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The objective of this study was to outline the dynamics of prokineticin-2 pathway in relation to clinical-pathological features of Parkinson's disease by examining olfactory neurons of patients.Thirty-eight patients (26 de novo, newly diagnosed) and 31 sex/age-matched healthy controls underwent noninvasive mucosa brushing for olfactory neurons collection, and standard clinical assessment. Gene expression levels of prokineticin-2, prokineticin-2 receptors type 1 and 2, and prokineticin-2-long peptide were measured in olfactory neurons by real-time polymerase chain reaction (PCR); moreover, the prokineticin-2 protein and α-synuclein species (total and oligomeric) were quantified by immunofluorescence staining.Prokineticin-2 expression was significantly increased in Parkinson's disease. De novo patients had higher prokineticin-2 levels, directly correlated with Movement Disorder Society-Sponsored Revision of the Unified Parkinson Disease Rating Scale (MDS-UPDRS) part III motor score. In addition, oligomeric α-synuclein was higher in Parkinson's disease and directly correlated with prokineticin-2 protein levels. Total α-synuclein did not differ between patients and controls.Prokineticin-2 is a chemokine showing neuroprotective effects in experimental models of Parkinson's disease, but translational proof of its role in patients is still lacking. Here, we used olfactory neurons as the ideal tissue to analyze molecular stages of neurodegeneration in vivo, providing unprecedented evidence that the prokineticin-2 pathway is activated in patients with Parkinson's disease. Specifically, prokineticin-2 expression in olfactory neurons was higher at early disease stages, proportional to motor severity, and associated with oligomeric α-synuclein accumulation. These data, consistently with preclinical findings, support prokineticin-2 as a candidate target in Parkinson's disease, and validate reliability of olfactory neurons to reflect pathological changes of the disease. ANN NEUROL 2022.

PURPOSE: To present a novel 3 Tesla 24-channel glove array that enables hand and wrist imaging in varying postures. METHODS: The glove array consists of an inner glove holding the electronics and an outer glove protecting the components. The inner glove consists of four main structures: palm, fingers, wrist, and a flap that rolls over on top. Each structure was constructed out of three layers: a layer of electrostatic discharge (ESD) flame resistant fabric, a layer of neoprene scuba, and a layer of mesh fabric. Lightweight and flexible high impedance coil (HIC) elements were inserted into dedicated tubes sewn into the fabric. Coil elements were deliberately shortened to minimize the matching interface. Siemens Tim 4G technology was used to connect all 24 HIC elements to the scanner with only one plug. RESULTS: The 24-channel glove array allows large motion of both wrist and hand while maintaining the signal-to-noise ratio needed for high-resolution imaging. CONCLUSION: In this work, a purpose-built 3T glove array that embeds 24 HIC elements is demonstrated for both hand and wrist imaging. The 24-channel glove array allows a great range of motion of both the wrist and hand while maintaining a high signal-to-noise ratio and providing good theoretical acceleration performance, thus enabling hand and wrist imaging at different postures to extract kinematic information.

Magnetic resonance fingerprinting (MRF) is a method to speed up acquisition of quantitative MRI data. However, MRF does not usually produce contrast-weighted images that are required by radiologists, limiting reachable total scan time improvement. Contrast synthesis from MRF could significantly decrease the imaging time.To improve clinical utility of MRF by synthesizing contrast-weighted MR images from the quantitative data provided by MRF, using U-nets that were trained for the synthesis task utilizing L1- and perceptual loss functions, and their combinations.Retrospective.Knee joint MRI data from 184 subjects from Northern Finland 1986 Birth Cohort (ages 33-35, gender distribution not available).A 3 T, multislice-MRF, proton density (PD)-weighted 3D-SPACE (sampling perfection with application optimized contrasts using different flip angle evolution), fat-saturated T2-weighted 3D-space, water-excited double echo steady state (DESS).Data were divided into training, validation, test, and radiologist's assessment sets in the following way: 136 subjects to training, 3 for validation, 3 for testing, and 42 for radiologist's assessment. The synthetic and target images were evaluated using 5-point Likert scale by two musculoskeletal radiologists blinded and with quantitative error metrics.Friedman's test accompanied with post hoc Wilcoxon signed-rank test and intraclass correlation coefficient. The statistical cutoff P0.05 adjusted by Bonferroni correction as necessary was utilized.The networks trained in the study could synthesize conventional images with high image quality (Likert scores 3-4 on a 5-point scale). Qualitatively, the best synthetic images were produced with combination of L1- and perceptual loss functions and perceptual loss alone, while L1-loss alone led to significantly poorer image quality (Likert scores below 3). The interreader and intrareader agreement were high (0.80 and 0.92, respectively) and significant. However, quantitative image quality metrics indicated best performance for the pure L1-loss.Synthesizing high-quality contrast-weighted images from MRF data using deep learning is feasible. However, more studies are needed to validate the diagnostic accuracy of these synthetic images.4.Stage 1.

Background Signal-to-noise ratio (SNR) is used to evaluate the performance of magnetic resonance (MR) imaging systems. Accurate and consistent estimations are needed to routinely use SNR to assess coils and image reconstruction techniques. Purpose To identify a reliable and practical method for SNR estimation in multiple-coil reconstructions. Study type Technical evaluation and comparison. Subjects/phantom A uniform phantom and four healthy volunteers: 35, 38, 39 y/o males, 25 y/o female. Field strength/sequence Two-dimensional multislice gradient-echo pulse sequence at 3 T and 7 T. Assessment Reference-standard SNR was calculated from 100 multiple replicas. Six SNR methods were compared against it: difference image (DI), analytic array combination (AC), pseudo-multiple-replica (PMR), generalized pseudo-replica (GPR), smoothed image subtraction (SIS), and DI with temporal instability correction (TIC). The assessment was repeated for different multiple-coil reconstructions. Statistical tests SNR methods were evaluated in terms of relative deviation (RD) and normalized mutual information (NMI) with respect to the reference-standard, using a linear regression (0.05 significance level) to assess how different factors affect accuracy. Results Average RD (phantom) for DI, AC, PMR, GPR, SIS, and TIC was 7.9%, 6%, 6.7%, 10.1%, 40%, and 14.6%, respectively. RD increased with acceleration. SNR maps with AC were the most similar to the reference standard (NMI = 0.358). Considering all brain regions of interest, average RD for all SNR methods varied 96% among volunteers but remained approximately 10% for AC, PMR, and GPR, whereas it was more than 30% for DI, SIS, and TIC. RD was mainly affected by image reconstruction (beta = 12) for AC and SNR entropy for SIS (beta = 19). Data conclusion AC provided accurate and robust SNR estimation. PMR and GPR are more generally applicable than AC. DI and TIC should be used only at low acceleration factors, when an additional noise-only scan cannot be acquired. SIS is a single-acquisition alternative to DI for generalized autocalibrating partial parallel acquisition (GRAPPA) reconstructions. Evidence level 1 TECHNICAL EFFICACY: Stage 1.

ispartof: STRAIN vol:58 issue:6 status: published

Background and purpose Status epilepticus (SE) is a heterogeneous condition and considerable variability exists in its etiology, semiology, electroencephalographic correlates, and response to treatment. The aim of the present study was to explore whether distinct phenotypes may be identified within SE with prominent motor symptoms. Methods Consecutive episodes of SE with prominent motor symptoms in patients aged ≥14 years were included. Etiology of SE was defined as symptomatic (acute, remote, progressive) or unknown. Electroencephalogram (EEG) recordings were searched for lateralized periodic discharges (LPDs), generalized sharply and/or triphasic periodic potentials (GPDs), and spontaneous burst suppression (BS). According to treatment response, SE was classified into responsive, refractory and super‐refractory. Average linkage hierarchical cluster analysis was performed with Pearson's correlation as a similarity measure. Results A total of 240 episodes of SE were identified. Three major clusters were found. The first cluster linked focal motor SE evolving into non‐convulsive SE (NCSE), presence of LPDs/GPDs on EEG, unknown etiology and treatment refractoriness. The second cluster linked convulsive and myoclonic SE evolving into NCSE, presence of spontaneous BS on EEG, progressive symptomatic etiology and super‐refractoriness. The third cluster linked convulsive and myoclonic SE not evolving into other semiologies, absence of LPDs/GPDs/spontaneous BS on EEG, acute symptomatic etiology and treatment responsiveness. Conclusions Distinct electroclinical phenotypes characterized by different response to pharmacological intervention can be identified within the heterogeneity of SE with prominent motor phenomena., The study explored whether distinct phenotypes may be identified within status epilepticus (SE) with prominent motor symptoms. Average linkage hierarchical cluster analysis was performed. Three major electro‐clinical phenotypes were identified. The first cluster associated focal motor SE evolving into non‐convulsive SE (NCSE), presence of LPDs/GPDs on EEG, unknown etiology and treatment refractoriness. The second cluster linked convulsive and myoclonic SE evolving into NCSE, presence of spontaneous BS on EEG, progressive symptomatic etiology and super‐refractoriness. The third cluster gathered convulsive and myoclonic SE not evolving into other semiologies, absence of LPDs/GPDs/spontaneous BS on EEG, acute symptomatic etiology and treatment responsiveness.