Multicenter development and validation of a probability-based model to diagnose Lewy body disease using ¹²³I-meta-iodobenzylguanidine.

Abstract

We previously proposed that a probability-based sympathetic ¹²³I-meta-iodobenzylguanidine (mIBG) index (SMILe) could distinguish the presence or absence of Lewy body disease (LBD) based on findings at a single center. However, whether the model would be useful in the real world remained uncertain. Therefore, we updated and evaluated its performance at five Japanese and three European institutions. We compared data from 967 patients with suspected LBD with 62 controls from a normal database (NDB). Of 815 patients with guideline-based diagnoses, 483 had LBD (Parkinson disease [PD] or dementia with Lewy bodies [DLB]) and 332 did not have LBD. Heart-to-mediastinum (H/M) ratios were standardized using a phantom-based method. Logistic regression models included early and late H/M ratios, age, sex, and comorbidities. We assessed diagnostic performance using ROC analysis and cross-validation. The updated model discriminated LBD from other diseases (AUC for early and late H/M, 0.880 0.899, respectively). Age correction of H/M ratios based on the NDB did not improve accuracy. Median early H/M ratios [SMILe probability] were 3.09 [12.8%] for NDB, 2.57 [37.5%] for Alzheimer disease, 1.76 [84.7%] for PD, and 1.62 [89.0%] for DLB, with significantly lower H/M ratios and higher probabilities in PD and DLB compared with controls (p < 0.0001). Late-phase imaging added value mainly in intermediate borderline (30%-70%) situations. Coronary artery disease attenuated the diagnostic performance of SMILe. The probability-based ¹²³I-mIBG model reliably differentiated LBD from other diseases. Standardization among sites supports global applicability and reflects real-world clinical practice.