Differentiation of inflammatory from degenerative changes in the sacroiliac joints by machine learning supported texture analysis. Issue 140 (July 2021)

• Record Type: Journal Article
• Authors: Kepp, Felix H.; Huber, Florian A.; Wurnig, Moritz C.; Mannil, Manoj; Kaniewska, Malwina; Guglielmi, Riccardo; Del Grande, Filippo; Guggenberger, Roman
• Is Part Of: European journal of radiology. Issue 140(2021)
• Publication Date: 2021-07
• Subjects: Magnetic resonance imaging -- Ankylosing spondylitis -- Computer-assisted image analysis -- Sacroiliac joint -- Lower back pain; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2021.109755
• Languages: English
• ISSNs: 0720-048X

Abstract

Highlights: Interreader agreement for qualitative SIJ assessment is fair to substantial. Agreement of qualitative assessment of SIJ with clinical reference is fair. TA outperforms qualitative differentiation of SpA from degeneration. CE-T1w MRI is the most important discriminator in detecting SpA with TA. Abstract: Purpose: To compare the diagnostic performance of texture analysis (TA) against visual qualitative assessment in the differentiation of spondyloarthritis (SpA) from degenerative changes in the sacroiliac joints (SIJ). Method: Ninety patients referred for suspected inflammatory lower back pain from the rheumatology department were retrospectively included at our university hospital institution. MRI at 3 T of the lumbar spine and SIJ was performed with oblique coronal T1-weighted (w), fluid-sensitive fat-saturated (fs) TIRM and fsT1w intravenously contrast-enhanced (CE) images. Subjects were divided into three age- and gender-matched groups (30 each) based on definite clinical diagnosis serving as clinical reference standard with either degenerative, inflammatory (SpA) or no changes of the SIJ. SIJ were rated qualitatively by two independent radiologists and quantitatively by region-of-interest-based TA with 304 features subjected to machine learning logistic regression with randomized ten-fold selection of training and validation data. Qualitative and quantitative results were evaluated for diagnostic performance and compared against clinical reference standard. Results: Agreement of radiologist's diagnose with clinical reference was fair for both readers (κ = 0.32 and 0.44). ROC statistics revealed significant outperformance of TA compared to qualitative ratings for differentiation of SpA from remainder (AUC = 0.89 vs. 0.75), SpA from degenerative (AUC = 0.91 vs. 0.67) and TIRM-positive SpA (i.e. with bone marrow edema) from remainder cases (AUC = 0.95 vs. 0.76). T1w-CE images were the most important discriminator for detection of SpA. Conclusions: TA is superior to qualitative assessment for the differentiation of inflammatory from degenerative changes of the SIJ. Intravenous CE-images increase diagnostic yield in quantitative TA.