Dataset Information

MRI Imaging of the Hemodynamic Vasculature of Neuroblastoma Predicts Response to Antiangiogenic Treatment.

ABSTRACT: Childhood neuroblastoma is a hypervascular tumor of neural origin, for which antiangiogenic drugs are currently being evaluated; however, predictive biomarkers of treatment response, crucial for successful delivery of precision therapeutics, are lacking. We describe an MRI-pathologic cross-correlative approach using intrinsic susceptibility (IS) and susceptibility contrast (SC) MRI to noninvasively map the vascular phenotype in neuroblastoma Th-MYCN transgenic mice treated with the vascular endothelial growth factor receptor inhibitor cediranib. We showed that the transverse MRI relaxation rate R 2* (second-1) and fractional blood volume (fBV, %) were sensitive imaging biomarkers of hemorrhage and vascular density, respectively, and were also predictive biomarkers of response to cediranib. Comparison with MRI and pathology from patients with MYCN-amplified neuroblastoma confirmed the high degree to which the Th-MYCN model vascular phenotype recapitulated that of the clinical phenotype, thereby supporting further evaluation of IS- and SC-MRI in the clinic. This study reinforces the potential role of functional MRI in delivering precision medicine to children with neuroblastoma. SIGNIFICANCE: This study shows that functional MRI predicts response to vascular-targeted therapy in a genetically engineered murine model of neuroblastoma.

SUBMITTER: Zormpas-Petridis K

PROVIDER: S-EPMC6558276 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

MRI Imaging of the Hemodynamic Vasculature of Neuroblastoma Predicts Response to Antiangiogenic Treatment.

Zormpas-Petridis Konstantinos K Jerome Neil P NP Blackledge Matthew D MD Carceller Fernando F Poon Evon E Clarke Matthew M McErlean Ciara M CM Barone Giuseppe G Koers Alexander A Vaidya Sucheta J SJ Marshall Lynley V LV Pearson Andrew D J ADJ Moreno Lucas L Anderson John J Sebire Neil N McHugh Kieran K Koh Dow-Mu DM Yuan Yinyin Y Chesler Louis L Robinson Simon P SP Jamin Yann Y

Cancer research 20190315 11

Childhood neuroblastoma is a hypervascular tumor of neural origin, for which antiangiogenic drugs are currently being evaluated; however, predictive biomarkers of treatment response, crucial for successful delivery of precision therapeutics, are lacking. We describe an MRI-pathologic cross-correlative approach using intrinsic susceptibility (IS) and susceptibility contrast (SC) MRI to noninvasively map the vascular phenotype in neuroblastoma Th-MYCN transgenic mice treated with the vascular endo ...[more]

PMID: 30877107

Similar Datasets

Project description:BACKGROUND:Whole-body MRI (WB-MRI) including diffusion-weighted image (DWI) have been widely used in patients with multiple myeloma. However, evidence for the value of WB-MRI in the evaluation of treatment response remains sparse. Therefore, we evaluated the role of WB-MRI in the response assessment. METHODS:In our WB-MRI registry, we searched multiple myeloma patients treated with chemotherapy who underwent both baseline and follow-up WB-MRI scans. Clinical responses were categorized as complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD), using IMWG criteria. Using RECIST 1.1, MD Anderson (MDA) criteria, and MDA-DWI criteria, imaging responses on WB-MRI were rated as CR, PR, SD, or PD by two radiologists independently. Then, discrepancy cases were resolved by consensus. Weighted Kappa analysis was performed to evaluate agreement between the imaging and clinical responses. The diagnostic accuracy of image responses in the evaluation of clinical CR, objective response (CR and PR), and PD was calculated. RESULTS:Forty-two eligible patients were included. There was moderate agreement between imaging and clinical responses (??=?0.54 for RECIST 1.1, ??=?0.58 for MDA criteria, ??=?0.69 for MDA-DWI criteria). WB-MRI showed excellent diagnostic accuracy in assessment of clinical PD (sensitivity 88.9%, specificity 94.7%, positive predictive value [PPV] 84.2%, negative predictive value [NPV] 96.4% in all three imaging criteria). By contrast, WB-MRI showed low accuracy in assessment of clinical CR (sensitivity 4.5%, specificity 98.1%, PPV 50.0%, NPV 71.2% in all three imaging criteria). As to the clinical objective response, the diagnostic accuracy was higher in MDA-DWI criteria than RECIST 1.1 and MDA criteria (sensitivity/specificity/PPV/NPV, 84.2%/94.4%/98.0%/65.4, 54.4%/100%/100%/40.9, and 61.4%/94.4%/97.2%/43.6%, respectively). CONCLUSIONS:In the imaging response assessment of multiple myeloma, WB-MRI showed excellent performance in the evaluation of PD, but not in the assessment of CR or objective response. When adding DWI to imaging response criteria, diagnostic accuracy for objective response was improved and agreement between imaging and clinical responses was increased.

Project description:Functional magnetic resonance imaging (fMRI), being an indirect measure of brain activity, is mathematically defined as a convolution of the unmeasured latent neural signal and the hemodynamic response function (HRF). The HRF is known to vary across the brain and across individuals, and it is modulated by neural as well as non-neural factors. Three parameters characterize the shape of the HRF, which is obtained by performing deconvolution on resting-state fMRI data: response height, time-to-peak and full-width at half-max. The data provided here, obtained from 47 healthy adults, contains these three HRF parameters at every voxel in the brain, as well as HRF parameters from the default-mode network (DMN). In addition, we have provided functional connectivity (FC) data from the same DMN regions, obtained for two cases: data with deconvolution (HRF variability minimized) and data with no deconvolution (HRF variability corrupted). This would enable researchers to compare regional changes in HRF with corresponding FC differences, to assess the impact of HRF variability on FC. Importantly, the data was obtained in a 7T MRI scanner. While most fMRI studies are conducted at lower field strengths, like 3T, ours is the first study to report HRF data obtained at 7T. FMRI data at ultra-high fields contains larger contributions from small vessels, consequently HRF variability is lower for small vessels at higher field strengths. This implies that findings made from this data would be more conservative than from data acquired at lower fields, such as 3T. Results obtained with this data and further interpretations are available in our recent research study (Rangaprakash et al., in press) [1]. This is a valuable dataset for studying HRF variability in conjunction with FC, and for developing the HRF profile in healthy individuals, which would have direct implications for fMRI data analysis, especially resting-state connectivity modeling. This is the first public HRF data at 7T.

Project description:PurposeThe tumor-associated vasculature (TAV) differs from healthy blood vessels by its convolutedness, leakiness, and chaotic architecture, and these attributes facilitate the creation of a treatment-resistant tumor microenvironment. Measurable differences in these attributes might also help stratify patients by likely benefit of systemic therapy (e.g., chemotherapy). In this work, we present a new category of computational image-based biomarkers called quantitative tumor-associated vasculature (QuanTAV) features, and demonstrate their ability to predict response and survival across multiple cancer types, imaging modalities, and treatment regimens involving chemotherapy.Experimental designWe isolated tumor vasculature and extracted mathematical measurements of twistedness and organization from routine pretreatment radiology (CT or contrast-enhanced MRI) of a total of 558 patients, who received one of four first-line chemotherapy-based therapeutic intervention strategies for breast (n = 371) or non-small cell lung cancer (NSCLC, n = 187).ResultsAcross four chemotherapy-based treatment strategies, classifiers of QuanTAV measurements significantly (P < 0.05) predicted response in held out testing cohorts alone (AUC = 0.63-0.71) and increased AUC by 0.06-0.12 when added to models of significant clinical variables alone. Similarly, we derived QuanTAV risk scores that were prognostic of recurrence-free survival in treatment cohorts who received surgery following chemotherapy for breast cancer [P = 0.0022; HR = 1.25; 95% confidence interval (CI), 1.08-1.44; concordance index (C-index) = 0.66] and chemoradiation for NSCLC (P = 0.039; HR = 1.28; 95% CI, 1.01-1.62; C-index = 0.66). From vessel-based risk scores, we further derived categorical QuanTAV high/low risk groups that were independently prognostic among all treatment groups, including patients with NSCLC who received chemotherapy only (P = 0.034; HR = 2.29; 95% CI, 1.07-4.94; C-index = 0.62). QuanTAV response and risk scores were independent of clinicopathologic risk factors and matched or exceeded models of clinical variables including posttreatment response.ConclusionsAcross these domains, we observed an association of vascular morphology on CT and MRI-as captured by metrics of vessel curvature, torsion, and organizational heterogeneity-and treatment outcome. Our findings suggest the potential of shape and structure of the TAV in developing prognostic and predictive biomarkers for multiple cancers and different treatment strategies.

Dataset Information

MRI Imaging of the Hemodynamic Vasculature of Neuroblastoma Predicts Response to Antiangiogenic Treatment.

Publications

MRI Imaging of the Hemodynamic Vasculature of Neuroblastoma Predicts Response to Antiangiogenic Treatment.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets