(1) Background: The Alberta Stroke Program Early CT Score (ASPECTS) is a standardized scoring tool used to evaluate the severity of acute ischemic stroke (AIS) on non-contrast CT (NCCT). Our aim in this study was to automate ASPECTS. (2) Methods: We utilized a total of 258 patient images with suspected AIS symptoms. Expert ASPECTS readings on NCCT were used as ground truths. A deep learning-based automatic detection (DLAD) algorithm was developed for automated ASPECTS scoring based on 168 training patient images using a convolutional neural network (CNN) architecture. An additional 90 testing patient images were used to evaluate the performance of the DLAD algorithm, which was then compared with ASPECTS readings on NCCT as performed by physicians. (3) Results: The sensitivity, specificity, and accuracy of DLAD for the prediction of ASPECTS were 65%, 82%, and 80%, respectively. These results demonstrate that the DLAD algorithm was not inferior to radiologist-read ASPECTS on NCCT. With the assistance of DLAD, the individual sensitivity of the ER physician, neurologist, and radiologist improved. (4) Conclusion: The proposed DLAD algorithm exhibits a reasonable ability for ASPECTS scoring on NCCT images in patients presenting with AIS symptoms. The DLAD algorithm could be a valuable tool to improve and accelerate the decision-making process of front-line physicians.

The shuffling gait with slowed speed and reduced stride length has been considered classic clinical features in idiopathic Parkinson’s disease (PD), and the risk of falling increases as the disease progresses. This raises the possibility that clinical disease severity might mediate the relationship between stride length and speed and the risk of falling in patients with PD. Sixty-one patients with PD patients underwent the clinical scores as well as quantitative biomechanical measures during walking cycles before and after dopamine replacement therapy. Mediation analysis tests whether the direct effect of an independent variable (stride length and speed) on a dependent variable (three-step fall prediction model score) can be explained by the indirect influence of the mediating variable (Unified Parkinson’s Disease Rating Scale (UPDRS) total scores). The results demonstrate that decreased stride length, straight walking speed, and turning speed is associated with increased three-step fall prediction model score (r = −0.583, p < 0.0001, r = −0.519, p < 0.0001, and r = −0.462, p < 0.0001, respectively). We further discovered that UPDRS total scores value is negatively correlated with stride length, straight walking, and turning speed (r = −0.651, p < 0.0001, r = −0.555, p < 0.0001, and r = −0.372, p = 0.005, respectively) but positively correlated with the fall prediction model score value (r = 0.527, p < 0.0001). Further mediation analysis shows that the UPDRS total score values serve as mediators between lower stride length, straight walking, and turning speed and higher fall prediction model score values. Our results highlighted the relationship among stride length and speed, clinical disease severity, and risk of falling. As decreased stride length and speed are hallmarks of falls, monitoring the changes of quantitative biomechanical measures along with the use of wearable technology in a longitudinal study can provide a scientific basis for pharmacology, rehabilitation programs, and selecting high-risk candidates for surgical treatment to reduce future fall risk.

To identify the vulnerable areas associated with systemic oxidative stress and further disruption of these vulnerable areas by measuring the associated morphology and functional network alterations in Parkinson’s disease (PD) patients with and without cognitive impairment. This prospective study was approved by the institutional review board of KCGMH, and written informed consent was obtained. Between December 2010 and May 2015, 41 PD patients with different levels of cognitive functions and 29 healthy volunteers underwent peripheral blood sampling to quantify systemic oxidative stress, as well as T1W volumetric and resting state functional MRI (rs-fMRI) scans. Rs-fMRI was used to derive the healthy intrinsic connectivity patterns seeded by the vulnerable areas associated with any of the significant oxidative stress markers. The two groups were compared in terms of the functional connectivity correlation coefficient (fc-CC) and gray matter volume (GMV) of the network seeded by the vulnerable areas. The levels of oxidative stress markers, including leukocyte apoptosis and adhesion molecules, were significantly higher in the PD group. Using whole-brain VBM-based correlation analysis, the bilateral mesial temporal lobes (MTLs) were identified as the most vulnerable areas associated with lymphocyte apoptosis (P < 0.005). We found that the MTL network of healthy subjects resembled the PD-associated atrophy pattern. Furthermore, reduced fc-CC and GMV were further associated with the aggravated cognitive impairment. The MTLs are the vulnerable areas associated with peripheral lymphocyte infiltration, and disruptions of the MTL functional network in both architecture and functional connectivity might result in cognitive impairments in Parkinson’s disease.

The respiratory dysfunction of patients with Parkinson’s disease (PD) has drawn increasing attention. This study evaluated the relationship between gray matter volume (GMV), as determined by voxel-based morphometry (VBM), and respiratory dysfunction in patients with PD and correlated it with systemic inflammatory markers. Whole-brain VBM analysis was performed on 3-dimensional T1-weighted images in 25 PD patients with abnormal pulmonary function (13 men, 12 women; mean age: 62.9 ± 10.8 years) and, for comparison, on 25 sex- and age-matched PD patients with normal pulmonary function (14 men, 11 women; mean age: 62.3 ± 6.9 years). Inflammatory markers were determined by flow cytometry. The differences and correlations in regional GMV, clinical severity and inflammatory markers were determined after adjusting for age, gender and total intracranial volume (TIV). Compared with the normal pulmonary function group, the abnormal pulmonary function group had smaller GMV in several brain regions, including the left parahippocampal formation, right fusiform gyrus, right cerebellum crus, and left postcentral gyri. Forced expiratory volume in 1 s (FEV1) and maximal expiratory flow after expiration of 50% of forced vital capacity (MEF50) were positively correlated with regional GMV. There were no significant differences in the level of serum inflammatory markers between two groups. Our findings suggested that involvement of the central autonomic network and GM loss may underlie the respiratory dysfunction in PD patients.

Background: To investigate the relationship between fat content and the cross-sectional area of psoas and thigh muscles, and clinical severity in patients with Parkinson’s disease. Materials and Methods: Twenty-five patients and 20 age- and sex-matched normal controls were recruited. All subjects underwent MRI study to determine the fat content of the bilateral psoas and thigh muscles. Muscle quality was measured by grasp, walking speed, and cross-sectional area. All patients underwent clinical surveys to evaluate disease severity and frailty, and analyses of the correlations between muscle quality and disease severity were performed. Results: Compared with the controls, patients exhibited higher fatty content in the measured muscles. The higher fat infiltration of measured muscles was significantly correlated with increased disease severity and frailty in patients. The fat fraction of the bilateral medial compartment of the thigh was correlated with the Unified Parkinson Disease Rating Scale-I results and the fat fraction of the bilateral anterior compartment of the thigh was correlated with weakness and exhaustion in patients. Conclusions: Decreased quality in psoas and thigh muscles is prominent in Parkinson’s disease which is further associated with disease severity and frailty. Awareness of the risk of sarcopenia and associated sequelae might improve patient care and outcomes.

Purpose: Risk of falls is a common sequela affecting patients with Parkinson’s disease (PD). Although motor impairment and dementia are correlated with falls, associations of brain structure and cognition deficits with falls remain unclear. Material and Methods: Thirty-five PD patients with dementia (PDD), and 37 age- and sex-matched healthy subjects were recruited for this study. All participants received structural magnetic resonance imaging (MRI) scans, and disease severity and cognitive evaluations. Additionally, patient fall history was recorded. Regional structural differences between PDD with and without fall groups were performed using voxel-based morphometry processing. Stepwise logistic regression analysis was used to predict the fall risk in PDD patients. Results: The results revealed that 48% of PDD patients experienced falls. Significantly lower gray matter volume (GMV) in the left calcarine and right inferior frontal gyrus in PDD patients with fall compared to PDD patients without fall were noted. The PDD patients with fall exhibited worse UPDRS-II scores compared to PDD patients without fall and were negatively correlated with lower GMV in the left calcarine (p/r = 0.004/−0.492). Furthermore, lower GMV in the left calcarine and right inferior frontal gyrus correlated with poor attention and executive functional test scores. Multiple logistic regression analysis showed that the left calcarine was the only variable (p = 0.004, 95% CI = 0.00–0.00) negatively associated with the fall event. Conclusions: PDD patients exhibiting impaired motor function, lower GMV in the left calcarine and right inferior frontal gyrus, and notable cognitive deficits may have increased risk of falls.