Intelligent cholinergic white matter pathways algorithm based on U-net reflects cognitive impairment in patients with silent cerebrovascular disease.

BACKGROUND AND OBJECTIVE: The injury of the cholinergic white matter pathway underlies cognition decline in patients with silent cerebrovascular disease (SCD) with white matter hyperintensities (WMH) of vascular origin. However, the evaluation of the cholinergic white matter pathway is complex with poor consistency. We established an intelligent algorithm to evaluate WMH in the cholinergic pathway. METHODS: Patients with SCD with WMH of vascular origin were enrolled. The Cholinergic Pathways Hyperintensities Scale (CHIPS) was used to measure cholinergic white matter pathway impairment. The intelligent algorithm used a deep learning model based on convolutional neural networks to achieve WMH segmentation and CHIPS scoring. The diagnostic value of the intelligent algorithm for moderate-to-severe cholinergic pathway injury was calculated. The correlation between the WMH in the cholinergic pathway and cognitive function was analysed. RESULTS: A number of 464 patients with SCD were enrolled in internal training and test set. The algorithm was validated using data from an external cohort comprising 100 patients with SCD. The sensitivity, specificity and area under the curve of the intelligent algorithm to assess moderate and severe cholinergic white matter pathway injury were 91.7%, 87.3%, 0.903 (95% CI 0.861 to 0.952) and 86.5%, 81.3%, 0.868 (95% CI 0.819 to 0.921) for the internal test set and external validation set. for the. The general cognitive function, execution function and attention showed significant differences among the three groups of different CHIPS score (all p<0.05). DISCUSSION: We have established the first intelligent algorithm to evaluate the cholinergic white matter pathway with good accuracy compared with the gold standard. It helps more easily assess the cognitive function in patients with SCD.

U-fiber analysis: a toolbox for automated quantification of U-fibers and white matter hyperintensities.

Background: Whether white matter hyperintensities (WMHs) involve U-fibers is of great value in understanding the different etiologies of cerebral white matter (WM) lesions. However, clinical practice currently relies only on the naked eye to determine whether WMHs are in the vicinity of U-fibers, and there is a lack of good neuroimaging tools to quantify WMHs and U-fibers. Methods: Here, we developed a multimodal neuroimaging toolbox named U-fiber analysis (UFA) that can automatically extract WMHs and quantitatively characterize the volume and number of WMHs in different brain regions. In addition, we proposed an anatomically constrained U-fiber tracking scheme and quantitatively characterized the microstructure diffusion properties, fiber length, and number of U-fibers in different brain regions to help clinicians to quantitatively determine whether WMHs in the proximal cortex disrupt the microstructure of U-fibers. To validate the utility of the UFA toolbox, we analyzed the neuroimaging data from 246 patients with cerebral small vessel disease (cSVD) enrolled at Zhongshan Hospital between March 2018 and November 2019 in a cross-sectional study. Results: According to the manual judgment of the clinician, the patients with cSVD were divided into a WMHs involved U-fiber group (U-fiber-involved group, 51 cases) and WMHs not involved U-fiber group (U-fiber-spared group, 163 cases). There were no significant differences between the U-fiber-spared group and the U-fiber-involved group in terms of age (P=0.143), gender (P=0.462), education (P=0.151), Mini-Mental State Examination (MMSE) scores (P=0.151), and Montreal Cognitive Assessment (MoCA) scores (P=0.411). However, patients in the U-fiber-involved group had higher Fazekas scores (P<0.001) and significantly higher whole brain WMHs (P=0.046) and deep WMH volumes (P<0.001) compared to patients in the U-fiber-spared group. Moreover, the U-fiber-involved group had higher WMH volumes in the bilateral frontal [P(left) <0.001, P(right) <0.001] and parietal lobes [P(left) <0.001, P(right) <0.001]. On the other hand, patients in the U-fiber-involved group had higher mean diffusivity (MD) and axial diffusivity (AD) in the bilateral parietal [P(left, MD) =0.048, P(right, MD) =0.045, P(left, AD) =0.015, P(right, AD) =0.015] and right frontal-parietal regions [P(MD) =0.048, P(AD) =0.027], and had significantly reduced mean fiber length and number in the right parietal [P(length) =0.013, P(number) =0.028] and right frontal-parietal regions [P(length) =0.048] compared to patients in the U-fiber-spared group. Conclusions: Our results suggest that WMHs in the proximal cortex may disrupt the microstructure of U-fibers. Our tool may provide new insights into the understanding of WM lesions of different etiologies in the brain.

Association between gait features assessed by artificial intelligent system and cognitive function decline in patients with silent cerebrovascular disease: study protocol of a multicenter prospective cohort study (ACCURATE-2).

BACKGROUND: Gait disturbances may appear prior to cognitive dysfunction in the early stage of silent cerebrovascular disease (SCD). Subtle changes in gait characteristics may provide an early warning of later cognitive decline. Our team has proposed a vision-based artificial intelligent gait analyzer for the rapid detection of spatiotemporal parameters and walking pattern based on videos of the Timed Up and Go (TUG) test. The primary objective of this study is to investigate the relationship between gait features assessed by our artificial intelligent gait analyzer and cognitive function changes in patients with SCD. METHODS: This will be a multicenter prospective cohort study involving a total of 14 hospitals from Shanghai and Guizhou. One thousand and six hundred patients with SCD aged 60-85 years will be consecutively recruited. Eligible patients will undergo the intelligent gait assessment and neuropsychological evaluation at baseline and at 1-year follow-up. The intelligent gait analyzer will divide participant into normal gait group and abnormal gait group according to their walking performance in the TUG videos at baseline. All participants will be naturally observed during 1-year follow-up period. Primary outcome are the changes in Mini-Mental State Examination (MMSE) score. Secondary outcomes include the changes in intelligent gait spatiotemporal parameters (step length, gait speed, step frequency, step width, standing up time, and turning back time), the changes in scores on other neuropsychological tests (Montreal Cognitive Assessment, the Stroop Color Word Test, and Digit Span Test), falls events, and cerebrovascular events. We hypothesize that both groups will show a decline in MMSE score, but the decrease of MMSE score in the abnormal gait group will be more significant. CONCLUSION: This study will be the first to explore the relationship between gait features assessed by an artificial intelligent gait analyzer and cognitive decline in patients with SCD. It will demonstrate whether subtle gait abnormalities detected by the artificial intelligent gait analyzer can act as a cognitive-related marker for patients with SCD. TRIAL REGISTRATION: This trial was registered at ClinicalTrials.gov ( NCT04456348 ; 2 July 2020).

Randomised parallel trial on the effectiveness and cost-effectiveness in screening gait disorder of silent cerebrovascular disease assisted by artificial intelligent system versus clinical doctors (ACCURATE-1): study protocol.

IntroductionSilent cerebrovascular disease (SCD), which is a common disease in the elderly, leads to cognitive decline, gait disorders, depression and urination dysfunction, and increases the risk of cerebrovascular events. Our study aims to compare the accuracy of the diagnosis of SCD-related gait disorders between the intelligent system and the clinician. Our team have developed an intelligent evaluation system for gait. This study will evaluate whether the intelligent system can help doctors make clinical decisions and predictions, which aids the early prevention and treatment of SCD. METHODS AND ANALYSIS: This study is a multi-centred, prospective, randomised and controlled trial.SCD subjects aged 60-85 years in Shanghai and Guizhou will be recruited continuously. All subjects will randomly be divided into a doctor with intelligence assistance group or a doctor group, at a 1:1 ratio. The doctor and intelligent assistant group will accept the intelligent system evaluation. The intelligent system obtains gait parameters by an Red-Green-Blue-depth camera and computer vision algorithm. The doctor group will accept the clinicians' routine treatment procedures. Meanwhile, all subjects will accept the panel's gait assessment and recognition rating scale as the gold standard. The primary outcome is the sensitivity of the intelligent system and clinicians to screen for gait disorders. The secondary outcomes include the healthcare costs and the incremental cost effectiveness ratio of intelligent systems and clinicians to screen for gait disorders. ETHICS AND DISSEMINATION: Approval was granted by the Ethics Committee of Zhongshan Hospital affiliated with Fudan University on 26 November 2019. The approval number is B2019-027(2) R. All subjects will sign an informed consent form before enrolment. Serious adverse events will be reported to the main researchers and ethics committees. The subjects' data will be kept strictly confidential. The results will be disseminated in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04457908.

Idiopathic basal ganglia calcification associated with new MYORG mutation site: A case report.

BACKGROUND: Idiopathic basal ganglia calcification (IBGC) is a neurodegenerative disease characterized by symmetrical calcification of basal ganglia and other brain region, also known as Fahr's disease. It can be sporadic or familial, and there is no definite etiology at present. With the development of neuroimaging, the number of reports of IBGC has increased in recent years. However, due to its hidden onset, diverse clinical manifestations, and low incidence, it is likely to be misdiagnosed or ignored by potential patients and their family. CASE SUMMARY: We report a case of a 61-year-old man who presented with symptoms of dysphagia and alalia. His computed tomography scan of the brain revealed bilateral symmetric calcifications of basal ganglia, cerebellum, thalamus, and periventricular area. The genetic test showed a new mutation sites of MYORG, c.1438T>G mutation and c.1271_1272 TGGTGCGC insertion mutation. He was finally diagnosed with IBGC. CONCLUSION: It is important to detect MYORG mutation when IBGC is suspected, especially in those without an obvious family history, for better understanding of the underlying mechanism and identifying potential treatments.

Impact of severe tricuspid regurgitation on accuracy of systolic pulmonary arterial pressure measured by Doppler echocardiography: Analysis in an unselected patient population.

Pulmonary arterial pressure is an important index in cardiovascular disorders, especially for pulmonary hypertension (PH). Doppler echocardiography (DE) is widely used as a noninvasive method to assess pulmonary arterial pressure. However, recent studies have found several hemodynamic factors that affect its accuracy in estimating systolic pulmonary arterial pressure (sPAP). But the effect of tricuspid regurgitation (TR) has not been investigated. Therefore, our study is aimed to determine whether the severity of TR will affect the accuracy of sPAP measured by DE in an unselected patient population. We retrospectively studied 177 patients who underwent DE and right heart catheterization (RHC) examinations. Patients were categorized into 3 groups according to the severity of TR (mild, moderate, and severe). The discrepancy in sPAP measured by DE and RHC was calculated and compared in each group. Determinants of discordant results between two methods were also evaluated. Age, gender, interval between DE and RHC, sequence of DE and RHC were similar among groups (all P>.05). Differences in sPAP, RAP, and tricuspid regurgitation pressure gradient (TR-PG) were similar in group 1 and 2 (all P>.05), while all significantly higher in group 3 (all P<.05). The difference in sPAP between DE and RHC was affected independently by severe TR and severe PH (both P<.05). Severe TR and severe PH affect the accuracy of sPAP measured by DE. Modification of echocardiographic sPAP measurements by taking into consideration of these factors may lead to reduced systemic errors.