US-20260127743-A1 - COMPUTATIONAL SIMULATIONS OF ANATOMICAL STRUCTURES AND BODY SURFACE ELECTRODE POSITIONING

US20260127743A1US 20260127743 A1US20260127743 A1US 20260127743A1US-20260127743-A1

Abstract

A method may include identifying a simulated three-dimensional representation corresponding to an internal anatomy of a subject based on a match between a computed two-dimensional image corresponding to the simulated three-dimensional representation and a two-dimensional image depicting the internal anatomy of the subject. Simulations of the electrical activities measured by a recording device with standard lead placement and nonstandard lead placement may be computed based on the simulated three-dimensional representation. A clinical electrogram and/or a clinical vectorgram for the subject may be corrected based on a difference between the simulations of electrical activities to account for deviations arising from patient-specific lead placement as well as variations in subject anatomy and pathophysiology.

Inventors

David E. Krummen
Christopher J. T. Villongco

Assignees

THE VEKTOR GROUP, INC.
THE REGENTS OF THE UNIVERSITY OF CALIFORNIA

Dates

Publication Date: 20260507
Application Date: 20250926

Claims (20)

1 . A system, comprising: at least one processor; and at least one memory including program code which when executed by the at least one processor provides operations comprising: identifying, in a library including a plurality of simulated three-dimensional representations, a first simulated three-dimensional representation corresponding to a first internal anatomy of a first subject, the first simulated three-dimensional representation being identified based at least on a match between a first computed two-dimensional image corresponding to the first simulated three-dimensional representation and a two-dimensional image depicting the first internal anatomy of the first subject; and generating an output including the simulated three-dimensional representation of the first internal anatomy of the first subject.
2 . The system of claim 1 , wherein the operations further comprise: generating the library including by generating, based on a first three-dimensional representation of a second internal anatomy of a second subject, the first simulated three-dimensional representation, the first simulated three-dimensional representation being generated by at least varying one or more attributes of the second internal anatomy of the second subject.
3 . The system of claim 2 , wherein the one or more attributes include a skeletal property, an organ geometry, a musculature, and/or a subcutaneous fat distribution.
4 . The system of claim 2 , wherein the library is further generated to include the first three-dimensional representation of the second internal anatomy of the second subject and/or a second three-dimensional representation of a third internal anatomy of a third subject having at least one different attribute than the second internal anatomy of the second subject.
5 . The system of claim 2 , wherein the generating of the library further includes generating, based at least on the first simulated three-dimensional representation, the first computed two-dimensional image.
6 . The system of claim 5 , wherein the generating of the first computed two-dimensional image includes determining, based at least on a density and/or a transmissivity of one or more tissues included in the first simulated three-dimensional representation, a quantity of radiation able to pass through the one or more tissues included in the first simulated three-dimensional representation to form the first computed two-dimensional image.
7 . The system of claim 2 , wherein the first three-dimensional representation of the second internal anatomy of the second subject comprises a computed tomography (CT) scan and/or a magnetic resonance imaging (MRI) scan depicting the second internal anatomy of the second subject.
8 . The system of claim 1 , wherein the first simulated three-dimensional representation is further associated with a diagnosis of a condition depicted in the first simulated three-dimensional representation, and wherein the output is further generated to include the diagnosis.
9 . The system of claim 1 , wherein the operations further comprise: determining a first similarity index indicating a closeness of the match between the first computed two-dimensional image and the two-dimensional image depicting the first internal anatomy of the first subject, the first simulated three-dimensional representation identified as corresponding to the first internal anatomy of the first subject based at least on the first similarity index exceeding a threshold value and/or the first similarity index being greater than a second similarity index indicating a closeness of a match between a second computed two-dimensional image corresponding to a second simulated three-dimensional representation and the two-dimensional image depicting the first internal anatomy of the first subject.
10 . The system of claim 1 , wherein the first computed two-dimensional image is determined to match the two-dimensional image depicting the first internal anatomy of the first subject by at least applying an image comparison technique.
11 . The system of claim 10 , wherein the image comparison technique comprises scale invariant feature transform (SIFT), speed up robust feature (SURF), binary robust independent elementary features (BRIEF), and/or oriented FAST and rotated BRIEF (ORB).
12 . The system of claim 10 , wherein the image comparison technique comprises a machine learning model.
13 . The system of claim 12 , wherein the machine learning model comprises an autoencoder and/or a neural network.
14 . The system of claim 1 , wherein the operations further comprise: determining, based at least on the two-dimensional image depicting the first internal anatomy of the first subject, a lead placement for a recording device configured to measure an electrical activity of an organ, the recording device including one or more leads configured to detect a change in voltage on a body surface corresponding to the electrical activity of the organ; and generating, based at least on the lead placement and the first simulated three-dimensional representation of the first internal anatomy of the first subject, a simulation of the electrical activity measured by the recording device.
15 . The system of claim 14 , wherein the simulation of the electrical activity measured by the recording device includes a signal detected by each of the one or more leads included in the recording device.
16 . The system of claim 14 , wherein the recording device is configured to perform an electrocardiography (ECG) and/or an electroencephalography (EEG).
17 . The system of claim 14 , wherein the output is further generated to include the lead placement and/or the simulation of the electrical activity measured by the recording device.
18 . The system of claim 1 , wherein the identifying of the first simulated three-dimensional representation further includes eliminating a second simulated three-dimensional representation based at least on a mismatch between a demographics and/or a vital statistics of the first subject and a second subject depicted in the second simulated three-dimensional representation.
19 . The system of claim 1 , wherein the identifying of the first simulated three-dimensional representation further includes eliminating a second simulated three-dimensional representation based at least on a condition depicted in the second simulated three-dimensional representation being inconsistent with one or more symptoms of the first subject.
20 . The system of claim 1 , wherein the operations further comprise: providing, to a client, the output including by sending, to the client, at least a portion of the output and/or generating a user interface configured to display at least the portion of the output at the client.

Description

CROSS-REFERENCE TO RELATED APPLICATION(S) This application is a continuation of U.S. Application No. Ser. No. 17/930,155, filed on Sep. 7, 2022, entitled “COMPUTATIONAL SIMULATIONS OF ANATOMICAL STRUCTURES AND BODY SURFACE ELECTRODE POSITIONING,” which is a continuation of U.S. Application No. Ser. No. 16/785,530, filed on Feb. 7, 2022, entitled “COMPUTATIONAL SIMULATIONS OF ANATOMICAL STRUCTURES AND BODY SURFACE ELECTRODE POSITIONING,” which is a continuation of International Application No. PCT/US 19/40740, filed on Jul. 5, 2019, entitled “COMPUTATIONAL SIMULATIONS OF ANATOMICAL STRUCTURES AND BODY SURFACE ELECTRODE POSITIONING,” which claims priority to U.S. Provisional Application No. 62/694,401 entitled “COMPUTATIONAL THORACIC AND ECG TRANSFORM VIA 2D RADIOGRAPHY” and filed on Jul. 5, 2018, the disclosure of each of these applications is incorporated herein by reference in its entirety. TECHNICAL FIELD The subject matter described herein relates generally to medical imaging and more specifically to computationally simulating images of anatomical structures and electrical activity to permit the accurate determination of subject 3-dimensional anatomy and electrical rhythm diagnosis and source localization. BACKGROUND Medical imaging refers to techniques and processes for obtaining data characterizing a subject's internal anatomy and pathophysiology including, for example, images created by the detection of radiation either passing through the body (e.g. x-rays) or emitted by administered radiopharmaceuticals (e.g. gamma rays from technetium (99mTc) medronic acid given intravenously). By revealing internal anatomical structures obscured by other tissues such as skin, subcutaneous fat, and bones, medical imagining is integral to numerous medical diagnosis and/or treatments. Examples of medical imaging modalities include 2-dimensional imaging such as: x-ray plain films; bone scintigraphy; and thermography, and 3-dimensional imaging modalities such as: magnetic resonance imaging (MRI); computed tomography (CT), cardiac sestamibi scanning, and positron emission tomography (PET) scanning. SUMMARY Systems, methods, and articles of manufacture, including computer program products, are provided for computationally simulating a three-dimensional representation of an anatomical structure. In some example embodiments, there is provided a system that includes at least one processor and at least one memory. The at least one memory may include program code that provides operations when executed by the at least one processor. The operations may include: identifying, in a library including a plurality of simulated three-dimensional representations, a first simulated three-dimensional representation corresponding to a first internal anatomy of a first subject, the first simulated three-dimensional representation being identified based at least on a match between a first computed two-dimensional image corresponding to the first simulated three-dimensional representation and a two-dimensional image depicting the first internal anatomy of the first subject; and generating an output including the simulated three-dimensional representation of the first internal anatomy of the first subject. In some variations, one or more features disclosed herein including the following features can optionally be included in any feasible combination. The operations may further include generating the library including by generating, based on a first three-dimensional representation of a second internal anatomy of a second subject, the first simulated three-dimensional representation. The first simulated three-dimensional representation may be generated by at least varying one or more attributes of the second internal anatomy of the second subject. The one or more attributes may include a skeletal property, an organ geometry, a musculature, and/or a subcutaneous fat distribution. The library may be further generated to include the first three-dimensional representation of the second internal anatomy of the second subject and/or a second three-dimensional representation of a third internal anatomy of a third subject having at least one different attribute than the second internal anatomy of the second subject. In some variations, the generating of the library may include generating, based at least on the first simulated three-dimensional representation, the first computed two-dimensional image. The generating of the first computed two-dimensional image may include determining, based at least on a density and/or a transmissivity of one or more tissues included in the first simulated three-dimensional representation, a quantity of radiation able to pass through the one or more tissues included in the first simulated three-dimensional representation to form the first computed two-dimensional image. In some variations, the first three-dimensional representation of the second internal anatomy of the second subject may include a computed tomography (C