Radiomics from multisite MRI and clinical data to predict clinically significant prostate cancer

BACKGROUND

Magnetic resonance imaging (MRI) is useful in the diagnosis of clinically significant prostate cancer (csPCa). MRI-derived radiomics may support the diagnosis of csPCa.

PURPOSE

To investigate whether adding radiomics from biparametric MRI to predictive models based on clinical and MRI parameters improves the prediction of csPCa in a multisite-multivendor setting.

MATERIAL AND METHODS

Clinical information (PSA, PSA density, prostate volume, and age), MRI reviews (PI-RADS 2.1), and radiomics (histogram and texture features) were retrieved from prospectively included patients examined at different radiology departments and with different MRI systems, followed by MRI-ultrasound fusion guided biopsies of lesions PI-RADS 3-5. Predictive logistic regression models of csPCa (Gleason score ≥7) for the peripheral (PZ) and transition zone (TZ), including clinical data and PI-RADS only, and combined with radiomics, were built and compared using receiver operating characteristic (ROC) curves.

RESULTS

In total, 456 lesions in 350 patients were analyzed. In PZ and TZ, PI-RADS 4-5 and PSA density, and age in PZ, were independent predictors of csPCa in models without radiomics. In models including radiomics, PI-RADS 4-5, PSA density, age, and ADC energy were independent predictors in PZ, and PI-RADS 5, PSA density and ADC mean in TZ. Comparison of areas under the ROC curve (AUC) for the models without radiomics (PZ: AUC = 0.82, TZ: AUC = 0.80) versus with radiomics (PZ: AUC = 0.82, TZ: AUC = 0.82) showed no significant differences (PZ: P = 0.366; TZ: P = 0.171).

CONCLUSION

PSA density and PI-RADS are potent predictors of csPCa. Radiomics do not add significant information to our multisite-multivendor dataset.

Transitional zone prostate cancer: Performance of texture-based machine learning and image-based deep learning

This study is aimed to explore the performance of texture-based machine learning and image-based deep-learning for enhancing detection of Transitional-zone prostate cancer (TZPCa) in the background of benign prostatic hyperplasia (BPH), using a one-to-one correlation between prostatectomy-based pathologically proven lesion and MRI. Seventy patients confirmed as TZPCa and twenty-nine patients confirmed as BPH without TZPCa by radical prostatectomy. For texture analysis, a radiologist drew the region of interest (ROI) for the pathologically correlated TZPCa and the surrounding BPH on T2WI. Significant features were selected using Least Absolute Shrinkage and Selection Operator (LASSO), trained by 3 types of machine learning algorithms (logistic regression [LR], support vector machine [SVM], and random forest [RF]) and validated by the leave-one-out method. For image-based machine learning, both TZPCa and BPH without TZPCa images were trained using convolutional neural network (CNN) and underwent 10-fold cross validation. Sensitivity, specificity, positive and negative predictive values were presented for each method. The diagnostic performances presented and compared using an ROC curve and AUC value. All the 3 Texture-based machine learning algorithms showed similar AUC (0.854-0.861)among them with generally high specificity (0.710-0.775). The Image-based deep learning showed high sensitivity (0.946) with good AUC (0.802) and moderate specificity (0.643). Texture -based machine learning can be expected to serve as a support tool for diagnosis of human-suspected TZ lesions with high AUC values. Image-based deep learning could serve as a screening tool for detecting suspicious TZ lesions in the context of clinically suspected TZPCa, on the basis of the high sensitivity.

Post-MRI transrectal micro-ultrasonography of transition zone PI-RADS > 2 lesions for biopsy guidance

OBJECTIVE

To prospectively determine the value of post-MRI micro-ultrasonography (microUS) in the diagnosis of transition zone (TZ) significant prostate cancer (sPCa).

PATIENTS AND METHODS

Eighty-four consecutive men (66 ± 6.3 years) with a mean PSA level of 10.2 ± 7.4 ng/mL and at least one TZ-PI-RADS > 2 lesion were included. All patients had MRI-directed microUS and biopsy. Sensitivity and specificity of post-MRI microUS to visualize PI-RADS > 2 TZ lesions, the cancer detection rate of TZ-sPCa, and tumor characteristics according to their visibility on microUS were evaluated. Interreader agreement for detecting microUS+ lesions was evaluated using Cohen's kappa test.

RESULTS

Of the 92 PI-RADS > 2 lesions, 71 (71/92; 77%) were visible on microUS and biopsy was performed without image fusion, which was required for the 21 invisible lesions (21/92; 22.8%). TZ-sPCa detection rate was 51.1% (47/92). Sensitivity and specificity of MRI-directed microUS were 83% (39/47; 95% CI: 69.2-92.4%) and 28.9% (13/45; 95% CI: 16.4-44.3%), on a per-lesion basis and 86.4% (38/45; 95% CI: 72.6-94.8%) and 27.5% (11/40; 95% CI: 14.6-43.9%) on a per-patient basis. Visible tumors on microUS exhibited a larger volume and a lower mean ADC value than non-visible tumors (15.8 ± 5.1 vs. 12.5 ± 3.6 mm and 0.82 ± 1.1 × 10³ vs. 0.9 ± 1.4 × 10^-3 mm²/s) (p = 0.02). Non-visible tumors showed a heterogeneous non-specific echotexture or were masked by the shadowing caused by corpora amylacea. Interreader agreement was almost perfect (kappa = 0.88; 95% CI: 0.79-0.95). The main limitation is the single-center feature of the study.

CONCLUSION

MRI-targeted transrectal microUS is effective to detect TZ-sPCa. TRUS-MRI image fusion helps overcome limitations due to TZ tissue heterogeneity.

KEY POINTS

microUS can visualize the majority of MRI-detected PI-RADS > 2 TZ lesions (sensitivity = 83%). Interreader agreement of MRI-directed microUS in the detection of TZ lesions appears excellent (kappa = 0.88). In 77% of PI-RADS > 2 TZ lesions, biopsy was performed under microUS visual control. MRI fusion system was only used to overcome limitations due to tissue heterogeneity of benign prostatic hyperplasia.

Combination of MRI prostate and 18F-DCFPyl PSMA PET/CT detects all clinically significant prostate cancers in treatment-naive patients: An international multicentre retrospective study

INTRODUCTION

Clinical and biochemical assessment and biopsies can miss clinically significant prostate cancers (csPCa) in up to 20% of patients and diagnose clinically insignificant tumours leading to overtreatment. This retrospective study analyses the accuracy of ¹⁸ F-DCFPyL PET/CT in detecting csPCa as a primary diagnostic tool and directly compares it with mpMRI prostate in treatment-naive patients. The two modalities are then correlated to determine whether they are better in combination, than either alone.

METHODS

This is a retrospective dual-institution study of patients who underwent contemporaneous MRI and PSMA-PET between January 2017 and March 2020 with histologic confirmation. The images were re-reviewed and concordance between modalities assessed. Results were compared with histopathology to determine the ability of MRI and PSMA-PET to detect csPCA.

RESULTS

MRI and PSMA-PET detected the same index lesion in 90.8% of cases with a kappa of 0.82. PET detected an additional 6.2% of index lesions which were MRI occult. MRI detected an additional 3.1% which were PET occult. No additional csPCa was identified on pathology which was not seen on imaging. The sensitivity of PSMA-PET in detecting csPCa is 96.7% and that of MRI is 93.4% with no statistically significant difference between the two (P = 0.232). Both modalities detected all four cases of non-csPCa with these being considered false positives.

CONCLUSION

Both mpMRI and 18F-DCFPyL-PSMA-PET/CT have high sensitivity for detecting csPCa with high agreement between modalities. There were no synchronous csPCa lesions detected on pathology that were not detected on imaging too.

Effectiveness of Dynamic Contrast Enhanced MRI with a Split Dose of Gadoterate Meglumine for Detection of Prostate Cancer

RATIONALE AND OBJECTIVES

To evaluate whether dynamic contrast enhanced (DCE) MRI with a split injection of 30% followed by 70% of a standard dose (30PSD and 70PSD) of gadoterate meglumine (DOTAREM) can improve diagnosis of prostate cancer (PCa).

MATERIALS AND METHODS

MRI for twenty patients was performed on a Philips Ingenia 3T scanner without an endorectal coil followed by subsequent radical prostatectomy. DCE 3D T1-FFE data were acquired with injection of 0.03 mmol/kg followed after 2 minutes by 0.07 mmol/kg of DOTAREM. Regions-of-interest on histologically verified PCa and normal tissue in different prostate zones and the iliac artery were drawn. Average signal intensity as function of time was calculated for each ROI and fitted by using the signal intensity form of the Tofts (SI-Tofts) model to extract physiological parameters (K^trans and v_e). In addition, the scaled arterial input function (AIF) obtained from 30PSD data was used to analyze 70PSD data.

RESULTS

The AIF obtained from 30PSD data showed both first and second passes clearly and had much higher peak magnitude than AIFs from 70PSD data. K^trans was significantly (p < 0.05) larger in PCa than in normal tissue in peripheral zone (PZ) and central zone (CZ) for both 70PSD and 70PSD data analyzed with a scaled AIF. K^trans in cancer overlapped with that of normal tissue in the transition zone (TZ). There was no statistical difference in v_e between cancer and normal tissue. Receiver operating characteristic analysis showed that use of the AIF from 30PSD data to analyze 70PSD data increased the diagnostic efficacy of K^trans in the PZ and CZ.

CONCLUSION

The split dose protocol for injection of Dotarem increased diagnostic accuracy of quantitative analysis with the SI-Tofts model.

Detection rate and variables associated with incidental prostate cancer by holmium laser enucleation of the prostate

OBJECTIVES

Holmium laser enucleation of the prostate is well-established and effective for bladder outlet obstruction due to benign prostatic hyperplasia. The objective of this study was to examine the detection rate of incidental prostate cancer by holmium laser enucleation of the prostate and variables associated with them.

METHODS

A total of 612 patients were enrolled. We retrospectively examined the detection rate of incidental prostate cancer and perioperative variables associated with them.

RESULTS

Forty-nine of 612 patients were diagnosed with incidental prostate cancer. Univariate logistic regression analysis showed that higher prostate-specific antigen density (odds ratio 3.34, 95% confidence interval 1.02-10.94, P = 0.05), higher prostate-specific antigen density of the transition zone (odds ratio 2.28, 95% confidence interval 1.02-5.09, P = 0.04), and findings of the prostate cancer on magnetic resonance imaging (peripheral zone: odds ratio 4.71, 95% confidence interval 1.70-13.1, P = 0.003; transition zone: odds ratio 3.46, 95% confidence interval 1.74-6.86, P < 0.001; peripheral and transition zones: odds ratio 6.00, 95% confidence interval 1.51-23.8, P = 0.01) were significantly associated with incidental prostate cancer. Multivariate logistic regression analysis showed that findings of the prostate cancer on magnetic resonance imaging (peripheral zone: odds ratio 4.36, 95% confidence interval 1.49-12.8, P = 0.001; transition zone: odds ratio 3.54, 95% confidence interval 1.75-7.16, P < 0.001; peripheral and transition zones: odds ratio 6.14, 95% confidence interval 1.53-24.5, P = 0.01) was an independent risk factor for incidental prostate cancer.

CONCLUSION

The detection rate of incidental prostate cancer was 8.0%, and findings of the prostate cancer on magnetic resonance imaging were an independent predictive factor for incidental prostate cancer.

Clinical impact of ultra-high b-value (3000 s/mm2) diffusion-weighted magnetic resonance imaging in prostate cancer at 3T: comparison with b-value of 2000 s/mm2

OBJECTIVE

High b-value diffusion-weighted imaging (hDWI) with a b-value of 2000 s/mm² provides insufficient image contrast between benign and malignant tissues and an overlap of apparent diffusion coefficient (ADC) between Gleason grades (GG) in prostate cancer (PC). We compared image quality, PC detectability, and discrimination ability for PC aggressiveness between ultra-high b-value DWI (uhDWI) of 3000 s/mm² and hDWI.

METHODS

The subjects were 49 patients with PC who underwent 3T multiparametric MRI. Single-shot echo-planar DWI was acquired with b-values of 0, 2000, and 3000 s/mm². Anatomical distortion of prostate (AD), signal intensity of benign prostate (PSI), and lesion conspicuity score (LCS) were assessed using a 4-point scale; and signal-to-noise ratio, contrast-to-noise ratio, and mean ADC (×10^-3 mm²/s) of lesion (lADC) and surrounding benign region (bADC) were measured.

RESULTS

PSI was significantly lower in uhDWI than in hDWI (p < 0.001). AD, LCS, signal-to-noise ratio, and contrast-to-noise ratio were comparable between uhDWI and hDWI (all p > 0.05). In contrast, lADC was significantly lower than bADC in both uhDWI and hDWI (both p < 0.001). In comparison of lADC between tumors of ≤GG2 and those of ≥GG3, both uhDWI and hDWI showed significant difference (p = 0.007 and p = 0.021, respectively). AUC for separating tumors of ≤GG2 from those of ≥GG3 was 0.731 in hDWI and 0.699 in uhDWI (p = 0.161).

CONCLUSION

uhDWI suppressed background signal better than hDWI, but did not contribute to increased diagnostic performance in PC.

ADVANCES IN KNOWLEDGE

Compared with hDWI, uhDWI could not contribute to increased diagnostic performance in PC.

A narrative review of biparametric MRI (bpMRI) implementation on screening, detection, and the overall accuracy for prostate cancer

Prostate cancer is the most common malignancy in American men following skin cancer, with approximately one in eight men being diagnosed during their lifetime. Over the past several decades, the treatment of prostate cancer has evolved rapidly, so too has screening. Since the mid-2010s, magnetic resonance imaging (MRI)-guided biopsies or 'targeted biopsies' has been a rapidly growing topic of clinical research within the field of urologic oncology. The aim of this publication is to provide a review of biparametric MRI (bpMRI) utilization for the diagnosis of prostate cancer and a comparison to multiparametric MRI (mpMRI). Through single-centered studies and meta-analysis across all identified pertinent published literature, bpMRI is an effective tool for the screening and diagnosis of prostate cancer. When compared with the diagnostic accuracy of mpMRI, bpMRI identifies prostate cancer at comparable rates. In addition, when omitting dynamic contrast-enhanced (DCE) protocol to the MRI, patients incur reduced costs and shorter imaging time while providers can offer more tests to their patient population.

A non-inferiority comparative analysis of micro-ultrasonography and MRI-targeted biopsy in men at risk of prostate cancer

OBJECTIVE

To compare the efficacy of multiparametric magnetic resonance imaging (mpMRI)-directed and micro-ultrasonography (micro-US)-directed biopsy for detecting clinically significant (Grade Group >1) prostate cancer (csPCa).

MATERIALS AND METHODS

A total of 203 patients were prospectively enrolled at three institutions across Germany and Austria in the period from January 2019 to December 2019. During each biopsy, the urologist was blinded to the mpMRI report until after the micro-US targets had been assessed. After unblinding, targets were then sampled using software-assisted fusion, followed by systematic samples. The primary outcome measure was non-inferiority of micro-US to detect csPCa, with a detection ratio of at least 80% that of mpMRI.

RESULTS

A total of 79 csPCa cases were detected overall (39%). Micro-US-targeted biopsy detected 58/79 cases (73%), while mpMRI-targeted biopsy detected 60/79 (76%) and non-targeted (completion sampling) samples detected 45/79 cases (57%). mpMRI-targeted samples alone detected 7/79 (9%) csPCa cases which were missed by micro-US-targeted and non-targeted samples. Three of these seven were anterior lesions with 2/7 in the transition zone. Micro-US-targeted samples alone detected 5/79 (6%) and completion sampling alone detected 4/79 cases (5%). Micro-US was non-inferior to mpMRI and detected 97% of the csPCa cases detected by mpMRI-targeted biopsy (95% CI 80-116%; P = 0.023).

CONCLUSIONS

This is the first multicentre prospective study comparing micro-US-targeted biopsy with mpMRI-targeted biopsy. The study provides further evidence that micro-US can reliably detect cancer lesions and suggests that micro-US biopsy might be as effective as mpMRI for detection of csPCA. This result has significant implications for increasing accessibility, reducing costs and expediting diagnosis.

Modified Predictive Model and Nomogram by Incorporating Prebiopsy Biparametric Magnetic Resonance Imaging With Clinical Indicators for Prostate Biopsy Decision Making

Purpose

The purpose of this study is to explore the value of combining bpMRI and clinical indicators in the diagnosis of clinically significant prostate cancer (csPCa), and developing a prediction model and Nomogram to guide clinical decision-making.

Methods

We retrospectively analyzed 530 patients who underwent prostate biopsy due to elevated serum prostate specific antigen (PSA) levels and/or suspicious digital rectal examination (DRE). Enrolled patients were randomly assigned to the training group (n = 371, 70%) and validation group (n = 159, 30%). All patients underwent prostate bpMRI examination, and T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) sequences were collected before biopsy and were scored, which were respectively named T2WI score and DWI score according to Prostate Imaging Reporting and Data System version 2 (PI-RADS v.2) scoring protocol, and then PI-RADS scoring was performed. We defined a new bpMRI-based parameter named Total score (Total score = T2WI score + DWI score). PI-RADS score and Total score were separately included in the multivariate analysis of the training group to determine independent predictors for csPCa and establish prediction models. Then, prediction models and clinical indicators were compared by analyzing the area under the curve (AUC) and decision curves. A Nomogram for predicting csPCa was established using data from the training group.

Results

In the training group, 160 (43.1%) patients had prostate cancer (PCa), including 128 (34.5%) with csPCa. Multivariate regression analysis showed that the PI-RADS score, Total score, f/tPSA, and PSA density (PSAD) were independent predictors of csPCa. The prediction model that was defined by Total score, f/tPSA, and PSAD had the highest discriminatory power of csPCa (AUC = 0.931), and the diagnostic sensitivity and specificity were 85.1% and 87.5%, respectively. Decision curve analysis (DCA) showed that the prediction model achieved an optimal overall net benefit in both the training group and the validation group. In addition, the Nomogram predicted csPCa revealed good estimation when compared with clinical indicators.

Conclusion

The prediction model and Nomogram based on bpMRI and clinical indicators exhibit a satisfactory predictive value and improved risk stratification for csPCa, which could be used for clinical biopsy decision-making.

Diagnosis of transition zone prostate cancer by multiparametric MRI: added value of MR spectroscopic imaging with sLASER volume selection

Background

Current multiparametric MRI (mp-MRI) in routine clinical practice has poor-to-moderate diagnostic performance for transition zone prostate cancer. The aim of this study was to evaluate the potential diagnostic performance of novel ¹H magnetic resonance spectroscopic imaging (MRSI) using a semi-localized adiabatic selective refocusing (sLASER) sequence with gradient offset independent adiabaticity (GOIA) pulses in addition to the routine mp-MRI, including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) and quantitative dynamic contrast enhancement (DCE) for transition zone prostate cancer detection, localization and grading.

Methods

Forty-one transition zone prostate cancer patients underwent mp-MRI with an external phased-array coil. Normal and cancer regions were delineated by two radiologists and divided into low-risk, intermediate-risk, and high-risk categories based on TRUS guided biopsy results. Support vector machine models were built using different clinically applicable combinations of T2WI, DWI, DCE, and MRSI. The diagnostic performance of each model in cancer detection was evaluated using the area under curve (AUC) of the receiver operating characteristic diagram. Then accuracy, sensitivity and specificity of each model were calculated. Furthermore, the correlation of mp-MRI parameters with low-risk, intermediate-risk and high-risk cancers were calculated using the Spearman correlation coefficient.

Results

The addition of MRSI to T2WI + DWI and T2WI + DWI + DCE improved the accuracy, sensitivity and specificity for cancer detection. The best performance was achieved with T2WI + DWI + MRSI where the addition of MRSI improved the AUC, accuracy, sensitivity and specificity from 0.86 to 0.99, 0.83 to 0.96, 0.80 to 0.95, and 0.85 to 0.97 respectively. The (choline + spermine + creatine)/citrate ratio of MRSI showed the highest correlation with cancer risk groups (r = 0.64, p < 0.01).

Conclusion

The inclusion of GOIA-sLASER MRSI into conventional mp-MRI significantly improves the diagnostic accuracy of the detection and aggressiveness assessment of transition zone prostate cancer.

Utility of Quantitative T2-Mapping Compared to Conventional and Advanced Diffusion Weighted Imaging Techniques for Multiparametric Prostate MRI in Men with Hip Prosthesis

BACKGROUND

Diffusion weighted imaging (DWI) is fundamental for prostate cancer (PCa) detection with MRI; however, limited by susceptibility artifact from hip prosthesis.

PURPOSE

To evaluate image quality and ability to detect PCa with quantitative T2-mapping and DWI in men with hip prosthesis undergoing prostate MRI.

STUDY TYPE

Prospective, cross-sectional study.

POPULATION

Thirty consecutive men with hip replacement (18 unilateral, 12 bilateral) undergoing prostate MRI from 2019 to 2021.

FIELD STRENGTH/SEQUENCE

3-T; multiparametric MRI (T2W, DCE-MRI, echo-planar [EPI]-DWI), T2-mapping (Carr-Purcell-Meiboom-Gill), FOCUS-EPI-DWI, PROPELLER-DWI.

ASSESSMENT

Five blinded radiologists independently evaluated MRI image quality using a 5-point Likert scale. PI-RADS v2.1 scores were applied in four interpretation strategies: 1) T2W-FSE+DCE-MRI+EPI-DWI, 2) T2W-FSE+DCE-MRI+EPI-DWI+FOCUS-EPI-DWI, 3) T2W-FSE+DCE-MRI+EPI-DWI+PROPELLER-DWI, 4) T2W-FSE+DCE-MRI+EPI-DWI+T2-maps. Five-point confidence scores were recorded.

STATISTICAL ANALYSIS

ANOVA, Kruskal-Wallis with pair-wise comparisons by Wilcoxon sign-rank, and paired t-tests, P < 0.05 was considered significant. Cohen's Kappa (k) for PI-RADSv2.1 scoring and proportion of correctly classified lesions tabulated for pathology-confirmed cases with 95% confidence intervals (CIs).

RESULTS

For all radiologists, T2-map image quality was significantly higher than EPI-DWI, FOCUS-EPI-DWI, and PROPELLER-DWI and similar (P = 0.146-0.706) or significantly better (for two readers) than T2W-FSE and DCE-MRI. PI-RADS v2.1 agreement improved comparing strategy A (k = 0.46) to strategy B (k = 0.58) to strategy C (k = 0.58) and was highest with strategy D which included T2-maps (k = 1.00). Radiologists' confidence was significantly highest with strategy D. Strategies B and C had similar confidence (P = 0.051-0.063) both significantly outperforming strategy A. Twelve men with 17 lesions had pathology confirmed diagnoses (13 PCa, 4 benign). Strategy D had the highest proportion of correctly classified lesions (76.5-82.4%) with overlapping 95% confidence intervals.

DATA CONCLUSION

T2-mapping may be a valuable adjunct to prostate MRI in men with hip replacement resulting in improved image quality, higher reader confidence, interobserver agreement, and accuracy in PI-RADS scoring.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 2.

Diagnostic accuracy of high b-value diffusion weighted imaging for patients with prostate cancer: a diagnostic comprehensive analysis

We performed a meta-analysis to assess the diagnostic accuracy of high b-value diffusion-weighted imaging for patients with prostate cancer. A comprehensive literature search of the PubMed, Excerpta Medica Database, Cochrane Library, China National Knowledge Infrastructure, China Biology Medicine disc, and Wanfang databases from January 1, 1995, to April 30, 2021, was conducted. The quality of the retrieved papers was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and their 95% confidence intervals (CIs) were evaluated using bivariate mixed effects models. A total of twenty-four articles matched the selection criteria and were finally included after screening the titles, abstracts, and full texts of 641 initial articles. The pooled sensitivity and specificity (95% CI) were 0.84 (0.80-0.87) and 0.87 (0.81-0.91), respectively. The pooled positive and negative likelihood ratios (95% CI) were 6.4 (4.4-9.3) and 0.19 (0.16-0.23), respectively. The diagnostic odds ratio was 34 (95% CI: 22-51). The area under the summary receiver operator characteristic curve was 0.91 (95% CI: 0.88-0.93). Subgroup analysis presents similar results. The diagnostic accuracy of high b-value diffusion-weighted imaging was similarly high in the qualitative and quantitative evaluation of prostate cancer.

Comparison of mono-exponential, bi-exponential, kurtosis, and fractional-order calculus models of diffusion-weighted imaging in characterizing prostate lesions in transition zone

PURPOSE

To compare various models of diffusion-weighted imaging including mono-exponential, bi-exponential, diffusion kurtosis (DK) and fractional-order calculus (FROC) models in diagnosing prostate cancer (PCa) in transition zone (TZ) and distinguish the high-grade PCa [Gleason score (GS) ≥ 7] lesions from the total of low-grade PCa (GS ≤ 6) lesions and benign prostatic hyperplasia (BPH) in TZ.

METHODS

80 Patients with 103 lesions were included in this study. Nine metrics [including apparent diffusion coefficient (ADC) derived from mono-exponential model, slow diffusion coefficient (D_s), fast diffusion coefficient (D_f),, and f (the fraction of fast diffusion) from bi-exponential model; mean diffusivity (MD) and mean kurtosis (MK) from DK model; diffusion coefficient (D), fractional-order derivative in space (β), and spatial metric (μ) from FROC model] were calculated. Comparisons between BPH and PCa lesions as well as between clinically significant PCa (CsPCa) (GS ≥ 7, n = 31) and clinically insignificant lesions (Cins) (GS ≤ 6 and BPH, n = 72) of these metrics were conducted. Mann-Whitney U-test and receiver operating characteristic (ROC) analysis were used for statistical evaluations.

RESULTS

The areas under the ROC curve (AUC) values of β derived from FROC model were 0.778 and 0.853 in differentiating PCa from BPH and in differentiating CS (GS ≥ 7) from Cins (GS ≤ 6 and BPH), both were the highest compared to other metrics. The AUC value of β was significantly higher than that of ADC (P = 0.009) in differentiating CS from Cins, while the differentiation between BPH and PCa did not reach the statistical significance when comparing with ADC (P = 0.089).

CONCLUSION

Although no significant difference was found in distinguishing PCa from BPH, the metric β derived from FROC model was superior to other diffusion metrics in differentiation between CS and Cins in TZ.

Diagnostic Performance of PI-RADS v2, Proposed Adjusted PI-RADS v2 and Biparametric Magnetic Resonance Imaging for Prostate Cancer Detection: A Preliminary Study

Purpose: To evaluate the diagnostic performance of PI-RADS v2, proposed adjustments to PI-RADS v2 (PA PI-RADS v2) and biparametric magnetic resonance imaging (MRI) for prostate cancer detection. Methods: A retrospective cohort of 224 patients with suspected prostate cancer was included from January 2016 to November 2018. All the patients underwent a multi-parametric MR scan before biopsy. Two radiologists independently evaluated the MR examinations using PI-RADS v2, PA PI-RADS v2, and a biparametric MRI protocol, respectively. Receiver operating characteristic (ROC) curves for the three different protocols were drawn. Results: In total, 90 out of 224 cases (40.18%) were pathologically diagnosed as prostate cancer. The area under the ROC curves (AUC) for diagnosing prostate cancers by biparametric MRI, PI-RADS v2, and PA PI-RADS v2 were 0.938, 0.935, and 0.934, respectively. For cancers in the peripheral zone (PZ), the diagnostic sensitivity was 97.1% for PI-RADS v2/PA PI-RADS v2 and 96.2% for biparametric MRI. Moreover, the specificity was 84.0% for biparametric MRI and 58.0% for PI-RADS v2/PA PI-RADS v2. For cancers in the transition zone (TZ), the diagnostic sensitivity was 93.4% for PA PI-RADS v2 and 88.2% for biparametric MRI/PI-RADS v2. Furthermore, the specificity was 95.4% for biparametric MRI/PI-RADS v2 and 78.0% for PA PI-RADS v2. Conclusions: The overall diagnostic performance of the three protocols showed minimal differences. For lesions assessed as being category 3 using the biparametric MRI protocol, PI-RADS v2, or PA PI-RADS v2, it was thought prostate cancer detection could be improved. Attention should be paid to false positive results when PI-RADS v2 or PA PI-RADS v2 are used.

Impact of the Number of Cores on the Prostate Cancer Detection Rate in Men Undergoing in-Bore Magnetic Resonance Imaging-Guided Targeted Biopsies

OBJECTIVE

To determine the incremental detection rate of clinically significant prostate cancer (csPCa) provided by sequential cores during in-bore magnetic resonance imaging (MRI)-guided prostate biopsies.

METHODS

Single-center, retrospective interpretation of prospectively acquired data in men without previous diagnosis of csPCa who underwent in-bore MRI-guided prostate biopsy between May 2017 and December 2019. Endpoints included detection of csPCa (grade group [GG] ≥ 2) and rate of GG upgrade provided by additional cores. Descriptive statistics presented as mean and standard deviation for the continuous variables, and frequency and percentage for the categorical variables.

RESULTS

Four hundred and forty-three men with 747 lesions met eligibility criteria. Clinically significant prostate cancer was detected in 43.1% (322/747) of the biopsied lesions and GG 2 PCa or greater was identified by the first core in 78.3% (252/322) of them. On a per-core basis, cores 2, 3, 4, and 5 found new csPCa in 6% (42/744), 4% (26/719), 1% (2/137), and 0% (0/11) of the cases. Core biopsy 2, 3, 4, and 5 resulted in GG upgrade in 12% (91/744), 7% (49/719), 7% (9/137), and 0% (0/11) of the lesions, respectively. Each additional core was associated with a mean increase of 5 minutes in the duration of the biopsy.

CONCLUSIONS

In men undergoing in-bore MRI-guided prostate biopsies, 3 targeted cores per lesion provide an optimal trade-off between detection of clinically significant tumors and biopsy duration.

Novel ultrasound-based volume estimation of prostatic benign enlargement to improve decision-making on surgical approach

Aim:

To assess the precision of preoperative ultrasonography (US)-determined prostate volume and to propose formulas for improving it.

Methods:

This retrospective study comprised 155 consecutive men who underwent open prostatectomy for benign prostatic hyperplasia (BPH) between 2013 and 2019. Preoperative prostate volume was estimated by either abdominal US (AUS) (n = 92) or transrectal US (TRUS) (n = 63), and was compared with the weight of surgically enucleated tissue at a conversion rate of 1 ml (US) = 1 g tissue. Statistical analysis was conducted and a novel formula for prostate volume was constructed.

Results:

The median prostate volumes by AUS and TRUS were 140 ml [interquartile ratio (IQR) 111–182] and 108 ml (IQR 93–120), respectively. Enucleated tissue weight was lower than the AUS assessment by a median difference of 50 g (IQR 28.7–75.7; p < 0.001), and lower than the TRUS assessment by a median difference of 27 g, IQR 10–43, p < 0.001). Using a cutoff of 80 ml, 30 (33%) AUS patients and 23 (36%) TRUS patients underwent unneeded open procedures. Mathematical calculations revealed two formulas that significantly adjusted for the actual weight: 1.082*Age + 0.523*AUS − 53.845 for AUS and 0.138*age + 2.22*prostate-specific antigen + 0.453*TRUS + 11.682 for TRUS (p < 0.001). These formulas increased the overall US prostate volume accuracy from 65% to 85%.

Conclusion:

Assessment of prostate volume by US is imprecise for decision-making of whether to perform open simple prostatectomy for BPH. Our novel formulas may enhance stratification of patients with prostatic enlargement to a more optimal surgical approach. Future studies in larger cohorts are needed to substantiate our results.

Round table: arguments in supporting abbreviated or biparametric MRI of the prostate protocol

Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 update, in the attempt to improve clinical guidelines for multiparametric magnetic resonance imaging (mpMRI) of the prostate, has clear limitations. The role of dynamic contrast-enhanced sequences is not defined, precise guidance on the clinical management (biopsy or clinical surveillance) for score 3 lesions [equivocal for clinical significant prostate cancer (sPCa)] is not offered and criteria for lesions interpretation remain difficult and subjective. We report criteria and arguments in supporting the use of abbreviated or biparametric prostate MRI protocol in clinical practice for detection and management of PCa.

The effect of gadolinium-based contrast agent administration on magnetic resonance fingerprinting-based T1 relaxometry in patients with prostate cancer

Magnetic resonance fingerprinting (MRF) is a rapidly developing fast quantitative mapping technique able to produce multiple property maps with reduced sensitivity to motion. MRF has shown promise in improving the diagnosis of clinically significant prostate cancer but requires further validation as part of a prostate multiparametric (mp) MRI protocol. mpMRI protocol mandates the inclusion of dynamic contrast enhanced (DCE) imaging, known for its significant T1 shortening effect. MRF could be used to measure both pre- and post-contrast T1 values, but its utility must be assessed. In this proof-of-concept study, we sought to evaluate the variation in MRF T1 measurements post gadolinium-based contrast agent (GBCA) injection and the utility of such T1 measurements to differentiate peripheral and transition zone tumours from normal prostatic tissue. We found that the T1 variation in all tissues increased considerably post-GBCA following the expected significant T1 shortening effect, compromising the ability of MRF T1 to identify transition zone lesions. We, therefore, recommend performing MRF T1 prior to DCE imaging to maintain its benefit for improving detection of both peripheral and transition zone lesions while reducing additional scanning time. Demonstrating the effect of GBCA on MRF T1 relaxometry in patients also paves the way for future clinical studies investigating the added value of post-GBCA MRF in PCa, including its dynamic analysis as in DCE-MRF.

PI-RADS Versions 2 and 2.1: Interobserver Agreement and Diagnostic Performance in Peripheral and Transition Zone Lesions Among Six Radiologists

BACKGROUND. PI-RADS version 2.1 (v2.1) modifications primarily address transition zone (TZ) interpretation. The revisions also impact peripheral zone (PZ) interpretation, which has received less attention. OBJECTIVE. The purpose of this study was to compare interobserver agreement of PI-RADS version 2 (v2) and v2.1 in the prostate PZ and TZ and perform a pilot comparison of their diagnostic performance in the two zones. METHODS. Six radiologists with varying experience retrospectively assessed 80 prostate lesions (40 PZ, 40 TZ) on MRI in separate sessions for PI-RADS v2 and v2.1. Interobserver agreement was assessed using Conger kappa (κ). For 50 lesions with pathology data, average AUC for detecting clinically significant cancer was compared between versions using multireader multicase statistical methods. Error variance and covariance results informed post hoc power analysis. RESULTS. Interobserver agreement for PI-RADS category 4 or greater was higher for version 2.1 (κ = 0.64) than version 2 (κ = 0.51) in the PZ, but similar for version 2 (κ = 0.64) and version 2.1 (κ = 0.60) in the TZ. The PI-RADS v2.1 DWI descriptor "linear/wedge-shaped" had higher agreement than its predecessor version 2 descriptor "indistinct hypointense" (κ = 0.52 vs κ = 0.18) and yielded 14 more true-negative versus five more false-negative interpretations. The ADC signal descriptor "markedly hypointense," for which only version 2.1 provides a specific definition, had lower agreement in version 2.1 (κ = 0.26) than version 2 (κ = 0.52). Modified TZ T2-weighted category 2 descriptors in version 2.1 had fair agreement (κ = 0.21), and agreement for PI-RADS category 2 in the TZ was lower in version 2.1 (κ = 0.31) than version 2 (κ = 0.57). DWI upgraded a TZ lesion category from 2 to 3 in four patients, detecting two additional cancers. Average AUC was not different between versions 2 and 2.1 for the PZ (AUC, 0.81 vs 0.85; p = .24) or the TZ (AUC, 0.69 vs 0.69; p = .94), though among experienced readers AUC was higher for version 2.1 than version 2 for the PZ (0.91 vs 0.82; p = .001). Overall performance comparison had sufficient power (0.8) to detect a 0.085 difference in AUC. CONCLUSION. Interobserver agreement improved using PI-RADS v2.1 in the PZ but not the TZ. Diagnostic performance improved using version 2.1 only in the PZ for experienced readers. Specific version 2.1 modifications yielded mixed results. CLINICAL IMPACT. The impact of PI-RADS v2.1 in the PZ is notable given the emphasis on version 2.1 TZ modifications. The findings suggest areas in which additional modification could further improve interobserver agreement and performance.

Current Status of MRI and PET in the NCCN Guidelines for Prostate Cancer

Prostate cancer (PCa) represents a significant source of morbidity and mortality for men in the United States, with approximately 1 in 9 being diagnosed with PCa in their lifetime. The role of imaging in the evaluation of men with PCa has evolved and currently plays a central role in diagnosis, treatment planning, and evaluation of recurrence. Appropriate use of multiparametric MRI (mpMRI) and MRI-guided transrectal ultrasound (MR-TRUS) biopsy increases the detection of clinically significant PCa while decreasing the detection of clinically insignificant PCa. This process may help patients with clinically insignificant PCa avoid the adverse effects of unnecessary therapy. In the setting of a known PCa, patients with low-grade disease can be observed using active surveillance, which often includes a combination of prostate-specific antigen (PSA) testing, serial mpMRI, and, if indicated, follow-up systematic and targeted TRUS-guided tissue sampling. mpMRI can provide important information in the posttreatment setting, but PET/CT is creating a paradigm shift in imaging standards for patients with locally recurrent and metastatic PCa. This article examines the strengths and limitations of mpMRI for initial PCa diagnosis, active surveillance, recurrent disease evaluation, and image-guided biopsies, and the use of PET/CT imaging in men with recurrent PCa. The goal of this review is to provide a rational basis for current NCCN Clinical Practice Guidelines in Oncology for PCa as they pertain to the use of these advanced imaging modalities.

Prostate magnetic resonance imaging technique

Multiparametric magnetic resonance (MR) imaging of the prostate is an excellent tool to detect clinically significant prostate cancer, and it has widely been incorporated into clinical practice due to its excellent tissue contrast and image resolution. The aims of this article are to describe the prostate MR imaging technique for detection of clinically significant prostate cancer according to PI-RADS v2.1, as well as alternative sequences and basic aspects of patient preparation and MR imaging artifact avoidance.

MRI-directed high-frequency (29MhZ) TRUS-guided biopsies: initial results of a single-center study

OBJECTIVES

To evaluate the ability of high-frequency (29 MHz) transrectal micro-ultrasound (microUS) as a second-look examination after biparametric MRI (bp-MRI) and to reidentify focal lesions seen on diagnostic MRI and to detect new ones METHODS: A total of 118 consecutive men (mean age, 66 ± 13 [SD] years; range, 49-93 years) with a mean prostate-specific antigen level of 11 ± 19 (SD) ng/mL (range, 2-200 ng/mL) and at least one focal lesion (MRI+) with a score > 2 on bp-MRI were included. Of these, 79/118 (66.9%) were biopsy-naïve and 102/118 (86.5%) had non-suspicious rectal examination. All patients had MRI-directed microUS-guided biopsy using a 29-MHz transducer. All lesions visible on micro-ultrasound (microUS+) were targeted without image fusion, which was only used for MRI+/microUS- lesions. Significant prostate cancer (sPCa) was defined by a Gleason score ≥ 7 or a maximum cancer core length > 3 mm.

RESULTS

A total of 144 focal prostatic lesions were analyzed, including 114 (114/144, 79.2%) MRI+/microUS+ lesions, 13 MRI+/microUS- lesions (13/144, 9%), and 17 MRI-/microUS+ lesions (17/144, 11.8%). Significant PCa was detected in 70 MRI+/microUS+ lesions (70/114, 61.4%), in no MRI+/microUS- lesion (0/13, 0%), and in 4 MRI-/microUS+ lesions (4/17, 23.5%). The sensitivity and specificity of microUS on a per-patient and a per-lesion basis were 100% (95% CI, 84.9-100%) and 22.8% (95% CI, 12.5-35.8%) and 100% (95% CI, 85.1-100%) and 22.6% (95% CI, 12.3-36.2%), respectively.

CONCLUSION

MicroUS, as a second-look examination, may show promise to localize targets detected on bp-MRI.

KEY POINTS

• Used as a second-look examination, microUS-guided biopsies have a 100% detection rate of sCa originating in the PZ or lower third of the TZ, without microUS-MRI image fusion. • MicroUS results may provide additional information about lesions visible on MRI. • MicroUS may provide the ability to detect small PZ lesions undetected by bp-MRI.

Direct Comparison of PI-RADS Version 2 and 2.1 in Transition Zone Lesions for Detection of Prostate Cancer: Preliminary Experience

BACKGROUND

There appears to be less agreement in the identification of cancers in the transition zone (TZ), which is not as reliable as those in peripheral zone when using the Prostate Imaging Reporting and Data System (PI-RADS) version 2 (v2). In response to such shortcomings, the updated version 2.1 was introduced, which incorporated diffusion-weighted imaging (DWI) into category 2 and clarified lexicons.

PURPOSE

To compare the diagnostic performance for the detection of clinically significant TZ prostate cancers (csPCa) and interreader agreement between PI-RADS v2.1 and v2.

STUDY TYPE

Retrospective study.

POPULATION

In all, 142 patients, 201 TZ lesions.

FIELD STRENGTH/SEQUENCE

3.0T; T₂ -weighted image and DWI.

ASSESSMENT

Lesions were scored by three independent readers using PI-RADS v2 and v2.1.

STATISTICAL TESTS

The sensitivity and specificity at category ≥3 were compared between v2 and v2.1 using the generalized estimating equation model. Detection rates for csPCa of upgraded and downgraded lesions in the use of PI-RADS v2.1 from v2 were assessed. Interreader agreement was assessed using κ statistics.

RESULTS

PI-RADS v2.1 showed a higher sensitivity and specificity (94.5% and 60.9%) than v2 (91.8% and 56.3%) for category ≥3 lesions in the detection of csPCa, although not significantly. Of eight upgraded lesions from category 2 to 3 (2 + 1) with an incorporated DWI, 50% (4/8) were csPCa. This was significantly higher than category 2 lesions (4.4%; P = 0.003). No csPCa was detected among the 22.8% (46/201) downgraded lesions. There was a moderate interreader agreement for scores ≥3 (κ = 0.565) in v2.1, which was slightly higher than that for v2 (κ = 0.534), although not significantly.

DATA CONCLUSION

PI-RADS v2.1 provides moderate and comparable interreader agreement at category ≥3 than v2 in the TZ lesions. Upgraded lesions from category 2 to 3 demonstrated a higher detection rate of csPCa than category 2 lesions in v2.1.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:577-586.

Comparison of biparametric and multiparametric MRI in the diagnosis of prostate cancer

PURPOSE

To compare the diagnostic accuracy of biparametric MRI (bpMRI) and multiparametric MRI (mpMRI) for prostate cancer (PCa) and clinically significant prostate cancer (csPCa) and to explore the application value of dynamic contrast-enhanced (DCE) MRI in prostate imaging.

METHODS AND MATERIALS

This study retrospectively enrolled 235 patients with suspected PCa in our hospital from January 2016 to December 2017, and all lesions were histopathologically confirmed. The lesions were scored according to the Prostate Imaging Reporting and Data System version 2 (PI-RADS V2). The bpMRI (T2-weighted imaging [T2WI], diffusion-weighted imaging [DWI]/apparent diffusion coefficient [ADC]) and mpMRI (T2WI, DWI/ADC and DCE) scores were recorded to plot the receiver operating characteristic (ROC) curves. The area under the curve (AUC), accuracy, sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) for each method were calculated and compared. The patients were further stratified according to bpMRI scores (bpMRI ≥3, and bpMRI = 3, 4, 5) to analyse the difference in DCE MRI between PCa and non-PCa lesions (as well as between csPCa and non-csPCa).

RESULTS

The AUC values for the bpMRI and mpMRI protocols for PCa were comparable (0.790 [0.732-0.840] and 0.791 [0.733-0.841], respectively). The accuracy, sensitivity, specificity, PPV and NPV of bpMRI for PCa were 76.2, 79.5, 72.6, 75.8, and 76.6%, respectively, and the values for mpMRI were 77.4, 84.4, 69.9, 75.2, and 80.6%, respectively. The AUC values for the bpMRI and mpMRI protocols for the diagnosis of csPCa were similar (0.781 [0.722-0.832] and 0.779 [0.721-0.831], respectively). The accuracy, sensitivity, specificity, PPV and NPV of bpMRI for csPCa were 74.0, 83.8, 66.9, 64.8, and 85.0%, respectively; and 73.6, 87.9, 63.2, 63.2, and 87.8%, respectively, for mpMRI. For patients with bpMRI scores ≥3, positive DCE results were more common in PCa and csPCa lesions (both P = 0.001). Further stratification analysis showed that for patients with a bpMRI score = 4, PCa and csPCa lesions were more likely to have positive DCE results (P = 0.003 and P < 0.001, respectively).

CONCLUSION

The diagnostic accuracy of bpMRI is comparable with that of mpMRI in the detection of PCa and the identification of csPCa. DCE MRI is helpful in further identifying PCa and csPCa lesions in patients with bpMRI ≥3, especially bpMRI = 4, which may be conducive to achieving a more accurate PCa risk stratification. Rather than omitting DCE, we think further comprehensive studies are required for prostate MRI.

Detectability of prostate cancer in different parts of the gland with 3-Tesla multiparametric magnetic resonance imaging: correlation with whole-mount histopathology

BACKGROUND

We investigated whether the detectability of prostate cancer with 3-Tesla (3T) multiparametric magnetic resonance imaging (mpMRI) differs by tumor location.

METHODS

We identified 136 patients with prostate cancer who underwent 3-T mpMRI before prostatectomy at a single academic center. Two uroradiologists scored all MRIs with Prostate Imaging-Reporting and Data System version 2 (PI-RADS v2). A genitourinary pathologist mapped tumor foci from serial whole-mount radical prostatectomy sections. We assessed concordance of images with cancer sites. Tumor foci with Gleason score ≥  3 + 4 or volume ≥ 0.5 mL were considered significant.

RESULTS

A total of 122 foci in 106 cases were identified with mpMRI. Twenty-four were PI-RADS 3, 52 were 4, and 46 were 5. A total of 274 tumor foci were identified with whole-mount pathology. The sensitivity stratified by location to detect significant cancer with a PI-RADS cutoff value of 3 was 56.0% overall, 50.0% in the peripheral zone (PZ), 71.2% in the transitional zone (TZ), 62.4% anterior, 49.5% posterior, 42.0% apical, 63.6% in the midgland, and 43.8% in the gland base. In multivariate analysis, tumor location was not a significant predictor of identification by mpMRI. Tumor volume, Gleason score, and index tumor status were significantly associated with identification by mpMRI.

CONCLUSIONS

mpMRI detected the majority of high-grade and large cancers, but had low sensitivity in the PZ, posterior, and apex and base of the gland. The high prevalence of low-volume, low-Gleason score index tumors, as well as satellite tumors in those areas, accounted for the difference.

Similarities and differences between Likert and PIRADS v2.1 scores of prostate multiparametric MRI: a pictorial review of histology-validated cases

The UK National Institute for Health and Care Excellence (NICE) 2019 "Prostate cancer: diagnosis and management" guidelines have recommended that all patients suspected of prostate cancer undergo multiparametric magnetic resonance imaging (mpMRI) prior to biopsy. The Likert scoring system is advocated for mpMRI reporting based on multicentre studies that have demonstrated its effectiveness within the National Health Service (NHS). In recent years, there has been considerable drive towards standardised prostate reporting, which led to the development of "Prostate Imaging-Reporting And Data System" (PI-RADS). The PI-RADS system has been adopted by the majority of European countries and within the US. This paper reviews these systems indicating the similarities and specific differences that exist between PI-RADS and Likert assessment through a series of histologically proven clinical cases.

Diagnosis of Prostate Cancer by Use of MRI-Derived Quantitative Risk Maps: A Feasibility Study

OBJECTIVE. The purpose of this study was to develop a new quantitative image analysis tool for estimating the risk of cancer of the prostate by use of quantitative multiparametric MRI (mpMRI) metrics. MATERIALS AND METHODS. Thirty patients with biopsy-confirmed prostate cancer (PCa) who underwent preoperative 3-T mpMRI were included in the study. Quantitative mpMRI metrics-apparent diffusion coefficient (ADC), T2, and dynamic contrast-enhanced (DCE) signal enhancement rate (α)-were calculated on a voxel-by-voxel basis for the whole prostate and coregistered. A normalized risk value (0-100) for each mpMRI parameter was obtained, with high risk values associated with low T2 and ADC and high signal enhancement rate. The final risk score was calculated as a weighted sum of the risk scores (ADC, 40%; T2, 40%; DCE, 20%). Data from five patients were used as training set to find the threshold for predicting PCa. In the other 25 patients, any region with a minimum of 30 con-joint voxels (≈ 4.8 mm2) with final risk score above the threshold was considered positive for cancer. Lesion-based and sector-based analyses were performed by matching prostatectomyverified malignancy and PCa predicted with the risk analysis tool. RESULTS. The risk map tool had sensitivity of 76.6%, 89.2%, and 100% for detecting all lesions, clinically significant lesions (≥ Gleason 3 + 4), and index lesions, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value for PCa detection for all lesions in the sector-based analysis were 78.9%, 88.5%, 84.4%, and 84.1%, respectively, with an ROC AUC of 0.84. CONCLUSION. The risk analysis tool is effective for detecting clinically significant PCa with reasonable sensitivity and specificity in both peripheral and transition zones.

Interobserver Agreement and Positivity of PI-RADS Version 2 Among Radiologists with Different Levels of Experience

RATIONALE AND OBJECTIVES

To evaluate interobserver agreement of Prostate Imaging Reporting and Data System (PI-RADS) v2 category among radiologists with different levels of experience. The secondary objective was to evaluate the positivity for significant cancer among each category (splitting category 4 into two) and among different lesion sizes.

MATERIALS AND METHODS

Institutional review board and ethics comitee approved retrospective study. Eight radiologists with different levels of experienced in prostatic magnetic resonance imaging-two more experienced, four with intermediate experience, and two abdominal radiology fellows-interpreted 160 lesions. Reference standard was fusion-targeted biopsy. Percentage agreement, k coefficients, and analysis concordance were used.

RESULTS

Coefficient of concordance according to categories was 0.71 considering both zones, 0.72 for peripheral zone (PZ) and 0.44 for peripheral zone (TZ). Agreement for PI-RADS score of 3 or greater was 0.48 in PZ and 0.57 in TZ. Tumor positivity rates were 54.3% and 66.0% for PI-RADS 3 + 1 and 4 for PZ, respectively; and 25.0 and 49.2% for PI-RADS 3 + 1 and 4 for TZ, respectively (p < 0.001 in both analysis). Lesions <10, 10-14, and ≥15 mm had 55.3%, 74.6%, and 93.5% of positivity rates for cancer in PZ (p = 0.002 and <0.001) and 26.7%, 56.5%, and 59.6% in TZ, respectively (p = 0.245 and 0.632). Sensitivities, specificities, and accuracies of magnetic resonance imaging for prostate cancer using PI-RADS v2 were 76%, 72%, and 74% for PZ; and 76%, 69%, and 71% for TZ, respectively.

CONCLUSION

This study shows that PI-RADS v2 has overall good interobserver agreement among radiologists with different levels of experience. PI-RADS category 3 + 1 showed lower positivity rates for significant cancer compared to category 4. Lastly, lesions 10-14 mm has similar positivity rates compared to ≥15 mm for TZ lesions.

Revisiting quantitative multi-parametric MRI of benign prostatic hyperplasia and its differentiation from transition zone cancer

PURPOSE

This study investigates the multiparametric MRI (mpMRI) appearance of different types of benign prostatic hyperplasia (BPH) and whether quantitative mpMRI is effective in differentiating between prostate cancer (PCa) and BPH.

MATERIALS AND METHODS

Patients (n = 60) with confirmed PCa underwent preoperative 3T MRI. T2-weighted, multi-echo T2-weighted, diffusion weighted and dynamic contrast enhanced images (DCE) were obtained prior to undergoing prostatectomy. PCa and BPH (cystic, glandular or stromal) were identified in the transition zone and matched with MRI. Quantitative mpMRI metrics: T2, ADC and DCE-MRI parameters using an empirical mathematical model were measured.

RESULTS

ADC values were significantly lower (p < 0.001) in PCa compared to all BPH types and can differentiate between PCa and BPH with high accuracy (AUC = 0.87, p < 0.001). T2 values were significantly lower (p < 0.001) in PCa compared to cystic BPH only, while glandular (p = 0.27) and stromal BPH (p = 0.99) showed no significant difference from PCa. BPH mimics PCa in the transition zone on DCE-MRI evidenced by no significant difference between them. mpMRI values of glandular (ADC = 1.31 ± 0.22 µm²/ms, T2 = 115.7 ± 37.3 ms) and cystic BPH (ADC = 1.92 ± 0.43 µm²/ms, T2 = 242.8 ± 117.9 ms) are significantly different. There was no significant difference in ADC (p = 0.72) and T2 (p = 0.46) between glandular and stromal BPH.

CONCLUSIONS

Multiparametric MRI and specifically quantitative ADC values can be used for differentiating PCa and BPH, improving PCa diagnosis in the transition zone. However, DCE-MRI metrics are not effective in distinguishing PCa and BPH. Glandular BPH are not hyperintense on ADC and T2 as previously thought and have similar quantitative mpMRI measurements to stromal BPH. Glandular and cystic BPH appear differently on mpMRI and are histologically different.

Differentiating Transition Zone Cancers From Benign Prostatic Hyperplasia by Histogram Analysis of Apparent Diffusion Coefficient Maps With Standard and Ultrahigh b-value Diffusion-weighted MR Imaging

OBJECTIVE

To compare the diagnostic performance of standard and ultrahigh b-value Diffusion-weighted Imaging (DWI) using volumetric histogram analysis in differentiating transition zone (TZ) cancer from benign prostatic hyperplasia (BPH).

METHODS

57 TZ cancer and 61 BPH patients received standard (1000 s/mm) and ultrahigh b-value (2000 s/mm) DWI. The diagnostic ability of ADC histogram parameters derived from two DWI for differentiating TZ cancer from BPH was determined by receiver operating characteristic curve.

RESULTS

Median, minimum, the 10th, 25th percentile ADC in both ADC1000 and ADC2000 and skewness in ADC2000 had significant differences between TZ cancer and BPH (for all, P < 0.05).The 10th percentile ADC showed highest area under the ROC curve (AUC) in both ADC1000 and ADC2000.The 10th percentile ADC of ADC2000 showed significantly higher AUC than did ADC1000 (P = 0.0385).

CONCLUSIONS

The 10th percentile ADC obtained from ultrahigh b-value DWI performed better for differentiating TZ cancer from BPH.

Diagnostic Performance and Interobserver Consistency of the Prostate Imaging Reporting and Data System Version 2: A Study on Six Prostate Radiologists with Different Experiences from Half a Year to 17 Years

Background:

One of the main aims of the updated Prostate Imaging Reporting and Data System Version 2 (PI-RADS v2) is to diminish variation in the interpretation and reporting of prostate imaging, especially among readers with varied experience levels. This study aimed to retrospectively analyze diagnostic consistency and accuracy for prostate disease among six radiologists with different experience levels from a single center and to evaluate the diagnostic performance of PI-RADS v2 scores in the detection of clinically significant prostate cancer (PCa).

Methods:

From December 2014 to March 2016, 84 PCa patients and 99 benign prostatic shyperplasia patients who underwent 3.0T multiparametric magnetic resonance imaging before biopsy were included in our study. All patients received evaluation according to the PI-RADS v2 scale (1–5 scores) from six blinded readers (with 6 months and 2, 3, 4, 5, or 17 years of experience, respectively, the last reader was a reviewer/contributor for the PI-RADS v2). The correlation among the readers' scores and the Gleason score (GS) was determined with the Kendall test. Intra-/inter-observer agreement was evaluated using κ statistics, while receiver operating characteristic curve and area under the curve analyses were performed to evaluate the diagnostic performance of the scores.

Results:

Based on the PI-RADS v2, the median κ score and standard error among all possible pairs of readers were 0.506 and 0.043, respectively; the average correlation between the six readers' scores and the GS was positive, exhibiting weak-to-moderate strength (r = 0.391, P = 0.006). The AUC values of the six radiologists were 0.883, 0.924, 0.927, 0.932, 0.929, and 0.947, respectively.

Conclusion:

The inter-reader agreement for the PI-RADS v2 among the six readers with different experience is weak to moderate. Different experience levels affect the interpretation of MRI images.

Prospective comparison of a fast 1.5-T biparametric with the 3.0-T multiparametric ESUR magnetic resonance imaging protocol as a triage test for men at risk of prostate cancer

OBJECTIVE

To compare prospectively the diagnostic performance of a biparametric (T2-weighted imaging [T2WI] and diffusion-weighted imaging [DWI]) 1.5-T fast magnetic resonance imaging (fMRI) protocol with the standard 3.0-T multiparametric MRI (mpMRI) protocol of the European Society of Urological Imaging (ESUR) in men referred for a prostate biopsy.

PATIENTS AND METHODS

Ninety patients with a prostate cancer (PCa) risk of ≥10% according to the SWOP calculator 4 underwent first fMRI and then the reference mpMRI. Patients with Prostate Imaging Reporting and Data System (PI-RADS) v.2 lesions ≥3/5 on the mpMRI were scheduled for MRI/ultrasonography (US) fusion-guided prostate biopsy. Performance of fMRI was assessed using receiver-operating characteristic curve analysis and mpMRI as reference. Calculation of inter-technique agreement on PI-RADS v.2 score by Cohen's κ.

RESULTS

The diagnostic accuracy of fMRI shown by the lesion-based analysis was excellent: area under the curve (AUC) 0.961 (P < 0.001), sensitivity 95%, specificity 97%, positive predictive value (PPV) 99%, negative predictive value (NPV) 89%. The patient-based analysis showed an AUC for fMRI of 0.975 (P < 0.001), a sensitivity of 98%, a specificity of 97%, a PPV of 98% and an NPV of 97%. Agreement on the PI-RADS score between both protocols was found to be good (κ = 0.78 [0.57; 0.99]); fMRI missing PI-RADS 4 lesions in three patients. Biopsy results showed no cancer in two patients (two cores per nodule) and Gleason 6 cancer in one patient. There was only one false-positive fMRI, with a PI-RADS score of 4, whose biopsy was negative.

CONCLUSION

In the triage of men with a high risk of PCa for prostate biopsy, an f MRI protocol (1.5-T magnet, T2WI + DWI, <15 min) may safely replace the traditional ESUR 3.0-T mpMRI protocol, saving time and contrast injection.

The diagnostic accuracy of high b-value diffusion- and T2-weighted imaging for the detection of prostate cancer: a meta-analysis

Purpose

This study aims to investigate the role of diffusion-weighted imaging (DWI) and T₂-weighted imaging (T₂WI) in combination for the detection of prostate cancer, specifically assessing the role of high b-values (> 1000 s/mm²), with a systematic review and meta-analysis of the existing published data.

Methods

The electronic databases MEDLINE, EMBASE, and OpenSIGLE were searched between inception and September 1, 2017. Eligible studies were those that reported the sensitivity and specificity of DWI and T₂WI for the diagnosis of prostate cancer by visual assessment using a histopathologic reference standard. The QUADAS-2 critical appraisal tool was used to assess the quality of included studies. A meta-analysis with pooling of sensitivity, specificity, likelihood, and diagnostic odds ratios was undertaken, and a summary receiver-operating characteristics (sROC) curve was constructed. Predetermined subgroup analysis was also performed.

Results

Thirty-three studies were included in the final analysis, evaluating 2949 patients. The pooled sensitivity and specificity were 0.69 (95% CI 0.68–0.69) and 0.84 (95% CI 0.83–0.85), respectively, and the sROC AUC was 0.84 (95% CI 0.81–0.87). Subgroup analysis showed significantly better sensitivity with high b-values (> 1000 s/mm²). There was high statistical heterogeneity between studies.

Conclusion

The diagnostic accuracy of combined DWI and T₂WI is good with high b-values (> 1000 s/mm²) seeming to improve overall sensitivity while maintaining specificity. However, further large-scale studies specifically looking at b-value choice are required before a categorical recommendation can be made.

Electronic supplementary material

The online version of this article (10.1007/s00261-017-1400-4) contains supplementary material, which is available to authorized users.

Online Interactive Case-Based Instruction in Prostate Magnetic Resonance Imaging Interpretation Using Prostate Imaging and Reporting Data System Version 2: Effect for Novice Readers

PURPOSE

To assess the effect on reader performance of an interactive case-based online tutorial for prostate magnetic resonance imaging (MRI) interpretation using Prostate Imaging and Reporting Data System (PI-RADS).

METHODS

An educational website was developed incorporating scrollable multiparametric prostate MRI examinations with annotated solutions based on PI-RADS version 2. Three second-year radiology residents evaluated a separate set of 60 prostate MRI examinations both before and after review of the online case material, identifying and scoring dominant lesions. These 60 examinations included 30 benign cases and 30 cases with a dominant lesion demonstrating Gleason score ≥3 + 4 tumor on fusion-targeted biopsy. The readers' pooled performance was compared between the 2 sessions using logistic regression and Wilcoxon signed rank tests.

RESULTS

All readers completed the online material within four-hours. Review of the online material significantly improved sensitivity (from 57.8%-73.3%, P = 0.003) and negative predictive value (from 69.2%-78.2%, P = 0.049), but not specificity (from 70.0%-67.8%, P = 0.692) or positive predictive value (from 59.6%-64.7%, P = 0.389). Reader confidence (1-10 scale; 10 = maximal confidence) also improved significantly (from 5.6 ± 2.7 to 6.3 ± 2.6, P = 0.026). However, accuracy of assigned PI-RADS scores did not improve significantly (from 45.5%-53.3%, P = 0.149).

CONCLUSION

An online interactive case-based website in prostate MRI interpretation improved novice readers' sensitivity and negative predictive value for tumor detection, as well as readers' confidence. This online material may serve as a resource complementing existing traditional methods of instruction by providing a more flexible educational experience among a larger volume of learners. However, further more targeted educational initiatives regarding the proper application of PI-RADS remain warranted.

Differentiation of prostate cancer and stromal hyperplasia in the transition zone with histogram analysis of the apparent diffusion coefficient

Background Prostate cancer and stromal hyperplasia (SH) in the transition zone (TZ) are difficult to discriminate by conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI). Purpose To investigate the apparent diffusion coefficient (ADC) of prostate cancer and SH in the TZ with histogram analysis and the ability of ADC metrics to differentiate between these two tissues. Material and Methods Thirty-three cancer and 29 SH lesions in the TZ of 54 patients undergoing preoperative DWI (b-value 0, 1000 s/mm²) were analyzed. All the lesions on the MR images were localized based on histopathologic correlations. The 10th, 25th, and 50th percentiles, and the mean ADC values were calculated for the two tissues and compared. The efficiencies of the 10th, 25th, and 50th ADC percentiles in differentiating the two tissues were compared with that of the mean ADC with receiver operating characteristic (ROC) analysis. Results The 10th, 25th, and 50th percentiles and mean ADC values (×10^-3 mm²/s) were 0.86 ± 0.15, 0.89 ± 0.16, 0.94 ± 0.16, and 1.03 ± 0.17 in SH and 0.64 ± 0.12, 0.69 ± 0.12, 0.72 ± 0.16, and 0.83 ± 0.15 in TZ cancer, respectively. The parameters were all significantly lower in cancer than SH. The 10th ADC percentile yielded an area under the ROC curve (AUC) of 0.87 for the differentiation of carcinomas from SH, which was higher than the mean ADC (0.80) ( P < 0.05), and the AUCs of the 25th (0.82) and 50th (0.83) percentiles exhibited no differences from those of the mean ADC ( P > 0.05). Conclusion Histogram analysis of ADC values may potentially improve the differentiation of prostate cancer from SH in the TZ.

Multiparametric magnetic resonance imaging for transition zone prostate cancer: essential findings, limitations, and future directions

OBJECTIVE

Review the multiparametric MRI (mpMRI) findings of transition zone (TZ) prostate cancer (PCa) using T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) MRI and to integrate mpMRI findings with clinical history, laboratory values, and histopathology.

CONCLUSION

TZ prostate tumors are challenging to detect clinically and at MRI. mpMRI using the combination of sequences has the potential to improve accuracy of TZ cancer detection and staging.

An update of pitfalls in prostate mpMRI: a practical approach through the lens of PI-RADS v. 2 guidelines

Objectives

The aim of the current report is to provide an update in the imaging interpretation of prostate cancer on multiparametric magnetic resonance imaging (mpMRI), with a special focus on how to discriminate pathological tissue from the most common pitfalls that may be encountered during daily clinical practice using the Prostate Imaging Reporting and Data System (PI-RADS) version 2 guidelines.

Methods

All the cases that are shown in this pictorial review comply with the European Society of Urogenital Radiology (ESUR) guidelines for technical mpMRI requirements.

Results

Despite the standardised manner to report mpMRI (PI-RADS v. 2), some para-physiologic appearances of the prostate can mimic cancer. As such, it is crucial to be aware of these pitfalls, in order to avoid the under/overestimation of prostate cancer.

Conclusions

A detailed knowledge of normal and abnormal findings in mpMRI of the prostate is pivotal for an accurate management of the wide spectrum of clinical scenarios that radiologists may encounter during their daily practice.

Teaching Points

• Some para-physiologic appearances of the prostate may mimic cancer.

• Knowledge of normal and abnormal findings in prostate mpMRI is pivotal.

• Any radiologist involved in prostate mpMRI reporting should be aware of pitfalls.

Accuracy of dynamic contrast-enhanced magnetic resonance imaging in the diagnosis of prostate cancer: systematic review and meta-analysis

The goals of this meta-analysis were to assess the effectiveness of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in patients with prostate carcinoma (PCa) and to explore the risk profiles with the highest benefit. Systematic electronic searched were conducted in database. We used patient-based and biopsy-based pooled weighted estimates of the sensitivity, specificity, and a summary receiver operating characteristic (SROC) curve for assessing the diagnostic performance of DCE. We performed direct and indirect comparisons of DCE and other methods of imaging. A total of 26 articles met the inclusion criteria for the analysis. DCE-MRI pooled sensitivity was 0.53 (95% CI 0.39 to 0.67), with a specificity of 0.88 (95% CI 0.83 to 0.92) on whole gland. The peripheral zone pooled sensitivity was 0.70 (95% CI 0.46 to 0.86), with a specificity of 0.88 (95% CI 0.76 to 0.94). Compared with T2-weighted imaging (T2WI), DCE was statistically superior to T2. In conclusion, DCE had relatively high specificity in detecting PCa but relatively low sensitivity as a complementary functional method. DCE-MRI might help clinicians exclude cases of normal tissue and serve as an adjunct to conventional imaging when seeking to identify tumor foci in patients with PCa.

Head-To-Head Comparison Between High- and Standard-b-Value DWI for Detecting Prostate Cancer: A Systematic Review and Meta-Analysis

OBJECTIVE

The purpose of this study was to perform a head-to-head comparison between high-b-value (> 1000 s/mm²) and standard-b-value (800-1000 s/mm²) DWI regarding diagnostic performance in the detection of prostate cancer.

MATERIALS AND METHODS

The MEDLINE and EMBASE databases were searched up to April 1, 2017. The analysis included diagnostic accuracy studies in which high- and standard-b-value DWI were used for prostate cancer detection with histopathologic examination as the reference standard. Methodologic quality was assessed with the revised Quality Assessment of Diagnostic Accuracy Studies tool. Sensitivity and specificity of all studies were calculated and were pooled and plotted in a hierarchic summary ROC plot. Meta-regression and multiple-subgroup analyses were performed to compare the diagnostic performances of high- and standard-b-value DWI.

RESULTS

Eleven studies (789 patients) were included. High-b-value DWI had greater pooled sensitivity (0.80 [95% CI, 0.70-0.87]) (p = 0.03) and specificity (0.92 [95% CI, 0.87-0.95]) (p = 0.01) than standard-b-value DWI (sensitivity, 0.78 [95% CI, 0.66-0.86]); specificity, 0.87 [95% CI, 0.77-0.93] (p < 0.01). Multiple-subgroup analyses showed that specificity was consistently higher for high- than for standard-b-value DWI (p ≤ 0.05). Sensitivity was significantly higher for high- than for standard-b-value DWI only in the following subgroups: peripheral zone only, transition zone only, multiparametric protocol (DWI and T2-weighted imaging), visual assessment of DW images, and per-lesion analysis (p ≤ 0.04).

CONCLUSION

In a head-to-head comparison, high-b-value DWI had significantly better sensitivity and specificity for detection of prostate cancer than did standard-b-value DWI. Multiple-subgroup analyses showed that specificity was consistently superior for high-b-value DWI.