Dataset Information

Quantification of hepatocellular carcinoma heterogeneity with multiparametric magnetic resonance imaging.

ABSTRACT: Tumour heterogeneity poses a significant challenge for treatment stratification. The goals of this study were to quantify heterogeneity in hepatocellular carcinoma (HCC) using multiparametric magnetic resonance imaging (mpMRI), and to report preliminary data correlating quantitative MRI parameters with advanced histopathology and gene expression in a patient subset. Thirty-two HCC patients with 39 HCC lesions underwent mpMRI including diffusion-weighted imaging (DWI), blood-oxygenation-level-dependent (BOLD), tissue-oxygenation-level-dependent (TOLD) and dynamic contrast-enhanced (DCE)-MRI. Histogram characteristics [central tendency (mean, median) and heterogeneity (standard deviation, kurtosis, skewness) MRI parameters] in HCC and liver parenchyma were compared using Wilcoxon signed-rank tests. Histogram data was correlated between MRI methods in all patients and with histopathology and gene expression in 14 patients. HCCs exhibited significantly higher intra-tissue heterogeneity vs. liver with all MRI methods (P < 0.030). Although central tendency parameters showed significant correlations between MRI methods and with each of histopathology and gene expression, heterogeneity parameters exhibited additional complementary correlations between BOLD and DCE-MRI and with histopathologic hypoxia marker HIF1α and gene expression of Wnt target GLUL, pharmacological target FGFR4, stemness markers EPCAM and KRT19 and immune checkpoint PDCD1. Histogram analysis combining central tendency and heterogeneity mpMRI features is promising for non-invasive HCC characterization on the imaging, histologic and genomics levels.

SUBMITTER: Hectors SJ

PROVIDER: S-EPMC5446396 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Quantification of hepatocellular carcinoma heterogeneity with multiparametric magnetic resonance imaging.

Hectors Stefanie J SJ Wagner Mathilde M Bane Octavia O Besa Cecilia C Lewis Sara S Remark Romain R Chen Nelson N Fiel M Isabel MI Zhu Hongfa H Gnjatic Sacha S Merad Miriam M Hoshida Yujin Y Taouli Bachir B

Scientific reports 20170526 1

Tumour heterogeneity poses a significant challenge for treatment stratification. The goals of this study were to quantify heterogeneity in hepatocellular carcinoma (HCC) using multiparametric magnetic resonance imaging (mpMRI), and to report preliminary data correlating quantitative MRI parameters with advanced histopathology and gene expression in a patient subset. Thirty-two HCC patients with 39 HCC lesions underwent mpMRI including diffusion-weighted imaging (DWI), blood-oxygenation-level-dep ...[more]

PMID: 28550313

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Project description:PurposeThe clinical utility of multiparametric magnetic resonance imaging (mpMRI) for the detection and localization of prostate cancer (PCa) has been evaluated and validated. However, the implementation of mpMRI into the clinical practice remains some burden of cost and availability for patients and society. We aimed to predict the results of prostate mpMRI using the clinical parameters and multivariable model to reduce unnecessary mpMRI scans.MethodsWe retrospectively identified 784 men who underwent mpMRI scans and subsequent prostate biopsy between 2016 and 2020 according to the inclusion criterion. The cohort was split into a training cohort of 548 (70%) patients and a validation cohort of 236 (30%) patients. Clinical parameters including age, prostate-specific antigen (PSA) derivates, and prostate volume (PV) were assessed as the predictors of mpMRI results. The mpMRI results were divided into groups according to the reports: "negative", "equivocal", and "suspicious" for the presence of PCa.ResultsUnivariate analysis showed that the total PSA (tPSA), free PSA (fPSA), PV, and PSA density (PSAD) were significant predictors for suspicious mpMRI (P < 0.05). The PSAD (AUC = 0.77) and tPSA (AUC = 0.74) outperformed fPSA (AUC = 0.68) and PV (AUC = 0.62) in the prediction of the mpMRI results. The multivariate model (AUC = 0.80) had a similar diagnostic accuracy with PSAD (P = 0.108), while higher than tPSA (P = 0.024) in predicting the mpMRI results. The multivariate model illustrated a better calibration and substantial improvement in the decision curve analysis (DCA) at a threshold above 20%. Using the PSAD with a 0.13 ng/ml2 cut-off could spare the number of mpMRI scans by 20%, keeping a 90% sensitivity in the prediction of suspicious MRI-PCa and missing three (3/73, 4%) clinically significant PCa cases. At the same sensitivity level, the multivariate model with a 32% cut-off could spare the number of mpMRI scans by 27%, missing only one (1/73, 1%) clinically significant PCa case.ConclusionOur multivariate model could reduce the number of unnecessary mpMRI scans without comprising the diagnostic ability of clinically significant PCa. Further prospective validation is required.

Project description:ObjectivesThe aim of this study was to evaluate the repeatability of a region of interest (ROI) volume and mean apparent diffusion coefficient (ADC) in standard-of-care 3 T multiparametric magnetic resonance imaging (mpMRI) of the prostate obtained with the use of endorectal coil.Materials and methodsThis prospective study was Health Insurance Portability and Accountability Act compliant, with institutional review board approval and written informed consent. Men with confirmed or suspected treatment-naive prostate cancer scheduled for mpMRI were offered a repeat mpMRI within 2 weeks. Regions of interest corresponding to the whole prostate gland, the entire peripheral zone (PZ), normal PZ, and suspected tumor ROI (tROI) on axial T2-weighted, dynamic contrast-enhanced subtract, and ADC images were annotated and assessed using Prostate Imaging Reporting and Data System (PI-RADS) v2. Repeatability of the ROI volume for each of the analyzed image types and mean ROI ADC was summarized with repeatability coefficient (RC) and RC%.ResultsA total of 189 subjects were approached to participate in the study. Of 40 patients that gave initial agreement, 15 men underwent 2 mpMRI examinations and completed the study. Peripheral zone tROIs were identified in 11 subjects. Tumor ROI volume was less than 0.5 mL in 8 of 11 subjects. PI-RADS categories were identical between baseline-repeat studies in 11/15 subjects and differed by 1 point in 4/15. Peripheral zone tROI volume RC (RC%) was 233 mm (71%) on axial T2-weighted, 422 mm (112%) on ADC, and 488 mm (119%) on dynamic contrast-enhanced subtract. Apparent diffusion coefficient ROI mean RC (RC%) were 447 × 10 mm/s (42%) in PZ tROI and 471 × 10 mm/s (30%) in normal PZ. Significant difference in repeatability of the tROI volume across series was observed (P < 0.005). The mean ADC RC% was lower than volume RC% for tROI ADC (P < 0.05).ConclusionsPI-RADS v2 overall assessment was highly repeatable. Multiparametric magnetic resonance imaging sequences differ in volume measurement repeatability. The mean tROI ADC is more repeatable compared with tROI volume in ADC. Repeatability of prostate ADC is comparable with that in other abdominal organs.

Project description:Background:Current magnetic resonance imaging (MRI) of pancreatic disease is qualitative in nature. Quantitative imaging offers several advantages, including increased reproducibility and sensitivity to detect mild or diffuse disease. The role of multiparametric mapping MRI in characterizing various tissue types in pancreatic disease such as chronic pancreatitis (CP) and pancreatic ductal adenocarcinoma (PDAC) has rarely been evaluated. Purpose:To evaluate the feasibility of multiparametric mapping [T1, T2, and apparent diffusion coefficient (ADC)] in defining tissue characteristics that occur in CP and PDAC to improve disease diagnosis. Materials and Methods:Pancreatic MRI was performed in 17 patients with PDAC undergoing therapy, 7 patients with CP, and 29 healthy volunteers with no pancreatic disease. T1 modified Look-Locker Inversion Recovery (T1 MOLLI), T2-prepared gradient-echo, and multi-slice single-shot echo-planar diffusion weighted imaging (SS-EPI DWI) sequences were used for data acquisition. Regions of interest (ROIs) of pancreas in PDAC, CP, and control subjects were outlined by an experienced radiologist. One-way analysis of variance (ANOVA) was used to compare the difference between groups and regions of the pancreas, and Tukey tests were used for multiple comparison testing within groups. Receiver operator characteristic (ROC) curves were analyzed, and the areas under the curves (AUCs) were calculated using single parameter and combined parameters, respectively. Results:T1, T2, and ADC values of the entire pancreas among PDAC, CP, and control subjects; and between upstream and downstream portions of the pancreas in PDAC patients were all significantly different (p < 0.05). The AUC values were 0.90 for T1, 0.55 for T2, and 0.71 for ADC for independent prediction of PDAC. By combining T1, T2, and ADC, the AUC value was 0.94 (sensitivity 91.54%, specificity 85.81%, 95% CI: 0.92-0.96), which yielded higher accuracy than any one parameter only (p < 0.001). Conclusion:Multiparametric mapping MRI is feasible for the evaluation of the differences between PDAC, CP, and normal pancreas tissues. The combination of multiple parameters of T1, T2, and ADC provides a higher accuracy than any single parameter alone in tissue characterization of the pancreas.

Dataset Information

Quantification of hepatocellular carcinoma heterogeneity with multiparametric magnetic resonance imaging.

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Quantification of hepatocellular carcinoma heterogeneity with multiparametric magnetic resonance imaging.

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