Clinicopathological and Imaging Distinction Between Ocular Adnexal MALT Lymphoma and IgG4-Related Ophthalmic Disease.

PURPOSE: To characterize clinicopathologic and imaging differences between ocular adnexal mucosa-associated lymphoid tissue lymphoma (OAML) and IgG4-related ophthalmic disease (IgG4-ROD) and to evaluate clinical and artificial intelligence-assisted approaches for differentiating these entities.

DESIGN

Retrospective, single-center observational cross-sectional study.

PARTICIPANTS

Four hundred patients with pathologically confirmed orbital lymphoproliferative disease, including OAML (n = 287) and IgG4-ROD (n = 113), treated at West China Hospital between 2010 and 2024.

METHODS

Clinical, serologic, imaging, histopathologic, immunophenotypic, and molecular features were systematically compared between groups. A multivariable logistic regression model based on routinely available clinical variables was developed for early differentiation. Artificial intelligence models were additionally trained using radiological CT/MRI images and digital pathology whole-slide images.

MAIN OUTCOME MEASURES: Distinct clinical and pathologic characteristics between OAML and IgG4-ROD and diagnostic discrimination assessed by area under the receiver operating characteristic curve (AUC).

RESULTS

OAML more frequently presented as unilateral orbital or conjunctival lesions and showed monoclonal features, including light-chain restriction and immunoglobulin gene rearrangements. In contrast, IgG4-ROD predominantly involved bilateral lacrimal glands and demonstrated fibro-inflammatory changes with abundant IgG4⁺ plasma cells. Serum IgG4 levels overlapped substantially between groups. The clinical model achieved an AUC of 0.865. Radiology- and pathology-based artificial intelligence models achieved AUCs of 0.933 and 0.946, respectively, and pathology-informed radiology training further improved discrimination (AUC 0.974).

CONCLUSIONS

Integrated clinical, imaging, and pathologic assessment provides practical distinctions between OAML and IgG4-ROD. Artificial intelligence-assisted imaging analysis may complement conventional diagnostic pathways and support differentiation in clinically ambiguous orbital lymphoproliferative disease.