A 3-Dimensional Morphometric Analysis of 4 Midsagittal Planes for CT Scan Reference Determination in Children with Syndromic Craniosynostosis.

OBJECTIVE: To identify the suitable and practical midsagittal plane (MSP) reference for computed tomography (CT) scan skull analysis in patients with syndromic craniosynostosis. DESIGN: Retrospective study. SETTING: Tertiary referral hospital. PATIENTS AND PARTICIPANTS: A total of 19 full skull CT scans of syndromic craniosynostosis patients. METHODS: Seven craniofacial landmarks located on the midline and 4 MSPs that was previously published and clinically recognized (Planes: SPBaS, SPNSANS, SPLOrPo and SPZFTP) were constructed from the CT images. The absolute distance of every plane from 7 landmarks were then calculated. These distances were subsequently subjected to statistical analysis. MAIN OUTCOME MEASURE(S): The absolute distance of different MSPs from 7 landmarks. RESULTS: The distances of landmarks measured to SPBaS were the highest, with the most prominent fluctuation. The fluctuation of the SPNSANS, SPLOrPo and SPZFTP had similar direction changes, with the latter being the closest. Pairwise comparisons demonstrated statistical differences (P < .008 using the Bonferroni correction) between the measured distances of A point (M = 0.25, SD = 0.16) and B point (M = 2.21, SD = 1.6) to SPNSANS. There were statistical significances between distances of B point (M = 1.68, SD = 1.07) and CG point (M = 0.55, SD = 0.37) to SPZFTP plane. There was no statistical significance on each landmark to SPLOrPo. CONCLUSIONS: The study demonstrates that SPBaS is not recommended for MSP reference. While SPNSANS should be carefully selected, the application of SPLOrPo and SPZFTP are interchangeable, with the SPZFTP plane slightly exaggerating the mandible deviation relative to the superior and posterior of the midface.

Classification of optic neuritis in neuromyelitis optica spectrum disorders (NMOSD) on MRI using CNN with transfer learning and manipulation of pre-processing on augmentation.

Neuromyelitis optica spectrum disorder (NMOSD), also known as Devic disease, is an autoimmune central nervous system disorder in humans that commonly causes inflammatory demyelination in the optic nerves and spinal cord. Inflammation in the optic nerves is termed optic neuritis (ON). ON is a common clinical presentation; however, it is not necessarily present in all NMOSD patients. ON in NMOSD can be relapsing and result in severe vision loss. To the best of our knowledge, no study utilises deep learning to classify ON changes on MRI among patients with NMOSD. Therefore, this study aims to deploy eight state-of-the-art CNN models (Inception-v3, Inception-ResNet-v2, ResNet-101, Xception, ShuffleNet, DenseNet-201, MobileNet-v2, and EfficientNet-B0) with transfer learning to classify NMOSD patients with and without chronic ON using optic nerve magnetic resonance imaging. This study also investigated the effects of data augmentation before and after dataset splitting on cropped and whole images. Both quantitative and qualitative assessments (with Grad-Cam) were used to evaluate the performances of the CNN models. The Inception-v3 was identified as the best CNN model for classifying ON among NMOSD patients, with accuracy of 99.5%, sensitivity of 98.9%, specificity of 93.0%, precision of 100%, NPV of 99.0%, and F1-score of 99.4%. This study also demonstrated that the application of augmentation after dataset splitting could avoid information leaking into the testing datasets, hence producing more realistic and reliable results.

Review of Magnetic Resonance Imaging and Post-processing for the Brain Tumor-related Epilepsy Study.

20% of brain tumor patients present with seizures at the onset of diagnosis, while a further 25-40% develop epileptic seizures as the tumor progresses. Tumor-related epilepsy (TRE) is a condition in which the tumor causes recurring, unprovoked seizures. The occurrence of TRE differs between patients, along with the effectiveness of treatment methods. Therefore, determining the tumor properties that correlate with epilepsy can help guide TRE treatment. This article reviews the MRI sequences and image post-processing algorithms in the study of TRE. It focuses on epilepsy caused by glioma tumors because it is the most common type of malignant brain tumor and it has a high prevalence of epilepsy. In correlational TRE studies, conventional MRI sequences and diffusion-weighted MRI (DWI) are used to extract variables related to the tumor radiological characteristics, called imaging factors. Image post-processing is used to correlate the imaging factors with the incidence of epilepsy. The earlier studies of TRE used univariate and multivariate analysis to study the correlations between specific variables and incidence of epilepsy. Later, studies used voxel-based morphometry and voxel lesion-symptom mapping. Radiomics has been recently used to post-process the images for the study of TRE. This article will discuss the limitation of the existing imaging modalities and post-processing algorithms. It ends with some suggestions and challenges for future TRE studies.

Quantitative and Qualitative Analysis of 18 Deep Convolutional Neural Network (CNN) Models with Transfer Learning to Diagnose COVID-19 on Chest X-Ray (CXR) Images.

Coronavirus disease 2019 (COVID-19) is a disease caused by a novel strain of coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), severely affecting the lungs. Our study aims to combine both quantitative and qualitative analysis of the convolutional neural network (CNN) model to diagnose COVID-19 on chest X-ray (CXR) images. We investigated 18 state-of-the-art CNN models with transfer learning, which include AlexNet, DarkNet-19, DarkNet-53, DenseNet-201, GoogLeNet, Inception-ResNet-v2, Inception-v3, MobileNet-v2, NasNet-Large, NasNet-Mobile, ResNet-18, ResNet-50, ResNet-101, ShuffleNet, SqueezeNet, VGG-16, VGG-19, and Xception. Their performances were evaluated quantitatively using six assessment metrics: specificity, sensitivity, precision, negative predictive value (NPV), accuracy, and F1-score. The top four models with accuracy higher than 90% are VGG-16, ResNet-101, VGG-19, and SqueezeNet. The accuracy of these top four models is between 90.7% and 94.3%; the F1-score is between 90.8% and 94.3%. The VGG-16 scored the highest accuracy of 94.3% and F1-score of 94.3%. The majority voting with all the 18 CNN models and top 4 models produced an accuracy of 93.0% and 94.0%, respectively. The top four and bottom three models were chosen for the qualitative analysis. A gradient-weighted class activation mapping (Grad-CAM) was used to visualize the significant region of activation for the decision-making of image classification. Two certified radiologists performed blinded subjective voting on the Grad-CAM images in comparison with their diagnosis. The qualitative analysis showed that SqueezeNet is the closest model to the diagnosis of two certified radiologists. It demonstrated a competitively good accuracy of 90.7% and F1-score of 90.8% with 111 times fewer parameters and 7.7 times faster than VGG-16. Therefore, this study recommends both VGG-16 and SqueezeNet as additional tools for the diagnosis of COVID-19.

Structured Imaging Approach for Viral Encephalitis.

MR imaging is essential in diagnosing viral encephalitis. Clinical features, cerebrospinal fluid analysis and pathogen confirmation by polymerase chain reaction can be supported by assessing imaging features. MR imaging patterns with typical locations can identify pathogens such as temporal lobe for herpes simplex virus type 1; bilateral thalami for Japanese encephalitis and influenza virus ; and brainstem for enterovirus and rabies. In this article, we have reviewed representative viral encephalitis and its MR imaging patterns. In addition, we also presented acute viral encephalitis without typical MR imaging patterns, such as dengue and varicella-zoster virus encephalitis.

Preliminary study of longitudinal changes in the pituitary and brain of children on growth hormone therapy.

BACKGROUND: In subjects with isolated growth hormone deficiency (IGHD), recombinant human growth hormone (rhGH) is an approved method to achieve potential mid-parental height. However, data reporting rhGH treatment response in terms of brain structure volumes were scarce. We report the volumetric changes of the pituitary gland, basal ganglia, corpus callosum, thalamus, hippocampus and amygdala in these subjects post rhGH treatment. MATERIALS AND METHODS: This was a longitudinal study of eight IGHD subjects (2 males, 6 females) with a mean age of 11.1 ± 0.8 years and age-matched control groups. The pituitary gland, basal ganglia and limbic structures volumes were obtained using 3T MRI voxel-based morphology. The left-hand bone age was assessed using the Tanner-Whitehouse method. Follow-up imaging was performed after an average of 1.8 ± 0.4 years on rhGH. RESULTS: Subjects with IGHD had a smaller mean volume of the pituitary gland, right thalamus, hippocampus, and amygdala than the controls. After rhGH therapy, these volumes normalized to the age-matched controls. Corpus callosum of IGHD subjects had a larger mean volume than the controls and did not show much volume changes in response to rhGH therapy. There were changes towards normalization of bone age deficit of IGHD in response to rhGH therapy. CONCLUSION: The pituitary gland, hippocampus, and amygdala volumes in IGHD subjects were smaller than age-matched controls and showed the most response to rhGH therapy. Semi-automated volumetric assessment of pituitary gland, hippocampus, and amygdala using MRI may provide an objective assessment of response to rhGH therapy.

Lipid Alterations in Glioma: A Systematic Review.

Gliomas are highly lethal tumours characterised by heterogeneous molecular features, producing various metabolic phenotypes leading to therapeutic resistance. Lipid metabolism reprogramming is predominant and has contributed to the metabolic plasticity in glioma. This systematic review aims to discover lipids alteration and their biological roles in glioma and the identification of potential lipids biomarker. This systematic review was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Extensive research articles search for the last 10 years, from 2011 to 2021, were conducted using four electronic databases, including PubMed, Web of Science, CINAHL and ScienceDirect. A total of 158 research articles were included in this study. All studies reported significant lipid alteration between glioma and control groups, impacting glioma cell growth, proliferation, drug resistance, patients' survival and metastasis. Different lipids demonstrated different biological roles, either beneficial or detrimental effects on glioma. Notably, prostaglandin (PGE2), triacylglycerol (TG), phosphatidylcholine (PC), and sphingosine-1-phosphate play significant roles in glioma development. Conversely, the most prominent anti-carcinogenic lipids include docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and vitamin D3 have been reported to have detrimental effects on glioma cells. Furthermore, high lipid signals were detected at 0.9 and 1.3 ppm in high-grade glioma relative to low-grade glioma. This evidence shows that lipid metabolisms were significantly dysregulated in glioma. Concurrent with this knowledge, the discovery of specific lipid classes altered in glioma will accelerate the development of potential lipid biomarkers and enhance future glioma therapeutics.

OFF-Period Purposeless Groaning in Parkinsonism.

Background: Purposeless groaning is primarily encountered in patients with progressive supranuclear palsy and has also been reported to occur in advanced Parkinson's disease (PD). Objective: We describe a case of pronounced purposeless groaning occurring as a medication OFF-period nonmotor phenomenon in PD. To our knowledge, this has not been previously reported in the literature. Methods and Materials: We describe and provide video documentation of a patient with moderately advanced PD and motor fluctuations, in whom OFF-period groaning was reported by the family and observed during clinic consultations to be a prominent feature, occupying approximately 40% of his OFF periods as calculated from his PD diary. Conclusions: Although rare, OFF-period purposeless groaning in PD can be very disruptive and add significantly to caregiver burden. It is postulated to be a disinhibitory and perseverative behavior related to overactivation of the cingulo-periaqueductal circuit; further study is needed to delineate the underlying pathophysiological mechanisms.

Bone Marrow Fat Distribution in Patients With ß-Thalassemia: A Study Using Chemical Shift-Based Water-Fat MRI.

RATIONALE AND OBJECTIVES: Molecular studies have shown the changes in bone marrow fat in relation to altered hematopoiesis. This study aims to investigate the changes in the bone marrow fat in patients affected by ß-thalassemia by using chemical shift-encoded (CSE)-MRI. MATERIALS AND METHODS: Twenty-three subjects, comprising of six healthy (17-31 years old) and 17 ß-thalassemia subjects (19-39 years old), were scanned using a multiecho fast low angle shot sequence (0.94 × 0.94 × 3.00 mm3) and a stimulated echo acquisition mode sequence using 3T MRI. Bone marrow proton density fat fraction (PDFF) was quantified in the left femur of each subject. Regression and Bland-Altman analysis were used to analyze agreement between CSE-MRI and 1H-MRS. PDFF distribution was analyzed using Hartigan's dip test and the computed Wasserstein distances. Jonckheere-Terpstra trend analysis was performed to evaluate the effect of disease severity on PDFF distribution. RESULTS: An excellent agreement was found between PDFF measured using CSE-MRI with 1H-MRS (R2 = 0.91; bias =-1.41%). Healthy subjects showed left-skewed or bimodal PDFF distribution while ß-thalassemia subjects showed bimodal, normal or right-skewed distribution. Jonckheere-Terpstra test shows that PDFF distribution was increasingly different from the norm as disease severity increased (TJT = 166.0, z = 3.806, p < 0.05). Increase in variability of PDFF distribution within each subject group was also seen with increasing disease severity (TJT = 169.0, z = 3.971, p < 0.05). CONCLUSION: CSE-MRI is a promising tool to demonstrate spatial changes and variability in marrow fat distribution, resulting from ineffective erythropoiesis.

Automatic COVID-19 Detection Using Exemplar Hybrid Deep Features with X-ray Images.

COVID-19 and pneumonia detection using medical images is a topic of immense interest in medical and healthcare research. Various advanced medical imaging and machine learning techniques have been presented to detect these respiratory disorders accurately. In this work, we have proposed a novel COVID-19 detection system using an exemplar and hybrid fused deep feature generator with X-ray images. The proposed Exemplar COVID-19FclNet9 comprises three basic steps: exemplar deep feature generation, iterative feature selection and classification. The novelty of this work is the feature extraction using three pre-trained convolutional neural networks (CNNs) in the presented feature extraction phase. The common aspects of these pre-trained CNNs are that they have three fully connected layers, and these networks are AlexNet, VGG16 and VGG19. The fully connected layer of these networks is used to generate deep features using an exemplar structure, and a nine-feature generation method is obtained. The loss values of these feature extractors are computed, and the best three extractors are selected. The features of the top three fully connected features are merged. An iterative selector is used to select the most informative features. The chosen features are classified using a support vector machine (SVM) classifier. The proposed COVID-19FclNet9 applied nine deep feature extraction methods by using three deep networks together. The most appropriate deep feature generation model selection and iterative feature selection have been employed to utilise their advantages together. By using these techniques, the image classification ability of the used three deep networks has been improved. The presented model is developed using four X-ray image corpora (DB1, DB2, DB3 and DB4) with two, three and four classes. The proposed Exemplar COVID-19FclNet9 achieved a classification accuracy of 97.60%, 89.96%, 98.84% and 99.64% using the SVM classifier with 10-fold cross-validation for four datasets, respectively. Our developed Exemplar COVID-19FclNet9 model has achieved high classification accuracy for all four databases and may be deployed for clinical application.

Optic canal characteristics in pediatric syndromic craniosynostosis.

The aim of this study was to compare optic canal parameters of syndromic craniosynostosis patients with those of normal patients to visit the possibility of optic nerve impingement as a cause of visual impairment. Computed tomography scan images were processed using the Materialise Interactive Medical Image Control System (MIMICS) Research 21.0 software (Materialise NV, Leuven, Belgium). Eleven optic canal parameters were measured: 1) height of optic canal on the cranial side, 2) height of optic canal on the orbital side 3) length of the medial wall of the optic canal, 4) length of the lateral canal wall of the optic canal, 5) diameter of the optic canal at five points (Q1-Q4 and mid canal), and 6) area and perimeter of optic canal. These measurements were obtained for both the right and left optic canals. The study sample comprised four Crouzon syndrome, five Apert syndrome, and three Pfeiffer syndrome patients. The age of these syndromic craniosynostosis patients ranged from 2 to 63 months. The height of the optic canal on the orbital side (p = 0.041), diameter of the mid canal (p = 0.040), and diameter between the mid-canal and the cranial opening (Q3) (p = 0.079) for syndromic craniosynostosis patients were statistically narrower compared with those of normal patients when a significance level of 0.1 was considered. Scatter plots for the ages of patients versus the above parameters gave three separated clusters that suggested the arresting of optic canal development with age. The findings from this study demonstrated a narrowing of the optic canal in syndromic craniosynostosis patients, and indicate that optic canal anatomical characteristics may have an association with visual impairment among pediatric syndromic craniosynostosis patients.

Spectrum of imaging findings of papillary breast disease: A radiopathological review in a tertiary center.

ABSTRACT: To evaluate the clinical and imaging findings of papillary breast neoplasm and review the pathologic correlation at a tertiary center.Retrospective study of patients diagnosed with benign and malignant papillary lesions between 2008 to 2018. 147 patients were identified with histology diagnosis of papillary lesions. The clinical, imaging, and pathological characteristics were reviewed.Patient cohort included 147 women diagnosed with papillary lesions (mean age at diagnosis 53.8 years) and were divided into 3 histology groups (benign, atypical, and malignant). Common clinical presentations were breast lump (n = 60) and nipple discharge (n = 29), 48 patients were asymptomatic.Only 37 were detected as a mass lesion on mammogram. The presence of mass lesion on mammogram was the most common feature in all 3 papillary lesion groups, and with the presence of asymmetric density, were the 2 mammographic features significantly associated (P < .05) with malignancy.All lesions were detected on ultrasound. The most common sonographic features for all 3 groups were the presence of a mass and irregular shape. Among all the sonographic features assessed, larger size, presence of vascularity and absence of dilated ducts were significantly associated (P < .05) with malignancy.Feature pattern recognition of the variety of benign, atypical and malignant papillary neoplasm on ultrasound and mammogram, with emphasis on size, presence of vascularity and dilated ducts on ultrasound and presence of mass, and architectural distortion on mammogram, is important in the assessment of patients with suspected ductal lesions to facilitate optimal treatment and surgical care.

Diagnostic accuracy of tomosynthesis-guided vacuum assisted breast biopsy of ultrasound occult lesions.

This study aims to evaluate the diagnostic accuracy of digital breast tomosynthesis-guided vacuum assisted breast biopsy (DBT-VABB) of screening detected suspicious mammographic abnormalities comprising of calcifications, asymmetric densities, architectural distortions and spiculated masses. In this institutionally approved study, a total of 170 (n = 170) DBT-VABB were performed, 153 (90%) were for calcifications, 8 (4.7%) for spiculated mass, 5 (2.9%) for asymmetric density and 4 (2.4%) for architectural distortion. All these lesions were not detected on the corresponding ultrasound. Histopathology results revealed 140 (82.4%) benign, 9 (5.3%) borderline and 21 (12.4%) malignant lesions. The total upgrade rate at surgery was 40% for atypical ductal hyperplasia and 5.9% for ductal carcinoma in-situ. 3.6% discordant benign lesions showed no upgrade. DBT-VABB showed 100% specificity, 91.3% sensitivity and 100% positive predictive value (PPV) for detecting malignant lesions. The negative predictive value (NPV) was 80%. 2 (1.2%) patients had mild complications and 1 (0.6%) had severe pain. Our study showed that DBT-VABB was a safe and reliable method, with high sensitivity, specificity, PPV and NPV in the diagnosis of non-palpable benign and malignant breast lesions. Our data also confirmed the accuracy of DBT-VABB in detecting malignant lesions and we suggest further surgical excision in borderline lesions for a more accurate diagnostic evaluation.

Validity and reliability of the Neuropsychological Assessment Battery - Screening Module (S-NAB) in a subset of Malaysian population with mild traumatic brain injury (mTBI).

This study assessed the validity (construct validity) and reliability (internal consistency) of the Neuropsychological Assessment Battery Screening Module (S-NAB) in detecting mild cognitive deficit/alteration in multicultural, multilingual, and multiethnic mild traumatic brain injury (mTBI) population of Malaysia. S-NAB and Montreal Cognitive Assessment (MoCA) data from 114 patients with mTBI (93 males; 21 females) aged 18 to 60 years old were obtained at University Malaya Medical Center, Malaysia. The mean age was 28.17 ± 8.57 years and mean education years was 12.40 ± 2.01. Convergent validity was assessed between S-NAB domain scores and MoCA total scores by using Pearson's correlation and internal consistency was assessed using Cronbach's alpha. Acceptable internal consistency (α ≥ .70) was found for Attention, Language, and Memory domains but weak internal consistencies (α < .50) were found for Spatial and Executive Function domains. There were positive but weak correlations between S-NAB and MoCA. These findings provide some support for the application of S-NAB in assessing mild cognitive deficits of mTBI population in a Malaysian setting.

Osteoporosis in Parkinson's Disease: Relevance of Distal Radius Dual-Energy X-Ray Absorptiometry (DXA) and Sarcopenia.

Osteoporotic fractures are common in Parkinson's disease (PD). Standard dual-energy X-ray absorptiometry (DXA) measuring bone mineral density (BMD) at the femoral neck and lumbar spine (central sites) has suboptimal sensitivity in predicting fracture risk in the general population. An association between sarcopenia and osteoporosis in PD has not been studied. We compared BMD and osteoporosis prevalence in PD patients vs controls; determined the osteoporosis detection rates using central alone vs central plus distal radius DXA; and analyzed factors (in particular, sarcopenia) associated with osteoporosis. One hundred and fifty-six subjects (102 patients with PD, 54 spousal/sibling controls) underwent femoral neck-lumbar spine-distal radius DXA. Seventy-three patients and 46 controls were assessed for sarcopenia using whole-body DXA and handgrip strength. Patients underwent clinical and serum biochemical evaluations. PD patients had significantly lower body mass index compared to controls. After adjustment for possible confounders, distal radius BMD and T-scores were significantly lower in PD patients compared to controls, but not at the femoral neck/lumbar spine. With distal radius DXA, an additional 11.0% of patients were diagnosed with osteoporosis (32.0% to 43.0%), vs 3.7% in controls (33.3% to 37.0%) additionally diagnosed; this increase was largely driven by the markedly higher detection rate in female PD patients. Female gender (adjusted odds ratio [ORadjusted] = 11.3, 95% confidence interval [CI]: 2.6-48.6) and sarcopenia (ORadjusted = 8.4, 95% CI: 1.1-64.9) were independent predictors for osteoporosis in PD. Distal radius DXA increased osteoporosis detection, especially in female PD patients, suggesting that diagnostic protocols for osteoporosis in PD could be optimized. A close association between osteoporosis and sarcopenia was documented for the first time in PD, which has important implications for clinical management and future research.

Neural Fiber Integrity in High- Versus Low-Grade Glioma using Probabilistic Fiber Tracking.

RATIONALE AND OBJECTIVES: Gliomatous tumors are known to affect neural fiber integrity, either by displacement or destruction. The aim of this study is to investigate the integrity and distribution of the white matter tracts within and around the glioma regions using probabilistic fiber tracking. MATERIAL AND METHODS: Forty-two glioma patients were subjected to MRI using a standard tumor protocol with diffusion tensor imaging (DTI). The tumor and peritumor regions were delineated using snake model with reference to structural and diffusion MRI. A preprocessing pipeline of the structural MRI image, DTI data, and tumor regions was implemented. Tractography was performed to delineate the white matter (WM) tracts in the selected tumor regions via probabilistic fiber tracking. DTI indices were investigated through comparative mapping of WM tracts and tumor regions in low-grade gliomas (LGG) and high-grade gliomas (HGG). RESULTS: Significant differences were seen in the planar tensor (Cp) in peritumor regions; mean diffusivity, axial diffusivity and pure isotropic diffusion in solid-enhancing tumor regions; and fractional anisotropy, axial diffusivity, pure anisotropic diffusion (q), total magnitude of diffusion tensor (L), relative anisotropy, Cp and spherical tensor (Cs) in solid nonenhancing tumor regions for affected WM tracts. In most cases of HGG, the WM tracts were not completely destroyed, but found intact inside the tumor. DISCUSSION: Probabilistic fiber tracking revealed the existence and distribution of WM tracts inside tumor core for both LGG and HGG groups. There were more DTI indices in the solid nonenhancing tumor region, which showed significant differences between LGG and HGG.

Microstructural Integrity of Peripheral Nerves in Charcot-Marie-Tooth Disease: An MRI Evaluation Study.

BACKGROUND: Charcot-Marie-Tooth (CMT) disease is diagnosed through clinical findings and genetic testing. While there are neurophysiological tools and clinical functional scales in CMT, objective disease biomarkers that can facilitate in monitoring disease progression are limited. PURPOSE: To investigate the utility of diffusion tensor imaging (DTI) in determining the microstructural integrity of sciatic and peroneal nerves and its correlation with the MRI grading of muscle atrophy severity and clinical function in CMT as determined by the CMT neuropathy score (CMTNS). STUDY TYPE: Prospective case-control. SUBJECTS: Nine CMT patients and nine age-matched controls. FIELD STRENGTH/SEQUENCE: 3 T T1 -weighted in-/out-of phase spoiled gradient recalled echo (SPGR) and DTI sequences. ASSESSMENT: Fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) values for sciatic and peroneal nerves were obtained from DTI. Muscle atrophy was graded according to the Goutallier classification using in-/out-of phase SPGRs. DTI parameters and muscle atrophy grades were compared between CMT and controls, and the relationship between DTI parameters, muscle atrophy grades, and CMTNS were assessed. STATISTICAL TESTS: The Wilcoxon Signed Ranks test was used to compare DTI parameters between CMT and controls. The relationship between DTI parameters, muscle atrophy grades, and CMTNS were analyzed using the Spearman correlation. Receiver operating characteristic (ROC) analyses of DTI parameters that can differentiate CMT from healthy controls were done. RESULTS: There was a significant reduction in FA and increase in RD of both nerves (P < 0.05) in CMT, with significant correlations between FA (negative; P < 0.05) and RD (positive; P < 0.05) with muscle atrophy grade. In the sciatic nerve, there was significant correlation between FA and CMTNS (r = -0.795; P < 0.05). FA and RD could discriminate CMT from controls with high sensitivity (77.8-100%) and specificity (88.9-100%). DATA CONCLUSION: There were significant differences of DTI parameters between CMT and controls, with significant correlations between DTI parameters, muscle atrophy grade, and CMTNS. Level of Evidence 2 Technical Efficacy Stage 2 J. MAGN. RESON. IMAGING 2021;53:437-444.

Optic Canal Analysis in Syndromic Craniosynostosis: Volumetric and Surface Area Validation Study Using Different Measurement Modalities.

BACKGROUND: In syndromic craniosynostosis (SC), unlike persistent corneal irritation due to severe exophthalmos and increased intracranial pressure, optic canal (OC) stenosis has been scarcely reported to cause visual impairment. This study aimed to validate the OC volumetric and surface area measurement among SC patients. METHODS: Sixteen computed tomography scan of SC patients (8 months-6 years old) were imported to Materialise Interactive Medical Image Control System (MIMICS) and Materialise 3-matics software. Three-dimensional (3D) OC models were fabricated, and linear measurements were obtained. Mathematical formulas were used for calculation of OC volume and surface area from the 3D model. The same measurements were obtained from the software and used as ground truth. Data normality was investigated before statistical analyses were performed. Wilcoxon test was used to validate differences of OC volume and surface area between 3D model and software. RESULTS: The mean values for OC surface area for 3D model and MIMICS software were 103.19 mm2 and 31.27 mm2, respectively, whereas the mean for OC volume for 3D model and MIMICS software were 184.37 mm2 and 147.07 mm2, respectively. Significant difference was found between OC volume (P = 0.0681) and surface area (P = 0.0002) between 3D model and software. CONCLUSION: Optic canal in SC is not a perfect conical frustum thus making 3D model measurement and mathematical formula for surface area and volume estimation not ideal. Computer software remains the best modality to gauge dimensional parameter and is useful to elucidates the relationship of OC and eye function as well as aiding intervention in SC patients.