A hybrid method for traumatic brain injury lesion segmentation

Traumatic brain injuries are significant effects of disability and loss of life. Physicians employ computed tomography (CT) images to observe the trauma and measure its severity for diagnosis and treatment. Due to the overlap of hemorrhage and normal brain tissues, segmentation methods sometimes lead to false results. The study is more challenging to unitize the AI field to collect brain hemorrhage by involving patient datasets employing CT scans images. We propose a novel technique free-form object model for brain injury CT image segmentation based on superpixel image processing that uses CT to analyzing brain injuries, quite challenging to create a high outstanding simple linear iterative clustering (SLIC) method. The maintains a strategic distance of the segmentation image to reduced intensity boundaries. The segmentation image contains marked red hemorrhage to modify the free-form object model. The contour labelled by the red mark is the output from our free-form object model. We proposed a hybrid image segmentation approach based on the combined edge detection and dilation technique features. The approach diminishes computational costs, and the show accomplished 96.68% accuracy. The segmenting brain hemorrhage images are achieved in the clustered region to construct a free-form object model. The study also presents further directions on future research in this domain

Diagnostic Values of Red Flags and a Clinical Prediction Score for Emergent Intracranial Lesions in Non-Traumatic Pediatric Headaches

Introduction: Diagnosis of emergent intracranial lesions that require emergency treatment either medically or surgically in non-traumatic pediatric headaches is important. Red-flag signs and symptoms are commonly used as justification for neuroimaging; however, evidence on its diagnostic values is limited. The study aims to identify diagnostic values of red-flags and develop a clinical prediction score to help improve the diagnostic yield of neuroimaging. Methods: A retrospective review of 109 pediatric patients from 2006 to 2020 who presented with a non-traumatic headache was conducted. A clinical prediction score from red flags was developed using multivariate logistic regression. Discriminatory ability was examined using the area under the receiver operating characteristic curve. Results: A total of 51 patients were diagnosed with emergent intracranial lesions. Four potential clinical red flag predictors were identified: (1) acute onset (less than 3 months), (2) altered conscious state, (3) focal motor abnormality, and (4) and ocular/pupillary abnormality or squint. A clinical prediction score was developed with good discriminatory properties (0.84). Conclusions: Clinical predictor scores from these four red flags may play an important role in maximizing neuroimaging and proper management for pediatric patients with non-traumatic headaches. Future validation studies are needed and could guide referrals and optimize the use of neuroimaging for these patients

Sphenoid Sinus Diseases: A Review of 1,442 Patients

Objective. To review and report diseases of the sphenoid sinus from the literature and from a university hospital. Methods. Inpatients’ data were retrospectively gathered and reviewed from January 2006 to June 2016. Clinical data, imaging, organisms, and pathological reports were collected. Pathology was divided into infection/inflammation, tumor, and miscellaneous. A literature review was performed with the search term “isolated sphenoid disease” in PubMed. Original primary studies with 20 patients or more were reviewed. Results and Discussion. One hundred and twenty-two patients were enrolled. Seventy-two subjects were female (59%). The average age was 54.3 years (±18.0). Imaging abnormalities were found incidentally in 27 patients (22.1%). The most common symptom was headache (63.9%). Visual loss, the second most common symptom, was more frequent in the tumor group (30.6% versus 54.2%). From the literature review, 21 primary studies with 1,320 total patients were included. From all studies and the present study, infection/inflammation was the most common pathology (75%) [95% confidence interval (CI): 0.696, 0.804]. Overall, tumors were found in 18.9% and malignant tumors in 7.0% [95% CI: 0.045, 0.095]. Conclusion. A specific diagnosis of a sphenoid lesion is needed during active investigation. Infection/inflammation was the most common pathology and malignancy was found in 7%

A comparison of performance between a deep learning model with residents for localization and classification of intracranial hemorrhage

Abstract Intracranial hemorrhage (ICH) from traumatic brain injury (TBI) requires prompt radiological investigation and recognition by physicians. Computed tomography (CT) scanning is the investigation of choice for TBI and has become increasingly utilized under the shortage of trained radiology personnel. It is anticipated that deep learning models will be a promising solution for the generation of timely and accurate radiology reports. Our study examines the diagnostic performance of a deep learning model and compares the performance of that with detection, localization and classification of traumatic ICHs involving radiology, emergency medicine, and neurosurgery residents. Our results demonstrate that the high level of accuracy achieved by the deep learning model, (0.89), outperforms the residents with regard to sensitivity (0.82) but still lacks behind in specificity (0.90). Overall, our study suggests that the deep learning model may serve as a potential screening tool aiding the interpretation of head CT scans among traumatic brain injury patients

A Founder Intronic Variant in P3H1 Likely Results in Aberrant Splicing and Protein Truncation in Patients of Karen Descent with Osteogenesis Imperfecta Type VIII

One of the most important steps in post-translational modifications of collagen type I chains is the hydroxylation of carbon-3 of proline residues by prolyl-3-hydroxylase-1 (P3H1). Genetic variants in P3H1 have been reported to cause autosomal recessive osteogenesis imperfecta (OI) type VIII. Clinical and radiographic examinations, whole-exome sequencing (WES), and bioinformatic analysis were performed in 11 Thai children of Karen descent affected by multiple bone fractures. Clinical and radiographic findings in these patients fit OI type VIII. Phenotypic variability is evident. WES identified an intronic homozygous variant (chr1:43212857A > G; NM_022356.4:c.2055 + 86A > G) in P3H1 in all patients, with parents in each patient being heterozygous for the variant. This variant is predicted to generate a new “CAG” splice acceptor sequence, resulting in the incorporation of an extra exon that leads to a frameshift in the final exon and subsequent non-functional P3H1 isoform a. Alternative splicing of P3H1 resulting in the absence of functional P3H1 caused OI type VIII in 11 Thai children of Karen descent. This variant appears to be specific to the Karen population. Our study emphasizes the significance of considering intronic variants

A Founder Intronic Variant in <i>P3H1</i> Likely Results in Aberrant Splicing and Protein Truncation in Patients of Karen Descent with Osteogenesis Imperfecta Type VIII

One of the most important steps in post-translational modifications of collagen type I chains is the hydroxylation of carbon-3 of proline residues by prolyl-3-hydroxylase-1 (P3H1). Genetic variants in P3H1 have been reported to cause autosomal recessive osteogenesis imperfecta (OI) type VIII. Clinical and radiographic examinations, whole-exome sequencing (WES), and bioinformatic analysis were performed in 11 Thai children of Karen descent affected by multiple bone fractures. Clinical and radiographic findings in these patients fit OI type VIII. Phenotypic variability is evident. WES identified an intronic homozygous variant (chr1:43212857A > G; NM_022356.4:c.2055 + 86A > G) in P3H1 in all patients, with parents in each patient being heterozygous for the variant. This variant is predicted to generate a new “CAG” splice acceptor sequence, resulting in the incorporation of an extra exon that leads to a frameshift in the final exon and subsequent non-functional P3H1 isoform a. Alternative splicing of P3H1 resulting in the absence of functional P3H1 caused OI type VIII in 11 Thai children of Karen descent. This variant appears to be specific to the Karen population. Our study emphasizes the significance of considering intronic variants

Clinical and Genetic Studies of the First Monozygotic Twins with Pfeiffer Syndrome

Objective: To report the clinical and radiographic findings and molecular etiology of the first monozygotic twins affected with Pfeiffer syndrome. Methods: Clinical and radiographic examination and whole exome sequencing were performed on two monozygotic twins with Pfeiffer syndrome. Results: An acceptor splice site mutation in FGFR2 (c.940-2A&gt;G) was detected in both twins. The father and both twins shared the same haplotype, indicating that the mutant allele was from their father&rsquo;s chromosome who suffered severe upper airway obstruction and subsequent obstructive sleep apnea. Hypertrophy of nasal turbinates appears to be a newly recognized finding of Pfeiffer syndrome. Increased intracranial pressure in both twins were corrected early by fronto-orbital advancement with skull expansion and open osteotomy, in order to prevent the more severe consequences of increased intracranial pressure, including hydrocephalus, the bulging of the anterior fontanelle, and the diastasis of suture. Conclusions: Both twins carried a FGFR2 mutation and were discordant for lambdoid synostosis. Midface hypoplasia, narrow nasal cavities, and hypertrophic nasal turbinates resulted in severe upper airway obstruction and subsequent obstructive sleep apnea in both twins. Hypertrophy of the nasal turbinates appears to be a newly recognized finding of Pfeiffer syndrome. Fronto-orbital advancement with skull expansion and open osteotomy was performed to treat increased intracranial pressure in both twins. This is the first report of monozygotic twins with Pfeiffer syndrome

The RSNA Cervical Spine Fracture CT Dataset.

This dataset is composed of cervical spine CT images with annotations related to fractures; it is available at https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/

The RSNA Cervical Spine Fracture CT Dataset.

This dataset is composed of cervical spine CT images with annotations related to fractures; it is available at https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/