein flow, as a renal artery flow, or as a hepatic vein flow of the patient based on the portal vein score, the hepatic vein score, and the renal artery score.

17. The system of claim 16, wherein the renal heuristic algorithm comprises: a first renal heuristic that is configured to be executed by the processor to analyze the data segment for a first organ blood flow signal with a flow direction that is always toward the ultrasound transducer probe; a second renal heuristic that is configured to be executed by the processor to analyze the first organ blood flow signal in the data segment and determine whether first organ blood flow signal is always pulsatile with a heartbeat of the patient; and a third renal heuristic that is configured to be executed by the processor to analyze the first organ blood flow signal for a velocity profile that is biphasic with a pulse segment followed in time by a steady segment, wherein the pulse segment is higher in velocity than the steady segment, the pulse segment is shorter in time than the steady segment, and the steady segment decreases in velocity with time.

18. The system of claim 17, wherein the renal heuristic algorithm comprises: a fourth renal heuristic that is configured to be executed by the processor to analyze the data segment for a second organ blood flow signal; and a fifth renal heuristic that is configured to be executed by the processor to analyze the second organ blood flow signal for a flow direction that is always away from the ultrasound transducer probe.

19. The system of claim 16, wherein the hepatic vein heuristic algorithm comprises: a first hepatic heuristic that is configured to be executed by the processor to analyze the data segment for an organ blood flow signal that is always pulsatile with a heartbeat of the patient;a second hepatic heuristic that is configured to be executed by the processor to analyze the organ blood flow signal for a flow direction reversal in the organ blood flow signal relative to the ultrasound transducer probe during each heartbeat of the patient recorded in the data segment; a third hepatic heuristic that is configured to be executed by the processor to analyze the flow direction reversal of the organ blood flow signal for non-symmetry in time, velocity, and volume within a cardiac cycle of the patient; and a fourth hepatic heuristic that is configured to be executed by the processor to analyze the organ blood flow signal for more flow volume and flow velocity away from the ultrasound transducer probe than toward the ultrasound transducer probe within the cardiac cycle of the patient.

20. The system of claim 16, wherein the portal vein heuristic algorithm comprises: a first portal heuristic that is configured to be executed by the processor to analyze the data segment for a blood flow signal flowing toward the ultrasound transducer probe; a second portal heuristic that is configured to be executed by the processor to analyze the blood flow signal for pulsatility with the heartbeat of the patient; and a third portal heuristic that is configured to be executed by the processor to analyze the pulsatility of the blood flow signal for a sawtooth-shaped velocity profile with inclined segments and declined segments that are approximately symmetrical in slope and time.

21. The system of claims 16, wherein the processor is configured to execute the monitoring software code to process the data segment concurrently through the renal heuristic algorithm, the portal vein heuristic algorithm, and the hepatic vein heuristic algorithm to identify whether the Doppler flow signal is from the renal artery flow, the portal vein blood flow, or the hepatic vein blood flow of the patient.

22. The system of claim 16, wherein the ultrasound transducer probe comprises a two- dimensional array of transducer elements.

23. The system of claim 22, wherein the ultrasound transducer probe is configured to operate at a center frequency between 0.5 MHz and 4.0 MHz to penetrate more than 15 cm into the patient.

24. The system of claim 16, wherein the ultrasound transducer probe is configured to perform three-dimensional scanning.

25. The system of claims 16, further comprising: a hemodynamic sensor configured to measure cardiac cycles of the patient during the surgery, the medical procedure, or the medical observation, and wherein the hemodynamic sensor is in electric communication with the processor of the blood flow monitor to deliver cardiac cycle measurements to the processor.

26. An organ blood flow monitor comprises: an ultrasound transducer probe; an adhesive patch connected to the ultrasound transducer probe for attaching the ultrasound transducer probe to a patient; a system memory that stores monitoring software code, wherein the monitoring software code comprises an organ recognition module; and a processor configured to execute the organ recognition module to: scan a Doppler flow signal sensed in an abdomen of the patient by the ultrasound transducer probe for at least two cardiac cycles of the patient; and process the scanned Doppler flow signal through a renal heuristic algorithm of the organ recognition module to identify whether the scanned Doppler flow signal is from a renal blood flow of the patient.

27. The organ blood flow monitor of claim 26, wherein the ultrasound transducer probe comprises a two-dimensional array of transducer elements.

28. The organ blood flow monitor of claim 27, further comprising: a beamformer configured to drive the two-dimensional array of transducer elements of the ultrasound transducer probe to track the Doppler flow signal.

29. The organ blood flow monitor of claim 26, wherein the ultrasound transducer probe is configured to perform three-dimensional scans.

30. The organ blood flow monitor of claim 26, wherein the renal heuristic algorithm comprises: a first renal heuristic that is configured to be executed by the processor to analyze the data segment for a first organ blood flow signal with a flow direction that is always toward the ultrasound transducer probe; a second renal heuristic that is configured to be executed by the processor to analyze the first organ blood flow signal in the data segment and determine whetherfirst organ blood flow signal is always pulsatile with a heartbeat of the patient; and a third renal heuristic that is configured to be executed by the processor to analyze the first organ blood flow signal for a velocity profile that is biphasic with a pulse segment followed in time by a steady segment, wherein the pulse segment is higher in velocity than the steady segment, the pulse segment is shorter in time than the steady segment, and the steady segment decreases in velocity with time.

31. The organ blood flow monitor of claim 30, wherein the renal heuristic algorithm comprises: a fourth renal heuristic that is configured to be executed by the processor to analyze the data segment for a second organ blood flow signal; and a fifth renal heuristic that is configured to be executed by the processor to analyze the second organ blood flow signal for a flow direction that is always away from the ultrasound transducer probe.

32. The organ blood flow monitor of claim 26, wherein the organ recognition module further comprises: a portal vein heuristic algorithm that is configured to be executed by the processor to identify whether the scanned Doppler flow signal is from a portal vein blood flow of the patient; and a hepatic vein heuristic algorithm that is configured to be executed by the processor to identify whether the scanned Doppler flow signal is from a hepatic vein blood flow of the patient.

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