Glymphatic function assessment in Parkinson's disease using diffusion tensor image analysis along the perivascular space.

INTRODUCTION: Glymphatic dysfunction can contribute to α-synucleinopathies. We examined glymphatic function in idiopathic Parkinson's disease (PD) utilizing Diffusion Tensor Image Analysis aLong the Perivascular Space (DTI-ALPS). METHODS: This study enrolled consecutive patients diagnosed with de novo PD between June 2017 and March 2019 who underwent brain DTI with concurrent 123I-2ß-carbomethoxy-3ß-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane (123I-FP-CIT) SPECT, and age- and sex-matched controls. From DTI-ALPS, the ALPS-index was calculated as a ratio of diffusivities along the x-axis in the region of neural fibers passing vertically to the diffusivities perpendicular to them, which reflected perivascular water motion at the lateral ventricular body level. The ALPS-index of the PD and control groups was compared using Student's t-test; its correlations with clinical scores for motor and cognition (UPDRS-III, MMSE, and MoCA) and striatal dopamine transporter uptake measured by 123I-FP-CIT specific binding ratios (SBRs) were examined using a correlation coefficient. RESULTS: In all, 54 patients in the de novo PD group (31 women, 23 men; mean age, 68.9 ± 9.4 years) and 54 in the control group (mean age, 69.0 ± 10.5 years) were included. The ALPS-index was lower in the PD group than in the controls (1.51 ± 0.22 versus 1.66 ± 0.20; P < 0.001). In the PD group, the ALPS-index negatively correlated with the UPDRS-III score (r = -0.526), and positively correlated with the MMSE (r = 0.377) and MoCA scores (r = 0.382) (all, P < 0.05). No correlation was observed between the ALPS-index and striatal 123I-FP-CIT SBRs (P > 0.05). CONCLUSIONS: DTI-ALPS can reveal glymphatic dysfunction in patients with PD, whose severity correlated with motor and cognitive dysfunction, but not striatal dopamine transporter uptake.

[MRI Findings in Parkinson's Disease: Radiologic Assessment of Nigrostriatal Degeneration]. / 파킨슨병의 ìžê¸°ê³µëª ì˜ìƒ 소견: í‘ì§ˆì„ ì¡°ì²´ 변성의 ì˜ìƒí•™ì  평가.

Parkinson's disease (PD) is a movement disorder that develops due to degenerative loss of dopaminergic cells in the substantia nigra of the midbrain. Recent advances in MRI techniques have demonstrated various imaging findings that can reflect the underlying pathophysiological processes occurring in Parkinson's disease. Many imaging studies have shown that such findings can assist in the diagnosis of Parkinson's disease and its differentiation from atypical parkinsonism. In this review, we present MRI techniques that can be used in clinical assessment, such as nigrosome imaging and neuromelanin imaging, and we provide the detailed imaging features of Parkinson's disease reflecting nigrostriatal degeneration.

Diagnostic assessment of magnetic resonance imaging for patients with intralabyrinthine schwannoma: A systematic review.

OBJECTIVES: Recent advancements in high-resolution imaging have improved the diagnostic assessment of magnetic resonance imaging (MRI) for intralabyrinthine schwannoma (ILS). This systematic review aimed to evaluate the diagnostic performance of MRI for patients with ILS. METHODS: Ovid-MEDLINE and EMBASE databases were searched for related studies on the diagnostic performance of MRI for patients with ILS published up to February 10, 2020. The primary endpoint was the diagnostic performance of MRI for ILS. The quality of the enrolled studies was assessed using tailored questionnaires and the Quality Assessment of Diagnostic Accuracy Studies-2 criteria. RESULTS: Overall, 6 retrospective studies that included 122 patients with ILS from a parent population of 364 were included. The sample size, parent population and its composition, reference standard, detailed parameters of MRI, and even the diagnostic methods varied between the studies. The studies had moderate quality. The sensitivity of combination of T2WI and CE-T1WI was over 90%. Relative sensitivity of T2WI comparative to CE-T1WI ranged from 62% to 100%, and the specificity were 100%. CONCLUSIONS: MRI has acceptable diagnostic performance for ILS. There is a need for well-organized research to reduce the factors causing heterogeneity.

Deep Learning-Based Computer-Aided Detection System for Automated Treatment Response Assessment of Brain Metastases on 3D MRI.

BACKGROUND: Although accurate treatment response assessment for brain metastases (BMs) is crucial, it is highly labor intensive. This retrospective study aimed to develop a computer-aided detection (CAD) system for automated BM detection and treatment response evaluation using deep learning. METHODS: We included 214 consecutive MRI examinations of 147 patients with BM obtained between January 2015 and August 2016. These were divided into the training (174 MR images from 127 patients) and test datasets according to temporal separation (temporal test set #1; 40 MR images from 20 patients). For external validation, 24 patients with BM and 11 patients without BM from other institutions were included (geographic test set). In addition, we included 12 MRIs from BM patients obtained between August 2017 and March 2020 (temporal test set #2). Detection sensitivity, dice similarity coefficient (DSC) for segmentation, and agreements in one-dimensional and volumetric Response Assessment in Neuro-Oncology Brain Metastases (RANO-BM) criteria between CAD and radiologists were assessed. RESULTS: In the temporal test set #1, the sensitivity was 75.1% (95% confidence interval [CI]: 69.6%, 79.9%), mean DSC was 0.69 ± 0.22, and false-positive (FP) rate per scan was 0.8 for BM ≥ 5 mm. Agreements in the RANO-BM criteria were moderate (κ, 0.52) and substantial (κ, 0.68) for one-dimensional and volumetric, respectively. In the geographic test set, sensitivity was 87.7% (95% CI: 77.2%, 94.5%), mean DSC was 0.68 ± 0.20, and FP rate per scan was 1.9 for BM ≥ 5 mm. In the temporal test set #2, sensitivity was 94.7% (95% CI: 74.0%, 99.9%), mean DSC was 0.82 ± 0.20, and FP per scan was 0.5 (6/12) for BM ≥ 5 mm. CONCLUSIONS: Our CAD showed potential for automated treatment response assessment of BM ≥ 5 mm.

Radiofrequency Ablation of Facial Venolymphatic Malformations: Assessment of Efficacy and Safety and the Role of Injectable Electrodes.

PURPOSE: To evaluate the efficacy and safety of ultrasound (US)-guided radiofrequency (RF) ablation in the treatment of facial microcystic lymphatic malformations (mLMs) or mixed venolymphatic malformations (VLMs) and to introduce the "induced-paralysis" technique with the use of an injectable electrode to minimize neural complications. MATERIALS AND METHODS: Data from patients with symptomatic facial mLMs or mixed VLMs who underwent US-guided RF ablation in 2014-2017 were retrospectively reviewed. Computed tomography (CT) and/or magnetic resonance (MR) imaging was used to localize any functional structures close to the target lesion. Treatment outcome was assessed by 4-point cosmetic grading score (CGS). Treatment outcome was compared between patients with vs without a functional structure close to the lesion and those treated with a noninjectable vs an injectable electrode. Immediate and late complications were assessed during follow-up. RESULTS: Data from 15 patients were evaluated. Initial CGS and median volume were significantly decreased at the last follow-up in all patients (from 4 to 1 and from 7 mL to 0.7 mL, respectively; P < .05). Treatment outcome differed significantly between those with and without a functional structure on CT or MR imaging (P < .05) but showed no difference between noninjectable (n = 9) and injectable electrodes (n = 6). Two cases of transient cranial nerve palsy were seen in the noninjectable electrode group. CONCLUSIONS: US-guided RF ablation is effective in patients with facial mLMs or mixed VLMs. The induced-paralysis technique with an injectable electrode has the potential to ensure technical safety without compromising efficacy.