Davis C. Woodworth

Recurrent Glioblastoma Treated with Bevacizumab: Contrast-enhanced T1-weighted Subtraction Maps Improve Tumor Delineation and Aid Prediction of Survival in a Multicenter Clinical Trial

PURPOSE To compare the capability to aid prediction of clinical outcome measures, including progression-free survival (PFS) and overall survival (OS), between volumetric estimates from contrast material-enhanced (CE) T1-weighted subtraction maps and traditional segmentation in a randomized multicenter clinical trial of recurrent glioblastoma (GBM) patients treated with bevacizumab. MATERIALS AND METHODS All patients participating in this study signed institutional review board-approved informed consent at their respective institutions prior to enrolling in the multicenter clinical trial. One-hundred sixty patients with recurrent GBM enrolled as part of a HIPAA-compliant, multicenter clinical trial (AVF3708 g, BRAIN trial). Contrast-enhancing tumor volumes and change in volumes as a response to therapy were quantified by using either conventional segmentation or CE T1-weighted subtraction maps created by voxel-by-voxel subtraction of intensity-normalized nonenhanced T1-weighted images from CE T1-weighted images. These volumes were then tested as predictors of PFS and OS by using log-rank univariate analysis, the multivariate Cox proportional hazards regression model, and receiver operating characteristic analysis. RESULTS Use of CE T1-weighted subtraction maps qualitatively improved visualization and improved quantification of tumor volume after bevacizumab treatment. Significant trends between the volume of tumor and change in tumor volume after therapy on CE T1-weighted subtraction maps were found for both PFS and OS (pretreatment volume < 15 cm(3), P < .003; posttreatment volume < 7.5 cm(3), P < .05; percentage change in volume > 25%, P = .004 for PFS and P = .053 for OS). CE T1-weighted subtraction maps were significantly better at aiding prediction of 6-month PFS and 12-month OS compared with conventional segmentation by using receiver operating characteristic analysis (P < .05). CONCLUSION Use of CE T1-weighted subtraction maps improved visualization and aided better prediction of patient survival in recurrent GBM treated with bevacizumab compared with conventional segmentation of CE T1-weighted images. Clinical trial registration no. NCT00345163. Online supplemental material is available for this article.

Pretreatment ADC Histogram Analysis Is a Predictive Imaging Biomarker for Bevacizumab Treatment but Not Chemotherapy in Recurrent Glioblastoma

BACKGROUND AND PURPOSE: Pre-treatment ADC characteristics have been shown to predict response to bevacizumab in recurrent glioblastoma multiforme. However, no studies have examined whether ADC characteristics are specific to this particular treatment. The purpose of the current study was to determine whether ADC histogram analysis is a bevacizumab-specific or treatment-independent biomarker of treatment response in recurrent glioblastoma multiforme. MATERIALS AND METHODS: Eighty-nine bevacizumab-treated and 43 chemotherapy-treated recurrent glioblastoma multiformes never exposed to bevacizumab were included in this study. In all patients, ADC values in contrast-enhancing ROIs from MR imaging examinations performed at the time of recurrence, immediately before commencement of treatment for recurrence, were extracted and the resulting histogram was fitted to a mixed model with a double Gaussian distribution. Mean ADC in the lower Gaussian curve was used as the primary biomarker of interest. The Cox proportional hazards model and log-rank tests were used for survival analysis. RESULTS: Cox multivariate regression analysis accounting for the interaction between bevacizumab- and non-bevacizumab-treated patients suggested that the ability of the lower Gaussian curve to predict survival is dependent on treatment (progression-free survival, P = .045; overall survival, P = .003). Patients with bevacizumab-treated recurrent glioblastoma multiforme with a pretreatment lower Gaussian curve > 1.2 μm2/ms had a significantly longer progression-free survival and overall survival compared with bevacizumab-treated patients with a lower Gaussian curve < 1.2 μm2/ms. No differences in progression-free survival or overall survival were observed in the chemotherapy-treated cohort. Bevacizumab-treated patients with a mean lower Gaussian curve > 1.2 μm2/ms had a significantly longer progression-free survival and overall survival compared with chemotherapy-treated patients. CONCLUSIONS: The mean lower Gaussian curve from ADC histogram analysis is a predictive imaging biomarker for bevacizumab-treated, not chemotherapy-treated, recurrent glioblastoma multiforme. Patients with recurrent glioblastoma multiforme with a mean lower Gaussian curve > 1.2 μm2/ms have a survival advantage when treated with bevacizumab.

Increased sensitivity to radiochemotherapy in IDH1 mutant glioblastoma as demonstrated by serial quantitative MR volumetry

BACKGROUND Isocitrate dehydrogenase 1 (IDH1) mutations have been linked to favorable outcomes in patients with glioblastoma multiforme (GBM). Recent in vitro experiments suggest that IDH1 mutation sensitizes tumors to radiation damage. We hypothesized that radiographic treatment response would be significantly different between IDH1 mutant versus wild-type GBMs after radiotherapy (RT) and concurrent temozolomide (TMZ). METHODS A total of 39 newly diagnosed GBM patients with known IDH1 mutational status (10 IDH1 mutants), who followed standard therapy and had regular post-contrast T1W (T1+C) and T2W/ fluid-attenuated inversion recovery (FLAIR) images in the 6-month period after starting RT, were enrolled. The volume of contrast-enhancing and FLAIR hyperintensity were calculated from each scan. Linear and polynomial regression techniques were used to estimate the rate of change and temporal patterns in tumor volumes. RESULTS IDH1 mutant GBMs demonstrated a favorable response to RT/TMZ in the study period, as demonstrated by 10 of 10 mutants showing radiographic response (decreasing V(T1+C)), compared with 13 of 29 wild-types (P < .001). During the study period, V(T1+C) and V(FLAIR) changed at -3.6% per week and +0.6% per week in IDH1 mutant tumors, respectively, as compared with +0.8% per week and +5.2% per week in IDH1 wild-type tumors (P = .0076 and P = .0118, respectively). Amongst the radiographic responders, IDH1 mutant GBMs still demonstrated significant progression-free and overall survival benefit. Aggregated tumor kinetics by group showed significant lower rate in IDH1 mutant GBMs in specific periods: >105 days for V(FLAIR) and 95-120 and >150 days for V(T1+C) from starting RT/TMZ. CONCLUSIONS The current study supports the hypothesis that IDH1 mutant GBMs are more sensitive to radiochemotherapy than IDH1 wild-type GBMs.

Patterns of brain structural connectivity differentiate normal weight from overweight subjects

Background Alterations in the hedonic component of ingestive behaviors have been implicated as a possible risk factor in the pathophysiology of overweight and obese individuals. Neuroimaging evidence from individuals with increasing body mass index suggests structural, functional, and neurochemical alterations in the extended reward network and associated networks. Aim To apply a multivariate pattern analysis to distinguish normal weight and overweight subjects based on gray and white-matter measurements. Methods Structural images (N = 120, overweight N = 63) and diffusion tensor images (DTI) (N = 60, overweight N = 30) were obtained from healthy control subjects. For the total sample the mean age for the overweight group (females = 32, males = 31) was 28.77 years (SD = 9.76) and for the normal weight group (females = 32, males = 25) was 27.13 years (SD = 9.62). Regional segmentation and parcellation of the brain images was performed using Freesurfer. Deterministic tractography was performed to measure the normalized fiber density between regions. A multivariate pattern analysis approach was used to examine whether brain measures can distinguish overweight from normal weight individuals. Results 1. White-matter classification: The classification algorithm, based on 2 signatures with 17 regional connections, achieved 97% accuracy in discriminating overweight individuals from normal weight individuals. For both brain signatures, greater connectivity as indexed by increased fiber density was observed in overweight compared to normal weight between the reward network regions and regions of the executive control, emotional arousal, and somatosensory networks. In contrast, the opposite pattern (decreased fiber density) was found between ventromedial prefrontal cortex and the anterior insula, and between thalamus and executive control network regions. 2. Gray-matter classification: The classification algorithm, based on 2 signatures with 42 morphological features, achieved 69% accuracy in discriminating overweight from normal weight. In both brain signatures regions of the reward, salience, executive control and emotional arousal networks were associated with lower morphological values in overweight individuals compared to normal weight individuals, while the opposite pattern was seen for regions of the somatosensory network. Conclusions 1. An increased BMI (i.e., overweight subjects) is associated with distinct changes in gray-matter and fiber density of the brain. 2. Classification algorithms based on white-matter connectivity involving regions of the reward and associated networks can identify specific targets for mechanistic studies and future drug development aimed at abnormal ingestive behavior and in overweight/obesity.

Unique Microstructural Changes in the Brain Associated with Urological Chronic Pelvic Pain Syndrome (UCPPS) Revealed by Diffusion Tensor MRI, Super-Resolution Track Density Imaging, and Statistical Parameter Mapping: A MAPP Network Neuroimaging Study

Studies have suggested chronic pain syndromes are associated with neural reorganization in specific regions associated with perception, processing, and integration of pain. Urological chronic pelvic pain syndrome (UCPPS) represents a collection of pain syndromes characterized by pelvic pain, namely Chronic Prostatitis/Chronic Pelvic Pain Syndrome (CP/CPPS) and Interstitial Cystitis/Painful Bladder Syndrome (IC/PBS), that are both poorly understood in their pathophysiology, and treated ineffectively. We hypothesized patients with UCPPS may have microstructural differences in the brain compared with healthy control subjects (HCs), as well as patients with irritable bowel syndrome (IBS), a common gastrointestinal pain disorder. In the current study we performed population-based voxel-wise DTI and super-resolution track density imaging (TDI) in a large, two-center sample of phenotyped patients from the multicenter cohort with UCPPS (N = 45), IBS (N = 39), and HCs (N = 56) as part of the MAPP Research Network. Compared with HCs, UCPPS patients had lower fractional anisotropy (FA), lower generalized anisotropy (GA), lower track density, and higher mean diffusivity (MD) in brain regions commonly associated with perception and integration of pain information. Results also showed significant differences in specific anatomical regions in UCPPS patients when compared with IBS patients, consistent with microstructural alterations specific to UCPPS. While IBS patients showed clear sex related differences in FA, MD, GA, and track density consistent with previous reports, few such differences were observed in UCPPS patients. Heat maps illustrating the correlation between specific regions of interest and various pain and urinary symptom scores showed clustering of significant associations along the cortico-basal ganglia-thalamic-cortical loop associated with pain integration, modulation, and perception. Together, results suggest patients with UCPPS have extensive microstructural differences within the brain, many specific to syndrome UCPPS versus IBS, that appear to be localized to regions associated with perception and integration of sensory information and pain modulation, and seem to be a consequence of longstanding pain.

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

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.

Baseline pretreatment contrast enhancing tumor volume including central necrosis is a prognostic factor in recurrent glioblastoma: evidence from single- and multicenter trials

Background. The prognostic significance of baseline contrast enhancing tumor prior to second- or third-line therapy in recurrent glioblastoma (GBM) for overall survival (OS) remains controversial, particularly in the context of repeated surgical resection and/or use of anti-angiogenic therapy. In the current study, we examined recurrent GBM patients from both single and multicenter clinical trials to test whether baseline enhancing tumor volume, including central necrosis, is a significant prognostic factor for OS in recurrent GBM. Methods. Included were 497 patients with recurrent GBM from 4 data sources: 2 single-center sites (University of Toronto, University of California Los Angeles) and 2 phase II multicenter trials (AVF3708G, Bevacizumab ± Irinotecan, NCT00345163; XL184-201, Cabozantinib, NCT00704288). T1 subtraction maps were used to define volume of contrast enhancing tumor, including central necrosis. Cox multivariable and univariate analyses were used to evaluate the relationship between tumor volume prior to second- or third-line therapy and OS. Results. Both continuous measures of baseline tumor volume and tumors dichotomized into large (≥15cc) and small (<15cc) tumors were significant predictors of OS (P<.0001), independently of age and treatment. Univariate analysis demonstrated significant OS differences (P<.05) between large (≥15cc) and small (<15cc) tumors in patients under all therapeutic scenarios. Only patients treated with cabozantinib who previously failed anti-angiogenic therapy did not show an OS dependence on baseline tumor volume. Conclusions. Baseline tumor volume is a significant prognostic factor in recurrent GBM. Clinical trial treatment arms must have a balanced distribution of tumor size, and tumor size should be considered when interpreting therapeutic efficacy.

Correlation between degree of subvoxel spinal cord compression measured with super-resolution tract density imaging and neurological impairment in cervical spondylotic myelopathy

OBJECT The purpose of this study was to explore the use of super-resolution tract density images derived from probabilistic diffusion tensor imaging (DTI) tractography of the spinal cord as an imaging surrogate for microstructural integrity and functional impairment in patients with cervical spondylosis. METHODS Structural MRI and DTI images were collected for 27 patients with cervical spondylosis with (n= 21) and without (n= 6) functional impairment as defined by the modified Japanese Orthopaedic Association Scale (mJOA). DTI was performed axially through the site of compression in a total of 20 directions with 10 averages. Probabilistic tractography was performed at 0.5-mm isotropic spatial resolution using the streamline technique combined with constrained spherical deconvolution. The following measurements were calculated for each patient: maximum tract density at the site of compression, average tract density in rostral normal-appearing spinal cord, and the ratio of maximum density to normal density. RESULTS Compared with normal tissue, the site of compression exhibited elevated fiber tract density in all patients, and a higher fiber tract density was also noted in focal areas at the site of compression in patients with functional impairment. There was a strong negative correlation between maximum tract density and mJOA score (R(2)= 0.6324, p < 0.0001) and the ratio of maximum tract density to normal tract density (R(2)= 0.6647, p < 0.0001). When grouped according to severity of neurological impairment (asymptomatic, mJOA score of 18; mild, mJOA score of 15-17; moderate, mJOA score of 11-14; and severe, mJOA score < 11), the results showed a significant difference in the ratio between severe and both no impairment (p= 0.0009) and any impairment (p= 0.036). A ratio of maximum fiber tract density at the site of compression to fiber tract density at C-2 greater than 1.45 had 82% sensitivity and 70% specificity for identifying patients with moderate to severe impairment (ROC AUC= 0.8882, p= 0.0009). CONCLUSIONS These results support the use of DTI as a surrogate for determining spinal cord integrity in patients with cervical spondylosis. Probabilistic tractography provides spinal cord microstructural information that can help discern clinical status in cervical spondylosis patients with varying degrees of neurological impairment.

Multisite, multimodal neuroimaging of chronic urological pelvic pain: Methodology of the MAPP Research Network

The Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network is an ongoing multi-center collaborative research group established to conduct integrated studies in participants with urologic chronic pelvic pain syndrome (UCPPS). The goal of these investigations is to provide new insights into the etiology, natural history, clinical, demographic and behavioral characteristics, search for new and evaluate candidate biomarkers, systematically test for contributions of infectious agents to symptoms, and conduct animal studies to understand underlying mechanisms for UCPPS. Study participants were enrolled in a one-year observational study and evaluated through a multisite, collaborative neuroimaging study to evaluate the association between UCPPS and brain structure and function. 3D T1-weighted structural images, resting-state fMRI, and high angular resolution diffusion MRI were acquired in five participating MAPP Network sites using 8 separate MRI hardware and software configurations. We describe the neuroimaging methods and procedures used to scan participants, the challenges encountered in obtaining data from multiple sites with different equipment/software, and our efforts to minimize site-to-site variation.

Diffusion MRI phenotypes predict overall survival benefit from anti-VEGF monotherapy in recurrent glioblastoma: Converging evidence from phase II trials

Purpose: Anti-VEGF therapies remain controversial in the treatment of recurrent glioblastoma (GBM). In the current study, we demonstrate that recurrent GBM patients with a specific diffusion MR imaging signature have an overall survival (OS) advantage when treated with cediranib, bevacizumab, cabozantinib, or aflibercept monotherapy at first or second recurrence. These findings were validated using a separate trial comparing bevacizumab with lomustine. Experimental Design: Patients with recurrent GBM and diffusion MRI from the monotherapy arms of 5 separate phase II clinical trials were included: (i) cediranib (NCT00035656); (ii) bevacizumab (BRAIN Trial, AVF3708g; NCT00345163); (iii) cabozantinib (XL184-201; NCT00704288); (iv) aflibercept (VEGF Trap; NCT00369590); and (v) bevacizumab or lomustine (BELOB; NTR1929). Apparent diffusion coefficient (ADC) histogram analysis was performed prior to therapy to estimate “ADCL,” the mean of the lower ADC distribution. Pretreatment ADCL, enhancing volume, and clinical variables were tested as independent prognostic factors for OS. Results: The coefficient of variance (COV) in double baseline ADCL measurements was 2.5% and did not significantly differ (P = 0.4537). An ADCL threshold of 1.24 μm2/ms produced the largest OS differences between patients (HR ∼ 0.5), and patients with an ADCL > 1.24 μm2/ms had close to double the OS in all anti-VEGF therapeutic scenarios tested. Training and validation data confirmed that baseline ADCL was an independent predictive biomarker for OS in anti-VEGF therapies, but not in lomustine, after accounting for age and baseline enhancing tumor volume. Conclusions: Pretreatment diffusion MRI is a predictive imaging biomarker for OS in patients with recurrent GBM treated with anti-VEGF monotherapy at first or second relapse. Clin Cancer Res; 23(19); 5745–56. ©2017 AACR.