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Cerebral palsy (CP) is a neurological disorder that dissipates body posture and impairs motor functions. It may lead to an intellectual disability and affect the quality of life. Early intervention is critical and challenging due to the uncooperative body movements of children, potential infant recovery, a lack of a single vision modality, and no specific contrast or slice-range selection and association. Early and timely CP identification and vulnerable brain MRI scan associations facilitate medications, supportive care, physical therapy, rehabilitation, and surgical interventions to alleviate symptoms and improve motor functions. The literature studies are limited in selecting appropriate contrast and utilizing contrastive coupling in CP investigation. After numerous experiments, we introduce deep learning models, namely SSeq-DL and SMS-DL, correspondingly trained on single-sequence and multiple brain MRIs. The introduced models are tailored with specialized attention mechanisms to learn susceptible brain trends associated with CP along the MRI slices, specialized parallel computing, and fusions at distinct network layer positions to significantly identify CP. The study successfully experimented with the appropriateness of single and coupled MRI scans, highlighting sensitive slices along the depth, model robustness, fusion of contrastive details at distinct levels, and capturing vulnerabilities. The findings of the SSeq-DL and SMSeq-DL models report lesion-vulnerable regions and covered slices trending in age range to assist radiologists in early rehabilitation., Competing Interests: Declarations Conflict of interest As the corresponding author on behalf of all the authors, I declare that all the authors are aware of the submission and have no conflict of interest. The submitted paper contains original, unpublished results and is not currently under consideration elsewhere. Ethical permission The sample collection was carried out at Children’s Hospital with approval from the corresponding committee, with Reference No. 202004105. The recruited patients’ age range lies from 1 month to 17 years, with a mean age of 4.86 years. The guardian was notified with written consent to agree to conduct the study. All methods were performed per relevant guidelines and regulations., (© 2024. The Author(s).)

Objective: This study aims to explore differences in the static and dynamic amplitude of low-frequency fluctuations (sALFF and dALFF) in resting-state functional MRI (rs-fMRI) data between patients with Benign childhood epilepsy with centrotemporal spikes (SeLECTS) and healthy controls (HCs)., Materials and Methods: We recruited 45 patient with SeLECTS and 55 HCs, employing rs-fMRI to assess brain activity. The analysis utilized a two-sample t-test for primary comparisons, supplemented by stratification and matching based on clinical and demographic characteristics to ensure comparability between groups. Post hoc analyses assessed the relationships between sALFF/dALFF alterations and clinical demographics, incorporating statistical adjustments for potential confounders and performing sensitivity analysis to test the robustness of our findings., Results: Our analysis identified significant differences in sALFF and dALFF between patient with SeLECTS and HCs. Notably, increases in sALFF and dALFF were observed in the right middle temporal gyrus and left superior temporal gyrus among patient with SeLECTS, while a decrease in dALFF was seen in the right cerebellum crus 1. Additionally, a positive correlation was found between abnormal dALFF variability in specific brain regions and various clinical and demographic factors of patient with SeLECTS, with age being one such influential factor., Conclusion: This investigation provides insights into the assessment of local brain activity in SeLECTS through both static and dynamic approaches. It highlights the significance of non-invasive neuroimaging techniques in understanding the complexities of epilepsy syndromes like SeLECTS and emphasizes the need to consider a range of clinical and demographic factors in neuroimaging studies of neurological disorders., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Benign childhood epilepsy with centrotemporal spikes (BECTS), a common pediatric epilepsy, may lead to cognitive decline when compounded by Electrical Status Epilepticus during Sleep (ESES). Emerging evidence suggests that disruptions in the Salience Network (SN) contribute significantly to the cognitive deficits observed in BECTS-ESES. Our study rigorously investigates the dynamic functional connectivity (dFC) within the SN and its correlation with cognitive impairments in BECTS-ESES, employing advanced neuroimaging and neuropsychological assessments., Methods: In this research, 45 patients diagnosed with BECTS-ESES and 55 age-matched healthy controls (HCs) participated. We utilized resting-state functional magnetic resonance imaging (fMRI) and Independent Component Analysis (ICA) to identify three fundamental SN nodes: the right Anterior Insula (rAI), left Anterior Insula (lAI), and the Anterior Cingulate Cortex (ACC). A two-sample t-test facilitated the comparison of dFC between these pivotal regions and other brain areas., Results: Significantly, the BECTS-ESES group demonstrated increased dFC, particularly between the ACC and the right Middle Occipital Gyrus, and from the rAI to the right Superior Parietal Gyrus and Cerebellum, and from the lAI to the left Postcentral Gyrus. Such dFC augmentations provide neural insights potentially explaining the neuropsychological deficits in BECTS-ESES children. Employing comprehensive neuropsychological evaluations, we mapped these dFC disruptions to specific cognitive impairments encompassing memory, executive functioning, language, and attention. Through multiple regression analysis and path analysis, a preliminary but compelling association was discovered linking dFC disturbances directly to cognitive impairments. These findings underscore the critical role of SN disruptions in BECTS-ESES cognitive dysfunctions., Limitation: Our cross-sectional design and analytic methods preclude definitive mediation models and causal inferences, leaving the precise nature of dFC's mediating role and its direct impact by BECTS-ESES partially unresolved. Future longitudinal and confirmatory studies are needed to comprehensively delineate these associations., Conclusion: Our study heralds dFC within the SN as a vital biomarker for cognitive impairment in pediatric epilepsy, advocating for targeted cognitive-specific interventions in managing BECTS-ESES. The preliminary nature of our findings invites further studies to substantiate these associations, offering profound implications for the prognosis and therapeutic strategies in BECTS-ESES, thereby underlining the importance of this research in the field of pediatric neurology and epilepsy management., Competing Interests: Declaration of competing interest The authors declare that they have no computing financial interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) stand as pivotal diagnostic tools for brain disorders, offering the potential for mutually enriching disease diagnostic perspectives. However, the costs associated with PET scans and the inherent radioactivity have limited the widespread application of PET. Furthermore, it is noteworthy to highlight the promising potential of high-field and ultra-high-field neuroimaging in cognitive neuroscience research and clinical practice. With the enhancement of MRI resolution, a related question arises: can high-resolution MRI improve the quality of PET images?, Purpose: This study aims to enhance the quality of synthesized PET images by leveraging the superior resolution capabilities provided by high-field and ultra-high-field MRI., Methods: From a statistical perspective, the joint probability distribution is considered the most direct and fundamental approach for representing the correlation between PET and MRI. In this study, we proposed a novel model, the joint diffusion attention model, namely, the joint diffusion attention model (JDAM), which primarily focuses on learning information about the joint probability distribution. JDAM consists of two primary processes: the diffusion process and the sampling process. During the diffusion process, PET gradually transforms into a Gaussian noise distribution by adding Gaussian noise, while MRI remains fixed. The central objective of the diffusion process is to learn the gradient of the logarithm of the joint probability distribution between MRI and noise PET. The sampling process operates as a predictor-corrector. The predictor initiates a reverse diffusion process, and the corrector applies Langevin dynamics., Results: Experimental results from the publicly available Alzheimer's Disease Neuroimaging Initiative dataset highlight the effectiveness of the proposed model compared to state-of-the-art (SOTA) models such as Pix2pix and CycleGAN. Significantly, synthetic PET images guided by ultra-high-field MRI exhibit marked improvements in signal-to-noise characteristics when contrasted with those generated from high-field MRI data. These results have been endorsed by medical experts, who consider the PET images synthesized through JDAM to possess scientific merit. This endorsement is based on their symmetrical features and precise representation of regions displaying hypometabolism, a hallmark of Alzheimer's disease., Conclusions: This study establishes the feasibility of generating PET images from MRI. Synthesis of PET by JDAM significantly enhances image quality compared to SOTA models., (© 2024 American Association of Physicists in Medicine.)

Objective. In Magnetic Resonance (MR) parallel imaging with virtual channel-expanded Wave encoding, limitations are imposed on the ability to comprehensively and accurately characterize the background phase. These limitations are primarily attributed to the calibration process relying solely on center low-frequency Auto-Calibration Signals (ACS) data for calibration. Approach. To tackle the challenge of accurately estimating the background phase in wave encoding, a novel deep neural network model guided by deep phase priors is proposed with integrated virtual conjugate coil (VCC) extension. Concretely, within the proposed framework, the background phase is implicitly characterized by employing a carefully designed decoder convolutional neural network, leveraging the inherent characteristics of phase smoothness and compact support in the transformed domain. Furthermore, the proposed model with wave encoding benefits from additional priors, which incorporate transmission sparsity of the latent image and coil sensitivity smoothness. Main results. Ablation experiments were conducted to ascertain the proposed method's capability to implicitly represent CSM and the background phase. Subsequently, the superiority of the proposed method is demonstrated through confidence comparisons with competing methods, employing 4-fold and 5-fold acceleration experiments. In achieving 4-fold and 5-fold acceleration, the optimal quantitative metrics (PSNR/SSIM/NMSE) are 44.1359 dB/0.9863/0.0008 (4-fold) and 41.2074/0.9846/0.0017 (5-fold), respectively. Furthermore, the generalizability of the proposed method is further validated by conducting acceleration experiments with T1, T2, T2*, and various undersampling patterns. In addition, the DPP delivered much better performance than the conventional methods by exploring accelerated phase-sensitive SWI imaging. In SWI accelerated imaging, it also surpasses the optimal competing method in terms of (PSNR/SSIM/NMSE) with 0.096%/0.009%/0.0017%. Significance. The proposed method enables precise characterization of the background phase in the integrated VCC and wave encoding framework, supported via theoretical analysis and empirical findings. Our code is available at:https://github.com/sober235/DPP., (© 2024 Institute of Physics and Engineering in Medicine.)

Attention deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopment disorder. The deficit in working memory is a central cognitive impairment in ADHD. The SNAP-25 is a neurotransmitter vesicular docking protein whose MnlI polymorphism (rs3746544) is located in the 3'-untranslated region (3'-UTR) and known to be linked to ADHD, but the underlying mechanism of this polymorphism remains unclear. Using a functional connectivity density (FCD) mapping method based on resting-state functional magnetic resonance imaging in a sample of male children diagnosed with ADHD, we first investigated the correlation between SNAP-25 rs3746544 and FCD hubs. Compared with rs3746544 G-allele carriers, TT homozygous, which confers a high risk for ADHD, exhibited significantly decreased local and long-range FCD in anterior cingulate cortex, and decreased local FCD in the dorsal lateral prefrontal cortex. Moreover, both higher local and long-range FCD could predict better WM capacity. The current findings provide new insights into the underlying neural mechanisms linking SNAP-25 rs3746544 with the risk for ADHD via the endophenotype of brain functional connectivity., (Copyright © 2018 Elsevier B.V. All rights reserved.)

We aimed to perform a meta-analysis to systematically determine the most consistent regions of gray matter volume (GMV) abnormality in patients of unilateral mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS), and to reveal the difference of GMV abnormality between the patients with left-sided and right-sided MTLE-HS. A comprehensive and systematic search was performed in PubMed for voxel-based morphometry (VBM) studies of MTLE-HS. A total of 12 MTLE-HS studies, including 9 left-sided MTLE-HS (LMTLE-HS) and 8 right-sided MTLE-HS (RMTLE-HS) studies were included. The activation likelihood estimation (ALE) method was applied in our meta-analysis. Compared to the healthy controls, MTLE-HS patients showed significant GMV decrease in the parahippocampal gyrus, left pulvinar and right pyramis. For LMTLE-HS, the most consistent GMV decrease was detected in the left parahippocampal gyrus. For RMTLE-HS, the most consistent GMV decrease was found in the right parahippocampal gyrus. No shared regions of significant GMV reduction were found between LMTLE-HS and RMTLE-HS either. This meta-analysis revealed that MTLE-HS patients had significant GMV reduction even beyond the hippocampus, and the subtypes showed distinct reduction patterns. Our findings, if were further verified with larger samples, would have implications for the clinical diagnosis of MTLE-HS.

Objective: Cognitive impairments had been reported in childhood acute lymphoblastic leukemia, what caused the impairments needed to be demonstrated, chemotherapy-related or the disease itself. The primary aim of this exploratory investigation was to determine if there were changes in brain function of children with acute lymphoblastic leukemia before chemotherapy., Methods: In this study, we advanced a measure named regional homogeneity to evaluate the resting-state brain activities, intelligence quotient test was performed at same time. Using regional homogeneity, we first investigated the resting state brain function in patients with new onset childhood acute lymphoblastic leukemia before chemotherapy, healthy children as control., Results: The decreased ReHo values were mainly founded in the default mode network and left frontal lobe, bilateral inferior parietal lobule, bilateral temporal lobe, bilateral occipital lobe, precentral gyrus, bilateral cerebellum in the newly diagnosed acute lymphoblastic leukemia patients compared with the healthy control. While in contrast, increased ReHo values were mainly shown in the right frontal lobe (language area), superior frontal gyrus-R, middle frontal gyrus-R and inferior parietal lobule-R for acute lymphoblastic leukemia patients group. There were no significant differences for intelligence quotient measurements between the acute lymphoblastic leukemia patient group and the healthy control in performance intelligence quotient, verbal intelligence quotient, total intelligence quotient., Conclusion: The altered brain functions are associated with cognitive change and language, it is suggested that there may be cognition impairment before the chemotherapy. Regional homogeneity by functional magnetic resonance image is a sensitive way for early detection on brain damage in childhood acute lymphoblastic leukemia., (Copyright © 2017 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.)

Background: To report the diversity of MRI features of brainstem encephalitis (BE) induced by Enterovirus 71. This is supported by implementation and testing of our new classification scheme in order to improve the diagnostic level on this specific disease., Methods: Neuroimaging of 91 pediatric patients who got EV71 related BE were hospitalized between March, 2010 to October, 2012, were analyzed retrospectively. All patients underwent pre- and post-contrast MRI scan. Thereafter, 31 patients were randomly called back for follow-up MRI study during December 2013 to August 2014. The MRI signal patterns of BE primary lesion were analyzed and classified according to MR signal alteration at various disease stages. Findings in fatal and non-fatal cases were compared, and according to the MRI scan time point during the course of this disease, the patients' conditions were classified as 1) acute stage, 2) convalescence stage, 3) post mortem stage, and 4) long term follow-up study., Results: 103 patients were identified. 11 patients did not undergo MRI, as they died within 48 hours. One patient died on 14th day without MR imaging. 2 patients had postmortem MRI. Medical records and imaging were reviewed in the 91 patients, aged 4 months to 12 years, and two cadavers who have had MRI scan. At acute stage: the most frequent pattern (40 patients) was foci of prolonged T1 and T2 signal, with (15) or without (25) contrast enhancement. We observed a novel pattern in 4 patients having foci of low signal intensity on T2WI, with contrast enhancement. Another pattern in 10 patients having foci of contrast enhancement without abnormalities in T1WI or T2WI weighted images. Based on 2 cases, the entire medulla and pons had prolonged T1 and T2 signal, and 2 of our postmortem cases demonstrated the same pattern. At convalescence stage, the pattern observed in 4 patients was foci of prolonged T1 and T2 signal without contrast enhancement. Follow-up MR study of 31 cases showed normal in 26 cases, and demonstrated foci of prolonged T1 and T2 signal with hyper-intensity on FLAIR in 3 cases, or of prolonged T1 and T2 signal with hypo-intensity on FLAIR in 2 cases. Most importantly, MR findings of each case were thoroughly investigated and classified according to phases and MRI signal alteration., Conclusions: This study has provided enhanced and useful information for the MRI features of BE induced by EV71, apart from common practice established by previous reports. In addition, a classification scheme that summarizes all types of features based on the MRI signal at the four different stages of the disease would be helpful to improve the diagnostic level., Competing Interests: The authors have declared that no competing interests exist.

Background: The objective of this study is to assess standardized histograms of signal intensities of T1 signal and T2 signal on sagittal view without enhancement during (1) acute stage, and (2) convalescence stage of pediatric patients with Enterovirus 71 related brainstem encephalitis (BE), and with respect to (3) healthy normal., Methods: Our subjects were hospitalized between March 2010 and October 2012, and underwent pre- and post-contrast MRI studies. The research question to be answered is whether the comparison of the MRI image intensity histograms and relevant statistical quantification can add new knowledge to the diagnosis of BE patients. So, both 25 cases in acute stage with prolonged T1 and T2 signal, without enhancement, and 13 cases in convalescence stage were introduced. In additional, a healthy group with 25 cases was recruited for comparison., Results: MRI signal intensity histogram changes of the lesions were compared at the acute and convalescence stages of the disease. Our preliminary results suggest that standardized histograms of signal intensities and their statistical properties are able to provide diagnostic information for the clinical assessment of the disease. Different stages pertaining to the histogram plots comparison showed that overall T1 signal intensity values increase as we traverse from the acute stage to the convalescence stage. And then for the healthy subjects, the T2 signal intensity values changed their magnitudes in a reverse direction. However, exceptions of this can happen in four cases where the primary lesions occurred in the brainstem that developed encephalomalacia resulting in a lower signal in T1WI and higher signal in T2WI. Statistical analysis revealed there was significant difference of T1 signal intensity among the three groups; and also, the T2 signal intensity was lower than other two groups., Conclusions: Standardized histogram of T1 and T2 intensity provide valuable and useful information for disease diagnosis and evaluation, which can potentially help medical doctors to save the lives of children.

Objective: The purpose of this study was to investigate regional homogeneity (ReHo) in children with new-onset drug-naïve Benign Epilepsy with Centrotemporal Spikes (BECTS), chronic BECTS and healthy controls (HC) using the Regional Homogeneity (ReHo) method applied to resting state fMRI data., Methods: Resting state fMRI data was collected from three groups of children aged 6-13, including new onset drug naïve BECTS, chronic BECTS with medication, and HC; the data analyzed by ReHo method. Mandarin school exams scores were acquired and compared across groups., Results: There were three main findings. Firstly, compared with HC, abnormally increased ReHo was observed in bilateral sensorimotor regions in new onset BECTS which normalized or even reversed in the chronic BECTS group. Secondly, enhanced ReHo was found in the left frontal language region in the two BECTS groups, with even higher ReHo value in the chronic group. Lastly, decreased ReHo was found in regions of the default mode network (DMN), bilateral occipital lobes and cerebellum in both the new onset and chronic BECTS groups, lower in chronic BECTS. Behavioral analyses of school scores showed the chronic BECTS group presented significantly lower scores compared to HC (p<.05)., Significance: The coherence of low frequency fluctuations is disrupted in sensorimotor, language and DMN-related regions in new-onset BECTS. Some of these effects seem to be selectively normalized in chronic BECTS, thus allowing us to explore possible chronicity and AED-induced effects on BECTS. Abnormal ReHo in left language and DMN regions could be responsible for impairments of cognitive function., (Published by Elsevier B.V.)

Background: Influenza A (H1N1) can cause severe neurological complications., Objective: The purpose of this study was to analyze clinical and MRI features of neurological complications after H1N1 infection in critically ill children., Materials and Methods: We retrospectively analyzed clinical and neuroimaging findings in 17 children who were hospitalized in an intensive care unit with severe neurological complications after H1N1 infection in South China between September 2009 and December 2011. All children underwent pre- and post-contrast-enhanced brain MRI. Postmortem studies were performed in two children., Results: Six children died, five because of acute necrotizing encephalopathy (ANE) and one because of intracranial fungal infection. Eleven recovered; their manifestations of H1N1 were meningitis (3), encephalitis (1) and influenza encephalopathy (7). MRI features of ANE included multiple symmetrical brain lesions demonstrating prolonged T1 and T2 signal in the thalami, internal capsule, lenticular nucleus and pontine tegmentum. Postmortem MRI in two children with acute necrotizing encephalopathy showed diffuse prolonged T1 and T2 signal in the bilateral thalami, brainstem deformation and tonsillar herniation., Conclusion: Fatal neurological complications in children after H1N1 infection include ANE and opportunistic fungal infection. MRI is essential for identification of neurological complications and for clinical evaluation.

Introduction: This study was conducted to investigate MRI and associated clinical characteristics of brainstem encephalitis induced by enterovirus 71 (EV71) in children with hand-foot-mouth disease (HFMD)., Methods: We analyzed clinical and imaging data from 42 HFMD cases with EV71-induced brainstem encephalitis. All patients underwent plain and enhanced MRI cranial scans and were placed into one of two groups according to MRI enhancement results, an enhanced group or a nonenhanced group., Results: Thirty-two cases were positive on MRI exam. The primary location of the lesion for brainstem encephalitis was the dorsal pons and medulla oblongata (32 cases), followed by the cerebellar dentate nucleus (8 cases), midbrain (5 cases), and thalamus (2 cases). Plain T1-weighted images showed isointense or hypointense signals, and T2-weighted images showed isointense and hyperintense signals. Enhanced MRI scans showed that 12 cases had slight to moderate enhancement; 4 of these were normal on plain scan. The time from MRI examination to disease onset was statistically different between the enhanced (n = 12) and nonenhanced (n = 21) groups with a mean of 7.67 days (SD = 1.07) vs 11.95 days (SD = 5.33), respectively. The most common neurological symptoms for brainstem encephalitis were myoclonus and tremor. The greater the area of affected brain, the more severe the clinical symptoms were., Conclusion: The locations of EV71-induced HFMD-associated brainstem encephalitis lesions are relatively specific. Enhanced MRI scans could also identify the lesions missed by early plain scans. MRI scans can provide important information for clinical evaluation and treatment.

Objectives: To evaluate the diagnostic accuracy of whole-body MRI (WB-MRI) for assessment of hematological malignancies' therapeutic response. Methods: PubMed, Embase, and Web of Science were searched up to August 2021 to identify studies reporting the diagnostic performance of WB-MRI for the assessment of hematological malignancies' treatment response. A bivariate random-effects model was applied for the generation of the pooled diagnostic performance. Results: Fourteen studies with 457 patients with lymphoma, multiple myeloma, and sarcoma (very small proportion) were analyzed. Overall pooled sensitivity and specificity of WB-MRI were 0.88 (95% CI: 0.73–0.95) and 0.86 (95% CI: 0.73–0.93), respectively. Studies using whole-body diffusion-weighted imaging (WB-DWI) showed higher sensitivity than those that did not (0.94 vs. 0.55, p = 0.02). The pooled concordance rate of WB-MRI to assess hematological malignancies' treatment response with reference standard was 0.78 (95% CI: 0.59–0.96). WB-MRI and PET/CT showed similar diagnostic performance (sensitivity [0.83 vs. 0.92, p = 0.11] and specificity [0.87 vs. 0.76, p = 0.73]). Conclusion: WB-MRI has high diagnostic performance for hematological malignancies' treatment response assessment. The adding of WB-DWI is strongly associated with increased sensitivity. [ABSTRACT FROM AUTHOR]

Objective: We aimed to identify the consistent regions of gray matter volume (GMV) abnormalities in idiopathic generalized epilepsy (IGE), and to study the difference of GMV abnormalities among IGE subsyndromes by applying activation likelihood estimation (ALE) meta-analysis. Methods: A systematic review of VBM studies on GMV of patients with absence epilepsy (AE), juvenile myoclonic epilepsy (JME), IGE and controls indexed in PubMed and ScienceDirect from January 1999 to June 2016 was conducted. A total of 12 IGE studies, including 7 JME and 3 AE studies, were selected. Meta-analysis was performed on these studies by using the pooled and within-subtypes analysis (). Based on the above results, between-subtypes contrast analysis was carried out to detect the abnormal GMV regions common in and unique to each subtype as well. Results: IGE demonstrated significant GMV increase in right ventral lateral nucleus (VL) and right medial frontal gyrus, and significant GMV decrease in bilateral pulvinar. For JME, significant GMV increase was seen in right medial frontal gyrus, right anterior cingulate cortex (ACC), while significant GMV decrease was found in right pulvinar. In AE, the most significant GMV increase was found in right VL, and slight GMV reduction was seen in right medial dorsal nucleus, right subcallosal gyrus, left caudate and left precuneus. No overlapped and unique regions with significant GMV abnormalities were found between JME and AE. Significance: This meta-analysis demonstrated that thalamo-frontal network was a structure with significant GMV abnormality in IGE, and the IGE subsyndromes showed different GMV abnormal regions. These observations may provide instructions on the clinical diagnosis of IGE. [ABSTRACT FROM AUTHOR]

Background: The objective of this study is to assess standardized histograms of signal intensities of T1 signal and T2 signal on sagittal view without enhancement during (1) acute stage, and (2) convalescence stage of pediatric patients with Enterovirus 71 related brainstem encephalitis (BE), and with respect to (3) healthy normal.Methods: Our subjects were hospitalized between March 2010 and October 2012, and underwent pre- and post-contrast MRI studies. The research question to be answered is whether the comparison of the MRI image intensity histograms and relevant statistical quantification can add new knowledge to the diagnosis of BE patients. So, both 25 cases in acute stage with prolonged T1 and T2 signal, without enhancement, and 13 cases in convalescence stage were introduced. In additional, a healthy group with 25 cases was recruited for comparison.Results: MRI signal intensity histogram changes of the lesions were compared at the acute and convalescence stages of the disease. Our preliminary results suggest that standardized histograms of signal intensities and their statistical properties are able to provide diagnostic information for the clinical assessment of the disease. Different stages pertaining to the histogram plots comparison showed that overall T1 signal intensity values increase as we traverse from the acute stage to the convalescence stage. And then for the healthy subjects, the T2 signal intensity values changed their magnitudes in a reverse direction. However, exceptions of this can happen in four cases where the primary lesions occurred in the brainstem that developed encephalomalacia resulting in a lower signal in T1WI and higher signal in T2WI. Statistical analysis revealed there was significant difference of T1 signal intensity among the three groups; and also, the T2 signal intensity was lower than other two groups.Conclusions: Standardized histogram of T1 and T2 intensity provide valuable and useful information for disease diagnosis and evaluation, which can potentially help medical doctors to save the lives of children. [ABSTRACT FROM AUTHOR]

• Deep learning-based features can provide additional information beyond the scope of human visual perception. • We developed and validated a vision transformer-based model, named Riskformer, from preoperative MRI. • Riskformer score could provide independent and incremental prognostic value over existing clinical factors in OS prediction. Glioblastoma is the most common malignant brain tumor in adults. Despite aggressive treatment, its prognosis is still poor, with a median overall survival of less than 15 months. In this study, we developed and validated a vision transformer-based model, named Riskformer, built from preoperative MRI for predicting OS in patients with newly diagnosed IDH-wildtype glioblastoma patients. Riskformer score was associated with OS as an independent prognostic factor in patients with IDH-wildtype glioblastoma. In the training dataset (hazard ratio [HR]: 5.930, 95% confidence interval [CI]: 3.933–8.942, P < 0.001), validation dataset (HR: 2.436, 95% CI: 1.334–4.447, P < 0.001) and testing dataset (HR: 4.651, 95% CI: 2.233–9.688, P < 0.001). The Riskformer score could provide independent and incremental prognostic value over existing clinical factors in OS prediction in patients with IDH-wildtype glioblastoma. [ABSTRACT FROM AUTHOR]