AI-Driven Spinal Implant Planning and Intraoperative Tracking

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Solution Overview

Problem

Current spinal surgery techniques lack precision in implant selection and surgical planning, often resulting in suboptimal spinal curvature correction due to the inability to accurately match spinal implants with patient-specific anatomy, leading to variable surgical outcomes.

Innovation Solution

A system utilizing predictive modeling, machine learning, and artificial intelligence to analyze preoperative medical images and spinopelvic parameters, generating patient-specific spinal treatment plans and intraoperative tracking to ensure precise implantation of spinal rods and screws, aligning with predetermined surgical plans in real-time.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional spinal surgery techniques are used, then surgical procedures can be performed, but implant selection and surgical planning lack precision resulting in suboptimal spinal curvature correction

Engineering Contradiction:

Improvespinal curvature correction accuracyVSAvoidsurgical outcome consistency

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The system performs preoperative planning and simulation before surgery to determine optimal implant selection and positioning. Virtual surgical planning allows surgeons to preview and adjust surgical strategies, implant configurations, and expected outcomes before actual surgery, thereby improving precision and reliability of surgical results

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system incorporates intraoperative tracking and real-time feedback mechanisms that compare actual surgical progress against the preoperative plan. This allows for immediate corrections and adjustments during surgery, ensuring that the final outcome matches the optimized surgical plan and improving both precision and consistency

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If generic spinal implants are used, then implantation can be performed, but the ability to accurately match spinal implants with patient-specific anatomy is limited

Engineering Contradiction:

Improveimplant-anatomy matching precisionVSAvoidpatient-specific implant customization

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system creates virtual copies and digital models of the patient's specific spinal anatomy through imaging and 3D reconstruction. These digital twins allow for precise measurement, planning, and simulation without requiring physical custom implants, achieving patient-specific matching through information copying rather than physical customization

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The system develops a universal software platform that can handle various implant types, surgical approaches, and patient anatomies through a single integrated system. This multi-functional platform provides patient-specific planning capabilities for different spinal conditions and implant configurations without requiring separate specialized tools for each case

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Reliability

If manual surgical planning is used, then surgical procedures can be performed, but variable surgical outcomes result due to lack of real-time guidance

Engineering Contradiction:

Improvesurgical outcome consistencyVSAvoidsurgical efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system implements intraoperative tracking with real-time feedback that continuously monitors surgical progress against the preoperative plan. This feedback loop provides immediate guidance to surgeons, ensuring consistent outcomes while maintaining surgical efficiency through automated tracking rather than manual measurements

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system replaces manual surgical planning and intraoperative measurement with automated computer-based planning and tracking systems. This substitution of mechanical/manual processes with digital automation improves both consistency of outcomes and surgical efficiency by reducing human error and time consumption

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS11877801B2Systems, methods, and devices for developing patient-specific spinal implants, treatments, operations, and/or procedures

Publication Date: 2024.01.23 MEDICREA INT SA

AI summary

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.