Apparent diffusion coefficient value and ratio as noninvasive potential biomarkers to predict prostate cancer grading: comparison with prostate biopsy and radical prostatectomy specimen

Role of MRI in the Risk Assessment of Primary Prostate Cancer

A successful paradigm shift toward personalized management strategies for patients with prostate cancer (PCa) is heavily dependent on the availability of noninvasive diagnostic tools capable of accurately establishing the true extent of disease at the time of diagnosis and estimating the risk of subsequent disease progression and related mortality. Although there is still considerable scope for improvement in its diagnostic, predictive, and prognostic capabilities, multiparametric prostate magnetic resonance imaging (MRI) is currently regarded as the imaging modality of choice for local staging of PCa. A negative MRI, that is, the absence of any MRI-visible intraprostatic lesion, has a high negative predictive value for the presence of clinically significant PCa and can substantiate the consideration of active surveillance as a preferred initial management approach. MRI-derived quantitative and semi-quantitative parameters can be utilized to noninvasively characterize MRI-visible prostate lesions and identify those patients who are most likely to benefit from radical treatment, and differentiate them from patients with benign or indolent prostate pathology that may also be visible on MRI. This literature review summarizes current strategies how MRI can be used to determine a tailored management strategy for an individual patient.

Quantified analysis of histological components and architectural patterns of gleason grades in apparent diffusion coefficient restricted areas upon diffusion weighted MRI for peripheral or transition zone cancer locations

PURPOSE

To quantify and compare the histological components and architectural patterns of Gleason grades in cancerous areas with restriction on apparent diffusion coefficient (ADC) maps.

MATERIALS AND METHODS

Twelve consecutive cases with 14 separate ADC restriction areas, positive for cancer in the peripheral zone (PZ) and transition zone (TZ) were included. All had 3 Tesla MRI and radical prostatectomy. Ten regions of interest (ROIs) within and outside the 14 ADC restriction areas positive for cancer were selected. For each ROI, we performed quantitative analysis of (a) prostate benign and malignant histological component surface ratios, including stroma, glands, epithelium, lumen, cellular nuclei; (b) percent of Gleason grades and measures of ADC values. Means of histological components according to ADC restriction for cancerous area were compared with analyses of variance with repeated measures.

RESULTS

Independent predictors of the probability of cancer were median epithelium/ROI ratio (P = 0.001) and nuclei/ROI ratio (P = 0.03). Independent predictors of the probability of ADC restriction were malignant glands/ROI and luminal space/ROI (P < 0.0001). Effect of malignant glands/ROI area was different according to the localization of the ROI (P = 0.03). We observed an overall difference between the means for all of the histological components for the comparison of true positive and false negative (P < 0.0001), except for the percent of Gleason grade 4 (P = 0.18). In TZ cancers, a predominant grade 3 pattern was associated with low ADC values. In PZ cancers, a predominant grade 4 pattern was associated with low ADC values.

CONCLUSION

Determinants of low ADC were high ratio of malignant glands/ROI area which may be seen in Gleason grades 3 or 4 cancers.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1786-1796.

Incremental value of high b value diffusion-weighted magnetic resonance imaging at 3-T for prediction of extracapsular extension in patients with prostate cancer: preliminary experience

PURPOSE

To investigate whether high b value diffusion-weighted imaging (DWI) contributes to the improvement of diagnostic ability of extracapsular extension (ECE) in prostate cancer (PC).

MATERIALS AND METHODS

Forty-three patients with PC underwent multiparametric MRI including DWI (b values: 0, 2000 s/mm²) at 3-T. Two radiologists assessed the presence of ECE and the diagnostic certainty degree using conventional diagnostic method by consensus. Tumor apparent diffusion coefficient (ADC, ×10^-3 mm²/s) was also measured. Independent predictors of ECE were identified among PSA, tumor ADC, Gleason score, and conventional MRI. ECE in patients with low diagnostic certainty by conventional MRI was further reevaluated using ADC cutoff value, and the results were combined with those of patients with high diagnostic certainty by conventional MRI (MRI + ADC method).

RESULTS

Tumor ADC was an independent predictor of ECE, and the ADC cutoff value was 0.72. The sensitivity, specificity, and accuracy of conventional MRI and MRI + ADC method in the diagnosis of ECE were 44, 92, and 72%, and 78, 96, and 88%, respectively. Among MRI findings leading to the judgement of low diagnostic certainty, broad tumor contact was most common (72% of the patients).

CONCLUSIONS

The addition of ADC obtained with high b value DWI at 3-T to conventional MRI improved the diagnostic ability of ECE.

A model describing diffusion in prostate cancer

PURPOSE

Quantitative diffusion MRI has frequently been studied as a means of grading prostate cancer. Interpretation of results is complicated by the nature of prostate tissue, which consists of four distinct compartments: vascular, ductal lumen, epithelium, and stroma. Current diffusion measurements are an ill-defined weighted average of these compartments. In this study, prostate diffusion is analyzed in terms of a model that takes explicit account of tissue compartmentalization, exchange effects, and the non-Gaussian behavior of tissue diffusion.

METHOD

The model assumes that exchange between the cellular (ie, stromal plus epithelial) and the vascular and ductal compartments is slow. Ductal and cellular diffusion characteristics are estimated by Monte Carlo simulation and a two-compartment exchange model, respectively. Vascular pseudodiffusion is represented by an additional signal at b = 0. Most model parameters are obtained either from published data or by comparing model predictions with the published results from 41 studies. Model prediction error is estimated using 10-fold cross-validation.

RESULTS

Agreement between model predictions and published results is good. The model satisfactorily explains the variability of ADC estimates found in the literature.

CONCLUSION

A reliable model that predicts the diffusion behavior of benign and cancerous prostate tissue of different Gleason scores has been developed. Magn Reson Med 78:316-326, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Diffusion-weighted MRI for early detection and characterization of prostate cancer in the transgenic adenocarcinoma of the mouse prostate model

PURPOSE

To improve early diagnosis of prostate cancer to aid clinical decision-making. Diffusion-weighted magnetic resonance imaging (DW-MRI) is sensitive to water diffusion throughout tissues, which correlates with Gleason score, a histological measure of prostate cancer aggressiveness. In this study the ability of DW-MRI to detect prostate cancer onset and development was evaluated in transgenic adenocarcinoma of the mouse prostate (TRAMP) mice.

MATERIALS AND METHODS

T2 -weighted and DW-MRI were acquired using a 7T MR scanner, 200 mm bore diameter; 10 TRAMP and 6 C57BL/6 control mice were scanned every 4 weeks from 8 weeks of age until sacrifice at 28-30 weeks. After sacrifice, the genitourinary tract was excised and sectioned for histological analysis. Histology slides registered with DW-MR images allowed for validation of DW-MR images and the apparent diffusion coefficient (ADC) as tools for cancer detection and disease stratification. An automated early assessment tool based on ADC threshold values was developed to aid cancer detection and progression monitoring.

RESULTS

The ADC differentiated between control prostate ((1.86 ± 0.20) × 10(-3) mm(2) /s) and normal TRAMP prostate ((1.38 ± 0.10) × 10(-3) mm(2) /s) (P = 0.0001), between TRAMP prostate and well-differentiated cancer ((0.93 ± 0.18) × 10(-3) mm(2) /s) (P = 0.0006), and between well-differentiated cancer and poorly differentiated cancer ((0.63 ± 0.06) × 10(-3) mm(2) /s) (P = 0.02).

CONCLUSION

DW-MRI is a tool for early detection of cancer, and discrimination between cancer stages in the TRAMP model. The incorporation of DW-MRI-based prostate cancer stratification and monitoring could increase the accuracy of preclinical trials using TRAMP mice.

Prostate cancer risk stratification with magnetic resonance imaging

In recent years, multiparametric magnetic resonance imaging (mpMRI) has shown promise for prostate cancer (PCa) risk stratification. mpMRI, often followed by targeted biopsy, can be used to confirm low-grade disease before enrollment in active surveillance. In patients with intermediate or high-risk PCa, mpMRI can be used to inform surgical management. mpMRI has sensitivity of 44% to 87% for detection of clinically significant PCa and negative predictive value of 63% to 98% for exclusion of significant disease. In addition to tumor identification, mpMRI has also been shown to contribute significant incremental value to currently used clinical nomograms for predicting extraprostatic extension. In combination with conventional clinical criteria, accuracy of mpMRI for prediction of extraprostatic extension ranges from 92% to 94%, significantly higher than that achieved with clinical criteria alone. Supplemental sequences, such as diffusion-weighted imaging and dynamic contrast-enhanced imaging, allow quantitative evaluation of cancer-suspicious regions. Apparent diffusion coefficient appears to be an independent predictor of PCa aggressiveness. Addition of apparent diffusion coefficient to Epstein criteria may improve sensitivity for detection of significant PCa by as much as 16%. Limitations of mpMRI include variability in reporting, underestimation of PCa volume and failure to detect clinically significant disease in a small but significant number of cases.

Multiparametric MRI and targeted prostate biopsy: Improvements in cancer detection, localization, and risk assessment

Introduction

Multiparametric-MRI (mp-MRI) is an evolving noninvasive imaging modality that increases the accurate localization of prostate cancer at the time of MRI targeted biopsy, thereby enhancing clinical risk assessment, and improving the ability to appropriately counsel patients regarding therapy.

Material and methods

We used MEDLINE/PubMed to conduct a comprehensive search of the English medical literature. Articles were reviewed, data was extracted, analyzed, and summarized. In this review, we discuss the mp-MRI prostate exam, its role in targeted prostate biopsy, along with clinical applications and outcomes of MRI targeted biopsies.

Results

Mp-MRI, consisting of T2-weighted imaging, diffusion-weighted imaging, dynamic contrast-enhanced imaging, and possibly MR spectroscopy, has demonstrated improved specificity in prostate cancer detection as compared to conventional T2-weighted images alone. An MRI suspicion score has been developed and is depicted using an institutional Likert or, more recently, a standardized reporting scale (PI-RADS). Techniques of MRI-targeted biopsy include in-gantry MRI guided biopsy, TRUS-guided visual estimation biopsy, and software co-registered MRI-US guided biopsy (MRI-US fusion). Among men with no previous biopsy, MRI-US fusion biopsy demonstrates up to a 20% increase in detection of clinically significant cancers compared to systematic biopsy while avoiding a significant portion of low risk disease. These data suggest a potential role in reducing over-detection and, ultimately, over-treatment. Among men with previous negative biopsy, 72–87% of cancers detected by MRI targeted biopsy are clinically significant. Among men with known low risk cancer, repeat biopsy by MR-targeting improves risk stratification in selecting men appropriate for active surveillance secondarily reducing the need for repetitive biopsy during surveillance.

Conclusions

Use of mp-MRI for targeting prostate biopsies has the potential to reduce the sampling error associated with conventional biopsy by providing better disease localization and sampling. MRI-ultrasound fusion-targeted prostate biopsy may improve the identification of clinically significant prostate cancer while limiting detection of indolent disease, ultimately facilitating more accurate risk stratification. Literature supports the clinical applications of MRI-targeted biopsy in men who have never been biopsied before, those with a prior negative biopsy, and those with low risk disease considering active surveillance.

Combined Biparametric Prostate Magnetic Resonance Imaging and Prostate-specific Antigen in the Detection of Prostate Cancer: A Validation Study in a Biopsy-naive Patient Population

OBJECTIVE

To validate the use of biparametric (T2- and diffusion-weighted) magnetic resonance imaging (B-MRI) and prostate-specific antigen (PSA) or PSA density (PSAD) in a biopsy-naive cohort at risk for prostate cancer (PCa).

METHODS

All patients (n = 59) underwent PSA screening and digital rectal exam prior to a B-MRI followed by MRI or transrectal ultrasound fusion-guided targeted biopsy. Previously reported composite formulas incorporating screen positive lesions (SPL) on B-MRI and PSA or PSAD were developed to maximize PCa detection. For PSA, a patient was considered screen positive if PSA level + 6 × (the number of SPL) >14. For PSAD, screening was positive if PSAD × 14 + (the number of SPL) >4.25. These schemes were employed in this new test set to validate the initial formulas. Performance assessment of these formulas was determined for all cancer detection and for tumors with Gleason ≥3 + 4.

RESULTS

Screen positive lesions on B-MRI had the highest sensitivity (95.5%) and negative predictive value of 71.4% compared with PSA and PSAD. B-MRI significantly improved sensitivity (43.2-72.7%, P = .0002) when combined with PSAD. The negative predictive value of PSA increased with B-MRI, achieving 91.7% for B-MRI and PSA for Gleason ≥3 + 4. Overall accuracies of the composite equations were 81.4% (B-MRI and PSA) and 78.0% (B-MRI and PSAD).

CONCLUSION

Validation with a biopsy-naive cohort demonstrates the parameter SPL performed better than PSA or PSAD alone in accurately detecting PCa. The combined use of B-MRI, PSA, and PSAD resulted in improved accuracy for detecting clinically significant PCa.

Does normalisation improve the diagnostic performance of apparent diffusion coefficient values for prostate cancer assessment? A blinded independent-observer evaluation

AIM

To evaluate the performance of normalised apparent diffusion coefficient (ADC) values for prostate cancer assessment when performed by independent observers blinded to histopathology findings.

MATERIALS AND METHODS

Fifty-eight patients undergoing 3 T phased-array coil magnetic resonance imaging (MRI) including diffusion-weighted imaging (DWI; maximal b-value 1000 s/mm(2)) before prostatectomy were included. Two radiologists independently evaluated the images, unaware of the histopathology findings. Regions of interest (ROIs) were drawn within areas showing visually low ADC within the peripheral zone (PZ) and transition zone (TZ) bilaterally. ROIs were also placed within regions in both lobes not suspicious for tumour, allowing computation of normalised ADC (nADC) ratios between suspicious and non-suspicious regions. The diagnostic performance of ADC and nADC were compared.

RESULTS

For PZ tumour detection, ADC achieved significantly higher area under the receiver operating characteristic curve (AUC; p=0.026) and specificity (p=0.021) than nADC for reader 1, and significantly higher AUC (p=0.025) than nADC for reader 2. For TZ tumour detection, nADC achieved significantly higher specificity (p=0.003) and accuracy (p=0.004) than ADC for reader 2. For PZ Gleason score >3+3 tumour detection, ADC achieved significantly higher AUC (p=0.003) and specificity (p=0.005) than nADC for reader 1, and significantly higher AUC (p=0.023) than nADC for reader 2. For TZ Gleason score >3+3 tumour detection, ADC achieved significantly higher specificity (p=0.019) than nADC for reader 1.

CONCLUSION

In contrast to prior studies performing unblinded evaluations, ADC was observed to outperform nADC overall for two independent observers blinded to the histopathology findings. Therefore, although strategies to improve the utility of ADC measurements in prostate cancer assessment merit continued investigation, caution is warranted when applying normalisation to improve diagnostic performance in clinical practice.