Towards MR-Based Trochleoplasty Planning

TL;DR

This paper introduces a novel MRI-based pipeline that generates high-resolution, patient-specific 3D models of the trochlear region to improve planning for trochleoplasty surgeries, reducing radiation and enhancing surgical outcomes.

Contribution

The authors develop a pipeline combining super-resolution MRI, segmentation, and a diffusion model to produce detailed 3D pseudo-healthy trochlear morphologies without needing CT scans.

Findings

Generated sub-millimeter 3D shapes suitable for surgical planning

Significant improvements in sulcus angle and trochlear groove depth

Pipeline reduces radiation by eliminating the need for CT scans

Abstract

To treat Trochlear Dysplasia (TD), current approaches rely mainly on low-resolution clinical Magnetic Resonance (MR) scans and surgical intuition. The surgeries are planned based on surgeons experience, have limited adoption of minimally invasive techniques, and lead to inconsistent outcomes. We propose a pipeline that generates super-resolved, patient-specific 3D pseudo-healthy target morphologies from conventional clinical MR scans. First, we compute an isotropic super-resolved MR volume using an Implicit Neural Representation (INR). Next, we segment femur, tibia, patella, and fibula with a multi-label custom-trained network. Finally, we train a Wavelet Diffusion Model (WDM) to generate pseudo-healthy target morphologies of the trochlear region. In contrast to prior work producing pseudo-healthy low-resolution 3D MR images, our approach enables the generation of sub-millimeter resolved 3D shapes compatible for pre- and intraoperative use. These can serve as preoperative blueprints for reshaping the femoral groove while preserving the native patella articulation. Furthermore, and in contrast to other work, we do not require a CT for our pipeline - reducing the amount of radiation. We evaluated our approach on 25 TD patients and could show that our target morphologies significantly improve the sulcus angle (SA) and trochlear groove depth (TGD). The code and interactive visualization are available at https://wehrlimi.github.io/sr-3d-planning/.