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Towards Visualizing Early-stage Osteonecrosis using Intraoperative Imaging Modalities.

Mingxu Liu¹, Alejandro Martin-Gomez^1,2, Julius K Oni³

¹Biomechanical- and Image-Guided Surgical Systems (BIGSS), Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.

Computer Methods in Biomechanics and Biomedical Engineering. Imaging & Visualization

|January 5, 2024

Summary

This summary is machine-generated.

This study presents a novel framework for localizing osteonecrosis of the femoral head (ONFH) using CT scans. The method aids in visualizing necrotic lesions, potentially improving surgical planning for ONFH treatment.

Keywords:

Computer Assisted Intervention Deep Learning Image Guided Intervention Registration Segmentation Visualization

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Area of Science:

Biomedical Engineering
Medical Imaging
Orthopedic Surgery

Background:

Osteonecrosis of the Femoral Head (ONFH) is a debilitating condition leading to bone cell death and potential hip replacement.
Early detection is crucial, but current intra-operative imaging like fluoroscopy often fails to identify early-stage ONFH lesions.
Accurate localization of necrotic areas is challenging, hindering timely surgical intervention.

Purpose of the Study:

To develop and validate a novel framework for localizing necrotic lesions in Computed Tomography (CT) images of the femoral head.
To enable visualization of ONFH lesions in CT, bridging the gap between MRI diagnosis and intra-operative guidance.
To investigate the framework's feasibility for integration into surgical workflows for conditions like ONFH.

Main Methods:

Utilized Deep Learning for automatic segmentation of femur, pelvis, and necrotic lesions in MRI scans.
Performed semi-automatic segmentation of these anatomies (excluding necrotic lesions) in CT scans.
Implemented pairwise registration of segmented anatomies from MRI and CT to localize necrosis within CT images.

Main Results:

The framework successfully segmented anatomical structures (femur, pelvis) in both MRI and CT.
Accurate registration of corresponding anatomical volumes was achieved.
Demonstrated the capability to visualize and localize ONFH lesions in CT and generated X-rays.

Conclusions:

The proposed framework enables accurate localization and visualization of osteonecrosis of the femoral head in CT scans.
This technology has the potential to enhance intra-operative guidance for procedures like core decompression.
The framework facilitates improved surgical planning and treatment for early-stage ONFH.