Discrimination of prostate cancer from normal peripheral zone and central gland tissue by using dynamic contrast-enhanced MR imaging

Dynamic contrast-enhanced MRI of the prostate: An intraindividual assessment of the effect of temporal resolution on qualitative detection and quantitative analysis of histopathologically proven prostate cancer

PURPOSE

To assess the effects of temporal resolution (R_T ) in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) on qualitative tumor detection and quantitative pharmacokinetic parameters in prostate cancer.

MATERIALS AND METHODS

This retrospective Institutional Review Board (IRB)-approved study included 58 men (64 ± 7 years). They underwent 3T prostate MRI showing dominant peripheral zone (PZ) tumors (24 with Gleason ≥ 4 + 3), prior to prostatectomy. Continuously acquired DCE utilizing GRASP (Golden-angle RAdial Sparse Parallel) was retrospectively reconstructed at R_T of 1.4 sec, 3.7 sec, 6.0 sec, 9.7 sec, and 14.9 sec. A reader placed volumes-of-interest on dominant tumors and benign PZ, generating quantitative pharmacokinetic parameters (k^trans , v_e ) at each R_T . Two blinded readers assessed each R_T for lesion presence, location, conspicuity, and reader confidence on a 5-point scale. Data were assessed by mixed-model analysis of variance (ANOVA), generalized estimating equation (GEE), and receiver operating characteristic (ROC) analysis.

RESULTS

R_T did not affect sensitivity (R1_all : 69.0%-72.4%, all P_adj  = 1.000; R1_{GS≥4 + 3} : 83.3-91.7%, all P_adj  = 1.000; R2_all : 60.3-69.0%, all P_adj  = 1.000; R2_{GS≥4 + 3} : 58.3%-79.2%, all P_adj  = 1.000). R1 reported greater conspicuity of GS ≥ 4 + 3 tumors at R_T of 1.4 sec vs. 14.9 sec (4.29 ± 1.23 vs. 3.46 ± 1.44; P_adj  = 0.029). No other tumor conspicuity pairwise comparison reached significance (R1_all : 2.98-3.43, all P_adj ≥ 0.205; R2_all : 2.57-3.19, all P_adj ≥ 0.059; R1_{GS≥4 + 3} : 3.46-4.29, all other P_adj ≥ 0.156; R2_{GS≥4 + 3} : 2.92-3.71, all P_adj ≥ 0.439). There was no effect of R_T on reader confidence (R1_all : 3.17-3.34, all P_adj  = 1.000; R2_all : 2.83-3.19, all P_adj ≥ 0.801; R1_{GS≥4 + 3} : 3.79-4.21, all P_adj  = 1.000; R2_{GS≥4 + 3} : 3.13-3.79, all P_adj  = 1.000). k^trans and v_e of tumor and benign tissue did not differ across R_T (all adjusted P values [P_adj ] = 1.000). R_T did not significantly affect area under the curve (AUC) of K^trans or v_e for differentiating tumor from benign (all P_adj  = 1.000).

CONCLUSION

Current PI-RADS recommendations for R_T of 10 seconds may be sufficient, with further reduction to the stated PI-RADS preference of R_T ≤ 7 seconds offering no benefit in tumor detection or quantitative analysis.

LEVEL OF EVIDENCE

3 J. MAGN. RESON. IMAGING 2017;45:1464-1475.

Differentiating Transition Zone Cancers From Benign Prostatic Hyperplasia by Quantitative Multiparametric Magnetic Resonance Imaging

OBJECTIVE

The aim of this study was to evaluate the value of quantitative diffusion and perfusion parameters to aid in discriminating between transition zone carcinomas and benign prostatic hyperplasia (BPH).

MATERIALS AND METHODS

Twenty-four transition zone cancers and BPH nodules were contoured on T2-weighted magnetic resonance imaging (MRI), apparent diffusion coefficient (ADC) maps, and raw dynamic contrast-enhanced (DCE) MRI. Benign prostatic hyperplasia nodules were then stratified into 2 groups based on the presence or absence of a capsule. Apparent diffusion coefficient values, per-voxel Ktrans, kep, vp, and ve were all compared across all groups.

RESULTS

Average ADCs (×10 mm/s) were 1019.22, 1338.11, and 1272.46 for cancer, encapsulated BPH, and nonencapsulated BPH, respectively. Both subgroups of BPH were found to be significantly different than that of cancer (P < 0.05). No individual DCE-MRI parameter was significantly different between cancer and either BPH group. The area under the curve for ADC alone was 0.83, and no individual DCE imaging parameter improved the area under the curve of ADC.

CONCLUSIONS

Apparent diffusion coefficient may play a role in distinguishing TZ cancers from non-encapsulated BPH nodules that closely resemble cancer.

Dynamic Contrast-enhanced MR Imaging in Renal Cell Carcinoma: Reproducibility of Histogram Analysis on Pharmacokinetic Parameters

Pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) have been increasingly used to evaluate the permeability of tumor vessel. Histogram metrics are a recognized promising method of quantitative MR imaging that has been recently introduced in analysis of DCE-MRI pharmacokinetic parameters in oncology due to tumor heterogeneity. In this study, 21 patients with renal cell carcinoma (RCC) underwent paired DCE-MRI studies on a 3.0 T MR system. Extended Tofts model and population-based arterial input function were used to calculate kinetic parameters of RCC tumors. Mean value and histogram metrics (Mode, Skewness and Kurtosis) of each pharmacokinetic parameter were generated automatically using ImageJ software. Intra- and inter-observer reproducibility and scan–rescan reproducibility were evaluated using intra-class correlation coefficients (ICCs) and coefficient of variation (CoV). Our results demonstrated that the histogram method (Mode, Skewness and Kurtosis) was not superior to the conventional Mean value method in reproducibility evaluation on DCE-MRI pharmacokinetic parameters (K^trans & V_e) in renal cell carcinoma, especially for Skewness and Kurtosis which showed lower intra-, inter-observer and scan-rescan reproducibility than Mean value. Our findings suggest that additional studies are necessary before wide incorporation of histogram metrics in quantitative analysis of DCE-MRI pharmacokinetic parameters.

In vivo prostate cancer detection and grading using restriction spectrum imaging-MRI

BACKGROUND

Magnetic resonance imaging (MRI) is emerging as a robust, noninvasive method for detecting and characterizing prostate cancer (PCa), but limitations remain in its ability to distinguish cancerous from non-cancerous tissue. We evaluated the performance of a novel MRI technique, restriction spectrum imaging (RSI-MRI), to quantitatively detect and grade PCa compared with current standard-of-care MRI.

METHODS

In a retrospective evaluation of 33 patients with biopsy-proven PCa who underwent RSI-MRI and standard MRI before radical prostatectomy, receiver-operating characteristic (ROC) curves were performed for RSI-MRI and each quantitative MRI term, with area under the ROC curve (AUC) used to compare each term's ability to differentiate between PCa and normal prostate. Spearman rank-order correlations were performed to assess each term's ability to predict PCa grade in the radical prostatectomy specimens.

RESULTS

RSI-MRI demonstrated superior differentiation of PCa from normal tissue, with AUC of 0.94 and 0.85 for RSI-MRI and conventional diffusion MRI, respectively (P=0.04). RSI-MRI also demonstrated superior performance in predicting PCa aggressiveness, with Spearman rank-order correlation coefficients of 0.53 (P=0.002) and -0.42 (P=0.01) for RSI-MRI and conventional diffusion MRI, respectively, with tumor grade.

CONCLUSIONS

RSI-MRI significantly improves upon current noninvasive PCa imaging and may potentially enhance its diagnosis and characterization.

MR Imaging of the Prostate Gland

This article discusses MR imaging of the normal prostate and of disease conditions of the prostate including prostatitis, cystic lesions, amyloidosis, calculi, hematospermia, benign prostatic hyperplasia, and malignancy.

DCE MRI of prostate cancer

DCE MRI is an established component of multi-parametric MRI of the prostate. The sequence highlights the vascularization of cancerous lesions, allowing readers to corroborate suspicious findings on T2W and DW MRI and to note subtle lesions not visible on the other sequences. In this article, we review the technical aspects, methods of evaluation, limitations, and future perspectives of DCE MRI.

Computer-aided diagnosis: detection and localization of prostate cancer within the peripheral zone

We propose a methodology for prostate cancer detection and localization within the peripheral zone based on combining multiple segmentation techniques. We extract four image features using Gaussian and median filters. Subsequently, we use each image feature separately to generate binary segmentations. Finally, we take the intersection of all four binary segmentations, incorporating a model of the peripheral zone, and perform erosion to remove small false-positive regions. The initial evaluation of this method is based on 275 MRI images from 37 patients, and 86% of the slices were classified correctly with 87% and 86% sensitivity and specificity achieved, respectively. This paper makes two contributions: firstly, a novel computer-aided diagnosis approach, which is based on combining multiple segmentation techniques using only a small number of simple image features, and secondly, the development of the proposed method and its application in prostate cancer detection and localization using a single MRI modality with the results comparable with the state-of-the-art multimodality and advanced computer vision methods in the literature. Copyright © 2015 John Wiley & Sons, Ltd.

Multiparametric prostate MRI: focus on T2-weighted imaging and role in staging of prostate cancer

Multiparametric MRI (mpMRI) represents a growing modality for the non-invasive evaluation of prostate cancer (PCa) and is increasingly being used for patients with persistently elevated PSA and prior negative biopsies, for monitoring patients in active surveillance protocols, for preoperative characterization of cancer for surgical planning, and in planning for MRI-targeted biopsy. The focus of this work is twofold. First, we review the key role of T2-weighted imaging (T2WI) in mpMRI, specifically outlining how it is used for anatomic evaluation of the prostate, detection of clinically significant PCa, assessment of extraprostatic extension (EPE), and mimics of PCa on this sequence. We will also discuss optimal technical acquisition parameters for this sequence and recent technical advancements in T2WI. Second, we will delineate the role that mpMRI plays in the staging of PCa and describe the implications of the information that mpMRI can provide in determining the most appropriate management plan for the patient with PCa.

Quantitative Analysis of Prostate Multiparametric MR Images for Detection of Aggressive Prostate Cancer in the Peripheral Zone: A Multiple Imager Study

Purpose To assess the intermanufacturer variability of quantitative models in discriminating cancers with a Gleason score of at least 7 among peripheral zone (PZ) lesions seen at 3-T multiparametric magnetic resonance (MR) imaging. Materials and Methods An institutional review board-approved prospective database of 257 patients who gave written consent and underwent T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced imaging before prostatectomy was retrospectively reviewed. It contained outlined lesions found to be suspicious for malignancy by two independent radiologists and classified as malignant or benign after correlation with prostatectomy whole-mount specimens. One hundred six patients who underwent imaging with 3-T MR systems from two manufacturers were selected (data set A, n = 72; data set B, n = 34). Eleven parameters were calculated in PZ lesions: normalized T2-weighted signal intensity, skewness and kurtosis of T2-weighted signal intensity, T2 value, wash-in rate, washout rate, time to peak (TTP), mean apparent diffusion coefficient (ADC), 10th percentile of the ADC, and skewness and kurtosis of the histogram of the ADC values. Parameters were selected on the basis of their specificity for a sensitivity of 0.95 in diagnosing cancers with a Gleason score of at least 7, and the area under the receiver operating characteristic curve (AUC) for the models was calculated. Results The model of the 10th percentile of the ADC with TTP yielded the highest AUC in both data sets. In data set A, the AUC was 0.90 (95% confidence interval [CI]: 0.85, 0.95) or 0.89 (95% CI: 0.82, 0.94) when it was trained in data set A or B, respectively. In data set B, the AUC was 0.84 (95% CI: 0.74, 0.94) or 0.86 (95% CI: 0.76, 0.95) when it was trained in data set A or B, respectively. No third variable added significantly independent information in any data set. Conclusion The model of the 10th percentile of the ADC with TTP yielded accurate results in discriminating cancers with a Gleason score of at least 7 among PZ lesions at 3 T in data from two manufacturers. (©) RSNA, 2016 Online supplemental material is available for this article.

Dynamic contrast-enhanced MRI for oncology drug development

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a promising tool for evaluating tumor vascularity, as it can provide vasculature-derived, functional, and quantitative parameters. To implement DCE-MRI parameters as biomarkers for monitoring the effect of antiangiogenic or vascular-disrupting treatment, two crucial elements of surrogate endpoint, ie, validation and qualification, should be satisfied. Although early studies have shown the accuracy and reliability of DCE-MRI parameters for evaluating treatment-driven vascular alterations, there have been an increasing number of studies demonstrating the limitations of DCE-MRI parameters as surrogate endpoints. Therefore, in order to improve the application of DCE-MRI parameters in drug development, it is necessary to establish a standardized evaluation method and to determine the correct therapeutics-oriented meaning of individual DCE-MRI parameter. In this regard, this article describes the biophysical background and data acquisition/analysis techniques of DCE-MRI while focusing on the validation and qualification issues. Specifically, the causes of disagreement and confusion encountered in the preclinical and clinical trials using DCE-MRI are presented in detail. Finally, considering these limitations, we present potential strategies to optimize implementation of DCE-MRI. J. Magn. Reson. Imaging 2016;44:251-264.

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.

3D surface-based registration of ultrasound and histology in prostate cancer imaging

Several transrectal ultrasound (TRUS)-based techniques aiming at accurate localization of prostate cancer are emerging to improve diagnostics or to assist with focal therapy. However, precise validation prior to introduction into clinical practice is required. Histopathology after radical prostatectomy provides an excellent ground truth, but needs accurate registration with imaging. In this work, a 3D, surface-based, elastic registration method was developed to fuse TRUS images with histopathologic results. To maximize the applicability in clinical practice, no auxiliary sensors or dedicated hardware were used for the registration. The mean registration errors, measured in vitro and in vivo, were 1.5±0.2 and 2.1±0.5mm, respectively.

Models and methods for analyzing DCE-MRI: a review

PURPOSE

To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches.

METHODS

DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases.

RESULTS

Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors.

CONCLUSIONS

Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.

PET/Computed Tomography in the Individualization of Treatment of Prostate Cancer

Choline PET/computed tomographic (CT) imaging represents the most diffused PET imaging techniques to investigate patients with prostate cancer (PCa). It may show the site of tumor recurrence in a single step examination, earlier than other conventional imaging techniques. In this context, the availability of a diagnostic test capable of differentiating between potentially curable local recurrence and metastatic disease implying palliative approaches may play an important role in those patients in whom targeted therapies could be performed according to choline PET/CT results. This review analyzes the value of choline PET/CT imaging in the evaluation of treatment of patients with PCa.

Zone-specific logistic regression models improve classification of prostate cancer on multi-parametric MRI

OBJECTIVES

To assess the interchangeability of zone-specific (peripheral-zone (PZ) and transition-zone (TZ)) multiparametric-MRI (mp-MRI) logistic-regression (LR) models for classification of prostate cancer.

METHODS

Two hundred and thirty-one patients (70 TZ training-cohort; 76 PZ training-cohort; 85 TZ temporal validation-cohort) underwent mp-MRI and transperineal-template-prostate-mapping biopsy. PZ and TZ uni/multi-variate mp-MRI LR-models for classification of significant cancer (any cancer-core-length (CCL) with Gleason > 3 + 3 or any grade with CCL ≥ 4 mm) were derived from the respective cohorts and validated within the same zone by leave-one-out analysis. Inter-zonal performance was tested by applying TZ models to the PZ training-cohort and vice-versa. Classification performance of TZ models for TZ cancer was further assessed in the TZ validation-cohort. ROC area-under-curve (ROC-AUC) analysis was used to compare models.

RESULTS

The univariate parameters with the best classification performance were the normalised T2 signal (T2nSI) within the TZ (ROC-AUC = 0.77) and normalized early contrast-enhanced T1 signal (DCE-nSI) within the PZ (ROC-AUC = 0.79). Performance was not significantly improved by bi-variate/tri-variate modelling. PZ models that contained DCE-nSI performed poorly in classification of TZ cancer. The TZ model based solely on maximum-enhancement poorly classified PZ cancer.

CONCLUSION

LR-models dependent on DCE-MRI parameters alone are not interchangable between prostatic zones; however, models based exclusively on T2 and/or ADC are more robust for inter-zonal application.

KEY POINTS

• The ADC and T2-nSI of benign/cancer PZ are higher than benign/cancer TZ. • DCE parameters are significantly different between benign PZ and TZ, but not between cancerous PZ and TZ. • Diagnostic models containing contrast enhancement parameters have reduced performance when applied across zones.

Reproducibility of Dynamic Contrast-Enhanced MRI in Renal Cell Carcinoma: A Prospective Analysis on Intra- and Interobserver and Scan-Rescan Performance of Pharmacokinetic Parameters

The objective of this study was to investigate the intra- and interobserver as well as scan-rescan reproducibility of quantitative parameters of renal cell carcinomas (RCCs) with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). A total of 21 patients with clear cell RCCs (17 men, 4 woman; age 37-69 years, mean age 54.6 years, mean size, 5.0 ± 2.2 cm) were prospectively recruited from September 2012 to November 2012. Patients underwent paired DCE-MRI studies on a 3.0 T MR system with an interval of 48 to 72 hours. The extended-Tofts model and population-based arterial input function were used to calculate kinetic parameters. Three observers defined the 2-dimensional whole-tumor region of interest at the slice with the maximum diameter of the RCC. Intraobserver and scan-rescan differences were assessed using paired t tests, whereas interobserver differences using two-way analysis of variance. Intra- and interobserver reproducibility and scan-rescan reproducibility were evaluated using within-subject coefficient of variation (wCoV) and intraclass correlation coefficient (ICC). There were no significant intra-, interobserver, or scan-rescan differences in parameters (all P > 0.05). All ICCs for intra- and interobserver agreements were >0.75 (P < 0.05), whereas the scan-rescan agreement was moderate to good; V(e) (0.764, 95% confidence interval [CI]: 0.378-0.925) and K(ep) (0.906, 95% CI: 0.710-0.972) had higher ICC than K(trans) (0.686; 95% CI: 0.212-0.898) and V(p) (0.657; 95% CI: 0.164-0.888). In intra- and interobserver variability analyses, all parameters except V(p) had low wCoV values. K(trans) and V(e) had slightly lower intraobserver wCoV (1.2% and 0.9%) compared with K(ep) (3.7%), whereas all 3 of these parameters had similar interobserver wCoV values (2.5%, 3.1%, and 2.9%, respectively). Regarding scan-rescan variability, K(trans) and K(ep) showed slightly higher variation (15.6% and 15.4%) than V(e) (10.1%). V(p) had the largest wCoV in all variability analyses (all >30%). DCE-MRI demonstrated good intra- and interobserver reproducibility and moderate to good scan-rescan performance in the assessment of RCC using K(trans), K(ep), and V(e) as parameters under noncontinuous scanning mode. V(p) showed poor reproducibility, and thus may not be suitable for this scanning protocol.

False positive and false negative diagnoses of prostate cancer at multi-parametric prostate MRI in active surveillance

Abstract

MP-MRI is a critical component in active surveillance (AS) of prostate cancer (PCa) because of a high negative predictive value for clinically significant tumours. This review illustrates pitfalls of MP-MRI and how to recognise and avoid them. The anterior fibromuscular stroma and central zone are low signal on T2W-MRI/apparent diffusion coefficient (ADC), resembling PCa. Location, progressive enhancement and low signal on b ≥1000 mm²/s echo-planar images (EPI) are differentiating features. BPH can mimic PCa. Glandular BPH shows increased T2W/ADC signal, cystic change and progressive enhancement; however, stromal BPH resembles transition zone (TZ) PCa. A rounded morphology, low T2 signal capsule and posterior/superior location favour stromal BPH. Acute/chronic prostatitis mimics PCa at MP-MRI, with differentiation mainly on clinical grounds. Visual analysis of diffusion-weighted MRI must include EPI and appropriate windowing of ADC. Quantitative ADC analysis is limited by lack of standardization; the ADC ratio and ADC histogram analysis are alternatives to mean values. DCE lacks standardisation and has limited utility in the TZ, where T2W/DWI are favoured. Targeted TRUS-guided biopsies of MR-detected lesions are challenging. Lesions detected on MP-MRI may not be perfectly targeted with TRUS and this must be considered when faced with a suspicious lesion on MP-MRI and a negative targeted TRUS biopsy histopathological result.

Keypoints

• Multi-parametric MRI plays a critical role in prostate cancer active surveillance.

• Low T2W signal intensity structures appear dark on ADC, potentially simulating cancer.

• Stromal BPH mimics cancer at DWI and DCE.

• Long b value trace EPI should be reviewed

• Targeted biopsy of MR-detected lesions using TRUS guidance may be challenging.

Dynamic contrast-enhanced MRI for the detection of prostate cancer: meta-analysis

OBJECTIVE

The purpose of this study was to systematically review and meta-analyze dynamic contrast-enhanced MRI (DCE-MRI) for the detection of prostate cancer in comparison with standard evaluation with T2-weighted imaging.

MATERIALS AND METHODS

A PubMed electronic database search for the terms "dynamic contrast-enhanced," "prostate," and "MRI" was completed for articles up to September 17, 2013. All included studies had histopathologic correlation. Two by two contingency data were constructed for each study. A binormal bayesian ROC model was used to estimate and compare sensitivity, specificity, and AUC among eligible modalities.

RESULTS

Both DCE-MRI (0.82-0.86) and diffusion-weighted MRI (DWI) (0.84-0.88) yielded significantly better AUC than T2-weighted imaging (0.68-0.77). Moreover, partial AUC for the combination of DCE-MRI, DWI, and T2-weighted imaging was improved significantly (0.111; 0.103-0.119) when compared with DCE-MRI alone (0.079; 0.072-0.085) and T2-weighted imaging alone (0.079; 0.074-0.084) but not DWI alone (0.099; 0.091-0.108). Sensitivity and specificity were similar among the four modalities.

CONCLUSION

DCE-MRI improves AUC of tumor detection overall compared with T2-weighted imaging alone. Methods for DCE-MRI analysis require standardization, but visual analysis performs similar to semiquantitative methods. A two-parameter approach using DCE-MRI and T2-weighted imaging or DWI and T2-weighted imaging may be sufficient, and the latter may be more favorable for most routine prostate cancer imaging.

Multivariate modelling of prostate cancer combining magnetic resonance derived T2, diffusion, dynamic contrast-enhanced and spectroscopic parameters

OBJECTIVES

The objectives are determine the optimal combination of MR parameters for discriminating tumour within the prostate using linear discriminant analysis (LDA) and to compare model accuracy with that of an experienced radiologist.

METHODS

Multiparameter MRIs in 24 patients before prostatectomy were acquired. Tumour outlines from whole-mount histology, T2-defined peripheral zone (PZ), and central gland (CG) were superimposed onto slice-matched parametric maps. T2, Apparent Diffusion Coefficient, initial area under the gadolinium curve, vascular parameters (K(trans),Kep,Ve), and (choline+polyamines+creatine)/citrate were compared between tumour and non-tumour tissues. Receiver operating characteristic (ROC) curves determined sensitivity and specificity at spectroscopic voxel resolution and per lesion, and LDA determined the optimal multiparametric model for identifying tumours. Accuracy was compared with an expert observer.

RESULTS

Tumours were significantly different from PZ and CG for all parameters (all p < 0.001). Area under the ROC curve for discriminating tumour from non-tumour was significantly greater (p < 0.001) for the multiparametric model than for individual parameters; at 90 % specificity, sensitivity was 41 % (MRSI voxel resolution) and 59 % per lesion. At this specificity, an expert observer achieved 28 % and 49 % sensitivity, respectively.

CONCLUSION

The model was more accurate when parameters from all techniques were included and performed better than an expert observer evaluating these data.

KEY POINTS

• The combined model increases diagnostic accuracy in prostate cancer compared with individual parameters • The optimal combined model includes parameters from diffusion, spectroscopy, perfusion, and anatominal MRI • The computed model improves tumour detection compared to an expert viewing parametric maps.

Prostate cancer discrimination in the peripheral zone with a reduced field-of-view T(2)-mapping MRI sequence

OBJECTIVES

To evaluate the performance of T2 mapping in discriminating prostate cancer from normal prostate tissue in the peripheral zone using a practical reduced field-of-view MRI sequence requiring less than 3 minutes of scan time.

MATERIALS AND METHODS

Thirty-six patients with biopsy-proven peripheral zone prostate cancer without prior treatment underwent routine multiparametric MRI at 3.0T with an endorectal coil. An Inner-Volume Carr-Purcell-Meiboom-Gill imaging sequence that required 2.8 minutes to obtain data for quantitative T2 mapping covering the entire prostate gland was added to the routine multiparametric protocol. Suspected cancer (SC) and suspected healthy (SH) tissue in the peripheral zone were identified in consensus by three radiologists and were correlated with available biopsy results. Differences in mean T2 values in SC and SH regions-of-interest (ROIs) were tested for significance using unpaired Student's two-tailed t-test. The area under the receiver operating characteristic curve was used to assess the optimal threshold T2 value for cancer discrimination.

RESULTS

ROI analyses revealed significantly (p<0.0001) shorter T2 values in SC (85.4±12.3ms) compared to SH (169.6±38.7ms). An estimated T2 threshold of 99ms yielded a sensitivity of 92% and a specificity of 97% for prostate cancer discrimination.

CONCLUSIONS

Quantitative values derived from this clinically practical T2-mapping sequence allow high precision discrimination between healthy and cancerous peripheral zone in the prostate.

Logistic regression model for diagnosis of transition zone prostate cancer on multi-parametric MRI

OBJECTIVES

We aimed to develop logistic regression (LR) models for classifying prostate cancer within the transition zone on multi-parametric magnetic resonance imaging (mp-MRI).

METHODS

One hundred and fifty-five patients (training cohort, 70 patients; temporal validation cohort, 85 patients) underwent mp-MRI and transperineal-template-prostate-mapping (TPM) biopsy. Positive cores were classified by cancer definitions: (1) any-cancer; (2) definition-1 [≥Gleason 4 + 3 or ≥ 6 mm cancer core length (CCL)] [high risk significant]; and (3) definition-2 (≥Gleason 3 + 4 or ≥ 4 mm CCL) cancer [intermediate-high risk significant]. For each, logistic-regression mp-MRI models were derived from the training cohort and validated internally and with the temporal cohort. Sensitivity/specificity and the area under the receiver operating characteristic (ROC-AUC) curve were calculated. LR model performance was compared to radiologists' performance.

RESULTS

Twenty-eight of 70 patients from the training cohort, and 25/85 patients from the temporal validation cohort had significant cancer on TPM. The ROC-AUC of the LR model for classification of cancer was 0.73/0.67 at internal/temporal validation. The radiologist A/B ROC-AUC was 0.65/0.74 (temporal cohort). For patients scored by radiologists as Prostate Imaging Reporting and Data System (Pi-RADS) score 3, sensitivity/specificity of radiologist A 'best guess' and LR model was 0.14/0.54 and 0.71/0.61, respectively; and radiologist B 'best guess' and LR model was 0.40/0.34 and 0.50/0.76, respectively.

CONCLUSIONS

LR models can improve classification of Pi-RADS score 3 lesions similar to experienced radiologists.

KEY POINTS

• MRI helps find prostate cancer in the anterior of the gland • Logistic regression models based on mp-MRI can classify prostate cancer • Computers can help confirm cancer in areas doctors are uncertain about.

[Prostate cancer]

For many clinical issues regarding prostate cancer magnetic resonance imaging (MRI) is gaining increasing importance for prostate diagnostics. The high morphological resolution of T2-weighted sequences is unsurpassed compared to other imaging modalities. It enables not only the detection and localization of prostate cancer but also allows the evaluation of extracapsular extensions. Functional MRI methods, such as diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) MRI and proton magnetic resonance spectroscopy ((1)H-MRS) increase the specificity and to a lesser extent, the sensitivity of diagnostics. In accordance with the interdisciplinary S3 guidelines, prostate MRI is recommended for patients with at least one negative biopsy for cancer detection. According to the guidelines areas suspected of being cancerous should be selectively biopsied in addition to the systematic biopsy. The transmission of findings about the suspected tumor areas according to the structured PI-RADS classification system has proven its worth. The localization and staging of prostate carcinoma is best achieved with the help of MRI and is recommended in the S3 guidelines especially for tumors with a clinical stage cT3/4 or with a Gleason grading system score ≥8. In addition to these applications MRI is mainly used under study conditions for local recurrence or active surveillance.

Characterization of prostate cancer using T2 mapping at 3T: a multi-scanner study

RATIONALE AND OBJECTIVES

To assess the prostate T2 value as a predictor of malignancy on two different 3T scanners.

PATIENTS AND METHODS

Eighty-three pre-prostatectomy multiparametric MRIs were retrospectively evaluated [67 obtained on a General Electric MRI (scanner 1) and 16 on a Philips MRI (scanner 2)]. After correlation with prostatectomy specimens, readers measured the T2 value of regions-of-interest categorized as "cancers", "false positive lesions", or "normal tissue".

RESULTS

On scanner 1, in PZ, cancers had significantly lower T2 values than false positive lesions (P=0.02) and normal tissue (P=2×10(-9)). Gleason≥6 cancers had similar T2 values than false positive lesions and significantly higher T2 values than Gleason≥7 cancers (P=0.009). T2 values corresponding to a 25% and 75% risk of Gleason≥7 malignancy were respectively 132 ms (95% CI: 129-135 ms) and 77 ms (95% CI: 74-81 ms). In TZ, cancers had significantly lower T2 values than normal tissue (P=0.008), but not than false positive findings. Mean T2 values measured on scanner 2 were not significantly different than those measured on scanner 1 for all tissue classes.

CONCLUSION

All tested tissue classes had similar mean T2 values on both scanners. In PZ, the T2 value was a significant predictor of Gleason≥7 cancers.

Perfusion CT is a valuable diagnostic method for prostate cancer: a prospective study of 94 patients

Purpose

The aim of this study is to assess the usefulness of perfusion computer tomography (pCT) in prostate cancer (PCa) diagnostics.

Materials and Methods

94 patients with biopsy-proven PCa were enrolled in the study. Dynamic pCT of the prostate gland was performed for 50 seconds after an intravenous injection of contrast medium. Blood flow (BF), blood volume (BV), mean transit time (MTT) and permeability surface area product (PS) were computed in the suspected PCa area and in normal prostatic tissue.

Results

PCa was visible in pCT in 90 of the 94 examined patients as a focal peripheral CT enhancement. When PCa was located in the peripheral zone (PZ), it was visible on perfusion maps, mostly showing an early peak followed by wash-out. The average values of all perfusion parameters were higher for tumour than for normal prostate tissue (p < 0.000). BV and BF were dependent on tumour grade expressed by the Gleason score (GS). All PCa cases were divided into groups, according to histological grade, as low (GS ≤ 6), medium (GS = 7), and high (GS > 7). In high-grade PCa, the mean BF value was significantly higher (p = 0.001) than the mean value of BF low- and medium-grade PCa (p = 0.011). Similar results were obtained regarding the mean values of BV; the more aggressive the cancer grade, the higher the mean BV value (p = 0.04).

Conclusion

CT quantitative perfusion imaging allows PCa to be distinguished from normal prostate tissue. The highest values for BF and BV were observed in the most aggressive PCa grade.

Direct parametric reconstruction from undersampled (k, t)-space data in dynamic contrast enhanced MRI

The Magnetic Resonance Imaging (MRI) signal can be made sensitive to functional parameters that provide information about tissues. In dynamic contrast enhanced (DCE) MRI these functional parameters are related to the microvasculature environment and the concentration changes that occur rapidly after the injection of a contrast agent. Typically DCE images are reconstructed individually and kinetic parameters are estimated by fitting a pharmacokinetic model to the time-enhancement response; these methods can be denoted as "indirect". If undersampling is present to accelerate the acquisition, techniques such as kt-FOCUSS can be employed in the reconstruction step to avoid image degradation. This paper suggests a Bayesian inference framework to estimate functional parameters directly from the measurements at high temporal resolution. The current implementation estimates pharmacokinetic parameters (related to the extended Tofts model) from undersampled (k, t)-space DCE MRI. The proposed scheme is evaluated on a simulated abdominal DCE phantom and prostate DCE data, for fully sampled, 4 and 8-fold undersampled (k, t)-space data. Direct kinetic parameters demonstrate better correspondence (up to 70% higher mutual information) to the ground truth kinetic parameters (of the simulated abdominal DCE phantom) than the ones derived from the indirect methods. For the prostate DCE data, direct kinetic parameters depict the morphology of the tumour better. To examine the impact on cancer diagnosis, a peripheral zone prostate cancer diagnostic model was employed to calculate a probability map for each method.

Multiparametric magnetic resonance imaging of the prostate: technical aspects and role in clinical management

The heterogeneity and largely indolent nature of prostate cancer require better tools to avoid overdetection of low-risk disease and improve diagnostic accuracy in high-risk patients. During the last 3 decades, magnetic resonance imaging (MRI) has evolved to become the most accurate imaging technique for prostate cancer detection and staging, with a promising role in risk stratification. Because each MRI technique has advantages and limitations, state of the art of the so-called multiparametric MRI of the prostate is achieved combining anatomical T2-weighted imaging integrated with other techniques in which image contrast is related to the pathophysiology of the disease, such as diffusion-weighted imaging, dynamic contrast-enhanced imaging, and MR spectroscopy. After reviewing this article, readers will understand the clinical challenges in the management of patients with confirmed or suspected prostate cancer, when and how multiparametric MRI of the prostate can provide meaningful information, and how to perform and interpret it.

Molecular research in urology 2014: update on PET/MR imaging of the prostate

This article gives an overview of recent publications and potential indications of Positron emission tomography/ Magnetic resonance (PET/MR) imaging of prostate cancer.

A data-driven approach to prostate cancer detection from dynamic contrast enhanced MRI

Magnetic resonance imaging (MRI), particularly dynamic contrast enhanced (DCE) imaging, has shown great potential in prostate cancer diagnosis and staging. In the current practice of DCE-MRI, diagnosis is based on quantitative parameters extracted from the series of T1-weighted images acquired after the injection of a contrast agent. To calculate these parameters, a pharmacokinetic model is fitted to the T1-weighted intensities. Most models make simplistic assumptions about the perfusion process. Moreover, these models require accurate estimation of the arterial input function, which is challenging. In this work we propose a data-driven approach to characterization of the prostate tissue that uses the time series of DCE T1-weighted images without pharmacokinetic modeling. This approach uses a number of model-free empirical parameters and also the principal component analysis (PCA) of the normalized T1-weighted intensities, as features for cancer detection from DCE MRI. The optimal set of principal components is extracted with sparse regularized regression through least absolute shrinkage and selection operator (LASSO). A support vector machine classifier was used with leave-one-patient-out cross validation to determine the ability of this set of features in cancer detection. Our data is obtained from patients prior to radical prostatectomy and the results are validated based on histological evaluation of the extracted specimens. Our results, obtained on 449 tissue regions from 16 patients, show that the proposed data-driven features outperform the traditional pharmacokinetic parameters with an area under ROC of 0.86 for LASSO-isolated PCA parameters, compared to 0.78 for pharmacokinetic parameters. This shows that our novel approach to the analysis of DCE data has the potential to improve the multiparametric MRI protocol for prostate cancer detection.

Dynamic contrast-enhanced MR imaging features of the normal central zone of the prostate

RATIONALE AND OBJECTIVES

Evaluate qualitative dynamic contrast-enhanced magnetic resonance imaging (MRI) characteristics of normal central zone based on recently described central zone MRI features.

MATERIALS AND METHODS

Institutional review board-approved, Health Insurance Portability and Accountability Act compliant study, 59 patients with prostate cancer, histopathology proven to not involve central zone or prostate base, underwent endorectal MRI before prostatectomy. Two readers independently reviewed T2-weighted images and apparent diffusion coefficient (ADC) maps identifying normal central zone based on low signal intensity and location. Next, two readers drew bilateral central zone regions of interest on dynamic contrast-enhanced magnetic resonance images in consensus and independently recorded enhancement curve types as type 1 (progressive), type 2 (plateau), and type 3 (wash-out). Identification rates of normal central zone and enhancement curve type were recorded and compared for each reviewer. The institutional review board waiver was approved and granted 05/2010.

RESULTS

Central zone identified in 92%-93% of patients on T2-weighted images and 78%-88% on ADC maps without significant difference between identification rates (P = .63 and P = .15 and inter-reader agreement (κ) is 0.64 and 0.29, for T2-weighted images and ADC maps, respectively). All central zones were rated either curve type 1 or curve type 2 by both radiologists. No statistically significant difference between the two radiologists (P = .19) and inter-reader agreement was κ = 0.37.

CONCLUSIONS

Normal central zone demonstrates either type 1 (progressive) or type 2 (plateau) enhancement curves on dynamic contrast-enhanced MRI that can be potentially useful to differentiate central zone from prostate cancer that classically demonstrates a type 3 (wash-out) enhancement curve.

Diffusion-tensor MRI at 3 T: differentiation of central gland prostate cancer from benign prostatic hyperplasia

OBJECTIVE

The purpose of this article is to retrospectively evaluate the utility of diffusion-tensor imaging (DTI) at 3 T in differentiating central gland prostate cancer from benign prostatic hyperplasia (BPH).

MATERIALS AND METHODS

Eighty consecutive patients (57 with central gland cancer and 23 without central gland cancer) were included in this study. All patients underwent T2-weighted imaging and DTI at 3 T, followed by surgery. For predicting central gland cancer, experienced and less-experienced radiologists independently analyzed T2-weighted imaging and combined T2-weighted imaging and DTI, respectively. Apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values were measured for central gland cancers and BPH foci of stromal and glandular hyperplasia. Statistical analyses were performed using McNemar test, linear mixed model, receiver operating characteristic (ROC), and kappa statistics.

RESULTS

For predicting central gland cancers, the area under the curve (Az) of combined T2-weighted imaging and DTI for the experienced (0.915) and less-experienced reader (0.753) was superior to that of T2-weighted imaging (0.723 vs 0.664; p<0.001). The mean ADC and FA values were 0.77×10(-3) mm2/s and 0.35, respectively, for central gland cancers, 1.22×10(-3) mm2/s and 0.26, respectively, for stromal hyperplasia foci, and 1.59×10(-3) mm2/s and 0.21, respectively, for glandular hyperplasia foci, and the values differed significantly. For differentiating central gland cancer from stromal hyperplasia foci and glandular hyperplasia foci, Az values of ADC versus FA were 0.989 and 1.0 versus 0.818 and 0.916, respectively, and the difference was statistically different.

CONCLUSION

DTI at 3 T is useful for distinguishing central gland cancers from BPH foci, with significantly different ADC and FA values. Furthermore, ADC showed greater diagnostic accuracy than FA in differentiating central gland cancers from stromal and glandular hyperplasia foci.

Semi-quantitative parameter analysis of DCE-MRI revisited: monte-carlo simulation, clinical comparisons, and clinical validation of measurement errors in patients with type 2 neurofibromatosis

PURPOSE

To compare semi-quantitative (SQ) and pharmacokinetic (PK) parameters for analysis of dynamic contrast enhanced MR data (DCE-MRI) and investigate error-propagation in SQ parameters.

METHODS

Clinical data was collected from five patients with type 2-neurofibromatosis (NF2) receiving anti-angiogenic therapy for rapidly growing vestibular schwannoma (VS). There were 7 VS and 5 meningiomas. Patients were scanned prior to therapy and at days 3 and 90 of treatment. Data was collected using a dual injection technique to permit direct comparison of SQ and PK parameters. Monte Carlo modeling was performed to assess potential measurement errors in SQ parameters in persistent, washout, and weakly enhancing tissues. The simulation predictions for five semi-quantitative parameters were tested using the clinical DCE-MRI data.

RESULTS

In VS, SQ parameters and Ktrans showed close correlation and demonstrated similar therapy induced reductions. In meningioma, only the denoised Signal Enhancement Ratio (Rse1/se2(DN)) showed a significant therapy induced reduction (p<0.05). Simulation demonstrated: 1) Precision of SQ metrics normalized to the pre-contrast-baseline values (MSErel and ∑MSErel) is improved by use of an averaged value from multiple baseline scans; 2) signal enhancement ratio Rmse1/mse2 shows considerable susceptibility to noise; 3) removal of outlier values to produce a new parameter, Rmse1/mse2(DN), improves precision and sensitivity to therapy induced changes. Direct comparison of in-vivo analysis with Monte Carlo simulation supported the simulation predicted error distributions of semi-quantitative metrics.

CONCLUSION

PK and SQ parameters showed similar sensitivity to anti-angiogenic therapy induced changes in VS. Modeling studies confirmed the benefits of averaging baseline signal from multiple images for normalized SQ metrics and demonstrated poor noise tolerance in the widely used signal enhancement ratio, which is corrected by removal of outlier values.

Dynamic contrast-enhanced magnetic resonance imaging in prostate cancer clinical trials: potential roles and possible pitfalls

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) evaluates the tissue microvasculature and may have a role in assessing and predicting therapeutic response in prostate cancer (PCa). In this review, we review principles of DCE-MRI and present the potential quantitative information that can be obtained. We discuss how it may be used as a biomarker for treatment with antiangiogenic and antivascular agents and potentially identify patients with PCa who may benefit from this form of therapy. Likewise, DCE-MRI may play a role in assessing response to combined androgen deprivation therapy and radiation therapy and theoretically could be a prognostic biomarker in evaluating second-generation hormone therapies. We also address the challenges of using DCE-MRI in PCa clinical trials and discuss the difficulties with standardization of this methodology to allow for biomarker validation, with particular reference to PCa.

Non-Gaussian water diffusion kurtosis imaging of prostate cancer

PURPOSE

To evaluate the non-Gaussian water diffusion properties of prostate cancer (PCa) and determine the diagnostic performance of diffusion kurtosis (DK) imaging for distinguishing PCa from benign tissues within the peripheral zone (PZ), and assessing tumor lesions with different Gleason scores.

MATERIALS AND METHODS

Nineteen patients who underwent diffusion weighted (DW) magnetic resonance imaging using multiple b-values and were pathologically confirmed with PCa were enrolled in this study. Apparent diffusion coefficient (ADC) was derived using a monoexponential model, while diffusion coefficient (D) and kurtosis (K) were determined using a DK model. Differences between the ADC, D and K values of benign PZ and PCa, as well as those of tumor lesions with Gleason scores of 6, 7 and ≥8 were assessed. Correlations between parameters D and K in PCa were analyzed using Pearson's correlation coefficient. ADC, D and K values were correlated with Gleason scores of 6, 7 and ≥8, respectively.

RESULTS

ADC and D values were significantly (p<0.001) lower in PCa (0.79±0.14μm(2)/ms and 1.56±0.23μm(2)/ms, respectively) compared to benign PZ (1.23±0.19μm(2)/ms and 2.54±0.24μm(2)/ms, respectively). K values were significantly (p<0.001) greater in PCa (0.96±0.20) compared to benign PZ (0.59±0.08). D and K showed fewer overlapping values between benign PZ and PCa compared to ADC. There was a strong negative correlation between D and K values in PCa (Pearson correlation coefficient r=-0.729; p<0.001). ADC and K values differed significantly in tumor lesions with Gleason scores of 6, 7 and ≥8 (p<0.001 and p=0.001, respectively), although no significant difference was detected for D values (p=0.325). Significant correlations were found between the ADC value and Gleason score (r=-0.828; p<0.001), as well as the K value and Gleason score (r=0.729; p<0.001).

CONCLUSION

DK model may add value in PCa detection and diagnosis. K potentially offers a new metric for assessment of PCa.

Multidimensional MR spectroscopic imaging of prostate cancer in vivo

Prostate cancer (PCa) is the second most common type of cancer among men in the United States. A major limitation in the management of PCa is an inability to distinguish, early on, cancers that will progress and become life threatening. One-dimensional (1D) proton ((1)H) MRS of the prostate provides metabolic information such as levels of choline (Ch), creatine (Cr), citrate (Cit), and spermine (Spm) that can be used to detect and diagnose PCa. Ex vivo high-resolution magic angle spinning (HR-MAS) of PCa specimens has revealed detection of more metabolites such as myo-inositol (mI), glutamate (Glu), and glutamine (Gln). Due to the J-modulation and signal overlap, it is difficult to quantitate Spm and other resonances in the prostate clearly by single- and multivoxel-based 1D MR spectroscopy. This limitation can be minimized by adding at least one more spectral dimension by which resonances can be spread apart, thereby increasing the spectral dispersion. However, recording of multivoxel-based two-dimensional (2D) MRS such as J-resolved spectroscopy (JPRESS) and correlated spectroscopy (L-COSY) combined with 2D or three-dimensional (3D) magnetic resonance spectroscopic imaging (MRSI) using conventional phase-encoding can be prohibitively long to be included in a clinical protocol. To reduce the long acquisition time required for spatial encoding, the echo-planar spectroscopic imaging (EPSI) technique has been combined with correlated spectroscopy to give four-dimensional (4D) echo-planar correlated spectroscopic imaging (EP-COSI) as well as J-resolved spectroscopic imaging (EP-JRESI) and the multi-echo (ME) variants. Further acceleration can be achieved using non-uniform undersampling (NUS) and reconstruction using compressed sensing (CS). Earlier versions of 2D MRS, theory of 2D MRS, spectral apodization filters, newer developments and the potential role of multidimensional MRS in PCa detection and management will be reviewed here.

Role of high-field MR in studies of localized prostate cancer

Magnetic resonance imaging is attracting increasing attention from the uroradiological community as a modality to guide the management of prostate cancer. With the high incidence of prostate cancer it might come as a surprise that for a very long time (and in many places even at present) treatment decisions were being made without the use of detailed anatomical and functional imaging of the prostate gland at hand. Although T2 -weighted MRI can provide great anatomical detail, by itself it is not specific enough to discriminate cancer from benign disease, so other functional MRI techniques have been explored to aid in detection, localization, staging and risk assessment of prostate cancer. With the current evolution of clinical MR systems from 1.5 to 3 T it is important to understand the advantages and the challenges of the higher magnetic field strength for the different functional MR techniques most used in the prostate: T2 -weighted MRI, diffusion-weighted MRI, MR spectroscopic imaging and dynamic contrast-enhanced imaging. In addition to this, the use of the endorectal coil at different field strengths is discussed in this review, together with an outlook of the possibilities of ultra-high-field MR for the prostate.

Imaging and Markers as Novel Diagnostic Tools in Detecting Insignificant Prostate Cancer: A Critical Overview

Recent therapeutic advances for managing low-risk prostate cancer include the active surveillance and focal treatment. However, locating a tumor and detecting its volume by adequate sampling is still problematic. Development of predictive biomarkers guiding individual therapeutic choices remains an ongoing challenge. At the same time, prostate cancer magnetic resonance imaging is gaining increasing importance for prostate diagnostics. The high morphological resolution of T2-weighted imaging and functional MRI methods may increase the specificity and sensitivity of diagnostics. Also, recent studies founded an ability of novel biomarkers to identify clinically insignificant prostate cancer, risk of progression, and association with poor differentiation and, therefore, with clinical significance. Probably, the above mentioned methods would improve tumor characterization in terms of its volume, aggressiveness, and focality. In this review, we attempted to evaluate the applications of novel imaging techniques and biomarkers in assessing the significance of the prostate cancer.

The role of magnetic resonance imaging in the diagnosis and management of prostate cancer

BACKGROUND

The diagnosis of prostate cancer has long been plagued by the absence of an imaging tool that reliably detects and localises significant tumours. Recent evidence suggests that multi-parametric MRI could improve the accuracy of diagnostic assessment in prostate cancer. This review serves as a background to a recent USANZ position statement. It aims to provide an overview of MRI techniques and to critically review the published literature on the clinical application of MRI in prostate cancer.

TECHNICAL ASPECTS

The combination of anatomical (T2-weighted) MRI with at least two of the three functional MRI parameters - which include diffusion-weighted imaging, dynamic contrast-enhanced imaging and spectroscopy - will detect greater than 90% of significant (moderate to high risk) tumours; however MRI is less reliable at detecting tumours that are small (<0.5 cc), low grade (Gleason score 6) or in the transitional zone. The higher anatomical resolution provided by 3-Tesla magnets and endorectal coils may improve the accuracy, particularly in primary tumour staging.

SCREENING

The use of mpMRI to determine which men with an elevated PSA should undergo biopsy is currently the subject of two large clinical trials in Australia. MRI should be used with caution in this setting and then only in centres with established uro-radiological expertise and quality control mechanisms in place. There is sufficient evidence to justify using MRI to determine the need for repeat biopsy and to guide areas in which to focus repeat biopsy.

IMAGE-DIRECTED BIOPSY

MRI-directed biopsy is an exciting concept supported by promising early results, but none of the three proposed techniques have so far been proven superior to standard biopsy protocols. Further evidence of superior accuracy and core-efficiency over standard biopsy is required, before their costs and complexities in use can be justified.

TREATMENT SELECTION AND PLANNING

When used for primary-tumour staging (T-staging), MRI has limited sensitivity for T3 disease, but its specificity of greater than 95% may be useful in men with intermediate-high risk disease to identify those with advanced T3 disease not suitable for nerve sparing or for surgery at all. MRI appears to be of value in planning dosimetry in men undergoing radiotherapy, and in guiding selection for and monitoring on active surveillance.

Clinical utility of endorectal MRI-guided prostate biopsy: preliminary experience

PURPOSE

To investigate the potential clinical utility of endorectal MRI-guided biopsy in patients with known or suspected prostate cancer.

MATERIALS AND METHODS

We prospectively recruited 24 men with known or suspected prostate cancer in whom MRI-guided biopsy was clinically requested after multiparametric endorectal MRI showed one or more appropriate targets. One to six 18-gauge biopsy cores were obtained from each patient. Transrectal ultrasound guided biopsy results and post MRI-guided biopsy complications were also recorded.

RESULTS

MRI-guided biopsy was positive in 5 of 7 patients with suspected prostate cancer (including 2 of 4 with prior negative ultrasound-guided biopsies), in 8 of 12 with known untreated prostate cancer (including 5 where MRI-guided biopsy demonstrated a higher Gleason score than ultrasound guided biopsy results), and in 3 of 5 with treated cancer. MRI-guided biopsies had a significantly higher maximum percentage of cancer in positive cores when compared with ultrasound guided biopsy (mean of 37 ± 8% versus 13 ± 4%; P = 0.01). No serious postbiopsy complications occurred.

CONCLUSION

Our preliminary experience suggests endorectal MRI-guided biopsy may safely contribute to the management of patients with known or suspected prostate cancer by making a new diagnosis of malignancy, upgrading previously diagnosed disease, or diagnosing local recurrence.

3 Tesla multiparametric MRI for GTV-definition of Dominant Intraprostatic Lesions in patients with Prostate Cancer--an interobserver variability study

PURPOSE

To evaluate the interobserver variability of gross tumor volume (GTV) - delineation of Dominant Intraprostatic Lesions (DIPL) in patients with prostate cancer using published MRI criteria for multiparametric MRI at 3 Tesla by 6 different observers.

MATERIAL AND METHODS

90 GTV-datasets based on 15 multiparametric MRI sequences (T2w, diffusion weighted (DWI) and dynamic contrast enhanced (DCE)) of 5 patients with prostate cancer were generated for GTV-delineation of DIPL by 6 observers. The reference GTV-dataset was contoured by a radiologist with expertise in diagnostic imaging of prostate cancer using MRI. Subsequent GTV-delineation was performed by 5 radiation oncologists who received teaching of MRI-features of primary prostate cancer before starting contouring session. GTV-datasets were contoured using Oncentra Masterplan® and iplan® Net. For purposes of comparison GTV-datasets were imported to the Artiview® platform (Aquilab®), GTV-values and the similarity indices or Kappa indices (KI) were calculated with the postulation that a KI > 0.7 indicates excellent, a KI > 0.6 to < 0.7 substantial and KI > 0.5 to < 0.6 moderate agreement. Additionally all observers rated difficulties of contouring for each MRI-sequence using a 3 point rating scale (1 = easy to delineate, 2 = minor difficulties, 3 = major difficulties).

RESULTS

GTV contouring using T2w (KI-T2w = 0.61) and DCE images (KI-DCE = 0.63) resulted in substantial agreement. GTV contouring using DWI images resulted in moderate agreement (KI-DWI = 0.51). KI-T2w and KI-DCE was significantly higher than KI-DWI (p = 0.01 and p = 0.003). Degree of difficulty in contouring GTV was significantly lower using T2w and DCE compared to DWI-sequences (both p < 0.0001). Analysis of delineation differences revealed inadequate comparison of functional (DWI, DCE) to anatomical sequences (T2w) and lack of awareness of non-specific imaging findings as a source of erroneous delineation.

CONCLUSIONS

Using T2w and DCE sequences at 3 Tesla for GTV-definition of DIPL in prostate cancer patients by radiation oncologists with knowledge of MRI features results in substantial agreement compared to an experienced MRI-radiologist, but for radiotherapy purposes higher KI are desirable, strengthen the need for expert surveillance. DWI sequence for GTV delineation was considered as difficult in application.

Interscanner comparison of dynamic contrast-enhanced MRI in prostate cancer: 1.5 versus 3 T MRI

PURPOSE

The aim of the study was the comparison of the diagnostic potential of dynamic contrast-enhanced magnetic resonance imaging to differentiate between prostate carcinoma and normal prostate tissue as well as prostatitis at 2 different field strengths: 1.5 versus 3 T.

METHODS

Sixty-six patients with biopsy and/or prostatectomy of the prostate were included in the study. Magnetic resonance imaging was performed at 1.5 T in 20 patients with biopsy-proven prostate cancer (PC) and in 8 patients with prostatitis; at 3 T, we analyzed 27 patients with prostatectomy-proven PC and 11 patients with prostatitis. All examinations were performed using a combined body and endorectal coil protocol and a 2-dimensional TurboFLASH T1-weighted gradient echo sequence to calculate plasma flow (PF) and mean transit time (MTT) values. A total of 28 of 38 areas of normal prostate tissue, 20 of 27 areas of PC, and 8 of 11 prostatitis were analyzed at 1.5 or 3T. For the normalization, we calculated PC/normal and prostatitis/normal tissue ratios of PF and MTT for each patient.

RESULTS

Prostate cancer showed higher PF (P < 0.0001) and shorter MTT (P < 0.0001) at 3 T and at 1.5 T (P < 0.0001 for PF and P = 0.0016 for MTT) compared with the normal tissue. In comparison with the normal tissue, prostatitis had a statistically significant higher PF at 1.5 T (P = 0.0156) but not at 3 T (P = 0.17) and no significantly shorter MTT values both at 3 (P = 0.15) and 1.5 T (P = 0.25). Sensitivity and specificity for differentiating PC from prostatitis with PF were 46% and 88% at 1.5 T (cutoff ratio, 2.3) and 89% and 73% at 3 T (cutoff ratio, 1.2), respectively. Sensitivity and specificity for MTT were 77% and 100% at 1.5 T (cutoff ratio, 0.7) and 70% and 100% at 3 T (cutoff ratio, 0.6), respectively. We found no significant relationship between the Gleason score and PF/MTT (P = 0.17/0.11 for 1.5 T and P = 0.23/0.18 for 3 T).

CONCLUSIONS

The differentiation between PC and the normal tissue is possible with both field strengths. Prostate cancer can be better distinguished from prostatitis at 3 T compared with 1.5 T. The differentiation between prostatitis and the normal tissue is limited at both field strengths.

Prostatic arterial embolization: post-procedural follow-up

Prostatic arterial embolization (PAE) gained special attention in the past years as a potential minimally invasive technique for benign prostatic hyperplasia. Treatment decisions are based on morbidity and quality-of-life issues and the patient has a central role in decision-making. Medical therapy is a first-line treatment option and surgery is usually performed to improve symptoms and decrease the progression of disease in patients who develop complications or who have inadequately controlled symptoms on medical treatment. The use of validated questionnaires to assess disease severity and sexual function, uroflowmetry studies, prostate-specific antigen and prostate volume measurements are essential when evaluating patients before PAE and to evaluate response to treatment. PAE may be performed safely with minimal morbidity and without associated mortality. The minimally invasive nature of the technique inducing a significant improvement in symptom severity associated with prostate volume reduction and a slight improvement in the sexual function are major advantages. However, as with other surgical therapies for benign prostatic hyperplasia, up to 15% of patients fail to show improvement significantly after PAE, and there is a modest improvement of the peak urinary flow.