DPP: deep phase prior for parallel imaging with wave encoding.

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.

Predicting Antiseizure Medication Treatment in Children with Rare Tuberous Sclerosis Complex-Related Epilepsy Using Deep Learning.

BACKGROUND AND PURPOSE: Tuberous sclerosis complex disease is a rare, multisystem genetic disease, but appropriate drug treatment allows many pediatric patients to have positive outcomes. The purpose of this study was to predict the effectiveness of antiseizure medication treatment in children with tuberous sclerosis complex-related epilepsy. MATERIALS AND METHODS: We conducted a retrospective study involving 300 children with tuberous sclerosis complex-related epilepsy. The study included the analysis of clinical data and T2WI and FLAIR images. The clinical data consisted of sex, age of onset, age at imaging, infantile spasms, and antiseizure medication numbers. To forecast antiseizure medication treatment, we developed a multitechnique deep learning method called WAE-Net. This method used multicontrast MR imaging and clinical data. The T2WI and FLAIR images were combined as FLAIR3 to enhance the contrast between tuberous sclerosis complex lesions and normal brain tissues. We trained a clinical data-based model using a fully connected network with the above-mentioned variables. After that, a weighted-average ensemble network built from the ResNet3D architecture was created as the final model. RESULTS: The experiments had shown that age of onset, age at imaging, infantile spasms, and antiseizure medication numbers were significantly different between the 2 drug-treatment outcomes (P < .05). The hybrid technique of FLAIR3 could accurately localize tuberous sclerosis complex lesions, and the proposed method achieved the best performance (area under the curve = 0.908 and accuracy of 0.847) in the testing cohort among the compared methods. CONCLUSIONS: The proposed method could predict antiseizure medication treatment of children with rare tuberous sclerosis complex-related epilepsy and could be a strong baseline for future studies.

Activation Map Reveals Language Impairment in Children with Benign Epilepsy with Centrotemporal Spikes (BECTS).

Objective: Neuropsychological evidence revealed language impairment in children with benign epilepsy with centrotemporal spikes (BECTS). This study investigates language function using task-activated fMRI. Methods: We conducted a language task fMRI study on three groups on a 3.0T MRI scanner, including a new onset drug naïve group (NODN-BECTS, n=11, age=9.6±1.6), an established epilepsy with medication-treated group (Med-BECTS, n=17, age=10.7±2.2) and a healthy control group (HC, n=18, age=10.8±1.7). We use MATLAB14 and SPM12 to pre-process and analyze the data. A one-sample t-test was used to identify task-related brain activation changes in each group, based on the general linear model (GLM). And, then two sample t-test was performed to compare different activated regions between groups. In addition, scores on the most recent Mandarin school exams were acquired to examine and contrast extra-scanner language performance. Results: Statistical results show that some language-related brain regions (such as the left superior frontal gyrus and cerebellar vermis) were additionally activated in the NODN-BECTS group compared with the HC group. Compared with NODN-BECTS and HC groups, decreased activations were found in language-related regions in the Med-BECTS group, including the left insula, superior and middle frontal gyri, and bilateral middle occipital gyri. On the Mandarin school exams, the average score for HC was 87.3±8.2, NODN was 84.8±7.8, and Med was 78.2±13.2. There was a trend toward statistical significance between the Med and the HC (p = 0.074) as well as NODN (p = 0.092) groups. No statistically significant differences were found between the HC and the NODN-BECTS groups. Significance: Language task fMRI reveals additional areas of activation in new onset BECTS compared to healthy controls which may be compensatory in nature. Antiseizure medications (ASMs) and/or longer duration of BECTS additionally appears to affect language-related regions and reduce their functional ability.

Recognizing Pediatric Tuberous Sclerosis Complex Based on Multi-Contrast MRI and Deep Weighted Fusion Network.

Multi-contrast magnetic resonance imaging (MRI) is wildly applied to identify tuberous sclerosis complex (TSC) children in a clinic. In this work, a deep convolutional neural network with multi-contrast MRI is proposed to diagnose pediatric TSC. Firstly, by combining T2W and FLAIR images, a new synthesis modality named FLAIR3 was created to enhance the contrast between TSC lesions and normal brain tissues. After that, a deep weighted fusion network (DWF-net) using a late fusion strategy is proposed to diagnose TSC children. In experiments, a total of 680 children were enrolled, including 331 healthy children and 349 TSC children. The experimental results indicate that FLAIR3 successfully enhances the visibility of TSC lesions and improves the classification performance. Additionally, the proposed DWF-net delivers a superior classification performance compared to previous methods, achieving an AUC of 0.998 and an accuracy of 0.985. The proposed method has the potential to be a reliable computer-aided diagnostic tool for assisting radiologists in diagnosing TSC children.

Machine learning and statistic analysis to predict drug treatment outcome in pediatric epilepsy patients with tuberous sclerosis complex.

OBJECTIVES: We aimed to investigate the association between multi-modality features and epilepsy drug treatment outcomes and propose a machine learning model to predict epilepsy drug treatment outcomes with multi-modality features. METHODS: This retrospective study consecutively enrolled 103 epilepsy children with rare TSC. Multi-modality data were used to characterize risk factors for epilepsy drug treatment outcome of TSC, including clinical data, TSC1, and TSC2 genes test results, magnetic resonance imaging (MRI), computerized tomography (CT), and electroencephalogram (EEG). Three common feature selection methods and six common machine learning models were used to find the best combination of feature selection and machine learning model for epilepsy drug treatment outcomes prediction with multi-modality features for TSC clinical application. RESULTS: The analysis of variance based on selected 35 features combined with multilayer perceptron (MLP) model achieved the best area-under-curve score (AUC) of 0.812 (±0.005). Infantile spasms, EEG discharge type, epileptiform discharge in the right frontal area of EEG, drug-resistant epilepsy, gene mutation type, and type II lesions were positively correlated with drug treatment outcome. Age of onset and age of visiting doctors were negatively correlated with drug treatment outcome (p < 0.05). Our machine learning results found that among MRI features, lesion type is the most important in the outcome prediction, followed by location and quantity. CONCLUSION: We developed and validated an effective prediction model for epilepsy drug treatment outcomes of TSC. Our results suggested that multi-modality features analysis and MLP-based machine learning can predict epilepsy drug treatment outcomes of TSC.

Myelin oligodendrocyte glycoprotein antibody-associated aseptic meningitis without neurological parenchymal lesions: A novel phenotype.

BACKGROUND: Myelin oligodendrocyte glycoprotein (MOG) antibodies mediate inflammatory demyelinating diseases of the central nervous system. This study aimed to understand the clinical characteristics of MOG antibody-associated aseptic meningitis (MOGAM). METHODS: Here, we report the cases of two children with MOGAM. A systematic literature review was conducted and included patients who had MOGAM only, without neurological parenchymal lesions. The clinical characteristics that may have affected the outcome were statistically analyzed. RESULTS: We reviewed 12 cases of MOGAM; male: female = 9: 3. Prolonged fever lasting over 7 days (11/12) was the most frequent symptom, followed by headache (10/12), vomiting (5/12), and seizures (4/12). None of the patients had focal neurological manifestations or parenchymal lesions on imaging. Cerebrospinal fluid (CSF) leukocytosis was observed in all patients (12/12), and blood leukocytosis and elevated CSF pressure was observed in all patients who had corresponding results (9/9 and 4/4, respectively). Seizures occurrence was lower than that of MOG antibody-associated cortical encephalitis. Seven cases progressed to other MOG antibody-associated diseases (MOGADs) in the later phase of MOGAM. Patients who did not progress to other MOGADs had a shorter disease duration from onset to the initiation of intravenous methylprednisolone than those who did. All the patients achieved full recovery after steroid treatment. One patient had relapses. CONCLUSIONS: MOGAM without inflammatory demyelination is a rare but distinct phenotype of MOGAD, with fewer clinical manifestations mimicking bacterial or viral meningitis/encephalomeningitis. Delayed diagnosis and treatment may induce the progression to other severe MOGADs. Early recognition of this unique autoimmune aseptic meningitis may contribute to early diagnosis, treatment, and better outcomes.

Identification of Children's Tuberous Sclerosis Complex with Multiple-contrast MRI and 3D Convolutional Network.

Identifying rare tuberous sclerosis complex (TSC) children is valuable and crucial. Magnetic resonance imaging (MRI) is used for rare TSC diagnoses. In this work, T2w and FLAIR were combined as a new modality named FLAIR3 to maximize the contrast between TSC lesions and normal-appearing brain tissues. After that, for the first time, we propose to use two different 3D CNN combined with late fusion strategies to diagnose TSC. A total of 520 children were enrolled in the study, including 260 health and 260 TSC children. The experiments had shown that the FLAIR3 could effectively improve the conspicuity of TSC lesions and classification performance. And the results showed the proposed late fusion method can improve the classification performance and achieve the state-of-the-art performance of the AUC of 0.994 and the accuracy of 0.971, which could be treated as an effective computer-aided diagnostic tool to help clinical radiologists diagnose TSC children. Clinical Relevance- Our deep learning method can be a non-invasive, efficient, and reliable way to help clinical radiologists to identify TSC patients. FLAIR3 can provide clinicians with a new modality to accurately localize TSC lesions in TSC patients.

Mosaicism in tuberous sclerosis complex: Lowering the threshold for clinical reporting.

Tuberous sclerosis complex (TSC) is a multi-system genetic disorder. Most patients have germline mutations in TSC1 or TSC2 but, 10%-15% patients do not have TSC1/TSC2 mutations detected on routine clinical genetic testing. We investigated the contribution of low-level mosaic TSC1/TSC2 mutations in unsolved sporadic patients and families with TSC. Thirty-one sporadic TSC patients negative on routine testing and eight families with suspected parental mosaicism were sequenced using deep panel sequencing followed by droplet digital polymerase chain reaction. Pathogenic variants were found in 22/31 (71%) unsolved sporadic patients, 16 were mosaic (median variant allele fraction [VAF] 6.8% in blood) and 6 had missed germline mutations. Parental mosaicism was detected in 5/8 families (median VAF 1% in blood). Clinical testing laboratories typically only report pathogenic variants with allele fractions above 10%. Our findings highlight the critical need to change laboratory practice by implementing higher sensitivity assays to improve diagnostic yield, inform patient management and guide reproductive counseling.

Liver transplantation for late-onset ornithine transcarbamylase deficiency: A case report.

BACKGROUND: Ornithine transcarbamylase deficiency (OTCD) is an X-linked inherited disorder and characterized by marked elevation of blood ammonia. The goal of treatment is to minimize the neurological damage caused by hyperammonemia. OTCD can be cured by liver transplantation (LT). Post-transplant patients can discontinue anti- hyperammonemia agents and consume a regular diet without the risk of developing hyperammonemia. The neurological damage caused by hyperammonemia is almost irreversible. CASE SUMMARY: An 11.7-year-old boy presented with headache, vomiting, and altered consciousness. The patient was diagnosed with late-onset OTCD. After nitrogen scavenging treatment and a protein-free diet, ammonia levels were reduced to normal on the third day of admission. Nevertheless, the patient remained in a moderate coma. After discussion, LT was performed. Following LT, the patient's blood ammonia and biochemical indicators stabilized in the normal range, he regained consciousness, and his nervous system function significantly recovered. Two months after LT, blood amino acids and urine organic acids were normal, and brain magnetic resonance imaging showed a decrease in subcortical lesions. CONCLUSION: LT can significantly improve partial neurological impairment caused by late-onset OTCD hyperammonemic encephalopathy, and LT can be actively considered when early drug therapy is ineffective.

Identification of a Novel Canonical Splice Site Variant TSC2 c.2967-1G>T That is Not Associated With Tuberous Sclerosis Pathogenesis.

Tuberous sclerosis, also known as tuberous sclerosis complex (TSC), is an autosomal dominant defect characterized by hamartomas in multiple organ systems. Inactivating variants cause this defect in either the TSC1 gene or the TSC2 gene, leading to hamartin or tuberin protein dysfunction, thus resulting in TSC. The diagnostic criteria for TSC suggest that it can be diagnosed by identifying a heterozygous pathogenic variant of TSC1 or TSC2, even in the absence of clinical signs. In a 4-year-old girl, we identified a splicing variant (NM_000548.4: c.2967-1G>T) that she inherited from her father. Neither the girl (patient) nor her father showed typical features of TSC. This variant is located in a NAGNAG acceptor, which can produce mRNA isoforms that differ by a three-nucleotide indel. Reverse transcription polymerase chain reaction analysis of the patient and both parents' blood RNA samples suggested two different splicing patterns, and these two splicing patterns differed in the presence or absence of the first codon of exon 27, thus providing two splicing products designated as isoforms A and B, respectively. Furthermore, the proportions of these two patterns varied between the patient and either parent. A minigene assay further confirmed that the c.2967-1G>T variant led to the absence of isoform A (including the first codon of exon 27). The finding of our study demonstrates this variant, c.2967-1G>T, disrupts the balance of an alternative splice event which involves the use of two tandem alternatives acceptors and is not associated with typical symptoms of tuberous sclerosis. Our finding is of importance for genetic counseling and suggests that we need to be vigilant to avoid misdiagnosis when we encounter such a site.

Non-convulsive Status Epilepticus in SEMA6B-Related Progressive Myoclonic Epilepsy: A Case Report With Literature Review.

Progressive myoclonic epilepsy (PME) is a group of rare diseases characterized by progressive myoclonus, cognitive impairment, ataxia, and other neurologic deficits. PME has high genetic heterogeneity, and more than 40 genes are reportedly associated with this disorder. SEMA6B encodes a member of the semaphorin family and was first reported to cause PME in 2020. Herein, we present a rare case of PME due to a novel SEMA6B gene mutation in a 6-year-old boy born to healthy non-consanguineous Chinese parents. His developmental milestones were delayed, and he developed recurrent atonic seizures and myoclonic seizures without fever at 3 years and 11 months of age. He experienced recurrent myoclonic seizures, non-convulsive status epilepticus (NCSE), atonic seizures, and atypical absence seizures during the last 2 years. At different time points since onset, valproic acid, levetiracetam, piracetam, and clobazam were used to control the intractable seizures. Notably, NCSE was controlled by a combination of piracetam with clobazam and valproic acid instead of intravenous infusion of midazolam and phenobarbital. Due to the limited number of cases reported to date, the clinical description of our case provides a better understanding of the genotype-phenotype correlations associated with PME and indicate that piracetam may be effective against NCSE in patients with SEMA6B-related PME.

A de novo PUM1 Variant in a Girl With a Dravet-Like Syndrome: Case Report and Literature Review.

In the recent 3 years, subjects with Pumilio1-associated developmental disability, ataxia, and seizure syndrome have been identified as harboring Pumilio homolog 1 (PUM1) mutations. However, the characteristics of the seizure phenotype remain to be elucidated. We herein described a 3-year-old female proband who was diagnosed with developmental and epileptic encephalopathy presenting with some features suggestive of a Dravet-like syndrome. For genetic analyses, trio-based whole-exome sequencing and array comparative genomic hybridization were performed. Consequently, a de novo heterozygous missense variant was identified in exon 22 of the PUM1 gene: NM_001020658: c.3439C > T (p.Arg1147Trp). Upon thoroughly reviewing the existing literature, nine cases of PUM1 mutation-related epilepsy were identified, and their clinical features were summarized. A relationship between PUM1 mutation and clinical manifestations characteristic of a Dravet-like syndrome was proposed. To our knowledge, this is the first report of a patient with PUM1 mutation presenting with a Dravet-like syndrome.

Long-term outcomes of infantile spasms in children treated with ketogenic diet therapy in combination with anti-seizure medications in a resource-limited region.

Objective: Despite numerous guidelines, the overall outcome of infantile spasms is poor, with only a small number of patients being able to attend school. The purpose of this study was to investigate long-term outcomes. Patients had poor access to the recommended first-line anti-seizure medications (ASMs), such as hormones (corticotropin or prednisolone/prednisone) and vigabatrin, and their alternative treatment was other ASMs and a ketogenic diet. Methods: Patients suffering from infantile spasms who had at least 2 years of medical records in the electronic medical record system between January 2014 and August 2022 were included in this study. Patient information was retrospectively reviewed. All patients had received ketogenic diet therapy (mainly classical ketogenic diet therapy). The ketogenic diet therapy was combined with ASMs not used as first-line therapies. The primary endpoint outcome measure was the number of patients with seizure freedom. The secondary measures included the duration of ketogenic diet therapy, choice of ASMs, and patient development at the last visit. Results: A total of 177 patients with infantile spasms were included, and 152 (86%) of them had seizure freedom. The median duration from the first to the last hospital visit was 53.27 months, and the number of visits was 47.00. The median age at the initial hospital visit was 8.00 months, and the median age at initiation of the ketogenic diet was 17.73 months. At the last visit, the proportions of patients with neurodevelopmental delay, developmental epileptic encephalopathy, drug-resistant epilepsy, and generalized seizures increased significantly. The frequently used ASMs were topiramate, valproic acid, levetiracetam, nitrazepam, and vitamin B6 injection, while the recommended first-line drugs corticotropin and vigabatrin were rarely selected. The study duration of 9.5 years was divided into three periods but the prescription of ASMs did not change significantly between these periods. Conclusions: Although the seizure freedom rate was high with ketogenic diet therapy combined with non-standard ASMs, the patients had a significant neurodevelopmental delay at the last visit, which was, however, similar to that of standard treatment. To improve the outcomes of infantile spasms, multicenter clinical trials of the ketogenic diet as a first-line treatment in combination with non-standard ASMs are needed.

Joint reconstruction framework of compressed sensing and nonlinear parallel imaging for dynamic cardiac magnetic resonance imaging.

Compressed Sensing (CS) and parallel imaging are two promising techniques that accelerate the MRI acquisition process. Combining these two techniques is of great interest due to the complementary information used in each. In this study, we proposed a novel reconstruction framework that effectively combined compressed sensing and nonlinear parallel imaging technique for dynamic cardiac imaging. Specifically, the proposed method decouples the reconstruction process into two sequential steps: In the first step, a series of aliased dynamic images were reconstructed from the highly undersampled k-space data using compressed sensing; In the second step, nonlinear parallel imaging technique, i.e. nonlinear GRAPPA, was utilized to reconstruct the original dynamic images from the reconstructed k-space data obtained from the first step. In addition, we also proposed a tailored k-space down-sampling scheme that satisfies both the incoherent undersampling requirement for CS and the structured undersampling requirement for nonlinear parallel imaging. The proposed method was validated using four in vivo experiments of dynamic cardiac cine MRI with retrospective undersampling. Experimental results showed that the proposed method is superior at reducing aliasing artifacts and preserving the spatial details and temporal variations, compared with the competing k-t FOCUSS and k-t FOCUSS with sensitivity encoding methods, with the same numbers of measurements.

Clinical Characterization of Anti-GQ1b Antibody Syndrome in Childhood.

Objective: To delineate the comprehensive clinical features of anti-GQ1b antibody syndrome in childhood. Methods: The clinical data of children diagnosed with anti-GQ1b antibody syndrome at two Chinese tertiary pediatric neurology centers were collected and analyzed. We also conducted a systematic literature review on anti-GQ1b antibody syndrome in children. Results: This study included 78 children with anti-GQ1b antibody syndrome, consisting of 12 previously unreported cases from the two Chinese centers. The median onset age was 10 years (range, 2-18 years). The most common phenotype was acute ophthalmoparesis (32%), followed by classic Miller Fisher syndrome (15%), and Bickerstaff brainstem encephalitis (12%). External ophthalmoplegia (48%), sensory disturbance (9%), and bulbar palsy (9%) were the three most frequent onset symptom manifestations. Brain or spinal lesions on MRI and abnormal recordings by nerve conduction study were present in 18% (12/68) and 60% (27/45) of cases, respectively. There was CSF albuminocytologic dissociation in 34% of the patients (23/68). IV immunoglobulin alone or combined with steroids or plasma exchange was administered to 58% of patients (42/72). We did not find a significant correlation between early improvement up to 3 months and age onset and phenotype. All patients showed different degrees of recovery, and 81% (57/70) had complete recovery within 1 year. Conclusions: Acute ophthalmoparesis and classic Miller Fisher syndrome are the most common phenotypes of anti-GQ1b antibody syndrome in childhood. The majority of patients show good response to immunotherapy and have favorable prognosis.

Altered brain function in new onset childhood acute lymphoblastic leukemia before chemotherapy: A resting-state fMRI study.

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.