Table 2

Technical details of machine learning algorithms (10 studies)

Extracting ROIClassification modelsMethods of evaluating performanceGround truth annotations
Bordner et al21AutomaticallyDL: Mask-RCNNInternal and external testASAS MRI sacroiliitis±of each persons’ MRI
Ye et al22Manually (two MS radiologists)mRMR and LASSOValidationASAS clinical diagnosis of AxSpA±of each person
Tenório et al23Manually (two MS radiologists)ANNValidationASAS MRI sacroiliitis±of each persons’ MRI
Roels et al24AutomaticallyDL: ResNet18Validation and external testBMO±of each persons’ MRI
Lin et al25AutomaticallyDL: CNN (+ Attention-U-Net)Internal testASAS MRI sacroiliitis±of each persons’ MRI or each images
Bressem et al26Not applicable*DL: Res-Neural networkValidation and external testASAS MRI sacroiliitis ±, structural changes of SI joints ±, active inflammatory changes of SI joints±of each persons’ MRI
Nicolaes et al27Manually (three MS radiologists)DL: unclear architectureValidationBMO±of each persons’ MRI
Lee et al28Manually (two rheumatologists and one radiologist)DL: CNN (+ResNet18)ValidationASAS MRI sacroiliitis±of each persons’ MRI or each images
Kepp et al29Manually (two radiologists)ANN (+k-nearest neighbour)ValidationASAS MRI sacroiliitis±, TIRM positive ASAS sacroiliitis±, MRI sacroiliitis versus degenerative changes of each persons’ MRI
Faleiros et al30Manually (one MS radiologist)ANN, SVM, k-nearest neighbourValidation and internal testASAS MRI sacroiliitis±of each persons’ MRI
  • *Not extracted ROI.

  • ANN, artificial neural network; ASAS, Assessment of Spondyloarthritis International Society; AxSpA, axial spondyloarthritis; BMO, bone marrow oedema; CNN, convolutional neural network; DL, deep learning; LASSO, least absolute shrinkage and selection operator; mRMR, minimum-redundancy-maximum-relevance; MS, muscular skeleton; RCNN, regions with convolutional neural networks; ROI, region of interest; SI, sacroiliac; SVM, support vector machine; TIRM, Turbo Inversion Recovery Magnitude.