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Background: Bioactive materials have now raised considerable attention for the treatment of osteoarthritis (OA), such as knee OA, rheumatoid OA, and temporomandibular joint (TMJ) OA. TMJ-OA is a common disease associated with an imbalance of cartilage regeneration, tissue inflammation, and disability in mouth movement. Recently, biological materials or molecules have been developed for TMJ-OA therapy; however, ideal treatment is still lacking. In this study, we used the combination of a human platelet rich plasma with hyaluronic acid (hPRP/HA) for TMJ-OA therapy to perform a clinical trial in dish to humans. Method: Herein, hPRP was prepared, and the hPRP/HA combined concentration was optimized by MTT assay. For the clinical trial in dish, pro-inflammatory-induced in-vitro and in-vivo mimic 3D TMJ-OA models were created, and proliferation, gene expression, alcian blue staining, and IHC were used to evaluate chondrocyte regeneration. For the animal studies, complete Freund's adjuvant (CFA) was used to induce the TMJ-OA rat model, and condyle and disc regeneration were investigated through MRI. For the clinical trial in humans, 12 patients with TMJ-OA who had disc displacement and pain were enrolled. The disc displacement and pain at baseline and six months were measured by MRI, and clinical assessment, respectively. Results: Combined hPRP/HA treatment ameliorated the proinflammatory-induced TMJ-OA model and promoted chondrocyte proliferation by activating SOX9, collagen type I/II, and aggrecan. TMJ-OA pathology–related inflammatory factors were efficiently downregulated with hPRP/HA treatment. Moreover, condylar cartilage was regenerated by hPRP/HA treatment in a proinflammatory-induced 3D neocartilage TMJ-OA-like model. During the animal studies, hPRP/HA treatment strongly repaired the condyle and disc in a CFA-induced TMJ-OA rat model. Furthermore, we performed a clinical trial in humans, and the MRI data demonstrated that after 6 months of treatment, hPRP/HA regenerated the condylar cartilage, reduced disc displacement, alleviated pain, and increased the maximum mouth opening (MMO). Overall, clinical trials in dish to human results revealed that hPRP/HA promoted cartilage regeneration, inhibited inflammation, reduced pain, and increased joint function in TMJ-OA. Conclusion: Conclusively, this study highlighted the therapeutic potential of the hPRP and HA combination for TMJ-OA therapy, with detailed evidence from bench to bedside. Trial registration Taipei Medical University Hospital (TMU-JIRB No. N201711041). Registered 24 November 2017. https://tmujcrc.tmu.edu.tw/inquiry_general.php. [ABSTRACT FROM AUTHOR]

Background: On the basis of visual-dependent reading method, radiological recognition and assessment of neonatal hyperbilirubinemia (NH) or acute bilirubin encephalopathy (ABE) on conventional magnetic resonance imaging (MRI) sequences are challenging. Prior studies had shown that radiomics was possible to characterize ABE-induced intensity and morphological changes on MRI sequences, and it has emerged as a desirable and promising future in quantitative and objective MRI data extraction. To investigate the utility of radiomics based on T1-weighted sequences for identifying neonatal ABE in patients with hyperbilirubinemia and differentiating between those with NH and the normal controls. Methods: A total of 88 patients with NH were enrolled, including 50 patients with ABE and 38 ABE-negative individuals, and 70 age-matched normal neonates were included as controls. All participants were divided into training and validation cohorts in a 7:3 ratio. Radiomics features extracted from the basal ganglia of T1-weighted sequences on magnetic resonance imaging were evaluated and selected to set up the prediction model using the K-nearest neighbour-based bagging algorithm. A receiver operating characteristic curve was plotted to assess the differentiating performance of the radiomics-based model. Results: Four of 744 radiomics features were selected for the diagnostic model of ABE. The radiomics model yielded an area under the curve (AUC) of 0.81 and 0.82 in the training and test cohorts, with accuracy, precision, sensitivity, and specificity of 0.82, 0.80, 0.91, and 0.69 and 0.78, 0.8, 0.8, and 0.75, respectively. Six radiomics features were selected in this model to distinguish those with NH from the normal controls. The AUC for the training cohort was 0.97, with an accuracy of 0.92, a precision of 0.92, a sensitivity of 0.93, and a specificity of 0.90. The performance of the radiomics model was confirmed by testing the test cohort, and the AUC, accuracy, precision, sensitivity, and specificity were 0.97, 0.92, 0.96, 0.89, and 0.95, respectively. Conclusions: The proposed radiomics model based on traditional TI-weighted sequences may be used effectively for identifying ABE and even differentiating patients with NH from the normal controls, which can provide microcosmic information beyond experience-dependent vision and potentially assist in clinical diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Background: Autism spectrum disorder (ASD) is a heritable condition related to brain development that affects a person's perception and socialization with others. Here, we examined variability in the brain morphology in ASD children and adolescent individuals at the level of brain cortical structural profiles and the level of each brain regional measure. Methods: We selected brain structural MRI data in 600 ASDs and 729 normal controls (NCs) from Autism Brain Imaging Data Exchange (ABIDE). The personalized estimate of similarity between gray matter volume (GMV) profiles of an individual to that of others in the same group was assessed by using the person-based similarity index (PBSI). Regional contributions to PBSI score were utilized for brain age gap estimation (BrainAGE) prediction model establishment, including support vector regression (SVR), relevance vector regression (RVR), and Gaussian process regression (GPR). The association between BrainAGE prediction in ASD and clinical performance was investigated. We further explored the related inter‐regional profiles of gene expression from the Allen Human Brain Atlas with variability differences in the brain morphology between groups. Results: The PBSI score of GMV was negatively related to age regardless of the sample group, and the PBSI score was significantly lower in ASDs than in NCs. The regional contributions to the PBSI score of 126 brain regions in ASDs showed significant differences compared to NCs. RVR model achieved the best performance for predicting brain age. Higher inter-individual brain morphology variability was related to increased brain age, specific to communication symptoms. A total of 430 genes belonging to various pathways were identified as associated with brain cortical morphometric variation. The pathways, including short-term memory, regulation of system process, and regulation of nervous system process, were dominated mainly by gene sets for manno midbrain neurotypes. Limitations: There is a sample mismatch between the gene expression data and brain imaging data from ABIDE. A larger sample size can contribute to the model training of BrainAGE and the validation of the results. Conclusions: ASD has personalized heterogeneity brain morphology. The brain age gap estimation and transcription-neuroimaging associations derived from this trait are replenished in an additional direction to boost the understanding of the ASD brain. [ABSTRACT FROM AUTHOR]

Background: The purpose of this study was to determine whether advanced quantitative magnetic resonance imaging (MRI) can be deployed outside of large, research-oriented academic hospitals and into community care settings to predict eventual pathological complete response (pCR) to neoadjuvant therapy (NAT) in patients with locally advanced breast cancer.Methods: Patients with stage II/III breast cancer (N = 28) were enrolled in a multicenter study performed in community radiology settings. Dynamic contrast-enhanced (DCE) and diffusion-weighted (DW)-MRI data were acquired at four time points during the course of NAT. Estimates of the vascular perfusion and permeability, as assessed by the volume transfer rate (Ktrans) using the Patlak model, were generated from the DCE-MRI data while estimates of cell density, as assessed by the apparent diffusion coefficient (ADC), were calculated from DW-MRI data. Tumor volume was calculated using semi-automatic segmentation and combined with Ktrans and ADC to yield bulk tumor blood flow and cellularity, respectively. The percent change in quantitative parameters at each MRI scan was calculated and compared to pathological response at the time of surgery. The predictive accuracy of each MRI parameter at different time points was quantified using receiver operating characteristic curves.Results: Tumor size and quantitative MRI parameters were similar at baseline between groups that achieved pCR (n = 8) and those that did not (n = 20). Patients achieving a pCR had a larger decline in volume and cellularity than those who did not achieve pCR after one cycle of NAT (p < 0.05). At the third and fourth MRI, changes in tumor volume, Ktrans, ADC, cellularity, and bulk tumor flow from baseline (pre-treatment) were all significantly greater (p < 0.05) in the cohort who achieved pCR compared to those patients with non-pCR.Conclusions: Quantitative analysis of DCE-MRI and DW-MRI can be implemented in the community care setting to accurately predict the response of breast cancer to NAT. Dissemination of quantitative MRI into the community setting allows for the incorporation of these parameters into the standard of care and increases the number of clinical community sites able to participate in novel drug trials that require quantitative MRI. [ABSTRACT FROM AUTHOR]

Background: Donepezil is an approved therapy for the treatment of Alzheimer's disease (AD). Results across clinical trials have been inconsistent, which may be explained by design-methodological issues, the pathophysiological heterogeneity of AD, and diversity of included study participants. We investigated whether response to donepezil differs in mild cognitive impaired (MCI) individuals demonstrating different magnetic resonance imaging (MRI) subtypes. Methods: From the Hippocampus Study double-blind, randomized clinical trial, we included 173 MCI individuals (donepezil = 83; placebo = 90) with structural MRI data, at baseline and at clinical follow-up assessments (6–12-month). Efficacy outcomes were the annualized percentage change (APC) in hippocampal, ventricular, and total grey matter volumes, as well as in the AD cortical thickness signature. Participants were classified into MRI subtypes as typical AD, limbic-predominant, hippocampal-sparing, or minimal atrophy at baseline. We primarily applied a subtyping approach based on continuous scale of two subtyping dimensions. We also used the conventional categorical subtyping approach for comparison. Results: Donepezil-treated MCI individuals showed slower atrophy rates compared to the placebo group, but only if they belonged to the minimal atrophy or hippocampal-sparing subtypes. Importantly, only the continuous subtyping approach, but not the conventional categorical approach, captured this differential response. Conclusions: Our data suggest that individuals with MCI, with hippocampal-sparing or minimal atrophy subtype, may have improved benefit from donepezil, as compared with MCI individuals with typical or limbic-predominant patterns of atrophy. The newly proposed continuous subtyping approach may have advantages compared to the conventional categorical approach. Future research is warranted to demonstrate the potential of subtype stratification for disease prognosis and response to treatment. Trial registration: ClinicalTrial.gov NCT00403520. Submission Date: November 21, 2006. [ABSTRACT FROM AUTHOR]

Background: The cerebellum plays key roles in the pathology of multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD), but the way in which these conditions affect how the cerebellum communicates with the rest of the brain (its connectome) and associated genetic correlates remains largely unknown. Methods: Combining multimodal MRI data from 208 MS patients, 200 NMOSD patients and 228 healthy controls and brain-wide transcriptional data, this study characterized convergent and divergent alterations in within-cerebellar and cerebello-cerebral morphological and functional connectivity in MS and NMOSD, and further explored the association between the connectivity alterations and gene expression profiles. Results: Despite numerous common alterations in the two conditions, diagnosis-specific increases in cerebellar morphological connectivity were found in MS within the cerebellar secondary motor module, and in NMOSD between cerebellar primary motor module and cerebral motor- and sensory-related areas. Both diseases also exhibited decreased functional connectivity between cerebellar motor modules and cerebral association cortices with MS-specific decreases within cerebellar secondary motor module and NMOSD-specific decreases between cerebellar motor modules and cerebral limbic and default-mode regions. Transcriptional data explained > 37.5% variance of the cerebellar functional alterations in MS with the most correlated genes enriched in signaling and ion transport-related processes and preferentially located in excitatory and inhibitory neurons. For NMOSD, similar results were found but with the most correlated genes also preferentially located in astrocytes and microglia. Finally, we showed that cerebellar connectivity can help distinguish the three groups from each other with morphological connectivity as predominant features for differentiating the patients from controls while functional connectivity for discriminating the two diseases. Conclusions: We demonstrate convergent and divergent cerebellar connectome alterations and associated transcriptomic signatures between MS and NMOSD, providing insight into shared and unique neurobiological mechanisms underlying these two diseases. [ABSTRACT FROM AUTHOR]

Background: The isolated rapid-eye-movement sleep behavior disorder (iRBD) is a prodromal condition of Lewy body disease including Parkinson's disease and dementia with Lewy bodies (DLB). We aim to investigate the longitudinal evolution of DLB-related cortical thickness signature in a prospective iRBD cohort and evaluate the possible predictive value of the cortical signature index in predicting dementia-first phenoconversion in individuals with iRBD. Methods: We enrolled 22 DLB patients, 44 healthy controls, and 50 video polysomnography-proven iRBD patients. Participants underwent 3-T magnetic resonance imaging (MRI) and clinical/neuropsychological evaluations. We characterized DLB-related whole-brain cortical thickness spatial covariance pattern (DLB-pattern) using scaled subprofile model of principal components analysis that best differentiated DLB patients from age-matched controls. We analyzed clinical and neuropsychological correlates of the DLB-pattern expression scores and the mean values of the whole-brain cortical thickness in DLB and iRBD patients. With repeated MRI data during the follow-up in our prospective iRBD cohort, we investigated the longitudinal evolution of the cortical thickness signature toward Lewy body dementia. Finally, we analyzed the potential predictive value of cortical thickness signature as a biomarker of phenoconversion in iRBD cohort. Results: The DLB-pattern was characterized by thinning of the temporal, orbitofrontal, and insular cortices and relative preservation of the precentral and inferior parietal cortices. The DLB-pattern expression scores correlated with attentional and frontal executive dysfunction (Trail Making Test-A and B: R = − 0.55, P = 0.024 and R = − 0.56, P = 0.036, respectively) as well as visuospatial impairment (Rey-figure copy test: R = − 0.54, P = 0.0047). The longitudinal trajectory of DLB-pattern revealed an increasing pattern above the cut-off in the dementia-first phenoconverters (Pearson's correlation, R = 0.74, P = 6.8 × 10−4) but no significant change in parkinsonism-first phenoconverters (R = 0.0063, P = 0.98). The mean value of the whole-brain cortical thickness predicted phenoconversion in iRBD patients with hazard ratio of 9.33 [1.16–74.12]. The increase in DLB-pattern expression score discriminated dementia-first from parkinsonism-first phenoconversions with 88.2% accuracy. Conclusion: Cortical thickness signature can effectively reflect the longitudinal evolution of Lewy body dementia in the iRBD population. Replication studies would further validate the utility of this imaging marker in iRBD. [ABSTRACT FROM AUTHOR]

Background: The cerebellum contains more than 50% of all neurons in the brain and is involved in a broad range of cognitive functions, including social communication and social cognition. Inconsistent atypicalities in the cerebellum have been reported in individuals with autism compared to controls suggesting the limits of categorical case control comparisons. Alternatively, investigating how clinical dimensions are related to neuroanatomical features, in line with the Research Domain Criteria approach, might be more relevant. We hypothesized that the volume of the "cognitive" lobules of the cerebellum would be associated with social difficulties. Methods: We analyzed structural MRI data from a large pediatric and transdiagnostic sample (Healthy Brain Network). We performed cerebellar parcellation with a well-validated automated segmentation pipeline (CERES). We studied how social communication abilities—assessed with the social component of the Social Responsiveness Scale (SRS)—were associated with the cerebellar structure, using linear mixed models and canonical correlation analysis. Results: In 850 children and teenagers (mean age 10.8 ± 3 years; range 5–18 years), we found a significant association between the cerebellum, IQ and social communication performance in our canonical correlation model. Limitations: Cerebellar parcellation relies on anatomical boundaries, which does not overlap with functional anatomy. The SRS was originally designed to identify social impairments associated with autism spectrum disorders. Conclusion: Our results unravel a complex relationship between cerebellar structure, social performance and IQ and provide support for the involvement of the cerebellum in social and cognitive processes. [ABSTRACT FROM AUTHOR]

Background: Long-term follow-up using volumetric measurement could significantly assist in the management of vestibular schwannomas (VS). Manual segmentation of VS from MRI for treatment planning and follow-up assessment is labor-intensive and time-consuming. This study aims to develop a deep learning technique to fully automatically segment VS from MRI. Methods: This study retrospectively analyzed MRI data of 737 patients who received gamma knife radiosurgery for VS. Treatment planning T1-weighted isotropic MR and manually contoured gross tumor volumes (GTV) were used for model development. A 3D convolutional neural network (CNN) was built on ResNet blocks. Spatial attenuation and deep supervision modules were integrated in each decoder level to enhance the training for the small tumor volume on brain MRI. The model was trained and tested on 587 and 150 patient data, respectively, from this institution (n = 495) and a publicly available dataset (n = 242). The model performance were assessed by the Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), average symmetric surface (ASSD) and relative absolute volume difference (RAVD) of the model segmentation results against the GTVs. Results: Measured on combined testing data from two institutions, the proposed method achieved mean DSC of 0.91 ± 0.08, ASSD of 0.3 ± 0.4 mm, HD95 of 1.3 ± 1.6 mm, and RAVD of 0.09 ± 0.15. The DSCs were 0.91 ± 0.09 and 0.92 ± 0.06 on 100 testing patients of this institution and 50 of the public data, respectively. Conclusions: A CNN model was developed for fully automated segmentation of VS on T1-Weighted isotropic MRI. The model achieved good performance compared with physician clinical delineations on a sizeable dataset from two institutions. The proposed method potentially facilitates clinical workflow of radiosurgery for VS patient management. [ABSTRACT FROM AUTHOR]

Background: Major depressive disorder (MDD) with atypical features, namely depression with atypical features (AFD), is one of the most common clinical specifiers of MDD, closely associated with bipolar disorder (BD). However, there is still a lack of clinical guidelines for the diagnosis, treatment, and prognosis of AFD. Our study mainly focuses on three issues about how to identify AFD, what is the appropriate individualized treatment for AFD, and what are the predictive biomarkers of conversion to BD. Methods: The Study of Individualized Diagnosis and Treatment for Depression with Atypical Features (iDoT-AFD) is a multicenter, prospective, open-label study consisting of a 12-week randomized controlled trial (RCT) and a continued follow-up until 4 years or reaching the study endpoint. It is enrolling 480 patients with AFD (120 per treatment arm), 100 patients with BD, and 100 healthy controls (HC). Multivariate dimension information is collected including clinical features, cognitive function, kynurenine pathway metabolomics, and multimodal magnetic resonance imaging (MRI) data. Firstly, multivariate informatics analyses are performed to recognize patients with AFD from participants including the first-episode and recurrent atypical depression, patients with BD, and patients with HC. Secondly, patients with atypical depression are randomly allocated to one of the four treatment groups including "single application of selective serotonin reuptake inhibitor (SSRI) or serotonin-noradrenaline reuptake inhibitor (SNRI)", "SSRI/SNRI combined with mood stabilizer," "SSRI/SNRI combined with quetiapine (≥ 150 mg/day)," or "treatment as usual (TAU)" and then followed up 12 weeks to find out the optimized treatment strategies. Thirdly, patients with atypical depression are followed up until 4 years or switching to BD, to explore the risk factors of conversion from atypical depression to BD and eventually build the risk warning model of conversion to BD. Discussion: The first enrolment was in August 2019. The iDoT-AFD study explores the clinical and biological markers for the diagnosis, treatment, and prognosis of AFD and further provides evidence for clinical guidelines of AFD. Trial registration: ClinicalTrials.gov NCT04209166. Registered on December 19, 2019. [ABSTRACT FROM AUTHOR]

Introduction: Although machine learning classifiers have been frequently used to detect Alzheimer's disease (AD) based on structural brain MRI data, potential bias with respect to sex and age has not yet been addressed. Here, we examine a state-of-the-art AD classifier for potential sex and age bias even in the case of balanced training data. Methods: Based on an age- and sex-balanced cohort of 432 subjects (306 healthy controls, 126 subjects with AD) extracted from the ADNI data base, we trained a convolutional neural network to detect AD in MRI brain scans and performed ten different random training-validation-test splits to increase robustness of the results. Classifier decisions for single subjects were explained using layer-wise relevance propagation. Results: The classifier performed significantly better for women (balanced accuracy 87.58 ± 1.14 % ) than for men ( 79.05 ± 1.27 % ). No significant differences were found in clinical AD scores, ruling out a disparity in disease severity as a cause for the performance difference. Analysis of the explanations revealed a larger variance in regional brain areas for male subjects compared to female subjects. Discussion: The identified sex differences cannot be attributed to an imbalanced training dataset and therefore point to the importance of examining and reporting classifier performance across population subgroups to increase transparency and algorithmic fairness. Collecting more data especially among underrepresented subgroups and balancing the dataset are important but do not always guarantee a fair outcome. [ABSTRACT FROM AUTHOR]

Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by impaired social and communication skills, narrow interests, and repetitive behavior. It is known that the cerebellum plays a vital role in controlling movement and gait posture. However, recently, researchers have reported that the cerebellum may also be responsible for other functions, such as social cognition, reward, anxiety, language, and executive functions. Methods: In this study, we ascertained volumetric differences from cerebellar lobular analysis from children with ASD, ASD siblings, and typically developing healthy controls. In this cross-sectional study, a total of 30 children were recruited, including children with ASD (N = 15; mean age = 27.67 ± 5.1 months), ASD siblings (N = 6; mean age = 17.5 ± 3.79 months), and typically developing children (N = 9; mean age = 17.67 ± 3.21 months). All the MRI data was acquired under natural sleep without using any sedative medication. We performed a correlation analysis with volumetric data and developmental and behavioral measures obtained from these children. Two-way ANOVA and Pearson correlation was performed for statistical data analysis. Results: We observed intriguing findings from this study, including significantly increased gray matter lobular volumes in multiple cerebellar regions including; vermis, left and right lobule I–V, right CrusII, and right VIIb and VIIIb, respectively, in children with ASD, compared to typically developing healthy controls and ASD siblings. Multiple cerebellar lobular volumes were also significantly correlated with social quotient, cognition, language, and motor scores with children with ASD, ASD siblings, and healthy controls, respectively. Conclusions: This research finding helps us understand the neurobiology of ASD and ASD-siblings, and critically advances current knowledge about the cerebellar role in ASD. However, results need to be replicated for a larger cohort from longitudinal research study in future. [ABSTRACT FROM AUTHOR]

Background: The present study determines the feasibility of generating an average arterial input function (Avg-AIF) from a limited population of patients with neck nodal metastases to be used for pharmacokinetic modeling of dynamic contrast-enhanced MRI (DCE-MRI) data in clinical trials of larger populations. Methods: Twenty patients (mean age 50 years [range 27-77 years]) with neck nodal metastases underwent pretreatment DCE-MRI studies with a temporal resolution of 3.75 to 7.5 sec on a 1.5T clinical MRI scanner. Eleven individual AIFs (Ind-AIFs) met the criteria of expected enhancement pattern and were used to generate Avg-AIF. Tofts model was used to calculate pharmacokinetic DCE-MRI parameters. Bland-Altman plots and paired Student t-tests were used to describe significant differences between the pharmacokinetic parameters obtained from individual and average AIFs. Results: Ind-AIFs obtained from eleven patients were used to calculate the Avg-AIF. No overall significant difference (bias) was observed for the transfer constant (Ktrans) measured with Ind-AIFs compared to Avg-AIF (p = 0.20 for region-of- interest (ROI) analysis and p = 0.18 for histogram median analysis). Similarly, no overall significant difference was observed for interstitial fluid space volume fraction (ve) measured with Ind-AIFs compared to Avg-AIF (p = 0.48 for ROI analysis and p = 0.93 for histogram median analysis). However, the Bland-Altman plot suggests that as Ktrans increases, the Ind-AIF estimates tend to become proportionally higher than the Avg-AIF estimates. Conclusion: We found no statistically significant overall bias in Ktrans or ve estimates derived from Avg-AIF, generated from a limited population, as compared with Ind-AIFs. However, further study is needed to determine whether calibration is needed across the range of Ktrans. The Avg-AIF obtained from a limited population may be used for pharmacokinetic modeling of DCE-MRI data in larger population studies with neck nodal metastases. Further validation of the Avg-AIF approach with a larger population and in multiple regions is desirable. [ABSTRACT FROM AUTHOR]

Background: Uterine adenomyosis is a benign disease, common among women in their 40 and 50 s, characterised by ectopic endometrial tissue in the uterine myometrial layer. Adenomyosis causes infertility and has a negative effect on the outcomes of in vitro fertilisation (IVF)/intracytoplasmic sperm injection (ICSI) embryo transfer (ET) cycles. It has also been reported to have different characteristics depending on the adenomyotic lesion localisation. The effect of its localisation on IVF/ICSI-ET outcomes is unclear. This study aimed to investigate whether adenomyotic lesion localisation, assessed using magnetic resonance imaging (MRI), was associated with outcomes of IVF/ICSI-ET cycles. Methods: This multicentre, joint, retrospective cohort study analysed the medical records of 67 infertile patients with adenomyosis who underwent IVF/ICSI with fresh and frozen-thawed ET at five participating facilities from January 2012 to December 2016 and for whom MRI data were available. Fifteen patients were excluded; therefore, the MRI data of 52 patients were evaluated by two radiologists. We assessed the localisation of and classified adenomyotic lesions into advanced (invades the full thickness of the uterine myometrium), extrinsic (localised on the serosal side), and intrinsic (localised on the endometrial side) subtypes. Results: There were 40 advanced, nine extrinsic, and three intrinsic cases, and the outcomes of 100, 27, and nine ET cycles, respectively, were analysed. Pregnancy loss/clinical pregnancy and live birth rates of the advanced, extrinsic, and intrinsic groups were 64 % (16/25) and 9 % (9/100), 33.3 % (3/9) and 22.2 % (6/27), and 50 % (1/2) and 11.1 % (1/9), respectively. A logistic regression analysis adjusted for age, prior miscarriage, and body mass index showed that the extrinsic group had fewer pregnancy losses (odds ratio 0.06; 95 % confidence interval [CI]: 0.00–0.54, p = 0.026) and more live births (odds ratio 6.05; 95 % CI: 1.41–29.65, p = 0.018) than the advanced group. Conclusions: Adenomyotic lesions exert different effects on IVF/ICSI-ET outcomes. Thus, MRI assessments of adenomyosis in infertile patients are beneficial. Establishment of treatment plans based on adenomyotic lesion localisation should be considered. [ABSTRACT FROM AUTHOR]

Background: Many medical imaging techniques utilize fitting approaches for quantitative parameter estimation and analysis. Common examples are pharmacokinetic modeling in dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI)/computed tomography (CT), apparent diffusion coefficient calculations and intravoxel incoherent motion modeling in diffusion-weighted MRI and Z-spectra analysis in chemical exchange saturation transfer MRI. Most available software tools are limited to a special purpose and do not allow for own developments and extensions. Furthermore, they are mostly designed as stand-alone solutions using external frameworks and thus cannot be easily incorporated natively in the analysis workflow. Results: We present a framework for medical image fitting tasks that is included in the Medical Imaging Interaction Toolkit MITK, following a rigorous open-source, well-integrated and operating system independent policy. Software engineering-wise, the local models, the fitting infrastructure and the results representation are abstracted and thus can be easily adapted to any model fitting task on image data, independent of image modality or model. Several ready-to-use libraries for model fitting and use-cases, including fit evaluation and visualization, were implemented. Their embedding into MITK allows for easy data loading, pre- and post-processing and thus a natural inclusion of model fitting into an overarching workflow. As an example, we present a comprehensive set of plug-ins for the analysis of DCE MRI data, which we validated on existing and novel digital phantoms, yielding competitive deviations between fit and ground truth. Conclusions: Providing a very flexible environment, our software mainly addresses developers of medical imaging software that includes model fitting algorithms and tools. Additionally, the framework is of high interest to users in the domain of perfusion MRI, as it offers feature-rich, freely available, validated tools to perform pharmacokinetic analysis on DCE MRI data, with both interactive and automatized batch processing workflows. [ABSTRACT FROM AUTHOR]

Background: In preclinical Alzheimer’s disease, it is unclear why some individuals with amyloid pathologic change are asymptomatic (stage 1), whereas others experience subjective cognitive decline (SCD, stage 2). Here, we examined the association of stage 1 vs. stage 2 with structural brain reserve in memory-related brain regions. Methods: We tested whether the volumes of hippocampal subfields and parahippocampal regions were larger in individuals at stage 1 compared to asymptomatic amyloid-negative older adults (healthy controls, HCs). We also tested whether individuals with stage 2 would show the opposite pattern, namely smaller brain volumes than in amyloid-negative individuals with SCD. Participants with cerebrospinal fluid (CSF) biomarker data and bilateral volumetric MRI data from the observational, multi-centric DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE) study were included. The sample comprised 95 amyloid-negative and 26 amyloid-positive asymptomatic participants as well as 104 amyloid-negative and 47 amyloid-positive individuals with SCD. Volumes were based on high-resolution T2-weighted images and automatic segmentation with manual correction according to a recently established high-resolution segmentation protocol. Results: In asymptomatic individuals, brain volumes of hippocampal subfields and of the parahippocampal cortex were numerically larger in stage 1 compared to HCs, whereas the opposite was the case in individuals with SCD. MANOVAs with volumes as dependent data and age, sex, years of education, and DELCODE site as covariates showed a significant interaction between diagnosis (asymptomatic versus SCD) and amyloid status (Aß42/40 negative versus positive) for hippocampal subfields. Post hoc paired comparisons taking into account the same covariates showed that dentate gyrus and CA1 volumes in SCD were significantly smaller in amyloid-positive than negative individuals. In contrast, CA1 volumes were significantly (p = 0.014) larger in stage 1 compared with HCs. Conclusions: These data indicate that HCs and stages 1 and 2 do not correspond to linear brain volume reduction. Instead, stage 1 is associated with larger than expected volumes of hippocampal subfields in the face of amyloid pathology. This indicates a brain reserve mechanism in stage 1 that enables individuals with amyloid pathologic change to be cognitively normal and asymptomatic without subjective cognitive decline. [ABSTRACT FROM AUTHOR]

Background and purpose: Ki-67 labeling index (LI) is an important indicator of tumor cell proliferation in glioma, which can only be obtained by postoperative biopsy at present. This study aimed to explore the correlation between Ki-67 LI and apparent diffusion coefficient (ADC) parameters and to predict the level of Ki-67 LI noninvasively before surgery by multiple MRI characteristics. Methods: Preoperative MRI data of 166 patients with pathologically confirmed glioma in our hospital from 2016 to 2020 were retrospectively analyzed. The cut-off point of Ki-67 LI for glioma grading was defined. The differences in MRI characteristics were compared between the low and high Ki-67 LI groups. The receiver operating characteristic (ROC) curve was used to estimate the accuracy of each ADC parameter in predicting the Ki-67 level, and finally a multivariate logistic regression model was constructed based on the results of ROC analysis. Results: ADCmin, ADCmean, rADCmin, rADCmean and Ki-67 LI showed a negative correlation (r = − 0.478, r = − 0.369, r = − 0.488, r = − 0.388, all P < 0.001). The Ki-67 LI of low-grade gliomas (LGGs) was different from that of high-grade gliomas (HGGs), and the cut-off point of Ki-67 LI for distinguishing LGGs from HGGs was 9.5%, with an area under the ROC curve (AUROC) of 0.962 (95%CI 0.933–0.990). The ADC parameters in the high Ki-67 group were significantly lower than those in the low Ki-67 group (all P < 0.05). The peritumoral edema (PTE) of gliomas in the high Ki-67 LI group was higher than that in the low Ki-67 LI group (P < 0.05). The AUROC of Ki-67 LI level assessed by the multivariate logistic regression model was 0.800 (95%CI 0.721–0.879). Conclusions: There was a negative correlation between ADC parameters and Ki-67 LI, and the multivariate logistic regression model combined with peritumoral edema and ADC parameters could improve the prediction ability of Ki-67 LI. [ABSTRACT FROM AUTHOR]

Background: At present, there is no consensus on the optimal biomechanical method for Posterior cruciate ligament (PCL) reconstruction, and the "critical corner" that is produced by the femoral tunnel is currently considered to be one of the main reasons for PCL failure. Thus, the purpose of this study was to identify one or several different tunnels of the femur, thereby reducing the influence of the "critical corner" without reducing the posterior stability of the knee. Methods: CT and MRI data of the knee joint of a healthy adult man were collected, and computer-related software was used to reconstruct the finite element model of the knee joint, to provide different properties to different materials and to allow for the performance of a finite element analysis of the reconstructed model. The position of the femoral tunnel was positioned and partitioned according to anatomical posture, and three areas were divided (the antero-proximal region, the antero-distal region and the posterior region). In addition, we applied a posterior tibial load of 134 N to the reconstructed model, recorded and compared different tunnels of the femur, conducted peak stress at the flexion of the knee joint of 0°, 30°, 60° and 90°, and elicited the displacement of the proximal tibia. Results: Among the 20 different femoral tunnels, the graft peak stress was lower in tunnels 4, 12 and 18 than in the PCL anatomical footpath tunnel 13, especially at high flexion angles (60° and 90°). These three tunnels did not increase the posterior displacement of the proximal tibia compared with the anatomical footpath tunnel 13. Conclusion: In summary, among the options for PCL reconstruction of the femoral tunnel, the tunnels located 5 mm distal to the footprint and 5 mm anterior to the footprint could reduce the peak stress of the graft; additionally, it may reduce the "critical corner" and was shown to not reduce the posterior stability of the knee joint. [ABSTRACT FROM AUTHOR]

Background: Detecting changes in pulsatile cerebrospinal fluid (CSF) flow may assist clinical management decisions, but spinal CSF flow is relatively understudied. Traumatic spinal cord injuries (SCI) often cause spinal cord swelling and subarachnoid space (SAS) obstruction, potentially causing pulsatile CSF flow changes. Pigs are emerging as a favoured large animal SCI model; therefore, the aim of this study was to characterise CSF flow along the healthy pig spine. Methods: Phase-contrast magnetic resonance images (PC-MRI), retrospectively cardiac gated, were acquired for fourteen laterally recumbent, anaesthetised and ventilated, female domestic pigs (22–29 kg). Axial images were obtained at C2/C3, T8/T9, T11/T12 and L1/L2. Dorsal and ventral SAS regions of interest (ROI) were manually segmented. CSF flow and velocity were determined throughout a cardiac cycle. Linear mixed-effects models, with post-hoc comparisons, were used to identify differences in peak systolic/diastolic flow, and maximum velocity (cranial/caudal), across spinal levels and dorsal/ventral SAS. Velocity wave speed from C2/C3 to L1/L2 was calculated. Results: PC-MRI data were obtained for 11/14 animals. Pulsatile CSF flow was observed at all spinal levels. Peak systolic flow was greater at C2/C3 (dorsal: − 0.32 ± 0.14 mL/s, ventral: − 0.15 ± 0.13 mL/s) than T8/T9 dorsally (− 0.04 ± 0.03 mL/s; p < 0.001), but not different ventrally (− 0.08 ± 0.08 mL/s; p = 0.275), and no difference between thoracolumbar levels (p > 0.05). Peak diastolic flow was greater at C2/C3 (0.29 ± 0.08 mL/s) compared to T8/T9 (0.03 ± 0.03 mL/s, p < 0.001) dorsally, but not different ventrally (p = 1.000). Cranial and caudal maximum velocity at C2/C3 were greater than thoracolumbar levels dorsally (p < 0.001), and T8/T9 and L1/L2 ventrally (p = 0.022). Diastolic velocity wave speed was 1.41 ± 0.39 m/s dorsally and 1.22 ± 0.21 m/s ventrally, and systolic velocity wave speed was 1.02 ± 0.25 m/s dorsally and 0.91 ± 0.22 m/s ventrally. Conclusions: In anaesthetised and ventilated domestic pigs, spinal CSF has lower pulsatile flow and slower velocity wave propagation, compared to humans. This study provides baseline CSF flow at spinal levels relevant for future SCI research in this animal model. [ABSTRACT FROM AUTHOR]

Background: Atrial fibrillation (AF) is a strong risk factor for Alzheimer's disease (AD) independent of ischemic stroke. However, the clinicopathological impact of AF on the severity of AD has not been well elucidated. We aimed to investigate the clinical differences between dementia patients with AF and those without AF by means of imaging data. Methods: Following approval from the institutional ethics committee, patients with newly diagnosed AD or amnestic mild cognitive impairment (aMCI) were retrospectively screened (n = 170, 79.5 ± 7.4 years old). Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Based on the MRI data, the cerebral volume, cerebral microbleeds (CMBs), periventricular white matter lesions (WMLs), and deep WMLs were evaluated. The regional cerebral blood flow (rCBF) was measured using 123I-IMP SPECT. Results: Of the patients, 14 (8.2%) and 156 (91.8%) had AF (AF group) and sinus rhythm (SR group), respectively. The AF group had significantly lower MMSE scores than the SR group (average [standard deviation (SD)]: 19.4 [4.4] and 22.0 [4.4], respectively; p = 0.0347). Cerebral volume and CMBs did not differ between the two groups. The periventricular WMLs, but not the deep WMLs, were significantly larger in the AF group than in the SR group (mean [SD] mL: 6.85 [3.78] and 4.37 [3.21], respectively; p = 0.0070). However, there was no significant difference in rCBF in the areas related to AD pathology between the two groups. Conclusion: AD and aMCI patients with AF showed worse cognitive decline along with larger periventricular WMLs compared to those with SR, although the reduction of rCBF was not different between patients with AF and SR. The white matter lesions may be a more important pathology than the impairment of cerebral blood flow in dementia patients with AF. A larger study is needed to confirm our findings in the future. [ABSTRACT FROM AUTHOR]

Background: Neurological soft signs (NSS) are often reported in patients with schizophrenia and may vary with psychopathological symptoms during the course of disease. Many cross-sectional neuroimaging studies have shown that NSS are associated with disturbed network connectivity in schizophrenia. However, it remains unclear how these associations change over time during the course of disorder. Methods: In present study, 20 patients with first-episode schizophrenia and 20 controls underwent baseline structural magnetic resonance imaging (MRI) scan and at one-year follow-up. Structural network characteristics of patients and controls were analyzed using graph theoretical approach based on MRI data. NSS were assessed using the Heidelberg scale. Results: At baseline, patients demonstrated significant changes of the local network properties mainly involving regions of the cortical-subcortical-cerebellar circuits compared to healthy controls. For further analysis, the whole patient group was dichotomized into a NSS-persisting and NSS-decreasing subgroup. After one-year follow-up, the NSS-persisting subgroup showed decreased betweenness in right inferior opercular frontal cortex, left superior medial frontal cortex, left superior temporal cortex, right putamen and cerebellum vermis and increased betweenness in right lingual cortex. However, the NSS-decreasing subgroup exhibited only localized changes in right middle temporal cortex, right insula and right fusiform with decreased betweenness, and in left lingual cortex with increased betweenness. Conclusions: These findings provide evidence for brain network reorganization subsequent to clinical disease manifestation in patients with first-episode schizophrenia, and support the hypothesis that persisting NSS refer to progressive brain network abnormalities in patients with schizophrenia. Therefore, NSS could help to establish a better prognosis in first-episode schizophrenia patients. [ABSTRACT FROM AUTHOR]

Background: The heterogeneity within Alzheimer's disease (AD) seriously challenges the development of disease-modifying treatments. We investigated volume of the basal forebrain, hippocampus, and precuneus in atrophy subtypes of AD and explored the relevance of subtype stratification in a small clinical trial on encapsulated cell biodelivery (ECB) of nerve growth factor (NGF) to the basal forebrain. Methods: Structural MRI data was collected for 90 amyloid-positive patients and 69 amyloid-negative healthy controls at baseline, 6-, 12-, and 24-month follow-up. The effect of the NGF treatment was investigated in 10 biopsy-verified AD patients with structural MRI data at baseline and at 6- or 12-month follow-up. Patients were classified as typical, limbic-predominant, hippocampal-sparing, or minimal atrophy AD, using a validated visual assessment method. Volumetric analyses were performed using a region-of-interest approach. Results: All AD subtypes showed reduced basal forebrain volume as compared with the healthy controls. The limbic-predominant subtype showed the fastest basal forebrain atrophy rate, whereas the minimal atrophy subtype did not show any significant volume decline over time. Atrophy rates of the hippocampus and precuneus also differed across subtypes. Our preliminary data from the small NGF cohort suggest that the NGF treatment seemed to slow the rate of atrophy in the precuneus and hippocampus in some hippocampal-sparing AD patients and in one typical AD patient. Conclusions: The cholinergic system is differentially affected in distinct atrophy subtypes of AD. Larger studies in the future should confirm that this differential involvement of the cholinergic system may contribute to subtype-specific response to cholinergic treatment. Our preliminary findings suggest that future clinical trials should target specific subtypes of AD, or at least report treatment effects stratified by subtype. Trial registration: ClinicalTrials.gov identifier: NCT01163825. Registered 14 July 2010. [ABSTRACT FROM AUTHOR]

Background: Uterine fibroid embolisation (UFE) is an established treatment method for symptomatic uterine myomas. This study evaluates the efficacy of UFE using objective magnetic resonance imaging (MRI) data for size and perfusion analysis as well as patient questionnaires assessing fibroid-related symptoms. Method: Patients underwent MR-Angiography before UFE and 4 days, 6 and 12 months after the procedure. The images were evaluated using dedicated software. Patient questionnaires were completed before UFE and at 12 months follow-up, focussing on the embolization procedure and symptoms associated with uterine fibroids. Statistical analysis of the questionnaires was performed using paired sample t-test and Wilcoxon signed rank test, while Kruskal–Wallis test and Friedman test were applied for MRI-analysis. Results: Eleven women were included. There was a significant reduction in fibroid-related symptoms. The volume reduction after 12 months was significant in both, uterus and myomas, after an initial increase in uterine volume at the first post-interventional MRI. The perfusion analysis showed that blood flow to the fibroids could be significantly reduced up to 12 months after UFE while uterine tissue was not affected. Conclusion: This study shows that uterine fibroid embolisation induces a significant long-term decrease in myoma size and perfusion while healthy uterine tissue remains unaffected. Fibroid-related symptoms are reduced for the sake of improved quality of life. [ABSTRACT FROM AUTHOR]

Background: Seizures can occur unpredictably in patients with acute encephalitis syndrome (AES), and many suffer from poor long-term neurological sequelae. Establishing factors associated with acute seizures risk and poor outcomes could support clinical care. We aimed to conduct regional and volumetric analysis of cerebral oedema on magnetic resonance imaging (MRI) in patients with AES. We assessed the relationship of brain oedema with acute seizure activity and long-term neurological outcome. Methods: In a multi-centre cohort study, adults and children presenting with an AES were recruited in the UK. The clinical and brain MRI data were retrospectively reviewed. The outcomes variables were inpatient acute seizure activity and neurological disability at six-months post-discharge. A poor outcome was defined as a Glasgow outcome score (GOS) of 1–3. We quantified regional brain oedema on MRI through stereological examination of T2-weighted images using established methodology by independent and blinded assessors. Clinical and neuroimaging variables were analysed by multivariate logistic regression to assess for correlation with acute seizure activity and outcome. Results: The study cohort comprised 69 patients (mean age 31.8 years; 53.6% female), of whom 41 (59.4%) had acute seizures as inpatients. A higher Glasgow coma scale (GCS) score on admission was a negative predictor of seizures (OR 0.61 [0.46–0.83], p = 0.001). Even correcting for GCS on admission, the presence of cortical oedema was a significant risk factor for acute seizure activity (OR 5.48 [1.62–18.51], p = 0.006) and greater volume of cerebral oedema in these cortical structures increased the risk of acute seizures (OR 1.90 [1.12–3.21], p = 0.017). At six-month post-discharge, 21 (30.4%) had a poor neurological outcome. Herpes simplex virus encephalitis was associated with higher risk of poor outcomes in univariate analysis (OR 3.92 [1.08–14.20], p = 0.038). When controlling for aetiology, increased volume of cerebral oedema was an independent risk factor for adverse neurological outcome at 6 months (OR 1.73 [1.06–2.83], p = 0.027). Conclusions: Both the presence and degree of cerebral oedema on MRIs of patients with AES may help identify patients at risk of acute seizure activity and subsequent long-term morbidity. [ABSTRACT FROM AUTHOR]

Background: Meniscus root tear is an uncommon but detrimental injury of the knee. Hoop stress is lost during meniscus root tear, which can lead to excessive tibiofemoral contact pressure and early development of osteoarthritis. Posterolateral meniscus root tears (PLRT) are more commonly associated with anterior cruciate ligament (ACL) tears. As the lateral compartment is less congruent than the medial compartment, it is more susceptible to a shearing force, which is increased in the ACL-deficient knee. In accordance with the compressive axial load, the increase in the tibial slope would generate a greater shearing force. The additional lateral compartment mobility caused by ACL tear should be reduced after ACL reconstruction (ACLR). However, there is a lack of evidence to conclude that ACLR can sufficiently limit the effect of large tibial slope (LTS) on the healing after PLRT repair. This study aimed to evaluate whether a steep LTS would be a risk factor for poorer clinical outcomes after PLRT repair concomitant with ACLR. Methods: In this retrospective study, a chart review was conducted to identify patients with concomitant unilateral primary ACLR and PLRT repair. Patients with a partial tear or healed tear were excluded. Postoperative MRI and clinical assessments were performed at a mean follow up of 35 months. MRI data was used to measure the LTS, medial tibial slope (MTS), coronal tibial slope (CTS), the lateral-to-medial slope difference (LTS-MTS) and meniscus healing and extrusion. Functional outcomes were evaluated by patient-reported outcomes (International Knee Documentation Committee [IKDC], Lysholm and Tegner scores) and KT-1000 arthrometer assessment. Interobserver reproducibility was assessed by two reviewers. Results: Twenty-five patients were identified for the analysis. Patients with larger LTS and larger LTS-MTS differences were shown to be correlated with poorer IKDC scores after surgery (R = -0.472, p = 0.017 and R = -0.429, p = 0.032, respectively). Herein, patients with LTS ≥ 6° or LTS-MTS ≥ 3° demonstrated poorer IKDC scores. Conclusion: A large LTS (≥ 6°) and a large difference of LTS-MTS (≥ 3°) were shown to be risk factors for poorer functional and radiological outcomes for PLRT repair in patients after ACLR. Clinically, closer monitoring and a more stringent rehabilitation plan for patients with LTS ≥ 6° or LTS-MTS ≥ 3° would be recommended. [ABSTRACT FROM AUTHOR]

Background: To investigate the potential value of the pretreatment MRI-based radiomic model in predicting the overall survival (OS) of nasopharyngeal carcinoma (NPC) patients with local residual tumors after intensity-modulated radiotherapy (IMRT). Methods: A total of 218 consecutive nonmetastatic NPC patients with local residual tumors after IMRT [training cohort (n = 173) and validation cohort (n = 45)] were retrospectively included in this study. Clinical and MRI data were obtained. Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) were used to select the radiomic features from pretreatment MRI. The clinical, radiomic, and combined models for predicting OS were constructed. The models' performances were evaluated using Harrell's concordance index (C-index), calibration curve, and decision curve analysis. Results: The C-index of the radiomic model was higher than that of the clinical model, with the C-index of 0.788 (95% CI 0.724–0.852) versus 0.672 (95% CI 0.599–0.745) in the training cohort and 0.753 (95% CI 0.604–0.902) versus 0.634 (95% CI 0.593–0.675) in the validation cohort. Calibration curves showed good agreement between the radiomic model-predicted probability of 2- and 3-year OS and the actual observed probability in the training and validation groups. Decision curve analysis showed that the radiomic model had higher clinical usefulness than the clinical model. The discrimination of the combined model improved significantly in the training cohort (P < 0.01) but not in the validation cohort, with the C-index of 0.834 and 0.734, respectively. The radiomic model divided patients into high- and low-risk groups with a significant difference in OS in both the training and validation cohorts. Conclusions: Pretreatment MRI-based radiomic model may improve OS prediction in NPC patients with local residual tumors after IMRT and may assist in clinical decision-making. [ABSTRACT FROM AUTHOR]

Background: This study aimed to quantify the morphological changes of temporomandibular joint (TMJ) discs after disc repositioning surgery using the three-dimensional (3D) modeling. Methods: Thirty patients who diagnosed with unilateral ADDwoR were included to compare the morphological differences between ADDWoR discs and normal discs, and fifteen patients who experienced unilateral or bilateral disc repositioning surgery were included to analyze the morphological changes before and after disc repositioning surgery. Disc 3D reconstruction and analyses were performed using magnetic resonance imaging (MRI) data. Results: In the unilateral ADDwoR patients, volume, superficial area, length, and maximum longitudinal-sectional area of the ADDwoR disc were significantly smaller compared with the non-affected discs. However, there was no significant difference in width and cross-sectional areas between ADDwoR discs and non-affected discs. In patients who subjected to disc repositioning surgery, disc volume, superficial area, length, width and maximum longitudinal-sectional area of TMJ discs were markedly increased 6 months after surgery. Conclusions: This study demonstrated that the TMJ discs tended to be morphologically smaller in volume and shorter in length under ADDwoR status. Importantly, the ADDwoR discs tended to morphologically recover toward non-affected discs after 6 months follow-up following TMJ disc repositioning surgery. [ABSTRACT FROM AUTHOR]

Background: We aimed to analyze the computed tomography (CT) and magnetic resonance imaging (MRI) findings of gouty arthritis primarily involving the large joints of the upper limbs, signal or density characteristics of the tophi, growth patterns, involvement of the adjacent joints, and differentiation from other lesions occurring in this area and to discuss the causes of misdiagnosis. Methods: CT and MRI data were collected from 14 patients with gouty arthritis, primarily involving the shoulder and elbow joints, and their imaging features were analyzed. Results: All the patiens were ranged from 28-85 years old, and the tophi deposition can be observed on either CT or MRI.The tophi deposition apperas as slightly higher density nodules or masses on CT images,or nodules or masses on MRI with isosignal/hypointensity on T1WI and hyperintensity on T2WI. Five patients showed narrowing of the affected joint space, four had different degrees of bone erosion under the articular surface, eight developed joint effusion, and all showed surrounding soft tissue swelling. The tophi grew around the joint, with anterolateral and posterolateral tophi predominantly in the shoulder joint and dorsal tophi predominantly in the elbow joint on the MRI, with compression and edema of the surrounding soft tissues. Conclusions: Gouty arthritis occurs in the large joints of the upper limbs and is characterized by fluid accumulation in the joint capsule and the formation of tophi. These tophi are usually large, with subcutaneous bone resorption and erosion, with or without cartilage destruction. However, extensive edema appeared in the soft tissue around the tophi, but the edema only produced pressure without any obvious signs of soft tissue infiltration, which may be distinguished from the joint tumor. In addition, the gout incidence rate is increased in young patients. Therefore, when the patient has a large joint mass, it is important to confirm whether there is a history of gout. [ABSTRACT FROM AUTHOR]

Introduction: Pre-treatment risk and prognostic groups are the cornerstone for deciding management in non-metastatic prostate cancer. All however, were developed in the pre-MRI era. Here we compared categorisation of cancers using either only clinical parameters or with MRI enhanced information in men referred for suspected prostate cancer from an unscreened population.Patient and Methods: Data from men referred from primary care to our diagnostic service and with both clinical (digital rectal examination [DRE] and systematic biopsies) and MRI enhanced attributes (MRI stage and combined systematic/targeted biopsies) were used for this study. Clinical vs MRI data were contrasted for clinico-pathological and risk group re-distribution using the European Association of Urology (EAU), American Urological Association (AUA) and UK National Institute for Health Care Excellence (NICE) Cambridge Prognostic Group (CPG) models. Differences were retrofitted to a population cohort with long-term prostate cancer mortality (PCM) outcomes to simulate impact on model performance. We further contrasted individualised overall survival (OS) predictions using the Predict Prostate algorithm.Results: Data from 370 men were included (median age 66y). Pre-biopsy MRI stage reassignments occurred in 7.8% (versus DRE). Image-guided biopsies increased Grade Group 2 and ≥ Grade Group 3 assignments in 2.7% and 2.9% respectively. The main change in risk groups was more high-risk cancers (6.2% increase in the EAU and AUA system, 4.3% increase in CPG4 and 1.9% CPG5). When extrapolated to a historical population-based cohort (n = 10,139) the redistribution resulted in generally lower concordance indices for PCM. The 5-tier NICE-CPG system outperformed the 4-tier AUA and 3-tier EAU models (C Index 0.70 versus 0.65 and 0.64). Using an individualised prognostic model, changes in predicted OS were small (median difference 1% and 2% at 10- and 15-years' respectively). Similarly, estimated treatment survival benefit changes were minimal (1% at both 10- and 15-years' time frame).Conclusion: MRI guided diagnostics does change pre-treatment risk groups assignments but the overall prognostic impact appears modest in men referred from unscreened populations. Particularly, when using more granular tiers or individualised prognostic models. Existing risk and prognostic models can continue to be used to counsel men about treatment option until long term survival outcomes are available. [ABSTRACT FROM AUTHOR]

Background: Multiple sclerosis (MS) is an inflammatory and degenerative disease of the central nervous system with an increasing worldwide prevalence. Since 1993, more than 15 disease-modifying immunotherapies (DMTs) have been licenced and have shown moderate efficacy in clinical trials. Based on the heterogeneity of the disease and the partial effectiveness of therapies, a personalised medicine approach would be valuable taking individual prognosis and suitability of a chosen therapy into account to gain the best possible treatment effect. The primary objective of this review is to assess the differential treatment effects of all approved DMTs in subgroups of adults with clinically isolated syndrome or relapsing forms of MS. We will analyse possible treatment effect modifiers (TEM) defined by baseline demographic characteristics (gender, age), and diagnostic (i.e. MRI measures) and clinical (i.e. relapses, disability level) measures of MS disease activity. Methods: We will include all published and accessible unpublished primary and secondary analyses of randomised controlled trials (RCTs) with a follow-up of at least 12 months investigating the efficacy of at least one approved DMT, with placebo or other approved DMTs as control intervention(s) in subgroups of trial participants. As the primary outcome, we will address disability as defined by the Expanded Disability Status Scale or multiple sclerosis functional composite scores followed by relapse frequency, quality of life measures, and side effects. MRI data will be analysed as secondary outcomes. MEDLINE, EMBASE, CINAHL, LILACS, CENTRAL and major trial registers will be searched for suitable studies. Titles and abstracts and full texts will be screened by two persons independently using Covidence. The risk of bias will be analysed based on the Cochrane "Risk of Bias 2" tool, and the certainty of evidence will be assessed using GRADE. Treatment effects will be reported as rate ratio or odds ratio. Primary analyses will follow the intention-to-treat principle. Meta-analyses will be carried out using random-effects models. Discussion: Given that individual patient data from clinical studies are often not available, the review will allow to analyse the evidence on TEM in MS immunotherapy and thus support clinical decision making in individual cases. Systematic review registration: PROSPERO CRD42021279665. [ABSTRACT FROM AUTHOR]

Background: Given the aging population worldwide and the COVID-19 pandemic, which has been found to be associated with a deterioration in Alzheimer's disease (AD) symptoms, investigating methods to prevent or delay cognitive decline in preclinical AD and AD itself is important. The trial described in this protocol aims to evaluate the effects of a staged integral art-based cognitive intervention (SIACI) in older adults with CIs (preclinical AD [SCD or MCI] and mild AD), in order to gather evidence on the effects of SIACI on cognition and psychological/psychosocial health gains and determine the mechanisms. Methods: The planned study is a single-center, parallel-arm, randomized controlled trial with allocation concealment and outcome assessor blinding. A total of 88 participants will be randomized to two groups: (i) an intervention group that receives the 16-week, 24-session SIACI program and (ii) a waitlist control group (which will receive the SIACI program after completing the follow-up assessment). Global cognitive function, specific domains of cognition (memory, language, executive function, and visuospatial skills), and other health-related outcomes (quality of life, anxiety, depression, sleep quality, and physical activity level) will be measured at baseline, immediately after the intervention, and at the 6-month follow-up. Blood biomarkers, event-related potential (ERP)-P300, and magnetic resonance imaging (MRI) data will be collected at baseline and immediately after the intervention to explore the mechanisms of SIACI. Discussion: The trial will elucidate the immediate and long-term effects of SIACI based on neuropsychological testing and blood biomarkers, and neuroscience involving ERP-P300 and MRI parameters will make it possible to explore the mechanisms of SIACI in older adults with CIs. The results will provide evidence on the effectiveness of an AT-based cognitive intervention, which may delay or even halt cognitive decline in preclinical AD and AD itself. Trial registration: ChiCTR, ChiCTR2100044959. Registered 03 April 2021. [ABSTRACT FROM AUTHOR]

Background: Identifying the causal genes at the risk loci and elucidating their roles in schizophrenia (SCZ) pathogenesis remain significant challenges. To explore risk variants associated with gene expression in the human brain and to identify genes whose expression change may contribute to the susceptibility of SCZ, here we report a comprehensive integrative study on SCZ.Methods: We systematically integrated the genetic associations from a large-scale SCZ GWAS (N = 56,418) and brain expression quantitative trait loci (eQTL) data (N = 175) using a Bayesian statistical framework (Sherlock) and Summary data-based Mendelian Randomization (SMR). We also measured brain structure of 86 first-episode antipsychotic-naive schizophrenia patients and 152 healthy controls with the structural MRI.Results: Both Sherlock (P = 3. 38 × 10-6) and SMR (P = 1. 90 × 10-8) analyses showed that TYW5 mRNA expression was significantly associated with risk of SCZ. Brain-based studies also identified a significant association between TYW5 protein abundance and SCZ. The single-nucleotide polymorphism rs203772 showed significant association with SCZ and the risk allele is associated with higher transcriptional level of TYW5 in the prefrontal cortex. We further found that TYW5 was significantly upregulated in the brain tissues of SCZ cases compared with controls. In addition, TYW5 expression was also significantly higher in neurons induced from pluripotent stem cells of schizophrenia cases compared with controls. Finally, combining analysis of genotyping and MRI data showed that rs203772 was significantly associated with gray matter volume of the right middle frontal gyrus and left precuneus.Conclusions: We confirmed that TYW5 is a risk gene for SCZ. Our results provide useful information toward a better understanding of the genetic mechanism of TYW5 in risk of SCZ. [ABSTRACT FROM AUTHOR]

Background: Notch volume is associated with anterior cruciate ligament (ACL) injury. Manual tracking of intercondylar notch on MR images is time-consuming and laborious. Deep learning has become a powerful tool for processing medical images. This study aims to develop an MRI segmentation model of intercondylar fossa based on deep learning to automatically measure notch volume, and explore its correlation with ACL injury.Methods: The MRI data of 363 subjects (311 males and 52 females) with ACL injuries incurred during non-contact sports and 232 subjects (147 males and 85 females) with intact ACL were retrospectively analyzed. Each layer of intercondylar fossa was manually traced by radiologists on axial MR images. Notch volume was then calculated. We constructed an automatic segmentation system based on the architecture of Res-UNet for intercondylar fossa and used dice similarity coefficient (DSC) to compare the performance of segmentation systems by different networks. Unpaired t-test was performed to determine differences in notch volume between ACL-injured and intact groups, and between males and females.Results: The DSCs of intercondylar fossa based on different networks were all more than 0.90, and Res-UNet showed the best performance. The notch volume was significantly lower in the ACL-injured group than in the control group (6.12 ± 1.34 cm3 vs. 6.95 ± 1.75 cm3, P < 0.001). Females had lower notch volume than males (5.41 ± 1.30 cm3 vs. 6.76 ± 1.51 cm3, P < 0.001). Males and females who had ACL injuries had smaller notch than those with intact ACL (p < 0.001 and p < 0.005). Men had larger notches than women, regardless of the ACL injuries (p < 0.001).Conclusion: Using a deep neural network to segment intercondylar fossa automatically provides a technical support for the clinical prediction and prevention of ACL injury and re-injury after surgery. [ABSTRACT FROM AUTHOR]

Importance: The entry of artificial intelligence into medicine is pending. Several methods have been used for the predictions of structured neuroimaging data, yet nobody compared them in this context. Objective: Multi-class prediction is key for building computational aid systems for differential diagnosis. We compared support vector machine, random forest, gradient boosting, and deep feed-forward neural networks for the classification of different neurodegenerative syndromes based on structural magnetic resonance imaging. Design, setting, and participants: Atlas-based volumetry was performed on multi-centric T1-weighted MRI data from 940 subjects, i.e., 124 healthy controls and 816 patients with ten different neurodegenerative diseases, leading to a multi-diagnostic multi-class classification task with eleven different classes. Interventions: N.A. Main outcomes and measures: Cohen's kappa, accuracy, and F1-score to assess model performance. Results: Overall, the neural network produced both the best performance measures and the most robust results. The smaller classes however were better classified by either the ensemble learning methods or the support vector machine, while performance measures for small classes were comparatively low, as expected. Diseases with regionally specific and pronounced atrophy patterns were generally better classified than diseases with widespread and rather weak atrophy. Conclusions and relevance: Our study furthermore underlines the necessity of larger data sets but also calls for a careful consideration of different machine learning methods that can handle the type of data and the classification task best. [ABSTRACT FROM AUTHOR]

Background: Studies exploring topological properties of the metabolic network during the presymptomatic stage of genetic frontotemporal dementia (FTD) are scarce. However, such knowledge is important for understanding brain function and disease pathogenesis. Therefore, we aimed to explore FTD-specific patterns of metabolism topology reconfiguration in microtubule-associated protein tau (MAPT) mutation carriers before the onset of symptoms. Methods: Six asymptomatic carriers of the MAPT P301L mutation were compared with 12 non-carriers who all belonged to the same family of FTD. For comparison, we included 32 behavioral variant FTD (bvFTD) patients and 33 unrelated healthy controls. Each participant underwent neuropsychological assessments, genetic testing, and a hybrid positron emission tomography (PET)/magnetic resonance imaging (MRI) scan. Voxel-wise gray matter volumes and standardized uptake value ratios were calculated and compared for structural MRI and fluorodeoxyglucose (FDG)-PET, separately. The sparse inverse covariance estimation method (SICE) was applied to topological properties and metabolic connectomes of brain functional networks derived from 18F-FDG PET/MRI data. Independent component analysis was used to explore the metabolic connectivity of the salience (SN) and default mode networks (DMN). Results: The asymptomatic MAPT carriers performed normal global parameters of the metabolism network, whereas bvFTD patients did not. However, we revealed lost hubs in the ventromedial prefrontal, orbitofrontal, and anterior cingulate cortices and reconfigured hubs in the anterior insula, precuneus, and posterior cingulate cortex in asymptomatic carriers compared with non-carriers, which overlapped with the comparisons between bvFTD patients and controls. Similarly, significant differences in local parameters of these nodes were present between asymptomatic carriers and non-carriers. The reduction in the connectivity of lost hub regions and the enhancement of connectivity between reconfigured hubs and components of the frontal cortex were marked during the asymptomatic stage. Metabolic connectivity within the SN and DMN was enhanced in asymptomatic carriers compared with non-mutation carriers but reduced in bvFTD patients relative to controls. Conclusions: Our findings showed that metabolism topology reconfiguration, characterized by the earliest involvement of medial prefrontal areas and active compensation in task-related regions, was present in the presymptomatic phase of genetic FTD with MAPT mutation, which may be used as an imaging biomarker of increased risk of FTD. [ABSTRACT FROM AUTHOR]

Background Early hormone-positive breast cancers typically have favorable outcomes, yet long-term surveillance is crucial due to the risk of late recurrences. While many studies associate MMP-11 expression with poor prognosis in breast cancer, few focus on early-stage cases. This study explores MMP-11 as an early prognostic marker in hormonepositive breast cancers. Methods In this retrospective study, 228 women with early hormone-positive invasive ductal carcinoma, treated surgically between 2011 and 2016, were included. MMP-11 expression was measured by immunohistochemistry, and its association with clinical and MRI data was analyzed. Results Among the patients (aged 31–89, median 60, with average tumor size of 15.7 mm), MMP-11 staining was observed in half of the cases. This positivity correlated with higher uPA levels and tumor grade but not with nodal status or size. Furthermore, MMP-11 positivity showed specific associations with MRI features. Over a follow-up period of 6.5 years, only 12 oncological events occurred. Disease-free survival was linked to Ki67 and MMP-11. Conclusion MMP-11, primarily present in tumor-surrounding stromal cells, correlates with tumor grade and uPA levels. MMP-11 immunohistochemical score demonstrates a suggestive trend in association with disease-free survival, independent of Ki67 and other traditional prognostic factors. This highlights the potential of MMP-11 as a valuable marker in managing early hormone-positive breast cancer. [ABSTRACT FROM AUTHOR]

Background: Cognitive impairments are prevalent across mood disorders and psychosis spectrum disorders, but there is a lack of real-life-like cognitive training programmes. Fully immersive virtual reality has the potential to ensure motivating and engaging cognitive training directly relevant to patients' daily lives. We will examine the effect of a 4-week, intensive virtual reality-based cognitive remediation programme involving daily life challenges on cognition and daily life functioning in patients with mood disorders or psychosis spectrum disorders and explore the neuronal underpinnings of potential treatment efficacy. Methods: The trial has a randomized, controlled, double-blinded, parallel-group design. We will include 66 symptomatically stable outpatients with mood disorders or psychosis spectrum disorders aged 18–55 years with objective and subjective cognitive impairment. Assessments encompassing a virtual reality test of daily life cognitive skills, neuropsychological testing, measures of daily life functioning, symptom ratings, questionnaires on subjective cognitive complaints, and quality of life are carried out at baseline, after the end of 4 weeks of treatment and at a 3-month follow-up after treatment completion. Functional magnetic resonance imaging scans are performed at baseline and at the end of treatment. The primary outcome is a broad cognitive composite score comprising five subtasks on a novel ecologically valid virtual reality test of daily life cognitive functions. Two complete data sets for 54 patients will provide a power of 80% to detect a clinically relevant between-group difference in the primary outcome. Behavioural data will be analysed using linear mixed models in SPSS, while MRI data will be analysed with the FMRIB Expert Analysis Tool (FEAT). Treatment-related changes in neural activity from baseline to end of treatment will be investigated for the dorsal prefrontal cortex and hippocampus as the regions of interest. Discussion: The results will provide insight into whether virtual reality-based cognitive remediation has beneficial effects on cognition and functioning in symptomatically stable patients with mood disorders or psychosis spectrum disorders, which can aid future treatment development. Trial registration: ClinicalTrials.gov NCT06038955. Registered on September 15, 2023. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder is one of the most common neurodevelopmental conditions associated with sensory and social communication impairments. Previous neuroimaging studies reported that atypical nodal- or network-level functional brain organization in individuals with autism was associated with autistic behaviors. Although dimensionality reduction techniques have the potential to uncover new biomarkers, the analysis of whole-brain structural connectome abnormalities in a low-dimensional latent space is underinvestigated. In this study, we utilized autoencoder-based feature representation learning for diffusion magnetic resonance imaging-based structural connectivity in 80 individuals with autism and 61 neurotypical controls that passed strict quality controls. We generated low-dimensional latent features using the autoencoder model for each group and adopted an integrated gradient approach to assess the contribution of the input data for predicting latent features during the encoding process. Subsequently, we compared the integrated gradient values between individuals with autism and neurotypical controls and observed differences within the transmodal regions and between the sensory and limbic systems. Finally, we identified significant associations between integrated gradient values and communication abilities in individuals with autism. Our findings provide insights into the whole-brain structural connectome in autism and may help identify potential biomarkers for autistic connectopathy. [ABSTRACT FROM AUTHOR]

Background: Dementia with Lewy bodies (DLB) is the second most common dementia type in patients older than 65 years. Its atrophy patterns remain unknown. Its similarities to Parkinson's disease and differences from Alzheimer's disease are subjects of current research.Methods: The aim of our study was (i) to form a group of patients with DLB (and a control group) and create a 3D MRI data set (ii) to volumetrically analyze the entire brain in these groups, (iii) to evaluate visual and manual metric measurements of the innominate substance for real-time diagnosis, and (iv) to compare our groups and results with the latest literature. We identified 102 patients with diagnosed DLB in our psychiatric and neurophysiological archives. After exclusion, 63 patients with valid 3D data sets remained. We compared them with a control group of 25 patients of equal age and sex distribution. We evaluated the atrophy patterns in both (1) manually and (2) via Fast Surfers segmentation and volumetric calculations. Subgroup analyses were done of the CSF data and quality of 3D T1 data sets.Results: Concordant with the literature, we detected moderate, symmetric atrophy of the hippocampus, entorhinal cortex and amygdala, as well as asymmetric atrophy of the right parahippocampal gyrus in DLB. The caudate nucleus was unaffected in patients with DLB, while all the other measured territories were slightly too moderately atrophied. The area under the curve analysis of the left hippocampus volume ratio (< 3646mm3) revealed optimal 76% sensitivity and 100% specificity (followed by the right hippocampus and left amygdala). The substantia innominata's visual score attained a 51% optimal sensitivity and 84% specificity, and the measured distance 51% optimal sensitivity and 68% specificity in differentiating DLB from our control group.Conclusions: In contrast to other studies, we observed a caudate nucleus sparing atrophy of the whole brain in patients with DLB. As the caudate nucleus is known to be the last survivor in dopamine-uptake, this could be the result of an overstimulation or compensation mechanism deserving further investigation. Its relative hypertrophy compared to all other brain regions could enable an imaging based identification of patients with DLB via automated segmentation and combined volumetric analysis of the hippocampus and amygdala. [ABSTRACT FROM AUTHOR]

Background: Cervical extension and flexion are presumably harmful to patients with degenerative cervical myelopathy (DCM) because they worsen medullary compression visible on dynamic magnetic resonance imaging (MRI). Dynamic somatosensory evoked potentials (SSEPs) are an objective tool to measure the electrophysiological function of the spinal cord at different neck positions. In contrast to previous hypotheses, a considerable proportion of patients with DCM present improved SSEPs upon extension and flexion compared to a neutral position.Methods: Patients with DCM who underwent preoperative dynamic SSEP examinations and subsequent decompression surgeries between 2015 and 2019 were retrospectively evaluated. We compared extension and flexion SSEPs with neutral SSEPs in each patient and classified them into extension-improved (EI) or extension-nonimproved (EN) and flexion-improved (FI) or flexion-nonimproved (FN) groups. Preoperative clinical evaluations, decompression surgical methods and one-year follow-up clinical data were recorded. Cervical spondylolisthesis and cervical alignment types were evaluated on plain cervical lateral radiographs. The number of stenotic segments, Mühle stenosis grade and disc degeneration stage of the most severe segment, and presence of ligamentum flavum hypertrophy and intramedullary T2 weighted imaging (T2WI) hyperintensity were evaluated on lateral and axial MRI. Data were compared between the EN and EN groups or FI and FN groups with T-tests, chi-square tests or Kruskal-Wallis tests. Prediction criteria were determined with logistic regression analyses.Results: Forty-nine patients were included, and 9 (18.4%) and 11 (22.4%) showed improved extension and flexion SSEPs compared to their own neutral SSEPs, respectively. Interestingly, EI or FI patients had significantly better one-year postoperative mJOA recoveries than EN or FN patients (T-test, P < 0.001). Moreover, the disease duration (T-test, P = 0.024), involved segment number (Kruskal-Wallis test, P < 0.001), and cervical alignment type (chi-square test, P = 0.005) varied significantly between the EI and EN groups. The FI group presented a significantly higher Mühle stenosis grade than the FN group (Kruskal-Wallis test, P = 0.038). Furthermore, ≤ 2 involved segments and straight or sigmoid cervical alignment were significant criteria predicting improved extension SSEPs (probability: 85.7%), while Mühle stenosis Grade 3 and disease duration ≤6 months were significant criteria predicting improved flexion SSEPs (probability: 85.7%).Conclusions: Our findings provide evidence for neurophysiological improvement in patients with DCM at extension and flexion and its significance in predicting prognoses. Moreover, certain clinical and radiographic criteria may help predict neurophysiological improvement upon extension or flexion.Trial Registration: " [2020]151 ". Retrospectively registered on April 30, 2020. [ABSTRACT FROM AUTHOR]

Background: Clinical and etiological varieties remain major obstacles to decompose heterogeneity in autism spectrum disorders (ASD). Recently, neuroimaging raised new hope to identify neurosubtypes of ASD for further understanding the biological mechanisms behind the disorder. Methods: In this study, brain structural MRI data and clinical measures of 221 male subjects with ASD and 257 healthy controls were selected from 7 independent sites from the Autism Brain Image Data Exchange database (ABIDE). Heterogeneity through discriminative analysis (HYDRA), a recently-proposed semi-supervised clustering method was utilized to divide individuals with ASD into several neurosubtypes by regional volumetric measures of gray matter, white matter, and cerebrospinal fluid. Voxel-wise volume, clinical measures, dynamic resting-state functional magnetic resonance imaging (R-fMRI) measures among different neurosubtypes of ASD were explored. In addition, support vector machine (SVM) model was applied to test whether the neurosubtyping of ASD could improve diagnostic accuracy of ASD. Results: Two neurosubtypes of ASD with different voxel-wise volumetric patterns were revealed. The full-scale intelligence quotient (IQ), verbal IQ, Autism Diagnostic Observation Schedule (ADOS) total scores and ADOS severity scores were significantly different between the two neurosubtypes, the total intracranial volume was correlated with performance IQ in Subtype 1 and was correlated with ADOS communication score and ADOS social score in Subtype 2. Compared with Subtype 2, Subtype 1 showed lower dynamic R-fMRI measures, lower dynamic functional architecture stability, higher mean and lower standard deviation (SD) of concordance among dynamic R-fMRI measures in cerebellum. In addition, classification accuracies between ASD neurosubtypes and healthy controls were significantly improved compared with classification accuracy between entire ASD group and healthy controls. Limitations: The present study excluded female subjects and left-handed subjects, which limited the ability to investigate the associations between these factors and the heterogeneity of ASD. Conclusions: The two distinct neuroanatomical subtypes of ASD validated by other data modalities not only adds reliability of the result, but also bridges from brain phenomenology to clinical behavior. The current neurosubtypes of ASD could facilitate understanding the neuropathology of this disorder and could be potentially used to improve clinical decision-making process and optimize treatment. [ABSTRACT FROM AUTHOR]

Background: More patients with left-hemispheric than right-hemispheric strokes are admitted to hospitals. This is due to the easier recognition of cortical symptoms of the dominant-hemisphere. The thalamus constitutes a "micromodel" of the brain cortex with structure-function relationships known to be asymmetric, especially for language, memory, and visuo-spatial neurocognitive functions. The goal of this study was to characterize clinical symptoms and lesion distribution patterns of patients with acute isolated thalamic stroke (ITS) and to evaluate whether leftsided lesions are overrepresented in the hospital. Methods: We performed a radiological database search including all brain scans performed in the Center of Neurology and Neurosurgery of the University Hospital Frankfurt between 2010 and 2019. A total of 5733 patients presenting with acute ischemic stroke were screened for ITS. Based on the MRI data, a lesion-overlap map was then generated to visualize the ITS lesion distribution. Results: Fifty-eight patients with unilateral ITS were identified. A majority of 38 patients (65.5%) showed left-sided ITS, whereas only 20 patients (34.5%) had right-sided ITS (p = 0.012). A particular difference was found for ITS lesions in the anterior thalamus of the anterolateral (n = 10) and anteromedian (n = 3) vascular territory, which were located in the left thalamus in 85% of patients (p = 0.011). No distribution difference was found for ITS lesions in the inferomedial (n = 7), central (n = 8), inferolateral (n = 23) and posterior (n = 7) vascular territories. The neuropsychological symptoms of thalamic aphasia (n = 8), neurocognitive impairment (n = 6), behavioral changes (n = 2), neglect (n = 2) and memory deficits (n = 3) were described predominantly in patients with left-sided ITS (p < 0.01). In contrast, other stroke symptoms (e.g., sensorimotor hemi-syndromes) did not reveal a side preponderance. Conclusions: The better recognizability of left anterior compared to right anterior thalamic stroke symptoms may have an impact on the frequency in which ITS patients are admitted to the hospital. Clinical characteristics of right anterior thalamic stroke should therefore be further investigated, and diagnostic instruments towards their detection be identified. [ABSTRACT FROM AUTHOR]

Background: Acupuncture is effective for reducing the symptoms of neck pain (NP). However, the underlying mechanisms are not fully elucidated. Based on evaluating the efficacy of two acupuncture prescriptions for treating NP, this study aims to investigate the potential central mechanism of acupuncture treatment for NP by functional magnetic resonance imaging (fMRI).Methods: This is a randomized controlled trial; 86 patients will be randomly assigned into two acupuncture treatment groups at a ratio of 1:1. The whole study period includes 2 weeks baseline, 2 weeks treatments, and 12 weeks follow-up (4 and 12 weeks after treatment). The pain severity, the neck disability index, the cervical range of motion, and the pressure pain threshold, etc., will be used to evaluate the clinical efficacy of two acupuncture prescriptions for NP treatment. The MRI scans will be performed to detect cerebral activity changes of 20 patients in each group. The clinical data and MRI data will be analyzed, respectively. Pearson correlation coefficient will be used to evaluate the association between changes of cerebral activity features and improvement of clinical symptoms.Discussion: The results will provide further evidence for the clinical application of acupuncture in the treatment of NP.Trial Registration: Chinese Clinical Trial Registry ChiCTR2000040930 . Registered on 16 December 2020. [ABSTRACT FROM AUTHOR]

Background: Appropriate structural and material properties are essential for finite-element-modeling (FEM). In knee FEM, structural information could extract through 3D-imaging, but the individual subject's tissue material properties are inaccessible.Purpose: The current study's purpose was to develop a methodology to estimate the subject-specific stiffness of the tibiofemoral joint using finite-element-analysis (FEA) and MRI data of knee joint with and without load.Methods: In this study, six Magnetic Resonance Imaging (MRI) datasets were acquired from 3 healthy volunteers with axially loaded and unloaded knee joint. The strain was computed from the tibiofemoral bone gap difference (ΔmBGFT) using the knee MR images with and without load. The knee FEM study was conducted using a subject-specific knee joint 3D-model and various soft-tissue stiffness values (1 to 50 MPa) to develop subject-specific stiffness versus strain models.Results: Less than 1.02% absolute convergence error was observed during the simulation. Subject-specific combined stiffness of weight-bearing tibiofemoral soft-tissue was estimated with mean values as 2.40 ± 0.17 MPa. Intra-subject variability has been observed during the repeat scan in 3 subjects as 0.27, 0.12, and 0.15 MPa, respectively. All subject-specific stiffness-strain relationship data was fitted well with power function (R2 = 0.997).Conclusion: The current study proposed a generalized mathematical model and a methodology to estimate subject-specific stiffness of the tibiofemoral joint for FEM analysis. Such a method might enhance the efficacy of FEM in implant design optimization and biomechanics for subject-specific studies. Trial registration The institutional ethics committee (IEC), Indian Institute of Technology, Delhi, India, approved the study on 20th September 2017, with reference number P-019; it was a pilot study, no clinical trail registration was recommended. [ABSTRACT FROM AUTHOR]

Background: In terms of diagnostic and therapeutic management, clinicians should adequately address the frequent aspects of temporomandibular joint (TMJ) osteoarthritis (OA) associated with disk displacement. Condylar erosion (CE) is considered an inflammatory subset of OA and is regarded as a sign of progressive OA changes potentially contributing to changes in dentofacial morphology or limited mandibular growth. The purpose of this study was to establish a risk prediction model of CE by a multivariate logistic regression analysis to predict the individual risk of CE in TMJ arthralgia. It was hypothesized that there was a closer association between CE and magnetic resonance imaging (MRI) indicators. Methods: This retrospective paired-design study enrolled 124 consecutive TMJ pain patients and analyzed the clinical and TMJ-related MRI data in predicting CE. TMJ pain patients were categorized according to the research diagnostic criteria for temporomandibular disorders (RDC/TMD) Axis I protocol. Each patient underwent MRI examination of both TMJs, 1–7 days following clinical examination. Results: In the univariate analysis analyses, 9 influencing factors were related to CE, of which the following 4 as predictors determined the binary multivariate logistic regression model: missing posterior teeth (odds ratio [OR] = 1.42; P = 0.018), RDC/TMD of arthralgia coexistant with disk displacement without reduction with limited opening (DDwoR/wLO) (OR = 3.30, P = 0.007), MRI finding of disk displacement without reduction (OR = 10.96, P < 0.001), and MRI finding of bone marrow edema (OR = 11.97, P < 0.001). The model had statistical significance (chi-square = 148.239, Nagelkerke R square = 0.612, P < 0.001). Out of the TMJs, 83.9% were correctly predicted to be CE cases or Non-CE cases with a sensitivity of 81.4% and a specificity of 85.2%. The area under the receiver operating characteristic curve was 0.916. Conclusion: The established prediction model using the risk factors of TMJ arthralgia may be useful for predicting the risk of CE. The data suggest MRI indicators as dominant factors in the definition of CE. Further research is needed to improve the model, and confirm the validity and reliability of the model. [ABSTRACT FROM AUTHOR]

Background: Mobile 3-dimensional fluoroscopes are an integral part of modern neurosurgical operating theatres and can also be used in combination with free available image post processing to depict cerebral vessels. In preparation of stereotactic surgery, preoperative Computed Tomography (CT) may be required for image fusion. Contrast CT may be of further advantage for image fusion as it regards the vessel anatomy in trajectory planning. Time-consuming in-hospital transports are necessary for this purpose. Mobile 3D-fluoroscopes may be used to generate a CT equal preoperative data set without an in-hospital transport. This study was performed to determine the feasibility and image quality of intraoperative 3-dimensional fluoroscopy with intravenous contrast administration in combination with stereotactical procedures. Methods: 6 patients were included in this feasibility study. After fixation in a radiolucent Mayfield clamp a rotational fluoroscopy scan was performed with 50 mL iodine contrast agent. The image data sets were merged with the existing MRI images at a planning station and visually evaluated by two observer. The operation times were compared between the frame-based and frameless systems ("skin-to-skin" and "OR entry to exit"). Results: The procedure proves to be safe. The entire procedure from fluoroscope positioning to the transfer to the planning station took 5–6 min with an image acquisition time of 24 s. In 5 of 6 cases, the fused imaging was able to reproduce the vascular anatomy accurately and in good quality. Both time end-points were significantly shorter compared to frame-based interventions. Conclusion: The images could easily be transferred to the planning and navigation system and were successfully merged with the MRI data set. The procedure can be completely integrated into the surgical workflow. Preoperative CT imaging or transport under anaesthesia may even be replaced by this technique in the future. Furthermore, hemorrhages can be successfully visualized intraoperatively and might prevent time delays in emergencies. [ABSTRACT FROM AUTHOR]

Background: Increased catabolism has recently been recognized as a clinical manifestation of amyotrophic lateral sclerosis (ALS). The hypothalamic systems have been shown to be involved in the metabolic dysfunction in ALS, but the exact extent of hypothalamic circuit alterations in ALS is yet to be determined. Here we explored the integrity of large-scale cortico-hypothalamic circuits involved in energy homeostasis in murine models and in ALS patients. Methods: The rAAV2-based large-scale projection mapping and image analysis pipeline based on Wholebrain and Ilastik software suites were used to identify and quantify projections from the forebrain to the lateral hypothalamus in the SOD1(G93A) ALS mouse model (hypermetabolic) and the FusΔNLS ALS mouse model (normo-metabolic). 3 T diffusion tensor imaging (DTI)-magnetic resonance imaging (MRI) was performed on 83 ALS and 65 control cases to investigate cortical projections to the lateral hypothalamus (LHA) in ALS. Results: Symptomatic SOD1(G93A) mice displayed an expansion of projections from agranular insula, ventrolateral orbitofrontal and secondary motor cortex to the LHA. These findings were reproduced in an independent cohort by using a different analytic approach. In contrast, in the FusΔNLS ALS mouse model hypothalamic inputs from insula and orbitofrontal cortex were maintained while the projections from motor cortex were lost. The DTI-MRI data confirmed the disruption of the orbitofrontal-hypothalamic tract in ALS patients. Conclusion: This study provides converging murine and human data demonstrating the selective structural disruption of hypothalamic inputs in ALS as a promising factor contributing to the origin of the hypermetabolic phenotype. [ABSTRACT FROM AUTHOR]