Dynamic Contrast-enhanced Magnetic Resonance Imaging Parameters Research Articles

Correlation of Semi-Quantitative Breast-Specific Gamma Imaging Findings with Dynamic Contrast-Enhanced MRI Parameters Assessed by a Computer-Aided Evaluation Program for Breast Cancer

Correlation of Semi-Quantitative Breast-Specific Gamma Imaging Findings with Dynamic Contrast-Enhanced MRI Parameters Assessed by a Computer-Aided Evaluation Program for Breast Cancer

Dynamic contrast-enhanced magnetic resonance imaging of prostate cancer: A review of current methods and applications.

In many areas of oncology, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has proven to be a clinically useful, non-invasive functional imaging technique to quantify tumor vasculature and tumor perfusion characteristics. Tumor angiogenesis is an essential process for tumor growth, proliferation, and metastasis. Malignant lesions demonstrate rapid extravasation of contrast from the intravascular space to the capillary bed due to leaky capillaries associated with tumor neovascularity. DCE-MRI has the potential to provide information regarding blood flow, areas of hypoperfusion, and variations in endothelial permeability and microvessel density to aid treatment selection, enable frequent monitoring during treatment and assess response to targeted therapy following treatment. This review will discuss the current status of DCE-MRI in cancer imaging, with a focus on its use in imaging prostate malignancies as well as weaknesses that limit its widespread clinical use. The latest techniques for quantification of DCE-MRI parameters will be reviewed and compared.

Comparison of semi-quantitative and quantitative dynamic contrast-enhanced MRI evaluations of vertebral marrow perfusion in a rat osteoporosis model

BackgroundThis study aims to investigate the technical feasibility of semi-quantitative and quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in the assessment of longitudinal changes of marrow perfusion in a rat osteoporosis model, using bone mineral density (BMD) measured by micro-computed tomography (micro-CT) and histopathology as the gold standards.MethodsFifty rats were randomly assigned to the control group (n=25) and ovariectomy (OVX) group whose bilateral ovaries were excised (n=25). Semi-quantitative and quantitative DCE-MRI, micro-CT, and histopathological examinations were performed on lumbar vertebrae at baseline and 3, 6, 9, and 12 weeks after operation. The differences between the two groups in terms of semi-quantitative DCE-MRI parameter (maximum enhancement, Emax), quantitative DCE-MRI parameters (volume transfer constant, Ktrans; interstitial volume, Ve; and efflux rate constant, Kep), micro-CT parameter (BMD), and histopathological parameter (microvessel density, MVD) were compared at each of the time points using an independent-sample t test. The differences in these parameters between baseline and other time points in each group were assessed via Bonferroni’s multiple comparison test. A Pearson correlation analysis was applied to assess the relationships between DCE-MRI, micro-CT, and histopathological parameters.ResultsIn the OVX group, the Emax values decreased significantly compared with those of the control group at weeks 6 and 9 (p=0.003 and 0.004, respectively). The Ktrans values decreased significantly compared with those of the control group from week 3 (p<0.05). However, the Ve values decreased significantly only at week 9 (p=0.032), and no difference in the Kep was found between two groups. The BMD values of the OVX group decreased significantly compared with those of the control group from week 3 (p<0.05). Transmission electron microscopy showed tighter gaps between vascular endothelial cells with swollen mitochondria in the OVX group from week 3. The MVD values of the OVX group decreased significantly compared with those of the control group only at week 12 (p=0.023). A weak positive correlation of Emax and a strong positive correlation of Ktrans with MVD were found.ConclusionsCompared with semi-quantitative DCE-MRI, the quantitative DCE-MRI parameter Ktrans is a more sensitive and accurate index for detecting early reduced perfusion in osteoporotic bone.

Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis.

PurposeThis study aimed to evaluate the difference of mass in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) characteristics between low-risk and non-low-risk breast cancers and to explore the possible pathological basis.Materials and MethodsApproval from the institutional review board and informed consent were acquired for this study. The MR images of 104 patients with pathologically proven breast cancer (104 lesions) were prospectively analyzed. All of included patients were Chinese woman. The DCE-MRI morphologic findings, apparent diffusion coefficient (ADC) values, quantitative DCE-MRI parameters, and pathological biomarkers between the two subtypes of breast cancer were compared. The quantitative DCE-MRI parameters and ADC values were added to the morphologic features in multivariate models to evaluate diagnostic performance in predicting low-risk breast cancer. The values were further subjected to the receiver operating characteristic (ROC) curve analysis.ResultsLow-risk tumors showed significantly lower Ktrans and Kep values (t = 2.065, P = 0.043 and t = 3.548, P = 0.001, respectively) and higher ADC value (t = 4.713, P = 0.000) than non-low-risk breast cancers. Our results revealed no significant differences in clinic data and conventional imaging findings between the two breast cancer subtypes. Adding the quantitative DCE-MRI parameters and ADC values to conventional MRI improved the diagnostic performance of MRI: The area under the ROC improved from 0.63 to 0.91. Low-risk breast cancers showed significantly lower matrix metalloproteinase (MMP)-2 expression (P = 0.000), lower MMP-9 expression (P = 0.001), and lower microvessel density (MVD) values (P = 0.008) compared with non-low-risk breast cancers. Ktrans and Kep values were positively correlated with pathological biomarkers. The ADC value showed a significant inverse correlation with pathological biomarkers.ConclusionsThe prediction parameter using Ktrans, Kep, and ADC obtained on DCE-MRI and diffusion-weighted imaging could facilitate the identification of low-risk breast cancers. Decreased biological factors, including MVD, vascular endothelial growth factor, MMP-2, and MMP-9, may explain the possible pathological basis.

The value of DCE-MRI in assessing histopathological and molecular biological features in induced rat epithelial ovarian carcinomas

BackgroundTo investigate dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) for assessing histopathological and molecular biological features in induced rat epithelial ovarian carcinomas (EOCs).Methods7,12-dimethylbenz[A]anthracene (DMBA) was applied to induce EOCs in situ in 46 SD rats. Conventional MRI and DCE-MRI were performed to evaluate the morphology and perfusion features of the tumors, including the time-signal intensity curve (TIC), volume transfer constant (Ktrans), rate constant (Kep), extravascular extracellular space volume ratio (Ve) and initial area under the curve (IAUC). DCE-MRI parameters were correlated with histological grade, microvascular density (MVD), vascular endothelial growth factor (VEGF) and fraction of Ki67-positive cells and the serum level of cancer antigen 125 (CA125).ResultsThirty-five of the 46 rats developed EOCs. DCE-MRI showed type III TIC more frequently than type II (29/35 vs. 6/35, p < 0.001) in EOCs. The two types of TIC of tumors had significant differences in the histological grade, MVD, expression of VEGF and Ki67, and the serum level of CA125 (all p < 0.01). Ktrans, Kep and IAUC values showed significant differences in different histological grades in overall and pairwise comparisons except for IAUC in grade 2 vs. grade 3 (all p < 0.01). There was no significant difference in Ve values among the three grade groups (p > 0.05). Ktrans, Kep and IAUC values were positively correlated with MVD, VEGF and Ki67 expression (all p < 0.01). Ve was not significantly correlated with MVD, VEGF expression, Ki67 expression and the CA125 level (all p > 0.05).ConclusionsTIC types and perfusion parameters of DCE-MRI can reflect tumor grade, angiogenesis and cell proliferation to some extent, thereby helping treatment planning and predicting prognosis.

Correlation Between Tumor Metabolism and Semiquantitative Perfusion MRI Metrics in Non–small Cell Lung Cancer

To correlate semiquantitative parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) and 18F-fluorodeoxyglucose (FDG)-PET for non-small cell lung cancer (NSCLC). A total of 24 NSCLC patients who underwent pretreatment FDG-PET and DCE-MRI were analyzed. SUVmax was measured from FDG-PET. DCE-MRI was obtained on 3T MRI scanner using a 4D T1-weighted high resolution imaging method with volume excitation (4D THRIVE) sequence during free breathing to achieve high temporal resolution. A total of 130 dynamic sequences were obtained over a period of 4.3 minutes with 30 coronal slices, 2.5 mm slice thickness, TR/TE of 10/2.0 ms, FA of 15°, in-plane resolution of up to 2 mm, and temporal resolution of 2 seconds. A bolus injection of 0.2 mL/kg of Gd-DTPA (Magnevist) followed by saline flush was used. DCE-MRI parameters consisting of mean, median, standard deviation (SD) and median absolute deviation (MAD) of peak enhancement, wash-in-slope (WIS), wash-out-slope (WOS), time-to-peak (TTP), time-to-half-peak (TTHP), initial gradient, wash-out gradient, signal enhancement ratio and initial area under the relative signal enhancement curve before 30 seconds, 60 seconds, 90 seconds, 120 seconds, 150 seconds, 180 seconds, TTP and TTHP (IAUCtthp) were calculated for each lesion. Univariate analysis (UVA) was performed using Spearman correlation. A linear regression model to predict SUVmax from DCE-MRI parameters was developed by multivariate analysis (MVA) using least absolute shrinkage selection operator (LASSO) in combination with leave-one-out cross-validation (LOOCV). In UVA, mean(WOS) (r = -0.456, P = 0.025), mean(IAUCtthp) (r = -0.439, P = 0.032), median(IAUCtthp) (r = -0.543, P = 0.006), and MAD(IAUCtthp) (r = -0.557, P = 0.005) were statistically significant; all these parameters were negatively correlated with SUVmax. In MVA, a linear combination of SD(WIS), SD(TTP), MAD(TTHP), and MAD(IAUCtthp) was statistically significant for predicting SUVmax (LOOCV-based adjusted R2 = 0.298, P = 0.0006). Decrease in SD(WIS), MAD(TTHP), and MAD(IAUCtthp), and increase in SD(TTP) were associated with significant increase in SUVmax. Association was found between SUVmax of FDG-PET and SD and MAD of DCE-MRI metrics derived during Gd-DTPA uptake phase in NSCLC, reflecting that intratumoral heterogeneity of angiogenesis in wash-in phase is associated with tumor metabolism. MAD(IAUCtthp) was consistently significant in both UVA and MVA, suggesting that lower spatial heterogeneity in intensity and rapidity of contrast wash-in is associated with higher metabolic rate in NSCLC. This study will facilitate better understanding of complex relationship between tumor vascularization and metabolism, and eventually help in guiding targeted therapy.

Quantitative free-breathing dynamic contrast-enhanced MRI in hepatocellular carcinoma using gadoxetic acid: correlations with Ki67 proliferation status, histological grades, and microvascular density.

To validate a free-breathing dynamic contrast-enhanced-MRI (DCE-MRI) in hepatocellular carcinoma (HCC) patients using gadoxetic acid, and to determine the relationship between DCE-MRI parameters and histological results. Thirty-four HCC patients were included in this prospective study. Free-breathing DCE-MRI data was acquired preoperatively on a 3.0 Tesla scanner. Perfusion parameters (K trans, K ep, V e and the semi-quantitative parameter of initial area under the gadolinium concentration-time curve, iAUC) were calculated and compared with tumor enhancement at contrast-enhanced CT. The relationship between DCE-MRI parameters and Ki67 indices, histological grades and microvascular density (MVD) was determined by correlation analysis. Differences of perfusion parameters between different histopathological groups were compared. Receiver operation characteristic (ROC) analysis of discriminating high-grades (grade III and IV) from low-grades (grade I and II) HCC was performed for perfusion parameters. Significant relationship was found between DCE-MRI and CT results. The DCE-MRI derived K trans were significantly negatively correlated with Ki-67 indices (rho=-0.408, P=0.017) and the histological grades (rho=-0.444, P=0.009) of HCC, and K ep and V e were significantly related with tumor MVD (rho=-0.405, P=0.017 for K ep; and rho=0.385, P=0.024 for V e). K trans, K ep, and iAUC demonstrated moderate diagnostic performance (iAUC=0.78, 0.77 and 0.80, respectively) for discriminating high-grades from low-grades HCC without significant differences. The DCE-MRI derived parameters demonstrated weak but significant correlations with tumor proliferation status, histological grades or microvascular density, respectively. This free-breathing DCE-MRI is technically feasible and offers a potential avenue toward non-invasive evaluation of HCC malignancy.

Dynamic contrast-enhanced MRI in orbital lymphoproliferative disorders: Effects of region of interest selection methods on time efficiency, measurement reproducibility, and diagnostic ability.

Previous studies indicated that dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) could serve as a useful biomarker for differentiating malignant from benign orbital lymphoproliferative disorders (OLPDs). To investigate the influence of different region of interest (ROI) selection methods on the measurements of DCE-MRI parameters, and their diagnostic ability in discriminating malignant from benign OLPDs. Retrospective study. In all, 46 patients with OLPDs (22 benign and 24 malignant). 3.T DCE-MRI using a 2D turbo fast low angle shot sequence postcontrast. DCE-MRI data were analyzed using three different ROI selection methods, including whole-tumor ROI (ROIWT ), single-slice ROI (ROISS ) and hot-spot ROI (ROIHS ). Quantitative parameters (Ktrans , Kep , Ve ) were calculated based on a modified Tofts model. Analysis of variance test, intraclass correlation coefficient (ICC), Bland-Altman plots, independent t-test, and receiver operating characteristic curve analyses were used for statistical analyses. The time required for outlining ROIWT was significantly longer than ROISS and ROIHS (P < 0.001). The measurements of DCE-MRI-derived parameters based on ROIHS demonstrated lowest ICC, followed by ROISS and ROIWT . Malignant OLPDs showed significantly higher Kep than benign mimics (P < 0.001), while no significant differences were found on Ktrans (ROIWT , P = 0.535; ROISS , P = 0.557; ROIHS , P = 0.400) and Ve (ROIWT , P = 0.071; ROISS , P = 0.079; ROIHS , P = 0.057). Kep -ROIWT showed the highest area under curve for differentiating malignant from benign OLPDs, followed by Kep -ROISS , and Kep-ROIHS ; however, the differences were not significant (ROIWT vs. ROISS , P = 0.407; ROIWT vs. ROIHS , P = 0.363; ROISS vs. ROIHS , P = 0.887). ROI selection methods could have an influence on the measurements of DCE-MRI parameters. Taking measurement time, reproducibility, and diagnostic ability into account, we suggest single-slice ROI to be used for differentiating malignant from benign OLPDs in clinical practice. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1298-1305.

Preoperative predicting malignancy in breast mass-like lesions: value of adding histogram analysis of apparent diffusion coefficient maps to dynamic contrast-enhanced magnetic resonance imaging for improving confidence level.

This study aims to find out the benefits of adding histogram analysis of apparent diffusion coefficient (ADC) maps onto dynamic contrast-enhanced MRI (DCE-MRI) in predicting breast malignancy. This study included 95 patients who were found with breast mass-like lesions from January 2014 to March 2016 (47 benign and 48 malignant). These patients were estimated by both DCE-MRI and diffusion-weighted imaging (DWI) and classified into two groups, namely, the benign and the malignant. Between these groups, the DCE-MRI parameters, including morphology, enhancement homogeneity, maximum slope of increase (MSI) and time-signal intensity curve (TIC) type, as well as histogram parameters generated from ADC maps were compared. Then, univariate and multivariate logistic regression analyses were conducted to determine the most valuable variables in predicting malignancy. Receiver operating characteristic curve analyses were taken to assess their clinical values. The lesion morphology, MSI and TIC Type (p < 0.05) were significantly different between the two groups. Multivariate logistic regression analyses revealed that irregular morphology, TIC Type II/III and ADC10 were important predictors for breast malignancy. Increased area under curve (AUC) and specificity can be achieved with Model 2 (irregular morphology + TIC Type II/III + ADC10 < 1.047 ×10-3 mm2 s-1) as the criterion than Model 1 (irregular morphology + TIC Type II/III) only (Model 2 vs Model 1; AUC, 0.822 vs 0.705; sensitivity, 68.8 vs 75.0%; specificity, 95.7 vs 66.0%). Irregular morphology, TIC Type II/III and ADC10 are indicators for predicting breast malignancy. Histogram analysis of ADC maps can provide additional value in predicting breast malignancy. Advances in knowledge: The morphology, MSI and TIC types in DCE-MRI examination have significant difference between the benign and malignant groups. A higher AUC can be achieved by using ADC10 as the diagnostic index than other ADC parameters, and the difference in AUC based on ADC10 and ADCmean was statistically significant. The irregular morphology, TIC Type II/III and ADC10 were significant predictors for malignant lesions.

Quantitative analysis of permeability for glioma grading using dynamic contrast-enhanced magnetic resonance imaging.

The objective of the present study was to quantitatively analyze the permeability of tumor entity and peritumor edema in glioma grading, using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In the present retrospective study, 80 patients underwent T1-weighted DCE-MRI examination at 3.0 T and the pathological results (including astrocytoma and oligodendroglioma) were obtained between January 2012 and June 2015. All cases were surgically validated as grade I–IV gliomas. The original DCE-MRI data were analyzed using dual compartment modified Tofts model. The forward volume transfer constant (Ktrans), backflux rate (kep) and fractional volume (ve) were calculated with the region of interest selected on the highest permeability area of the tumor entity and peritumor edema. Analysis of variance with the Bonferroni correction was used to compare the values of Ktrans, kep, and ve of the tumor entity and peritumor edema in different glioma grades. The results of the present study revealed that the Ktrans, kep, and ve values in each stage were associated with the pathological grading (r=0.951, 0.804 and 0.766, respectively). There were significant differences identified between different tumor grades in Ktrans, kep, with the exception being between grades II and III in kep. In addition, there was a significant difference revealed between grade I/II and grade III/IV in ve. Receiver operator characteristics curve analysis was used to evaluate the diagnosis accuracies of permeability parameters. Ktrans was demonstrated to exhibit the highest sensitivity and specificity for evaluating the tumor grade. With the threshold values of 0.160, 0.420 and 0.935 in Ktrans on tumor, glioma grades I vs. II, II vs III and III vs. IV may be differentiated with sensitivities of 0.900, 0.950 and 0.950, and specificities of 0.950, 0.950 and 0.850, respectively. Furthermore, associations were observed between the Ktrans, kep and ve values of peritumor edema and the pathological grading in glioma (Ktrans r=0.438, P<0.001; Kep r=0.385, P<0.001; Ve r=0.397, P<0.001, respectively). Ktrans values in peritumoral edema revealed significant differences between low-grade and high-grade glioma. The sensitivity and specificity for Ktrans of peritumor edema were 0.975 and 0.950, with a threshold value of 0.007. Therefore, the DCE-MRI parameters of Ktrans of tumor entity and peritumor edema in gliomas may be used to accurately differentiate glioma grades.

Volume fractions of DCE-MRI parameter as early predictor of histologic response in soft tissue sarcoma: A feasibility study

ObjectiveTo find early predictors of histologic response in soft tissue sarcoma through volume transfer constant (Ktrans) analysis based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Materials and methods11 Patients with soft tissue sarcoma of the lower extremity that underwent preoperative chemoradiotherapy followed by limb salvage surgery were included in this retrospective study. For each patient, DCE-MRI data sets were collected before and two weeks after therapy initiation, and histologic tumor cell necrosis rate (TCNR) was reported at surgery. The DCE-MRI volumes were aligned by registration. Then, the aligned volumes were used to obtain the Ktrans variation map. Accordingly, three sub-volumes (with increased, decreased or unchanged Ktrans) were defined and identified, and fractions of the sub-volumes, denoted as F+, F- and F0, respectively, were calculated. The predictive ability of volume fractions was determined by using area under a receiver operating characteristic curve (AUC). Linear regression analysis was performed to investigate the relationship between TCNR and volume fractions. In addition, the Ktrans values of the sub-volumes were compared. ResultsThe AUC for F- (0.896) and F0 (0.833) were larger than that for change of tumor longest diameter ΔD (0.625) and the change of mean KtransΔKtrans¯ (0.792). Moreover, the regression results indicated that TCNR was directly proportional to F0 (R2=0.75, P=0.0003), while it was inversely proportional to F- (R2=0.77, P=0.0002). However, TCNR had relatively weak linear relationship with ΔKtrans¯ (R2=0.64, P=0.0018). Additionally, TCNR did not have linear relationship with DD (R2=0.16, P=0.1246). ConclusionThe volume fraction F- and F0 have potential as early predictors of soft tissue sarcoma histologic response.

Textural features of dynamic contrast-enhanced MRI derived model-free and model-based parameter maps in glioma grading.

Presurgical glioma grading by dynamic contrast-enhanced MRI (DCE-MRI) has unresolved issues. The aim of this study was to investigate the ability of textural features derived from pharmacokinetic model-based or model-free parameter maps of DCE-MRI in discriminating between different grades of gliomas, and their correlation with pathological index. Retrospective. Forty-two adults with brain gliomas. 3.0T, including conventional anatomic sequences and DCE-MRI sequences (variable flip angle T1-weighted imaging and three-dimensional gradient echo volumetric imaging). Regions of interest on the cross-sectional images with maximal tumor lesion. Five commonly used textural features, including Energy, Entropy, Inertia, Correlation, and Inverse Difference Moment (IDM), were generated. All textural features of model-free parameters (initial area under curve [IAUC], maximal signal intensity [Max SI], maximal up-slope [Max Slope]) could effectively differentiate between grade II (n = 15), grade III (n = 13), and grade IV (n = 14) gliomas (P < 0.05). Two textural features, Entropy and IDM, of four DCE-MRI parameters, including Max SI, Max Slope (model-free parameters), vp (Extended Tofts), and vp (Patlak) could differentiate grade III and IV gliomas (P < 0.01) in four measurements. Both Entropy and IDM of Patlak-based Ktrans and vp could differentiate grade II (n = 15) from III (n = 13) gliomas (P < 0.01) in four measurements. No textural features of any DCE-MRI parameter maps could discriminate between subtypes of grade II and III gliomas (P < 0.05). Both Entropy and IDM of Extended Tofts- and Patlak-based vp showed highest area under curve in discriminating between grade III and IV gliomas. However, intraclass correlation coefficient (ICC) of these features revealed relatively lower inter-observer agreement. No significant correlation was found between microvascular density and textural features, compared with a moderate correlation found between cellular proliferation index and those features. Textural features of DCE-MRI parameter maps displayed a good ability in glioma grading. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1099-1111.

Application of Dynamic Contrast-Enhanced MRI in the Therapeutic Evaluation of the Chinese Medicine Kanglaite in Treating Colorectal Cancer

Background: Magnetic resonance imaging (MRI) can provide a reference for tumor treatment and its quantitative parameters can serve as imaging indicators that reflect tumor angiogenesis and vascularity. Kanglaite (KLT) has therapeutic effects on cancers. In this study, DCE-MRI was used to investigate its application in evaluating KLT anti-colorectal cancer. Objectives: Evaluating the efficacy of Kanglaite (KLT) injection for treatment of colorectal cancer with dynamic contrast-enhanced MRI (DCE-MRI) parameters. Methods: This study was an experimental study. The 20 successfully modeled nude mice were randomly assigned to 2 groups: blank control group (n = 10) and the KLT injection group (n = 10). The research protocol was approved by the ethics committee of the second affiliated hospital of Xinjiang medical university (protocol NO: 20140216-12) in 2015. A subcutaneous xenograft colorectal tumor model was subjected to KLT treatment. DCE-MRI obtain the parameters including Ktrans, Ve, Kep, Vp, immunohistochemical staining measure microvascular density (MVD), levels of vascular endothelial growth factor (VEGF), and proliferating cell nuclear antigen (PCNA). Results: Compared to the blank control, the volume of tumor in the KLT group markedly reduced by 49%. 48 hours after, compared to the blank control, the Ktrans (0.028 ± 0.009 vs 0.012 ± 0.006), Ve (0.312 ± 0.089 vs 0.287 ± 0.037), and Kep values (0.321 ± 0.056 vs 0.577 ± 0.033) decreased in KLT group (P < 0.05). In contrast, the Vp value (0.094 ± 0.037 vs 0.043 ± 0.017) was significantly elevated in the KLT group (P < 0.05). There is a correlation between Ktrans, Kep and VEGF score, MVD count, and PCNA score. Conclusions: The parameters of DCE-MRI may be used as imaging biomarkers for assessing the status of tumor-bearing vasculatures and provide a basis for evaluating the efficacy of anti-tumor drugs.

Assessment of therapeutic response in Crohn's disease using quantitative dynamic contrast enhanced MRI (DCE-MRI) parameters

The aim of the study was to investigate dynamic contrast enhanced MRI (DCE-MRI) as a potential marker to assess the therapeutic responses of fecal microbiota transplantation (FMT) in patients with Crohn's disease (CD) and to determine the parameter or combination of parameters most strongly associated with changes in clinical indicators after treatment.In 22 CD patients, DCE-MRI was performed with a 3.0T scanner. Parameters of DCE-MRI (vascular transfer constant [Ktrnas] and blood volume [BV]) in the terminal ileum were compared between before and day 90 after FMT treatment. The differences of clinical indicators (C-reactive protein [CRP], Harvey–Bradshaw index [HBI]) and DCE-MRI parameters (Ktrnas, BV) between pre- and post-treatment was calculated by Student's 2-tailed, paired t-test. The correlations between percent change of clinical indicators (ΔCRP, ΔHBI) with DCE-MRI parameters (ΔKtrnas, ΔBV) were analyzed by Pearson's correlation coefficients. A logistic regression model was used to identify the changes of DCE-MRI parameters related to the treatment outcomes. Receiver operating characteristic curves (ROCs) were generated to assess which DCE-MRI parameter showed the best accuracy for evaluation of therapeutic response.After treatment, mean values of clinical indicators decreased significantly (CRP: 62.68 ± 31.86 vs 43.55 ± 29.63 mg/L, P = .008; HBI: 7.18 ± 2.10 vs 5.73 ± 2.33, P = 0.012). Both DCE-MRI parameters showed prominent differences before and after treatment: Ktrans (1.86 ± 0.87 vs 1.39 ± 0.83 min−1, P = .017), BV (61.02 ± 28.49 vs 41.96 ± 22.75 mL/100 g, P = .005). There were significant correlations between ΔCRP or ΔHBI and percent change of CDE-MRI parameters (ΔKtrans to ΔCRP: 0.659; ΔKtrans to ΔHBI: 0.496; ΔBV to ΔCRP: 0.442; ΔBV to ΔHBI: 0.476). Compared to ΔKtrans and ΔBV individually, the combination of both parameters performed best in assessment of therapeutic response with an area under the ROCs (AUC) of 0.948.Ktrans and BV parameters derived from DCE-MRI have the potential to assess for therapeutic response after FMT treatment for CD. The combination of Ktrans and BV measurements improved the predictive capability compared to the individual parameters.

Quantitative in vivo imaging of tissue factor expression in glioma using dynamic contrast-enhanced MRI derived parameters

ObjectiveTissue Factor (TF) has been well established in angiogenesis, invasion, metastasis, and prognosis in glioma. A noninvasive assessment of TF expression status in glioma is therefore of obvious clinical relevance. Dynamic contrast-enhanced (DCE) MRI parameters have been used to evaluate microvascular characteristics and predict molecular expression status in tumors. Our aim is to investigate whether quantitative DCE-MRI parameters could assess TF expression in glioma. Materials and methodsThirty-two patients with histopathologically diagnosed supratentorial glioma who underwent DCE-MRI were retrospectively recruited. Extended Tofts linear model was used for DCE-MRI post-processing. Hot-spot, whole tumor cross-sectional approaches, and histogram were used for analysis of model based parameters. Four serial paraffin sections of each case were stained with TF, CD105, CD34 and α-Sooth Muscle Actin, respectively for evaluating the association of TF and microvascular properties. Pearson correlation was performed between percentage of TF expression area and DCE-MRI parameters, multiple microvascular indexes. ResultsVolume transfer constant (Ktrans) hot-spot value best correlated with TF (r=0.886, p<0.001), followed by 90th percentile Ktrans value (r=0.801, p<0.001). Moreover, histogram analysis of Ktrans value demonstrated that weak TF expression was associated with less heterogeneous and positively skewed distribution. Finally, pathology analysis revealed TF was associated with glioma grade and significantly correlated with these two dynamic angiogenic indexes which could be used to explain the strong correlation between Ktrans and TF expression. ConclusionOur results indicate that Ktrans may serve as a potential clinical imaging biomarker to predict TF expression status preoperatively in gliomas.

Association of parameters in dynamic contrast-enhanced MRI using reference region model with prognostic factors and molecular subtypes of breast cancer

To investigate the association of parameters in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using reference region model with prognostic factors and molecular subtypes of breast cancer. MRI and pathological data of 50 patients with pathologically confirmed invasive ductal carcinoma of the breast were retrospectively analyzed. Reference region model was applied to analyze pharmacokinetic quantitative parameters including volume transfer constant (RR Ktrans), rate constant (Kep) and the ratio of Ktrans to extracellular space volume (Ktrans/Ve). The associations of the above parameters with prognostic factors and molecular subtypes of breast cancer were analyzed. RR Ktrans and Kep were significantly higher in patients of histological grade 3 compared with those of histological grade 1 & 2 (all P<0.05); and the patients with estrogen receptor (ER)-negative and/or progesterone receptor (PR)-negative also had higher RR Ktrans and Kep than those with ER-positive or PR-positive (all P<0.05). For immunohistochemistry, RR Ktrans and Kep were significantly higher in triple negative breast cancer compared with luminal type breast cancer (all P<0.05). High RR Ktrans and Kep are associated with poor prognosis of breast cancer, and which can also be used to distinguish molecular subtypes of breast cancer.

Correlation between histogram analysis of dynamic contrast enhanced MRI and diffusion weighted imaging intravoxel incoherent motion quantitative parameters and Gleason score of prostate cancer

Objective To investigate the value and diagnostic efficiency of the quantitative dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) and intravoxel incoherent motion (IVIM) parameters using three dimention (3D)-histogram analysis for discriminating the Gleason score (GS) of prostate cancer. Methods A total of 53 patients pathologically confirmed as prostate cancer by systemic prostate biopsy who had routine, DCE and DWI-MRI scans were retrospectively analyzed. There were 15 cases for low-risk and 38 cases for intermediate/high-risk prostate cancer. The 3D ROI of all lesions based on T2WI was achieved by image registration to get the quantitative parameters of DCE-MRI and DWI-IVIM. The parameters of DCE-MRI contains: transfer constant (Ktrans), rate constant (Kep) and extracellular-extravascular volume fraction (Ve).The DWI-IVIM related quantitative parameters were ADC, diffusion coefficient (D), diffusion coefficient related to perfusion (D*) and perfusion fraction (f). Then the histogram analysis of these quantitative parameters was performed to get the mean, median, 25th percentile, 75th percentile, Skewness and Kurtosis. Using the Spearman rank correlation analysis to evaluate the correlation of these parameters and GS of prostate cancer. The diagnostic performance of these quantitative histogram parameters related to the GS in identifying low-risk and intermediate/high-risk of prostate cancer was carried by ROC. Results The Kep and Ktrans (mean, median, 25th, 75th) of DCE-MRI were positively correlated with GS (r value was 0.346 to 0.696, P<0.05). The ADC (mean, median, 25th, 75th), D (mean, median, 25th, 75th, Skewness, Kurtosis) and D*(25th) of DWI-IVIM were correlated with GS (r value was -0.544 to 0.428, P<0.05). The DCE-MRI quantitative parameters Kep (25th) had the highest area under curve (AUC, 0.961); The ADC (median) and D (25th) had higher AUC (0.832, 0.888) in the quantitative parameters of DWI-IVIM, the difference between Kep(25th) and ADC (median) was statistically significant (Z value was 2.212, P value was 0.027). The difference of AUC between Kep (25th) and D (25th), D (25th) and ADC (median) was not statistically significant (Z values were 1.027 and 1.398, P values were 0.162 and 0.304, respectively). Conclusion DCE and IVIM quantitative parameters (Kep, Ktrans, ADC, D) histogram analysis results are correlated with GS, and can be used for distinguishing low-risk from intermediate/high-risk prostate cancer. Key words: Prostate neoplasms; Magnetic resonance imaging; Comparative study

Dynamic Contrast-enhanced MR Imaging Parameters in Bone Metastases from Non-Small Cell Lung Cancer: Comparison between Lesions with and Lesions without Epidermal Growth Factor Receptor Mutation in Primary Lung Cancer.

Purpose To compare dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging parameters between metastatic bone lesions with and without the epidermal growth factor receptor (EGFR) mutation in consecutive patients with primary non-small cell lung cancer (NSCLC). Materials and Methods This study was approved by the institutional review board. Forty-seven patients with NSCLC and a confirmed EGFR mutation status (27 patients were positive and 26 were negative for EGFR mutation), who underwent DCE MR imaging for bone metastases between November 2012 and March 2016, were included in this study. Two radiologists independently analyzed the volume transfer constant (Ktrans), reflux rate (kep), and volume fraction of the extravascular extracellular matrix (ve) using image processing software. Intergroup comparisons of the mean measured parameters were performed with the Mann-Whitney U test. Interobserver agreement was calculated with the intraclass correlation coefficient. Results There was a high level of agreement between the two reviewers for all three parameters (intraclass correlation coefficient = 0.95 for Ktrans, 0.97 for kep, and 0.91 for ve). Ktrans was significantly higher in the EGFR mutation-positive group (P = .039 for reviewer 1, P = .032 for reviewer 2). kep was also higher in the EGFR mutation-positive group but showed statistical significance only in the evaluation performed by one reviewer (P = .048 for reviewer 2, P = .058 for reviewer 1). No significant difference was observed in ve (P = .873 for reviewer 1, P = .889 for reviewer 2). Conclusion The differences in the DCE MR imaging parameters between metastatic bone lesions with and without EGFR mutations in primary NSCLC may be attributed to differences in the vascular structure related to angiogenesis stimulated by the activation of the EGFR signaling pathway. © RSNA, 2017 Online supplemental material is available for this article.

Effects of arterial input function selection on kinetic parameters in brain dynamic contrast-enhanced MRI

PurposeKinetic parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) were suggested as a possible instrument for multi-parametric lesion characterization, but have not found their way into clinical practice yet due to inconsistent results. The quantification is heavily influenced by the definition of an appropriate arterial input functions (AIF). Regarding brain tumor DCE-MRI, there are currently several co-existing methods to determine the AIF frequently including different brain vessels as sources. This study quantitatively and qualitatively analyzes the impact of AIF source selection on kinetic parameters derived from commonly selected AIF source vessels compared to a population-based AIF model. Material and methods74 patients with brain lesions underwent 3D DCE-MRI. Kinetic parameters [transfer constants of contrast agent efflux and reflux Ktrans and kep and, their ratio, ve, that is used to measure extravascular-extracellular volume fraction and plasma volume fraction vp] were determined using extended Tofts model in 821 ROI from 4 AIF sources [the internal carotid artery (ICA), the closest artery to the lesion, the superior sagittal sinus (SSS), the population-based Parker model]. The effect of AIF source alteration on kinetic parameters was evaluated by tissue type selective intra-class correlation (ICC) and capacity to differentiate gliomas by WHO grade [area under the curve analysis (AUC)]. ResultsArterial AIF more often led to implausible ve >100% values (p<0.0001). AIF source alteration rendered different absolute kinetic parameters (p<0.0001), except for kep. ICC between kinetic parameters of different AIF sources and tissues were variable (0.08–0.87) and only consistent >0.5 between arterial AIF derived kinetic parameters. Differentiation between WHO III and II glioma was exclusively possible with vp derived from an AIF in the SSS (p=0.03; AUC 0.74). ConclusionThe AIF source has a significant impact on absolute kinetic parameters in DCE-MRI, which limits the comparability of kinetic parameters derived from different AIF sources. The effect is also tissue-dependent. The SSS appears to be the best choice for AIF source vessel selection in brain tumor DCE-MRI as it exclusively allowed for WHO grades II/III and III/IV glioma distinction (by vp) and showed the least number of implausible ve values.

Application on the quantitative perfusion parameters of dynamic contrast-enhanced MRI in the pathological subtype of uterine leiomyoma

Objective: To analyze the value of the quantitative perfusion parameters of dynamic contrast-enhanced MRI(DCE-MRI) in the pathological subtype of uterine leiomyoma. Methods: A total of 35 cases of uterine leiomyoma confirmed by surgery and pathology were retrospectively analyzed in Shaoxing People's Hospital from October 2015 to May 2016.All cases underwent DCE-MRI. Quantitative perfusion parameters were prospectively measured and analyzed, including transfer constant (K(trans)) , efflux rate constant (K(ep)), extravascular extracellular space volume ratio (V(e)), blood plasma volume ratio (V(p)), permeability surface area product (PS) and plasma flow (F(p)) , using signal-input two-compartment tracer kinetic models (Extended Tofts model and Exchange model) in 35 leiomyoma cases.After the operation, the 35 cases were divided into three groups according to the pathological classfication , the ordinary, the cellular and the degeneration type.To analyze the differences among the three groups about the quantitative perfusion parameters of uterine leiomyoma. Compared with the gold standard of pathological findings, the ROC curves were drawn to evaluate the diagnostic efficacy of different quantitative perfusion parameters. Results: In the ordinary, cellular and degeneration type of uterine leiomyoma, K(trans) value were respectively(0.684±0.341), (1.897±0.458), (0.554±0.514)/min; K(ep) were respectively(1.004±0.685), (2.362±1.001), (1.274±1.093)/min; V(e) were respectively 0.789%±0.186%, 0.806%±0.203%, 0.537%±0.314%; V(p) were respectively 0.145%±0.196%, 0.502%±0.338%, 0.062%±0.106% and F(p) were respectively(0.792±0.461), (2.426±0.509), (0.628±0.551)ml/min.Among three groups, the value of K(trans), K(ep), V(e), V(p) and F(p) had statistical difference(all P<0.05), the value of PS didn't have statistical difference. The value of K(trans), K(ep), V(p) and F(p) in cellular type were higher than the ordinary type(all P<0.01); the value of K(trans), V(p) and F(p) in cellular type were higher than the degeneration type(all P<0.01); the value of V(e) in ordinary type was higher than the degeneration type(P<0.05). The area under ROC curve was 0.981 for K(trans), 0.904 for K(ep), 0.622 for V(e), 0.840 for V(p) and 0.994 for F(p). Conclusion: The quantitative perfusion parameters of DCE-MRI , especially the value of K(trans), K(ep), V(p) and F(p) have a great diagnostic efficacy in the pathological classfication of uterine leiomyoma which will become a predictive factor of pathological classfication in uterine leiomyoma.