Hierarchical Multimodal Fusion of Multi-Sequence MRI and Clinical Metadata for the Classification of Rotator…

Cohort studyJournal of clinical medicine· Jul 2026

Hierarchical Multimodal Fusion of Multi-Sequence MRI and Clinical Metadata for the Classification of Rotator Cuff Tears.

Sergen Aşık, Ahmet Yazıcı, Murat Aşçı, İrfan Okumuşer

Shoulder & ElbowCohort studyDiagnosisQ2IF 3.5

A streamlined three-sequence MRI plus metadata model best classified rotator cuff tears

Hierarchical Multimodal Fusion of Multi-Sequence MRI and Clinical Metadata for the Classification of Rotator Cuff Tears.

Sergen Aşık … İrfan Okumuşer

Journal of clinical medicine · Jul 2026 · Q2 in General Medicine

Background

Rotator cuff tears are a leading cause of shoulder disability.

Purpose

This study evaluated a hierarchical, sequence-aware multimodal framework for patient-level binary rotator cuff tear classification.

Methods

A single-center cohort of 199 patients (100 tears, 99 controls) was analyzed across four MRI sequences (T1 coronal, T2 fat-suppressed sagittal, and proton density [PD] fat-suppressed coronal and transverse/axial) and nine demographic features.

n = 199 patients

Results

top model correctly separated torn from intact rotator cuffs in nearly every case

AUC 1.00 (95% CI 0.98 to 1.00)

CI excludes the null - significant

More results

In Study 0, the PD coronal ResNet50 model was the top baseline (AUC = 0.9834, F1 = 0.9515).

In Study 1, late decision fusion yielded the highest AUC (0.9909), while feature concatenation optimized threshold balance (F1 = 0.9502).

Metadata utility was configuration-dependent, assisting only fluid-sensitive combinations.

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Conclusion · 1 of 2

Rather than indiscriminately aggregating entire clinical protocols, multimodal fusion is optimized by selecting complementary imaging series.

Conclusion · 2 of 2

For binary classification, excluding non-fat-suppressed T1 images in favor of a streamlined T2 and PD set stabilized by clinical demographics maximized classification performance in this internally validated, single-center cohort.

Hierarchical Multimodal Fusion of Multi-Sequence MRI and Clinical Metadata for the Classification of Rotator Cuff Tears.

Hierarchical Multimodal Fusion of Multi-Sequence MRI and Clinical Metadata for the Classification of Rotator Cuff Tears.

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