What question did this study set out to answer?

To explore the use of ZOOMit-DWI radiomics for non-invasive early detection of primary Sjögren's disease.

March 1, 2026

Magnetic resonance imaging-based radiomics for early detection of primary Sjögren's disease using ZOOMit-DWI: a non-invasive diagnostic approach

Key Points

To explore the use of ZOOMit-DWI radiomics for non-invasive early detection of primary Sjögren's disease.
Utilized RFEP model based on parotid ZOOMit DWI radiomics
Assessed diagnostic accuracy of the model
Analyzed interpretability for clinical use
Demonstrated high diagnostic accuracy for early parotid gland injury
Showed potential for clinical translation in pSjD detection
Introduced AI-driven radiomics as a novel diagnostic tool

Abstract

The RFEP model, leveraging parotid ZOOMit DWI radiomics, shows high diagnostic accuracy and interpretability, offering a non-invasive tool for early parotid gland injury in pSjD. This study pioneers the application of AI-driven radiomics in pSjD diagnosis, paving the way for future research and clinical translation.

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Magnetic resonance imaging-based radiomics for early detection of primary Sjögren's disease using ZOOMit-DWI: a non-invasive diagnostic approach

Key Points

Abstract

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