Open-source image analysis tool for the identification and quantification of cortical interruptions and bone erosions in high-resolution peripheral quantitative computed tomography images of patients with rheumatoid arthritis

Mingjie Zhao, Justin J Tse, Michael T Kuczynski, Scott C Brunet, Ryan Yan, Klaus Engelke, Michiel Peters, Joop P van den Bergh, Bert van Rietbergen, Kathryn S Stok, Cheryl Barnabe, Yves Pauchard, Sarah L Manske*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Identification of bone erosions and quantification of erosion volume is important for rheumatoid arthritis diagnosis, and can add important information to evaluate disease progression and treatment effects. High-resolution peripheral quantitative computed tomography (HR-pQCT) is well suited for this purpose, however analysis methods are not widely available. The purpose of this study was to develop an open-source software tool for the identification and quantification of bone erosions using images acquired by HR-pQCT. The collection of modules, Bone Analysis Modules (BAM) - Erosion, implements previously published erosion analysis techniques as modules in 3D Slicer, an open-source image processing and visualization tool. BAM includes a module to automatically identify cortical interruptions, from which erosions are manually selected, and a hybrid module that combines morphological and level set operations to quantify the volume of bone erosions. HR-pQCT images of the second and third metacarpophalangeal (MCP) joints were acquired in patients with RA (XtremeCT, n = 14, XtremeCTII, n = 22). The number of cortical interruptions detected by BAM-Erosion agreed strongly with the previously published cortical interruption detection algorithm for both XtremeCT (r2 = 0.85) and XtremeCTII (r2 = 0.87). Erosion volume assessment by BAM-Erosion agreed strongly (r2 = 0.95) with the Medical Image Analysis Framework. BAM-Erosion provides an open-source erosion analysis tool that produces comparable results to previously published algorithms, with improved options for visualization. The strength of the tool is that it implements multiple image processing algorithms for erosion analysis on a single, widely available, open-source platform that can accommodate future updates.

Original languageEnglish
Article number116571
JournalBone
Volume165
Early online date26 Sept 2022
DOIs
Publication statusPublished - 2022

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