Patient-Specific Spinal Instruments for Decompression and Implant Placement
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Solution Overview
Problem
Conventional technologies in orthopedics lack the capability to utilize large data sets for generating patient-specific treatments and surgical interventions effectively, particularly in addressing spinal nerve compression, which often results in inadequate treatment outcomes due to limited and irrelevant patient data.
Innovation Solution
A system and method for providing patient-specific medical care by comparing a patient's data to a plurality of reference patient data sets, selecting subsets based on similarity and favorable outcomes, and generating decompression plans, surgical kits, and instrument designs to optimize treatment protocols, including the use of virtual models and predictive analytics to design patient-specific instruments and implants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional technologies are used for spinal treatment planning, then treatment protocols are established using limited available patient data, but the treatment outcomes are inadequate due to lack of correlation with large data sets and historical outcomes
Solution Approach 1:
The system performs preliminary actions by pre-computing and storing treatment outcomes from large data sets and historical patient records before actual treatment planning. Treatment protocols are pre-optimized by analyzing correlations between patient characteristics and treatment outcomes, so that when a new patient is evaluated, the system can quickly retrieve and apply the most suitable pre-determined treatment protocol rather than starting from scratch with limited data.
Solution Approach 2:
The system creates virtual models that are copies or representations of actual patient anatomy and characteristics. These virtual models allow the system to simulate and evaluate multiple treatment scenarios without risking actual patient safety. The virtual copies enable comprehensive analysis of treatment outcomes by testing various approaches on replicated patient data before implementing the optimal treatment in reality.
2Reliability
If spinal implants are used to relieve nerve compression, then treatment effectiveness is improved, but the difficulty of implanting devices increases due to complex anatomical considerations and precise placement requirements
Solution Approach 1:
The system performs preliminary surgical planning and virtual implant placement before actual surgery. Treatment protocols are pre-determined by analyzing patient-specific anatomy against large data sets, and the optimal implant type, size, and placement position are identified in advance. This preliminary planning reduces intraoperative decision-making complexity and guides the surgical team through the implantation process step-by-step.
Solution Approach 2:
The system introduces virtual models and simulation environments as intermediaries between the surgeon's intent and the actual implantation procedure. These virtual intermediaries allow for testing and optimization of implant placement strategies without directly affecting the patient. The system acts as a mediator by translating complex anatomical considerations into simplified, actionable surgical guidance that reduces implantation difficulty.
Data Source
AI summary
Systems and methods for designing and implementing patient-specific surgical procedures and/or medical devices are disclosed. In some embodiments, a method includes receiving a patient data set of a patient. The patient data set is compared to a plurality of reference patient data sets, wherein each of the plurality of reference patient data sets is associated with a corresponding reference patient. A subset of the plurality of reference patient data sets is selected based, at least partly, on similarity to the patient data set and treatment outcome of the corresponding reference patient. Based on the selected subset, at least one surgical procedure or medical device design for treating the patient is generated.