This review presents up-to-date imaging applications in the substantia nigra and its related structures used in Parkinson disease and other parkinsonian syndromes, assesses their usefulness, and di... Parkinson disease is characterized by dopaminergic cell loss in the substantia nigra of the midbrain. There are various imaging markers for Parkinson disease. Recent advances in MRI have enabled el...

Background Brain glymphatic dysfunction may contribute to the development of α-synucleinopathies. Yet, noninvasive imaging and quantification remain lacking. Purpose To examine glymphatic function of the brain in isolated rapid eye movement sleep behavior disorder (RBD) and its relevance to phenoconversion with use of diffusion-tensor imaging (DTI) analysis along the perivascular space (ALPS). Materials and Methods This prospective study included consecutive participants diagnosed with RBD, age- and sex-matched control participants, and participants with Parkinson disease (PD) who were enrolled and examined between May 2017 and April 2020. All study participants underwent 3.0-T brain MRI including DTI, susceptibility-weighted and susceptibility map-weighted imaging, and/or dopamine transporter imaging using iodine 123-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane SPECT at the time of participation. Phenoconversion status to α-synucleinopathies was unknown at the time of MRI. Participants were regularly followed up and monitored for any signs of α-synucleinopathies. The ALPS index reflecting glymphatic activity was calculated by a ratio of the diffusivities along the x-axis in the projection and association neural fibers to the diffusivities perpendicular to them and compared according to the groups with use of the Kruskal-Wallis and Mann-Whitney U tests. The phenoconversion risk in participants with RBD was evaluated according to the ALPS index with use of a Cox proportional hazards model. Results Twenty participants diagnosed with RBD (12 men; median age, 73 years [IQR, 66-76 years]), 20 control participants, and 20 participants with PD were included. The median ALPS index was lower in the group with RBD versus controls (1.53 vs 1.72; P = .001) but showed no evidence of a difference compared with the group with PD (1.49; P = .68). The conversion risk decreased with an increasing ALPS index (hazard ratio, 0.57 per 0.1 increase in the ALPS index [95% CI: 0.35, 0.93]; P = .03). Conclusion DTI-ALPS in RBD demonstrated a more severe reduction of glymphatic activity in individuals with phenoconversion to α-synucleinopathies. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Filippi and Balestrino in this issue.

Accurate detection of brain metastasis (BM) is important for cancer patients. We aimed to systematically review the performance and quality of machine-learning-based BM detection on MRI in the relevant literature. A systematic literature search was performed for relevant studies reported before April 27, 2020. We assessed the quality of the studies using modified tailored questionnaires of the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) criteria and the Checklist for Artificial Intelligence in Medical Imaging (CLAIM). Pooled detectability was calculated using an inverse-variance weighting model. A total of 12 studies were included, which showed a clear transition from classical machine learning (cML) to deep learning (DL) after 2018. The studies on DL used a larger sample size than those on cML. The cML and DL groups also differed in the composition of the dataset, and technical details such as data augmentation. The pooled proportions of detectability of BM were 88.7% (95% CI, 84–93%) and 90.1% (95% CI, 84–95%) in the cML and DL groups, respectively. The false-positive rate per person was lower in the DL group than the cML group (10 vs 135, P < 0.001). In the patient selection domain of QUADAS-2, three studies (25%) were designated as high risk due to non-consecutive enrollment and arbitrary exclusion of nodules. A comparable detectability of BM with a low false-positive rate per person was found in the DL group compared with the cML group. Improvements are required in terms of quality and study design.

BACKGROUND AND PURPOSE: There are a few reports regarding the outcome evaluation of balloon-expandable intracranial stent placement (BEICS). The purpose of our study was to evaluate the outcome and factors related to the adverse events (AEs) of BEICS. MATERIALS AND METHODS: We evaluated 100 consecutive patients who underwent BEICS. We assessed the procedural success (residual stenosis 50%) at 6 months. We also analyzed 18 factors including symptom patterns related to AE rate. Symptom patterns revealed 1) stable patients (n = 73) with improving, stationary, or resolved symptoms; and 2) unstable patients (n = 27) with gradual worsening or fluctuating symptoms (National Institutes of Health Stroke Scale [NIHSS] ≥4) within 2 days before stent placement. RESULTS: The procedural success rate was 99%. Overall, there were 10 (10%) AEs within the 6 months: 4 (4%) minor strokes, 3 (3%) major strokes, and 3 (3%) deaths including a death from myocardial infarction. AE rate was 4.1% in stable and 25.9% in unstable patients. Restenosis at 6 months revealed 0% (0/59). Good outcome (modified Rankin Scale ≤2) at 6 months was 97% (71/73) in stable and 67% (18/27) in unstable patients. Stepwise logistic regression model revealed that symptom pattern (unstable versus stable) was the only significant risk factor (OR, 8.167; 95% CI, 1.933–34.500; P = .004). CONCLUSION: BEICS revealed a low AE and good outcome rate at 6 months, especially in the stable patients. Midterm outcome was also favorable in the unstable patient group.