PAHPhysRAD: A Digital Imaging and Communications in Medicine Research Tool for Segmentation and Radiomic Feature Extraction.

Introduction: Segmentation and analysis of organs at risks (OARs) and tumor volumes are integral concepts in the development of radiotherapy treatment plans and prediction of patients' treatment outcomes. Aims: To develop a research tool, PAHPhysRAD, that can be used to semi- and fully automate segmentation of OARs. In addition, the proposed software seeks to extract 3214 radiomic features from tumor volumes and user-specified dose-volume parameters. Materials and Methods: Developed within MATLAB, PAHPhysRAD provides a comprehensive suite of segmentation tools, including manual, semi-automatic, and automatic options. For semi-autosegmentation, meta AI's Segment Anything Model was incorporated using the bounding box methods. Autosegmentation of OARs and tumor volume are implemented through a module that enables the addition of models in Open Neural Network Exchange format. To validate the radiomic feature extraction module in PAHPhysRAD, radiomic features extracted from gross tumor volume of 15 non-small cell lung carcinoma patients were compared against the features extracted from 3D Slicer™. The dose-volume parameters extraction module was validated using the dose volume data extracted from 28 tangential field-based breast treatment planning datasets. The volume receiving ≥20 Gy (V20) for ipsilateral lung and the mean doses received by the heart and ipsilateral lung, were compared against the parameters extracted from Eclipse. Results: The Wilcoxon signed-rank test revealed no significant difference between the majority of the radiomic features derived from PAHPhysRAD and 3D Slicer. The average mean lung and heart doses calculated in Eclipse were 5.51 ± 2.28 Gy and 1.64 ± 1.98 Gy, respectively. Similarly, the average mean lung and heart doses calculated in PAHPhysRAD were 5.45 ± 2.89 Gy and 1.67 ± 2.08 Gy, respectively. Conclusion: The MATLAB-based graphical user interface, PAHPhysRAD, offers a user-friendly platform for viewing and analyzing medical scans with options to extract radiomic features and dose-volume parameters. Its versatility, compatibility, and potential for further development make it an asset in medical image analysis.

Repurposing traditional U-Net predictions for sparse SAM prompting in medical image segmentation.

Objective:Automated medical image segmentation (MIS) using deep learning has traditionally relied on models built and trained from scratch, or at least fine-tuned on a target dataset. The Segment Anything Model (SAM) by Meta challenges this paradigm by providing zero-shot generalisation capabilities. This study aims to develop and compare methods for refining traditional U-Net segmentations by repurposing them for automated SAM prompting.Approach:A 2D U-Net with EfficientNet-B4 encoder was trained using 4-fold cross-validation on an in-house brain metastases dataset. Segmentation predictions from each validation set were used for automatic sparse prompt generation via a bounding box prompting method (BBPM) and novel implementations of the point prompting method (PPM). The PPMs frequently produced poor slice predictions (PSPs) that required identification and substitution. A slice was identified as a PSP if it (1) contained multiple predicted regions per lesion or (2) possessed outlier foreground pixel counts relative to the patient's other slices. Each PSP was substituted with a corresponding initial U-Net or SAM BBPM prediction. The patients' mean volumetric dice similarity coefficient (DSC) was used to evaluate and compare the methods' performances.Main results:Relative to the initial U-Net segmentations, the BBPM improved mean patient DSC by 3.93 ± 1.48% to 0.847 ± 0.008 DSC. PSPs constituted 20.01-21.63% of PPMs' predictions and without substitution performance dropped by 82.94 ± 3.17% to 0.139 ± 0.023 DSC. Pairing the two PSP identification techniques yielded a sensitivity to PSPs of 92.95 ± 1.20%. By combining this approach with BBPM prediction substitution, the PPMs achieved segmentation accuracies on par with the BBPM, improving mean patient DSC by up to 4.17 ± 1.40% and reaching 0.849 ± 0.007 DSC.Significance:The proposed PSP identification and substitution techniques bridge the gap between PPM and BBPM performance for MIS. Additionally, the uniformity observed in our experiments' results demonstrates the robustness of SAM to variations in prompting style. These findings can assist in the design of both automatically and manually prompted pipelines.

Investigation of Computed Tomography Numbers on Multiple Imaging Systems using Single and Multislice Methods.

Aim: The aim of this study is to determine the variation in Hounsfield values with single and multi-slice methods using in-house software on fan-beam computed tomography (FCT), linear accelerator (linac) cone-beam computed tomography (CBCT), and Icon-CBCT datasets acquired using Gammex and advanced electron density (AED) phantoms. Materials and Methods: The AED phantom was scanned on a Toshiba computed tomography (CT) scanner, five linac-based CBCT X-ray volumetric imaging systems, and Leksell Gamma Knife Icon. The variation between single and multi-slice methods was assessed by comparing scans acquired using Gammex and AED phantoms. The variation in Hounsfield units (HUs) between seven different clinical protocols was assessed using the AED phantom. A CIRS Model 605 Radiosurgery Head Phantom (TED) phantom was scanned on all three imaging systems to assess the target dosimetric changes due to HU variation. An in-house software was developed in MATLAB to assess the HU statistics and the trend along the longitudinal axis. Results: The FCT dataset showed a minimal variation (central slice ± 3 HU) in HU values along the long axis. A similar trend was also observed between the studied clinical protocols acquired on FCT. Variation among multiple linac CBCTs was insignificant. In the case of the water insert, a maximum HU variation of -7.23 ± 68.67 was observed for Linac 1 towards the inferior end of the phantom. All five linacs appeared to have a similar trend in terms of HU variation from the proximal to the distal end of the phantom, with a few outliers for Linac 5. Among three imaging modalities, the maximum variation was observed in gamma knife CBCTs, whereas FCT showed no appreciable deviation from the central value. In terms of dosimetric comparison, the mean dose in CT and Linac CBCT scans differed by <0.5 Gy, whereas at least a 1 Gy difference was observed between CT and gamma knife CBCT. Conclusion: This study shows a minimal variation with FCT between single, volume-based, and multislice methods, and hence the current approach of determining the CT-electron density curve based on a single-slice method would be sufficient for producing a HU calibrations curve for treatment planning. However, CBCTs acquired on linac, and in particular, gamma knife systems, show noticeable variations along the long axis, which is likely to affect the dose calculations performed on CBCTs. It is highly recommended to assess the Hounsfield values on multiple slices before using the HU curve for dose calculations.

Autism and developmental disability caused by KCNQ3 gain-of-function variants.

OBJECTIVE: Recent reports have described single individuals with neurodevelopmental disability (NDD) harboring heterozygous KCNQ3 de novo variants (DNVs). We sought to assess whether pathogenic variants in KCNQ3 cause NDD and to elucidate the associated phenotype and molecular mechanisms. METHODS: Patients with NDD and KCNQ3 DNVs were identified through an international collaboration. Phenotypes were characterized by clinical assessment, review of charts, electroencephalographic (EEG) recordings, and parental interview. Functional consequences of variants were analyzed in vitro by patch-clamp recording. RESULTS: Eleven patients were assessed. They had recurrent heterozygous DNVs in KCNQ3 affecting residues R230 (R230C, R230H, R230S) and R227 (R227Q). All patients exhibited global developmental delay within the first 2 years of life. Most (8/11, 73%) were nonverbal or had a few words only. All patients had autistic features, and autism spectrum disorder (ASD) was diagnosed in 5 of 11 (45%). EEGs performed before 10 years of age revealed frequent sleep-activated multifocal epileptiform discharges in 8 of 11 (73%). For 6 of 9 (67%) recorded between 1.5 and 6 years of age, spikes became near-continuous during sleep. Interestingly, most patients (9/11, 82%) did not have seizures, and no patient had seizures in the neonatal period. Voltage-clamp recordings of the mutant KCNQ3 channels revealed gain-of-function (GoF) effects. INTERPRETATION: Specific GoF variants in KCNQ3 cause NDD, ASD, and abundant sleep-activated spikes. This new phenotype contrasts both with self-limited neonatal epilepsy due to KCNQ3 partial loss of function, and with the neonatal or infantile onset epileptic encephalopathies due to KCNQ2 GoF. ANN NEUROL 2019;86:181-192.

POGZ truncating alleles cause syndromic intellectual disability.

BACKGROUND: Large-scale cohort-based whole exome sequencing of individuals with neurodevelopmental disorders (NDDs) has identified numerous novel candidate disease genes; however, detailed phenotypic information is often lacking in such studies. De novo mutations in pogo transposable element with zinc finger domain (POGZ) have been identified in six independent and diverse cohorts of individuals with NDDs ranging from autism spectrum disorder to developmental delay. METHODS: Whole exome sequencing was performed on five unrelated individuals. Sanger sequencing was used to validate variants and segregate mutations with the phenotype in available family members. RESULTS: We identified heterozygous truncating mutations in POGZ in five unrelated individuals, which were confirmed to be de novo or not present in available parental samples. Careful review of the phenotypes revealed shared features that included developmental delay, intellectual disability, hypotonia, behavioral abnormalities, and similar facial characteristics. Variable features included short stature, microcephaly, strabismus and hearing loss. CONCLUSIONS: While POGZ has been associated with neurodevelopmental disorders in large cohort studies, our data suggest that loss of function variants in POGZ lead to an identifiable syndrome of NDD with specific phenotypic traits. This study exemplifies the era of human reverse clinical genomics ushered in by large disease-directed cohort studies; first defining a new syndrome molecularly and, only subsequently, phenotypically.

A review of childhood and adolescent craniopharyngiomas with particular attention to hypothalamic obesity.

BACKGROUND: Although craniopharyngiomas are considered "benign" neoplasms by the World Health Organization classification, these tumors may create significant morbidity and mortality in patients. Hypothalamic obesity is a frequent complication of craniopharyngiomas and is refractory to current management options. PATIENTS/METHODS: We reviewed 24 cases of craniopharyngiomas treated from 1992 to 2010 in patients <18 years of age regarding clinical presentation, neuroimaging, recurrence, morbidity, and mortality, with particular attention to hypothalamic obesity. RESULTS: Our cohort conformed to published data in regard to neuroimaging characteristics, and clinical findings in the areas of endocrine, visual, neurological, neurobehavioral, and hypothalamic domains. At last follow-up, 53% of our patients were overweight (8%) or obese (46%). Only 25% of our patients had a healthy body mass index. Contrasting these data with body mass indices at diagnosis, where 21% of patients were overweight and 17% were obese, we found that there was a significant trend towards obesity over time. A significant portion of our mortality appears to be related to complications of obesity. The Native American population in Arizona appears to have a statistically greater incidence of obesity in childhood. Despite our small sample size, 75% of our Native Americans were obese at last follow-up and accounted for 50% of the mortality. CONCLUSION: Hypothalamic obesity is a significant complication of craniopharyngiomas associated with increased mortality. The development of hypothalamic obesity is influenced by premorbid obesity, genetics, and therapy received, specifically radiation. Because of the intractability of hypothalamic obesity, improved understanding of neuroendocrine mechanisms, genomics, and newer antiobesity medications will be necessary to curb this significant complication.

Utility and safety of prolonged video-EEG monitoring in a tertiary pediatric epilepsy monitoring unit.

Prolonged video-EEG (vEEG) monitoring helps characterize paroxysmal events and epilepsy. There is limited literature in pediatrics describing the safety and utility of vEEG. We retrospectively reviewed 454 pediatric epilepsy monitoring unit admissions over two years. Final event diagnoses, duration of seizures, and medical complications were analyzed. Two hundred twenty admissions (48.4%) captured epileptic seizures, 150 (33.0%) captured nonepileptic events, and 84 (18.5%) failed to capture any events. Medical complications were seen in 4 patients (1.8%) with no long-term complications. Seventeen episodes of status epilepticus occurred in 13 patients. This constituted 2.9% of all admissions and 5.9% of admissions with epileptic seizures. The median duration of status was 26 min, and three patients required transfer to the pediatric intensive care unit. Video-EEG monitoring had a high yield in capturing events and differentiating epileptic from nonepileptic events. Our pediatric patients experienced greater risk of status epilepticus but lesser risk of injury.

Calvarial defects and skeletal dysplasia in patients with neurofibromatosis Type 1.

OBJECT: Skull defects, including sphenoid dysplasia and calvarial defects, are rare but distinct findings in patients with neurofibromatosis Type 1 (NF1). The underlying pathophysiology is unclear. The goal of this study was to identify the clinical characteristics and natural history of skull defects in patients with NF1. METHODS: An electronic search engine of medical records was used to identify patients with NF1 and bony skull anomalies. All clinical, radiographic, pathology, and operative reports were reviewed. The relationship between bony anomalies and significant clinical associations was evaluated. This study received institutional review board approval. RESULTS: Twenty-one patients were identified. The mean age at NF1 diagnosis was 4.2 years. The mean age at skull defect diagnosis was 8.8 years (9.7 years in the sphenoid wing dysplasia group and 11.9 years in the calvarial defect group). Sphenoid dysplasia was associated with a plexiform neurofibroma or dural ectasia in 73.3% and 80.0% of cases, respectively. Calvarial defects were associated with a plexiform neurofibroma or dural ectasia in 66.7% and 33.3% of patients, respectively. An absence of either an associated neurofibroma or ectasia was not noted in any patient with sphenoid wing dysplasia or 25.0% of those with calvarial defects. In 6 patients, both types of skull defects presented simultaneously. Serial imaging studies were obtained for a mean follow-up time of 7.5 years (range 0.4-20.0 years). Of these patients with serial imaging, radiographic progression was found in 60% of cases of calvarial defects and 56% of cases of sphenoid wing dysplasia. Two patients underwent surgical repair of a skull defect, and both required repeat procedures. CONCLUSIONS: The majority of skull defects in patients with NF1 were associated with an adjacent structural lesion, such as a plexiform neurofibroma or dural ectasia. This findings from this cohort also support the concept of progression in defect size in more than half of the patients. Potential mechanisms by which these secondary lesions contribute to pathogenesis of the bony defect may include changes in the bony microenvironment. A better understanding of the pathophysiology of skull defects will help guide detection, improve treatment and outcome, and may contribute to the understanding of the pathogenesis of bony lesions in NF1.