Radiomic Quantification for MRI Assessment of Sacroiliac Joints of Patients with Spondyloarthritis

Ariane Priscilla Magalhães Tenório; José Raniery Ferreira-Junior; Vitor Faeda Dalto; Matheus Calil Faleiros; Rodrigo Luppino Assad; Paulo Louzada-Junior; Marcello Henrique Nogueira-Barbosa; Rangaraj Mandayam Rangayyan; Paulo Mazzoncini de Azevedo-Marques

doi:10.1007/s10278-021-00559-7

Radiomic Quantification for MRI Assessment of Sacroiliac Joints of Patients with Spondyloarthritis

J Digit Imaging. 2022 Feb;35(1):29-38. doi: 10.1007/s10278-021-00559-7. Epub 2022 Jan 7.

Authors

Ariane Priscilla Magalhães Tenório¹, José Raniery Ferreira-Junior², Vitor Faeda Dalto², Matheus Calil Faleiros², Rodrigo Luppino Assad², Paulo Louzada-Junior², Marcello Henrique Nogueira-Barbosa^{2

3}, Rangaraj Mandayam Rangayyan⁴, Paulo Mazzoncini de Azevedo-Marques²

Affiliations

¹ Ribeirão Preto Medical School, University of São Paulo, Av. dos Bandeirantes, 3900 Ribeirão Preto, SP, 14049-900, São Paulo, Brazil. tenorioapm@alumni.usp.br.
² Ribeirão Preto Medical School, University of São Paulo, Av. dos Bandeirantes, 3900 Ribeirão Preto, SP, 14049-900, São Paulo, Brazil.
³ Department of Orthopedic Surgery, University of Missouri Health Care, Columbia, MO, USA.
⁴ Schulich School of Engineering, University of Calgary, Calgary, AB, Canada.

Abstract

Spondyloarthritis (SpA) is a group of diseases primarily involving chronic inflammation of the spine and peripheral joints, as evaluated by magnetic resonance imaging (MRI). Considering the complexity of SpA, we performed a retrospective study to discover quantitative/radiomic MRI-based features correlated with SpA. We also investigated different fat-suppression MRI techniques to develop detection models for inflammatory sacroiliitis. Finally, these model results were compared with those of experienced musculoskeletal radiologists, and the concordance level was evaluated. Examinations of 46 consecutive patients were obtained using SPAIR (spectral attenuated inversion recovery) and STIR (short tau inversion recovery) MRI sequences. Musculoskeletal radiologists manually segmented the sacroiliac joints for further extraction of 230 MRI features from gray-level histogram/matrices and wavelet filters. These features were associated with sacroiliitis, SpA, and the current biomarkers of ESR (erythrocyte sedimentation rate), CRP (C-reactive protein), BASDAI (Bath Ankylosing Spondylitis Activity Index), BASFI (Bath Ankylosing Spondylitis Functional Index), and MASES (Maastricht Ankylosing Spondylitis Enthesis Score). The Mann-Whitney U test showed that the radiomic markers from both MRI sequences were associated with active sacroiliitis and with SpA and its axial and peripheral subtypes (p < 0.05). Spearman's coefficient also identified a correlation between MRI markers and data from clinical practice (p < 0.05). Fat-suppression MRI models yielded performances that were statistically equivalent to those of specialists and presented strong concordance in identifying inflammatory sacroiliitis. SPAIR and STIR acquisition protocols showed potential for the evaluation of sacroiliac joints and the composition of a radiomic model to support the clinical assessment of SpA.

Keywords: Artificial intelligence; Radiomics; Sacroiliitis; Spondyloarthritis.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Biomarkers
Humans
Magnetic Resonance Imaging / methods
Retrospective Studies
Sacroiliac Joint / diagnostic imaging
Sacroiliitis* / complications
Sacroiliitis* / diagnostic imaging
Spondylarthritis* / complications
Spondylarthritis* / diagnostic imaging
Spondylitis, Ankylosing* / complications
Spondylitis, Ankylosing* / diagnosis

Substances

Biomarkers