Generating 3D Pseudo-Healthy Knee MR Images to Support Trochleoplasty Planning
Michael Wehrli, Alicia Durrer, Paul Friedrich, Volodimir, Buchakchiyskiy, Marcus Mumme, Edwin Li, Gyozo Lehoczky, Carol C., Hasler, Philippe C. Cattin

TL;DR
This paper introduces a Wavelet Diffusion Model to generate patient-specific pseudo-healthy knee MR images, aiding preoperative trochleoplasty planning by improving anatomical accuracy and surgical guidance.
Contribution
The study presents a novel application of Wavelet Diffusion Models for inpainting knee MR images, enabling personalized, anatomically plausible pseudo-healthy scans for surgical planning.
Findings
Significant improvement in sulcus angle and trochlear groove depth measurements.
Enhanced D'Jour classification accuracy after inpainting.
Potential to support minimally invasive trochleoplasty procedures.
Abstract
Purpose: Trochlear Dysplasia (TD) is a common malformation in adolescents, leading to anterior knee pain and instability. Surgical interventions such as trochleoplasty require precise planning to correct the trochlear groove. However, no standardized preoperative plan exists to guide surgeons in reshaping the femur. This study aims to generate patient-specific, pseudo-healthy MR images of the trochlear region that should theoretically align with the respective patient's patella, potentially supporting the pre-operative planning of trochleoplasty. Methods: We employ a Wavelet Diffusion Model (WDM) to generate personalized pseudo-healthy, anatomically plausible MR scans of the trochlear region. We train our model using knee MR scans of healthy subjects. During inference, we mask out pathological regions around the patella in scans of patients affected by TD, and replace them with their…
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Taxonomy
MethodsDiffusion · ALIGN · Inpainting
