Collaborative Diagnostic Pathways for Unilateral Orbital Disease: A Clinicopathological Series.

PURPOSE: To report a retrospective tertiary-center series of unilateral orbital lesions and to illustrate a structured, experience-based multidisciplinary workflow integrating clinical, radiologic, and histopathologic data to support differential diagnosis and management in real-world practice.

PATIENTS AND

METHODS

This retrospective descriptive case-series included 18 patients with biopsy-confirmed unilateral orbital lesions evaluated between January 2021 and March 2025 at the Oculoplastic and Orbital Surgery Unit, Humanitas Research Hospital, Milan. Demographic, clinical, imaging, and histopathologic data were analyzed. Imaging included computed tomography (CT), magnetic resonance imaging (MRI) with diffusion-weighted imaging (DWI), and functional techniques such as MRA, PET/CT when indicated. Histopathology incorporated immunohistochemistry (IHC) and proliferative indices (Ki-67). Outcomes included final diagnosis, treatment, and early recurrence.

RESULTS

18 patients were included: dermoid cysts (n = 3), vascular malformations (n = 6), neurofibroma (n = 1), idiopathic orbital inflammation (n = 2), meningioma (n = 1), and epithelial malignancies (adenoid cystic carcinoma, basal cell carcinoma, squamous cell carcinoma, mucinous carcinoma, Merkel cell carcinoma; n = 5). Characteristic MRI and IHC patterns enabled accurate subclassification and guided informed-individualized management decisions, ranging from observation or image-guided sclerotherapy to complete surgical excision or multidisciplinary oncologic therapy. No recurrence occurred among benign lesions. Malignant epithelial tumors required adjuvant radiotherapy or systemic therapy according to histologic subtype and TNM stage.

CONCLUSION

A systematic, multidisciplinary approach integrating cross-sectional imaging and histopathologic assessment underpins effective diagnostic and therapeutic decision-making in unilateral orbital disease. The proposed workflow, derived from institutional practice, offers an illustrative and reproducible framework for clinical reasoning and therapeutic decision-making based on real case scenarios. Its adaptability lies in the use of structured clinical-radiologic algorithms, which may help optimize individualized management, facilitate timely referral, and reduce unnecessary invasive procedures, particularly within tertiary referral settings.