Cerebral Amyloid Angiopathy in Patients with Cognitive Impairment -Cerebrospinal Fluid Biomarkers.

INTRODUCTION: Cerebral amyloid angiopathy (CAA) is characterized by amyloid ß (Aß) deposition in brain vessels, leading to hemorrhagic phenomena and cognitive impairment. Magnetic resonance imaging (MRI)-based criteria allow a diagnosis of probable CAA in vivo, but such a diagnosis cannot predict the eventual development of CAA. METHODS: We conducted a retrospective cohort study of 464 patients with cognitive disorders whose data were included in a brain health biobank. De-identified parameters including sex, age, cognitive score, APOE status and cerebrospinal fluid (CSF) levels of Aß 1-40, Aß 1-42, phosphorylated tau, and total tau were assessed in those with and without CAA. Odds ratios (ORs) and 95% confidence intervals (CIs) were determined. RESULTS: CAA was present in 53 of 464 (11.5%) patients. P-tau level was significantly higher in those with CAA (115 vs 84.3 pg/ml p=0.038). In univariate analyses, the risk of developing CAA was higher with increased age (OR, 1.036; 95% CI: 1.008, 1.064; p = 0.011) and decreased CSF level of Aß 1-40 (OR, 0.685; 95% CI: 0.534, 0.878; p = 0.003). In multivariate analyses, the risk of CAA remained higher with a decreased CSF level of Aß 1-40 (OR, 0.681; 95% CI: 0.531, 0.874; p = 0.003). CONCLUSION: These findings suggest that Aß 1-40 levels in the CSF might be a useful molecular biomarker of CAA in patients with dementia.

Examining degenerative disease adjacent to lumbosacral transitional vertebrae: a retrospective cohort study.

OBJECTIVE: Bertolotti syndrome is a clinical diagnosis given to patients with low-back pain arising from a lumbosacral transitional vertebra (LSTV). While biomechanical studies have demonstrated abnormal torques and range of motion occurring at and above this type of LSTV, the long-term effects of these biomechanical changes on the LSTV adjacent segments are not well understood. This study examined degenerative changes at segments superjacent to the LSTV in patients with Bertolotti syndrome. METHODS: This study involved a retrospective comparison of patients between 2010 and 2020 with an LSTV and chronic back pain (Bertolotti syndrome) and control patients with chronic back pain with no LSTV. The presence of an LSTV was confirmed on imaging, and the caudal-most mobile segment above the LSTV was assessed for degenerative changes. Degenerative changes were assessed by grading the intervertebral disc, facets, degree of spinal stenosis, and spondylolisthesis using well documented grading systems. All computations were performed in R, version 4.1.0. All tests were two-sided, and p values < 0.05 was considered statistically significant. Separate logistic regression analyses were run with the associated dependent variables for each aim, with age at MRI and sex included as covariates. Odds ratios and 95% confidence intervals were computed. RESULTS: A total of 172 patients were included, 101 with Bertolotti syndrome and 71 controls. Control patients consisted of patients with low-back pain but no diagnosis of Bertolotti syndrome or an LSTV. Fifty-six Bertolotti (55.4%) and 27 control (38.0%) patients were female, (p = 0.03). After adjusting for age at MRI and sex, Bertolotti patients had pelvic incidence (PI) that was 9.83° greater than control patients (95% CI 5.15°-14.50°, p < 0.001). Sacral slope was not significantly different between the Bertolotti and control groups (beta estimate 3.10°, 95% CI -1.07° to 7.27°; p = 0.14). Bertolotti patients had 2.69 times higher odds of having a high disc grade at L4-5 (3-4 vs 0-2), compared with control patients (OR 2.69, 95% CI 1.28-5.90; p = 0.01). There were no significant differences between Bertolotti patients and controls for spondylolisthesis, facet grade, or spinal stenosis grade. CONCLUSIONS: Patients with Bertolotti syndrome had a significantly higher PI and were more likely to have adjacent-segment disease (ASD; L4-5) compared with control patients. However, after controlling for age and sex, PI and ASD did not appear to have a significant association within the cohort of Bertolotti patients. The altered biomechanics and kinematics in this condition may be a causative factor in this degeneration, although proof of causation is not possible in this study. This association may warrant closer follow-up protocols for patients being treated for Bertolotti syndrome, but further prospective studies are needed to establish if radiographic parameters can serve as an indicator for biomechanical alterations in vivo.

Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to Characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma.

The concept of tumor field effect implies that cancer is a systemic disease with its impact way beyond the visible tumor confines. For instance, in Glioblastoma (GBM), an aggressive brain tumor, the increase in intracranial pressure due to tumor burden often leads to brain herniation and poor outcomes. Our work is based on the rationale that highly aggressive tumors tend to grow uncontrollably, leading to pronounced biomechanical tissue deformations in the normal parenchyma, which when combined with local morphological differences in the tumor confines on MRI scans, will comprehensively capture tumor field effect. Specifically, we present an integrated MRI-based descriptor, radiomic-Deformation and Textural Heterogeneity (r-DepTH). This descriptor comprises measurements of the subtle perturbations in tissue deformations throughout the surrounding normal parenchyma due to mass effect. This involves non-rigidly aligning the patients' MRI scans to a healthy atlas via diffeomorphic registration. The resulting inverse mapping is used to obtain the deformation field magnitudes in the normal parenchyma. These measurements are then combined with a 3D texture descriptor, Co-occurrence of Local Anisotropic Gradient Orientations (COLLAGE), which captures the morphological heterogeneity and infiltration within the tumor confines, on MRI scans. In this work, we extensively evaluated r-DepTH for survival risk-stratification on a total of 207 GBM cases from 3 different cohorts (Cohort 1 ( n1 = 53 ), Cohort 2 ( n2 = 75 ), and Cohort 3 ( n3 = 79 )), where each of these three cohorts was used as a training set for our model separately, and the other two cohorts were used for testing, independently, for each training experiment. When employing Cohort 1 for training, r-DepTH yielded Concordance indices (C-indices) of 0.7 and 0.65, hazard ratios (HR) and Confidence Intervals (CI) of 10 (6 - 19) and 5 (3 - 8) on Cohorts 2 and 3, respectively. Similarly, training on Cohort 2 yielded C-indices of 0.6 and 0.7, HR and CI of 1 (0.7 - 2) and 3 (2 - 5) on Cohorts 1 and 3, respectively. Finally, training on Cohort 3 yielded C-indices of 0.75 and 0.63, HR and CI of 24 (10 - 57) and 12 (6 - 21) on Cohorts 1 and 2, respectively. Our results show that r-DepTH descriptor may serve as a comprehensive and a robust MRI-based prognostic marker of disease aggressiveness and survival in solid tumors.

Novel MRI deformation-heterogeneity radiomic features are associated with molecular subgroups and overall survival in pediatric medulloblastoma: Preliminary findings from a multi-institutional study.

Introduction: Medulloblastoma (MB) is a malignant, heterogenous brain tumor. Advances in molecular profiling have led to identifying four molecular subgroups of MB (WNT, SHH, Group 3, Group 4), each with distinct clinical behaviors. We hypothesize that (1) aggressive MB tumors, growing heterogeneously, induce pronounced local structural deformations in the surrounding parenchyma, and (b) these local deformations as captured on Gadolinium (Gd)-enhanced-T1w MRI are independently associated with molecular subgroups, as well as overall survival in MB patients. Methods: In this work, a total of 88 MB studies from 2 institutions were analyzed. Following tumor delineation, Gd-T1w scan for every patient was registered to a normal age-specific T1w-MRI template via deformable registration. Following patient-atlas registration, local structural deformations in the brain parenchyma were obtained for every patient by computing statistics from deformation magnitudes obtained from every 5mm annular region, 0 < d < 60 mm, where d is the distance from the tumor infiltrating edge. Results: Multi-class comparison via ANOVA yielded significant differences between deformation magnitudes obtained for Group 3, Group 4, and SHH molecular subgroups, observed up to 60-mm outside the tumor edge. Additionally, Kaplan-Meier survival analysis showed that the local deformation statistics, combined with the current clinical risk-stratification approaches (molecular subgroup information and Chang's classification), could identify significant differences between high-risk and low-risk survival groups, achieving better performance results than using any of these approaches individually. Discussion: These preliminary findings suggest there exists significant association of our tumor-induced deformation descriptor with overall survival in MB, and that there could be an added value in using the proposed radiomic descriptor along with the current risk classification approaches, towards more reliable risk assessment in pediatric MB.

Radiological and Clinical Value of 7T MRI for Evaluating 3T-Visible Lesions in Pharmacoresistant Focal Epilepsies.

Objective: The recent FDA approval of the first 7T MRI scanner for clinical diagnostic use in October 2017 will likely increase the utilization of 7T for epilepsy presurgical evaluation. This study aims at accessing the radiological and clinical value of 7T in patients with pharmacoresistant focal epilepsy and 3T-visible lesions. Methods: Patients with pharmacoresistant focal epilepsy were included if they had a lesion on pre-operative standard-of-care 3T MRI and also a 7T research MRI. An epilepsy protocol was used for the acquisition of the 7T MRI. Prospective visual analysis of 7T MRI was performed by an experienced board-certified neuroradiologist and communicated to the patient management team. The clinical significance of the additional 7T findings was assessed by intracranial EEG (ICEEG) ictal onset, surgical resection, post-operative seizure outcome and histopathology. A subset of lesions were demarked with arrows for subsequent, retrospective comparison between 3T and 7T by 7 neuroradiologists using a set of quantitative scales: lesion presence, conspicuity, boundary, gray-white tissue contrast, artifacts, and the most helpful sequence for diagnosis. Conger's kappa for multiple raters was performed for chance-adjusted agreement statistics. Results: A total of 47 patients were included, with the main pathology types of focal cortical dysplasia (FCD), hippocampal sclerosis, periventricular nodular heterotopia (PVNH), tumor and polymicrogyria (PMG). 7T detected additional smaller lesions in 19% (9/47) of patients, who had extensive abnormalities such as PMG and PVNH; however, these additional findings were not necessarily epileptogenic. 3T-7T comparison by the neuroradiologist team showed that lesion conspicuity and lesion boundary were significantly better at 7T (p < 0.001), particularly for FCD, PVNH and PMG. Chance-adjusted agreement was within the fair range for lesion presence, conspicuity and boundary. Gray-white contrast was significantly improved at 7T (p < 0.001). Significantly more artifacts were encountered at 7T (p < 0.001). Significance: For patients with 3T-visible lesions, 7T MRI may better elucidate the extent of multifocal abnormalities such as PVNH and PMG, providing potential targets to improve ICEEG implantation. Patients with FCD, PVNH and PMG would likely benefit the most from 7T due to improved lesion conspicuity and boundary. Pathologies in the antero-inferior temporal regions likely benefit less due to artifacts.

Sexually dimorphic radiogenomic models identify distinct imaging and biological pathways that are prognostic of overall survival in glioblastoma.

BACKGROUND: Recent epidemiological studies have suggested that sexual dimorphism influences treatment response and prognostic outcome in glioblastoma (GBM). To this end, we sought to (i) identify distinct sex-specific radiomic phenotypes-from tumor subcompartments (peritumoral edema, enhancing tumor, and necrotic core) using pretreatment MRI scans-that are prognostic of overall survival (OS) in GBMs, and (ii) investigate radiogenomic associations of the MRI-based phenotypes with corresponding transcriptomic data, to identify the signaling pathways that drive sex-specific tumor biology and treatment response in GBM. METHODS: In a retrospective setting, 313 GBM patients (male = 196, female = 117) were curated from multiple institutions for radiomic analysis, where 130 were used for training and independently validated on a cohort of 183 patients. For the radiogenomic analysis, 147 GBM patients (male = 94, female = 53) were used, with 125 patients in training and 22 cases for independent validation. RESULTS: Cox regression models of radiomic features from gadolinium T1-weighted MRI allowed for developing more precise prognostic models, when trained separately on male and female cohorts. Our radiogenomic analysis revealed higher expression of Laws energy features that capture spots and ripple-like patterns (representative of increased heterogeneity) from the enhancing tumor region, as well as aggressive biological processes of cell adhesion and angiogenesis to be more enriched in the "high-risk" group of poor OS in the male population. In contrast, higher expressions of Laws energy features (which detect levels and edges) from the necrotic core with significant involvement of immune related signaling pathways was observed in the "low-risk" group of the female population. CONCLUSIONS: Sexually dimorphic radiogenomic models could help risk-stratify GBM patients for personalized treatment decisions.

Tumor Habitat-derived Radiomic Features at Pretreatment MRI That Are Prognostic for Progression-free Survival in Glioblastoma Are Associated with Key Morphologic Attributes at Histopathologic Examination: A Feasibility Study.

PURPOSE: To identify radiomic features extracted from the tumor habitat on routine MR images that are prognostic for progression-free survival (PFS) and to assess their morphologic basis with corresponding histopathologic attributes in glioblastoma (GBM). MATERIALS AND METHODS: In this retrospective study, 156 pretreatment GBM MR images (gadolinium-enhanced T1-weighted, T2-weighted, and fluid-attenuated inversion recovery [FLAIR] images) were curated. Of these 156 images, 122 were used for training (90 from The Cancer Imaging Archive and 32 from the Cleveland Clinic, acquired between December 1, 2011, and May 1, 2018) and 34 were used for validation. The validation set was obtained from the Ivy Glioblastoma Atlas Project database, for which the percentage extent of 11 histologic attributes was available on corresponding histopathologic specimens of the resected tumor. Following expert annotations of the tumor habitat (necrotic core, enhancing tumor, and FLAIR-hyperintense subcompartments), 1008 radiomic descriptors (eg, Haralick texture features, Laws energy features, co-occurrence of local anisotropic gradient orientations [CoLIAGe]) were extracted from the three MRI sequences. The top radiomic features were obtained from each subcompartment in the training set on the basis of their ability to risk-stratify patients according to PFS. These features were then concatenated to create a radiomics risk score (RRS). The RRS was independently validated on a holdout set. In addition, correlations (P < .05) of RRS features were computed, with the percentage extent of the 11 histopathologic attributes, using Spearman correlation analysis. RESULTS: RRS yielded a concordance index of 0.80 on the validation set and constituted radiomic features, including Laws (capture edges, waves, ripple patterns) and CoLIAGe (capture disease heterogeneity) from enhancing tumor and FLAIR hyperintensity. These radiomic features were correlated with histopathologic attributes associated with disease aggressiveness in GBM, particularly tumor infiltration (P = .0044) and hyperplastic blood vessels (P = .0005). CONCLUSION: Preliminary findings demonstrated significant associations of prognostic radiomic features with disease-specific histologic attributes, with implications for risk-stratifying patients with GBM for personalized treatment decisions. Supplemental material is available for this article. © RSNA, 2020.

Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma?-A Feasibility Study.

A significant challenge in Glioblastoma (GBM) management is identifying pseudo-progression (PsP), a benign radiation-induced effect, from tumor recurrence, on routine imaging following conventional treatment. Previous studies have linked tumor lobar presence and laterality to GBM outcomes, suggesting that disease etiology and progression in GBM may be impacted by tumor location. Hence, in this feasibility study, we seek to investigate the following question: Can tumor location on treatment-naïve MRI provide early cues regarding likelihood of a patient developing pseudo-progression vs. tumor recurrence? In this study, 74 pre-treatment Glioblastoma MRI scans with PsP (33) and tumor recurrence (41) were analyzed. First, enhancing lesion on Gd-T1w MRI and peri-lesional hyperintensities on T2w/FLAIR were segmented by experts and then registered to a brain atlas. Using patients from the two phenotypes, we construct two atlases by quantifying frequency of occurrence of enhancing lesion and peri-lesion hyperintensities, by averaging voxel intensities across the population. Analysis of differential involvement was then performed to compute voxel-wise significant differences (p-value < 0.05) across the atlases. Statistically significant clusters were finally mapped to a structural atlas to provide anatomic localization of their location. Our results demonstrate that patients with tumor recurrence showed prominence of their initial tumor in the parietal lobe, while patients with PsP showed a multi-focal distribution of the initial tumor in the frontal and temporal lobes, insula, and putamen. These preliminary results suggest that lateralization of pre-treatment lesions toward certain anatomical areas of the brain may allow to provide early cues regarding assessing likelihood of occurrence of pseudo-progression from tumor recurrence on MRI scans.

Radiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma.

PURPOSE: To (i) create a survival risk score using radiomic features from the tumor habitat on routine MRI to predict progression-free survival (PFS) in glioblastoma and (ii) obtain a biological basis for these prognostic radiomic features, by studying their radiogenomic associations with molecular signaling pathways. EXPERIMENTAL DESIGN: Two hundred three patients with pretreatment Gd-T1w, T2w, T2w-FLAIR MRI were obtained from 3 cohorts: The Cancer Imaging Archive (TCIA; n = 130), Ivy GAP (n = 32), and Cleveland Clinic (n = 41). Gene-expression profiles of corresponding patients were obtained for TCIA cohort. For every study, following expert segmentation of tumor subcompartments (necrotic core, enhancing tumor, peritumoral edema), 936 3D radiomic features were extracted from each subcompartment across all MRI protocols. Using Cox regression model, radiomic risk score (RRS) was developed for every protocol to predict PFS on the training cohort (n = 130) and evaluated on the holdout cohort (n = 73). Further, Gene Ontology and single-sample gene set enrichment analysis were used to identify specific molecular signaling pathway networks associated with RRS features. RESULTS: Twenty-five radiomic features from the tumor habitat yielded the RRS. A combination of RRS with clinical (age and gender) and molecular features (MGMT and IDH status) resulted in a concordance index of 0.81 (P < 0.0001) on training and 0.84 (P = 0.03) on the test set. Radiogenomic analysis revealed associations of RRS features with signaling pathways for cell differentiation, cell adhesion, and angiogenesis, which contribute to chemoresistance in GBM. CONCLUSIONS: Our findings suggest that prognostic radiomic features from routine Gd-T1w MRI may also be significantly associated with key biological processes that affect response to chemotherapy in GBM.

7T MR of intracranial pathology: Preliminary observations and comparisons to 3T and 1.5T.

PURPOSE: There have been an increasing number of studies involving ultra-high-field 7T of intracranial pathology, however, comprehensive clinical studies of neuropathology at 7T still remain limited. 7T has the advantage of a higher signal-to-noise ratio and a higher contrast-to-noise ratio, compared to current low field clinical MR scanners. We hypothesized 7T applied clinically, may improve detection and characterization of intracranial pathology. MATERIALS AND METHODS: We performed an IRB-approved 7T prospective study of patients with neurological disease who previously had lower field 3T and 1.5T. All patients underwent 7T scans, using comparable clinical imaging protocols, with the aim of qualitatively comparing neurological lesions at 7T with 3T or 1.5T. To qualitatively assess lesion conspicuity at 7T compared with low field, 80-paired images were viewed by 10 experienced neuroradiologists and scored on a 5-point scale. Inter-rater agreement was characterized using a raw percent agreement and mean weighted kappa. RESULTS: One-hundred and four patients with known neurological disease have been scanned to date. Fifty-five patients with epilepsy, 18 patients with mild traumatic brain injury, 11 patients with known or suspected multiple sclerosis, 9 patients with amyotrophic lateral sclerosis, 4 patients with intracranial neoplasm, 2 patients with orbital melanoma, 2 patients with cortical infarcts, 2 patients with cavernous malformations, and 1 patient with cerebral amyloid angiopathy. From qualitative observations, we found better resolution and improved detection of lesions at 7T compared to 3T. There was a 55% raw inter-rater agreement that lesions were more conspicuous on 7T than 3T/1.5T, compared with a 6% agreement that lesions were more conspicuous on 3T/1.5T than 7T. CONCLUSION: Our findings show that the primary clinical advantages of 7T magnets, which include higher signal-to-noise ratio, higher contrast-to-noise ratio, smaller voxels and stronger susceptibility contrast, may increase lesion conspicuity, detection and characterization compared to low field 1.5T and 3T. However, low field which detects a plethora of intracranial pathology remains the mainstay for diagnostic imaging until limitations at 7T are addressed and further evidence of utility provided.