2019-20 Oncologic Neuroradiology Fellowship – UT MD Anderson Cancer Center

2019-20 Oncologic Neuroradiology Fellowship – UT MD Anderson Cancer Center

We are currently looking to fill our position for the Oncologic Neuroradiology Fellowship for 2019-2020 at MD Anderson Cancer Center in Houston, Texas.

For additional program information please visit:

Why MD Anderson

Fellowship at a top ranked cancer center in the country for several years running.

A comprehensive program of imaging for brain, spine, head and enck tumors, with focus on advanced imaging techniques.

The Section of Neuroradiology is an integral part of the Brain and Spine Center.

The Head and Neck Surgery Department is also a premiere oncologic service that also receives national and international referral with over 60-70 new tumor patients presenting in the average week.

Diverse case material providing fellow with exposure to the full gamut of head and neck imaging from primary diagnosis to surveillance in complex post-treatment cases.

Curriculum that includes journal club, case conferences, tumor board, advanced neurologic imaging conferences, weekly lectures, and multidisciplinary conferences.

Opportunities for research/publications.

The University of Texas MD Anderson Cancer Center is an equal employment opportunity employer.

If you have a question or have questions, please contact:
Komal Shah, MD
Associate Professor & Oncologic Neuroradiology Fellowship Program Director
Department of Diagnostic Radiology
The University of Texas MD Anderson Cancer Center, 1400 Pressler St. – Unit 1482
Houston, Texas 77030

Interested applicants should complete application at:
** Application and interview required by November 1, 2018, for consideration for fellowship beginning July 1, 2019

Applicants may also email the following; CV, USMLE transcript, Personal Statement, 3 LORS to:
Melanie Gracia – Program Administrative Assistant
Phone: 713-745-0567

1) Be board eligible or certified for diagnostic radiology or its foreign equivalent, 2) Have completed an ACGME approved neuroradiology 1 year fellowship or its foreign equivalent. Alternatively, significant work experience (at least 1 year full time …

The Bone Does Not Predict the Brain in Sturge-Weber Syndrome

Editor’s Choice

MR imaging of 139 children presenting with port-wine stain and/or Sturge-Weber syndrome between 1998 and 2017 was evaluated by 2 pediatric neuroradiologists for marrow signal abnormality and pial angioma and other Sturge-Weber syndrome features. Groups were divided into port-wine stain-only (without intracranial Sturge-Weber syndrome features) and Sturge-Weber syndrome (the presence of cerebral pial angioma). In the port-wine stain-only cohort, 78% had ipsilateral bony changes and 17% had no intraosseous changes. In the Sturge-Weber syndrome cohort, 84/99 had associated port-wine stain, 91% had bony changesipsilateral to the port-wine stain or had no bone changes in the absence of port-wine stain, and 77% had bony changes ipsilateral to a cerebral pial angioma. The authors conclude that intraosseous marrow changes are strongly associated with facial port-wine stain. No significant association was found between pial angioma and bone marrow changes.

sturge-weber syndrome

Brain Perfusion Measurements Using Multidelay Arterial Spin-Labeling Are Systematically Biased by the Number of Delays

Editor’s Choice

The authors assessed delay and transit time-uncorrected and transit time-corrected CBF maps in 87 healthy controls. Data analysis included voxelwise permutation-based between-sequence comparisons of 3-delay versus 7-delay, within-sequence comparison of transit time-uncorrected versus transit time-corrected maps, and average CBF calculations in regions that have been shown to differ. The 7-delay sequence estimated a higher CBF value than the 3-delay for the transit time-uncorrected and transit time-corrected maps in regions corresponding to the watershed areas. In the peripheral regions of the brain, the estimated delay was found to be longer for the 3-delay sequence while the inverse was found in the center of the brain. This study supports the necessity of standardizing acquisition parameters in multidelay arterial spin-labeling and identifying basic parameters as a confounding factor in CBF quantification studies.

Added Value of Spectroscopy to Perfusion MRI in the Differential Diagnostic Performance of Common Malignant Brain Tumors

Fellows’ Journal Club

From January 2013 to January 2016, fifty-five consecutive patients with histopathologically proved lymphomas, glioblastomas, and metastases were included in this study after undergoing MR imaging. The perfusion parameters (maximum relative CBV, maximum percentage of signal intensity recovery) and spectroscopic concentration ratios (lactate/Cr, Cho/NAA, Cho/Cr, and lipids/Cr) were analyzed individually and in optimal combinations. The highest differential diagnostic performance was obtained with the following combined classifiers: 1) maximum percentage of signal intensity recovery-Cho/NAA to discriminate lymphomas from glioblastomas and metastases; 2) relative CBV-Cho/NAA to discriminate glioblastomas from lymphomas and metastases; and 3) maximum percentage of signal intensity recovery-lactate/Cr and maximum percentage of signal intensity recovery-Cho/Cr to discriminate metastases from lymphomas and glioblastomas. The authors conclude that spectroscopy yielded an added performance value to perfusion using optimal combined classifiers of these modalities.

Contextual Radiology Reporting: A New Approach to Neuroradiology Structured Templates

Editor’s Choice

Contextual reporting is an alternative method of structured reporting that is specifically related to the disease or examination indication. These disease-specific reports provide content focused on the clinical diagnosis or symptom, discuss appropriate differential diagnoses, and highlight pertinent positives and negatives. The authors created a library of 50 contextual structured reports for neuroradiologists and emphasize their clinical value over noncontextual structured reporting.

Relationship between Cough-Associated Changes in CSF Flow and Disease Severity in Chiari I Malformation: An Exploratory Study Using Real-Time MRI

Editor’s Choice

The authors correlated disease severity in symptomatic patients with Chiari I malformation with cough-associated changes in CSF flow as measured with real-time MR imaging. Patients were classified into 2 groups by neurosurgeons blinded to MR imaging measurements: 1) nonspecific Chiari I malformation (5/13)—Chiari I malformation with nonspecific symptoms like non-cough-related or mild occasional cough-related headache, neck pain, dizziness, paresthesias, and/or trouble swallowing; 2) specific Chiari I malformation (8/13)—patients with Chiari I malformation with specific symptoms and/or objective findings like severe cough-related headache, myelopathy, syringomyelia, and muscle atrophy. There was a significant negative correlation between the percentage change in CSF stroke volume (resting to post coughing) and Chiari I malformation disease severity. They conclude that assessment of CSF flow response to a coughing challenge has the potential to become a valuable objective noninvasive test for clinical assessment of disease severity in patients with Chiari I malformation.

Clinical Significance of Intraplaque Hemorrhage in Low- and High-Grade Basilar Artery Stenosis on High-Resolution MRI

Fellows’ Journal Club

Patients with basilar artery stenosis (n=126; 66 symptomatic and 60 asymptomatic) underwent high-resolution MR imaging. The relationship between imaging findings (intraplaque hemorrhage, contrast enhancement, degree of stenosis, minimal lumen area, and plaque burden) and symptoms was analyzed. Intraplaque hemorrhage was identified in 22 patients (17.5%), including 21 (31.8%) symptomatic patients and 1 (1.7%) asymptomatic patient. Multivariate analysis showed that intraplaque hemorrhage was the strongest independent marker of symptomatic status. Contrast enhancement was also independently associated with symptomatic status. The authors conclude that intraplaque hemorrhage is present in both low- and high-grade stenotic basilar artery plaques and is independently associated with symptomatic stroke status. Intraplaque hemorrhage may identify high-risk plaque and provide new insight into the management of patients with stroke without significant stenosis.

Identification of Chronic Active Multiple Sclerosis Lesions on 3T MRI

Editor’s Choice

MR imaging–pathologic studies have reported that paramagnetic rims on 7T susceptibility-based MR imaging identify, in vivo, a subset of MS lesions with compartmentalized inflammation at the lesion edge and associated remyelination failure. High-resolution T2* and phase MR imaging were collected in 20 patients with MS at 3T and 7T. Phase rims were seen in 34 lesions at 7T and in 36 lesions at 3T by consensus. Inter- and intra-rater reliability were “substantial/good” both at 3T and 7T analysis. Nearly all 7T paramagnetic rims can also be seen at 3T. Imaging at 3T opens the possibility of implementing paramagnetic rims as an outcome measure.

Visualization and Classification of Deeply Seated Collateral Networks in Moyamoya Angiopathy with 7T MRI

Fellows’ Journal Club

This study aimed to evaluate morphologic patterns and the delineation of deeply seated collateral networks using ultra-high-field MRA in comparison with conventional DSA in 15 patients. Sequences acquired at 7T were TOF-MRA with 0.22 X 0.22 X 0.41 mm3 resolution and MPRAGE with 0.7 X 0.7 X 0.7 mm3 resolution. The relevant deeply seated collateral networks were classified into 2 categories and 6 pathways. A total of 100 collateral networks were detected on DSA; 106, on TOF-MRA; and 73, on MPRAGE. Delineation of deeply seated collateral networks was comparable between TOF-MRA and DSA. The authors demonstrate excellent delineation of 6 distinct deeply seated collateral network pathways in Moyamoya angiopathy.

Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas

Editor’s Choice

MR imaging data and molecular information were retrospectively obtained from The Cancer Imaging Archives for 259 patients with either low- or high-grade gliomas. A convolutional neural network was trained to classify IDH1 mutation status, 1p/19q codeletion, and MGMT promotor methylation status. Classification had high accuracy: IDH1 mutation status, 94%; 1p/19q codeletion, 92%; and MGMT promotor methylation status, 83%. The authors conclude that this shows the feasibility of a deep-learning CNN approach for the accurate classification of individual genetic mutations of both low- and high-grade gliomas and that the relevant MR imaging features acquired from an added dimensionality-reduction technique are concordant with existing literature, showing that neural networks are capable of learning key imaging components without prior feature selection or human directed training.