Predicting hematoma expansion in acute spontaneous intracerebral hemorrhage: integrating clinical factors with a multitask deep learning model for non-contrast head CT.

PURPOSE: To predict hematoma growth in intracerebral hemorrhage patients by combining clinical findings with non-contrast CT imaging features analyzed through deep learning. METHODS: Three models were developed to predict hematoma expansion (HE) in 572 patients. We utilized multi-task learning for both hematoma segmentation and prediction of expansion: the Image-to-HE model processed hematoma slices, extracting features and computing a normalized DL score for HE prediction. The Clinical-to-HE model utilized multivariate logistic regression on clinical variables. The Integrated-to-HE model combined image-derived and clinical data. Significant clinical variables were selected using forward selection in logistic regression. The two models incorporating clinical variables were statistically validated. RESULTS: For hematoma detection, the diagnostic performance of the developed multi-task model was excellent (AUC, 0.99). For expansion prediction, three models were evaluated for predicting HE. The Image-to-HE model achieved an accuracy of 67.3%, sensitivity of 81.0%, specificity of 64.0%, and an AUC of 0.76. The Clinical-to-HE model registered an accuracy of 74.8%, sensitivity of 81.0%, specificity of 73.3%, and an AUC of 0.81. The Integrated-to-HE model, merging both image and clinical data, excelled with an accuracy of 81.3%, sensitivity of 76.2%, specificity of 82.6%, and an AUC of 0.83. The Integrated-to-HE model, aligning closest to the diagonal line and indicating the highest level of calibration, showcases superior performance in predicting HE outcomes among the three models. CONCLUSION: The integration of clinical findings with non-contrast CT imaging features analyzed through deep learning showed the potential for improving the prediction of HE in acute spontaneous intracerebral hemorrhage patients.

Glymphatic MRI techniques in sleep and neurodegenerative diseases.

PURPOSE OF REVIEW: The purpose of this review article is to summarize the current in-vivo imaging techniques for the evaluation of the glymphatic function and discuss the factors influencing the glymphatic function and research directions in the future. RECENT FINDINGS: The glymphatic system allows the clearance of metabolic waste from the central nervous system (CNS). The glymphatic pathway has been investigated using intrathecal or intravenous injection of a gadolinium-based contrast agent (GBCA) on MRI, so-called glymphatic MRI. The glymphatic MRI indirectly visualizes the dynamic CSF flow and evaluated the glymphatic function in the animal and human models. Several clinical and preclinical studies using glymphatic MRI have confirmed that the glymphatic function is impaired in neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, and idiopathic normal pressure hydrocephalus. Furthermore, physiologic process such as sleep facilitates the glymphatic clearance, thus clearing accumulation of protein deposition, such as amyloid or tau, potentially delaying the progression of neurodegenerative diseases. SUMMARY: The glymphatic system plays a crucial role in clearing metabolic wastes in the brain. Glymphatic MR imaging using GBCA administration serves as a functional imaging tool to measure the glymphatic function and investigate various pathophysiologies of neurodegenerative diseases.

Reconstruction of spectra from truncated free induction decays by deep learning in proton magnetic resonance spectroscopy.

PURPOSE: To explore the applicability of convolutional neural networks (CNNs) in the reconstruction of spectra from truncated FIDs (tFIDs) in 1 H-MRS, which can be valuable in situations in which data sampling is highly limited, such as spectroscopic magnetic resonance fingerprinting. METHODS: Rat brain FIDs were simulated at 9.4 T based on in vivo data (N = 11) and randomly truncated by retaining 8, 16, 32, 64, 128, 256, 512, and 1024 (null truncation) points (denoted as tFID8 , tFID16 , … tFID1024 ). Using a U-net, 3 CNNs were individually trained (N = 40 000) in time domain only (FID to FID [FID CNNFID ]), in frequency domain only (spectrum to spectrum [spec CNNspec ]), and across the domains (FID to spectrum [FID CNNspec ]) to map the truncated data to their fully sampled versions. The CNNs were tested on the simulated data (N = 5000), and the CNN with the best performance was further tested on the in vivo data, for which the CNN-predicted fully sampled data were analyzed using the LCModel and the results were compared with those from the original, fully sampled data. RESULTS: The best result on the simulated data was obtained with spec CNNspec , which effectively recovered the spectral details even for those input spectra that appear as a hump due to substantial FID truncation (spectra from tFID16 and tFID32 ). Overall, its performance was significantly degraded on the in vivo data. Nonetheless, using spec CNNspec , several coupled spins in addition to the major singlets can be quantified from tFID128 with the error no larger than 10%. CONCLUSION: Upon the availability of more realistically simulated training data, CNNs can also be used in the reconstruction of spectra from truncated FIDs.

Perceived Trajectories of Past, Present, and Future Life Satisfaction of North Korean Defectors.

This study compared perceived trajectories of life satisfaction (LS) between North Korean defectors' (NKDs') and the general South Korean population and examined psychosocial factors associated with future LS. Data were obtained from 300 NKDs residing in South Korea and 5089 South Koreans using self-questionnaires and face-to-face interviews. LS values from 5 years ago (3.46 vs. 6.18) and at present (5.30 vs. 5.91) were lower in NKDs than the control group, but the inverse was true for expected LS score in 5 years (7.82 vs. 6.87). NKDs' LS trajectory showed a more statistically positive trend than that of the control group. Among NKDs, subjective sense of loneliness and satisfaction with one's sense of autonomy were associated with expected future LS. NKDs experience higher life satisfaction and expect an optimistic future relative to the control group. Social policies and therapeutic approaches to loneliness and improving a sense of autonomy may be beneficial.

Association of Body Mass Index with Suicide Behaviors, Perceived Stress, and Life Dissatisfaction in the Korean General Population.

OBJECTIVE: The purpose of the present study was to investigate the association between Body Mass Index, suicide, perceived stress, and life dissatisfaction in a general population sample of Korean adults. METHODS: A total of 6,022 nationally representative adults aged 18 to 74 were selected using a multistage cross-sectional cluster sampling method. Questionnaires regarding suicide behaviors, perceived stress, and life satisfaction were completed by the participants. They also reported their heights and weights, which were used to calculate BMI. Psychiatric disorders were diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, using the Korean version of the Composite International Diagnostic Interview. RESULTS: The results showed that being underweight was associated with higher risk for suicide ideation [odds ratio (OR), 1.6; 95% confidence interval (Cl), 1.18-2.05] and suicide attempt (OR, 2.0, 95% Cl, 1.23-3.31). Likewise, obesity also increased the risk of suicide ideation (OR, 1.3; 95% Cl, 1.11-1.56) although not suicide attempt. Furthermore, underweight individuals were more likely to report severe level of perceived stress (OR, 1.7; 95% Cl, 1.26-2.17) and life dissatisfaction (OR, 1.3; 95% Cl, 1.07-1.68). All of the results remained significant after adjusting for age, gender, education, and psychiatric illnesses. CONCLUSION: This study found that being underweight is a significant risk factor for suicide and poor subjective wellbeing in Korea. It suggests that BMI status may be an important modifiable factor for improving mental health in Korea.

Treadmill exercise after social isolation increases the levels of NGF, BDNF, and synapsin I to induce survival of neurons in the hippocampus, and improves depression-like behavior.

PURPOSE: We investigated the effects of 8 weeks of treadmill exercise on nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), and synapsin I protein expression and on the number of 5-bromo-2'-deoxyuridine-5'-mono-phosphate (BrdU)-positive cells in the dentate gyrus of the hippocampus in socially isolated rats. Additionally, we examined the effects of exercise on the number of serotonin (5-HT)- and tryptophan hydroxylase (TPH)-positive cells in the raphe nuclei and on depression behaviors induced by social isolation. METHODS: Forty male Sprague-Dawley rats were divided into four groups: (1) group housing and control group (GCG, n = 10); (2) group housing and exercise group (GEG, n = 10); (3) isolated housing and control group (ICG, n = 10); and (4) isolated housing and exercise group (IEG, n = 10). After 1 week of housing under the normal condition of 3 animals per cage, rats were socially isolated via transfer to individual cages for 8 weeks. Rats were then subjected to treadmill exercise for 5 days per week for 8 weeks during which time the speed of the treadmill was gradually increased. RESULTS: Compared to the GCG, levels of NGF, BDNF, and synapsin I were significantly decreased in the ICG and significantly increased in the IEG (p < 0.001 respectively). Significantly more BrdU-positive cells in the GEG were present as compared to the GCG and ICG, and more BrdU-positive cells were found in the IEG as compared to the ICG (p < 0.001). 5-HT-positive cells in the GEG were significantly increased compared to the GCG and ICG, and more of these cells were found in the IEG as compared to the ICG (p < 0.01). TPH-positive cells in the GEG were significantly increased compared to those in the GCG and ICG (p < 0.05). In the forced swim test, immobility time was significantly increased in the ICG and significantly decreased in the IEG as compared to the ICG (p < 0.01). CONCLUSION: These results showed that regular treadmill exercise following social isolation not only increased the levels of NGF, BDNF, and synapsin I to induce survival of neurons in the hippocampus but also improved depression by increasing the number of serotonergic cells in the raphe nuclei.