EP-4740863-A2 - SYSTEM AND METHOD FOR DETERMINING A TYPE OF A BRAIN DYSFUNCTION DURING MEDICAL PROCEDURES

EP4740863A2EP 4740863 A2EP4740863 A2EP 4740863A2EP-4740863-A2

Abstract

A method of determining a type of a brain dysfunction is discloses. The method may include: receiving an electroencephalogram (EEG) signal from an electrode placed on the head; calculating a regularity index for an electric activity of the brain based on EEG signal; detecting a temporal change in the regularity index; receiving a medical related input; and determining the type of brain dysfunction based on the temporal change in the regularity index and the medical related input.

Inventors

BAR ON SHAHAF, Dana
SHAHAF, GODED

Assignees

Rambam Med-Tech Ltd.

Dates

Publication Date: 20260513
Application Date: 20221027

Claims (15)

A method of determining a brain dysfunction, comprising: receiving an electroencephalogram (EEG) signal from an electrode placed on a patient' head at a location allowing detecting electrical activity of the brain; calculating regularity index for the electric activity of the brain based on the EEG signal; and detecting a regularity change in the regularity index by determining if the regularity index is at least one of: (c) below a first threshold value; and (d) a time derivative of the regularity index is above a second threshold value; receiving a medical related input, wherein the medical related input is at least one of: (iv) input related to the patient's medical history; (v) an anesthetic profile during a medical procedure; and (vi)an input related to a medical event; and determining a type of brain dysfunction based on the temporal change in the regularity index and the medical related input.
The method of claim 1, wherein the receiving input related to the patient related to the patient's medical history comprising at least one of: an age of the patient, a baseline cognitive profile and cardiovascular risk assessment.
The method according to any one of claims 1 to 2, wherein receiving the medical related input includes receiving a signal from at least one of: an external computing device and measurements received form at least one sensor.
The method of claim 3, wherein the input related to the medical event measurements is selected from: blood pressure, blood flow, temperature, saturation, glucose levels, other hemodynamic parameters, such as, pre-operative demographic and/or clinical data, ECG, central venous pressure and arterial invasive pressure, patient movements, target control infusion pumps of anesthetic medications (TCI) and patient movements monitoring.
The method of claim 3, wherein the external computing device is selected from a data storage with an electronic medical record, a controller of a bypass machine, a controller of a medication provision machine, a motion monitoring device, and a controller of the anesthetic machine.
The method according to any one of claims 1 to 5, wherein the input related to the medical event is received from one of: electronic medical record, blood pressure sensors, thermometer, camera, saturation sensor, US device, X-Ray device, end-tidal CO 2 (EtCO2) detector, motion detector, and transcranial Doppler.
The method according to any one of claims 1 to 6, wherein receiving the input related to the medical event includes receiving an input from a user via a user interface.
The method according to any one of claims 1 to 7, wherein the brain dysfunction is perioperative neurocognitive dysfunction (PND).
The method of claim 8, wherein the PND includes preoperatively diagnosed cognitive decline, postoperative delirium, delayed neurocognitive recovery, and postoperative cognitive dysfunction (POCD).
The method of claim 9, wherein determining a POCD is when the regularity index is below a POCD threshold value under certain anesthetic profile.
The method according to any one of claims 1 to 10, wherein the brain dysfunction is delirium and wherein determining delirium is when: a time derivative of the regularity index is above a delirium threshold value, indicating a decrease in the regularity index with time, and the anesthetic profile shows temporal reduction in the amount of anesthetic.
The method according to any one of claims 1 to 10, wherein the brain dysfunction is a stroke and wherein determining stroke is when the time derivative of the regularity index is above a first stroke threshold value and the input related to a medical event includes an input related to a surgery.
The method according to any one of claims 1 to 12, wherein the brain dysfunction is a seizure and wherein determining seizure is when: a time derivative of the regularity index is above a seizure threshold value, indicating a decrease in the regularity index with time, followed by a time derivative of the regularity index above another seizure threshold value.
The method according to any one of claims 1 to 13, wherein the regularity index is calculated based on at least one of: the amplitude of the signal; the change between consecutive wave amplitudes. In some embodiments, the index is calculated for a predetermined period of time; the power spectrum, of the signal, summarized for one of: specific frequencies, and a frequency band; and a degree of shifting in power spectrums distribution over specific frequencies or a band of frequencies in the signal.
The method according to any one of claims 1 to 14, wherein calculating the regularity index comprises at least one of: calculating, over time, at least one of the following using the amplitude of the signal: mean variability, median variability, standard deviation, percentile, variance and any combination thereof; calculating, over time, at least one of the following using the power spectrum of the signal: mean regularity, median regularity, standard deviation, percentile, variance and any combination thereof; calculating powers in the signal over the selected frequencies or the frequency bands, which associate with decreased or increased regularity; and calculating the powers in the signal over the selected periods of time.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of priority to U.S. Provisional Patent Application Nos. 63/279,132, filed November 14, 2021 entitled "SYSTEM AND METHOD FOR DETERMINING A TYPE OF A BRAIN INJURY DURING A MEDICAL PROCEDURE", and 63/309,722 filed February 14, 2022, entitled "SYSTEM AND METHOD FOR DETERMINING A TYPE OF A BRAIN DYSFUNCTION DURING A MEDICAL PROCEDURE", the contents of which are all incorporated herein by reference in their entirety. FIELD OF THE INVENTION The present invention relates generally to a method of determining a type of brain dysfunction. More specifically, the present invention relates to a system and a method of determining a type of brain dysfunction during a medical procedure or determining the occurrence of an acute fetus brain dysfunction during labor. BACKGROUND OF THE INVENTION Quick identification and classification of brain dysfunction is of the utmost importance. Certain types of dysfunctions, such as stroke, are largely reversible if treated rapidly. While in other conditions, such as delirium, it was shown that early intervention may reduce morbidity and mortality. However, identification and classification of brain dysfunction may be significantly delayed with patients under settings of reduced consciousness and/or reduced communication abilities in medical settings, such as, under anesthesia and in intensive care hospitalization. Intrapartum fetal monitoring to assess fetal well-being during labor is a key component of intrapartum management. Since certain types of intrapartum fetal distress are largely reversible if treated rapidly, early real time, recognition and identification of intrapartum fetal distress (e.g. due to fetal hypoxia) is one of the greatest challenges of modern obstetrics. Currently, over 85% of laboring patients undergo intrapartum fetal monitoring by continuous analysis of the fetal heart. Normal components of labor, such as contractions and maternal expulsive efforts, result in transient decreases in gas exchange for the fetus. Even in uncomplicated pregnancies these changes might place the fetus at risk for interruption in oxygenation which might cause fetal intrapartum asphyxia with any associated long-term disabilities. Nevertheless, the efficiency of the current electronic fetal monitoring (EFM) which uses fetal heart characteristics to assess fetal acidemia, hypoxia or fetal brain injury remains poor. A plethora of studies demonstrated that abnormal patterns of the fetal heart rate are of low predictive value for intrapartum fetal hypoxia, metabolic acidosis or brain injury (cerebral palsy CP). According to the Cochrane review, EFM did not decrease the rates of (CP, asphyxia complications or perinatal morbidity and the positive predictive value of non-reassuring FHR patterns for the prediction of CP among singleton newborns with normal birth is only 0.14% Electroencephalogram (EEG) is a well-established technology for monitoring brain function without the need for the patient's participation. EEG signals can be used to evaluate the degree of similarity of activity over the left and right hemispheres in patients. The degree of similarity or dissimilarity may be indicative of possible brain dysfunction. EEG can further be used for evaluating the degree of regularity of brain activity in patients. The degree of regularity or irregularity may also be indicative of possible brain dysfunction. However, there is no reliable method for identifying the type of brain dysfunction when the patient is under reduced consciousness and/or reduced communication abilities. Therefore, it is of value to generate effective systems to monitor such patients, using EEG, and to identify and classify, in real-time, dysfunction to their brain in order to derive immediate treatment recommendations. Furthermore, EEG signal can be used to evaluate fetal brain regularity during the process of labor. The degree of regularity, or irregularity, may be indicative of brain dysfunction. Continuous computerized evaluation of fetal brain regularity using a real-time EEG analysis might improve the sensitivity for early detection of intrapartum fetal brain distress and to derive immediate treatment recommendations. SUMMARY OF THE INVENTION Some aspects of the invention are directed to a method of determining a type of a brain dysfunction, comprising: receiving a first electroencephalogram (EEG) signal from an electrode placed on the first side of head of a patient at a location allowing detecting an electrical activity of a first hemisphere of the brain; receiving a second EEG signal from an electrode placed on the second side of the head of the patient at a location allowing detecting an electrical activity of a second hemisphere of the brain; calculating a similarity index for an electric activity between hemispheres of the brain based on the first and second signals; and detecting a temporal change in the similarity index by determining i