Assessment of diagnostic criteria for multifocal motor neuropathy in patients included in the Italian database.

BACKGROUND AND PURPOSE: This study aimed to assess the diagnostic criteria, ancillary investigations and treatment response using real-life data in multifocal motor neuropathy (MMN) patients. METHODS: Clinical and laboratory data were collected from 110 patients enrolled in the Italian MMN database through a structured questionnaire. Twenty-six patients were excluded due to the unavailability of nerve conduction studies or the presence of clinical signs and symptoms and electrodiagnostic abnormalities inconsistent with the MMN diagnosis. Analyses were conducted on 73 patients with a confirmed MMN diagnosis and 11 patients who did not meet the diagnostic criteria. RESULTS: The European Federation of Neurological Societies/Peripheral Nerve Society (EFNS/PNS) diagnostic criteria were variably applied. AUTHOR: When applying the American Association of Electrodiagnostic Medicine criteria, an additional 17% of patients fulfilled the criteria for probable/definite diagnosis whilst a further 9.5% missed the diagnosis. In 17% of the patients only compound muscle action potential amplitude, but not area, was measured and subsequently recorded in the database by the treating physician. Additional investigations, including anti-GM1 immunoglobulin M antibodies, cerebrospinal fluid analysis, nerve ultrasound and magnetic resonance imaging, supported the diagnosis in 46%-83% of the patients. Anti-GM1 immunoglobulin M antibodies and nerve ultrasound demonstrated the highest sensitivity. Additional tests were frequently performed outside the EFNS/PNS guideline recommendations. CONCLUSIONS: This study provides insights into the real-world diagnostic and management strategies for MMN, highlighting the challenges in applying diagnostic criteria.

Prevalence of non-stenotic vulnerable carotid plaques in embolic stroke of undetermined source.

INTRODUCTION: The latest research in ischaemic stroke pathogenesis is directed to unveil what is inside embolic stroke of undetermined source (ESUS). Whether vulnerable non stenotic carotid plaques (NSTEPS), i.e. atherosclerotic lesions in carotid arteries determining a stenosis lower than 50%, may represent a cause of stroke in ESUS is a matter of debate. We aimed to study the prevalence of NSTEPS in an ESUS population. PATIENTS AND METHODS: We retrospectively identified a consecutive ESUS population admitted to the Stroke-Unit of Careggi Hospital, Italy from 2019 to 2022. Characteristics of atherosclerotic plaques (thickness, ulceration, hypodensity) and their location (ipsilateral versus contralateral to the stroke) were studied on carotid CT angiography (CTA). Follow-up data were recorded up to 24 months after stroke. RESULTS: We identified 57 ESUS patients with unilateral ischaemic lesions studied with CTA; 53 (93%) had an ipsilateral carotid plaque, 81% contralateral, (p = 0.754) and 74% both. Plaques ipsilateral to stroke were ≥ 3 mm thick in 15 (28%) patients; hypodense in 14 (26%) and ulcerated in 5 (9%). The frequency of hypodensity was higher in ipsilateral compared to contralateral plaques (26% vs. 13%, p = 0.039) and ulceration was around four times more frequent, although not statistically significant (9% vs. 2%, p = 0.219). At follow-up, six patients had stroke recurrence (11%), 2 of them were in the same vascular territory of the former. DISCUSSION AND CONCLUSIONS: Our data suggest that plaques ipsilateral to stroke seem to be more frequently vulnerable and consequently more prone to embolization. Prospective data are needed to clarify the causal role of NSTEPS in ESUS.

Convolutional Neural Network-Based Automated Segmentation of Skeletal Muscle and Subcutaneous Adipose Tissue on Thigh MRI in Muscular Dystrophy Patients.

We aim to develop a deep learning-based algorithm for automated segmentation of thigh muscles and subcutaneous adipose tissue (SAT) from T1-weighted muscle MRIs from patients affected by muscular dystrophies (MDs). From March 2019 to February 2022, adult and pediatric patients affected by MDs were enrolled from Azienda Ospedaliera Universitaria Pisana, Pisa, Italy (Institution 1) and the IRCCS Stella Maris Foundation, Calambrone-Pisa, Italy (Institution 2), respectively. All patients underwent a bilateral thighs MRI including an axial T1 weighted in- and out-of-phase (dual-echo). Both muscles and SAT were manually and separately segmented on out-of-phase image sets by a radiologist with 6 years of experience in musculoskeletal imaging. A U-Net1 and U-Net3 were built to automatically segment the SAT, all the thigh muscles together and the three muscular compartments separately. The dataset was randomly split into the on train, validation, and test set. The segmentation performance was assessed through the Dice similarity coefficient (DSC). The final cohort included 23 patients. The estimated DSC for U-Net1 was 96.8%, 95.3%, and 95.6% on train, validation, and test set, respectively, while the estimated accuracy for U-Net3 was 94.1%, 92.9%, and 93.9%. Both of the U-Nets achieved a median DSC of 0.95 for SAT segmentation. The U-Net1 and the U-Net3 achieved an optimal agreement with manual segmentation for the automatic segmentation. The so-developed neural networks have the potential to automatically segment thigh muscles and SAT in patients affected by MDs.