MR susceptibility contrast imaging using a 2D simultaneous multi-slice gradient-echo sequence at 7T.
2019; 14 (7): e0219705
Imaging Evaluation of the Adult Presenting With New-Onset Seizure.
AJR. American journal of roentgenology
PURPOSE: To develop a 7T simultaneous multi-slice (SMS) 2D gradient-echo sequence for susceptibility contrast imaging, and to compare its quality to 3D imaging.METHODS: A frequency modulated and phase cycled RF pulse was designed to simultaneously excite multiple slices in multi-echo 2D gradient-echo imaging. The imaging parameters were chosen to generate images with susceptibility contrast, including T2*-weighted magnitude/phase images, susceptibility-weighted images and quantitative susceptibility/R2* maps. To compare their image quality with 3D gradient-echo imaging, both 2D and 3D imaging were performed on 11 healthy volunteers and 4 patients with multiple sclerosis (MS). The signal to noise ratio (SNR) in gray and white matter and their contrast to noise ratio (CNR) was simulated for the 2D and 3D magnitude images using parameters from the imaging. The experimental SNRs and CNRs were measured in gray/white matter and deep gray matter structures on magnitude, phase, R2* and QSM images from volunteers and the visibility of MS lesions on these images from patients was visually rated. All SNRs and CNRs were compared between the 2D and 3D imaging using a paired t-test.RESULTS: Although the 3D magnitude images still had significantly higher SNRs (by 13.0~17.6%), the 2D magnitude and QSM images generated significantly higher gray/white matter or globus pallidus/putamen contrast (by 13.3~87.5%) and significantly higher MS lesion contrast (by 5.9~17.3%).CONCLUSION: 2D SMS gradient-echo imaging can serve as an alternative to often used 3D imaging to obtain susceptibility-contrast-weighted images, with an advantage of providing better image contrast and MS lesion sensitivity.
View details for DOI 10.1371/journal.pone.0219705
View details for PubMedID 31314813
MR Imaging-Based Radiomic Signatures of Distinct Molecular Subgroups of Medulloblastoma.
AJNR. American journal of neuroradiology
OBJECTIVE: The purpose of this study is to discuss the evidence supporting the use of neuroimaging in adult patients presenting with new-onset seizure.CONCLUSION: Unenhanced CT should be the initial imaging examination performed for adults presenting with first unprovoked seizure in the acute setting to exclude conditions requiring urgent or emergent intervention. MRI has added benefits and should be considered for adults presenting acutely for whom the initial CT is negative and for those presenting with new-onset seizure in the nonacute setting.
View details for PubMedID 30299997
Contemporary Imaging of Cerebral Arteriovenous Malformations.
AJR. American journal of roentgenology
Distinct molecular subgroups of pediatric medulloblastoma confer important differences in prognosis and therapy. Currently, tissue sampling is the only method to obtain information for classification. Our goal was to develop and validate radiomic and machine learning approaches for predicting molecular subgroups of pediatric medulloblastoma.In this multi-institutional retrospective study, we evaluated MR imaging datasets of 109 pediatric patients with medulloblastoma from 3 children's hospitals from January 2001 to January 2014. A computational framework was developed to extract MR imaging-based radiomic features from tumor segmentations, and we tested 2 predictive models: a double 10-fold cross-validation using a combined dataset consisting of all 3 patient cohorts and a 3-dataset cross-validation, in which training was performed on 2 cohorts and testing was performed on the third independent cohort. We used the Wilcoxon rank sum test for feature selection with assessment of area under the receiver operating characteristic curve to evaluate model performance.Of 590 MR imaging-derived radiomic features, including intensity-based histograms, tumor edge-sharpness, Gabor features, and local area integral invariant features, extracted from imaging-derived tumor segmentations, tumor edge-sharpness was most useful for predicting sonic hedgehog and group 4 tumors. Receiver operating characteristic analysis revealed superior performance of the double 10-fold cross-validation model for predicting sonic hedgehog, group 3, and group 4 tumors when using combined T1- and T2-weighted images (area under the curve = 0.79, 0.70, and 0.83, respectively). With the independent 3-dataset cross-validation strategy, select radiomic features were predictive of sonic hedgehog (area under the curve = 0.70-0.73) and group 4 (area under the curve = 0.76-0.80) medulloblastoma.This study provides proof-of-concept results for the application of radiomic and machine learning approaches to a multi-institutional dataset for the prediction of medulloblastoma subgroups.
View details for PubMedID 30523141
In Vivo 7T MR Quantitative Susceptibility Mapping Reveals Opposite Susceptibility Contrast between Cortical and White Matter Lesions in Multiple Sclerosis
AMERICAN JOURNAL OF NEURORADIOLOGY
2016; 37 (10): 1808-1815
Brain arteriovenous malformation (AVM) rupture results in substantial morbidity and mortality. The goal of AVM treatment is eradication of the AVM, but the risk of treatment must be weighed against the risk of future hemorrhage.Imaging plays a vital role by providing the information necessary for AVM management. Here, we discuss the background, natural history, clinical presentation, and imaging of AVMs. In addition, we explain advances in techniques for imaging AVMs.
View details for DOI 10.2214/AJR.16.17306
View details for PubMedID 28267351
Imaging Neck Masses in the Neonate and Young Infant
SEMINARS IN ULTRASOUND CT AND MRI
2015; 36 (2): 120-137
Magnetic susceptibility measured with quantitative susceptibility mapping has been proposed as a biomarker for demyelination and inflammation in patients with MS, but investigations have mostly been on white matter lesions. A detailed characterization of cortical lesions has not been performed. The purpose of this study was to evaluate magnetic susceptibility in both cortical and WM lesions in MS by using quantitative susceptibility mapping.Fourteen patients with MS were scanned on a 7T MR imaging scanner with T1-, T2-, and T2*-weighted sequences. The T2*-weighted sequence was used to perform quantitative susceptibility mapping and generate tissue susceptibility maps. The susceptibility contrast of a lesion was quantified as the relative susceptibility between the lesion and its adjacent normal-appearing parenchyma. The susceptibility difference between cortical and WM lesions was assessed by using a t test.The mean relative susceptibility was significantly negative for cortical lesions (P < 10(-7)) but positive for WM lesions (P < 10(-22)). A similar pattern was also observed in the cortical (P = .054) and WM portions (P = .043) of mixed lesions.The negative susceptibility in cortical lesions suggests that iron loss dominates the susceptibility contrast in cortical lesions. The opposite susceptibility contrast between cortical and WM lesions may reflect both their structural (degree of myelination) and pathologic (degree of inflammation) differences, in which the latter may lead to a faster release of iron in cortical lesions.
View details for DOI 10.3174/ajnr.A4830
View details for Web of Science ID 000383984600014
View details for PubMedID 27282860
Head and neck masses occurring in the neonatal period and early infancy consist of vascular tumors, vascular malformations, benign and malignant soft tissue tumors, and other developmental lesions. Although some lesions can be diagnosed on clinical grounds, others can only be diagnosed by imaging. Beyond diagnosis, imaging plays a significant role in evaluating the location and extent of a lesion for possible intervention. In this article, we review the clinical presentation and imaging appearance of common and rare masses that may be encountered in this age group. We also highlight current treatment strategies for specific lesions.
View details for DOI 10.1053/j.sult.2015.01.004
View details for Web of Science ID 000355575300003
View details for PubMedID 26001942