Leland S. Hu

Relative Cerebral Blood Volume Values to Differentiate High-Grade Glioma Recurrence from Posttreatment Radiation Effect: Direct Correlation between Image-Guided Tissue Histopathology and Localized Dynamic Susceptibility-Weighted Contrast-Enhanced Perfusion MR Imaging Measurements

BACKGROUND AND PURPOSE: Differentiating tumor growth from posttreatment radiation effect (PTRE) remains a common problem in neuro-oncology practice. To our knowledge, useful threshold relative cerebral blood volume (rCBV) values that accurately distinguish the 2 entities do not exist. Our prospective study uses image-guided neuronavigation during surgical resection of MR imaging lesions to correlate directly specimen histopathology with localized dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging (DSC) measurements and to establish accurate rCBV threshold values, which differentiate PTRE from tumor recurrence. MATERIALS AND METHODS: Preoperative 3T gradient-echo DSC and contrast-enhanced stereotactic T1-weighted images were obtained in patients with high-grade glioma (HGG) previously treated with multimodality therapy. Intraoperative neuronavigation documented the stereotactic location of multiple tissue specimens taken randomly from the periphery of enhancing MR imaging lesions. Coregistration of DSC and stereotactic images enabled calculation of localized rCBV within the previously recorded specimen locations. All tissue specimens were histopathologically categorized as tumor or PTRE and were correlated with corresponding rCBV values. All rCBV values were T1-weighted leakage-corrected with preload contrast-bolus administration and T2/T2*-weighted leakage-corrected with baseline subtraction integration. RESULTS: Forty tissue specimens were collected from 13 subjects. The PTRE group (n = 16) rCBV values ranged from 0.21 to 0.71, tumor (n = 24) values ranged from 0.55 to 4.64, and 8.3% of tumor rCBV values fell within the PTRE group range. A threshold value of 0.71 optimized differentiation of the histopathologic groups with a sensitivity of 91.7% and a specificity of 100%. CONCLUSIONS: rCBV measurements obtained by using DSC and the protocol we have described can differentiate HGG recurrence from PTRE with a high degree of accuracy.

Radiogenomics to characterize regional genetic heterogeneity in glioblastoma

Background Glioblastoma (GBM) exhibits profound intratumoral genetic heterogeneity. Each tumor comprises multiple genetically distinct clonal populations with different therapeutic sensitivities. This has implications for targeted therapy and genetically informed paradigms. Contrast-enhanced (CE)-MRI and conventional sampling techniques have failed to resolve this heterogeneity, particularly for nonenhancing tumor populations. This study explores the feasibility of using multiparametric MRI and texture analysis to characterize regional genetic heterogeneity throughout MRI-enhancing and nonenhancing tumor segments. Methods We collected multiple image-guided biopsies from primary GBM patients throughout regions of enhancement (ENH) and nonenhancing parenchyma (so called brain-around-tumor, [BAT]). For each biopsy, we analyzed DNA copy number variants for core GBM driver genes reported by The Cancer Genome Atlas. We co-registered biopsy locations with MRI and texture maps to correlate regional genetic status with spatially matched imaging measurements. We also built multivariate predictive decision-tree models for each GBM driver gene and validated accuracies using leave-one-out-cross-validation (LOOCV). Results We collected 48 biopsies (13 tumors) and identified significant imaging correlations (univariate analysis) for 6 driver genes: EGFR, PDGFRA, PTEN, CDKN2A, RB1, and TP53. Predictive model accuracies (on LOOCV) varied by driver gene of interest. Highest accuracies were observed for PDGFRA (77.1%), EGFR (75%), CDKN2A (87.5%), and RB1 (87.5%), while lowest accuracy was observed in TP53 (37.5%). Models for 4 driver genes (EGFR, RB1, CDKN2A, and PTEN) showed higher accuracy in BAT samples (n = 16) compared with those from ENH segments (n = 32). Conclusion MRI and texture analysis can help characterize regional genetic heterogeneity, which offers potential diagnostic value under the paradigm of individualized oncology.

Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma

Background Genetic profiling represents the future of neuro-oncology but suffers from inadequate biopsies in heterogeneous tumors like Glioblastoma (GBM). Contrast-enhanced MRI (CE-MRI) targets enhancing core (ENH) but yields adequate tumor in only ~60% of cases. Further, CE-MRI poorly localizes infiltrative tumor within surrounding non-enhancing parenchyma, or brain-around-tumor (BAT), despite the importance of characterizing this tumor segment, which universally recurs. In this study, we use multiple texture analysis and machine learning (ML) algorithms to analyze multi-parametric MRI, and produce new images indicating tumor-rich targets in GBM. Methods We recruited primary GBM patients undergoing image-guided biopsies and acquired pre-operative MRI: CE-MRI, Dynamic-Susceptibility-weighted-Contrast-enhanced-MRI, and Diffusion Tensor Imaging. Following image coregistration and region of interest placement at biopsy locations, we compared MRI metrics and regional texture with histologic diagnoses of high- vs low-tumor content (≥80% vs <80% tumor nuclei) for corresponding samples. In a training set, we used three texture analysis algorithms and three ML methods to identify MRI-texture features that optimized model accuracy to distinguish tumor content. We confirmed model accuracy in a separate validation set. Results We collected 82 biopsies from 18 GBMs throughout ENH and BAT. The MRI-based model achieved 85% cross-validated accuracy to diagnose high- vs low-tumor in the training set (60 biopsies, 11 patients). The model achieved 81.8% accuracy in the validation set (22 biopsies, 7 patients). Conclusion Multi-parametric MRI and texture analysis can help characterize and visualize GBM’s spatial histologic heterogeneity to identify regional tumor-rich biopsy targets.

Cervical Spine MR Imaging Findings of Patients with Hirayama Disease in North America: A Multisite Study

The authors sought to determine if Hirayama disease in North America has the same imaging findings as it does in Asia. They assessed imaging studies in 21 patients and looked for loss of attachment of posterior dura, lower cord atrophy and high T2 signal, loss of cervical lordosis, and anterior dural shift in flexion. These 4 findings were able to discriminate patients from healthy controls. MR imaging findings in white North American patients with Hirayama disease include loss of attachment on neutral images and forward displacement of the dura with flexion. Findings are often present on neutral MR images and, in the appropriate clinical scenario, should prompt flexion MR imaging to evaluate anterior dural shift. BACKGROUND AND PURPOSE: Most studies of HD have been conducted in Asia, particularly Japan. To characterize the MR imaging findings of North American patients with HD, we reviewed neutral and flexion cervical MR imaging examinations performed for possible HD at 3 academic medical centers located in the Southeastern, Southwestern, and Midwestern regions of the United States. MATERIALS AND METHODS: Three neuroradiologists assessed the MR imaging examinations in a blinded fashion and reached a consensus rating for LOA of the posterior dura to the spine, lower spinal cord atrophy, spinal cord T2 hyperintensity, loss of cervical lordosis, anterior dural shift with flexion, and confidence of imaging diagnosis. Final reference diagnosis was established separately with a retrospective chart review by a neurologist. RESULTS: Twenty-one patients met the criteria for HD, all were North American males and all who reported their race were white. Seventeen patients did not meet the criteria and served as controls. Four imaging attributes, LOA, dural shift with flexion, consensus diagnosis of neutral images, and consensus diagnosis of combined neutral and flexion images were all able to discriminate the group with HD from the group without HD (P < .05 for each). Findings of HD were often present on neutral images, but the addition of flexion images increased diagnostic confidence. CONCLUSIONS: MR imaging findings in white North American patients with HD include LOA on neutral images and forward displacement of the dura with flexion. Findings are often present on neutral MR images and, in the appropriate clinical scenario, should prompt flexion MR imaging to evaluate anterior dural shift.

Is the blood–brain barrier really disrupted in all glioblastomas? A critical assessment of existing clinical data

The blood-brain barrier (BBB) excludes the vast majority of cancer therapeutics from normal brain. However, the importance of the BBB in limiting drug delivery and efficacy is controversial in high-grade brain tumors, such as glioblastoma (GBM). The accumulation of normally brain impenetrant radiographic contrast material in essentially all GBM has popularized a belief that the BBB is uniformly disrupted in all GBM patients so that consideration of drug distribution across the BBB is not relevant in designing therapies for GBM. However, contrary to this view, overwhelming clinical evidence demonstrates that there is also a clinically significant tumor burden with an intact BBB in all GBM, and there is little doubt that drugs with poor BBB permeability do not provide therapeutically effective drug exposures to this fraction of tumor cells. This review provides an overview of the clinical literature to support a central hypothesis: that all GBM patients have tumor regions with an intact BBB, and cure for GBM will only be possible if these regions of tumor are adequately treated.

Median Lingual Lymph Nodes: Prevalence on Imaging and Potential Implications for Oral Cavity Cancer Staging.

Objective This study sought to estimate the prevalence of median lingual lymph node (MLLN) metastases from oral cavity squamous cell carcinoma (OCSCC) and determine the frequency with which MLLNs can be identified with magnetic resonance imaging (MRI) in control subjects. Methods Pathology reports were used to identify patients with surgically treated OCSCC who underwent preoperative positron emission tomography–computed tomography to define the prevalence of MLLN metastases. As a control group, 500 consecutive face-neck MRIs from noncancer patients were reviewed for structures consistent with MLLNs. Results In the study group, 1 (0.95%) of 105 OCSCC cases demonstrated a single MLLN metastasis from a lateral tongue tumor (T4aN2c). The MLLN exceeded 1 cm in all planes and was abnormal in morphology. The frequency of suspected MLLNs in controls was 1.0%, with a maximum measurement of 0.9 cm. Conclusions Median lingual lymph nodes are infrequently identified with MRI in controls, concordant with the low prevalence of metastases from OCSCC to this inconstant nodal group.

Connecting Patterns of Tumor Growth with Sex Differences in Extreme Survivorship for Primary Glioblastoma Patients

Purpose: Patient sex is recognized as a significant determinant of outcome but the relative prognostic importance of molecular, imaging, and other clinical features of GBM has not yet been thoroughly explored for male versus female patients. Combining multi-modal MR images and patient clinical information, this investigation assesses which pretreatment MRI-based and clinical variables impact sex-specific survivorship in glioblastoma patients. Methods: We considered the multi-modal MRI and clinical data of 494 patients newly diagnosed with primary glioblastoma (299 males and 195 females). Patient MR images (T1Gd, T2, and T2-FLAIR) were segmented to quantify imageable tumor volumes for each MR sequence. Cox proportional hazard (CPH) models and Student’s t-tests were used to assess which variables were significantly associated with survival outcomes. We used machine learning algorithms to develop pruned decision trees to integrate the impact of these variables on patient survival. Results: Among males, tumor (T1Gd) radius was a significant predictor of overall survival (HR=1.027, p=0.044). Among females, higher tumor cell net invasion rate was a significant detriment to overall survival (HR=1.011, p<0.001). Female extreme survivors had significantly smaller tumors (T1Gd) (p=0.010 t-test), but tumor size was not significantly correlated with female overall survival (p=0.955 CPH). Both male and female extreme survivors had significantly lower tumor cell net proliferation rates than patients in other survival groups (M p=0.004, F p=0.001, t-test). Age at diagnosis was a significant predictive factor for overall survival length for both males and females (M HR= 1.030, F HR=1.022). Additional variables like extent of resection, tumor laterality, and IDH1 mutation status were also found to have sex-specific effects on overall survival. Conclusion: The results indicated that some variables, like the tumor cell diffuse invasion rate and tumor size, had sex-specific implications for survival, while other variables, such as age at diagnosis and tumor cell proliferation rate, impacted both sexes in the same way. Despite similar distributions of the MR imaging parameters between males and females, there was a sex-specific difference in how these parameters related to outcomes. The sex differences in the predictive value of these and other variables emphasizes the importance of considering sex as a biological factor when determining patient prognosis and treatment approach.Background Sex is recognized as a significant determinant of outcome among glioblastoma patients, but the relative prognostic importance of glioblastoma features has not been thoroughly explored for sex differences. Methods Combining multi-modal MR images, biomathematical models, and patient clinical information, this investigation assesses which pretreatment variables have a sex-specific impact on the survival of glioblastoma patients. Pretreatment MR images of 494 glioblastoma patients (299 males and 195 females) were segmented to quantify tumor volumes. Cox proportional hazard (CPH) models and Student’s t-tests were used to assess which variables were associated with survival outcomes. Results Among males, tumor (T1Gd) radius was a predictor of overall survival (HR=1.027, p=0.044). Among females, higher tumor cell net invasion rate was a significant detriment to overall survival (HR=1.011, p Conclusion Despite similar distributions of the MR imaging parameters between males and females, there was a sex-specific difference in how these parameters related to outcomes, which emphasizes the importance of considering sex as a biological factor when determining patient prognosis and treatment approach.

Neuroimaging abnormalities in patients with Cowden syndrome: Retrospective single-center study

Background We retrospectively reviewed the neuroimaging findings of patients with Cowden syndrome and determined their frequency in a single cohort. Methods Electronic medical records were queried from January 1999 to January 2017 to identify patients who fit the clinical criteria for diagnosis of Cowden syndrome with or without a documented PTEN mutation. Patients with brain MRI examinations were then identified. Results We retrospectively identified 44 patients with Cowden syndrome, 22 of whom had neuroimaging for review. Eleven (50%) had Lhermitte-Duclos disease, 4 (18.1%) had meningiomas, 13 (59.1%) had at least one developmental venous anomaly, 3 had cavernous malformations, 2 had evidence of dural arteriovenous fistula, 7 had increased white matter signal abnormalities relative to age (31.8%), 4 had prominent perivascular spaces, cerebellar tonsillar ectopia was present in 7 of 21 (33.3%), and 1 had cortical malformation. Conclusions It is important to recognize that in addition to Lhermitte-Duclos disease, other intracranial findings such as multiple venous anomalies, meningiomas, greater than expected white matter signal abnormality, prominent perivascular spaces, and cortical malformations may warrant a thorough evaluation for Cowden syndrome in the appropriate clinical setting. We further recommend that this broader spectrum of intracranial abnormalities be considered for addition to the Cowden syndrome diagnostic criteria at the time of next revision.

Abstract 3748: Perfusion MRI estimation of glioma microvascular density to predict tumor recurrence and treatment response: Validation study through stereotactic tissue analysis

Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DCnnPurpose: This study uses spatially accurate image-guided tissue analysis to evaluate the correlation between Perfusion MRI (pMRI) and tissue microvascular density parameters as markers for tumor recurrence and treatment response in high-grade glioma (HGG).nnMethods: Following Institutional Review Board approval, we recruited previously treated (including chemo-radiation therapy) HGG patients undergoing surgical re-resection of new enhancing lesions on surveillance MRI. Preoperatively, we acquired pMRI and contrast-enhanced stereotactic T1-Weighted (T1W) MRI data sets. Intraoperatively, we recorded stereotactic locations of multiple biopsies based on T1W data sets that guided surgery. Following surgery, we coregistered pMRI and T1W data sets to calculate localized relative cerebral blood volume (rCBV) for each stereotactic specimen location. For each specimen, we performed 1) standard HE and 2) immunohistochemical analysis with CD34 to highlight tissue vessels. We analyzed CD-34 stained slides with Axiovision Automeasure 3.4 (Zeiss, Germany) to calculate both total microvessel number (MVN) and total microvessel area (MVA), each normalized to total slide specimen area (μm2). We calculated Pearson correlations to establish relationships between a) rCBV and MVN; and b) rCBV and MVA. We also performed t-test to compare MVN, MVA, and rCBV values between tumor and PTRE samples. A neuroradiologist performed all coregistration and pMRI calculations, and a neuropathologist analyzed all tissue specimens, without knowledge of corresponding data. A biostatistician performed all statistical comparisons.nnResults: In this preliminary study, we included 16 tissue specimens (from 8 subjects), each diagnosed as either tumor (n=7) or PTRE (n=9). We successfully calculated localized rCBV and determined both MVA and MVN for each specimen. The rCBV values showed highest correlation with total vessel area (MVA) (r=0.65, p=0.007) and slightly less correlation with vessel number (MVN) (r=0.52, p=0.04). Tumor showed significantly higher values than PTRE for all parameters: rCBV (1.87 + 0.82 versus 0.78 + 0.2, p=.002); MVA (0.22 + 0.03 versus 0.04 + 0.007, p=0.0001); and MVN (0.0068 + 0.001 versus. 0.0016 + 0.0006, p=0.0004).nnConclusion: These preliminary results show the promise of Perfusion MRI to non-invasively estimate tissue microvessel density and distinguish tumor recurrence from treatment effects. The current study is ongoing to confirm results in a larger patient population.nnCitation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3748.