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Background Variability of acquisition and interpretation of prostate multiparametric MRI (mpMRI) persists despite implementation of the Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 due to the range of reader experience and subjectivity of lesion characterization. A quantitative method, hybrid multidimensional MRI (HM-MRI), may introduce objectivity. Purpose To compare performance, interobserver agreement, and interpretation time of radiologists using mpMRI versus HM-MRI to diagnose clinically significant prostate cancer. Materials and Methods In this retrospective analysis, men with prostatectomy or MRI-fused transrectal US biopsy-confirmed prostate cancer underwent mpMRI (triplanar T2-weighted, diffusion-weighted, and dynamic contrast-enhanced imaging) and HM-MRI (with multiple echo times and

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 (Ktrans and ve). 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. Ktrans 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. Ktrans in cancer overlapped with that of normal tissue in the transition zone (TZ). There was no statistical difference in ve 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 Ktrans 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.

BackgroundHighb-value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). To decrease scan time and improve signal-to-noise ratio, highb-value (>1000 s/mm2) images are often synthesized instead of acquired.PurposeQualitatively and quantitatively compare synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa.Study TypeRetrospectiveSubjects151 consecutive patients who underwent prostate MRI and biopsy.SequenceAxial DWI withb=0, 500, 1000, and 2000 s/mm2using a 3T clinical scanner using a 32-channel phased-array body coilAssessmentWe synthesized DWI forb=2000 s/mm2via extrapolation based on monoexponential decay, usingb=0 andb=500 s/mm2(sDWI500) andb=0,b=500, andb=1000 s/mm2(sDWI1000). Differences between sDWI and aDWI were evaluated within regions of interest (ROIs). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was also compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI.Statistical TestsDiscrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC). Statistical significance was assessed using bootstrap difference (two-sided α=0.05).ResultsWithin the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46±35% for sDWI1000and -67±24% for sDWI500. AUC for aDWI, sDWI500,sDWI1000, and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively. When considering the whole field of view, classification accuracy and qualitative image quality decreased notably for sDWI compared to aDWI and RSIrs.Data ConclusionsDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.

The spatial two-tissue compartment model (2TCM) was used to analyze prostate dynamic contrast enhanced (DCE) MRI data and compared with the standard Tofts model. A total of 29 patients with biopsy-confirmed prostate cancer were included in this IRB-approved study. MRI data were acquired on a Philips Achieva 3T-TX scanner. After T2-weighted and diffusion-weighted imaging, DCE data using 3D T1-FFE mDIXON sequence were acquired pre- and post-contrast media injection (0.1 mmol/kg Multihance) for 60 dynamic scans with temporal resolution of 8.3 s/image. The 2TCM has one fast (K1trans and k1ep) and one slow (K2trans and k2ep) exchanging compartment, compared with the standard Tofts model parameters (Ktrans and kep). On average, prostate cancer had significantly higher values (p < 0.007) than normal prostate tissue for all calculated parameters. There was a strong correlation (r = 0.94, p < 0.0001) between Ktrans and K1trans for cancer, but weak correlation (r = 0.28, p < 0.05) between kep and k1ep. Average root-mean-square error (RMSE) in fits from the 2TCM was significantly smaller (p < 0.001) than the RMSE in fits from the Tofts model. Receiver operating characteristic (ROC) analysis showed that fast K1trans had the highest area under the curve (AUC) than any other individual parameter. The combined four parameters from the 2TCM had a considerably higher AUC value than the combined two parameters from the Tofts model. The 2TCM may be useful for quantitative analysis of prostate DCE-MRI data and may provide new information in the diagnosis of prostate cancer.

Background Tissue estimates obtained by using microstructure imaging techniques, such as hybrid multidimensional (HM) MRI, may improve prostate cancer diagnosis but require histologic validation. Purpose To validate prostate tissue composition measured by using HM MRI, with quantitative histologic evaluation from whole-mount prostatectomy as the reference standard. Materials and Methods In this HIPAA-compliant study, from December 2016 to July 2018, prospective participants with biopsy-confirmed prostate cancer underwent 3-T MRI before radical prostatectomy. Axial HM MRI was performed with all combinations of echo times (57, 70, 150, and 200 msec) and

Purpose To compare the effect of different echo times (TE) on the detection of prostate cancer (PCa) on T2-weighted MR images. Materials and Methods This study recruited patients (n = 38) with histologically confirmed PCa who underwent preoperative 3T MRI. Three radiologists independently marked region on interests (ROIs) on suspected PCa lesions on T2-weighted images at different TEs: 90, 150, and 180 ms obtained with Turbo Spin Echo imaging protocol with multiple echoes. The ROIs were assigned a value 1–5 indicating the reviewer's confidence in accurately detecting PCa. These ROIs were compared to histologically confirmed PCa (n = 95) on whole mount prostatectomy sections to calculate sensitivity, positive predictive value (PPV), and confidence score. Results Two radiologists (R1, R2) showed significantly increased sensitivity for PCa detection at 180 ms TE compared to 90 ms (R1: 43.2, 50.5, 50.5%, R2: 45.3, 44.2, 53.7% at TE of 90, 150, 180 ms, respectively) (p = 0.048, 0.033 for R1 and R2). Sensitivity was similar for radiologist 3 (45.3%–46.3%) at different TE values (p = 0.953). No significant difference in the PPV (R1: 64.1%–70.6%, R2: 46.7%–56.0%, R3: 70.5%–81.5%) and the confidence score assigned (R1: 4.6–4.8, R2: 4.6–4.8 R3: 4.3–4.4) was found for either of the radiologists. Conclusion Our results suggest improved detection of PCa with similar PPV and confidence scores when higher TE values are utilized for T2-weighted image acquisition.

Background Recently developed time-dependent diffusion MRI has potential in characterizing cellular tissue microstructures; however, its value in imaging prostate cancer (PCa) remains unknown. Purpose To investigate the feasibility of time-dependent diffusion MRI-based microstructural mapping for noninvasively characterizing cellular properties of PCa and for discriminating between clinically significant PCa and clinically insignificant disease. Materials and Methods Men with a clinical suspicion of PCa were enrolled prospectively between October 2019 and August 2020. Time-dependent diffusion MRI data were acquired with pulsed and oscillating gradient diffusion MRI sequences at an equivalent diffusion time of 7.5-30 msec on a 3.0-T scanner. Time-dependent diffusion MRI-based microstructural parameters, including cell diameter, intracellular volume fraction, cellularity, and diffusivities, were estimated with a two-compartment model. These were compared for different International Society of Urological Pathology grade groups (GGs), and their performance in discriminating clinically significant PCa (GG1) from clinically insignificant disease (benign and GG 1) was determined with a linear discriminant analysis. The fitted microstructural parameters were validated by means of correlation with histopathologic measurements. Results In the 48 enrolled men, the time-dependent diffusion MRI measurements showed that higher GG was correlated with higher intracellular volume fraction and higher cellularity (intracellular volume fraction = 0.22, 0.36, 0.34, 0.37, and 0.40 in GGs 1-5, respectively

Rationale and Objectives This study compares the performance of T2 maps in the detection of prostate cancer (PCa) in comparison to T2-weighted (T2W) magnetic resonance images. Materials and Methods The prospective study was institutional review board approved. Consenting patients (n = 45) with histologic confirmed PCa underwent preoperative 3-T magnetic resonance imaging with or without endorectal coil. Two radiologists, working independently, marked regions of interests (ROIs) on PCa lesions separately on T2W images and T2 maps. Each ROI was assigned a score of 1–5 based on the confidence in accurately detecting cancer, with 5 being the highest confidence. Subsequently, the histologically confirmed PCa lesions (n = 112) on whole-mount sections were matched with ROIs to calculate sensitivity, positive predictive value (PPV), and radiologist confidence score. Quantitative T2 values of PCa and benign tissue ROIs were measured. Results Sensitivity and confidence score for PCa detection were similar for T2W images (51%, 4.5 ± 0.8) and T2 maps (52%, 4.5 ± 0.6). However, PPV was significantly higher (P = .001) for T2 maps (88%) compared to T2W (72%) images. The use of endorectal coils nominally improved sensitivity (T2W: 55 vs 47%, T2 map: 54% vs 48%) compared to the use of no endorectal coils, but not the PPV and the confidence score. Quantitative T2 values for PCa (105 ± 28 milliseconds) were significantly (P = 9.3 × 10−14) lower than benign peripheral zone tissue (211 ± 71 milliseconds), with moderate significant correlation with Gleason score (ρ = −0.284). Conclusions Our study shows that review of T2 maps by radiologists has similar sensitivity but higher PPV compared to T2W images. Additional quantitative information obtained from T2 maps is helpful in differentiating cancer from normal prostate tissue and determining its aggressiveness.

Rationale and Objectives To investigate whether pre-treatment quantitative multiparametric MRI can predict biochemical outcome of prostate cancer (PCa) patients treated with primary radiotherapy (RT). Materials and Methods Fifty-one patients with biopsy confirmed PCa underwent prostate multiparametric MRI on 3T MR scanner prior to RT. Thirty-seven men (73%) were treated with external beam RT alone, 12 men (24%) were treated with brachytherapy monotherapy, and two men (4%) were treated with external beam RT with brachytherapy boost. The index lesion was outlined by a radiologist and quantitative apparent diffusion coefficient (ADC), T2 and DCE parameters were measured. Biochemical failure was defined using the Phoenix criteria. Results After a median follow-up of 65 months, seven patients had biochemical failure. ADC had an area under the receiver operating characteristic curve of 0.71 for predicting RT outcome with significantly lower ADC (0.78 ± 0.17 vs 0.96 ± 0.26 µm2/ms, p = 0.04) of the index lesion in men with biochemical failure. Ideal ADC cutoff point (Youdens index) was 0.96 µm2/ms which had a sensitivity of 100% and specificity of 48% for predicting biochemical failure. Kaplan-Meier analysis showed that lower ADC values were associated with significantly lower freedom from biochemical failure (FFBF, p = 0.03, no failures out of 20 men if ADC ≥ 0.96 µm2/ms; seven of 31 with failures if ADC Conclusion Our results suggest that quantitative ADC values of the index lesion may predict biochemical failure following primary radiotherapy in patients with PCa. Lower ADC values were associated with inferior biochemical control.

Purpose High spectral and spatial resolution (HiSS) MRI is a spectroscopic imaging method focusing on water and fat resonances that has good diagnostic utility in breast imaging. The purpose of this work was to assess the feasibility and potential utility of HiSS MRI for the diagnosis of prostate cancer. Methods HiSS MRI was acquired at 3 T from six patients who underwent prostatectomy, yielding a train of 127 phase-coherent gradient echo (GRE) images. In the temporal domain, changes in voxel intensity were analyzed and linear (R) and quadratic (R1, R2) quantifiers of signal logarithm decay were calculated. In the spectral domain, three signal scaling-independent parameters were calculated: water resonance peak width (PW), relative peak asymmetry (PRA), and relative peak distortion from ideal Lorentzian shape (PRD). Seven cancer and five normal tissue regions of interest were identified in correlation with pathology and compared. Results HiSS-derived quantifiers, except R2, showed high reproducibility (coefficients of variation, 5%-14%). Spectral domain quantifiers performed better than temporal domain quantifiers, with receiver operator characteristic areas under the curve ranging from of 0.83 to 0.91. For temporal domain parameters, the range was 0.74 to 0.91. Low absolute values of the coefficients of correlation between monoexponential decay markers (R, PW) and resonance shape markers (PRA, PRD) were observed (range, 0.23-0.38). Conclusion The feasibility and potential diagnostic utility of HiSS MRI in the prostate at 3 T without an endorectal coil was confirmed. Weak correlation between well-performing markers indicates that complementary information could be leveraged to further improve diagnostic accuracy.

This study investigates whether administration of low doses of gadolinium-based contrast agent (GBCA) for dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) can be as effective as a standard dose in distinguishing prostate cancer (PCa) from benign tissue. In addition, we evaluated the combination of kinetic parameters from the low- and high-dose injection as a new diagnostic marker.Patients (n = 17) with histologically confirmed PCa underwent preoperative 3 T MRI. Dynamic contrast-enhanced MRI images were acquired at 8.3-second temporal resolution with a low dose (0.015 mmol/kg) and close to the standard dose (0.085 mmol/kg) of gadobentate dimeglumine bolus injections. Low-dose images were acquired for 3.5 minutes, followed by a 5-minute gap before acquiring standard dose images for 8.3 minutes. The data were analyzed qualitatively to investigate whether lesions could be detected based on early focal enhancement and quantitatively by fitting signal intensity as a function of time with an empirical mathematical model to obtain a maximum enhancement projection (MEP) and signal enhancement rate (α).Both low- and standard-dose DCE-MRI showed similar sensitivity (13/26 = 50%) and lesion conspicuity score (4.0 ± 1.0 vs 4.2 ± 0.9; P = 0.317) for PCa diagnosis on qualitative analysis. Prostate cancer showed significantly increased α compared with benign tissue for low (9.98 ± 5.84 vs 5.12 ± 2.95 s) but not for standard (4.27 ± 2.20 vs 3.35 ± 1.48 s) dose. The ratio of low-dose α to standard-dose α was significantly greater (P = 0.02) for PCa (2.8 ± 2.3) than for normal prostate (1.6 ± 0.9), suggesting changes in water exchange and T2* effects associated with cancer. In addition, decreases in the percentage change in T1 relaxation rate as a function of increasing contrast media concentration (ie, the "saturation effect") can also contribute to the observed differences in high-dose and low-dose α. Area under the receiver operating characteristic curve for differentiating PCa from benign tissue using α was higher for low dose (0.769) compared with standard dose (0.625). There were no significant differences between MEP calculated for PCa and normal tissue at the low and standard doses. Moderate significant Pearson correlation for DCE parameters, MEP (r = 0.53) and α (r = 0.58), was found between low and standard doses of GBCA.These preliminary results suggest that DCE-MRI with a low GBCA dose distinguishes PCa from benign prostate tissue more effectively than does the standard GBCA dose, based on signal enhancement rate. Diagnostic accuracy is similar on qualitative assessment. Prostate cancer diagnosis may be feasible with DCE-MRI with low-dose GBCA. In addition, comparison of enhancement kinetics after low and high doses of contrast media may provide diagnostically useful information.

PURPOSE: To evaluate whether compartmental analysis by using hybrid multidimensional magnetic resonance (MR) imaging can be used to diagnose prostate cancer and determine its aggressiveness. MATERIALS AND METHODS: Twenty-two patients with prostate cancer underwent preoperative 3.0-T MR imaging. Axial images were obtained with hybrid multidimensional MR imaging by using all combinations of echo times (47, 75, 100 msec) and b values of 0, 750, 1500 sec/mm(2), resulting in a 3 × 3 array of data associated with each voxel. Volumes of the tissue components stroma, epithelium, and lumen were calculated by fitting the hybrid data to a three-compartment signal model, with distinct, paired apparent diffusion coefficient (ADC) and T2 values associated with each compartment. Volume fractions and conventional ADC and T2 were measured for regions of interest in sites of prostatectomy-verified malignancy (n = 28) and normal tissue (n = 71). Receiver operating characteristic (ROC) analysis was used to evaluate the performance of various parameters in differentiating prostate cancer from benign tissue. RESULTS: Compared with normal tissue, prostate cancer showed significantly increased fractional volumes of epithelium (23.2% ± 7.1 vs 48.8% ± 9.2, respectively) and reduced fractional volumes of lumen (26.4% ± 14.1 vs 14.0% ± 5.2) and stroma (50.5% ± 15.7 vs 37.2% ± 9.1) by using hybrid multidimensional MR imaging. The fractional volumes of tissue components show a significantly higher Spearman correlation coefficient with Gleason score (epithelium: ρ = 0.652, P = .0001; stroma: ρ = −0.439, P = .020; lumen: ρ = −0.390, P = .040) compared with traditional T2 values (ρ = −0.292, P = .132) and ADCs (ρ = −0.315, P = .102). The area under the ROC curve for differentiation of cancer from normal prostate was highest for fractional volume of epithelium (0.991), followed by fractional volumes of lumen (0.800) and stroma (0.789). CONCLUSION: Fractional volumes of prostatic lumen, stroma, and epithelium change significantly when cancer is present. These parameters can be measured noninvasively by using hybrid multidimensional MR imaging and have the potential to improve the diagnosis of prostate cancer and determine its aggressiveness. (©) RSNA, 2018 Online supplemental material is available for this article.

RATIONALE AND OBJECTIVES: This study aimed to test high temporal resolution dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for different zones of the prostate and evaluate its performance in the diagnosis of prostate cancer (PCa). Determine whether the addition of ultrafast DCE-MRI improves the performance of multiparametric MRI. MATERIALS AND METHODS: Patients (n = 20) with pathologically confirmed PCa underwent preoperative 3T MRI with T2-weighted, diffusion-weighted, and high temporal resolution (~2.2 seconds) DCE-MRI using gadoterate meglumine (Guerbet, Bloomington, IN) without an endorectal coil. DCE-MRI data were analyzed by fitting signal intensity with an empirical mathematical model to obtain parameters: percent signal enhancement, enhancement rate (α), washout rate (β), initial enhancement slope, and enhancement start time along with apparent diffusion coefficient (ADC) and T2 values. Regions of interests were placed on sites of prostatectomy verified malignancy (n = 46) and normal tissue (n = 71) from different zones. RESULTS: Cancer (α = 6.45 ± 4.71 s(−1), β = 0.067 ± 0.042 s(−1), slope = 3.78 ± 1.90 s(−1)) showed significantly (P < .05) faster signal enhancement and washout rates than normal tissue (α = 3.0 ± 2.1 s(−1), β = 0.034 ± 0.050 s(−1), slope = 1.9 ± 1.4 s(−1)), but showed similar percentage signal enhancement and enhancement start time. Receiver operating characteristic analysis showed area under the curve for DCE parameters was comparable to ADC and T2 in the peripheral (DCE 0.67–0.82, ADC 0.80, T2 0.89) and transition zones (DCE 0.61–0.72, ADC 0.69, T2 0.75), but higher in the central zone (DCE 0.79–0.88, ADC 0.45, T2 0.45) and anterior fibromuscular stroma (DCE 0.86–0.89, ADC 0.35, T2 0.12). Importantly, combining DCE with ADC and T2 increased area under the curve by ~30%, further improving the diagnostic accuracy of PCa detection. CONCLUSION: Quantitative parameters from empirical mathematical model fits to ultrafast DCE-MRI improve diagnosis of PCa. DCE-MRI with higher temporal resolution may capture clinically useful information for PCa diagnosis that would be missed by low temporal resolution DCE-MRI. This new information could improve the performance of multiparametric MRI in PCa detection.

To evaluate utility of T2*-weighted (T2*W) MRI as a tool for intra-operative identification of ablation zone extent during focal laser ablation (FLA) of prostate cancer (PCa), as compared to the current standard of contrast-enhanced T1-weighted (T1W) MRI. Fourteen patients with biopsy-confirmed low- to intermediate-risk localized PCa received MRI-guided (1.5 T) FLA thermotherapy. Following FLA, axial multiple-TE T2*W images, diffusion-weighted images (DWI), and T2-weighted (T2W) images were acquired. Pre- and post-contrast T1W images were also acquired to assess ablation zone (n = 14) extent, as reference standard. Apparent diffusion coefficient (ADC) maps and subtracted contrast-enhanced T1W (sceT1W) images were calculated. Ablation zone regions of interest (ROIs) were outlined manually on all ablated slices. The contrast-to-noise ratio (CBR) of the ablation site ROI relative to the untreated contralateral prostate tissue was calculated on T2*W images and ADC maps and compared to that in sceT1W images. CBRs in ablation ROIs on T2*W images (TE = 32, 63 ms) did not differ (p = 0.33, 0.25) from those in sceT1W images. Bland–Altman plots of ROI size and CBR in ablation sites showed good agreement between T2*W (TE = 32, 63 ms) and sceT1W images, with ROI sizes on T2*W (TE = 63 ms) strongly correlated (r = 0.64, p = 0.013) and within 15% of those in sceT1W images. In detected ablation zone ROI size and CBR, non-contrast-enhanced T2*W MRI is comparable to contrast-enhanced T1W MRI, presenting as a potential method for intra-procedural monitoring of FLA for PCa. • T2*-weighted MR images with long TE visualize post-procedure focal laser ablation zone comparably to the contrast-enhanced T1-weighted MRI. • T2*-weighted MRI could be used as a plausible method for repeated intra-operative monitoring of thermal ablation zone in prostate cancer, avoiding potential toxicity due to heating of contrast agent.

OBJECTIVE. This study investigates the multiparametric MRI (mpMRI) characteristics and pathologic outcome of wedge-shaped lesions observed on T2-weighted images. MATERIALS AND METHODS. Seventy-six patients with histologically confirmed prostate cancer underwent preoperative 3-T MRI before undergoing radical prostatectomy. Two radiologists worked in consensus to mark wedge-shaped regions of hypointensity on T2-weighted images and assess their appearance on apparent diffusion coefficient (ADC) maps (to determine the degree of hypointensity) and dynamic contrast-enhanced (DCE) MRI (DCE-MRI) (to assess whether they showed early enhancement). The pathologic outcome of wedge-shaped lesions was assessed by matching MR images with whole-mount histologic specimens retrospectively. The difference in quantitative ADC values between malignant and benign wedge-shaped lesions was assessed using a t test. RESULTS. Thirty-five wedge-shaped regions were identified, 12 (34%) of which were found be malignant. Most malignant wedge-shaped regions were highly hypointense (10/12; 83%) on ADC maps and showed early enhancement on DCE-MRI (7/12; 58%). However, benign wedge-shaped lesions were predominantly mildly hypointense (13/23; 57%) on ADC maps and showed no early enhancement (15/23; 65%). Histologic correlates of the benign wedge-shaped regions showed prostatitis (acute inflammation [7/23; 30%] or chronic inflammation [9/23; 39%]), hemosiderin-laden macrophages (6/23; 26%), prominent blood vessels (7/23; 30%), intraluminal blood (6/23; 26%), and nonspecific atrophy (6/23; 26%). The mean (± SD) quantitative ADC value of malignant wedge-shaped regions (1.13 ± 0.11 μm2/ms) was significantly lower (p = 0.0001) than that of benign wedge-shaped regions (1.52 ± 0.27 μm2/ms). CONCLUSION. This study shows that a greater percentage of wedge-shaped features are malignant than was previously thought. Of importance, mpMRI (specifically, ADC maps) can distinguish between malignant and benign wedge-shaped features. ABD Sağlık ve İnsan Hizmetleri Bakanlığı

The Tofts pharmacokinetic model requires multiple calculations for analysis of dynamic contrast enhanced (DCE) MRI. In addition, the Tofts model may not be appropriate for the prostate. This can result in error propagation that reduces the accuracy of pharmacokinetic measurements. In this study, we present a compact solution allowing estimation of physiological parameters K(trans) and v(e) from ultrafast DCE acquisitions, without fitting DCE-MRI data to the standard Tofts pharmacokinetic model. Since the standard Tofts model can be simplified to the Patlak model at early times when contrast efflux from the extravascular extracellular space back to plasma is negligible, K(trans) can be solved explicitly for a specific time. Further, v(e) can be estimated directly from the late steady-state signal using the derivative form of Tofts model. Ultrafast DCE-MRI data were acquired from 18 prostate cancer patients on a Philips Achieva 3T-TX scanner. Regions-of-interest (ROIs) for prostate cancer, normal tissue, gluteal muscle, and iliac artery were manually traced. The contrast media concentration as function of time was calculated over each ROI using gradient echo signal equation with pre-contrast tissue T1 values, and using the ‘reference tissue’ model with a linear approximation. There was strong correlation (r = 0.88–0.91, p < 0.0001) between K(trans) extracted from the Tofts model and K(trans) estimated from the compact solution for prostate cancer and normal tissue. Additionally, there was moderate correlation (r = 0.65–0.73, p < 0.0001) between extracted versus estimated v(e). Bland-Altman analysis showed moderate to good agreement between physiological parameters extracted from the Tofts model and those estimated from the compact solution with absolute bias less than 0.20 min(−1) and 0.10 for K(trans) and v(e), respectively. The compact solution may decrease systematic errors and error propagation, and could increase the efficiency of clinical workflow. The compact solution requires high temporal resolution DCE-MRI due to the need to adequately sample the early phase of contrast media uptake.

To investigate the hypothesis that the clinically observed decrease in apparent diffusion coefficient (ADC) at diffusion-weighted magnetic resonance imaging with increasing prostate cancer Gleason grade can be attributed to an increasing volume of low-diffusivity epithelial cells and corresponding decreasing volumes of higher-diffusivity stroma and lumen space rather than to increased cell density.Tissue samples were acquired after institutional ethics review committee approval and informed consent from patients were obtained. Nuclear count, nuclear area, and gland component volumes (epithelium, stroma, lumen space) were measured in tissue from 14 patients. Gland component volumes and cellularity metrics were correlated with Gleason pattern (Spearman rank correlation coefficient) and measured ADC (Pearson correlation coefficient) in six prostates ex vivo. Differences between metrics for cancerous tissue and those for normal tissue were assessed by using a two-tailed two-sample t test. Linear mixed models with a post hoc Fisher least significant difference test were used to assess differences between gland component volumes and cellularity metrics for multiple groups. To adjust for a clustering effect due to repeated measures, the organ mean value of the measured metric for each tissue type was used in the analysis.There were significant differences between Gleason patterns for gland component volumes (P.05) but not nuclear count (P = .100) or area (P = .141). There was a stronger correlation of Gleason pattern with gland component volumes (n = 553) of epithelium (Spearman ρ = 0.898, P.001), stroma (ρ = -0.651, P.001), and lumen space (ρ = -0.912, P = .007) than with the cellularity metrics (n = 288) nuclear area (ρ = 0.422, P = .133) or nuclear count (ρ = 0.082, P = .780). There was a stronger correlation between measured ADC and lumen volume (r = 0.688, P.001) and epithelium volume (r = -0.647, P.001) than between ADC and nuclear count (r = -0.598, P.001) or nuclear area (r = -0.569, P.001) (n = 57).Differences in the gland compartment volumes of prostate tissue having distinct diffusivities, rather than changes in the conventionally cited "cellularity" metrics, are likely to be the major contributor to clinically observed variations of ADC in prostate tissue.