Morphometrics predicts the differential regurgitant fraction in bilateral pulmonary arteries of patients with repaired tetralogy of fallot.

In patients with repaired tetralogy of Fallot (rTOF), the regurgitant fraction (RF) in left pulmonary artery (LPA) and right pulmonary artery (RPA) is usually unequal. The morphometrics may play a crucial role in this RF discrepancy. Cardiovascular MR of 79 rTOF patients and 20 healthy controls were retrospectively enrolled. Forty-four from the 79 patients were matched in age, sex and body surface area to the 20 controls and were investigated for: (1) phase-contrast flow of main pulmonary artery (MPA), LPA, and RPA; (2) vascular angles: the angles between the thoracic anterior-posterior line (TAPL) with MPA (θM-AP), MPA with RPA (θM-R), and MPA with LPA (θM-L); (3) cardiac angle, the angle between TAPL and the interventricular septum; (4) area ratio of bilateral lung and hemithorax regions. Compared with the 20 controls, the 44 rTOF patients exhibited wider θM-AP, sharper θM-L angle, and a smaller θM-L/θM-R ratio. In the 79 rTOF patients, LPA showed lower forward, backward, and net flow, and greater RF as compared with RPA. Multivariate analysis showed that the RF of LPA was negatively associated with the θM-L/θM-R ratio and the age at surgery (R2 = 0.255). Conversely, the RF of RPA was negatively associated with the left lung/left hemithorax area ratio and cross-sectional area (CSA) of LPA, and positively associated with CSA of RPA and MPA (R2 = 0.366). In rTOF patients, the RF of LPA is more severe than that of RPA, which may be related to the vascular morphometrics. Different morphometric parameters are independently associated with the RF of LPA or RPA, which may offer potential insights for surgical strategies.

Impaired cerebral interstitial fluid dynamics in cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy.

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy, caused by cysteine-altering variants in NOTCH3, is the most prevalent inherited cerebral small vessel disease. Impaired cerebral interstitial fluid dynamics has been proposed as one of the potential culprits of neurodegeneration and may play a critical role in the initiation and progression of cerebral small vessel disease. In the present study, we aimed to explore the cerebral interstitial fluid dynamics in patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy and to evaluate its association with clinical features, imaging biomarkers and disease severity of cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy. Eighty-one participants carrying a cysteine-altering variant in NOTCH3, including 44 symptomatic cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy patients and 37 preclinical carriers, and 21 age- and sex-matched healthy control individuals were recruited. All participants underwent brain MRI studies and neuropsychological evaluations. Cerebral interstitial fluid dynamics was investigated by using the non-invasive diffusion tensor image analysis along the perivascular space method. We found that cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy patients exhibited significantly lower values of diffusion tensor image analysis along the perivascular space index comparing to preclinical carriers and healthy controls. For the 81 subjects carrying NOTCH3 variants, older age and presence of hypertension were independently associated with decreased diffusion tensor image analysis along the perivascular space index. The degree of cerebral interstitial fluid dynamics was strongly related to the severity of cerebral small vessel disease imaging markers, with a positive correlation between diffusion tensor image analysis along the perivascular space index and brain parenchymal fraction and negative correlations between diffusion tensor image analysis along the perivascular space index and total volume of white matter hyperintensity, peak width of skeletonized mean diffusivity, lacune numbers and cerebral microbleed counts. In addition, diffusion tensor image analysis along the perivascular space index was a significant risk factor associated with the development of clinical symptoms of stroke or cognitive dysfunction in individuals carrying NOTCH3 variants. In cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy patients, diffusion tensor image analysis along the perivascular space index was significantly associated with Mini-Mental State Examination scores. Mediation analysis showed that compromised cerebral interstitial fluid dynamics was not only directly associated with cognitive dysfunction but also had an indirect effect on cognition by influencing brain atrophy, white matter disruption, lacunar lesions and cerebral microbleeds. In conclusion, cerebral interstitial fluid dynamics is impaired in cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy and its disruption may play an important role in the pathogenesis of cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy. Diffusion tensor image analysis along the perivascular space index may serve as a biomarker of disease severity for cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy.

Application of project-based service-learning courses in medical education: trials of curriculum designs during the pandemic.

BACKGROUND: Due to COVID-19, face-to-face service activities in service-learning courses have become unfeasible. To address this challenge, this study aims to integrate project-based learning into medical education's service-learning curriculum. This study also seeks to evaluate the effectiveness of this instructional approach and identify factors that influence its success. METHODS: A total of 135 first-year medical students enrolled in a mandatory 1-credit service-learning course were recruited. The course involved various service activities aligned with the needs of the local community. The students were organized into 12 groups, each working on different service-learning projects, such as raising health awareness or educating the public about specific diseases. Following the completion of the course, a questionnaire was distributed among the students to gather feedback on the course, and 122 (valid responses were collected, representing a response rate of 90.3%). RESULTS: The results indicated that the project-based service-learning course significantly improved students' "interpersonal communication skills," their ability to "learn and grow from work," and their sense of "professionalism" (all p ≤ 0.037). Among the various aspects of service learning, the highest agreement was observed for "executing the project," followed by "group discussions and project formulation," "overall course review," "review of project outcomes," "outcome presentations," "teaching proposal writing and project brainstorming," "sharing of service-learning experiences by teachers," and "sharing of service-learning experiences by teaching assistants." Students also found certain factors to be beneficial in enhancing the learning effectiveness of service-learning courses, including "prize money for service-learning outcomes," "funding for service-learning activities," and "consultations from medical personnel" (all p ≤ 0.01). However, "course credit" and "photography software" did not show significant effects (both p > 0.05). The most preferred resources or activities for future service-learning courses were "course credit" and "face-to-face service-learning activities." CONCLUSIONS: The project-based learning method improved the learning effectiveness in service-learning courses. Students perceived that the number of course credits reflects the course value and plays a pivotal role in enhancing the learning effectiveness in service-learning courses. During the epidemic, students still expect to have face-to-face service activities in service-learning courses. Therefore, without the impact of the epidemic, service learning courses should return to face-to-face service activities.

Prediction of individual trigeminal pain sensitivity from gray matter structure within the sensorimotor network.

OBJECTIVE: To determine whether multivariate pattern regression analysis based on gray matter (GM) images constrained to the sensorimotor network could accurately predict trigeminal heat pain sensitivity in healthy individuals. BACKGROUND: Prediction of individual pain sensitivity is of clinical relevance as high pain sensitivity is associated with increased risks of postoperative pain, pain chronification, and a poor treatment response. However, as pain is a subjective experience accurate identification of such individuals can be difficult. GM structure of sensorimotor regions have been shown to vary with pain sensitivity. It is unclear whether GM structure within these regions can be used to predict pain sensitivity. METHODS: In this cross-sectional study, structural magnetic resonance images and pain thresholds in response to contact heat stimulation of the left supraorbital area were obtained from 79 healthy participants. Voxel-based morphometry was used to extract segmented and normalized GM images. These were then constrained to a mask encompassing the functionally defined resting-state sensorimotor network. The masked images and pain thresholds entered a multivariate relevance vector regression analysis for quantitative prediction of the individual pain thresholds. The correspondence between predicted and actual pain thresholds was indexed by the Pearson correlation coefficient (r) and the mean squared error (MSE). The generalizability of the model was assessed by 10-fold and 5-fold cross-validation. Non-parametric permutation tests were used to estimate significance levels. RESULTS: Trigeminal heat pain sensitivity could be predicted from GM structure within the sensorimotor network with significant accuracy (10-fold: r = 0.53, p < 0.001, MSE = 10.32, p = 0.001; 5-fold: r = 0.46, p = 0.001, MSE = 10.54, p < 0.001). The resulting multivariate weight maps revealed that accurate prediction relied on multiple widespread regions within the sensorimotor network. CONCLUSION: A multivariate pattern of GM structure within the sensorimotor network could be used to make accurate predictions about trigeminal heat pain sensitivity at the individual level in healthy participants. Widespread regions within the sensorimotor network contributed to the predictive model.

The Use of Neuroimaging for Predicting Sumatriptan Treatment Response in Patients With Migraine.

OBJECTIVES: To identify the neuroimaging predictors for the responsiveness of patients to sumatriptan and use an independent cohort for external validation. METHODS: Structuralized headache questionnaire and 3-Tesla brain magnetic resonance imaging were performed in migraine patients. Regional brain volumes were automatically calculated using FreeSurfer version 6.0, including bilateral amygdala, anterior cingulated cortex, caudate, putamen, precuneus, orbitofrontal cortex, superior frontal gyri, middle frontal gyri, hippocampus, and parahippocampus. A sumatriptan-responder was defined as headache relief within 2 h after the intake of sumatriptan in at least two out of three treated attacks. We constructed a prediction model for sumatriptan response using the regional brain volume and validated it with an independent cohort of migraine patients. RESULTS: A total of 105 migraine patients were recruited, including 73 sumatriptan responders (69.5%) and 32 (30.5%) non-responders. We divided the migraine patients into derivation (n = 73) and validation cohorts (n = 32). In the derivation cohort, left hippocampal volume was larger in sumatriptan responders (responders vs. non-responders: 3,929.5 ± 403.1 vs. 3,611.0 ± 389.9 mm3, p = 0.002), and patients with a larger left hippocampal volume had a higher response rate to sumatriptan (>4,036.2 vs. ≤4,036.2 mm3: 92.0 vs. 56.3%, p = 0.001). Based on the findings, we constructed a prediction model using the cutoff value of 4,036.2 mm3, and we found that patients with a left hippocampal volume >4,032.6 mm3 had a higher response rate to sumatriptan than those with a left hippocampal volume ≤4,032.6 mm3 (84.6 vs. 42.1%, odds ratio [OR] = 7.6 [95% confidence interval = 1.3-44.0], p = 0.013) in the validation cohort. CONCLUSION: Our study showed that left hippocampal volume is helpful to identify sumatriptan non-responders. This proof-of-concept study shows that left hippocampal volume could be used to predict the treatment response to sumatriptan in migraine patients.

Acceleration of Magnetic Resonance Fingerprinting Reconstruction Using Denoising and Self-Attention Pyramidal Convolutional Neural Network.

Magnetic resonance fingerprinting (MRF) based on echo-planar imaging (EPI) enables whole-brain imaging to rapidly obtain T1 and T2* relaxation time maps. Reconstructing parametric maps from the MRF scanned baselines by the inner-product method is computationally expensive. We aimed to accelerate the reconstruction of parametric maps for MRF-EPI by using a deep learning model. The proposed approach uses a two-stage model that first eliminates noise and then regresses the parametric maps. Parametric maps obtained by dictionary matching were used as a reference and compared with the prediction results of the two-stage model. MRF-EPI scans were collected from 32 subjects. The signal-to-noise ratio increased significantly after the noise removal by the denoising model. For prediction with scans in the testing dataset, the mean absolute percentage errors between the standard and the final two-stage model were 3.1%, 3.2%, and 1.9% for T1, and 2.6%, 2.3%, and 2.8% for T2* in gray matter, white matter, and lesion locations, respectively. Our proposed two-stage deep learning model can effectively remove noise and accurately reconstruct MRF-EPI parametric maps, increasing the speed of reconstruction and reducing the storage space required by dictionaries.

Brain volume changes in spontaneous intracranial hypotension: Revisiting the Monro-Kellie doctrine.

OBJECTIVES: In the application of the Monro-Kellie doctrine in spontaneous intracranial hypotension, the brain tissue volume is generally considered as a fixed constant. Traditionally, cerebral venous dilation is thought to compensate for decreased cerebrospinal fluid. However, whether brain tissue volume is invariable has not yet been explored. The objective of this study is to evaluate whether brain tissue volume is fixed or variable in spontaneous intracranial hypotension patients using automatic quantitative methods. METHODS: This retrospective and longitudinal study analyzed spontaneous intracranial hypotension patients between 1 January 2007 and 31 July 2015. Voxel-based morphometry was used to examine brain volume changes during and after the resolution of spontaneous intracranial hypotension. Brain structure volume was analyzed using Statistical Parametric Mapping version 12 and FMRIB Software Library v6.0. Post-treatment neuroimages were used as surrogate baseline measures. RESULTS: Forty-four patients with spontaneous intracranial hypotension were analyzed (mean [standard deviation] age, 37.8 [8.5] years; 32 female and 12 male). The whole brain tissue volume was decreased during spontaneous intracranial hypotension compared to follow-up (1180.3 [103.5] mL vs. 1190.4 [93.1] mL, difference: -10.1 mL [95% confidence interval: -18.4 to -1.8 mL], p = 0.019). In addition, ventricular cerebrospinal fluid volume was decreased during spontaneous intracranial hypotension compared to follow-up (15.8 [6.1] mL vs. 18.9 [6.9] mL, difference: -3.2 mL [95% confidence interval: -4.5 to -1.8 mL], p < 0.001). Longer anterior epidural cerebrospinal fluid collections, as measured by number of vertebral segments, were associated with greater reduction of ventricular cerebrospinal fluid volume (Pearson's r = -0.32, p = 0.036). CONCLUSION: The current study found the brain tissue volume and ventricular cerebrospinal fluid are decreased in spontaneous intracranial hypotension patients. The change in ventricular cerebrospinal fluid volume, but not brain tissue volume change, was associated with the severity of spinal cerebrospinal fluid leakage. These results challenge the assumption that brain tissue volume is a fixed constant.

Highly bright broadband red light produced by fluorescence polymer/InGaN hybrid light-emitting diodes.

The fabrication of fluorescence polymer/InGaN hybrid light-emitting diodes (LEDs) that emit highly bright broadband red light is presented in this Letter. The absorption peak of the fluorescence polymer was 455 nm, and the emission peak was 640 nm. The light output power and external quantum efficiency of hybrid LEDs at a driving current of 100 mA were 46.6 mW and 24.1%, respectively. The emission spectrum of hybrid LEDs was located at a wavelength of 641 nm, with a broadband FWHM of 106 nm. Thus this study offers potential methods for enhancing the output power of commercial white-light-emitting devices.

Electrical enhancement of direct methanol fuel cells by metal-plasma ion implantation Pt-Ru/C multilayer catalysts.

Direct methanol fuel cells (DMFC) have been widely studied owing to their simple cell configuration, high volume energy density, short start-up time, high operational reliability and other favorable characteristics. However, major limitations include high production cost, poisoning of the catalyst and methanol crossover. This study adopts a simple technique for preparing Pt-Ru/C multilayer catalysts, including magnetron sputtering (MS) and metal-plasma ion implantation (MPII). The Pt catalysts were sputtered onto the gas diffusion layer (GDL), followed by the implantation of Ru catalysts using MPII (at an accelerating voltage of 20 kV and an implantation dose of 1 x 10(16) ions/cm2). Pt-Ru is repeatedly processed to prepare Pt-Ru/C multilayer catalysts. The catalyst film structure and microstructure were analyzed by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and scanning electronic microscopy (SEM), respectively. The cell performance was tested using a potential stat/galvano-stat. The results reveal that the membrane electrode assembly (MEA) of four multilayer structures enhances the cell performance of DMFC. The measured power density is 2.2 mW/cm2 at a methanol concentration of 2 M, with an OCV of 0.493 V.