Faculty Bibliography

Quantitative, volumetric analysis of Magnetic Resonance Imaging (MRI) is a fundamental way researchers study the brain in a host of neurological conditions including normal maturation and aging. Despite the availability of open-source brain segmentation software, widespread clinical adoption of volumetric analysis has been hindered due to processing times and reliance on manual corrections. Here, we extend the use of deep learning models from proof-of-concept, as previously reported, to present a comprehensive segmentation of cortical and deep gray matter brain structures matching the standard regions of aseg+ aparc included in the commonly used open-source tool, Freesurfer. The work presented here provides a real-life, rapid deep learning-based brain segmentation tool to enable clinical translation as well as research application of quantitative brain segmentation. The advantages of the presented tool include short (~ 1 minute) processing time and improved segmentation quality. This is the first study to perform quick and accurate segmentation of 102 brain regions based on the surface-based protocol (DMK protocol), widely used by experts in the field. This is also the first work to include an expert reader study to assess the quality of the segmentation obtained using a deep-learning-based model. We show the superior performance of our deep-learning-based models over the traditional segmentation tool, Freesurfer. We refer to the proposed deep learning-based tool as DARTS (DenseUnet-based Automatic Rapid Tool for brain Segmentation)

Professional use of social media continues to increase. We analyzed Twitter use of our own American Society of Neuroradiology (ASNR) 2018 annual meeting, reviewing all Twitter posts (3020 tweets from 523 participants) containing the hashtag #ASNR18 from May 21, 2018, to June 12, 2018, extracting the transcripts from Symplur. Then, each tweet was categorized by the role of user, type of tweet, and topic. The dominant user category was neuroradiologist/radiologist (63%). The keynote address, "The Radiology Renaissance: Shaping the Future of Healthcare," presented by Andy DeLao @Cancergeek was the most frequently tweeted topic (10%). Comment on a session was the major type of tweet. When we compared the data with a similar analysis in 2014, our data analysis showed a growth in the use of Twitter in only 4 years.

BACKGROUND AND PURPOSE/OBJECTIVE:Few studies have shown MR imaging features and ADC correlating with molecular markers and survival in patients with glioma. Our purpose was to correlate MR imaging features and ADC with molecular subtyping and survival in adult diffuse gliomas. MATERIALS AND METHODS/METHODS:promoter methylation, and overall survival. RESULTS:wild-type glioma. Other MR imaging features were not statistically significant predictors of survival. CONCLUSIONS:wild-type gliomas.

INTRODUCTION: We hypothesize that surgical decompression for Chiari malformation type 1 (CM-1) is associated with statistically significant decrease in tonsillar pulsatility and that the degree of pulsatility can be reliably assessed regardless of the experience level of the reader. METHODS: An Institutional Review Board (IRB)-approved Health Insurance Portability and Accountability Act (HIPAA)-compliant retrospective study was performed on 22 children with CM-1 (8 males; mean age 11.4 years) who had cardiac-gated true-FISP sequence and phase-contrast cerebrospinal fluid (CSF) flow imaging as parts of routine magnetic resonance (MR) imaging before and after surgical decompression. The surgical technique (decompression with or without duraplasty) was recorded for each patient. Three independent radiologists with different experience levels assessed tonsillar pulsatility qualitatively and quantitatively and assessed peritonsillar CSF flow qualitatively. Results were analyzed. To evaluate reliability, Fleiss kappa for multiple raters on categorical variables and intra-class correlation for agreement in pulsatility ratings were calculated. RESULTS: After surgical decompression, the degree of tonsillar pulsatility appreciably decreased, confirmed by t test, both qualitatively (p values <0.001, <0.001, and 0.045 for three readers) and quantitatively (amount of decrease/p value for three readers 0.7 mm/<0.001, 0.7 mm/<0.001, and 0.5 mm/0.022). There was a better agreement among the readers in quantitative assessment of tonsillar pulsatility (kappa 0.753-0.834), compared to qualitative assessment of pulsatility (kappa 0.472-0.496) and qualitative assessment of flow (kappa 0.056 to 0.203). Posterior fossa decompression with duraplasty led to a larger decrease in tonsillar pulsatility, compared to posterior fossa decompression alone. CONCLUSION: Tonsillar pulsatility in CM-1 is significantly reduced after surgical decompression. Quantitative assessment of tonsillar pulsatility was more reliable across readers than qualitative assessments of tonsillar pulsatility or CSF flow.

BACKGROUND: To develop evidence-based treatment guidelines for Chiari malformation type 1 (CM-1), preoperative prognostic indices capable of stratifying patients for comparative trials are needed. OBJECTIVE: To develop a preoperative Chiari Severity Index (CSI) integrating the clinical and neuroimaging features most predictive of long-term patient-defined improvement in quality of life (QOL) after CM-1 surgery. METHODS: We recorded preoperative clinical (eg, headaches, myelopathic symptoms) and neuroimaging (eg, syrinx size, tonsillar descent) characteristics. Brief follow-up surveys were administered to assess overall patient-defined improvement in QOL. We used sequential sequestration to develop clinical and neuroimaging grading systems and conjunctive consolidation to integrate these indices to form the CSI. We evaluated statistical significance using the Cochran-Armitage test and discrimination using the C statistic. RESULTS: Our sample included 158 patients. Sequential sequestration identified headache characteristics and myelopathic symptoms as the most impactful clinical parameters, producing a clinical grading system with improvement rates ranging from 81% (grade 1) to 58% (grade 3) (P = .01). Based on sequential sequestration, the neuroimaging grading system included only the presence (55% improvement) or absence (74% improvement) of a syrinx >/=6 mm (P = .049). Integrating the clinical and neuroimaging indices, improvement rates for the CSI ranged from 83% (grade 1) to 45% (grade 3) (P = .002). The combined CSI had moderately better discrimination (c = 0.66) than the clinical (c = 0.62) or neuroimaging (c = 0.58) systems alone. CONCLUSION: Integrating clinical and neuroimaging characteristics, the CSI is a novel tool that predicts patient-defined improvement after CM-1 surgery. The CSI may aid preoperative counseling and stratify patients in comparative effectiveness trials.

OBJECTIVE: To compare the diagnostic yield and safety profiles of intraoperative magnetic resonance imaging (MRI)-guided needle brain biopsy with 2 traditional brain biopsy methods: frame-based and frameless stereotactic brain biopsy. METHODS: A retrospective analysis was performed of 288 consecutive needle brain biopsies in 277 patients undergoing stereotactic brain biopsy with any of the 3 biopsy methods at Brigham and Women's Hospital from 2000-2008. Variables including age, sex, history of radiation and previous surgery, pathology results, complications, and postoperative length of hospital stay were analyzed. RESULTS: Over the course of 8 years, 288 brain biopsies were performed. Of these, 253 (87.8%) biopsies yielded positive diagnostic tissue. Young age (<40 years old) and history of brain radiation or surgery were significant negative predictors for a positive biopsy diagnostic yield. Excluding patients with prior radiation or surgeries, no significant difference in diagnostic yield was detected among the 3 groups, with frame-based biopsies yielding 96.9%, frameless biopsies yielding 91.8%, and intraoperative MRI-guided needle biopsies yielding 89.9% positive diagnostic yield. Serious adverse events occurred 19 biopsies (6.6%). Intraoperative MRI-guided brain biopsies were associated with less serious adverse events and the shortest postoperative hospital stay. CONCLUSIONS: Frame-based, frameless stereotactic, and intraoperative MRI-guided brain needle biopsy techniques have comparable diagnostic yield for patients with no prior treatments (either radiation or surgery). Intraoperative MRI-guided brain biopsy is associated with fewer serious adverse events and shorter hospital stay.