Quantitative pharmacokinetic analysis of prostate cancer DCE-MRI at 3T: comparison of two arterial input functions on cancer detection with digitized whole mount histopathological validation

Effectiveness of Dynamic Contrast Enhanced MRI with a Split Dose of Gadoterate Meglumine for Detection of Prostate Cancer

RATIONALE AND OBJECTIVES

To evaluate whether dynamic contrast enhanced (DCE) MRI with a split injection of 30% followed by 70% of a standard dose (30PSD and 70PSD) of gadoterate meglumine (DOTAREM) can improve diagnosis of prostate cancer (PCa).

MATERIALS AND METHODS

MRI for twenty patients was performed on a Philips Ingenia 3T scanner without an endorectal coil followed by subsequent radical prostatectomy. DCE 3D T1-FFE data were acquired with injection of 0.03 mmol/kg followed after 2 minutes by 0.07 mmol/kg of DOTAREM. Regions-of-interest on histologically verified PCa and normal tissue in different prostate zones and the iliac artery were drawn. Average signal intensity as function of time was calculated for each ROI and fitted by using the signal intensity form of the Tofts (SI-Tofts) model to extract physiological parameters (K^trans and v_e). In addition, the scaled arterial input function (AIF) obtained from 30PSD data was used to analyze 70PSD data.

RESULTS

The AIF obtained from 30PSD data showed both first and second passes clearly and had much higher peak magnitude than AIFs from 70PSD data. K^trans was significantly (p < 0.05) larger in PCa than in normal tissue in peripheral zone (PZ) and central zone (CZ) for both 70PSD and 70PSD data analyzed with a scaled AIF. K^trans in cancer overlapped with that of normal tissue in the transition zone (TZ). There was no statistical difference in v_e between cancer and normal tissue. Receiver operating characteristic analysis showed that use of the AIF from 30PSD data to analyze 70PSD data increased the diagnostic efficacy of K^trans in the PZ and CZ.

CONCLUSION

The split dose protocol for injection of Dotarem increased diagnostic accuracy of quantitative analysis with the SI-Tofts model.

A Pilot Study of Multidimensional Diffusion MRI for Assessment of Tissue Heterogeneity in Prostate Cancer

OBJECTIVES

The objectives of this exploratory study were to investigate the feasibility of multidimensional diffusion magnetic resonance imaging (MddMRI) in assessing diffusion heterogeneity at both a macroscopic and microscopic level in prostate cancer (PCa).

MATERIALS AND METHODS

Informed consent was obtained from 46 subjects who underwent 3.0-T prostate multiparametric MRI, complemented with a prototype spin echo-based MddMRI sequence in this institutional review board-approved study. Prostate cancer tumors and comparative normal tissue from each patient were contoured on both apparent diffusion coefficient and MddMRI-derived mean diffusivity (MD) maps (from which microscopic diffusion heterogeneity [MKi] and microscopic diffusion anisotropy were derived) using 3D Slicer. The discriminative ability of MddMRI-derived parameters to differentiate PCa from normal tissue was determined using the Friedman test. To determine if tumor diffusion heterogeneity is similar on macroscopic and microscopic scales, the linear association between SD of MD and mean MKi was estimated using robust regression (bisquare weighting). Hypothesis testing was 2 tailed; P values less than 0.05 were considered statistically significant.

RESULTS

All MddMRI-derived parameters could distinguish tumor from normal tissue in the fixed-effects analysis (P < 0.0001). Tumor MKi was higher (P < 0.05) compared with normal tissue (median, 0.40; interquartile range, 0.29-0.52 vs 0.20-0.18; 0.25), as was tumor microscopic diffusion anisotropy (0.55; 0.36-0.81 vs 0.20-0.15; 0.28). The MKi could not be predicted (no significant association) by SD of MD. There was a significant correlation between tumor volume and SD of MD (R2 = 0.50, slope = 0.008 μm2/ms per millimeter, P < 0.001) but not between tumor volume and MKi.

CONCLUSIONS

This explorative study demonstrates that MddMRI provides novel information on MKi and microscopic anisotropy, which differ from measures at the macroscopic level. MddMRI has the potential to characterize tumor tissue heterogeneity at different spatial scales.

Differentiation between glioblastoma and primary CNS lymphoma: application of DCE-MRI parameters based on arterial input function obtained from DSC-MRI

OBJECTIVE

This study aimed to evaluate whether arterial input functions (AIFs) obtained from dynamic susceptibility contrast (DSC)-MRI (AIF_DSC) improve the reliability and diagnostic accuracy of dynamic contrast-enhanced (DCE)-derived pharmacokinetic (PK) parameters for differentiating glioblastoma from primary CNS lymphoma (PCNSL) compared with AIFs derived from DCE-MRI (AIF_DCE).

METHODS

This retrospective study included 172 patients with glioblastoma (n = 147) and PCNSL (n = 25). All patients had undergone preoperative DSC- and DCE-MRI. The volume transfer constant (K^trans), volume of the vascular plasma space (v_p), and volume of the extravascular extracellular space (v_e) were acquired using AIF_DSC and AIF_DCE. The relative cerebral blood volume (rCBV) was obtained from DSC-MRI. Intraclass correlation coefficients (ICC) and ROC curves were used to assess the reliability and diagnostic accuracy of individual parameters.

RESULTS

The mean K^trans, v_p, and v_e values revealed better ICCs with AIF_DSC than with AIF_DCE (K^trans, 0.911 vs 0.355; v_p, 0.766 vs 0.503; v_e, 0.758 vs 0.657, respectively). For differentiating all glioblastomas from PCNSL, the mean rCBV (AUC = 0.856) was more accurate than the AIF_DSC-driven mean K^trans, which had the largest AUC (0.711) among the DCE-derived parameters (p = 0.02). However, for glioblastomas with low rCBV (≤ 75th percentile of PCNSL; n = 30), the AIF_DSC-driven mean K^trans and v_p were more accurate than rCBV (AUC: K^trans, 0.807 vs rCBV, 0.515, p = 0.004; v_p, 0.715 vs rCBV, p = 0.045).

CONCLUSION

DCE-derived PK parameters using the AIF_DSC showed improved reliability and diagnostic accuracy for differentiating glioblastoma with low rCBV from PCNSL.

KEY POINTS

• An accurate differential diagnosis of glioblastoma and PCNSL is crucial because of different therapeutic strategies. • In contrast to the rCBV from DSC-MRI, another perfusion imaging technique, the DCE parameters for the differential diagnosis have been limited because of the low reliability of AIFs from DCE-MRI. • When we analyzed DCE-MRI data using AIFs from DSC-MRI (AIF_DSC), AIF_DSC-driven DCE parameters showed improved reliability and better diagnostic accuracy than rCBV for differentiating glioblastoma with low rCBV from PCNSL.

Use of Indicator Dilution Principle to Evaluate Accuracy of Arterial Input Function Measured With Low-Dose Ultrafast Prostate Dynamic Contrast-Enhanced MRI

Accurately measuring arterial input function (AIF) is essential for quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI). We used the indicator dilution principle to evaluate the accuracy of AIF measured directly from an artery following a low-dose contrast media ultrafast DCE-MRI. In total, 15 patients with biopsy-confirmed localized prostate cancers were recruited. Cardiac MRI (CMRI) and ultrafast DCE-MRI were acquired on a Philips 3 T Ingenia scanner. The AIF was measured at iliac arties following injection of a low-dose (0.015 mmol/kg) gadolinium (Gd) contrast media. The cardiac output (CO) from CMRI (CO_CMRI) was calculated from the difference in ventricular volume at diastole and systole measured on the short axis of heart. The CO from DCE-MRI (CO_DCE) was also calculated from the AIF and dose of the contrast media used. A correlation test and Bland–Altman plot were used to compare CO_CMRI and CO_DCE. The average (±standard deviation [SD]) area under the curve measured directly from local AIF was 0.219 ± 0.07 mM·min. The average (±SD) CO_CMRI and CO_DCE were 6.52 ± 1.47 L/min and 6.88 ± 1.64 L/min, respectively. There was a strong positive correlation (r = 0.82, P < .01) and good agreement between CO_CMRI and CO_DCE. The CO_DCE is consistent with the reference standard CO_CMRI. This indicates that the AIF can be measured accurately from an artery with ultrafast DCE-MRI following injection of a low-dose contrast media.

Investigating the role of DCE-MRI, over T2 and DWI, in accurate PI-RADS v2 assessment of clinically significant peripheral zone prostate lesions as defined at radical prostatectomy

PURPOSE

PI-RADS v2 dictates that dynamic contrast-enhanced (DCE) imaging be used to further classify peripheral zone (PZ) cases that receive a diffusion-weighted imaging equivocal score of three (DWI3), a positive DCE resulting in an increase in overall assessment score to a four, indicative of clinically significant prostate cancer (csPCa). However, the accuracy of DCE in predicting csPCa in DWI3 PZ cases is unknown. This study sought to determine the frequency with which DCE changes the PI-RADS v2 DWI3 assessment category, and to determine the overall accuracy of DCE-MRI in equivocal PZ DWI3 lesions.

MATERIALS AND METHODS

This is a retrospective study of patients with pathologically proven PCa who underwent prostate mpMRI at 3T and subsequent radical prostatectomy. PI-RADS v2 assessment categories were determined by a radiologist, aware of a diagnosis of PCa, but blinded to final pathology. csPCa was defined as a Gleason score ≥ 7 or extra prostatic extension at pathology review. Performance characteristics and diagnostic accuracy of DCE in assigning a csPCa assessment in PZ lesions were calculated.

RESULTS

A total of 271 men with mean age of 59 ± 6 years mean PSA 6.7 ng/mL were included. csPCa was found in 212/271 (78.2%) cases at pathology, 209 of which were localized in the PZ. DCE was necessary to further classify (45/209) of patients who received a score of DWI3. DCE was positive in 29/45 cases, increasing the final PI-RADS v2 assessment category to a category 4, with 16/45 having a negative DCE. When compared with final pathology, DCE was correct in increasing the assessment category in 68.9% ± 7% (31/45) of DWI3 cases.

CONCLUSION

DCE increases the accuracy of detection of csPCa in the majority of PZ lesions that receive an equivocal PI-RADS v2 assessment category using DWI.

Predictive role of PI-RADSv2 and ADC parameters in differentiating Gleason pattern 3 + 4 and 4 + 3 prostate cancer

PURPOSE

To compare the predictive roles of qualitative (PI-RADSv2) and quantitative assessment (ADC metrics), in differentiating Gleason pattern (GP) 3 + 4 from the more aggressive GP 4 + 3 prostate cancer (PCa) using radical prostatectomy (RP) specimen as the reference standard.

METHODS

We retrospectively identified treatment-naïve peripheral (PZ) and transitional zone (TZ) Gleason Score 7 PCa patients who underwent multiparametric 3T prostate MRI (DWI with b value of 0,1400 and where unavailable, 0,500) and subsequent RP from 2011 to 2015. For each lesion identified on MRI, a PI-RADSv2 score was assigned by a radiologist blinded to pathology data. A PI-RADSv2 score ≤ 3 was defined as "low risk," a PI-RADSv2 score ≥ 4 as "high risk" for clinically significant PCa. Mean tumor ADC (ADCT), ADC of adjacent normal tissue (ADCN), and ADCratio (ADCT/ADCN) were calculated. Stepwise regression analysis using tumor location, ADCT and ADCratio, b value, low vs. high PI-RADSv2 score was performed to differentiate GP 3 + 4 from 4 + 3.

RESULTS

119 out of 645 cases initially identified met eligibility requirements. 76 lesions were GP 3 + 4, 43 were 4 + 3. ADCratio was significantly different between the two GP groups (p = 0.001). PI-RADSv2 score ("low" vs. "high") was not significantly different between the two GP groups (p = 0.17). Regression analysis selected ADCT (p = 0.03) and ADCratio (p = 0.0007) as best predictors to differentiate GP 4 + 3 from 3 + 4. Estimated sensitivity, specificity, and accuracy of the predictive model in differentiating GP 4 + 3 from 3 + 4 were 37, 82, and 66%, respectively.

CONCLUSIONS

ADC metrics could differentiate GP 3 + 4 from 4 + 3 PCa with high specificity and moderate accuracy while PI-RADSv2, did not differentiate between these patterns.

Robust and efficient pharmacokinetic parameter non-linear least squares estimation for dynamic contrast enhanced MRI of the prostate

PURPOSE

To describe an efficient numerical optimization technique using non-linear least squares to estimate perfusion parameters for the Tofts and extended Tofts models from dynamic contrast enhanced (DCE) MRI data and apply the technique to prostate cancer.

METHODS

Parameters were estimated by fitting the two Tofts-based perfusion models to the acquired data via non-linear least squares. We apply Variable Projection (VP) to convert the fitting problem from a multi-dimensional to a one-dimensional line search to improve computational efficiency and robustness. Using simulation and DCE-MRI studies in twenty patients with suspected prostate cancer, the VP-based solver was compared against the traditional Levenberg-Marquardt (LM) strategy for accuracy, noise amplification, robustness to converge, and computation time.

RESULTS

The simulation demonstrated that VP and LM were both accurate in that the medians closely matched assumed values across typical signal to noise ratio (SNR) levels for both Tofts models. VP and LM showed similar noise sensitivity. Studies using the patient data showed that the VP method reliably converged and matched results from LM with approximate 3× and 2× reductions in computation time for the standard (two-parameter) and extended (three-parameter) Tofts models. While LM failed to converge in 14% of the patient data, VP converged in the ideal 100%.

CONCLUSION

The VP-based method for non-linear least squares estimation of perfusion parameters for prostate MRI is equivalent in accuracy and robustness to noise, while being more reliably (100%) convergent and computationally about 3× (TM) and 2× (ETM) faster than the LM-based method.

Differentiation of High-Grade from Low-Grade Astrocytoma: Improvement in Diagnostic Accuracy and Reliability of Pharmacokinetic Parameters from DCE MR Imaging by Using Arterial Input Functions Obtained from DSC MR Imaging

Purpose To evaluate whether arterial input functions (AIFs) derived from dynamic susceptibility-contrast (DSC) magnetic resonance (MR) imaging, or AIF_DSC values, improve diagnostic accuracy and reliability of the pharmacokinetic (PK) parameters of dynamic contrast material-enhanced (DCE) MR imaging for differentiating high-grade from low-grade astrocytomas, compared with AIFs obtained from DCE MR imaging (AIF_DCE). Materials and Methods This retrospective study included 226 patients (138 men, 88 women; mean age, 52.27 years ± 15.17; range, 24-84 years) with pathologically confirmed astrocytomas (World Health Organization grade II = 21, III = 53, IV = 152; isocitrate dehydrogenase mutant, 11.95% [27 of 226]; 1p19q codeletion 0% [0 of 226]). All patients underwent both DSC and DCE MR imaging before surgery, and AIF_DSC and AIF_DCE were obtained from each image. Volume transfer constant (K^trans), volume of vascular plasma space (v_p), and volume of extravascular extracellular space (v_e) were processed by using postprocessing software with two AIFs. The diagnostic accuracies of individual parameters were compared by using receiver operating characteristic curve (ROC) analysis. Intraclass correlation coefficients (ICCs) and the Bland-Altman method were used to assess reliability. Results The AIF_DSC-driven mean K^trans and v_e were more accurate for differentiating high-grade from low-grade astrocytoma than those derived by using AIF_DCE (area under the ROC curve: mean K^trans, 0.796 vs 0.645, P = .038; mean v_e, 0.794 vs 0.658, P = .020). All three parameters had better ICCs with AIF_DSC than with AIF_DCE (K^trans, 0.737 vs 0.095; v_p, 0.848 vs 0.728; v_e, 0.875 vs 0.581, respectively). In AIF analysis, maximal signal intensity (0.837 vs 0.524) and wash-in slope (0.800 vs 0.432) demonstrated better ICCs with AIF_DSC than AIF_DCE. Conclusion AIF_DSC-driven DCE MR imaging PK parameters showed better diagnostic accuracy and reliability for differentiating high-grade from low-grade astrocytoma than those derived from AIF_DCE. ^© RSNA, 2017 Online supplemental material is available for this article.

Diffusion-weighted endorectal MR imaging at 3T for prostate cancer: correlation with tumor cell density and percentage Gleason pattern on whole mount pathology

OBJECTIVE

To determine if tumor cell density and percentage of Gleason pattern within an outlined volumetric tumor region of interest (TROI) on whole-mount pathology (WMP) correlate with apparent diffusion coefficient (ADC) values on corresponding TROIs outlined on pre-operative MRI.

METHODS

Men with biopsy-proven prostate adenocarcinoma undergoing multiparametric MRI (mpMRI) prior to prostatectomy were consented to this prospective study. WMP and mpMRI images were viewed using 3D Slicer and each TROI from WMP was contoured on the high b-value ADC maps (b0, 1400). For each TROI outlined on WMP, TCD (tumor cell density) and the percentage of Gleason pattern 3, 4, and 5 were recorded. The ADC_mean, ADC_{10th percentile}, ADC_{90th percentile}, and ADC_ratio were also calculated in each case from the ADC maps using 3D Slicer.

RESULTS

Nineteen patients with 21 tumors were included in this study. ADC_mean values for TROIs were 944.8 ± 327.4 vs. 1329.9 ± 201.6 mm²/s for adjacent non-neoplastic prostate tissue (p < 0.001). ADC_mean, ADC_{10th percentile}, and ADC_ratio values for higher grade tumors were lower than those of lower grade tumors (mean 809.71 and 1176.34 mm²/s, p = 0.014; 10th percentile 613.83 and 1018.14 mm²/s, p = 0.009; ratio 0.60 and 0.94, p = 0.005). TCD and ADC_mean (ρ = -0.61, p = 0.005) and TCD and ADC_{10th percentile} (ρ = -0.56, p = 0.01) were negatively correlated. No correlation was observed between percentage of Gleason pattern and ADC values.

CONCLUSION

DWI MRI can characterize focal prostate cancer using ADC_ratio, ADC_{10th percentile}, and ADC_mean, which correlate with pathological tumor cell density.

Volumetry of the dominant intraprostatic tumour lesion: intersequence and interobserver differences on multiparametric MRI

OBJECTIVE

To establish the interobserver reproducibility of tumour volumetry on individual multiparametric (mp) prostate MRI sequences, validate measurements with histology and determine whether functional to morphological volume ratios reflect Gleason score.

METHODS

41 males with prostate cancer treated with prostatectomy (Cohort 1) or radical radiotherapy (Cohort 2), who had pre-treatment mpMRI [T2 weighted (T2W) MRI, diffusion-weighted (DW)-MRI and dynamic contrast-enhanced (DCE)-MRI], were studied retrospectively. Dominant intraprostatic lesions (DIPLs) were manually delineated on each sequence and volumes were compared between observers (n = 40 analyzable) and with radical prostatectomy (n = 20). Volume ratios of DW-MRI and DCE-MRI to T2W MRI were documented and compared between Gleason grade 3 + 3, 3 + 4 and 4 + 3 or greater categories.

RESULTS

Limits of agreement of DIPL volumes between observers were: T2W MRI 0.9, -1.1 cm3, DW-MRI 1.3, -1.7 cm3 and DCE-MRI 0.74, -0.89 cm3. In Cohort 1, T2W volumes overestimated fixed specimen histological volumes (+33% Observer 1, +16% Observer 2); DW- and DCE-MRI underestimated histological volume, the latter markedly so (-32% Observer 1, -79% Observer 2). Differences between T2W, DW- and DCE-MRI volumes were significant (p < 10-8). The ratio of DW-MRI volume (73.9 ± 18.1% Observer 1, 72.5 ± 21.9% Observer 2) and DCE-MRI volume (42.6 ± 24.6% Observer 1, 34.3 ± 24.9% Observer 2) to T2W volume was significantly different (p < 10-8), but these volume ratios did not differ between the Gleason grades.

CONCLUSION

The low variability of the DIPL volume on T2W MRI between Observers and agreement with histology indicates its suitability for delineation of gross tumour volume for radiotherapy planning. The volume of cellular tumour represented by DW-MRI is greater than the vascular (DCE) abnormality; ratios of both to T2W volume are independent of Gleason score. Advances in knowledge: (1) Manual volume measurement of tumour is reproducible within 1 cm3 between observers on all sequences, confirming suitability across observers for radiotherapy planning. (2) Volumes derived on T2W MRI most accurately represent in vivo lesion volumes. (3) The proportion of cellular (DW-MRI) or vascular (DCE-MRI) volume to morphological (T2W MRI) volume is not affected by Gleason score.

Benign prostatic hyperplasia after prostatic arterial embolization in a canine model: A 3T multiparametric MRI and whole-mount step-section pathology correlated longitudinal study

PURPOSE

To explore the morphological and functional characteristics of prostatic arterial embolization (PAE) in a canine model of benign prostatic hyperplasia (BPH) with 3T multiparametric magnetic resonance imaging (mp-MRI) and whole-mount step-section pathology correlation.

MATERIALS AND METHODS

Eight adult male beagle dogs with hormone-induced BPH underwent 3T mp-MRI before and 1, 3, and 6 months after PAE, with subsequent whole-mount step-section pathologic assessment. Images were acquired using T₁ -weighted images (T₁ WI), T₂ WI, 3D-SPACE, diffusion-weighted imaging (DWI), susceptibility-weighted imaging (SWI), T₂ -mapping, and dynamic contrast-enhanced (DCE) sequences. Variance analysis was performed to assess statistical differences in prostatic volume (PV), apparent diffusion coefficient (ADC), and T₂ values. Pearson correlation analysis was performed to correlate ADC, T₂ , and PV.

RESULTS

The PV decreased from baseline to 1, 3, and 6 months after PAE from (25.88 ± 7.09) cm³ to (6.48 ± 2.08) cm³ , (6.48 ± 3.39) cm³ , (6.20 ± 2.88) cm³ . The ADC values sequentially decreased from baseline to 1, 3, and 6 months after PAE from (1497.06 ± 222.72) × 10^-6 mm² /s to (1056.00 ± 189.46) × 10^-6 mm² /s, (950.48 ± 77.85) × 10^-6 mm² /s, (980.98 ± 107.78) × 10^-6 mm² /s. The T₂ values decreased from baseline to 1, 3, and 6 months after PAE were (83.74 ± 5.29) msec, (68.72 ± 5.66) msec, (53.96 ± 15.04) msec, (49.81 ± 13.34) msec, respectively. ADC and T₂ values were positively correlated with PV (r = 0.823 and 0.744, respectively). Microhemorrhages and hemosiderin were found on SWI after PAE.

CONCLUSION

3T mp-MRI may facilitate noninvasive assessment of morphological and functional changes of BPH after PAE.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1220-1229.

Improved performance of prostate DCE-MRI using a 32-coil vs. 12-coil receiver array

PURPOSE

To assess whether acquisition with 32 receiver coils rather than the vendor-recommended 12 coils provides significantly improved performance in 3D dynamic contrast-enhanced MRI (DCE-MRI) of the prostate.

MATERIALS

The study was approved by the institutional review board and was compliant with HIPAA. 50 consecutive male patients in whom prostate MRI was clinically indicated were prospectively imaged in March 2015 with an accelerated DCE-MRI sequence in which image reconstruction was performed using 12 and 32 coil elements. The two reconstructions were compared quantitatively and qualitatively. The first was done using signal-to-noise ratio (SNR) and g-factor analysis to assess sensitivity to acceleration. The second was done using a five-point scale by two experienced radiologists using criteria of perceived SNR, artifact, sharpness, and overall preference. Significance was assessed with the Wilcoxon signed rank test. Extension to T2-weighted spin-echo and diffusion sequences was assessed in phantom studies.

RESULTS

Reconstruction using 32 vs. 12 coil elements provided improved performance in DCE-MRI based on intrinsic SNR (18% higher) and g-factor statistics (14% higher), with a median 32% higher overall SNR within the prostate volume over all subjects. Reconstruction using 32 coils was qualitatively rated significantly improved (p<0.001) vs. 12 coils on the basis of perceived SNR and radiologist preference and equivalent for sharpness and artifact. Phantom studies suggested the improvement in intrinsic SNR could extend to T2-weighted spin-echo and diffusion sequences.

CONCLUSIONS

Reconstruction of 3D accelerated DCE-MRI studies of the prostate using 32 independent receiver coils provides improved overall performance vs. using 12 coils.

Patient-specific pharmacokinetic parameter estimation on dynamic contrast-enhanced MRI of prostate: Preliminary evaluation of a novel AIF-free estimation method

PURPOSE

To develop and evaluate a prostate-based method (PBM) for estimating pharmacokinetic parameters on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) by leveraging inherent differences in pharmacokinetic characteristics between the peripheral zone (PZ) and transition zone (TZ).

MATERIALS AND METHODS

This retrospective study, approved by the Institutional Review Board, included 40 patients who underwent a multiparametric 3T MRI examination and subsequent radical prostatectomy. A two-step PBM for estimating pharmacokinetic parameters exploited the inherent differences in pharmacokinetic characteristics associated with the TZ and PZ. First, the reference region model was implemented to estimate ratios of K^trans between normal TZ and PZ. Subsequently, the reference region model was leveraged again to estimate values for K^trans and v_e for every prostate voxel. The parameters of PBM were compared with those estimated using an arterial input function (AIF) derived from the femoral arteries. The ability of the parameters to differentiate prostate cancer (PCa) from benign tissue was evaluated on a voxel and lesion level. Additionally, the effect of temporal downsampling of the DCE MRI data was assessed.

RESULTS

Significant differences (P < 0.05) in PBM K^trans between PCa lesions and benign tissue were found in 26/27 patients with TZ lesions and in 33/38 patients with PZ lesions; significant differences in AIF-based K^trans occurred in 26/27 and 30/38 patients, respectively. The 75^th and 100^th percentiles of K^trans and v_e estimated using PBM positively correlated with lesion size (P < 0.05).

CONCLUSION

Pharmacokinetic parameters estimated via PBM outperformed AIF-based parameters in PCa detection. J. Magn. Reson. Imaging 2016;44:1405-1414.

Practical aspects of prostate MRI: hardware and software considerations, protocols, and patient preparation

The use of multiparametric MRI scans for the evaluation of men with prostate cancer has increased dramatically and is likely to continue expanding as new developments come to practice. However, it has not yet gained the same level of acceptance of other imaging tests. Partly, this is because of the use of suboptimal protocols, lack of standardization, and inadequate patient preparation. In this manuscript, we describe several practical aspects of prostate MRI that may facilitate the implementation of new prostate imaging programs or the expansion of existing ones.

Bolus arrival time and its effect on tissue characterization with dynamic contrast-enhanced magnetic resonance imaging

Matching the bolus arrival time (BAT) of the arterial input function (AIF) and tissue residue function (TRF) is necessary for accurate pharmacokinetic (PK) modeling of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). We investigated the sensitivity of volume transfer constant ([Formula: see text]) and extravascular extracellular volume fraction ([Formula: see text]) to BAT and compared the results of four automatic BAT measurement methods in characterization of prostate and breast cancers. Variation in delay between AIF and TRF resulted in a monotonous change trend of [Formula: see text] and [Formula: see text] values. The results of automatic BAT estimators for clinical data were all comparable except for one BAT estimation method. Our results indicate that inaccuracies in BAT measurement can lead to variability among DCE-MRI PK model parameters, diminish the quality of model fit, and produce fewer valid voxels in a region of interest. Although the selection of the BAT method did not affect the direction of change in the treatment assessment cohort, we suggest that BAT measurement methods must be used consistently in the course of longitudinal studies to control measurement variability.

Arterial input functions (AIFs) measured directly from arteries with low and standard doses of contrast agent, and AIFs derived from reference tissues

Measurements of arterial input function (AIF) can have large systematic errors at standard contrast agent doses in dynamic contrast enhanced MRI (DCE-MRI). We compared measured AIFs from low dose (AIFLD) and standard dose (AIFSD) contrast agent injections, as well as the AIF derived from a muscle reference tissue and artery (AIFref). Twenty-two prostate cancer patients underwent DCE-MRI. Data were acquired on a 3T scanner using an mDixon sequence. Gadobenate dimeglumine was injected twice, at doses of 0.015 and 0.085 mmol/kg. Directly measured AIFs were fitted with empirical mathematical models (EMMs) and compared to the AIF derived from a muscle reference tissue (AIFref). EMMs accurately fitted the AIFs. The 1st and 2nd pass peaks were visualized in AIFLD, but not in AIFSD, thus the peak and shape of AIFSD could not be accurately measured directly. The average scaling factor between AIFSD and AIFLD in the washout phase was only 56% of the contrast dose ratio (~6:1). The shape and magnitude of AIFref closely approximated that of AIFLD after empirically determined dose-dependent normalization. This suggests that AIFref may be a good approximation of the local AIF.

Comparison of different population-averaged arterial-input-functions in dynamic contrast-enhanced MRI of the prostate: Effects on pharmacokinetic parameters and their diagnostic performance

PURPOSE

To assess the effect of different population-averaged arterial-input-functions (pAIF) on pharmacokinetic parameters from dynamic contrast-enhanced MRI (DCE-MRI) and their diagnostic accuracy regarding the detection of potentially malignant prostate lesions.

MATERIALS AND METHODS

66 male patients (age 65.4±10.8y) with suspected prostate cancer underwent multiparametric MRI of the prostate including T2-w, DWI-w and DCE-MRI sequences at a 3T MRI scanner. All detected lesions were categorized based on ACR PI-RADS version 2 and divided into 2 groups (A: PI-RADS ≤3, n=32; B: PI-RADS >3, n=34). In each DCE-MRI dataset, pharmacokinetic parameters (Ktrans, Kep and ve) and goodness of fit (chi(2)) were generated using the Tofts model with 3 different pAIFs (fast, intermediate, slow) as provided by a commercially available postprocessing software. Pharmacokinetic parameters, their diagnostic accuracies and model fits were compared for the 3 pAIFs.

RESULTS

Ktrans, Kep and ve differed significantly among the 3 pAIFs (all p<.001). Ktrans and Kep were significantly higher in group B compared to group A (all p<.001). For chi(2), lowest results (representing highest goodness of fit) were found for intermediate pAIF (chi(2) 0.073). ROC analyses revealed comparable diagnostic accuracies for the different pAIFs, which were high for Ktrans and Kep and low for ve.

CONCLUSION

Choosing various pAIF types causes a high variability in pharmacokinetic parameter estimates. Therefore, it is of great importance to consider this as potential artifact and thus keep AIF type selection constant in DCE-MRI studies.