The role of MRI in prostate cancer active surveillance

The role of magnetic resonance imaging in active surveillance of prostate cancer

Active surveillance (AS) is an important strategy to avoid overtreatment of prostate cancer (PCa) and has become the standard of care for low-risk patients. The role of magnetic resonance imaging (MRI) in AS has expanded due to its ability to risk stratify patients with suspected or known PCa, and MRI has become an integral part of the AS protocols at various institutions. A negative pre-biopsy MRI result is associated with a very high negative predictive value for a Gleason score ≥ 3+4. A positive MRI result in men who are otherwise eligible for AS has been shown to be associated with the presence of high-grade PCa and therefore with ineligibility. In addition, MRI can be used to guide and determine the timing of per-protocol biopsy during AS. However, there are several MRI-related issues that remain unresolved, including the lack of a consensus and guidelines; concerns about gadolinium deposition in various tissues; and increased demand for higher efficiency and productivity. Similarly, the need for the combined use of targeted and systematic sampling is still a matter of debate when lesions are visible on MRI. Here, we review the current AS guidelines, as well as the accepted roles of MRI in patient selection and monitoring, the potential uses of MRI that are still in question, and the limitations of the method.

Does a screening digital rectal exam provide actionable clinical utility in patients with an elevated PSA and positive MRI?

Objective

To define the value of a digital rectal exam (DRE) in the prostate‐magnetic resonance imaging (MRI) era. Prostate MRI is increasingly used in men with elevated prostate‐specific antigen (PSA) prior to biopsy.

Methods

A retrospective study was performed in men with elevated PSA undergoing MRI followed by MRI fusion with systematic biopsy and men with elevated PSA/active surveillance with negative MRI followed by biopsy. Baseline clinicopathologic characteristics and DRE findings were collected. We examined performance of a positive DRE on sensitivity and specificity of diagnosing clinically significant prostate cancer (CSPC).

Results

A total of 339 patients had elevated PSA and positive MRI followed by MRI fusion guided with systematic biopsy. Pre‐biopsy DRE was documented in 286/339 patients, who were included in further analysis. About 81.6% positive, 78.7% questionable, and 55.8% negative DRE patients had CSPC. Positive DRE had 21.8% sensitivity and 91.3% specificity for CSPC. Positive or questionable DRE had 42.1% sensitivity and 81.5% specificity. Among 148 men with non‐CSPC (GG1)‐targeted biopsy, 28 had systematic biopsy with CSPC. About 5/28 had positive DRE and 8/28 had positive or questionable DRE. Twenty‐seven patients were included who had elevated PSA/on active surveillance with negative MRI and biopsy done within 2 years. About 77.8% had negative, 7.4% had questionable, and 14.8% men had positive DRE. About 7.4% had CSPC and all had a negative DRE.

Conclusions

Our study provides limited evidence for the value of a DRE. However, it does show occasional benefit in detecting GG2 or higher disease and given the lack of cost and side effects, should still be considered.

Prevalence of prostate cancer in PI-RADS version 2.1 T2-weighted transition zone 'nodule in nodule' and 'homogeneous mildly hypointense area between nodules' criteria: MRI-radical prostatectomy histopathological evaluation

OBJECTIVES

To evaluate the prevalence of prostate cancer (PCa) of two PI-RADS version (v) 2.1 transition zone (TZ) features (PI-RADS 1 ['nodule in nodule'] and 2 ['homogeneous mildly hypointense area between nodules']).

METHODS

With an institutional review board approval, from a 5-year cohort between 2012 and 2017, we retrospectively identified 53 consecutive men with radical prostatectomy (RP) confirmed TZ tumors and MRI. Three blinded radiologists (R1/2/3) independently evaluated T2-weighted and diffusion-weighted imaging (DWI) using PI-RADS v2.1 for the presence of (1) 'nodule in nodule' (recording 'cystic change', inner nodule encapsulation, size, and DWI score) and (2) 'homogeneous mildly hypointense area between nodules' (also recording size and DWI score). MRI-RP maps established ground truth. Primary tumor was evaluated assessing PI-RADS v2.1 category, size, and presence of imaging variants.

RESULTS

R1/2/3 identified 26/18/22 'nodule in nodule' respectively with 7.7% (2/26; 95% confidence interval [95% CI]: 0.1-17.9%), 5.6% (1/18; 95% CI: 0.01-16.1%), and 4.5% (1/22; 95% CI: 0.01-13.3%) PCa (both Gleason score 3 + 4 = 7). Agreement was fair-to-substantial, kappa = 0.222-0.696. 'Cystic change', inner nodule absent/incomplete encapsulation and DWI score ≥ 4 for R1/R2/R2 were present in 80.8% (21/26), 46.2% (12/26), 7.7% (2/26); 94.4% (17/18), 33.3% (6/18), 5.6% (1/18); and 59.1% (13/22), 63.6% (14/22), 9.1% (2/22). Both PCa had inner nodule absent/incomplete encapsulation and DWI score ≥ 4. No other TZ tumors demonstrated 'nodule in nodule', nodule 'cystic change', or 'homogeneous mildly hypointense area between nodules'. R1/2/3 identified 5/6/13 'homogeneous mildly hypointense area between nodules' with zero PCa for any reader (upper bound 95% CI: 24.7-52.2%). Interobserver agreement was fair-to-substantial, kappa = 0.104-0.779.

CONCLUSION

The proportion of cancers in PI-RADS v2.1 'nodule in nodule' was low (~5-8%) with zero cancers detected in 'homogeneous mildly hypointense area between nodules'. When 'nodule in nodule' inner nodule shows absent or incomplete encapsulation with marked restricted diffusion, PCa may be considered; however, this warrants further studies.

KEY POINTS

• The prevalence of clinically significant prostate cancers in PI-RADS v2.1 'nodule in nodule' was low (5-8%, 95% CI: 0.1-17.9%). • Clinically significant prostate cancer was only detected in the 'nodule in nodule' variant when the inner nodule showed absent or incomplete encapsulation ('atypical nodule') with marked restricted diffusion. • 'Homogeneous mildly hypointense area between nodules' is likely benign with no cancers identified in the current study, however, with a wide 95% CI due to low prevalence.

Genomic Analysis of Localized High-Risk Prostate Cancer Circulating Tumor Cells at the Single-Cell Level

Accurate risk classification of men with localized high-risk prostate cancer directly affects treatment management decisions and patient outcomes. A wide range of risk assessments and classifications are available. However, each one has significant limitations to distinguish between indolent and aggressive prostate cancers. Circulating tumor cells (CTCs) may provide an alternate additional source, beyond tissue biopsies, to enable individual patient-specific clinical assessment, simply because CTCs can reveal both tumor-derived and germline-specific genetic information more precisely than that gained from a single diagnostic biopsy. In this study, we combined a filtration-based CTC isolation technology with prostate cancer CTC immunophenotyping to identify prostate cancer CTCs. Next, we performed 3-D telomere profiling prior to laser microdissection and single-cell whole-exome sequencing (WES) of 21 CTCs and 4 lymphocytes derived from 10 localized high-risk prostate cancer patient samples. Localized high-risk prostate cancer patient CTCs present a high number of telomere signals with lower signal intensities (short telomeres). To capture the genetic diversity/heterogeneity of high-risk prostate cancer CTCs, we carried out whole-exome sequencing. We identified 202,241 single nucleotide variants (SNVs) and 137,407 insertion-deletions (indels), where less than 10% of these genetic variations were within coding regions. The genetic variation (SNVs + indels) and copy number alteration (CNAs) profiles were highly heterogeneous and intra-patient CTC variation was observed. The pathway enrichment analysis showed the presence of genetic variation in nine telomere maintenance pathways (patients 3, 5, 6, and 7), including an important gene for telomere maintenance called telomeric repeat-binding factor 2 (TRF2). Using the PharmGKB database, we identified nine genetic variations associated with response to docetaxel. A total of 48 SNVs can affect drug response for 24 known cancer drugs. Gene Set Enrichment Analysis (GSEA) (patients 1, 3, 6, and 8) identified the presence of CNAs in 11 different pathways, including the DNA damage repair (DDR) pathway. In conclusion, single-cell approaches (WES and 3-D telomere profiling) showed to be useful in unmasking CTC heterogeneity. DDR pathway mutations have been well-established as a target pathway for cancer therapy. However, the frequent CNA amplifications found in localized high-risk patients may play critical roles in the therapeutic resistance in prostate cancer.

Proteomic Tissue-Based Classifier for Early Prediction of Prostate Cancer Progression

Although ~40% of screen-detected prostate cancers (PCa) are indolent, advanced-stage PCa is a lethal disease with 5-year survival rates around 29%. Identification of biomarkers for early detection of aggressive disease is a key challenge. Starting with 52 candidate biomarkers, selected from existing PCa genomics datasets and known PCa driver genes, we used targeted mass spectrometry to quantify proteins that significantly differed in primary tumors from PCa patients treated with radical prostatectomy (RP) across three study outcomes: (i) metastasis ≥1-year post-RP, (ii) biochemical recurrence ≥1-year post-RP, and (iii) no progression after ≥10 years post-RP. Sixteen proteins that differed significantly in an initial set of 105 samples were evaluated in the entire cohort (n = 338). A five-protein classifier which combined FOLH1, KLK3, TGFB1, SPARC, and CAMKK2 with existing clinical and pathological standard of care variables demonstrated significant improvement in predicting distant metastasis, achieving an area under the receiver-operating characteristic curve of 0.92 (0.86, 0.99, p = 0.001) and a negative predictive value of 92% in the training/testing analysis. This classifier has the potential to stratify patients based on risk of aggressive, metastatic PCa that will require early intervention compared to low risk patients who could be managed through active surveillance.

Evaluation of relationships between the final Gleason score, PI-RADS v2 score, ADC value, PSA level, and tumor diameter in patients that underwent radical prostatectomy due to prostate cancer

INTRODUCTION

This study aimed to investigate the relationship between the serum PSA level, Gleason score (GS), PI-RADS v2 score, tumor ADC_min value, and the largest tumor diameter in patients that underwent radical prostatectomy (RP) due to prostate cancer (PCa) and to comparatively evaluate the variables of these parameters in clinically significant and insignificant PCa groups.

MATERIALS AND METHODS

The mpMRI examinations of the patients who underwent RP due to PCa were retrospectively evaluated. According to the final GS, the lesions were divided into two groups as clinically significant (GS ≥ 7) and insignificant (GS ≤ 6). The PSA value, tumor ADC_min value, tumor diameter, and PI-RADS score were compared between the clinically significant and nonsignificant PCa groups using Student's t-test. The correlations between the serum PSA level, GS, PI-RADS v2 score, tumor ADC_min value, and tumor diameter were evaluated separately (Pearson's correlation analysis was used for peripheral gland tumors, and Spearman's correlation analysis for central gland tumors). A ROC analysis was undertaken to evaluate the efficacy of the tumor ADC_min, diameter and PSA values in differentiating clinically significant and nonsignificant tumors.

RESULTS

In both central and peripheral gland tumors, there was a correlation between the PSA level, tumor diameter, PI-RADS score, ADC_min value, and GS at various levels (poor, moderate, and high). In central gland tumors, there was no significant difference between the two groups in terms of the PSA value and PI-RADS scores (p > 0.05), but the ADC_min value and diameter of the tumor significantly differed (p < 0.05). For peripheral gland tumors, significant differences were observed in all parameters (p < 0.05). The cut-off values for the peripheral and central gland tumors are as follows: lesion diameter, 13.5 mm and 19 mm; tumor ADC_min, 0.709 × 10^-3 mm²/s and 0.874 × 10^-3 mm²/s; and PSA level, 8.47 ng/ml and 11.10 ng/ml, respectively.

CONCLUSION

The current PI-RADS v2 scoring system can be inadequate in distinguishing clinically significant and insignificant groups in central gland tumors. A separate cut-off value of the tumor diameter should be determined for central and peripheral gland tumors. Tumor ADC_min values can be used as a predictive parameter. The PSA cut-off value should be kept lower in peripheral gland tumors.

Performance of T2 Maps in the Detection of Prostate Cancer

RATIONALE AND OBJECTIVES

This study compares the performance of T2 maps in the detection of prostate cancer (PCa) in comparison to T2-weighted (T2W) magnetic resonance images.

MATERIALS AND METHODS

The prospective study was institutional review board approved. Consenting patients (n = 45) with histologic confirmed PCa underwent preoperative 3-T magnetic resonance imaging with or without endorectal coil. Two radiologists, working independently, marked regions of interests (ROIs) on PCa lesions separately on T2W images and T2 maps. Each ROI was assigned a score of 1-5 based on the confidence in accurately detecting cancer, with 5 being the highest confidence. Subsequently, the histologically confirmed PCa lesions (n = 112) on whole-mount sections were matched with ROIs to calculate sensitivity, positive predictive value (PPV), and radiologist confidence score. Quantitative T2 values of PCa and benign tissue ROIs were measured.

RESULTS

Sensitivity and confidence score for PCa detection were similar for T2W images (51%, 4.5 ± 0.8) and T2 maps (52%, 4.5 ± 0.6). However, PPV was significantly higher (P = .001) for T2 maps (88%) compared to T2W (72%) images. The use of endorectal coils nominally improved sensitivity (T2W: 55 vs 47%, T2 map: 54% vs 48%) compared to the use of no endorectal coils, but not the PPV and the confidence score. Quantitative T2 values for PCa (105 ± 28 milliseconds) were significantly (P = 9.3 × 10^-14) lower than benign peripheral zone tissue (211 ± 71 milliseconds), with moderate significant correlation with Gleason score (ρ = -0.284).

CONCLUSIONS

Our study shows that review of T2 maps by radiologists has similar sensitivity but higher PPV compared to T2W images. Additional quantitative information obtained from T2 maps is helpful in differentiating cancer from normal prostate tissue and determining its aggressiveness.

Performance of Ultrafast DCE-MRI for Diagnosis of Prostate Cancer

RATIONALE AND OBJECTIVES

This study aimed to test high temporal resolution dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for different zones of the prostate and evaluate its performance in the diagnosis of prostate cancer (PCa). Determine whether the addition of ultrafast DCE-MRI improves the performance of multiparametric MRI.

MATERIALS AND METHODS

Patients (n = 20) with pathologically confirmed PCa underwent preoperative 3T MRI with T2-weighted, diffusion-weighted, and high temporal resolution (~2.2 seconds) DCE-MRI using gadoterate meglumine (Guerbet, Bloomington, IN) without an endorectal coil. DCE-MRI data were analyzed by fitting signal intensity with an empirical mathematical model to obtain parameters: percent signal enhancement, enhancement rate (α), washout rate (β), initial enhancement slope, and enhancement start time along with apparent diffusion coefficient (ADC) and T2 values. Regions of interests were placed on sites of prostatectomy verified malignancy (n = 46) and normal tissue (n = 71) from different zones.

RESULTS

Cancer (α = 6.45 ± 4.71 s^-1, β = 0.067 ± 0.042 s^-1, slope = 3.78 ± 1.90 s^-1) showed significantly (P <.05) faster signal enhancement and washout rates than normal tissue (α = 3.0 ± 2.1 s^-1, β = 0.034 ± 0.050 s^-1, slope = 1.9 ± 1.4 s^-1), but showed similar percentage signal enhancement and enhancement start time. Receiver operating characteristic analysis showed area under the curve for DCE parameters was comparable to ADC and T2 in the peripheral (DCE 0.67-0.82, ADC 0.80, T2 0.89) and transition zones (DCE 0.61-0.72, ADC 0.69, T2 0.75), but higher in the central zone (DCE 0.79-0.88, ADC 0.45, T2 0.45) and anterior fibromuscular stroma (DCE 0.86-0.89, ADC 0.35, T2 0.12). Importantly, combining DCE with ADC and T2 increased area under the curve by ~30%, further improving the diagnostic accuracy of PCa detection.

CONCLUSION

Quantitative parameters from empirical mathematical model fits to ultrafast DCE-MRI improve diagnosis of PCa. DCE-MRI with higher temporal resolution may capture clinically useful information for PCa diagnosis that would be missed by low temporal resolution DCE-MRI. This new information could improve the performance of multiparametric MRI in PCa detection.

Diagnosis of Prostate Cancer with Noninvasive Estimation of Prostate Tissue Composition by Using Hybrid Multidimensional MR Imaging: A Feasibility Study

Purpose To evaluate whether compartmental analysis by using hybrid multidimensional magnetic resonance (MR) imaging can be used to diagnose prostate cancer and determine its aggressiveness. Materials and Methods Twenty-two patients with prostate cancer underwent preoperative 3.0-T MR imaging. Axial images were obtained with hybrid multidimensional MR imaging by using all combinations of echo times (47, 75, 100 msec) and b values of 0, 750, 1500 sec/mm², resulting in a 3 × 3 array of data associated with each voxel. Volumes of the tissue components stroma, epithelium, and lumen were calculated by fitting the hybrid data to a three-compartment signal model, with distinct, paired apparent diffusion coefficient (ADC) and T2 values associated with each compartment. Volume fractions and conventional ADC and T2 were measured for regions of interest in sites of prostatectomy-verified malignancy (n = 28) and normal tissue (n = 71). Receiver operating characteristic (ROC) analysis was used to evaluate the performance of various parameters in differentiating prostate cancer from benign tissue. Results Compared with normal tissue, prostate cancer showed significantly increased fractional volumes of epithelium (23.2% ± 7.1 vs 48.8% ± 9.2, respectively) and reduced fractional volumes of lumen (26.4% ± 14.1 vs 14.0% ± 5.2) and stroma (50.5% ± 15.7 vs 37.2% ± 9.1) by using hybrid multidimensional MR imaging. The fractional volumes of tissue components show a significantly higher Spearman correlation coefficient with Gleason score (epithelium: ρ = 0.652, P = .0001; stroma: ρ = -0.439, P = .020; lumen: ρ = -0.390, P = .040) compared with traditional T2 values (ρ = -0.292, P = .132) and ADCs (ρ = -0.315, P = .102). The area under the ROC curve for differentiation of cancer from normal prostate was highest for fractional volume of epithelium (0.991), followed by fractional volumes of lumen (0.800) and stroma (0.789). Conclusion Fractional volumes of prostatic lumen, stroma, and epithelium change significantly when cancer is present. These parameters can be measured noninvasively by using hybrid multidimensional MR imaging and have the potential to improve the diagnosis of prostate cancer and determine its aggressiveness. ^© RSNA, 2018 Online supplemental material is available for this article.

Evaluation of MRI for diagnosis of extraprostatic extension in prostate cancer

PURPOSE

To assess the ability of magnetic resonance imaging (MRI) to diagnose extraprostatic extension (EPE) in prostate cancer.

MATERIALS AND METHODS

With Institutional Review Board (IRB) approval, 149 men with 170 ≥0.5 mL tumors underwent preoperative 3T MRI followed by radical prostatectomy (RP) between 2012-2015. Two blinded radiologists (R1/R2) assessed tumors using Prostate Imaging Reporting and Data System (PI-RADS) v2, subjectively evaluated for the presence of EPE, measured tumor size, and length of capsular contact (LCC). A third blinded radiologist, using MRI-RP-maps, measured whole-lesion: apparent diffusion coefficient (ADC) mean/centile and histogram features. Comparisons were performed using chi-square, logistic regression, and receiver operator characteristic (ROC) analysis.

RESULTS

The subjective EPE assessment showed high specificity (SPEC = 75.4/91.3% [R1/R2]), low sensitivity (SENS = 43.3/43.6% [R1/R2]), and area-under (AU) ROC curve = 0.67 (confidence interval [CI] 0.61-0.73) R1 and 0.61 (CI 0.53-0.70) R2; (k = 0.33). PI-RADS v2 scores were strongly associated with EPE (P < 0.001 / P = 0.008; R1/R2) with AU-ROC curve = 0.72 (0.64-0.79) R1 and 0.61 (0.53-0.70) R2; (k = 0.44). Tumors with EPE were larger (18.8 ± 7.8 [median 17, range 6-51] vs. 18.8 ± 4.9 [12, 6-28] mm) and had greater LCC (21.1 ± 14.9 [16, 1-85] vs. 13.6 ± 6.1 [11.5, 4-30] mm); P < 0.001 and 0.002, respectively. AU-ROC for size was 0.73 (0.64-0.80) and LCC was 0.69 (0.60-0.76), respectively. Optimal SENS/SPEC for diagnosis of EPE were: size ≥15 mm = 67.7/66.7% and LCC ≥11 mm = 84.9/44.8%. 10^th -centile ADC and ADC entropy were both associated with EPE (P = 0.02 and < 0.001), with AU-ROC = 0.56 (0.47-0.65) and 0.76 (0.69-0.83), respectively. Optimal SENS/SPEC for diagnosis of EPE with entropy ≥6.99 was 63.3/75.0%. 25^th -centile ADC trended towards being significantly lower with EPE (P = 0.06) with no difference in other ADC metrics (P = 0.25-0.88). Size, LCC, and ADC entropy improved sensitivity but reduced specificity compared with subjective analysis with no difference in overall accuracy (P = 0.38).

CONCLUSION

Measurements of tumor size, capsular contact, and ADC entropy improve sensitivity but reduce specificity for diagnosis of EPE compared to subjective assessment.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:176-185.

Prostate Imaging Reporting and Data System, Version 2, Assessment Categories and Pathologic Outcomes in Patients With Gleason Score 3 + 4 = 7 Prostate Cancer Diagnosed at Biopsy

OBJECTIVE

The purpose of this study is to assess associations between Prostate Imaging Reporting and Data System, version 2 (PI-RADSv2), categories and the presence of a tumor with a Gleason score (GS) of 4 + 3 = 7 or greater or the presence of extraprostatic extension (EPE) at radical prostatectomy (RP) in patients with a GS 3 + 4 = 7 tumor at biopsy.

MATERIALS AND METHODS

A total of 81 men with GS 3 + 4 = 7 prostate cancer diagnosed by transrectal ultrasound-guided biopsy underwent multiparametric MRI and RP between 2012 and 2015. Two blinded radiologists assessed multiparametric MR images and assigned PI-RADSv2 assessment categories (categories 1-5) with the use of sector maps, which were compared with regard to the location of the tumor, the GS, and the presence of EPE at RP. Comparisons were performed between groups with the use of chi-square and multivariate analysis. Diagnostic accuracy was assessed using ROC curve analysis, and localization was compared using the Fisher exact test.

RESULTS

A total of 53.1% of men (43/81) had EPE, and 21.0% (17/81) had GS 4 + 3 = 7 prostate cancer after RP, whereas 2.5% of men (2/81) had their tumors downgraded to GS 3 + 3 = 6. No statistically significant difference in patient age, prostate specific antigen level, or clinical stage existed between groups (p > 0.05). PI-RADSv2 assessment categories were significantly higher for GS 4 + 3 = 7 tumors (p = 0.03). PI-RADSv2 showed moderate accuracy for the diagnosis of GS 4 + 3 = 7 tumors (AUC, 0.65; 95% CI, 0.54-0.77), with a category of 4 or higher having a sensitivity and specificity for diagnosis of 94.1% and 23.4%, respectively. No patient with a PI-RADSv2 category lower than 3 had a GS 4 + 3 = 7 tumor. Accuracy of tumor localization ranged from 86.4% to 92.6%, with 88.2% of errors (15/17) occurring in GS 3 + 3 = 6 or GS 3 + 4 = 7 tumors (p = 0.30). PI-RADSv2 categories were noted to be higher when EPE was present (p < 0.001). Interobserver agreement was moderate (κ = 0.43).

CONCLUSION

For GS 3 + 4 = 7 cancers detected at transrectal ultrasound-guided biopsy, higher PI-RADSv2 assessment categories are associated with upgrading to GS 4 + 3 = 7 cancer and with the presence of EPE after RP. A PI-RADSv2 score of 3 or higher was 100% sensitive for diagnosing GS 4 + 3 = 7 tumors.

MRI assessment of pathological stage and surgical margins in anterior prostate cancer (APC) using subjective and quantitative analysis

PURPOSE

To evaluate magnetic resonance imaging (MRI) for assessment of extraprostatic extension (EPE) and positive surgical margins (PSM) in anterior prostate cancer (APC).

MATERIALS AND METHODS

With Institutional Review Board approval, 25 APC (>2/3 of tumor anterior to urethra) were assessed using 3T MRI by two blinded radiologists for: size and maximal leading edge of tumor (relative to anterior fibromuscular stroma [AFMS]) on b ≥1000 sec/mm² echo-planar-MRI fused onto T₂ -weighted-MRI, invasion of AFMS and EPE. Comparisons were performed between APCs by EPE/PSM using chi-square, multivariable analysis, and receiver operator characteristic (ROC) analysis.

RESULTS

The prevalence of EPE and PSM were 52% (13/25) and 36% (9/25). Tumor sizes were larger with EPE (22.5 ± 8.4 vs. 14.7 ± 6.3, P = 0.02) and PSM (23.0 ± 9.3 vs. 16.4 ± 7.0, P = 0.06). Area under ROC curve (AUC-ROC) for the diagnosis of EPE by tumor size was 0.77 (95% confidence interval [CI] 0.58-0.95); ≥16 mm size = sensitivity/specificity 69.2/66.7%. Maximal leading edge of tumor was greater with EPE (2.4 ± 2.2 vs. -0.2 ± 3.0) and PSM (2.8 ± 2.3 vs. -0.3 ± 2.5), (P = 0.023, 0.031). AUC-ROC for diagnosis of EPE/PSM by leading edge was 0.78 (CI 0.57-0.97) and 0.75 (CI 0.56-0.94). A ≥1 mm leading edge yielded sensitivity/specificity of 76.9/75.0% and 77.8/62.5% for diagnosis of EPE/PSM. 60-72% (15-18/25) tumors invaded AFMS (k = 0.74), which was not associated with EPE/PSM (P = 0.12-0.14). Radiologists' assessment of EPE had sensitivity/specificity of 61.5-69.2/50.0-75.0% (k = 0.53).

CONCLUSION

Tumor size and leading edge of tumor relative to AFMS may enable diagnosis of EPE and positive surgical margins in APC.

LEVEL OF EVIDENCE

2 J. MAGN. RESON. IMAGING 2017;45:1296-1303.

Combined PET/MRI: from Status Quo to Status Go. Summary Report of the Fifth International Workshop on PET/MR Imaging; February 15-19, 2016; Tübingen, Germany

This article provides a collaborative perspective of the discussions and conclusions from the fifth international workshop of combined positron emission tomorgraphy (PET)/magnetic resonance imaging (MRI) that was held in Tübingen, Germany, from February 15 to 19, 2016. Specifically, we summarise the second part of the workshop made up of invited presentations from active researchers in the field of PET/MRI and associated fields augmented by round table discussions and dialogue boards with specific topics. This year, this included practical advice as to possible approaches to moving PET/MRI into clinical routine, the use of PET/MRI in brain receptor imaging, in assessing cardiovascular diseases, cancer, infection, and inflammatory diseases. To address perceived challenges still remaining to innovatively integrate PET and MRI system technologies, a dedicated round table session brought together key representatives from industry and academia who were engaged with either the conceptualisation or early adoption of hybrid PET/MRI systems. Discussions during the workshop highlighted that emerging unique applications of PET/MRI such as the ability to provide multi-parametric quantitative and visual information which will enable not only overall disease detection but also disease characterisation would eventually be regarded as compelling arguments for the adoption of PET/MR. However, as indicated by previous workshops, evidence in favour of this observation is only growing slowly, mainly due to the ongoing inability to pool data cohorts from independent trials as well as different systems and sites. The participants emphasised that moving from status quo to status go entails the need to adopt standardised imaging procedures and the readiness to act together prospectively across multiple PET/MRI sites and vendors.

MicroRNAs as Biomarkers for Diagnosis, Prognosis and Theranostics in Prostate Cancer

Prostate cancer (PC) includes several phenotypes, from indolent to highly aggressive cancer. Actual diagnostic and prognostic tools have several limitations, and there is a need for new biomarkers to stratify patients and assign them optimal therapies by taking into account potential genetic and epigenetic differences. MicroRNAs (miRNAs) are small sequences of non-coding RNA regulating specific genes involved in the onset and development of PC. Stable miRNAs have been found in biofluids, such as serum and plasma; thus, the measurement of PC-associated miRNAs is emerging as a non-invasive tool for PC detection and monitoring. In this study, we conduct an in-depth literature review focusing on miRNAs that may contribute to the diagnosis and prognosis of PC. The role of miRNAs as a potential theranostic tool in PC is discussed. Using a meta-analysis approach, we found a group of 29 miRNAs with diagnostic properties and a group of seven miRNAs with prognostic properties, which were found already expressed in both biofluids and PC tissues. We tested the two miRNA groups on The Cancer Genome Atlas dataset of PC tissue samples with a machine-learning approach. Our results suggest that these 29 miRNAs should be considered as potential panel of biomarkers for the diagnosis of PC, both as in vivo non-invasive test and ex vivo confirmation test.

Whole-Tumor Quantitative Apparent Diffusion Coefficient Histogram and Texture Analysis to Predict Gleason Score Upgrading in Intermediate-Risk 3 + 4 = 7 Prostate Cancer

OBJECTIVE

The objective of our study was to evaluate whole-lesion quantitative apparent diffusion coefficient (ADC) for the prediction of Gleason score (GS) upgrading in 3 + 4 = 7 prostate cancer.

MATERIALS AND METHODS

Fifty-four patients with GS 3 + 4 = 7 prostate cancer diagnosed at systematic transrectal ultrasound (TRUS)-guided biopsy underwent 3-T MRI and radical prostatectomy (RP) between 2012 and 2014. A blinded radiologist contoured dominant tumors on ADC maps using histopathologic correlation. The whole-lesion mean ADC, ADC ratio (normalized to peripheral zone), ADC histogram, and texture analysis were compared between tumors with GS upgrading and those without GS upgrading using multivariate ROC analyses and logistic regression modeling.

RESULTS

Tumors were upgraded to GS 4 + 3 = 7 after RP in 26% (n = 14) of the 54 patients, and tumors were downgraded after RP in none of the patients. The mean ADC, ADC ratio, 10th-centile ADC, 25th-centile ADC, and 50th-centile ADC were similar between patients with GS 3 + 4 = 7 tumors (0.99 ± 0.22, 0.58 ± 0.15, 0.77 ± 0.31, 0.94 ± 0.28, and 1.15 ± 0.24, respectively) and patients with upgraded GS 4 + 3 = 7 tumors (1.02 ± 0.18, 0.55 ± 0.11, 0.71 ± 0.26, 0.89 ± 0.20, and 1.11 ± 0.16) (p > 0.05). Regression models combining texture features improved the prediction of GS upgrading. The combination of kurtosis, entropy, and skewness yielded an AUC of 0.76 (SE = 0.07) (p < 0.001), a sensitivity of 71%, and a specificity of 73%. The combination of kurtosis, heterogeneity, entropy, and skewness yielded an AUC of 0.77 (SE = 0.07) (p < 0.001), a sensitivity of 71%, and a specificity of 78%.

CONCLUSION

In this study, whole-lesion mean ADC, ADC ratio, and ADC histogram analysis were not predictive of pathologic upgrading of GS 3 + 4 = 7 prostate cancer after RP. ADC texture analysis improved accuracy.

In-parallel comparative evaluation between multiparametric magnetic resonance imaging, prostate cancer antigen 3 and the prostate health index in predicting pathologically confirmed significant prostate cancer in men eligible for active surveillance

OBJECTIVE

To assess the performance capabilities of multiparametric magnetic resonance imaging (mpMRI), the prostate health index (PHI) and prostate cancer antigen 3 (PCA3) in predicting the presence of pathologically confirmed significant prostate cancer (PCSPCa), according to the European Randomized Study of Screening Prostate Cancer definition, in a single cohort of patients who underwent radical prostatectomy (RP) but who were eligible for active surveillance (AS).

MATERIALS AND METHODS

An observational retrospective study was performed in 120 patients with prostate cancer (PCa), treated with robot-assisted RP but eligible for AS according to Prostate Cancer Research International: Active Surveillance criteria. Blood and urine specimens were collected before initial prostate biopsy for PHI and PCA3 measurements, respectively. In addition, all patients underwent mpMRI, preoperatively and 6-8 weeks after biopsy, with a 1.5T scanner using a four-to-five-channel phase array coil combined with an endorectal coin. mpMRI images were assessed and diagrams showing the prostate sextants were used to designate regions of abnormality within the prostate. Prostate findings were assigned to one of five categories according to Prostate Imaging-Reporting and Data System guidelines (PI-RADS) and considered positive for PCa if final PI-RADS score was >3 and negative if ≤3.

RESULTS

Pathologically confirmed reclassification was observed in 55 patients (45.8%). mpMRI showed good specificity and negative predictive value (0.61 and 0.73, respectively) for excluding PCSPCa compared with the PHI and PCA3. On multivariate analyses and after 1 000 bootstrapping resampling, the inclusion of both mpMRI and the PHI significantly increased the accuracy of the base model in predicting PCSPCa. For the prediction of PCSPCa, in particular, the base model had an area under the curve (AUC) of 0.71 which significantly increased by 4% with the addition of the PHI (AUC = 0.75; P < 0.01) and by 7% with the addition of mpMRI (AUC = 0.78; P < 0.01). Decision-curve analysis showed that the multivariable model with mpMRI had the highest net benefit.

CONCLUSION

In a single cohort of patients who underwent RP but who were eligible for AS, mpMRI and, to a lesser extent, the PHI, had an important role in discriminating the presence of PCSPCa; both measures could therefore be useful in the selection and monitoring of patients undergoing AS.

Current role of multiparametric magnetic resonance imaging for prostate cancer

Multiparametric magnetic resonance imaging (mp-MRI) has shown promising results in diagnosis, localization, risk stratification and staging of clinically significant prostate cancer, and targeting or guiding prostate biopsy. mp-MRI consists of T2-weighted imaging (T2WI) combined with several functional sequences including diffusion-weighted imaging (DWI), perfusion or dynamic contrast-enhanced imaging (DCEI) and spectroscopic imaging. Recently, mp-MRI has been used to assess prostate cancer aggressiveness and to identify anteriorly located tumors before and during active surveillance. Moreover, recent studies have reported that mp-MRI is a reliable imaging modality for detecting local recurrence after radical prostatectomy or external beam radiation therapy. Because assessment on mp-MRI can be subjective, use of the newly developed standardized reporting Prostate Imaging and Reporting Archiving Data System (PI-RADS) scoring system and education of specialist radiologists are essential for accurate interpretation. This review focuses on the current place of mp-MRI in prostate cancer and its evolving role in the management of prostate cancer.

Current role of multiparametric magnetic resonance imaging in the management of prostate cancer

The purpose of this review was to evaluate the current role of multiparametric magnetic resonance imaging (mp-MRI) in the management of prostate cancer (PC). The diagnosis of PC remains controversial owing to overdetection of indolent disease, which leads to overtreatment and subsequent patient harm. mp-MRI has the potential to equilibrate the imbalance between detection and treatment. The limitation of the data for analysis with this new technology is problematic, however. This issue has been compounded by a paradigm shift in clinical practice aimed at utilizing this modality, which has been rolled out in an ad hoc fashion often with commercial motivation. Despite a growing body of literature, pertinent clinical questions remain. For example, can mp-MRI be calibrated to reliably detect biologically significant disease? As with any new technology, objective evaluation of the clinical applications of mp-MRI is essential. The focus of this review was on the evaluation of mp-MRI of the prostate with respect to clinical utility.