Patient-Specific Virtual Spine Straightening and Vertebra Inpainting: An Automatic Framework for Osteoplasty Planning

Christina Bukas, Bailiang Jian, Luis Francisco Rodríguez Venegas, Francesca De Benetti, Sebastian Rühling, Anjany Sekuboyina, Jens Gempt, Jan Stefan Kirschke, Marie Piraud, Johannes Oberreuter, Nassir Navab, Thomas Wendler

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Symptomatic spinal vertebral compression fractures are often treated by osteoplasty where a cement-like material is injected into the bone to stabilize the fracture, restore the vertebral body height and alleviate pain. Leakage is a common complication and may occur due to too much cement being injected. Here, we propose an automated patient-specific framework that can allow physicians to calculate an upper bound of the volume of cement for particular types of VCFs and estimate the optimal outcome of osteoplasty. The framework uses the patient CT scan and the segmentation label of the fractured vertebra to build a virtual healthy spine. Firstly, the fractured spine is segmented with a three-step Convolutional Neural Network architecture. Next, a per-vertebra rigid registration to a healthy reference spine restores its curvature. Finally, a GAN-based inpainting approach replaces the fractured vertebra with an estimation of its original shape, the volume of which we use as an estimate of the original healthy vertebra volume. As a clinical application, we derive an upper bound on the amount of bone cement for the injection. We evaluate our framework by comparing the virtual vertebrae volumes of ten patients to their healthy equivalent and report an error of 3.88 ± 7.63%. The presented pipeline offers a first approach to a personalized automatic high-level framework for planning osteoplasty procedures.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2021 - 24th International Conference, Proceedings
EditorsMarleen de Bruijne, Marleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert
PublisherSpringer Science and Business Media Deutschland GmbH
Pages529-539
Number of pages11
ISBN (Print)9783030872014
DOIs
StatePublished - 2021
Event24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021 - Virtual, Online
Duration: 27 Sep 20211 Oct 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12904 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021
CityVirtual, Online
Period27/09/211/10/21

Keywords

  • Deformable registration
  • Inpainting
  • Spine osteoplasty

Fingerprint

Dive into the research topics of 'Patient-Specific Virtual Spine Straightening and Vertebra Inpainting: An Automatic Framework for Osteoplasty Planning'. Together they form a unique fingerprint.

Cite this