Publications by authors named "Jerrold L Boxerman"

40 Publications

The relationship between cerebral and retinal microbleeds in cerebral amyloid angiopathy (CAA): A pilot study.

J Neurol Sci 2021 04 1;423:117383. Epub 2021 Mar 1.

Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, Kingston, RI, USA; George and Anne Ryan Institute for Neuroscience, University of Rhode Island, Kingston, RI, USA; Department of Neurology, Alpert Medical School of Brown University, Providence, RI, USA; Department of Surgery (Ophthalmology), Alpert Medical School of Brown University, Providence, RI, USA.

Background: The standard in vivo diagnostic imaging technique for cerebral amyloid angiopathy (CAA) is costly and thereby of limited utility for point-of-care diagnosis and monitoring of treatment efficacy. Recent recognition that retinal changes may reflect cerebral changes in neurodegenerative disease provides an ideal opportunity for development of accessible and cost-effective biomarkers for point-of-care use in the detection and monitoring of CAA. In this pilot study, we examined structural and angiographic retinal changes in CAA patients relative to a control group, and compared retinal and cerebral pathology in a group of CAA patients.

Methods: We used spectral domain optical coherence tomography (SD-OCT) to image the retina and compared retinal microbleeds to both cerebral microbleeds and white matter hyperintensities (WMH) in CAA patients, as seen on MRI. We compared retinal angiographic changes, along with structural retinal neuronal layer changes in CAA patients and cognitively normal older adults, and examined the relationship between retinal and cerebral microbleeds and cognition in CAA patients.

Results: We found a trend level correlation between retinal and cerebral microbleeds in CAA patients. Moreover, we found a significant correlation between retinal microbleeds and episodic memory performance in CAA patients. There were no significant group differences between CAA patients and cognitively normal older adults on retinal angiographic or structural measurements.

Conclusion: Retinal microbleeds may reflect degree of cerebral microbleed burden in CAA. This picture was complicated by systolic hypertension in the CAA group, which is a confounding factor for the interpretation of these data. Our results stimulate motivation for pursuit of a more comprehensive prospective study to determine the feasibility of retinal biomarkers in CAA.
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http://dx.doi.org/10.1016/j.jns.2021.117383DOI Listing
April 2021

Consensus Recommendations for MRI and PET Imaging of Primary Central Nervous System Lymphoma: Guideline Statement from the International Primary CNS Lymphoma Collaborative Group (IPCG).

Neuro Oncol 2021 Feb 9. Epub 2021 Feb 9.

Department of Radiology, Neuroradiology Division, Mayo Clinic, Phoenix, AZ USA.

Advanced molecular and pathophysiologic characterization of Primary Central Nervous System Lymphoma (PCNSL) has revealed insights into promising targeted therapeutic approaches. Medical imaging plays a fundamental role in PCNSL diagnosis, staging, and response assessment. Institutional imaging variation and inconsistent clinical trial reporting diminishes the reliability and reproducibility of clinical response assessment. In this context, we aimed to: 1) critically review the use of advanced PET and MRI in the setting of PCNSL; 2) provide results from an international survey of clinical sites describing the current practices for routine and advanced imaging, and 3) provide biologically based recommendations from the International PCNSL Collaborative Group (IPCG) on adaptation of standardized imaging practices. The IPCG provides PET and MRI consensus recommendations built upon previous recommendations for standardized brain tumor imaging protocols (BTIP) in primary and metastatic disease. A biologically integrated approach is provided to addresses the unique challenges associated with the imaging assessment of PCNSL. Detailed imaging parameters facilitate the adoption of these recommendations by researchers and clinicians. To enhance clinical feasibility, we have developed both "ideal" and "minimum standard" protocols at 3T and 1.5T MR systems that will facilitate widespread adoption.
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http://dx.doi.org/10.1093/neuonc/noab020DOI Listing
February 2021

Robust breast cancer detection in mammography and digital breast tomosynthesis using an annotation-efficient deep learning approach.

Nat Med 2021 02 11;27(2):244-249. Epub 2021 Jan 11.

DeepHealth Inc., RadNet AI Solutions, Cambridge, MA, USA.

Breast cancer remains a global challenge, causing over 600,000 deaths in 2018 (ref. ). To achieve earlier cancer detection, health organizations worldwide recommend screening mammography, which is estimated to decrease breast cancer mortality by 20-40% (refs. ). Despite the clear value of screening mammography, significant false positive and false negative rates along with non-uniformities in expert reader availability leave opportunities for improving quality and access. To address these limitations, there has been much recent interest in applying deep learning to mammography, and these efforts have highlighted two key difficulties: obtaining large amounts of annotated training data and ensuring generalization across populations, acquisition equipment and modalities. Here we present an annotation-efficient deep learning approach that (1) achieves state-of-the-art performance in mammogram classification, (2) successfully extends to digital breast tomosynthesis (DBT; '3D mammography'), (3) detects cancers in clinically negative prior mammograms of patients with cancer, (4) generalizes well to a population with low screening rates and (5) outperforms five out of five full-time breast-imaging specialists with an average increase in sensitivity of 14%. By creating new 'maximum suspicion projection' (MSP) images from DBT data, our progressively trained, multiple-instance learning approach effectively trains on DBT exams using only breast-level labels while maintaining localization-based interpretability. Altogether, our results demonstrate promise towards software that can improve the accuracy of and access to screening mammography worldwide.
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http://dx.doi.org/10.1038/s41591-020-01174-9DOI Listing
February 2021

Radiographic read paradigms and the roles of the central imaging laboratory in neuro-oncology clinical trials.

Neuro Oncol 2021 02;23(2):189-198

UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA.

Determination of therapeutic benefit in intracranial tumors is intimately dependent on serial assessment of radiographic images. The Response Assessment in Neuro-Oncology (RANO) criteria were established in 2010 to provide an updated framework to better characterize tumor response to contemporary treatments. Since this initial update a number of RANO criteria have provided some basic principles for the interpretation of changes on MR images; however, the details of how to operationalize RANO and other criteria for use in clinical trials are ambiguous and not standardized. In this review article designed for the neuro-oncologist or treating clinician, we outline essential steps for performing radiographic assessments by highlighting primary features of the Imaging Charter (referred to as the Charter for the remainder of this article), a document that describes the clinical trial imaging methodology and methods to ensure operationalization of the Charter into the workings of a clinical trial. Lastly, we provide recommendations for specific changes to optimize this methodology for neuro-oncology, including image registration, requirement of growing tumor for eligibility in trials of recurrent tumor, standardized image acquisition guidelines, and hybrid reader paradigms that allow for both unbiased measurements and more comprehensive interpretation.
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http://dx.doi.org/10.1093/neuonc/noaa253DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7906061PMC
February 2021

Deep neural network to locate and segment brain tumors outperformed the expert technicians who created the training data.

J Med Imaging (Bellingham) 2020 Sep 16;7(5):055501. Epub 2020 Oct 16.

Mayo Clinic, Mathematical NeuroOncology Lab, Phoenix, Arizona, United States.

Deep learning (DL) algorithms have shown promising results for brain tumor segmentation in MRI. However, validation is required prior to routine clinical use. We report the first randomized and blinded comparison of DL and trained technician segmentations. We compiled a multi-institutional database of 741 pretreatment MRI exams. Each contained a postcontrast T1-weighted exam, a T2-weighted fluid-attenuated inversion recovery exam, and at least one technician-derived tumor segmentation. The database included 729 unique patients (470 males and 259 females). Of these exams, 641 were used for training the DL system, and 100 were reserved for testing. We developed a platform to enable qualitative, blinded, controlled assessment of lesion segmentations made by technicians and the DL method. On this platform, 20 neuroradiologists performed 400 side-by-side comparisons of segmentations on 100 test cases. They scored each segmentation between 0 (poor) and 10 (perfect). Agreement between segmentations from technicians and the DL method was also evaluated quantitatively using the Dice coefficient, which produces values between 0 (no overlap) and 1 (perfect overlap). The neuroradiologists gave technician and DL segmentations mean scores of 6.97 and 7.31, respectively ( ). The DL method achieved a mean Dice coefficient of 0.87 on the test cases. This was the first objective comparison of automated and human segmentation using a blinded controlled assessment study. Our DL system learned to outperform its "human teachers" and produced output that was better, on average, than its training data.
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http://dx.doi.org/10.1117/1.JMI.7.5.055501DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7567400PMC
September 2020

Detecting Large Vessel Occlusion at Multiphase CT Angiography by Using a Deep Convolutional Neural Network.

Radiology 2020 12 29;297(3):640-649. Epub 2020 Sep 29.

From the Departments of Diagnostic Imaging (M.T.S., M.J., J.L.B., G.L.B., R.A.M.), Diagnostic Imaging (A.D.Y.), and Neurosurgery (M.J., R.A.M.), Warren Alpert School of Medicine at Brown University, Rhode Island Hospital, 593 Eddy St, APC 701, Providence, RI 02903; Department of Computer Science, Brown University, Providence, RI (J.V., M.P.D., Y.H.K., S.S.S., H.J.T., A.W., H.L.C.W., C.E., U.C.); and the Norman Prince Neuroscience Institute, Rhode Island Hospital, Providence, RI (M.J., R.A.M.).

Background Large vessel occlusion (LVO) stroke is one of the most time-sensitive diagnoses in medicine and requires emergent endovascular therapy to reduce morbidity and mortality. Leveraging recent advances in deep learning may facilitate rapid detection and reduce time to treatment. Purpose To develop a convolutional neural network to detect LVOs at multiphase CT angiography. Materials and Methods This multicenter retrospective study evaluated 540 adults with CT angiography examinations for suspected acute ischemic stroke from February 2017 to June 2018. Examinations positive for LVO ( = 270) were confirmed by catheter angiography and LVO-negative examinations ( = 270) were confirmed through review of clinical and radiology reports. Preprocessing of the CT angiography examinations included vasculature segmentation and the creation of maximum intensity projection images to emphasize the contrast agent-enhanced vasculature. Seven experiments were performed by using combinations of the three phases (arterial, phase 1; peak venous, phase 2; and late venous, phase 3) of the CT angiography. Model performance was evaluated on the held-out test set. Metrics included area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Results The test set included 62 patients (mean age, 69.5 years; 48% women). Single-phase CT angiography achieved an AUC of 0.74 (95% confidence interval [CI]: 0.63, 0.85) with sensitivity of 77% (24 of 31; 95% CI: 59%, 89%) and specificity of 71% (22 of 31; 95% CI: 53%, 84%). Phases 1, 2, and 3 together achieved an AUC of 0.89 (95% CI: 0.81, 0.96), sensitivity of 100% (31 of 31; 95% CI: 99%, 100%), and specificity of 77% (24 of 31; 95% CI: 59%, 89%), a statistically significant improvement relative to single-phase CT angiography ( = .01). Likewise, phases 1 and 3 and phases 2 and 3 also demonstrated improved fit relative to single phase ( = .03). Conclusion This deep learning model was able to detect the presence of large vessel occlusion and its diagnostic performance was enhanced by using delayed phases at multiphase CT angiography examinations. © RSNA, 2020 See also the editorial by Ospel and Goyal in this issue.
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http://dx.doi.org/10.1148/radiol.2020200334DOI Listing
December 2020

Value of dynamic contrast perfusion MRI to predict early response to bevacizumab in newly diagnosed glioblastoma: results from ACRIN 6686 multicenter trial.

Neuro Oncol 2021 02;23(2):314-323

Department of Diagnostic Imaging, Rhode Island Hospital, and Warren Alpert Medical School of Brown University, Providence, Rhode Island.

Background: In Radiation Therapy Oncology Group (RTOG) 0825, a phase III trial of standard therapy with bevacizumab or without (placebo) in newly diagnosed glioblastoma, 44 patients underwent dynamic contrast enhanced (DCE) and/or dynamic susceptibility contrast (DSC) MRI in the American College of Radiology Imaging Network (ACRIN) trial 6686. The association between early changes in relative cerebral blood volume (rCBV) and volume transfer constant (Ktrans) with overall survival (OS) was evaluated.

Methods: MRI was performed at postop baseline (S0), immediately before (S1), 1 day after (S2), and 7 weeks after (S3) bevacizumab or placebo initiation. Mean normalized and standardized rCBV (nRCBV, sRCBV) and Ktrans were measured within contrast-enhancing lesion. Wilcoxon rank sum tests compared parameter changes from S1-S2 and S1-S3. Association with OS and progression-free survival (PFS) were determined using Kaplan-Meier and log-rank tests. Treatment response for groups stratified by pretreatment nRCBV (S0, S1) was explored. The intraclass correlation coefficient and repeatability coefficient for the placebo arm (S1-S2) were used to assess repeatability.

Results: Evaluable were 27-36 datasets per time point. Significant differences between treatment arms were found for changes in nRCBV and sRCBV from S1-S2 and S1-S3, and in Ktrans for S1-S3. Improved PFS (P = 0.05) but not OS (P = 0.46) was observed. High pretreatment rCBV predicted improved OS for bevacizumab-treated patients. Based on the intraclass correlation coefficient, sRCBV (0.92) was more repeatable than nRCBV (0.71) and Ktrans (0.75), consistent with repeatability coefficient values.

Conclusions: Bevacizumab significantly changes rCBV but not Ktrans as early as 1 day posttreatment in newly diagnosed glioblastoma unrelated to outcomes. Improvements in clinical trial design to maximize rCBV benefit are indicated.
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http://dx.doi.org/10.1093/neuonc/noaa167DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7906067PMC
February 2021

Evaluating the Use of rCBV as a Tumor Grade and Treatment Response Classifier Across NCI Quantitative Imaging Network Sites: Part II of the DSC-MRI Digital Reference Object (DRO) Challenge.

Tomography 2020 06;6(2):203-208

Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ.

We have previously characterized the reproducibility of brain tumor relative cerebral blood volume (rCBV) using a dynamic susceptibility contrast magnetic resonance imaging digital reference object across 12 sites using a range of imaging protocols and software platforms. As expected, reproducibility was highest when imaging protocols and software were consistent, but decreased when they were variable. Our goal in this study was to determine the impact of rCBV reproducibility for tumor grade and treatment response classification. We found that varying imaging protocols and software platforms produced a range of optimal thresholds for both tumor grading and treatment response, but the performance of these thresholds was similar. These findings further underscore the importance of standardizing acquisition and analysis protocols across sites and software benchmarking.
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http://dx.doi.org/10.18383/j.tom.2020.00012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289259PMC
June 2020

Consensus recommendations for a dynamic susceptibility contrast MRI protocol for use in high-grade gliomas.

Neuro Oncol 2020 09;22(9):1262-1275

Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.

Despite the widespread clinical use of dynamic susceptibility contrast (DSC) MRI, DSC-MRI methodology has not been standardized, hindering its utilization for response assessment in multicenter trials. Recently, the DSC-MRI Standardization Subcommittee of the Jumpstarting Brain Tumor Drug Development Coalition issued an updated consensus DSC-MRI protocol compatible with the standardized brain tumor imaging protocol (BTIP) for high-grade gliomas that is increasingly used in the clinical setting and is the default MRI protocol for the National Clinical Trials Network. After reviewing the basis for controversy over DSC-MRI protocols, this paper provides evidence-based best practices for clinical DSC-MRI as determined by the Committee, including pulse sequence (gradient echo vs spin echo), BTIP-compliant contrast agent dosing (preload and bolus), flip angle (FA), echo time (TE), and post-processing leakage correction. In summary, full-dose preload, full-dose bolus dosing using intermediate (60°) FA and field strength-dependent TE (40-50 ms at 1.5 T, 20-35 ms at 3 T) provides overall best accuracy and precision for cerebral blood volume estimates. When single-dose contrast agent usage is desired, no-preload, full-dose bolus dosing using low FA (30°) and field strength-dependent TE provides excellent performance, with reduced contrast agent usage and elimination of potential systematic errors introduced by variations in preload dose and incubation time.
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http://dx.doi.org/10.1093/neuonc/noaa141DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7523451PMC
September 2020

Detection of emergent large vessel occlusion stroke with CT angiography is high across all levels of radiology training and grayscale viewing methods.

Eur Radiol 2020 Aug 31;30(8):4447-4453. Epub 2020 Mar 31.

Department of Diagnostic Imaging, Warren Alpert School of Medicine at Brown University, 593 Eddy Street, Room 302, Providence, RI, 02903, USA.

Objectives: CT angiography (CTA) is essential in acute stroke to detect emergent large vessel occlusions (ELVO) and must be interpreted by radiologists with and without subspecialized training. Additionally, grayscale inversion has been suggested to improve diagnostic accuracy in other radiology applications. This study examines diagnostic performance in ELVO detection between neuroradiologists, non-neuroradiologists, and radiology residents using standard and grayscale inversion viewing methods.

Methods: A random, counterbalanced experimental design was used, where 18 radiologists with varying experiences interpreted the same patient images with and without grayscale inversion. Confirmed positive and negative ELVO cases were randomly ordered using a balanced design. Sensitivity, specificity, positive and negative predictive values as well as confidence, subjective assessment of image quality, time to ELVO detection, and overall interpretation time were examined between grayscale inversion (on/off) by experience level using generalized mixed modeling assuming a binary, negative binomial, and binomial distributions, respectively.

Results: All groups of radiologists had high sensitivity and specificity for ELVO detection (all > .94). Neuroradiologists were faster than non-neuroradiologists and residents in interpretation time, with a mean of 47 s to detect ELVO, as compared with 59 and 74 s, respectively. Residents were subjectively less confident than attending physicians. With respect to grayscale inversion, no differences were observed between groups with grayscale inversion vs. standard viewing for diagnostic performance (p = 0.30), detection time (p = .45), overall interpretation time (p = .97), and confidence (p = .20).

Conclusions: Diagnostic performance in ELVO detection with CTA was high across all levels of radiologist training level. Grayscale inversion offered no significant detection advantage.

Key Points: • Stroke is an acute vascular syndrome that requires acute vascular imaging. • Proximal large vessel occlusions can be identified quickly and accurately by radiologists across all training levels. • Grayscale inversion demonstrated minimal detectable benefit in the detection of proximal large vessel occlusions.
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http://dx.doi.org/10.1007/s00330-020-06814-9DOI Listing
August 2020

Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement.

Neuro Oncol 2019 11;21(11):1412-1422

Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.

Background: Longitudinal measurement of glioma burden with MRI is the basis for treatment response assessment. In this study, we developed a deep learning algorithm that automatically segments abnormal fluid attenuated inversion recovery (FLAIR) hyperintensity and contrast-enhancing tumor, quantitating tumor volumes as well as the product of maximum bidimensional diameters according to the Response Assessment in Neuro-Oncology (RANO) criteria (AutoRANO).

Methods: Two cohorts of patients were used for this study. One consisted of 843 preoperative MRIs from 843 patients with low- or high-grade gliomas from 4 institutions and the second consisted of 713 longitudinal postoperative MRI visits from 54 patients with newly diagnosed glioblastomas (each with 2 pretreatment "baseline" MRIs) from 1 institution.

Results: The automatically generated FLAIR hyperintensity volume, contrast-enhancing tumor volume, and AutoRANO were highly repeatable for the double-baseline visits, with an intraclass correlation coefficient (ICC) of 0.986, 0.991, and 0.977, respectively, on the cohort of postoperative GBM patients. Furthermore, there was high agreement between manually and automatically measured tumor volumes, with ICC values of 0.915, 0.924, and 0.965 for preoperative FLAIR hyperintensity, postoperative FLAIR hyperintensity, and postoperative contrast-enhancing tumor volumes, respectively. Lastly, the ICCs for comparing manually and automatically derived longitudinal changes in tumor burden were 0.917, 0.966, and 0.850 for FLAIR hyperintensity volume, contrast-enhancing tumor volume, and RANO measures, respectively.

Conclusions: Our automated algorithm demonstrates potential utility for evaluating tumor burden in complex posttreatment settings, although further validation in multicenter clinical trials will be needed prior to widespread implementation.
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http://dx.doi.org/10.1093/neuonc/noz106DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6827825PMC
November 2019

Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference Object (DRO).

Tomography 2019 03;5(1):110-117

Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ.

Relative cerebral blood volume (rCBV) cannot be used as a response metric in clinical trials, in part, because of variations in biomarker consistency and associated interpretation across sites, stemming from differences in image acquisition and postprocessing methods (PMs). This study leveraged a dynamic susceptibility contrast magnetic resonance imaging digital reference object to characterize rCBV consistency across 12 sites participating in the Quantitative Imaging Network (QIN), specifically focusing on differences in site-specific imaging protocols (IPs; n = 17), and PMs (n = 19) and differences due to site-specific IPs and PMs (n = 25). Thus, high agreement across sites occurs when 1 managing center processes rCBV despite slight variations in the IP. This result is most likely supported by current initiatives to standardize IPs. However, marked intersite disagreement was observed when site-specific software was applied for rCBV measurements. This study's results have important implications for comparing rCBV values across sites and trials, where variability in PMs could confound the comparison of therapeutic effectiveness and/or any attempts to establish thresholds for categorical response to therapy. To overcome these challenges and ensure the successful use of rCBV as a clinical trial biomarker, we recommend the establishment of qualifying and validating site- and trial-specific criteria for scanners and acquisition methods (eg, using a validated phantom) and the software tools used for dynamic susceptibility contrast magnetic resonance imaging analysis (eg, using a digital reference object where the ground truth is known).
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http://dx.doi.org/10.18383/j.tom.2018.00041DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6403027PMC
March 2019

Interreader Variability of Dynamic Contrast-enhanced MRI of Recurrent Glioblastoma: The Multicenter ACRIN 6677/RTOG 0625 Study.

Radiology 2019 02 27;290(2):467-476. Epub 2018 Nov 27.

From the Department of Radiology, Duke University Medical Center, 2301 Erwin Rd, Durham, NC 27710 (D.P.B.); Department of Biostatistics and Center for Statistical Sciences, Brown University, Providence, RI (Z.Z.); Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center, Houston, Tex (P.D.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (B.S.S.); Pharmascan Clinical Trials and Radiology Associates of Clearwater, University of South Florida, Clearwater, Fla (Y.S.); Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (R.C.M.); Neuro-Oncology Service, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel (F.B.); A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Mass (G.S.); Siemens Healthcare, Malvern, Pa (G.S.); Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, Tex (M.R.G.); and Department of Diagnostic Imaging, Rhode Island Hospital and Alpert Medical School of Brown University, Providence, RI (J.L.B.).

Purpose To evaluate factors contributing to interreader variation (IRV) in parameters measured at dynamic contrast material-enhanced (DCE) MRI in patients with glioblastoma who were participating in a multicenter trial. Materials and Methods A total of 18 patients (mean age, 57 years ± 13 [standard deviation]; 10 men) who volunteered for the advanced imaging arm of ACRIN 6677, a substudy of the RTOG 0625 clinical trial for recurrent glioblastoma treatment, underwent analyzable DCE MRI at one of four centers. The 78 imaging studies were analyzed centrally to derive the volume transfer constant (K) for gadolinium between blood plasma and tissue extravascular extracellular space, fractional volume of the extracellular extravascular space (v), and initial area under the gadolinium concentration curve (IAUGC). Two independently trained teams consisting of a neuroradiologist and a technologist segmented the enhancing tumor on three-dimensional spoiled gradient-recalled acquisition in the steady-state images. Mean and median parameter values in the enhancing tumor were extracted after registering segmentations to parameter maps. The effect of imaging time relative to treatment, map quality, imager magnet and sequence, average tumor volume, and reader variability in tumor volume on IRV was studied by using intraclass correlation coefficients (ICCs) and linear mixed models. Results Mean interreader variations (± standard deviation) (difference as a percentage of the mean) for mean and median IAUGC, mean and median K, and median v were 18% ± 24, 17% ± 23, 27% ± 34, 16% ± 27, and 27% ± 34, respectively. ICCs for these metrics ranged from 0.90 to 1.0 for baseline and from 0.48 to 0.76 for posttreatment examinations. Variability in reader-derived tumor volume was significantly related to IRV for all parameters. Conclusion Differences in reader tumor segmentations are a significant source of interreader variation for all dynamic contrast-enhanced MRI parameters. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Wolf in this issue.
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http://dx.doi.org/10.1148/radiol.2019181296DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6358054PMC
February 2019

Myelin water fraction changes in febrile seizures.

Clin Neurol Neurosurg 2018 12 10;175:61-67. Epub 2018 Oct 10.

Division of Pediatric Neurosurgery, Joe DiMaggio Children's Hospital, 1150N 35th Ave, Hollywood, FL, 33021, USA. Electronic address:

Objective: The objective of this feasibility study was to investigate whether myelin water fraction (MWF) patterns can differentiate children presenting with febrile seizures who will go on to develop nonfebrile epilepsy from those who will not.

Patients And Methods: As part of a prospective study of myelination patterns in pediatric epilepsy, seven subjects with febrile seizures underwent magnetic resonance imaging (MRI) including the following standard sequences-T1-weighted, T2-weighted, fluid-attenuated inversion recovery (FLAIR)-and an additional experimental sequence, multicomponent-derived equilibrium single-pulse observation of T1 and T2 (mcDESPOT) to quantify MWF. For each of these subjects, MWF maps were derived and compared with an age-matched population-averaged MWF atlas.

Results: All seven subjects (<5 years old) initially presented with febrile seizures. Of the seven, four had complex seizures and three had simple seizures. All of the children with simple febrile seizures had higher MWF compared with model-derived controls and did not develop epilepsy. All of the children with complex febrile seizures had lower MWF than their model-derived control, and two of these subjects later developed epilepsy.

Conclusion: This is the first study in which MWF maps were used to study children with febrile *seizures. This data suggests that relatively higher or stable MWF compared with normative data indicates a lower risk of nonfebrile epilepsy while relatively lower MWF may indicate a pathological condition that could lead to nonfebrile epilepsy.
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http://dx.doi.org/10.1016/j.clineuro.2018.10.005DOI Listing
December 2018

Group A streptococcus acute otitis media progressing to neuroinvasive disease in adults.

IDCases 2018 23;12:161-164. Epub 2018 May 23.

Department of Infectious Disease, Rhode Island Hospital and Alpert Medical School of Brown, Providence, RI, United States.

Acute otitis media affects 700 million people each year with children being disproportionately affected relative to adults. Group A streptococcus is a pathogen implicated in a broad array of human pathology. It is, however, a rare cause of acute otitis media and neuroinvasive disease in older adults with only 2-3 cases occurring per year in the United States. We describe two such cases from a single institution in Rhode Island in 2017. The clinical presentation, neuroimaging and management are reviewed. The mechanism of intracranial spread may have involved dehiscence of the bony tegmen of the roof of the middle ear cavity.
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http://dx.doi.org/10.1016/j.idcr.2018.05.012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6011036PMC
May 2018

First confirmed case of Powassan neuroinvasive disease in Rhode Island.

IDCases 2018 23;12:84-87. Epub 2018 Mar 23.

Department of Infectious Disease, Rhode Island Hospital and Alpert Medical School of Brown University, United States.

The Powassan Virus is the arthropod-borne vector responsible for Powassan neuroinvasive disease. The virus was first isolated in 1958 and has been responsible for approximately 100 cases of neuroinvasive disease. Rates of infection have been on the rise over the past decade with numerous states reporting their first confirmed case; New Jersey, New Hampshire and Connecticut all reported their first case within the last five years. We present here the first confirmed case of Powassan neuroinvasive disease in the nearby state of Rhode Island. A previously healthy 81-year-old female with known tick exposure presented with fever, altered sensorium, seizures and focal neurological deficits. After an extensive work-up that was largely unrevealing Powassan encephalitis was suspected. The diagnosis was confirmed with serological testing consisting of Powassan IgM enzyme-linked immunosorbent assay and Powassan plaque reduction neutralization testing. The case study provides evidence for the increasing spread of Powassan neuroinvasive disease and reinforces the importance of requesting focused testing for Powassan Virus in patients from an endemic area with a clinically compatible syndrome.
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http://dx.doi.org/10.1016/j.idcr.2018.03.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6010959PMC
March 2018

Prognostic value of contrast enhancement and FLAIR for survival in newly diagnosed glioblastoma treated with and without bevacizumab: results from ACRIN 6686.

Neuro Oncol 2018 09;20(10):1400-1410

Department of Radiology, Duke University Medical Center, Durham, North Carolina.

Background: ACRIN 6686/RTOG 0825 was a phase III trial of conventional chemoradiation plus adjuvant temozolomide with bevacizumab or without (placebo) in newly diagnosed glioblastoma. This study investigated whether changes in contrast-enhancing and fluid attenuated inversion recovery (FLAIR)-hyperintense tumor assessed by central reading prognosticate overall survival (OS).

Methods: Two hundred eighty-four patients (171 men; median age 57 y, range 19-79; 159 on bevacizumab) had MRI at post-op (baseline) and pre-cycle 4 of adjuvant temozolomide (22 wk post chemoradiation initiation). Four central readers measured bidimensional lesion enhancement (2D-T1) and FLAIR hyperintensity at both time points. Changes from baseline to pre-cycle 4 for both markers were dichotomized (increasing vs non-increasing). Cox proportional hazards model and Kaplan-Meier survival estimates were used for inference.

Results: Adjusting for treatment, increasing 2D-T1 (n = 262, hazard ratio [HR] = 2.07, 95% CI: 1.48-2.91, P < 0.0001) and FLAIR (n = 273, HR = 1.75, 95% CI: 1.26-2.41, P = 0.0008) significantly predicted worse OS. Median OS (days) was significantly shorter for patients with increasing versus non-increasing 2D-T1 for both bevacizumab (443 vs 535, P = 0.004) and placebo (526 vs 887, P = 0.001). Median OS was significantly shorter for patients with increasing versus non-increasing FLAIR for placebo (595 vs 872, P = 0.001), and trended similarly for bevacizumab (499 vs 535, P = 0.0935). Adjusting for 2D-T1 and treatment, increasing FLAIR represented significantly higher risk for death (HR = 1.59 [1.11-2.26], P = 0.01).

Conclusion: Increased 2D-T1 significantly predicts worse OS in both treatment groups, implying absence of a substantial proportion of pseudoprogression 22 weeks after initiation of standard therapy. FLAIR adds value beyond 2D-T1 in predicting OS, potentially addressing the pseudoresponse effect by substratifying bevacizumab-treated patients with non-increasing 2D-T1.
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http://dx.doi.org/10.1093/neuonc/noy049DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6120359PMC
September 2018

A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials.

Tomography 2017 Mar;3(1):41-49

Department of Imaging Research, Barrow Neurological Institute, Phoenix, Arizona.

The standardization and broad-scale integration of dynamic susceptibility contrast (DSC)-magnetic resonance imaging (MRI) have been confounded by a lack of consensus on DSC-MRI methodology for preventing potential relative cerebral blood volume inaccuracies, including the choice of acquisition protocols and postprocessing algorithms. Therefore, we developed a digital reference object (DRO), using physiological and kinetic parameters derived from in vivo data, unique voxel-wise 3-dimensional tissue structures, and a validated MRI signal computational approach, aimed at validating image acquisition and analysis methods for accurately measuring relative cerebral blood volume in glioblastomas. To achieve DSC-MRI signals representative of the temporal characteristics, magnitude, and distribution of contrast agent-induced T and changes observed across multiple glioblastomas, the DRO's input parameters were trained using DSC-MRI data from 23 glioblastomas (>40 000 voxels). The DRO's ability to produce reliable signals for combinations of pulse sequence parameters and contrast agent dosing schemes unlike those in the training data set was validated by comparison with in vivo dual-echo DSC-MRI data acquired in a separate cohort of patients with glioblastomas. Representative applications of the DRO are presented, including the selection of DSC-MRI acquisition and postprocessing methods that optimize CBV accuracy, determination of the impact of DSC-MRI methodology choices on sample size requirements, and the assessment of treatment response in clinical glioblastoma trials.
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http://dx.doi.org/10.18383/j.tom.2016.00286DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5454781PMC
March 2017

Pseudoprogression, radionecrosis, inflammation or true tumor progression? challenges associated with glioblastoma response assessment in an evolving therapeutic landscape.

J Neurooncol 2017 Sep 5;134(3):495-504. Epub 2017 Apr 5.

Department of Radiology, Mayo Clinic, Rochester, MN, USA.

The wide variety of treatment options that exist for glioblastoma, including surgery, ionizing radiation, anti-neoplastic chemotherapies, anti-angiogenic therapies, and active or passive immunotherapies, all may alter aspects of vascular permeability within the tumor and/or normal parenchyma. These alterations manifest as changes in the degree of contrast enhancement or T2-weighted signal hyperintensity on standard anatomic MRI scans, posing a potential challenge for accurate radiographic response assessment for identifying anti-tumor effects. The current review highlights the challenges that remain in differentiating true disease progression from changes due to radiation therapy, including pseudoprogression and radionecrosis, as well as immune or inflammatory changes that may occur as either an undesired result of cytotoxic therapy or as a desired consequence of immunotherapies.
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http://dx.doi.org/10.1007/s11060-017-2375-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7893814PMC
September 2017

Toxoplasmosis versus lymphoma: Cerebral lesion characterization using DSC-MRI revisited.

Clin Neurol Neurosurg 2017 Jan 2;152:84-89. Epub 2016 Dec 2.

Rhode Island Hospital, Department of Diagnostic Imaging, 593 Eddy Street, Providence, RI, 02903, United States; The Warren Alpert Medical School of Brown University, 222 Richmond Street, Providence, RI, 02903, United States. Electronic address:

Objective: CNS toxoplasmosis and lymphoma are often indistinguishable by conventional contrast-enhanced MRI. There is limited literature on the diagnostic efficacy of dynamic susceptibility contrast (DSC) MRI for differentiating these entities. This study assesses the clinical utility of relative cerebral blood volume (rCBV) for making a diagnosis and determines rCBV thresholds for differentiation using contemporary DSC-MRI.

Patients And Methods: Thirteen patients with 25 lesions (13 toxoplasmosis and 12 lymphoma) and pre-treatment DSC-MRI were identified retrospectively. Volumetric regions of interest of segmented enhancement were used to extract mean rCBV normalized to normal-appearing white matter for each lesion. We compared average mean rCBV between all toxoplasmosis and lymphoma lesions using a general mixed model. Three models were also compared for evaluating rCBV-based disease status in each patient: 1) mean rCBV of each lesion using a generalized estimating equation, 2) volume-weighted mean rCBV, and 3) maximum mean rCBV of all lesions using logistic regression.

Results: The average mean rCBV for all toxoplasmosis lesions was 0.98 (95% CI 0.55-1.41) compared to 2.07 (95% CI 1.71-2.43) for all lymphoma lesions, a significant difference (1.09, 95% CI 0.53-1.65, p=0.0013). For the three models used to evaluate rCBV-based disease status in each patient, a significant relationship was observed, with an optimal rCBV threshold of approximately 1.5 for distinguishing lymphoma from toxoplasmosis in each model.

Conclusion: RCBV derived from contemporary DSC-MRI is helpful for distinguishing between cerebral toxoplasmosis and cerebral lymphoma on an individual patient basis and may facilitate more timely initiation of appropriate directed therapy.
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http://dx.doi.org/10.1016/j.clineuro.2016.11.023DOI Listing
January 2017

Dynamic Susceptibility Contrast MR Imaging in Glioma: Review of Current Clinical Practice.

Magn Reson Imaging Clin N Am 2016 Nov 14;24(4):649-670. Epub 2016 Sep 14.

Department of Radiological Sciences, David Geffen School of Medicine at UCLA, 757 Westwood Plaza, 1621 East, Los Angeles, CA 90095, USA.

Dynamic susceptibility contrast (DSC) MR imaging, a perfusion-weighted MR imaging technique typically used in neuro-oncologic applications for estimating the relative cerebral blood volume within brain tumors, has demonstrated much potential for determining prognosis, predicting therapeutic response, and assessing early treatment response of gliomas. This review highlights recent developments using DSC-MR imaging and emphasizes the need for technical standardization and validation in prospective studies in order for this technique to become incorporated into standard-of-care imaging for patients with brain tumors.
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http://dx.doi.org/10.1016/j.mric.2016.06.005DOI Listing
November 2016

Management of Craniosynostosis at an Advanced Age: Controversies, Clinical Findings, and Surgical Treatment.

J Craniofac Surg 2016 Jul;27(5):e435-41

*Warren Alpert Medical School of Brown University †Department of Neurosurgery ‡Division of Ophthalmology, Warren Alpert Medical School of Brown University, Rhode Island Hospital and Hasbro Children's Hospital §Department of Diagnostic Imaging, Rhode Island Hospital and Warren Alpert Medical School of Brown University ||Division of Plastic Surgery, Mount Auburn Hospital, Cambridge, MA.

Background: The natural history of unrepaired craniosynostosis is not well defined. Delayed surgical intervention carries greater risk of postoperative complications and its functional benefits for older patients are poorly characterized. The authors reviewed patients in whom children presented beyond 1 year of age to better understand the natural history of craniosynostosis, and the risk-benefit relationship for delayed reconstruction.

Methods: After institutional IRB approval the authors conducted a retrospective review of patients who presented after 1 year of age with craniosynostosis. Type of craniosynostosis, age at evaluation, medical history, surgical findings, developmental abnormalities, ophthalmologic findings, and clinical course were reviewed.

Results: Ten patients with delayed presentation for craniosynostosis were identified. The mean age at presentation was 6.8 years ± 4.2 years (range, 3-17 years). Seven of 10 patients presented with developmental delay. Five patients presented with debilitating headaches. Five patients presented with comorbid Chiari malformations, 3 of whom required surgical decompression. Two patients had papilledema. Four patients underwent intracranial pressure monitoring, with elevated pressures found in 3 patients. Six patients underwent delayed cranial vault remodeling. There were no peri- or postoperative complications, including infection or residual bony defects, in those undergoing delayed operation.

Conclusions: Children who present in a delayed fashion with unrepaired craniosynostosis have high rates of debilitating headaches, developmental delays, head shape anomalies, and Chiari malformation. Five patients reporting preoperative headaches noted subjective improvements in headaches following delayed operation. Cranial reconstruction can be safely performed at an older age and is appropriate to consider in carefully selected patients for aesthetic and/or functional concerns.
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http://dx.doi.org/10.1097/SCS.0000000000002725DOI Listing
July 2016

Bidirectional Contrast agent leakage correction of dynamic susceptibility contrast (DSC)-MRI improves cerebral blood volume estimation and survival prediction in recurrent glioblastoma treated with bevacizumab.

J Magn Reson Imaging 2016 11 12;44(5):1229-1237. Epub 2016 Mar 12.

UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA.

Purpose: To evaluate a leakage correction algorithm for T and T2* artifacts arising from contrast agent extravasation in dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) that accounts for bidirectional contrast agent flux and compare relative cerebral blood volume (CBV) estimates and overall survival (OS) stratification from this model to those made with the unidirectional and uncorrected models in patients with recurrent glioblastoma (GBM).

Materials And Methods: We determined median rCBV within contrast-enhancing tumor before and after bevacizumab treatment in patients (75 scans on 1.5T, 19 scans on 3.0T) with recurrent GBM without leakage correction and with application of the unidirectional and bidirectional leakage correction algorithms to determine whether rCBV stratifies OS.

Results: Decreased post-bevacizumab rCBV from baseline using the bidirectional leakage correction algorithm significantly correlated with longer OS (Cox, P = 0.01), whereas rCBV change using the unidirectional model (P = 0.43) or the uncorrected rCBV values (P = 0.28) did not. Estimates of rCBV computed with the two leakage correction algorithms differed on average by 14.9%.

Conclusion: Accounting for T and T2* leakage contamination in DSC-MRI using a two-compartment, bidirectional rather than unidirectional exchange model might improve post-bevacizumab survival stratification in patients with recurrent GBM. J. Magn. Reson. Imaging 2016;44:1229-1237.
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http://dx.doi.org/10.1002/jmri.25227DOI Listing
November 2016

Physiologic MRI for assessment of response to therapy and prognosis in glioblastoma.

Neuro Oncol 2016 Apr 12;18(4):467-78. Epub 2015 Sep 12.

Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, California (M.S.S.); Department of Diagnostic Imaging, Rhode Island Hospital and Alpert Medical School of Brown University, Providence, Rhode Island (J.L.B.); Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California (W.B.P.).

Aside from bidimensional measurements from conventional contrast-enhanced MRI, there are no validated or FDA-qualified imaging biomarkers for high-grade gliomas. However, advanced functional MRI techniques, including perfusion- and diffusion-weighted MRI, have demonstrated much potential for determining prognosis, predicting therapeutic response, and assessing early treatment response. They may also prove useful for differentiating pseudoprogression from true progression after temozolomide chemoradiation and pseudoresponse from true response after anti-angiogenic therapy. This review will highlight recent developments using these techniques and emphasize the need for technical standardization and validation in prospective studies in order for these methods to become incorporated into standard-of-care imaging for brain tumor patients.
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http://dx.doi.org/10.1093/neuonc/nov179DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4799679PMC
April 2016

Response Assessment and Magnetic Resonance Imaging Issues for Clinical Trials Involving High-Grade Gliomas.

Top Magn Reson Imaging 2015 Jun;24(3):127-36

From the *Department of Diagnostic Imaging, Rhode Island Hospital; and †Alpert Medical School of Brown University, Providence, RI; and ‡Departments of Radiological Sciences and Biomedical Physics, and UCLA Neuro-Oncology Program, David Geffen School of Medicine at UCLA; and §Department of Bioengineering, Henri Samueli School of Engineering and Applied Sciences at UCLA, Los Angeles, CA.

There exist multiple challenges associated with the current response assessment criteria for high-grade gliomas, including the uncertain role of changes in nonenhancing T2 hyperintensity, and the phenomena of pseudoresponse and pseudoprogression in the setting of antiangiogenic and chemoradiation therapies, respectively. Advanced physiological magnetic resonance imaging (MRI), including diffusion and perfusion (dynamic susceptibility contrast MRI and dynamic contrast-enhanced MRI) sensitive techniques for overcoming response assessment challenges, has been proposed, with their own potential advantages and inherent shortcomings. Measurement variability exists for conventional and advanced MRI techniques, necessitating the standardization of image acquisition parameters in order to establish the utility of these imaging methods in multicenter trials for high-grade gliomas. This review chapter highlights the important features of MRI in clinical brain tumor trials, focusing on the current state of response assessment in brain tumors, advanced imaging techniques that may provide additional value for determining response, and imaging issues to be considered for multicenter trials.
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http://dx.doi.org/10.1097/RMR.0000000000000054DOI Listing
June 2015

Diffusion MRI quality control and functional diffusion map results in ACRIN 6677/RTOG 0625: a multicenter, randomized, phase II trial of bevacizumab and chemotherapy in recurrent glioblastoma.

Int J Oncol 2015 May 11;46(5):1883-92. Epub 2015 Feb 11.

Department of Radiology, Duke University Medical Center, Durham, NC, USA.

Functional diffusion mapping (fDM) is a cancer imaging technique that quantifies voxelwise changes in apparent diffusion coefficient (ADC). Previous studies have shown value of fDMs in bevacizumab therapy for recurrent glioblastoma multiforme (GBM). The aim of the present study was to implement explicit criteria for diffusion MRI quality control and independently evaluate fDM performance in a multicenter clinical trial (RTOG 0625/ACRIN 6677). A total of 123 patients were enrolled in the current multicenter trial and signed institutional review board-approved informed consent at their respective institutions. MRI was acquired prior to and 8 weeks following therapy. A 5-point QC scoring system was used to evaluate DWI quality. fDM performance was evaluated according to the correlation of these metrics with PFS and OS at the first follow-up time-point. Results showed ADC variability of 7.3% in NAWM and 10.5% in CSF. A total of 68% of patients had usable DWI data and 47% of patients had high quality DWI data when also excluding patients that progressed before the first follow-up. fDM performance was improved by using only the highest quality DWI. High pre-treatment contrast enhancing tumor volume was associated with shorter PFS and OS. A high volume fraction of increasing ADC after therapy was associated with shorter PFS, while a high volume fraction of decreasing ADC was associated with shorter OS. In summary, DWI in multicenter trials are currently of limited value due to image quality. Improvements in consistency of image quality in multicenter trials are necessary for further advancement of DWI biomarkers.
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http://dx.doi.org/10.3892/ijo.2015.2891DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4383029PMC
May 2015

Dynamic susceptibility contrast MRI measures of relative cerebral blood volume as a prognostic marker for overall survival in recurrent glioblastoma: results from the ACRIN 6677/RTOG 0625 multicenter trial.

Neuro Oncol 2015 Aug 2;17(8):1148-56. Epub 2015 Feb 2.

Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin (K.M.S., M.P.); Department of Biostatistics and Center for Statistical Sciences, Brown University, Providence, Rhode Island (Z.Z., B.S.S.); Department of Neuro-Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas (M.R.G.); Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts (A.G.S.); Department of Radiology, Duke University Medical Center, Durham, North Carolina (D.P.B.); Department of Diagnostic Imaging, Rhode Island Hospital, Providence, Rhode Island (J.L.B.); Alpert Medical School of Brown University, Providence, Rhode Island (J.L.B.).

Background: The study goal was to determine whether changes in relative cerebral blood volume (rCBV) derived from dynamic susceptibility contrast (DSC) MRI are predictive of overall survival (OS) in patients with recurrent glioblastoma multiforme (GBM) when measured 2, 8, and 16 weeks after treatment initiation.

Methods: Patients with recurrent GBM (37/123) enrolled in ACRIN 6677/RTOG 0625, a multicenter, randomized, phase II trial of bevacizumab with irinotecan or temozolomide, consented to DSC-MRI plus conventional MRI, 21 with DSC-MRI at baseline and at least 1 postbaseline scan. Contrast-enhancing regions of interest were determined semi-automatically using pre- and postcontrast T1-weighted images. Mean tumor rCBV normalized to white matter (nRCBV) and standardized rCBV (sRCBV) were determined for these regions of interest. The OS rates for patients with positive versus negative changes from baseline in nRCBV and sRCBV were compared using Wilcoxon rank-sum and Kaplan-Meier survival estimates with log-rank tests.

Results: Patients surviving at least 1 year (OS-1) had significantly larger decreases in nRCBV at week 2 (P = .0451) and sRCBV at week 16 (P = .014). Receiver operating characteristic analysis found the percent changes of nRCBV and sRCBV at week 2 and sRCBV at week 16, but not rCBV data at week 8, to be good prognostic markers for OS-1. Patients with positive change from baseline rCBV had significantly shorter OS than those with negative change at both week 2 and week 16 (P = .0015 and P = .0067 for nRCBV and P = .0251 and P = .0004 for sRCBV, respectively).

Conclusions: Early decreases in rCBV are predictive of improved survival in patients with recurrent GBM treated with bevacizumab.
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http://dx.doi.org/10.1093/neuonc/nou364DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4490871PMC
August 2015

Longitudinal DSC-MRI for Distinguishing Tumor Recurrence From Pseudoprogression in Patients With a High-grade Glioma.

Am J Clin Oncol 2017 Jun;40(3):228-234

*Department of Diagnostic Imaging Divisions of ¶Neuro-Oncology #Hematology/Oncology, Rhode Island Hospital †Warren Alpert Medical School, Brown University, Providence, RI Departments of ‡Radiological Sciences §Biomedical Physics, David Geffen School of Medicine at UCLA ∥Department of Bioengineering, Henry Samueli School of Engineering and Applied Science at UCLA, Los Angeles, CA.

Objective: For patients with high-grade glioma on clinical trials it is important to accurately assess time of disease progression. However, differentiation between pseudoprogression (PsP) and progressive disease (PD) is unreliable with standard magnetic resonance imaging (MRI) techniques. Dynamic susceptibility contrast perfusion MRI (DSC-MRI) can measure relative cerebral blood volume (rCBV) and may help distinguish PsP from PD.

Methods: A subset of patients with high-grade glioma on a phase II clinical trial with temozolomide, paclitaxel poliglumex, and concurrent radiation were assessed. Nine patients (3 grade III, 6 grade IV), with a total of 19 enhancing lesions demonstrating progressive enhancement (≥25% increase from nadir) on postchemoradiation conventional contrast-enhanced MRI, had serial DSC-MRI. Mean leakage-corrected rCBV within enhancing lesions was computed for all postchemoradiation time points.

Results: Of the 19 progressively enhancing lesions, 10 were classified as PsP and 9 as PD by biopsy/surgery or serial enhancement patterns during interval follow-up MRI. Mean rCBV at initial progressive enhancement did not differ significantly between PsP and PD (2.35 vs. 2.17; P=0.67). However, change in rCBV at first subsequent follow-up (-0.84 vs. 0.84; P=0.001) and the overall linear trend in rCBV after initial progressive enhancement (negative vs. positive slope; P=0.04) differed significantly between PsP and PD.

Conclusions: Longitudinal trends in rCBV may be more useful than absolute rCBV in distinguishing PsP from PD in chemoradiation-treated high-grade gliomas with DSC-MRI. Further studies of DSC-MRI in high-grade glioma as a potential technique for distinguishing PsP from PD are indicated.
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http://dx.doi.org/10.1097/COC.0000000000000156DOI Listing
June 2017

Ipilimumab treatment associated pituitary hypophysitis: clinical presentation and imaging diagnosis.

Clin Neurol Neurosurg 2014 Oct 29;125:125-30. Epub 2014 Jul 29.

Department of Diagnostic Imaging, Rhode Island Hospital, Alpert Medical School of Brown University, 593 Eddy Street, Providence 02903, USA. Electronic address:

Ipilimumab is an immunomodulating drug for use in treatment of unresectable or metastatic melanoma with autoimmune lymphocytic hypophysitis as a reported complication. We describe three recent cases of ipilimumab associated autoimmune hypophysitis (IAH) at our institution, and provide a selected literature review showing its variable clinical presentation, imaging appearance and treatment in order to expedite early and appropriate IAH management. Patients had variable clinical presentation of hypophysitis, including headache, fatigue, visual changes, endocrinopathy, and/or hyponatremia. Contrast enhanced MRI showed symmetric pituitary gland and stalk enlargement in all of our cases and received a presumptive diagnosis of IAH. Following cessation of therapy and treatment there was normalization of pituitary morphology at follow-up MRI and return to clinical baseline. Varying clinical presentation can complicate the diagnosis of lymphocytic hypophysitis. One must be cognizant of its overall clinical and radiologic picture in patients receiving ipilimumab, now commonly used for the treatment of metastatic melanoma.
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http://dx.doi.org/10.1016/j.clineuro.2014.06.011DOI Listing
October 2014