A study of MRI-based radiomics biomarkers for sacroiliitis and spondyloarthritis

Autor(es)

Magalhaes Tenorio, Ariane Priscilla ^[1] ; Faleiros, Matheus Calil ^[1] ; Ferreira Junior, Jose Raniery ^[1] ; Dalto, Vitor Faeda ^[1] ; Assad, Rodrigo Luppino ^[1] ; Louzada-Junior, Paulo ^[1] ; Yoshida, Hiroyuki ^[2] ; Nogueira-Barbosa, Marcello Henrique ^[1] ; De Azevedo-Marques, Paulo Mazzoncini ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Ribeirao Preto Med Sch, Av Bandeirantes 3900, BR-14049900 Ribeirao Preto, SP - Brazil

^[2] Harvard Med Sch, Massachusetts Gen Hosp, 25 New Chardon St, Boston, MA 02114 - USA

• Tipo de documento: Artigo Científico
• Fonte: INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY; v. 15, n. 10 JUN 2020.
• Citações Web of Science: 0

Resumo

Purpose To evaluate the performance of texture-based biomarkers by radiomic analysis using magnetic resonance imaging (MRI) of patients with sacroiliitis secondary to spondyloarthritis (SpA). Relevance: The determination of sacroiliac joints inflammatory activity supports the drug management in these diseases. Methods Sacroiliac joints (SIJ) MRI examinations of 47 patients were evaluated. Thirty-seven patients had SpA diagnoses (27 axial SpA and ten peripheral SpA) which was established previously after clinical and laboratory follow-up. To perform the analysis, the SIJ MRI was first segmented and warped. Second, radiomics biomarkers were extracted from the warped MRI images for associative analysis with sacroiliitis and the SpA subtypes. Finally, statistical and machine learning methods were applied to assess the associations of the radiomics texture-based biomarkers with clinical outcomes. Results All diagnostic performances obtained with individual or combined biomarkers reached areas under the receiver operating characteristic curves >= 0.80 regarding SpA related sacroiliitis and and SpA subtypes classification. Radiomics texture-based analysis showed significant differences between the positive and negative SpA groups and differentiated the axial and peripheral subtypes (P < 0.001). In addition, the radiomics analysis was also able to correctly identify the disease even in the absence of active inflammation. Conclusion We concluded that the application of the radiomic approach constitutes a potential noninvasive tool to aid the diagnosis of sacroiliitis and for SpA subclassifications based on MRI of sacroiliac joints. (AU)

• Processo FAPESP: 16/17078-0 - Mineração, indexação e visualização de Big Data no contexto de sistemas de apoio à decisão clínica (MIVisBD)
• Beneficiário: Agma Juci Machado Traina
• Linha de fomento: Auxílio à Pesquisa - Temático
• Processo FAPESP: 14/50889-7 - INCT 2014: em Medicina Assistida por Computação Científica (INCT-MACC)
• Beneficiário: José Eduardo Krieger
• Linha de fomento: Auxílio à Pesquisa - Temático