US-20260128165-A1 - MACHINE VISION INSTRUMENT RECONCILIATION AND USAGE PREDICTION IN THE SURGICAL OPERATING ROOM

US20260128165A1US 20260128165 A1US20260128165 A1US 20260128165A1US-20260128165-A1

Abstract

A system for reconciling instruments in an operating room with sterile instrument ingress and egress staging zones, in which each zone is equipped with an imaging device for machine vision, bar code reading, or the like. The system utilizes a process for classifying and counting instruments based on imaging device data, and may include a graphical user interface with separate interface devices for sterile and non-sterile personnel. An active and real-time reconciliation log may be provided to track instruments and resources still in the sterile field, and hence at risk of remaining in a patient's wound. A subsequent egress sub-stage analysis for counting instruments used versus not used in the procedure may be performed and the results thereof aggregated to generate or update a predictive model to anticipate the likely instruments and other resources needed for future surgical procedures of the same type, facilitating efficient instrument selection and preparation.

Inventors

William E. Butler
Brian V. NAHED
Elizabeth LAMB
Hector Andrade-Loarca

Assignees

William E. Butler
Brian V. NAHED
Elizabeth LAMB
Hector Andrade-Loarca

Dates

Publication Date: 20260507
Application Date: 20251106

Claims (20)

1 . A system for managing a plurality of instruments in a sterile field, the system comprising: at least one imaging device; one or more processors; and a non-transitory computer readable storage medium coupled to the one or more processors and storing instructions thereon that, when executed by the one or more processors, cause the one or more processors to: obtain one or more images of the plurality of instruments via the at least one imaging device upon ingress of the plurality of instruments into the sterile field; obtain one or more images of a set of the plurality of instruments via the at least one imaging device upon egress of the set of the plurality of instruments from the sterile field; generate an ingress inventory based on the one or more images obtained upon ingress of the plurality of instruments into the sterile field; generate an egress inventory based on the one or more images obtained upon egress of the set of the plurality of instruments from the sterile field; reconcile the ingress and egress inventories by comparing the ingress and egress inventories to determine whether or not one or more instruments were left in the sterile field; and output for display a result of the reconciliation to a user.
2 . The system of claim 1 , wherein the at least one imaging device includes a first imaging device configured to obtain one or images of the plurality of instruments upon ingress of the plurality of instruments into the sterile field, and a second imaging device configured to obtain one or more images of the set of the plurality of instruments upon egress of the set of the plurality of instruments from the sterile field.
3 . The system of claim 2 , wherein the instructions, when executed by the one or more processors, further cause the one or more processors to: identify each instrument introduced into the sterile field based on the one or more images obtained by the first imaging device upon ingress of the plurality of instruments to the sterile field; and identify each instrument removed from the sterile field based on the one or more images obtained by the second imaging device upon egress of the set of the plurality of instruments from the sterile field.
4 . The system of claim 3 , wherein to identify each instrument introduced and removed from the sterile field, the instructions, when executed by the one or more processors, further cause the one or more processors to: input the one or more images obtained by the first imaging device upon ingress to a first machine learning model trained to identify instruments from image data; and input the one or more images obtained by the second imaging device to a second machine learning model trained to identify instruments from image data.
5 . The system of claim 4 , wherein at least one of the first and second machine learning models is trained to distinguish between visually similar instruments based on the presence or absence of a decorative discriminator applied to one or more of the instruments.
6 . The system of claim 2 , wherein the at least one imaging device further comprises a third imaging device configured to read scannable codes carried by instruments, wherein the instructions, when executed by the one or more processors, further cause the one or more processors to: identify each instrument introduced into the sterile field based on a scannable code read by the third imaging device upon ingress or based on one or more images obtained by the first imaging device upon ingress; and identify each instrument removed from the sterile field based on a scannable code read by the third imaging device upon egress or based on the one or more images obtained by the second imaging device upon egress.
7 . The system of claim 6 , wherein the instructions, when executed by the one or more processors, further cause the one or more processors to: determine a number of instruments in a package based on a scannable code on the package read by the third imaging device upon ingress into the sterile field; determine a number of instruments in the package based on one or more images obtained by the first imaging device; and alert a user when the number of instruments determined by the system based on the scannable code differs from the number of instruments determined by the system based on the one or more images.
8 . The system of claim 1 , wherein the instructions, when executed by the one or more processors, further cause the one or more processors to prompt a user for confirmation that the instruments identified by the system upon ingress or egress are counted only once.
9 . The system of claim 1 , further comprising displaying, on a display screen, a graphical user interface with separate controls for sterile and non-sterile users.
10 . The system of claim 9 , further comprising: a sterile ingress computer for one or more sterile users to interact with the graphical user interface; and an egress computer for one or more non-sterile users to interact with the graphical user interface.
11 . The system of claim 2 , wherein the instructions, when executed by the one or more processors, further cause the one or more processors to obtain, using the second imaging device, images of the instruments with an optical filter adapted to detect hemoglobin, other body fluid, or body tissue; and classify the set of instruments identified by the machine learning model during egress as used or not-used based on the presence or absence, respectively, of body fluid and tissue on the instruments.
12 . The system of claim 11 , wherein the instructions, when executed by the one or more processors, further cause the one or more processors to generate or update a predictive model that predicts which instruments are likely to be used in a procedure based on a classification of instruments as used or not-used.
13 . The system of claim 12 , wherein the predictive model comprises an ordinal logistic regression configured to provide a probability value corresponding to the number of instruments predicted to be used in a particular surgical procedure.
14 . The system of claim 12 , wherein the predictive model comprises a large language model trained using a data set that includes usage data based on the classification of instruments used in a particular surgical procedure.
15 . The system of claim 12 , wherein the predictive model comprises a multivariate logistic regression configured to predict the number of instruments used in a particular surgical procedure.
16 . A method for managing a plurality of instruments in a sterile field, the method comprising: obtaining, using at least one imaging device, one or more images of the plurality of instruments upon ingress of the plurality of instruments into the sterile field; obtaining, using the at least one imaging device, one or more images of a set of the plurality of instruments upon egress of the set of the plurality of instruments from the sterile field; generating, using one or more processors, an ingress inventory based on the one or more images obtained upon ingress of the plurality of instruments into the sterile field; generating, using the one or more processors, an egress inventory based on the one or more images obtained upon egress of the set of the plurality of instruments from the sterile field; reconciling, using the one or more processors, the ingress and egress inventories by comparing the ingress and egress inventories to determine whether or not one or more instruments were left in the sterile field; and outputting, using a display device, a result of the reconciliation to a user.
17 . The method of claim 16 , wherein the at least one imaging device includes a first imaging device configured to obtain one or more images of the plurality of instruments upon ingress of the plurality of instruments into the sterile field, and a second imaging device configured to obtain one or more images of the set of the plurality of instruments upon egress of the set of the plurality of instruments from the sterile field.
18 . The method of claim 16 , further comprising: identifying, using the one or more processors, each instrument introduced into the sterile field based on the one or more images obtained by the first imaging device upon ingress of the plurality of instruments to the sterile field; and identifying, using the one or more processors, each instrument removed from the sterile field based on the one or more images obtained by the second imaging device upon egress of the set of the plurality of instruments from the sterile field.
19 . The method of claim 18 , wherein to identify each instrument introduced and removed from the sterile field, the one or more processors are further used to: input the one or more images obtained by the first imaging device upon ingress to a first machine learning model trained to identify instruments from image data; and input the one or more images obtained by the second imaging device to a second machine learning model trained to identify instruments from image data.
20 . The method of claim 19 , wherein at least one of the first and second machine learning models is trained to distinguish between visually similar instruments based on the presence or absence of a decorative discriminator applied to one or more of the instruments.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Provisional Ser. No. 63/716,886, filed Nov. 6, 2024 and titled MACHINE VISION INSTRUMENT RECONCILIATION AND USAGE PREDICTION IN THE SURGICAL OPERATING ROOM, which is incorporated by reference herein in its entirety. FIELD OF THE INVENTION The present invention relates generally to a system, method, and computer program product for reconciliation and/or usage prediction of instruments in a surgical operating room, and more particularly, using machine vision or other imaging techniques to identify, track, and predict usage of surgical instruments. BACKGROUND OF THE INVENTION When a surgical procedure is scheduled, an instrument pick list is delivered to the surgery supply department. The pick list is a compilation of the number and types of sterile surgical instruments likely to be used in the procedure. A surgery supply department may aggregate the instruments in the pick list into a case cart to be sterilized and delivered to the scheduled operating room in advance of the surgical procedure. During the surgical procedure, various team members provide assistance to one or more operators who perform the procedure. While some team members may stay within sterilized environments, other team members may not. As an example, a surgical technician performs within the sterile environment while a circulating nurse and anesthesia team perform in the operating room, but outside of the actual sterile environment. Prior to the surgical procedure, the operating room staff, primarily the surgical technician and the circulating nurse, open, inspect, and ensure that the correct type and number of surgical instruments are present. Counting surgical instruments and disposables such as sutures helps to reduce a number of risks to a patient, such as, for example, the risk of retaining an instrument in the patient's body (e.g., in the abdomen or the thorax). Retaining an instrument in the patient's body can be dangerous for any number of reasons, including a potentially imminent risk when an intraoperative MRI is used during the surgical procedure, where instruments must be removed from the magnetic field. If start and end counts of the surgical instruments and/or disposables match, then no instrument or disposable is assumed to have been retained in the body. If the counts do not match, then an instrument or disposable is considered to have been left in a body cavity of the patient. In such an event, the instruments or disposables are recounted, and if they still do not match, then the sterile field, including the body cavity of the patient, is searched for the retained instrument. Such searching may be assisted by an x-ray machine if the instrument is radio opaque (i.e., if it can be seen on X-rays). In practice, many surgical instruments supplied in sterile form to an operating room are not actually used during the surgical procedure. Supplying surgical instruments that are not ultimately utilized can be costly and inefficient, as they require additional time to sterilize, understand, include, store, and account for them. Conversely, instruments that are required for the surgical procedure but not pre-supplied are often identified before or during the surgical procedure. In this scenario, operating room staff are required to retrieve the instrument(s) needed while the patient is under anesthesia, often with an open wound. Such delays can unnecessarily decrease the safety of the surgical procedure by lengthening the period of anesthesia needed and/or the length of time a wound or incision is left open and exposed. If surgical instrument(s) are not present yet urgently needed, then the delay can also adversely impact patient safety by increasing the risk of blood loss, infection, or other complication. BRIEF SUMMARY OF THE INVENTION The present disclosure relates generally to a machine vision system and process for counting surgical instruments or disposables that ingress to a sterile or surgical field and that egress from the sterile or surgical field as a procedure nears completion, for maintaining detailed logs of the ingress and egress times of instruments, and for reconciling the ingress and egress machine vision logs. Additionally, a computerized predictive usage model may be generated based on the machine vision logs to increase the efficiency of future preparation and supply for sterile medical and surgical procedures. Methods, systems, and computer program products are provided for managing a plurality of instruments in a sterile field. In accordance with one aspect of the invention, the system may comprise at least one imaging device; and a non-transitory computer readable storage medium coupled to the one or more processors and storing instructions thereon that, when executed by the one or more processors, cause the one or more processors to obtain one or more images of the plurality of instruments via the at least one imaging device upon