Systems, methods, and devices for developing patient-specific spinal implants, treatments, operations, and/or procedures

Patent metadata

Field	Value
Publication number	US-2024115324-A1
Application number	US-202318545184-A
Country	US
Kind code	A1
Filing date	Dec 19, 2023
Priority date	Apr 2, 2019
Publication date	Apr 11, 2024
Grant date	—

Abstract

The disclosure herein relates to systems, methods, and devices for developing patient-specific spinal implants, treatments, operations, and/or procedures. In some embodiments, systems, methods, and devices described herein can comprise using artificial intelligence, machine learning, and/or predictive modeling to predict the outcome of a spinal surgery, one or more parameters of a spine of a patient after spinal surgery, for example after implantation of a spinal rod which can be patient-specific, and/or one or more parameters of one or more recommended patient-specific spinal rods. Furthermore, in some embodiments, systems, methods, and devices described herein can comprise intraoperative tracking for tracking and/or suggesting improvements during spinal surgery based on a pre-operatively determined surgical plan, for example in real-time or substantially real-time. In addition, in some embodiments, systems, methods, and devices described herein can comprise screw planning prior to spinal surgery.

First claim

What is claimed is:

1 . A computer-implemented method of predicting a surgical outcome a spinal surgery of a subject, the method comprising:
inputting, into a computer system, one or more preoperative inputs relating to the subject, wherein the one or more preoperative inputs comprise one or more preoperative medical images of a spine of the subject and one or more preoperative non-imaging data inputs of the subject; determining, using the computer system, one or more measurements from the inputted one or more preoperative medical images of the spine of the subject, wherein the one or more measurements comprise a position of one or more vertebrae of the spine of the subject; determining, using the computer system, one or more preoperative spinopelvic parameters based at least in part on the one or more determined measurements, wherein the one or more preoperative spinopelvic parameters comprise one or more of lumbar lordosis (LL), preoperative thoracic kyphosis (TK), pelvic incidence (PI), pelvic tilt (PT), or sagittal vertical axis (SVA) for one or more vertebrae; transforming, using the computer system, the determined one or more preoperative spinopelvic parameters to obtain one or more preoperative spinopelvic parameters in a frequency domain, wherein the transforming comprises applying a Fourier transformation to the determined one or more preoperative spinopelvic parameters; filtering, using the computer system, the one or more preoperative spinopelvic parameters in the frequency domain, wherein the filtering comprises filtering out one or more of the one or more preoperative spinopelvic parameters in the frequency domain comprising a frequency level above a predetermined threshold; applying, using the computer system, one or more predictive models to generate a predicted surgical outcome in the frequency domain based at least in part on the filtered one or more preoperative spinopelvic parameters in the frequency domain and the one or more preoperative non-imaging data inputs of the subject; and transforming, using the computer system, the generated predicted surgical outcome in the frequency domain to obtain a generated predictive surgical outcome in a spatial domain, wherein the transforming the generated predicted surgical outcome in the frequency domain comprises applying an inverse Fourier transformation to the generated predicted surgical outcome in the frequency domain, wherein the computer system comprises a computer processor and an electronic storage medium.

2 . The computer-implemented method of claim 1 , wherein the one or more predictive models comprises one or more of a generative adversarial network (GAN) algorithm, convolutional neural network (CNN) algorithm, or recurrent neural network (RNN) algorithm.

3 . The computer-implemented method of claim 1 , further comprising, generating, by the computer system, a preoperatively determined spinal surgical plan for the subject based at least in part on the generated predictive surgical outcome in the spatial domain.

4 . The computer-implemented method of claim 3 , wherein the generated preoperatively determined spinal surgical plan comprises one or more specifications of a spinal rod for implantation during the spinal surgery of the subject.

5 . The computer-implemented method of claim 1 , wherein the one or more measurements from the inputted one or more preoperative medical images of the spine of the subject are determined automatically by the computer system.

6 . The computer-implemented method of claim 1 , wherein the inputted one or more preoperative medical images of the spine of the subject comprises one or more sagittal x-ray images and one or more frontal x-ray images.

7 . The computer-implemented method of claim 1 , wherein the generated predictive surgical outcome in the spatial domain comprises one or more of one or more postoperative spinopelvic parameters or one or more specifications of a spinal rod to be implanted to the spine of the subject.

8 . The computer-implemented method of claim 1 , wherein the one or more preoperative inputs further comprise one or more specifications of a spinal rod proposed to be implanted to the spine of the subject.

Assignees

• Medicrea Int

Inventors

• Mosnier Thomas
• Senac Agathe
• Augagneur Céline
• Javelot Christophe Xavier Guillaume
• Sournac Denys

Classifications

• A61B34/30

  Surgical robots · CPC title

• A61B34/25

  User interfaces for surgical systems · CPC title

• A61B34/20

  Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis · CPC title

• A61B2034/2048

  using an accelerometer or inertia sensor · CPC title

• A61B2034/108

  Computer aided selection or customisation of medical implants or cutting guides · CPC title