Search

Purpose A strong prognostic score that enables a stratification of newly diagnosed Hodgkin Lymphoma (HL) to identify patients at high risk of refractory/relapsed disease is still needed. Our aim was to investigate the potential value of a radiomics analysis pipeline from whole-body MRI (WB-MRI) exams for clinical outcome prediction in patients with Hodgkin Lymphoma (HL). Materials and methods Index lesions from baseline WB-MRIs of 40 patients (22 females; mean age 31.7 ± 11.4 years) with newly diagnosed HL treated by ABVD chemotherapy regimen were manually segmented on T1-weighted, STIR, and DWI images for texture analysis feature extraction. A machine learning approach based on the Extra Trees classifier and incorporating clinical variables, 18F-FDG-PET/CT-derived metabolic tumor volume, and WB-MRI radiomics features was tested using cross-validation to predict refractory/relapsed disease. Results Relapsed disease was observed in 10/40 patients (25%), two of whom died due to progression of disease and graft versus host disease, while eight reached the complete remission. In total, 1403 clinical and radiomics features were extracted, of which 11 clinical variables and 171 radiomics parameters from both original and filtered images were selected. The 3 best performing Extra Trees classifier models obtained an equivalent highest mean accuracy of 0.78 and standard deviation of 0.09, with a mean AUC of 0.82 and standard deviation of 0.08. Conclusions Our preliminary results demonstrate that a combined machine learning and texture analysis model to predict refractory/relapsed HL on WB-MRI exams is feasible and may help in the clinical outcome prediction in HL patients.

Neuroblastoma is the most common extra-cranial solid tumor in pediatric patients. Despite the established role of 123I-MIBG and 131I-MIBG scintigraphy in this tumor, only limited data are available regarding the use of 124I-metaiodobenzylguanidine (MIBG) positron emission tomography (PET)/computed tomography (CT). We present our preliminary experience with 124I-MIBG PET/CT: two pediatric patients affected by neuroblastoma, who underwent 124I-MIBG PET/CT for pre-therapy distribution evaluation and restaging purposes. We aimed to evaluate whether 124I-MIBG PET/CT can detect as many or more neuroblastoma lesions than 123I/131I-MIBG imaging. Our cases show promising results, although further validation and standardization of 124I-MIBG PET/CT are required.

Primary progressive freezing gait (PPFG) is a clinical syndrome underlain by diverse neurodegenerative diseases and characterized by early occurrence of gait freezing. Either degeneration or integrity of the nigrostriatal terminals have been found by SPECT and PET studies. In this retrospective study, we evaluated (123)I-FP-CIT SPECT findings in a consecutive series of 13 PPFG patients with detailed clinical evaluation over time (mean follow-up duration: 3.1 ± 1.2 years). In all patients, (123)I-FP-CIT SPECT has been performed at the time of first clinical evaluation (1.7 ± 1.4 years after disease onset) and was compared with data from 23 age- and sex-matched healthy subjects. PPFG patients were categorized as having abnormal (n = 8) or normal (n = 5) SPECT. At disease onset, PPFG with abnormal SPECT had more frequent hypophonia, higher UPDRS-III scores and partial levodopa responsiveness. By contrast, PPFG with normal SPECT had more frequent bilateral plantar responses and no response to levodopa. At latest follow-up, initial diagnosis in the abnormal SPECT group was revised (n = 5) to progressive supranuclear palsy (n = 4) and pure akinesia with gait freezing (n = 1). Among the five patients with normal SPECT, follow-up evaluation disclosed corticobasal syndrome (n = 2) and primary lateral sclerosis (n = 1). Dopamine transporter imaging can capture the clinical heterogeneity of PPFG and might have a value to predict possible disease progression.