Magnetic resonance imaging in prostate cancer: the value of apparent diffusion coefficients for identifying malignant nodules

Quantification of Multi-Parametric Magnetic Resonance Imaging Based on Radiomics Analysis for Differentiation of Benign and Malignant Lesions of Prostate

Background

The most common cancer (non-cutaneous) malignancy among men is prostate cancer. Management of prostate cancer, including staging and treatment, playing an important role in decreasing mortality rates. Among all current diagnostic tools, multiparametric MRI (mp-MRI) has shown high potential in localizing and staging prostate cancer. Quantification of mp-MRI helps to decrease the dependency of diagnosis on readers' opinions.

Objective

The aim of this research is to set a method based on quantification of mp-MRI images for discrimination between benign and malignant prostatic lesions with fusion-guided MR imaging/transrectal ultrasonography biopsy as a pathology validation reference.

Material and Methods

It is an analytical research that 27 patients underwent the mp-MRI examination, including T1- and T2- weighted and diffusion weighted imaging (DWI). Quantification was done by calculating radiomic features from mp-MRI images. Receiver-operating-characteristic curve was done for each feature to evaluate the discriminatory capacity and linear discriminant analysis (LDA) and leave-one-out cross-validation for feature filtering to estimate the sensitivity, specificity and accuracy of the benign and malignant lesion differentiation process is used.

Results

An accuracy, sensitivity and specificity of 92.6%, 95.2% and 83.3%, respectively, were achieved from a subset of radiomics features obtained from T2-weighted images and apparent diffusion coefficient (ADC) maps for distinguishing benign and malignant prostate lesions.

Conclusion

Quantification of mp-MRI (T2-weighted images and ADC-maps) based on radiomics feature has potential to distinguish benign with appropriate accuracy from malignant prostate lesions. This technique is helpful in preventing needless biopsies in patients and provides an assisted diagnosis for classifications of prostate lesions.

Algorithms applied to spatially registered multi-parametric MRI for prostate tumor volume measurement

Background

Prostate tumor volume correlates with critical components of cancer staging such as Gleason score (GS) grade, predicted disease progression, and metastasis. Therefore, non-invasive tumor volume measurement may elevate clinical management. Radiology assessments of multi-parametric MRI (MP-MRI) commonly visually examine individual images to determine possible tumor presence. This study combines registered MP-MRI into a single image that display normal tissue and possible lesions. This study tests and exploits the vector nature of spatially registered MP-MRI by using supervised target detection algorithms (STDA) and color display and psychovisual analysis (CIELAB) to non-invasively estimate prostate tumor volume.

Methods

MRI, including T1, T2, diffusion [apparent diffusion coefficient (ADC)], dynamic contrast enhanced (DCE) images, were resampled, rescaled, translated, and stitched to form spatially registered Multi-parametric cubes. The multi-parametric or multi-spectral signatures (7-component or T1, T2, ADC, etc.) that characterize the prostate tumors were inserted into target detection algorithms with conical decision surfaces (adaptive cosine estimator, ACE). Various detection thresholds were applied to discriminate tumor from normal tissue. In addition, tumor appeared as yellow in color images that were created by assigning red to washout from DCE, green to high B from diffusion, and blue to autonomous diffusion image. The yellow voxels in the three-channel hypercube were visually identified by a reader and recording voxels that exceed a threshold in the b* component of the CIELAB algorithm. The number of reported tumor voxels were converted to volume based on spatial resolution and slice separation. The tumor volume measurements were quantitatively validated by comparing the tumor volume computations to the pathologist's assessment of the histology of sectioned whole mount prostates from 26 consecutive patients with prostate adenocarcinoma who underwent radical prostatectomy. This study analyzed tumors exceeding 1 cc and that also took up contrast material (18 patients).

Results

High correlation coefficients for tumor volume measurements using supervised target detection and color analysis vs. histology from wholemount prostatectomy were computed (R=0.83 and 0.91, respectively). A linear fit for tumor volume measurements using for supervised target detection and color analysis vs. tumor measurements from radical prostatectomy (after correcting for shrinkage from the radical prostatectomy) results in a slope of 1.02 and 3.02, respectively. A polynomial fit for the color analysis to the histology found (R=0.95). Voxels exceeding a threshold in the b* part of the CIELAB algorithm yielded correlation coefficients (0.71, 0.80) offsets (0.01 cc, -0.63 cc) and slopes (1.99, 0.89) against the wholemount prostatectomy and color analysis, respectively.

Conclusions

Supervised target detection and color display and analysis applied to registered MP-MRI non-invasively estimates prostate tumor volumes >1 cc and displaying angiogenesis.

Validation of T2- and diffusion-weighted magnetic resonance imaging for mapping intra-prostatic tumour prior to focal boost dose-escalation using intensity-modulated radiotherapy (IMRT)

BACKGROUND AND PURPOSE

To assess the diagnostic accuracy and inter-observer agreement of T2-weighted (T2W) and diffusion-weighted (DW) magnetic resonance imaging (MRI) for mapping intra-prostatic tumour lesions (IPLs) for the purpose of focal dose-escalation in prostate cancer radiotherapy.

MATERIALS AND METHODS

Twenty-six men selected for radical treatment with radiotherapy were recruited prospectively and underwent pre-treatment T2W+DW-MRI and 5 mm spaced transperineal template-guided mapping prostate biopsies (TTMPB). A 'traffic-light' system was used to score both data sets. Radiologically suspicious lesions measuring ≥0.5 cm3 were classified as red; suspicious lesions 0.2-0.5 cm3 or larger lesions equivocal for tumour were classified as amber. The histopathology assessment combined pathological grade and tumour length on biopsy (red = ≥4 mm primary Gleason grade 4/5 or ≥6 mm primary Gleason grade 3). Two radiologists assessed the MRI data and inter-observer agreement was measured with Cohens' Kappa co-efficient.

RESULTS

Twenty-five of 26 men had red image-defined IPLs by both readers, 24 had red pathology-defined lesions. There was a good correlation between lesions ≥0.5 cm3 classified "red" on imaging and "red" histopathology in biopsies (Reader 1: r = 0.61, p < 0.0001, Reader 2: r = 0.44, p = 0.03). Diagnostic accuracy for both readers for red image-defined lesions was sensitivity 85-86%, specificity 93-98%, positive predictive value (PPV) 79-92% and negative predictive value (NPV) 96%. Inter-observer agreement was good (Cohen's Kappa 0.61).

CONCLUSIONS

MRI is accurate for mapping clinically significant prostate cancer; diffusion-restricted lesions ≥0.5 cm3 can be confidently identified for radiation dose boosting.

Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer

OBJECTIVE

To develop different radiomic models based on the magnetic resonance imaging (MRI) radiomic features and machine learning methods to predict early intensity-modulated radiation therapy (IMRT) response, Gleason scores (GS) and prostate cancer (Pca) stages.

METHODS

Thirty-three Pca patients were included. All patients underwent pre- and post-IMRT T2-weighted (T2 W) and apparent diffusing coefficient (ADC) MRI. IMRT response was calculated in terms of changes in the ADC value, and patients were divided as responders and non-responders. A wide range of radiomic features from different feature sets were extracted from all T2 W and ADC images. Univariate radiomic analysis was performed to find highly correlated radiomic features with IMRT response, and a paired t test was used to find significant features between responders and non-responders. To find high predictive radiomic models, tenfold cross-validation as the criterion for feature selection and classification was applied on the pre-, post- and delta IMRT radiomic features, and area under the curve (AUC) of receiver operating characteristics was calculated as model performance value.

RESULTS

Of 33 patients, 15 patients (45%) were found as responders. Univariate analysis showed 20 highly correlated radiomic features with IMRT response (20 ADC and 20 T2). Two and fifteen T2 and ADC radiomic features were found as significant (P-value ≤ 0.05) features between responders and non-responders, respectively. Several cross-combined predictive radiomic models were obtained, and post-T2 radiomic models were found as high predictive models (AUC 0.632) followed by pre-ADC (AUC 0.626) and pre-T2 (AUC 0.61). For GS prediction, T2 W radiomic models were found as more predictive (mean AUC 0.739) rather than ADC models (mean AUC 0.70), while for stage prediction, ADC models had higher prediction performance (mean AUC 0.675).

CONCLUSIONS

Radiomic models developed by MR image features and machine learning approaches are noninvasive and easy methods for personalized prostate cancer diagnosis and therapy.

A biomimetic tumor tissue phantom for validating diffusion-weighted MRI measurements

PURPOSE

To develop a biomimetic tumor tissue phantom which more closely reflects water diffusion in biological tissue than previously used phantoms, and to evaluate the stability of the phantom and its potential as a tool for validating diffusion-weighted (DW) MRI measurements.

METHODS

Coaxial-electrospraying was used to generate micron-sized hollow polymer spheres, which mimic cells. The bulk structure was immersed in water, providing a DW-MRI phantom whose apparent diffusion coefficient (ADC) and microstructural properties were evaluated over a period of 10 months. Independent characterization of the phantom's microstructure was performed using scanning electron microscopy (SEM). The repeatability of the construction process was investigated by generating a second phantom, which underwent high resolution synchrotron-CT as well as SEM and MR scans.

RESULTS

ADC values were stable (coefficients of variation (CoVs) < 5%), and varied with diffusion time, with average values of 1.44 ± 0.03 µm2 /ms (Δ = 12 ms) and 1.20 ± 0.05 µm2 /ms (Δ = 45 ms). Microstructural parameters showed greater variability (CoVs up to 13%), with evidence of bias in sphere size estimates. Similar trends were observed in the second phantom.

CONCLUSION

A novel biomimetic phantom has been developed and shown to be stable over 10 months. It is envisaged that such phantoms will be used for further investigation of microstructural models relevant to characterizing tumor tissue, and may also find application in evaluating acquisition protocols and comparing DW-MRI-derived biomarkers obtained from different scanners at different sites. Magn Reson Med 80:147-158, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

The efficacy and utilisation of preoperative multiparametric magnetic resonance imaging in robot-assisted radical prostatectomy: does it change the surgical dissection plan?

Objective

We investigated the effect of the use of multiparametric prostate magnetic resonance imaging (mp-MRI) on the dissection plan of the neurovascular bundle and the oncological results of our patients who underwent robot-assisted radical prostatectomy.

Material and methods

We prospectively evaluated 60 consecutive patients, including 30 patients who had (Group 1), and 30 patients who had not (Group 2) mp-MRI before robot-assisted radical prostatectomy. Based on the findings of mp-MRI, the dissection plan was changed as intrafascial, interfascial, and extrafascial in the mp-MRI group. Two groups were compared in terms of age, prostate-specific antigen (PSA), Gleason sum scores and surgical margin positivity.

Results

There was no statistically significant difference between the two groups in terms of age, PSA, biopsy Gleason score, final pathological Gleason score and surgical margin positivity. mp-MRI changed the initial surgical plan in 18 of 30 patients (60%) in Group 1. In seventeen of these patients (56%) surgical plan was changed from non-nerve sparing to interfascial nerve sparing plan. In one patient dissection plan was changed to non-nerve sparing technique which had extraprostatic extension on final pathology. Surgical margin positivity was similar in Groups 1, and 2 (16% and 13%, respectively) although, Group 1 had higher number of high- risk patients. mp-MRI confirmed the primary tumour localisation in the final pathology in 27 of of 30 patients (90%).

Conclusion

Preoperative mp-MRI effected the decision to perform a nerve-sparing technique in 56% of the patients in our study; moreover, changing the dissection plan from non-nerve-sparing technique to a nerve sparing technique did not increase the rate of surgical margin positivity.

Geometric distortion correction in prostate diffusion-weighted MRI and its effect on quantitative apparent diffusion coefficient analysis

PURPOSE

To evaluate the effect of correction for B₀ inhomogeneity-induced geometric distortion in echo-planar diffusion-weighted imaging on quantitative apparent diffusion coefficient (ADC) analysis in multiparametric prostate MRI.

METHODS

Geometric distortion correction was performed in echo-planar diffusion-weighted images (b = 0, 50, 400, 800 s/mm² ) of 28 patients, using two b₀ scans with opposing phase-encoding polarities. Histology-matched tumor and healthy tissue volumes of interest delineated on T₂ -weighted images were mapped to the nondistortion-corrected and distortion-corrected data sets by resampling with and without spatial coregistration. The ADC values were calculated on the volume and voxel level. The effect of distortion correction on ADC quantification and tissue classification was evaluated using linear-mixed models and logistic regression, respectively.

RESULTS

Without coregistration, the absolute differences in tumor ADC (range: 0.0002-0.189 mm² /s×10^-3 (volume level); 0.014-0.493 mm² /s×10^-3 (voxel level)) between the nondistortion-corrected and distortion-corrected were significantly associated (P < 0.05) with distortion distance (mean: 1.4 ± 1.3 mm; range: 0.3-5.3 mm). No significant associations were found upon coregistration; however, in patients with high rectal gas residue, distortion correction resulted in improved spatial representation and significantly better classification of healthy versus tumor voxels (P < 0.05).

CONCLUSIONS

Geometric distortion correction in DWI could improve quantitative ADC analysis in multiparametric prostate MRI. Magn Reson Med 79:2524-2532, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Multiparametric Magnetic Resonance Imaging of the Prostate for Tumour Detection and Local Staging: Imaging in 1.5T and Histopathologic Correlation

PURPOSE

The study sought to prospectively evaluate which technique among T2-weighted images, dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), diffusion-weighted (DW) MRI, or a combination of the 2, is best suited for prostate cancer detection and local staging.

METHODS

Twenty-seven consecutive patients with biopsy-proven adenocarcinoma of the prostate underwent MRI on a 1.5T scanner with a surface phased-array coil prior radical prostatectomy. Combined anatomical and functional imaging was performed with the use of T2-weighted sequences, DCE MRI, and DW MRI. We compared the imaging results with whole mount histopathology.

RESULTS

For the multiparametric approach, significantly higher sensitivity values, that is, 53% (95% confidence interval [CI]: 41.0-64.1) were obtained as compared with each modality alone or any combination of the 3 modalities (P < .05). The specificity for this multiparametric approach, being 90.3% (95% CI: 86.3-93.3) was not significantly higher (P < .05) as compared with the values of the combination of T2+DCE MRI, DW+DCE MRI, or DCE MRI alone. Among the 3 techniques, DCE had the best performance for tumour detection in both the peripheral and the transition zone. High negative predictive value rates (>86%) were obtained for both tumour detection and local staging.

CONCLUSIONS

The combination of T2-weighted sequences, DCE MRI, and DW MRI yields higher diagnostic performance for tumour detection and local staging than can any of these techniques alone or even any combination of them.

Multiparametric MRI in the Detection of Clinically Significant Prostate Cancer

Prostate cancer is the most common cancer among men aged 50 years and older in developed countries and the third leading cause of cancer-related death in men. Multiparametric prostate MR imaging is currently the most accurate imaging modality to detect, localize, and stage prostate cancer. The role of multi-parametric MR imaging in the detection of clinically significant prostate cancer are discussed. In addition, insights are provided in imaging techniques, protocol, and interpretation.

Application of an unsupervised multi-characteristic framework for intermediate-high risk prostate cancer localization using diffusion-weighted MRI

PURPOSE

The aim of this proof-of-concept work is to propose an unsupervised framework that combines multiple parameters, in "positive-if-all-positive" manner, from different models to localize tumors.

METHODS

A voxel-by-voxel analysis of the DW-MRI images of whole prostate was performed to obtain parametric maps for D*, D, f, and K using the IVIM and kurtosis models. Ten patients with moderate or high-risk prostate cancer were included in study. The mean age and serum PSA for these 10 patients were 65years (range 54-78) and 21.9ng/mL (range 4.84-44.81), respectively. These patients were scanned using a DW spin-echo sequence with echo-planar readout with 16 equidistantly spaced b-values in the range of 0-2000s/mm² (TE=58ms; TR=3990ms; spatial resolution 2.19×2.19×2.73mm³, slices =26, FOV=140×140mm, slice gap =0.27mm, NSA=2).

RESULTS

The proposed framework detected 24 lesions of which 14 were true positive with 58% tumor detection rate on lesion-based analysis with sensitivity of 100%. The mpMRI evaluation (PIRADSv2) identified 12 of 14 true positive lesions with sensitivity of 86%; positive predictive value of mpMRI was 92%. The index lesions were visible on all framework maps and were coded as the most suspicious in 9 of 10 patients.

CONCLUSION

Preliminary results of the proposed framework indicate high patient-based sensitivity with 100% detection rate for identifying moderate-high risk aggressive index lesions.

Anterior prostate cancer: Current perspectives and diagnostic dilemmas

Anterior zone (transition zone and anterior horn of peripheral zone) tumours represent 20–30% of all prostate cancers. Traditional transrectal prostate biopsies fail to sample this area of the prostate gland adequately, thereby underestimating the true extent of anterior zone cancers. This article outlines the behaviour and significance of this entity and discusses investigations that are currently available which may aid in their detection. The implementation of transperineal template-guided prostate biopsies will allow optimal sampling of the anterior zone whilst advances in the field of magnetic resonance imaging allow the use of multiple sequences (T2-weighted, spectroscopy, diffusion weighted and dynamic contrast enhancement) to identify these tumours accurately. Such investigations will result in more accurate risk stratification compared with the current diagnostic pathway, and could lead to improved management in this subset of men.

Tissue Microstructure Is Linked to MRI Parameters and Metabolite Levels in Prostate Cancer

INTRODUCTION

Magnetic resonance imaging (MRI) can portray spatial variations in tumor heterogeneity, architecture, and its microenvironment in a non-destructive way. The objective of this study was to assess the relationship between MRI parameters measured on patients in vivo, individual metabolites measured in prostatectomy tissue ex vivo, and quantitative histopathology.

MATERIALS AND METHODS

Fresh frozen tissue samples (n = 53 from 15 patients) were extracted from transversal prostate slices and linked to in vivo MR images, allowing spatially matching of ex vivo measured metabolites with in vivo MR parameters. Color-based segmentation of cryosections of each tissue sample was used to identify luminal space, stroma, and nuclei.

RESULTS

Cancer samples have significantly lower area percentage of lumen and higher area percentage of nuclei than non-cancer samples (p ≤ 0.001). Apparent diffusion coefficient is significantly correlated with percentage area of lumen (ρ = 0.6, p < 0.001) and percentage area of nuclei (ρ = -0.35, p = 0.01). There is a positive correlation (ρ = 0.31, p = 0.053) between citrate and percentage area of lumen. Choline is negatively correlated with lumen (ρ = -0.38, p = 0.02) and positively correlated with percentage area of nuclei (ρ = 0.38, p = 0.02).

CONCLUSION

Microstructures that are observed by histopathology are linked to MR characteristics and metabolite levels observed in prostate cancer.

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

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

Role of multiparametric magnetic resonance imaging in early detection of prostate cancer

Abstract

Most prostate cancers (PC) are currently found on the basis of an elevated PSA, although this biomarker has only moderate accuracy. Histological confirmation is traditionally obtained by random transrectal ultrasound guided biopsy, but this approach may underestimate PC. It is generally accepted that a clinically significant PC requires treatment, but in case of an non-significant PC, deferment of treatment and inclusion in an active surveillance program is a valid option. The implementation of multiparametric magnetic resonance imaging (mpMRI) into a screening program may reduce the risk of overdetection of non-significant PC and improve the early detection of clinically significant PC. A mpMRI consists of T2-weighted images supplemented with diffusion-weighted imaging, dynamic contrast enhanced imaging, and/or magnetic resonance spectroscopic imaging and is preferably performed and reported according to the uniform quality standards of the Prostate Imaging Reporting and Data System (PIRADS). International guidelines currently recommend mpMRI in patients with persistently rising PSA and previous negative biopsies, but mpMRI may also be used before first biopsy to improve the biopsy yield by targeting suspicious lesions or to assist in the selection of low-risk patients in whom consideration could be given for surveillance.

Teaching Points

• MpMRI may be used to detect or exclude significant prostate cancer.

• MpMRI can guide targeted rebiopsy in patients with previous negative biopsies.

• In patients with negative mpMRI consideration could be given for surveillance.

• MpMRI may add valuable information for the optimal treatment selection.

Apparent Diffusion Coefficient Value Is Not Dependent on Magnetic Resonance Systems and Field Strength Under Fixed Imaging Parameters in Brain

OBJECTIVE

The aim of the study was to investigate the causes of apparent diffusion coefficient (ADC) measurement errors and to determine the optimal scanning parameters that are independent of the field strength and vendors of the magnetic resonance (MR) system.

MATERIALS AND METHODS

Brain MR images of 10 healthy volunteers were scanned using 6 MR scanners of different field strengths and vendors in 2 different institutions. Ethical review board approvals were obtained for this study, and all volunteers gave their informed consents. Coefficient of variation (CV) of ADC values were compared for their differences in various MR scanners and in the scanned subjects.

RESULTS

The CV of ADC values for 6 different scanners of 6 brains was 3.32%. The CV for repeated measurements in 1 day (10 scans per day) and in 10 days (scan per day for 10 days) for 1 subject was 1.72% and 2.96%, respectively (n = 5, P < 0.001). The CV of measurements for 10 healthy subjects was 5.22%. The measurement errors of the ADC values for 6 different MR units in 1 subject were higher than the intrascanner variance for the same subject but were lower than the intersubject variance for the same scanner.

CONCLUSIONS

The variance in the ADC values for different MR scanners is reasonably small if appropriate scanning parameters (repetition time, >3000 ms; echo time, minimum; and high enough signal-to-noise ratio of high-b diffusion-weighted image) are used.

Evaluation of Imaging Quality and ADC for the Tetrahedral Gradients of Diffusion Weighted Imaging

The diffusion weighted images (DWIs) are used widely in clinical practice. Recently, the gradient overplus imaging was developed in addition to orthogonal technique for the duration method of motion-probing gradient pulses. The gradient overplus technique can reduce the load of a gradient strength, and enables setting of the shortest TE compared with the orthogonal gradients, and moreover it has the information on diffusion tensor. The apparent diffusion coefficient (ADC) values, signal-to-noise ratio (SNR), and geometric distortion were compared for the two duration methods of DWI using four different phantoms of coefficient of viscosity. In the gradient overplus, the time of smallest TE became smaller than the orthogonal gradients according to the increase of the b value. As a result, SNR increased by shortening of TE, and thus the geometric distortion was improved. Moreover, the ADC value did not show any difference in the two duration methods of DWI. The gradient overplus technique is a more useful technique in a clinical study than the orthogonal gradients because the quality of image is improved, and the ADC value is the same as the orthogonal gradients.

Diffusion weighted magnetic resonance imaging and its recent trend-a survey

Since its inception in 1985, diffusion weighted magnetic resonance imaging has been evolving and is becoming instrumental in diagnosis and investigation of tissue functions in various organs including brain, cartilage, and liver. Even though brain related pathology and/or investigation remains as the main application, diffusion weighted magnetic resonance imaging (DWI) is becoming a standard in oncology and in several other applications. This review article provides a brief introduction of diffusion weighted magnetic resonance imaging, challenges involved and recent advancements.

Update and current status of diffusion-weighted MRI in anorectal malignancy

SUMMARY 

Diffusion-weighted imaging (DWI) is an MRI technique that yields unique information regarding the movement of water molecules at the cellular level. Now widely available and rapid to perform the sequence is increasingly utilized within abdominopelvic oncology, including anorectal cancer imaging. Unfortunately, the diffusion properties of anorectal tumors are complex and not fully understood, with areas of cellular tumor, necrosis and fibrosis co-existing. While DWI shows promise both for staging and in assessing treatment response in anorectal cancer, there remains a lack of consensus regarding its role and integration into standard MRI protocols. This article outlines the basic science behind DWI and reviews the current evidence base for its use in anorectal cancer.

Apparent Ultra-High b-Value Diffusion-Weighted Image Reconstruction via Hidden Conditional Random Fields

A promising, recently explored, alternative to ultra-high b-value diffusion weighted imaging (UHB-DWI) is apparent ultra-high b-value diffusion-weighted image reconstruction (AUHB-DWR), where a computational model is used to assist in the reconstruction of apparent DW images at ultra-high b -values. Firstly, we present a novel approach to AUHB-DWR that aims to improve image quality. We formulate the reconstruction of an apparent DW image as a hidden conditional random field (HCRF) in which tissue model diffusion parameters act as hidden states in this random field. The second contribution of this paper is a new generation of fully connected conditional random fields, called the hidden stochastically fully connected conditional random fields (HSFCRF) that allows for efficient inference with significantly reduced computational complexity via stochastic clique structures. The proposed AUHB-DWR algorithms, HCRF and HSFCRF, are evaluated quantitatively in nine different patient cases using Fisher's criteria, probability of error, and coefficient of variation metrics to validate its effectiveness for the purpose of improving intensity delineation between expert identified suspected cancerous and healthy tissue within the prostate gland. The proposed methods are also examined using a prostate phantom, where the apparent ultra-high b-value DW images reconstructed using the tested AUHB-DWR methods are compared with real captured UHB-DWI. The results illustrate that the proposed AUHB-DWR methods has improved reconstruction quality and improved intensity delineation compared with existing AUHB-DWR approaches.

Multiparametric magnetic resonance imaging of the prostate: current concepts

Multiparametric MR (mpMR) imaging is rapidly evolving into the mainstay in prostate cancer (PCa) imaging. Generally, the examination consists of T2-weighted sequences, diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) evaluation, and less often proton MR spectroscopy imaging (MRSI). Those functional techniques are related to biological properties of the tumor, so that DWI correlates to cellularity and Gleason scores, DCE correlates to angiogenesis, and MRSI correlates to cell membrane turnover. The combined use of those techniques enhances the diagnostic confidence and allows for better characterization of PCa. The present article reviews and illustrates the technical aspects and clinical applications of each component of mpMR imaging, in a practical approach from the urological standpoint.

Diffusion-weighted imaging of the male pelvis

Diffusion-weighted (DW) imaging is playing an increasingly important role in disease detection, prognostication, and monitoring of treatment response. Particularly in the realm of oncology, the potential applications for DW imaging continue to expand. In this article, the authors detail the role of DW imaging for pathologic processes involving the male pelvis. The authors describe the current data, new insights, and ongoing controversies regarding DW imaging of the male pelvis with a particular emphasis on oncologic applications. The authors also discuss imaging techniques and common pitfalls for DW imaging in this anatomic region.

The Utility of Diffusion Weighted Imaging (DWI) Using Apparent Diffusion Coefficient (ADC) Values in Discriminating Between Prostate Cancer and Normal Tissue

Background

The aim of this study was to investigate the utility of diffusion weighted imaging (DWI) using Apparent Diffusion Coefficient (ADC) values in discriminating between patients with tumors and normal prostate tissue before the initial systematic core biopsy. The relationship between histological grade of prostate cancer and ADC values in the peripheral zone was also investigated.

Material/Methods

Our study included 62 patients who underwent magnetic resonance imaging (MRI) of the pelvis. The examinations were performed in T1-, T2-weighted, DWI and T1 after dynamic contrast administration sequences. In all patients there were abnormal foci within the peripheral zone determined in DWI/ADC. ADC values were compared with the Gleason score (GS) after core needle biopsy (CNB) in patients with low, medium and high stage tumors.

Results

Within the examined group of patients, ADC was statistically higher for normal tissue than for cancerous tissue (p=0.00). Mean ADC values for patients with low, intermediate and high GS were 0.85±0.03, 0.72±0.03, and 0.61±0.04, respectively.

Conclusions

DWI/ADC is useful in differentiating high-risk patients from those at low and intermediate risk, since there is a significant correlation between ADC values determined in patients included in three different groups according to their Gleason score. This information may be helpful in the assessment of prostate cancer aggressiveness.

Assessment of apparent diffusion coefficient values as predictor of aggressiveness in peripheral zone prostate cancer: comparison with Gleason score

Purpose. To determine association between apparent diffusion coefficient value on diffusion-weighted imaging and Gleason score in patients with prostate cancer. Methods. This retrospective case series was conducted at Radiology Department of Aga Khan University between June 2009 and June 2011. 28 patients with biopsy-proven prostate cancer were included who underwent ultrasound guided sextant prostate biopsy and MRI. MRI images were analyzed on diagnostic console and regions of interest were drawn. Data were entered and analyzed on SPSS 20.0. ADC values were compared with Gleason score using one-way ANOVA test. Results. In 28 patients, 168 quadrants were biopsied and 106 quadrants were positive for malignancy. 89 lesions with proven malignancy showed diffusion restriction. The mean ADC value for disease with a Gleason score of 6 was 935 mm²/s (SD = 248.4 mm²/s); Gleason score of 7 was 837 mm²/s (SD = 208.5 mm²/s); Gleason score of 8 was 614 mm²/s (SD = 108 mm²/s); and Gleason score of 9 was 571 mm²/s (SD = 82 mm²/s). Inverse relationship was observed between Gleason score and mean ADC values. Conclusion. DWI and specifically quantitative ADC values may help differentiate between low-risk (Gleason score, 6), intermediate-risk (Gleason score, 7), and high-risk (Gleason score 8 and 9) prostate cancers, indirectly determining the aggressiveness of the disease.

Monte Carlo bias field correction in endorectal diffusion imaging

Prostate cancer is one of the leading causes of cancer death in the male population. The detection of prostate cancer using imaging has been challenging until recently. Multiparametric magnetic resonance imaging (MRI) has been shown to allow accurate localization of the cancers and can help direct biopsies to cancer foci, which is required to plan the treatment. The interpretation of MRI, however, requires a high level of expertise and review of large multiparametric datasets. An endorectal receiver coil is often used to improve signal-to-noise ratio and aid in detection of smaller cancer foci. Moreover, computed high b-value diffusion-weighted imaging show improved delineation of tumors but is subject to strong bias fields near the coil. Here, a nonparametric approach to bias field correction for endorectal diffusion imaging via Monte Carlo sampling is introduced. It will be shown that the delineation between the prostate gland and the background and intensity inhomogeneity may be improved using the proposed approach. High b-value generated results also show improved visualization of tumor regions. The results suggest that Monte Carlo bias correction may have potential as a preprocessing tool for endorectal diffusion images for the prostate cancer detection and localization or segmentation.

Diffusion-weighted MRI and its role in prostate cancer

In the last 5 years, the multiparametric approach has been investigated as the method for the MRI of prostate cancer. In multiparametric MRI of the prostate, at least two functional MRI techniques, such as diffusion-weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI, are combined with conventional MRI, such as T2 -weighted imaging. DW-MRI has the ability to qualitatively and quantitatively represent the diffusion of water molecules by the apparent diffusion coefficient, which indirectly reflects tissue cellularity. DW-MRI is characterized by a short acquisition time without the administration of contrast medium. Thus, DW-MRI has the potential to become established as a noninvasive diagnostic method for tumor detection and localization, tumor aggressiveness, local staging and local recurrence after various therapies. Accordingly, radiologists should recognize the principles of DW-MRI, the methods of image acquisition and the pitfalls of image interpretation.

Diffusion-weighted MRI for detecting prostate tumour in men at increased genetic risk

BACKGROUND

Diffusion-weighted (DW)-MRI is invaluable in detecting prostate cancer. We determined its sensitivity and specificity and established interobserver agreement for detecting tumour in men with a family history of prostate cancer stratified by genetic risk.

METHODS

51 men with a family history of prostate cancer underwent T2-W + DW-endorectal MRI at 3.0 T. Presence of tumour was noted at right and left apex, mid and basal prostate sextants by 2 independent observers, 1 experienced and the other inexperienced in endorectal MRI. Sensitivity and specificity against a 10-core sampling technique (lateral and medial cores at each level considered together) in men with >2× population risk based on 71 SNP analysis versus those with lower genetic risk scores was established. Interobserver agreement was determined at a subject level.

RESULTS

Biopsies indicated cancer in 28 sextants in 13/51 men; 32 of 51 men had twice the population risk (>0.25) based on 71 SNP profiling. Sensitivity/specificity per-subject for patients was 90.0%/86.4% (high-risk) vs. 66.7%/100% (low-risk, observer 1) and 60.0%/86.3% (high-risk) vs. 33.3%/93.8% (low-risk, observer 2) with moderate overall inter-observer agreement (kappa = 0.42). Regional sensitivities/specificities for high-risk vs. low-risk for observer 1 apex 72.2%/100% [33.3%/100%], mid 100%/93.1% [100%/97.3%], base 16.7%/98.3% [0%/100%] and for observer 2 apex 36.4%/98.1% [0%/100%], mid 28.6%/96.5% [100%/100%], base 20%/100% [0%/97.3%] were poorer as they failed to detect multiple lesions.

CONCLUSION

Endorectal T2W + DW-MRI at 3.0 T yields high sensitivity and specificity for tumour detection by an experienced observer in screening men with a family history of prostate cancer and increased genetic risk.

The role of magnetic resonance imaging (MRI) in focal therapy for prostate cancer: recommendations from a consensus panel

OBJECTIVE

To establish a consensus on the utility of multiparametric magnetic resonance imaging (mpMRI) to identify patients for focal therapy.

METHODS

Urological surgeons, radiologists, and basic researchers, from Europe and North America participated in a consensus meeting about the use of mpMRI in focal therapy of prostate cancer. The consensus process was face-to-face and specific clinical issues were raised and discussed with agreement sought when possible. All participants are listed among the authors. Topics specifically did not include staging of prostate cancer, but rather identifying the optimal requirements for performing MRI, and the current status of optimally performed mpMRI to (i) determine focality of prostate cancer (e.g. localising small target lesions of ≥0.5 mL), (ii) to monitor and assess the outcome of focal ablation therapies, and (iii) to identify the diagnostic advantages of new MRI methods. In addition, the need for transperineal template saturation biopsies in selecting patients for focal therapy was discussed, if a high quality mpMRI is available. In other words, can mpMRI replace the role of transperineal saturation biopsies in patient selection for focal therapy?

RESULTS

Consensus was reached on most key aspects of the meeting; however, on definition of the optimal requirements for mpMRI, there was one dissenting voice. mpMRI is the optimum approach to achieve the objectives needed for focal therapy, if made on a high quality machine (3T with/without endorectal coil or 1.5T with endorectal coil) and judged by an experienced radiologist. Structured and standardised reporting of prostate MRI is paramount. State of the art mpMRI is capable of localising small tumours for focal therapy. State of the art mpMRI is the technique of choice for follow-up of focal ablation.

CONCLUSIONS

The present evidence for MRI in focal therapy is limited. mpMRI is not accurate enough to consistently grade tumour aggressiveness. Template-guided saturation biopsies are no longer necessary when a high quality state of the art mpMRI is available; however, suspicious lesions should always be confirmed by (targeted) biopsy.

Prognostic value of preoperative multiparametric magnetic resonance imaging (MRI) for predicting biochemical recurrence after radical prostatectomy

OBJECTIVE

To evaluate the suitability of preoperative multiparametric magnetic resonance imaging (MRI) positivity as a predictor of biochemical recurrence after radical prostatectomy (RP).

PATIENTS AND METHODS

We reviewed the clinical records of patients who underwent either standard RP or laparoscopic RP between January 2005 and December 2009 at our institution. Patients who received radiotherapy or androgen deprivation therapy before surgery were excluded. A total of 314 patients met the study inclusion criteria. Cox proportional hazard regression models were used for analyses. In accordance with the criteria in the established guidelines, a radiologist scored the probability of the presence of prostate cancer using a five-point scale of diagnostic confidence level. The highest confidence level of any pulse sequence was considered as the evaluation result.

RESULTS

MRI positivity was significantly associated with a high clinical stage (cT ≥ 2; P = 0.039), a high positive biopsy core rate (≥0.2; P < 0.001), a high biopsy Gleason score ([GS] ≥8; P < 0.001) and a high pathological GS (≥8; P = 0.005). Univariate analysis and multivariate analysis showed that MRI positivity was a prognostic indicator in the analysis that included only preoperative variables and also in the analysis including preoperative and pathological variables.

CONCLUSION

Multiparametric MRI positivity can independently predict biochemical recurrence after RP.

Usefulness of diffusion-weighted magnetic resonance imaging in the diagnosis of prostate cancer

RATIONALE AND OBJECTIVES

The aim of this study was to evaluate the diagnostic accuracy of diffusion-weighted magnetic resonance imaging (DWI) in prostate cancer.

MATERIALS AND METHODS

The MEDLINE, Embase, CANCERLIT, and Cochrane Library databases were searched for studies published from January 2001 to August 2011 evaluating the diagnostic performance of DWI in detecting prostate carcinoma. Sensitivities and specificities were determined across studies, and summary receiver-operating characteristic curves were constructed using hierarchical regression models.

RESULTS

Sixteen studies (18 subsets) with a total of 852 patients were included. Six studies (seven subsets) examining men with pathologically confirmed prostate cancer (260 patients) had pooled sensitivity and specificity of 0.88 (95% confidence interval [CI], 0.76-0.95) and 0.84 (95% CI, 0.76-0.90), respectively. Compared to patients at high risk for clinically relevant cancer, sensitivity was higher in low-risk patients (0.94 [95% CI, 0.89-0.97] vs 0.62 [95% CI, 0.54-0.70], P < .05), but specificity was lower (0.86 [95% CI, 0.72-0.94] vs 0.89 [95% CI, 0.83-0.93], P < .05). Ten studies (11 subsets) examining patients with suspected prostate cancer (592 patients) had pooled sensitivity and specificity of 0.76 (95% CI, 0.68-0.84) and 0.86 (95% CI, 0.79-0.91). Sensitivity was lower in high-risk patients (0.74 [95% CI, 0.57-0.87] vs 0.78 [95% CI, 0.70-0.84], P > .05), but specificity was higher (0.92 [95% CI, 0.89-0.94] vs 0.78 [95% CI, 0.70-0.84], P < .05).

CONCLUSIONS

A limited number of small studies suggest that DWI could be a rule-in test for high-risk patients. Further prospective studies including larger populations are necessary to confirm the actual value of DWI in this field.

Defining prostate cancer risk before prostate biopsy

Prostate cancer is the most commonly diagnosed cancer in men. At present, patients are selected for prostate biopsy on the basis of age, serum prostate specific antigen (PSA), and prostatic digital rectal examination (DRE) findings. However, due to limitations in the use of PSA and DRE, many patients undergo unnecessary prostate biopsy. A further problem arises as many patients are diagnosed and treated for indolent disease. This review of the literature highlights the strengths and weaknesses of existing methods of prebiopsy risk stratification and evaluates promising serum, urine, and radiologic prostate cancer biomarkers, which may improve risk stratification for prostate biopsy in the future.

Washout gradient in dynamic contrast-enhanced MRI is associated with tumor aggressiveness of prostate cancer

PURPOSE

To investigate the associations between dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) parameters and the Gleason score (GS) for prostate cancer (PCA) with localization information provided by concurrent apparent diffusion coefficient (ADC) maps.

MATERIALS AND METHODS

Forty-three male patients received MR scans, including diffusion tensor imaging (DTI) and DCE MRI, on a 1.5 T MR system. All patients were confirmed to have PCA in the following biopsy within 2 weeks. ADC maps calculated from DTI were used to colocalize cancerous and noncancerous regions on DCE MRI for perfusion analysis retrospectively. Semiquantitative parameters (peak enhancement, initial gradient, and washout gradient [WG] and quantitative parameters [K(trans) , ν(e) , and k(ep) ]) were calculated and correlated with the GS. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of the perfusion parameters in assessing the aggressiveness of PCA.

RESULTS

A total of 41 PCA nodules were included in the analysis. Among all quantitative and semiquantitative parameters, only WG showed significant correlation with GS (r = -0.75, P < 0.0001). By defining tumor aggressiveness as a GS >6, WG demonstrated a good diagnostic performance, with the area under the ROC curve being 0.88. Under a cutoff point of WG = 0.125 min(-1) , the sensitivity and specificity were 0.87 and 0.78, respectively.

CONCLUSION

WG shows a significant association with GS and good diagnostic performance in assessing tumor aggressiveness. Therefore, WG is a potential marker of GS.

Diffusion-weighted MRI for locally recurrent prostate cancer after external beam radiotherapy

OBJECTIVE

The objectives of our study were to establish the apparent diffusion coefficients (ADCs) of tumor and nontumor irradiated tissues in patients with suspected postradiation recurrence of prostate cancer and to determine the sensitivity and specificity of a combination of T2-weighted and diffusion-weighted imaging (DWI) for detecting local recurrence.

MATERIALS AND METHODS

Twenty-four patients with rising prostate-specific antigen levels after having completed radiation therapy 30-130 months earlier (median, 62 months) underwent endorectal T2-weighted imaging and DWI (b = 0, 100, 300, 500, and 800 s/mm(2)) followed by transrectal ultrasound (TRUS)-guided biopsy. Images were scored prospectively as positive for tumor if a region of low signal intensity on T2-weighted imaging within the prostate corresponded with a focally restricted area on the ADC map. A region of interest (ROI) was drawn around the suspicious lesion on a single slice of the ADC map and a corresponding ROI was drawn around presumed nontumor irradiated peripheral zone and central gland tissues on the opposite side of the prostate. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were determined against TRUS-guided biopsy reference standard (octant, n = 17; sextant, n = 5; two samples, n = 1; 12 samples, n = 1).

RESULTS

Sixteen of 24 patients (66.7%) had positive histology findings. The median tumor ROI area was 0.37 cm(2) (quartiles, 0.30 and 0.82 cm(2)). The sensitivity, specificity, PPV, and NPV for detecting tumor were 93.8%, 75%, 88.2%, and 85.7%, respectively. A cutoff ADC of 1216 × 10(-6) mm(2)/s could predict tumor with 100% sensitivity and 96% specificity (area under the receiver operating characteristic curve = 0.992).

CONCLUSION

An ADC derived from DWI is a useful adjunct to T2-weighted MRI for detecting local tumor recurrence larger than 0.4 cm(2) within the prostate.

Detectability of low and intermediate or high risk prostate cancer with combined T2-weighted and diffusion-weighted MRI

OBJECTIVES

To evaluate the incremental value of diffusion-weighted imaging (DWI) in combination with T2-weighted imaging to detect low (Gleason score, ≤ 6) and intermediate or high risk (Gleason score, ≥ 7) prostate cancer.

METHODS

Fifty-one patients who underwent MRI before prostatectomy were evaluated. Two readers independently scored the probability of tumour in eight regions of prostate on T2-weighted images (T2WI) and T2WI combined with apparent diffusion coefficient (ADC) maps. Data were divided into two groups--low risk and intermediate or high risk prostate cancer--and correlated with histopathological results. Diagnostic performance parameters, areas under the receiver-operating characteristic curve (AUCs) and interreader agreement were calculated.

RESULTS

For both readers, AUCs of combined T2WI and ADC maps were greater than those of T2WI in intermediate or high risk (reader 1, 0.887 vs. 0.859; reader 2, 0.732 vs 0.662, P < 0.05) prostate cancers, but not in low risk (reader 1, 0.719 vs 0.725; reader 2, 0.685 vs. 0.680, P > 0.05) prostate cancers. Weighted κ value of combined T2WI and ADC maps was 0.689.

CONCLUSIONS

The addition of DWI to T2-weighted imaging improves the accuracy of detecting intermediate or high risk prostate cancers, but not for low risk prostate cancer detection.

KEY POINTS

• Gleason scores influence diagnostic performance of MRI for prostate cancer detection. • Addition of DWI does not improve low risk prostate cancer detection. • Combined T2WI and DWI may help select intermediate or high risk patients.

Reducing the influence of b-value selection on diffusion-weighted imaging of the prostate: evaluation of a revised monoexponential model within a clinical setting

PURPOSE

To compare the accuracy of standard and revised monoexponential models of diffusion-weighted magnetic resonance imaging (DW-MRI) data for differentiating malignant from benign prostate tissue, using surgical pathology as the reference standard.

MATERIALS AND METHODS

The Institutional Review Board waived informed consent for this Health Insurance Portability and Accountability Act (HIPAA)-compliant, retrospective study of 46 patients (median age = 61 years; range: 42-85 years) who underwent DW-MRI between May and December 2008 before radical prostatectomy for biopsy-proven prostate cancer, had no prior treatment, and had whole-mount step-section pathology maps available showing at least one peripheral zone (PZ) lesion >0.1 cm(3) . DW-MRI data were obtained for b-values of 0, 400, and 700 s/mm(2) . Apparent diffusion coefficients (ADCs) were estimated from PZ regions of interest (ROIs) on b = 0, 700 and b = 0, 400 s/mm(2) images, using a standard monoexponential model. The true diffusion coefficient (D) and perfusion fraction (f) were measured using a revised monoexponential model incorporating all three b-values. Areas under receiver operating characteristic curves (AUCs) were calculated to assess the accuracy of individual parameters and a logistic regression model combining D and f (D+f) in distinguishing malignant ROIs; P < 0.05 denoted significance.

RESULTS

ADC(400) (AUC = 0.81, P < 0.0001), ADC(700) (AUC = 0.79, P < 0.0001), D (AUC = 0.71, P = 0.0001) and D + f distinguished malignant from benign ROIs (AUC = 0.82, P < 0.0001), but f did not (AUC = 0.56, P = 0.28); D + f was significantly more accurate than D (P = 0.016) but not more accurate than ADC(400) (P = 0.26) or ADC(700) (P = 0.12).

CONCLUSION

The true diffusion coefficient provides an additional DW-MRI parameter for distinguishing prostate cancer that is less influenced than the ADC by b-value selection.

Principles and applications of diffusion-weighted imaging in cancer detection, staging, and treatment follow-up

Diffusion-weighted imaging relies on the detection of the random microscopic motion of free water molecules known as Brownian movement. With the development of new magnetic resonance (MR) imaging technologies and stronger diffusion gradients, recent applications of diffusion-weighted imaging in whole-body imaging have attracted considerable attention, especially in the field of oncology. Diffusion-weighted imaging is being established as a pivotal aspect of MR imaging in the evaluation of specific organs, including the breast, liver, kidney, and those in the pelvis. When used in conjunction with apparent diffusion coefficient mapping, diffusion-weighted imaging provides information about the functional environment of water in tissues, thereby augmenting the morphologic information provided by conventional MR imaging. Detected changes include shifts of water from extracellular to intracellular spaces, restriction of cellular membrane permeability, increased cellular density, and disruption of cellular membrane depolarization. These findings are commonly associated with malignancies; therefore, diffusion-weighted imaging has many applications in oncologic imaging and can aid in tumor detection and characterization and in the prediction and assessment of response to therapy.

A fully automatic method to register the prostate gland on T2-weighted and EPI-DWI images

Prostate adenocarcinoma (PCa) is the most frequent noncutaneous cancer among men in developed countries. Magnetic Resonance (MR) has been used to detect PCa and several clinical trials report on the accuracy of the test. Multiparametric MR imaging (mpMRI) is defined as the integration of information from different morphological and functional datasets. mpMRI could be used to increase the performances of prostate MR, therefore allowing a more accurate assessment of the tumor gland extent, while reducing reporting time and interobserver variability. The first step to perform such a multiparametric analysis is to correct for voluntary and involuntary movements during the acquisitions, as well as for image distortion in the Diffusion Weighted (DWI) images. The aim of this work is to present a fully automatic registration algorithm between T2w and DWI images, able to realign the images and to correct the distortions in the DWI. Results showed a good overlap after registration and a strong decrease of mean surface distance in both the central gland and peripheral zone. These promising results suggest that the algorithm could be integrated in a CAD system which will combine the pharmacokinetic parameters derived from DCE-MRI, T2w MRI and DWI MR to generate one comprehensive value assessing the risk of malignancy. However to perform such a multiparametric analysis, it is necessary to correct for voluntary and involuntary (breathing, heart beating) movements during the DCE-MRI acquisition, and to realign also the DCE-MRI sequence to the T2w sequence.

Correlation of Gleason scores with diffusion-weighted imaging findings of prostate cancer

The purpose of our study was to compare the apparent diffusion coefficient (ADC) derived from diffusion-weighted imaging (DWI) of prostate cancer (PCa) patients with three classes of pathological Gleason scores (GS). Patients whose GS met these criteria (GS 3 + 3, GS 3 + 4, and GS 4 + 3) were included in this study. The DWI was performed using b values of 0, 50, and 400 s/mm² in 44 patients using an endorectal coil on a 1.5T MRI scanner. The apparent diffusion coefficient (ADC) values were calculated from the DWI data of patients with three different Gleason scores. In patients with a high-grade Gleason score (4 + 3), the ADC values were lower in the peripheral gland tissue, pathologically determined as tumor compared to low grade (3 + 3 and 3 + 4). The mean and standard deviation of the ADC values for patients with GS 3 + 3, GS 3 + 4, and GS 4 + 3 were 1.135 ± 0.119, 0.976 ± 0.103 and 0.831 ± 0.087 mm²/sec. The ADC values were statistically significant (P < 0.05) between the three different scores with a trend of decreasing ADC values with increasing Gleason scores by one-way ANOVA method. This study shows that the DWI-derived ADC values may help differentiate aggressive from low-grade PCa.