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Histogram analysis of prostate cancer on dynamic contrast-enhanced magnetic resonance imaging: A preliminary study emphasizing on zonal difference.

ABSTRACT: BACKGROUND:This study evaluated the performance of histogram analysis in the time course of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for differentiating cancerous tissues from benign tissues in the prostate. METHODS:We retrospectively analyzed the histograms of DCE-MRI of 30 patients. Histograms within regions of interest(ROI) in the peripheral zone (PZ) and transitional zone (TZ) were separately analyzed. The maximum difference wash-in slope (MWS) and delay phase slope (DPS) were defined for each voxel. Differences in histogram parameters, namely the mean, standard deviation (SD), the coefficient of variation (CV), kurtosis, skewness, interquartile range (IQR), percentile (P10, P25, P75, P90, and P90P10), Range, and modified full width at half-maximum (mFWHM) between cancerous and benign tissues were assessed. RESULTS:In the TZ, CV for ROIs of 7.5 and 10mm was the only significantly different parameter of the MWS (P = 0.034 and P = 0.004, respectively), whereas many parameters of the DPS (mean, skewness, P10, P25, P50, P75 and P90) differed significantly (P = <0.001-0.016 and area under the curve [AUC] = 0.73-0.822). In the PZ, all parameters of the MWS exhibited significant differences, except kurtosis and skewness in the ROI of 7.5mm(P = <0.001-0.017 and AUC = 0.865-0.898). SD, IQR, mFWHM, P90P10 and Range were also significant differences in the DPS (P = 0.001-0.035). CONCLUSION:The histogram analysis of DCE-MRI is a potentially useful approach for differentiating prostate cancer from normal tissues. Different histogram parameters of the MWS and DPS should be applied in the TZ and PZ.

SUBMITTER: Lai CC

PROVIDER: S-EPMC6372178 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Histogram analysis of prostate cancer on dynamic contrast-enhanced magnetic resonance imaging: A preliminary study emphasizing on zonal difference.

Lai Chih-Ching CC Huang Pin-Hsun PH Wang Fu-Nien FN Shen Shu-Huei SH Wang Hsin-Kai HK Liu Hsian-Tzu HT Chung Hsiao-Jen HJ Lin Tzu-Ping TP Chang Yen-Hwa YH Pan Chin-Chen CC Peng Shin-Lei SL

PloS one 20190212 2

<h4>Background</h4>This study evaluated the performance of histogram analysis in the time course of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for differentiating cancerous tissues from benign tissues in the prostate.<h4>Methods</h4>We retrospectively analyzed the histograms of DCE-MRI of 30 patients. Histograms within regions of interest(ROI) in the peripheral zone (PZ) and transitional zone (TZ) were separately analyzed. The maximum difference wash-in slope (MWS) and delay ...[more]

PMID: 30753222

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Project description:The prediction of monoclonal antibody (mAb) disposition within solid tumors for individual patients is difficult due to inter-patient variability in tumor physiology. Improved a priori prediction of mAb pharmacokinetics in tumors may facilitate the development of patient-specific dosing protocols and facilitate improved selection of patients for treatment with anti-cancer mAb. Here, we report the use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), with tumor penetration of the contrast agent gadobutrol used as a surrogate, to improve physiologically based pharmacokinetic model (PBPK) predictions of cetuximab pharmacokinetics in epidermal growth factor receptor (EGFR) positive xenografts. In the initial investigations, mice bearing Panc-1, NCI-N87, and LS174T xenografts underwent DCE-MRI imaging with the contrast agent gadobutrol, followed by intravenous dosing of an 125Iodine-labeled, non-binding mAb (8C2). Tumor concentrations of 8C2 were determined following the euthanasia of mice (3 h-6 days after 8C2 dosing). Potential predictor relationships between DCE-MRI kinetic parameters and 8C2 PBPK parameters were evaluated through covariate modeling. The addition of the DCE-MRI parameter Ktrans alone or Ktrans in combination with the DCE-MRI parameter Vp on the PBPK parameters for tumor blood flow (QTU) and tumor vasculature permeability (σTUV) led to the most significant improvement in the characterization of 8C2 pharmacokinetics in individual tumors. To test the utility of the DCE-MRI covariates on a priori prediction of the disposition of mAb with high-affinity tumor binding, a second group of tumor-bearing mice underwent DCE-MRI imaging with gadobutrol, followed by the administration of 125Iodine-labeled cetuximab (a high-affinity anti-EGFR mAb). The MRI-PBPK covariate relationships, which were established with the untargeted antibody 8C2, were implemented into the PBPK model with considerations for EGFR expression and cetuximab-EGFR interaction to predict the disposition of cetuximab in individual tumors (a priori). The incorporation of the Ktrans MRI parameter as a covariate on the PBPK parameters QTU and σTUV decreased the PBPK model prediction error for cetuximab tumor pharmacokinetics from 223.71 to 65.02%. DCE-MRI may be a useful clinical tool in improving the prediction of antibody pharmacokinetics in solid tumors. Further studies are warranted to evaluate the utility of the DCE-MRI approach to additional mAbs and additional drug modalities.

Project description:Key pointsThe blood-brain barrier (BBB) is an important and dynamic structure which contributes to homeostasis in the central nervous system. BBB permeability changes occur in health and disease but measurement of BBB permeability in humans is not straightforward. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can be used to model the movement of gadolinium contrast into the brain, expressed as the influx constant Ki . Here evidence is provided that Ki as measured by DCE-MRI behaves as expected for a marker of overall BBB leakage. These results support the use of DCE-MRI for in vivo studies of human BBB permeability in health and disease.AbstractBlood-brain barrier (BBB) leakage can be measured using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as the influx constant Ki . To validate this method we compared measured Ki with biological expectations, namely (1) higher Ki in healthy individual grey matter (GM) versus white matter (WM), (2) GM/WM cerebral blood volume (CBV) ratio close to the histologically established GM/WM vascular density ratio, (3) higher Ki in visibly enhancing multiple sclerosis (MS) lesions versus MS normal appearing white matter (NAWM), and (4) higher Ki in MS NAWM versus healthy individual NAWM. We recruited 13 healthy individuals and 12 patients with MS and performed whole-brain 3D DCE-MRI at 3 T. Ki and CBV were calculated using Patlak modelling for manual regions of interest (ROI) and segmented tissue masks. Ki was higher in control GM versus WM (P = 0.001). CBV was higher in GM versus WM (P = 0.005, mean ratio 1.9). Ki was higher in visibly enhancing MS lesions versus MS NAWM (P = 0.002), and in MS NAWM versus controls (P = 0.014). Bland-Altman analysis showed no significant difference between ROI and segmentation methods (P = 0.638) and an intra-class correlation coefficient showed moderate single measure consistency (0.610). Ki behaves as expected for a compound marker of permeability and surface area. The GM/WM CBV ratio measured by this technique is in agreement with the literature. This adds evidence to the validity of Ki measured by DCE-MRI as a marker of overall BBB leakage.

Dataset Information

Histogram analysis of prostate cancer on dynamic contrast-enhanced magnetic resonance imaging: A preliminary study emphasizing on zonal difference.

Publications

Histogram analysis of prostate cancer on dynamic contrast-enhanced magnetic resonance imaging: A preliminary study emphasizing on zonal difference.

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