# US 10,863,933 B2 · System and methods for managing blood loss of a patient > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,863,933 B2 - Document ID: US10863933B2 - Status: Granted - Kind: B2 - Application number: 15/943,561 - Filed: 2018-04-02 - Published: 2019-01-10 - Granted: 2020-12-15 - Earliest claimed: 2012-05-14 - Assignees: Gauss Surgical, Inc. - Applicants: Gauss Surgical, Inc. - Inventors: Siddarth Satish; Ali Zandifar; Kevin J Miller - Web page: https://patentgrep.com/patent/US10863933B2 ## CPC - A61B 5/14535: {for measuring haematocrit} - A61B 5/0082: {adapted for particular medical purposes} - A61B 5/02028: {Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction} - A61B 5/02042: {Determining blood loss or bleeding, e.g. during a surgical procedure} - A61B 5/4848: {Monitoring or testing the effects of treatment, e.g. of medication} - A61B 5/4875: {Hydration status, fluid retention of the body} - A61B 5/7278: {Artificial waveform generation or derivation, e.g. synthesizing signals from measured signals} - G01N 33/49: Blood {(chemical methods for determining blood cell populations G01N33/5094; chemical analysis of blood groups or blood types G01N33/80)} - A61B 5/742: {using visual displays (displays for heart-related electrical signals, e.g. ECG, A61B5/339)} - A61B 2576/00: Medical imaging apparatus involving image processing or analysis (A61B1/00009, A61B6/52 and A61B8/52 take precedence) - G01N 2015/1472: {with colour} - G16H 30/40: for processing medical images, e.g. editing - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q) - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract One variation of the method for managing blood loss of a patient includes: receiving an image of a physical sample; extracting a feature from an area of the image corresponding to the physical sample; estimating a blood volume indicator of the physical sample according to the extracted feature; estimating a patient blood loss based on the blood volume indicator; estimating a euvolemic patient hematocrit based on an estimated patient blood volume and the estimated patient blood loss; receiving a measured patient hematocrit; and generating a volemic status indicator based on a comparison between the measured patient hematocrit and the estimated euvolemic patient hematocrit. ## Claims ### Claim 1 A method for managing blood loss of a patient, comprising: tracking a quantity of a fluid administered to the patient intravenously; receiving an image of a physical sample; extracting a feature from an area of the image correlated with the physical sample; estimating a red blood cell content of the physical sample based on the extracted feature; estimating an extracorporeal blood content of the physical sample based on the estimated red blood cell content of the physical sample; and estimating a hematocrit of the patient based on a previous hematocrit of the patient, the quantity of the fluid administered to the patient, and the estimated extracorporeal blood content of the physical sample. ### Claim 2 (depends on 1) The method of claim 1, wherein tracking the quantity of the fluid administered to the patient intravenously comprises tracking the quantity of a fluid of a known composition administered to the patient according to a transfusion rate, wherein estimating hematocrit of the patient comprises estimating the hematocrit of the patient further based on the known composition of the fluid. ### Claim 3 (depends on 1) The method of claim 1, wherein extracting the feature from the area of the image correlated with the physical sample comprises extracting a subset of pixels from a set of pixels within the area of the image. ### Claim 4 (depends on 3) The method of claim 3, wherein receiving the image of the physical sample comprises receiving an image of a surgical sponge gauze and correlating a time stamp of the image with a time of use of the surgical sponge gauze, wherein estimating the extracorporeal blood content of the physical sample comprises converting the estimated red blood cell content of the physical sample into an extracorporeal blood volume according to a patient hematocrit estimated at a time approximate the time of use of the surgical sponge gauze. ### Claim 5 (depends on 1) The method of claim 1, wherein receiving the image of the physical sample comprises receiving a set of sequential images of a surgical suction canister, wherein estimating the extracorporeal blood content of the physical sample comprises estimating the extracorporeal blood content of the surgical suction canister according to estimates of the volume of the surgical suction canister based on each image in the set of sequential images, estimated hematocrits of the patient based on each image in the set of sequential images, and estimated red blood cell contents of the surgical suction canister based on each image in the set of sequential images over time. ### Claim 6 (depends on 3) The method of claim 3, wherein estimating the red blood cell content of the physical sample comprises matching the subset of pixels with a template image in a library of template images. ### Claim 7 (depends on 6) The method of claim 6, wherein the template images include pixels tagged with known hemoglobin or red blood cell content. ### Claim 8 (depends on 3) The method of claim 3, wherein extracting the feature from the area of the image comprises extracting at least one feature of the subset of pixels, and estimating the red blood cell content of the physical sample comprises transforming the at least one feature into a red blood cell content of the physical sample according to a parametric model. ### Claim 9 (depends on 8) The method of claim 8, wherein the parametric model relates the at least one extracted feature to a hemoglobin concentration value correlatable to an estimated red blood cell content. ### Claim 10 (depends on 1) The method of claim 1, wherein the extracted feature is a color-related value. ### Claim 11 (depends on 1) The method of claim 1, wherein estimating the extracorporeal blood content comprises estimating an extracorporeal blood volume based on the estimated red blood cell content and a static patient hematocrit value. ### Claim 12 (depends on 1) The method of claim 1, wherein estimating the extracorporeal blood content comprises estimating a blood volume based on the estimated red blood cell content and a dynamic patient hematocrit value. ### Claim 13 (depends on 1) The method of claim 1, further comprising tracking the estimated hematocrit of the patient over time. ### Claim 14 (depends on 1) The method of claim 1, further comprising triggering an alarm in response to the estimated hematocrit of the patient being outside a predefined range. ### Claim 15 (depends on 1) The method of claim 1, further comprising tracking total estimated extracorporeal blood content across multiple physical samples. ### Claim 16 (depends on 15) The method of claim 15, further comprising triggering an alarm in response to the total estimated extracorporeal blood content being outside an acceptable range. ### Claim 17 (depends on 1) The method of claim 1, further comprising displaying the estimated hematocrit of the patient.