Multiparametric magnetic resonance imaging: Current role in prostate cancer management

Prospective analysis of the diagnostic accuracy of digital rectal examination and magnetic resonance imaging for T staging of prostate cancer

Background

Accurate staging of prostate cancer (PCa) is the basis for the risk stratification to select targeted treatment. Therefore, this study aimed to compare the diagnostic accuracy rates of magnetic resonance imaging (MRI) and digital rectal examination (DRE) for preoperative T staging of potentially resectable PCa.

Methods

From March 2021 to March 2022, patients with PCa with T staging by prostate biopsy were included. All examinations used postoperative histopathologic T staging as the reference standard. All patients underwent DRE and MRI before the puncture. Two blinded urologists and radiologists independently evaluated DRE and MRI, respectively. Before the examination, patients were then divided into early- (T1, T2) and late-(T3, T4) stage cancer. Analysis of a paired sample sign test was performed to determine differences between DRE and MRI.

Results

A total of 136 study participants with PCa were evaluated histopathologically, of whom 71% (97/136) and 29% (39/136) were at the early- and late-stage cancer, respectively. MRI had a significantly higher accuracy (91.9% vs. 76.5%, P < 0.001) compared with DRE. Further, MRI showed a higher sensitivity than DRE to diagnose early PCa (92.8% vs. 74.2%; P < 0.001). However, the specificity was not significantly different between them (89.7% vs. 82.1%; P = 0.375). Area under the curve (receiver operating curve) values were calculated as 0.78 ± 0.038 (95% confidence interval [CI], 0.71-0.86), 0.91 ± 0.028 (95% CI, 0.86-0.97), and 0.872 ± 0.028 (95% CI, 0.80-0.92) for DRE-, MRI-, MRI + DRE-based PCa predictions, respectively. The prediction performance of MRI was better than that of DRE (DeLong test, z = 3.632, P = 0.0003) and MRI + DRE (DeLong test, z = 3.715, P = 0.0002).

Conclusion

For resectable PCa, the diagnostic potential of MRI in assessing the T stage was higher than that of DRE. However, DRE is still valuable, especially for patients with locally advanced PCa.

Impact of Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography on the Therapeutic Decision of Prostate Carcinoma Primary Staging: A Retrospective Analysis at the Brazilian National Public Health System

BACKGROUND

Prostate cancer (PCa) is the most common malignant tumor in males and conventional imaging does not provide accurate primary staging. Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) presents superior performance and strongly affects therapeutic choice.

OBJECTIVE

The aim of this study was to evaluate the impact of PSMA PET, compared with conventional imaging methods, on the therapeutic approach in primary staging scenarios in patients with PCa treated at the Brazilian National Public Health System.

METHODS

Overall, 35 patients diagnosed with PCa were evaluated using PSMA after conventional staging imaging with multiparametric magnetic resonance (MMR) and/or total abdominal computed tomography (CT) scan and bone scintigraphy (BS). The PCa extension identified by PET was compared with conventional imaging; staging changes and the management impact were then determined. PET comparison with conventional imaging, staging, and decision-making changes was analyzed using descriptive statistics.

RESULTS

PET revealed local disease (LD) in 15 (42.9%) patients, seminal vesicle invasion (SVI) in 5 (14.3%) patients, pelvic nodal impairment (PNI) in 7 (20%) patients, pelvic and distant nodes in 3 (8.6%) patients, pelvic nodes and bone metastasis in 4 (11.4%) patients, and pelvic and distant nodes and bone metastasis in 1 (2.8%) patient. Staging changes were observed in 60% of patients, with downstaging predominance (76.2%). Volume increase was identified in 11 (31.4%) patients (only 4 related to upstaging, 36.4%). The board changed management decisions for 60% of the patients. The main limitations of this study were the sample size and its retrospective nature.

CONCLUSIONS

PSMA findings changed the management decisions in more than half of the patients, which made the majority eligible for locoregional treatment and avoided unnecessary procedures in the systemic disease scenario.

Multiparametric MRI is not sufficient for prostate cancer staging: A single institutional experience validated by a multi-institutional regional collaborative

OBJECTIVE

Multiparametric magnetic resonance imaging (mpMRI) has been increasingly utilized in prostate cancer (CaP) diagnosis and staging. While Level 1 data supports MRI utility in CaP diagnosis, there is less data on staging utility. We sought to evaluate the real-world accuracy of mpMRI in staging localized CaP.

MATERIALS AND METHODS

Men who underwent radical prostatectomy (RP) for CaP in 2021 at our institution were identified. Sensitivity, specificity, positive predictive value and negative predictive value of mpMRI in predicting pT2N0 organ confined disease , extracapsular extension , seminal vesicle invasion , lymph node involvement, and bladder neck invasion were evaluated. Associations between MRI accuracy and AUA risk stratification (AUA RS), MRI institution (MRI-I), MRI strength (1.5 vs. 3T) (MRI-S), and MRI timing (MRI-T) were assessed. These analyses were repeated using Pennsylvania Urologic Regional Collaborative (PURC) data.

RESULTS

Institutional and community mpMRI CaP staging data demonstrated poor sensitivity (2.9%-49.2%% vs. 16.8%-24.4%), positive predictive value (40%-100% vs. 35.8%-68.2%), and negative predictive value (56.3%-94.3% vs. 68.4%-96.2%) in predicting surgical pathologic features - in contrast, specificity (89.1%-100% vs. 93.9%-98.6%) was adequate. mpMRI accuracy for extracapsular extension, seminal vesicle invasion, and lymph node involvement was significantly (p < 0.001) associated with AUA RS. There was no association between mpMRI accuracy and MRI-I, MRI-S, and MRI-T.

CONCLUSION

Despite enthusiasm for its use, in a real-world setting, mpMRI appears to be a poor staging study for localized CaP and is unreliable as the sole means of staging patients prior to prostatectomy. mpMRI should be used cautiously as a staging tool for CaP, and should be interpreted considering individual patient risk strata.

Effects of dynamic contrast enhancement on transition zone prostate cancer in Prostate Imaging Reporting and Data System Version 2.1

BACKGROUND

The aim of the study was to analyse the effects of dynamic contrast enhanced (DCE)-MRI on transitional-zone prostate cancer (tzPCa) and clinically significant transitional-zone prostate cancer (cs-tzPCa) in Prostate Imaging Reporting and Data System (PI-RADS) Version 2.1.

PATIENTS AND METHODS

The diagnostic efficiencies of T2-weighted imaging (T2WI) + diffusion-weighted imaging (DWI), T2WI + dynamic contrast-enhancement (DCE), and T2WI + DWI + DCE in tzPCa and cs-tzPCa were compared using the score of ≥ 4 as the positive threshold and prostate biopsy as the reference standard.

RESULTS

A total of 425 prostate cases were included in the study: 203 cases in the tzPCa group, and 146 in the cs-tzPCa group. The three sequence combinations had the similar areas under the curves in diagnosing tzPCa and cs-tzPCa (all P < 0.05). The sensitivity of T2WI + DCE and T2WI + DWI + DCE (84.7% and 85.7% for tzPCa; 88.4% and 89.7% for cs-tzPCa, respectively) in diagnosing tzPCa and cs-tzPCa was significantly greater than that of T2WI + DWI (79.3% for tzPCa; 82.9% for cs-tzPCa). The specificity of T2WI + DWI (86.5% for tzPCa; 74.9% for cs-tzPCa) were significantly greater than those of T2WI + DCE and T2WI + DWI + DCE (68.0% and 68.5% for tzPCa; 59.1% and 59.5% for cs-tzPCa, respectively) (all P > 0.05). The diagnostic efficacies of T2WI + DCE and T2WI + DWI + DCE had no significant differences (all P < 0.05).

CONCLUSIONS

DCE can improve the sensitivity of diagnosis for tzPCa and cs-tzPCa, and it is useful for small PCa lesion diagnosis.

Biparametric MRI-based radiomics classifiers for the detection of prostate cancer in patients with PSA serum levels of 4∼10 ng/mL

Purpose

To investigate the predictive performance of the combined model by integrating clinical variables and radiomic features for the accurate detection of prostate cancer (PCa) in patients with prostate-specific antigen (PSA) serum levels of 4-10 ng/mL.

Methods

A retrospective study of 136 males (mean age, 67.3 ± 8.4 years) with Prostate Imaging-Reporting and Data System (PI-RADS) v2.1 category ≤3 lesions and PSA serum levels of 4-10 ng/mL were performed. All patients underwent multiparametric MRI at 3.0T and transrectal ultrasound-guided systematic prostate biopsy in their clinical workup. Radiomic features were extracted from axial T2-weighted images (T2WI) and apparent diffusion coefficient (ADC) maps of each patient using PyRadiomics. Pearson correlation coefficient (PCC) and recursive feature elimination (RFE) were implemented to identify the most significant radiomic features. Independent clinic-radiological factors were identified via univariate and multivariate regression analyses. Seven machine-learning algorithms were compared to construct a single-layered radiomic score (ie, radscore) and multivariate regression analysis was applied to construct the fusion radscore. Finally, the radiomic nomogram was further developed by integrating useful clinic-radiological factors and fusion radscore using multivariate regression analysis. The discriminative power of the nomogram was evaluated by area under the curve (AUC), DeLong test, calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC).

Results

The transitional zone-specific antigen density was identified as the only independent clinic-radiological factor, which yielded an AUC of 0.592 (95% confidence interval [CI]: 0.527-0.657). The ADC radscore based on six features and Naive Bayes achieved an AUC of 0.779 (95%CI: 0.730-0.828); the T2WI radscore based on 13 features and Support Vector Machine yielded an AUC of 0.808 (95%CI: 0.761-0.855). The fusion radscore obtained an improved AUC of 0.844 (95%CI: 0.801-0.887), which was higher than the single-layered radscores (both P<0.05). The radiomic nomogram achieved the highest value among all models (all P<0.05), with an AUC of 0.872 (95%CI: 0.835-0.909). Calibration curve showed good agreement and DCA together with CIC confirmed the clinical benefits of the radiomic nomogram.

Conclusion

The radiomic nomogram holds the potential for accurate and noninvasive identification of PCa in patients with PI-RADS ≤3 lesions and PSA of 4-10 ng/mL, which could reduce unnecessary biopsy.

Comparison between biparametric and multiparametric MRI diagnosis strategy for prostate cancer in the peripheral zone using PI-RADS version 2.1

PURPOSE

To compare and analyse the diagnostic value of PI-RADS v2.1 when used with biparametric MRI (bpMRI) versus multiparametric MRI (mpMRI), DWI versus T2WI to detect peripheral-zone prostate cancer (pzPCa) and clinically significant peripheral-zone prostate cancer (cs-pzPCa).

METHODS

The diagnostic efficiencies of mpMRI and bpMRI as well as DWI and T2WI in pzPCa and cs-pzPCa were compared using a PI-RADS score of ≥ 4 as the positive threshold and prostate biopsy and radical prostatectomy as the reference standards.

RESULTS

A total of 307 prostate cases were included in the study, including 142 in the non-pzPCa group, 165 in the pzPCa group, and 130 in the cs-pzPCa group. The AUCs of mpMRI and bpMRI were 0.717 and 0.733 (P = 0.317), respectively, for the diagnosis of pzPCa (sensitivities: 89.1% and 81.8%; specificities: 54.2% and 64.8%, both P < 0.001) and 0.594 and 0.602 (P = 0.756), respectively, for the diagnosis of cs-pzPCa (sensitivities: 93.1% and 86.2%, P = 0.004; specificities: 25.7% and 34.3%, P = 0.250). The AUCs of DWI and T2WI were 0.733 and 0.749 (P = 0.308), respectively, for the diagnosis of pzPCa (sensitivities: 81.8% and 84.2%; specificities: 64.8% and 66.2%, both P > 0.05) and 0.602 and 0.581 (P = 0.371), respectively, for the diagnosis of cs-pzPCa (sensitivities: 86.2% and 87.7%; specificities: 34.3% and 28.6%, both P > 0.05).

CONCLUSION

mpMRI and bpMRI as well as DWI and T2WI using PI-RADS v2.1 exhibited similar diagnostic efficiency in pzPCa and cs-pzPCa.

Prediction of clinically significant prostate cancer with a multimodal MRI-based radiomics nomogram

Objective

To develop and validate a multimodal MRI-based radiomics nomogram for predicting clinically significant prostate cancer (CS-PCa).

Methods

Patients who underwent radical prostatectomy with pre-biopsy prostate MRI in three different centers were assessed retrospectively. Totally 141 and 60 cases were included in the training and test sets in cohort 1, respectively. Then, 66 and 122 cases were enrolled in cohorts 2 and 3, as external validation sets 1 and 2, respectively. Two different manual segmentation methods were established, including lesion segmentation and whole prostate segmentation on T2WI and DWI scans, respectively. Radiomics features were obtained from the different segmentation methods and selected to construct a radiomics signature. The final nomogram was employed for assessing CS-PCa, combining radiomics signature and PI-RADS. Diagnostic performance was determined by receiver operating characteristic (ROC) curve analysis, net reclassification improvement (NRI) and decision curve analysis (DCA).

Results

Ten features associated with CS-PCa were selected from the model integrating whole prostate (T2WI) + lesion (DWI) for radiomics signature development. The nomogram that combined the radiomics signature with PI-RADS outperformed the subjective evaluation alone according to ROC analysis in all datasets (all p&lt;0.05). NRI and DCA confirmed that the developed nomogram had an improved performance in predicting CS-PCa.

Conclusions

The established nomogram combining a biparametric MRI-based radiomics signature and PI-RADS could be utilized for noninvasive and accurate prediction of CS-PCa.

Multiparametric transrectal ultrasound for the diagnosis of peripheral zone prostate cancer and clinically significant prostate cancer: novel scoring systems

Background

To evaluate the diagnostic performance of multiparametric transrectal ultrasound (TRUS) and to design diagnostic scoring systems based on four modes of TRUS to predict peripheral zone prostate cancer (PCa) and clinically significant prostate cancer (csPCa).

Methods

A development cohort involved 124 nodules from 116 patients, and a validation cohort involved 72 nodules from 67 patients. Predictors for PCa and csPCa were extracted to construct PCa and csPCa models based on regression analysis of the development cohort. An external validation was performed to assess the performance of models using area under the curve (AUC). Then, PCa and csPCa diagnostic scoring systems were established to predict PCa and csPCa. The diagnostic accuracy was compared between PCa and csPCa scores and PI-RADS V2, using receiver operating characteristics (ROC) and decision curve analysis (DCA).

Results

Regression models were established as follows: PCa = − 8.284 + 4.674 × Margin + 1.707 × Adler grade + 3.072 × Enhancement patterns + 2.544 × SR; csPCa = − 7.201 + 2.680 × Margin + 2.583 × Enhancement patterns + 2.194 × SR. The PCa score ranged from 0 to 6 points, and the csPCa score ranged from 0 to 3 points. A PCa score of 5 or higher and a csPCa score of 3 had the greatest diagnostic performance. In the validation cohort, the AUC for the PCa score and PI-RADS V2 in diagnosing PCa were 0.879 (95% confidence interval [CI] 0.790–0.967) and 0.873 (95%CI 0.778–0.969). For the diagnosis of csPCa, the AUC for the csPCa score and PI-RADS V2 were 0.806 (95%CI 0.700–0.912) and 0.829 (95%CI 0.727–0.931).

Conclusions

The multiparametric TRUS diagnostic scoring systems permitted better identifications of peripheral zone PCa and csPCa, and their performances were comparable to that of PI-RADS V2.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12894-022-01013-8.

Safety and Diagnostic Yield of 68Ga Prostate-specific Membrane Antigen PET/CT Guided Robotic-assisted Transgluteal Prostatic Biopsy

Background Transrectal US-guided biopsy with or without MRI fusion is performed for diagnosing prostate cancer (PCa) but has limitations. Gallium 68 (⁶⁸Ga) prostate-specific membrane antigen (PSMA) PET/CT-guided targeted biopsy has the potential to improve diagnostic yield of PCa. Purpose To evaluate the safety and diagnostic yield of ⁶⁸Ga PSMA PET/CT-guided, robotic-arm assisted transgluteal prostatic biopsy. Materials and Methods In this single-center nonrandomized prospective trial, participants with a clinical suspicion of PCa (serum prostate-specific antigen level > 4 ng/mL) were recruited from January 2019 to September 2020. After whole-body ⁶⁸Ga PSMA PET/CT, participants with PSMA-avid intraprostatic lesions underwent PET-guided transgluteal biopsy by using an automated robotic arm. To assess safety and diagnostic yield, procedure-related complications and histopathologic results were documented. Pain during the procedure was scored by a visual analog scale. Descriptive statistics were applied; qualitative variables were reported in percentages. Results Seventy-eight participants (mean age, 66 years ± 7 [standard deviation]; 36 participants [46%] with prior negative results at transrectal US-guided biopsy) were enrolled. Fifty-six (72%) participants had PSMA-avid lesions (prior negative results at transrectal US-guided biopsy in 22 of 56 [39%]) and underwent targeted biopsy. PCa was confirmed in 54 of 56 (96%) participants, and clinically significant PCa (Gleason score ≥ 7) was confirmed in 24 of 54 (44%). Two participants had nonrepresentative samples that required rebiopsy. All participants experienced pain during the procedure, mild (median visual analog scale score, 1; interquartile range, 1-2) in 36 of 56 (64%) and moderate (median visual analog scale score, 5; interquartile range, 5-6) in 20 of 56 (36%). Postprocedure complications were noted in five of 56 (9%) participants and were minor (hematuria, four participants; hematospermia, one participant; and gluteal pain, two participants). No participant developed a postprocedural infection. Conclusion Transgluteal prostate-specific membrane antigen (PSMA) PET/CT-guided, robotic-targeted prostatic biopsy is safe with a high diagnostic yield of prostate cancer for PSMA-avid lesions. Clinical trial registration no. NCT05022576 © RSNA, 2022.

Imaging modalities for monitoring acute therapeutic effects after near-infrared photoimmunotherapy in vivo

Near-infrared photoimmunotherapy (NIR-PIT) induces immediate cell death after irradiation with near-infrared (NIR) light. Acute therapeutic effects caused by NIR-PIT before the change of tumor size is essential to be monitored by imaging modalities. We summarized and compared the imaging modalities for evaluating acute therapeutic effects after NIR-PIT, and aimed to provide a better understanding of advantages and disadvantages of each modality for evaluation in clinical applications. Fluorescence imaging and fluorescence lifetime, with high resolution, remains high accumulation of fluorescence dyes in the normal organs. High resolution and noninvasiveness are the major advantages of magnetic resonance imaging, while ¹⁸ F-fluorodeoxyglucose positron emission tomography provides information about the glucose metabolism. Optical coherence tomography provided more information about the blood vessels. Thus, all of the imaging modalities play an important role in evaluating acute therapeutic effects after NIR-PIT. Clinicians should choose suitable modality according to specific purpose and conditions in clinical application.

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.

Comparison of PI-RADS version 2.1 and PI-RADS version 2 regarding interreader variability and diagnostic accuracy for transition zone prostate cancer

PURPOSE

To compare the diagnostic performance of PI-RADS version 2.1 (PI-RADS v2.1) and PI-RADS v2 for transition zone prostate cancer (TZPC), and analyse its performance for readers with different experience levels.

METHODS

Eighty-five patients with suspected prostate cancer who underwent biopsy after MRI scan between January and December 2017 were retrospectively enrolled. One junior radiologist (reader 1, 1 year of experience in using PI-RADS v2) and one senior radiologist (reader 2, 6 years of experience) independently reviewed and assigned a score for each lesion according to PI-RADS v2.1 and v2. The template-guided transperineal prostate biopsy was used for standard of reference. To compare the diagnostic performance of the two methods, the AUC was calculated. The sensitivity, specificity, and accuracy were calculated at predefined positive values (PI-RADS ≥ 3). The interreader agreement and frequency of prostate cancer for each PI-RADS category were also calculated.

RESULTS

Among the 85 patients, 27 had prostate cancers, and 25 were clinically significant prostate cancer (csPCa). The AUC values for diagnosing clinically significant prostate cancer significantly increased with PI-RADS v2.1 for reader 2 (0.766 vs. 0.902, P = 0.009). The specificity and accuracy for both readers also increased with PI-RADS v2.1 (specificity: reader 1, 41.7% vs. 78.3% and reader 2, 33.3% vs. 81.7%; accuracy: reader 1, 52.9% vs. 76.5% and reader 2, 48.2% vs. 83.5%, all P < 0.05). The interreader agreement was good for both versions. The percentage of prostate cancer decreased in lower PI-RADS categories (PI-RADS 2) and increased in higher PI-RADS categories (PI-RADS 3 ~ 4).

CONCLUSION

Compared with PI-RADS v2, PI-RADS v2.1 may improve radiologists' diagnostic performance for TZPC.

Localized fluorescent imaging of multiple proteins on individual extracellular vesicles using rolling circle amplification for cancer diagnosis

Extracellular vesicles (EV) have attracted increasing attention as tumour biomarkers due to their unique biological property. However, conventional methods for EV analysis are mainly based on bulk measurements, which masks the EV‐to‐EV heterogeneity in tumour diagnosis and classification. Herein, a localized fluorescent imaging method (termed Digital Profiling of Proteins on Individual EV, DPPIE) was developed for analysis of multiple proteins on individual EV. In this assay, an anti‐CD9 antibody engineered biochip was used to capture EV from clinical plasma sample. Then the captured EV was specifically recognized by multiple DNA aptamers (CD63/EpCAM/MUC1), followed by rolling circle amplification to generate localized fluorescent signals. By‐analyzing the heterogeneity of individual EV, we found that the high‐dimensional data collected from each individual EV would provide more precise information than bulk measurement (ELISA) and the percent of CD63/EpCAM/MUC1‐triple‐positive EV in breast cancer patients was significantly higher than that of healthy donors, and this method can achieve an overall accuracy of 91%. Moreover, using DPPIE, we are able to distinguish the EV between lung adenocarcinoma and lung squamous carcinoma patients. This individual EV heterogeneity analysis strategy provides a new way for digging more information on EV to achieve multi‐cancer diagnosis and classification.

Real-world Evidence of Diffusion-weighted Imaging Combined With Magnetic Resonance Cholangiopancreatography for Pancreatic Tumor Screening: A Cross-Sectional Diagnostic Accuracy Study

OBJECTIVES

The aim was to clarify the sensitivity and specificity of diffusion-weighted imaging, as well as of that in combination with magnetic resonance cholangiopancreatography for pancreatic tumor diagnosis in real-world clinical setting.

METHODS

Subjects were 217 consecutive patients who underwent both magnetic resonance imaging and contrast-enhanced ultrasound sonography. Cases positive for a pancreatic tumor were confirmed based on pathological diagnosis, whereas negative cases were defined when no solid pancreatic tumor was detected by contrast-enhanced ultrasound sonography or a solid mass was detected but the diagnosis was ultimately denied based on pathological results. Diffusion-weighted imaging-positive was defined as a case with high signals and magnetic resonance cholangiopancreatography-positive when localized main pancreatic duct stenosis with caudal dilation was detected.We calculated sensitivity and specificity of each modality and those in combination based on sequential use for pancreatic tumor diagnosis.

RESULTS

Diffusion-weighted imaging showed a sensitivity of 94.4% and specificity of 94.5%, whereas those values for magnetic resonance cholangiopancreatography alone were 83.3% and 99.0%, respectively, and for the modalities in combination were 100% and 94.5%, respectively.

CONCLUSIONS

Diffusion-weighted imaging was more sensitive than magnetic resonance cholangiopancreatography, whereas those used in combination resulted in increased sensitivity.

Added Value of Biparametric MRI and TRUS-Guided Systematic Biopsies to Clinical Parameters in Predicting Adverse Pathology in Prostate Cancer

Objective

To develop novel models for predicting extracapsular extension (EPE), seminal vesicle invasion (SVI), or upgrading in prostate cancer (PCa) patients using clinical parameters, biparametric magnetic resonance imaging (bp-MRI), and transrectal ultrasonography (TRUS)-guided systematic biopsies.

Patients and Methods

We retrospectively collected data from PCa patients who underwent standard (12-core) systematic biopsy and radical prostatectomy. To develop predictive models, the following variables were included in multivariable logistic regression analyses: total prostate-specific antigen (TPSA), central transition zone volume (CTZV), prostate-specific antigen (PSAD), maximum diameter of the index lesion at bp-MRI, EPE at bp-MRI, SVI at bp-MRI, biopsy Gleason grade group, and number of positive biopsy cores. Three risk calculators were built based on the coefficients of the logit function. The area under the curve (AUC) was applied to determine the models with the highest discrimination. Decision curve analyses (DCAs) were performed to evaluate the net benefit of each risk calculator.

Results

A total of 222 patients were included in this study. Overall, 83 (37.4%), 75 (33.8%), and 107 (48.2%) patients had EPE, SVI, and upgrading at final pathology, respectively. The addition of bp-MRI data improved the discrimination of models for predicting SVI (0.807 vs 0.816) and upgrading (0.548 vs 0.625) but not EPE (0.766 vs 0.763). Similarly, models including clinical parameters, bp-MRI data, and information on systematic biopsies achieved the highest AUC in the prediction of EPE (0.842), SVI (0.913), and upgrading (0.794), and the three corresponding risk calculators yielded the highest net benefit.

Conclusion

We developed three easy-to-use risk calculators for the prediction of adverse pathological features based on patient clinical parameters, bp-MRI data, and information on systematic biopsies. This may be greatly beneficial to urologists in the decision-making process for PCa patients.

Radiomics Based on Multiparametric Magnetic Resonance Imaging to Predict Extraprostatic Extension of Prostate Cancer

Background: To develop a radiomics model based on multiparametric MRI (mpMRI) for preoperative prediction of extraprostatic extension (EPE) in patients with prostate cancer (PCa). Methods: Ninety-five pathology-confirmed PCa patients with 115 lesions (49 positive and 66 negative) were retrospectively enrolled. A 3.0T MR scanner was used to perform T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced imaging (DCE). Radiomics features extracted from T2WI, DWI, apparent diffusion coefficient (ADC), and DCE were used to build a radiomics model. Patients' clinical and pathological variables were also obtained to build a clinical model. The radiomics model and clinical model were further integrated to build a combined nomogram. All lesions were randomly divided into the training group (82 lesions) and the validation group (33 lesions). A least absolute shrinkage and selection operator (LASSO) regression algorithm was applied to build the radiomics model. The diagnostic performance of different models was assessed by calculating the area under the curve (AUC) and compared using the Delong test. The calibration curve and decision curve analyses were used to assess the calibration and clinical usefulness of the radiomics model. Results: The AUC values for the radiomics model in the training and validation group were 0.919 and 0.865, respectively, with a good calibration performance. The decision curve analysis confirmed the clinical utility of the radiomics model. The accuracy, sensitivity, and specificity were 81.8, 71.4, and 89.5% in the validation group. In the validation group, the radiomics model outperformed the clinical model (AUC = 0.658, P = 0.020), and was comparable with the combined nomogram (AUC = 0.857, P = 0.644). Conclusion: The radiomics model based on mpMRI could different EPE and non-EPE lesions with satisfactory diagnostic performance, and this model might assist in predicting EPE before prostatectomy.

Influence of the Location and Zone of Tumor in Prostate Cancer Detection and Localization on 3-T Multiparametric MRI Based on PI-RADS Version 2

OBJECTIVE. The objective of our study was to determine the performance of 3-T multiparametric MRI (mpMRI) for prostate cancer (PCa) detection and localization, stratified by anatomic zone and level, using Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) and whole-mount histopathology (WMHP) as reference. MATERIALS AND METHODS. Multiparametric MRI examinations of 415 consecutive men were compared with thin-section WMHP results. A genitourinary radiologist and pathologist collectively determined concordance. Two radiologists assigned PI-RADSv2 scores and sector location to all detected foci by consensus. Tumor detection rates were calculated for clinical and pathologic (tumor location and zone) variables. Both rigid and adjusted sector-matching models were used to account for fixation-related issues. RESULTS. Of 863 PCa foci in 16,185 prostate sectors, the detection of overall and index PCa lesions in the midgland, base, and apex was 54.9% and 83.1%, 42.1% and 64.0% (p = 0.04, p = 0.02), and 41.9% and 71.4% (p = 0.001, p = 0.006), respectively. Tumor localization sensitivity was highest in the midgland compared with the base and apex using an adjusted match compared with a rigid match (index lesions, 71.3% vs 43.7%; all lesions, 70.8% vs 36.0%) and was greater in the peripheral zone (PZ) than in the transition zone. Three-Tesla mpMRI had similarly high specificity (range, 93.8-98.3%) for overall and index tumor localization when using both rigid and adjusted sector-matching approaches. CONCLUSION. For 3-T mpMRI, the highest sensitivity (83.1%) for detection of index PCa lesions was in the midgland, with 98.3% specificity. Multiparametric MRI performance for sectoral localization of PCa within the prostate was moderate and was best for index lesions in the PZ using an adjusted model.

Radiomics prediction model for the improved diagnosis of clinically significant prostate cancer on biparametric MRI

Background

To evaluate the potential of clinical-based model, a biparametric MRI-based radiomics model and a clinical-radiomics combined model for predicting clinically significant prostate cancer (PCa).

Methods

In total, 381 patients with clinically suspicious PCa were included in this retrospective study; of those, 199 patients did not have PCa upon biopsy, while 182 patients had PCa. All patients underwent 3.0-T MRI examinations with the same acquisition parameters, and clinical risk factors associated with PCa (age, prostate volume, serum PSA, etc.) were collected. We randomly stratified the training and test sets using a 6:4 ratio. The radiomic features included gradient-based histogram features, grey-level co-occurrence matrix (GLCM), run-length matrix (RLM), and grey-level size zone matrix (GLSZM). Three models were developed using multivariate logistic regression analysis to predict clinically significant PCa: a clinical model, a radiomics model and a clinical-radiomics combined model. The diagnostic performance and clinical net benefit of each model were compared via receiver operating characteristic (ROC) curve analysis and decision curves, respectively.

Results

Both the radiomics model (AUC: 0.98) and the clinical-radiomics combined model (AUC: 0.98) achieved greater predictive efficacy than the clinical model (AUC: 0.79). The decision curve analysis also showed that the radiomics model and combined model had higher net benefits than the clinical model.

Conclusions

Compared with the evaluation of clinical risk factors associated with PCa only, the radiomics-based machine learning model can improve the predictive accuracy for clinically significant PCa, in terms of both diagnostic performance and clinical net benefit.

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.

Digital Rectal Examination Remains a Key Prognostic Tool for Prostate Cancer: A National Cancer Database Review

BACKGROUND

Prostate cancer clinical stage T2 (cT2) subclassifications, as determined by digital rectal examination (DRE), are a historic method of staging prostate cancer. However, given the potential discomfort associated with prostate examination and the wide availability of other prognostic tests, the necessity of DRE is uncertain. This study sought to determine the prognostic value of the prostate cancer cT2 subclassifications in a contemporary cohort of patients.

METHODS

The National Cancer Database was used to identify a cohort of men with high-risk clinical T2N0M0 prostate cancer treated with external-beam radiotherapy and androgen deprivation therapies ± surgery from 2004 to 2010. We assessed overall survival from a landmark time of 10 months using Kaplan-Meier and log-rank test analysis. A multivariate proportional hazards model was used to estimate the simultaneous effects of multiple factors, including cT2 subclassification and other well-established prognostic indicators of overall survival in prostate cancer.

RESULTS

A total of 5,291 men were included in the final analysis, with a median follow-up of 5.4 years. The cT2a, cT2b, and cT2c subclassifications demonstrated increasing hazard ratios of 1.00 (reference), 1.25 (95% CI, 1.07-1.45; P=.0046), and 1.43 (95% CI, 1.25-1.63; P<.0001), respectively, reflecting a higher probability of death with each incremental increase in cT2 subclassification. This finding was independent of other known prognostic variables on multivariate analysis.

CONCLUSIONS

Results show that cT2 subclassifications had independent prognostic value in a large and contemporary cohort of men. cT2 classification remains an important, low-cost prognostic tool for men with prostatic adenocarcinoma. The clinical relevance of this test should be appreciated and accounted for by providers treating prostate adenocarcinoma.

Comparison of preoperative locoregional Ga-68 PSMA-11 PET-CT and mp-MRI results with postoperative histopathology of prostate cancer

BACKGROUND

Conventional imaging modalities are inadequate to evaluate locoregional extension of prostate cancer (PCa). The aim of the current retrospective study was to investigate the diagnostic efficacy of Gallium-68 prostate-specific membrane antigen-11 (Ga-68 PSMA-11) positron emission tomography/computed tomography (PET/CT) and multiparametric magnetic resonance imaging (mp-MRI) for staging preoperative PCa patients with correlating histopathology.

MATERIALS AND METHODS

Twenty-four patients with histologically proven PCa underwent both Ga-68 PSMA-11 PET/CT and mp-MRI before robot-assisted laparoscopic radical prostatectomy. For each tumor area, correlations with histopathological results were defined for tumor localization, extraprostatic extension (EPE) of the tumor, invasion of seminal vesicle (SVI) and bladder neck invasion (BNI). In patients with regional lymph node (LN) dissection, histopathological results were also correlated with imaging modalities.

RESULTS

Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for detection of EPE and SVI were higher for mp-MRI than Ga-68 PSMA-11 PET/CT. On the other hand Ga-68 PSMA-11 PET/CT had significant successful results for detection of LN metastases when compared with mp-MRI. But for BNI detection both modalities had same insufficient results. Ga-68 PSMA-11 PET/CT had strong results for appropriate tumor localization in the gland.

CONCLUSION

Ga-68 PSMA PET/CT has superior results for assessing local LN metastases and for intraprostatic tumor localization. Whereas, mp-MRI must be the preferred modality for determining SVI and EPE. But both imaging modalities failed for determining BNI accurately. Both modalities should be used in conjunction with each other for better treatment planning.

Cylindrical illumination with angular coupling for whole-prostate photoacoustic tomography

Current diagnosis of prostate cancer relies on histological analysis of tissue samples acquired by biopsy, which could benefit from real-time identification of suspicious lesions. Photoacoustic tomography has the potential to provide real-time targets for prostate biopsy guidance with chemical selectivity, but light delivered from the rectal cavity has been unable to penetrate to the anterior prostate. To overcome this barrier, a urethral device with cylindrical illumination is developed for whole-prostate imaging, and its performance as a function of angular light coupling is evaluated with a prostate-mimicking phantom.

Correlations between Apparent Diffusion Coefficient and Gleason Score in Prostate Cancer: A Systematic Review

BACKGROUND

Reported data regarding the associations between apparent diffusion coefficient (ADC) of diffusion-weighted imaging (DWI) and Gleason score in prostate cancer (PC) are inconsistent.

OBJECTIVE

The aim of the present systematic review was to analyze relationships between ADC and Gleason score in PC.

DESIGN, SETTING, AND PARTICIPANTS

MEDLINE library, SCOPUS, and EMBASE databases were screened for relationships between ADC and Gleason score in PC up to April 2018. Overall, 39 studies with 2457 patients were identified. Data on the following parameters were extracted from the literature: number of patients, cancer localization, and correlation coefficients between ADC and Gleason score.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Associations between ADC and Gleason score were analyzed by the Spearman's correlation coefficient.

RESULTS AND LIMITATIONS

In overall sample, the pooled correlation coefficient between ADC and Gleason score was -0.45 (95% confidence interval [CI]=[-0.50; -0.40]). In PC in the transitional zone, the pooled correlation coefficient was -0.22 (95% CI=[-0.47; 0.03]). In PC in the peripheral zone, the pooled correlation coefficient was -0.48 (95% CI=[-0.54; -0.42]).

CONCLUSIONS

In PC located in the peripheral zone, ADC correlated moderately with Gleason score. In PC located in the transitional zone, ADC correlated weakly with Gleason score.

PATIENT SUMMARY

We reviewed studies using apparent diffusion coefficient for the prediction of Gleason score in prostate cancer patients.

Multiparametric (mp) MRI of prostate cancer

Prostate cancer (PCa) is one of the most prevalent cancers in men. A large number of men are detected with PCa; however, the clinical behavior ranges from low-grade indolent tumors that never develop into a clinically significant disease to aggressive, invasive tumors that may rapidly progress to metastatic disease. The challenges in clinical management of PCa are at levels of screening, diagnosis, treatment, and follow-up after treatment. Magnetic resonance imaging (MRI) methods have shown a potential role in detection, localization, staging, assessment of aggressiveness, targeting biopsies, etc. in PCa patients. Multiparametric MRI (mpMRI) is emerging as a better option compared to the individual imaging methods used in the evaluation of PCa. There are attempts to improve the reproducibility and reliability of mpMRI by using an objective scoring system proposed in the prostate imaging reporting and data system (PIRADS) for standardized reporting. Prebiopsy mpMRI may be used to detect PCa in men with elevated prostate-specific antigen or abnormal digital rectal examination and to enable targeted biopsies. mpMRI can also be used to decide on clinical management of patients, for example active surveillance, and may help in detecting only the pathology that requires detection. It can potentially not only guide patient selection for initial and repeat biopsy but also reduce false-negative biopsies. This review presents a description of the MR methods most commonly applied for investigations of prostate. The anatomical, functional and metabolic parameters obtained from these MR methods are discussed with regard to their physical basis and their contribution to mpMRI investigations of PCa.

Prostate cancer screening-when to start and how to screen?

Prostate-specific antigen (PSA) screening reduces prostate cancer (PCa) mortality; however such screening may lead to harm in terms of overdiagnosis and overtreatment. Therefore, upfront shared decision making involving a discussion about pros and cons between a physician and a patient is crucial. Total PSA remains the most commonly used screening tool and is a strong predictor of future life-threatening PCa. Currently there is no strong consensus on the age at which to start PSA screening. Most guidelines recommend PSA screening to start no later than at age 55 and involve well-informed men in good health and a life expectancy of at least 10–15 years. Some suggest to start screening in early midlife for men with familial predisposition and men of African-American descent. Others suggest starting conversations at age 45 for all men. Re-screening intervals can be risk-stratified as guided by the man’s age, general health and PSA-value; longer intervals for those at lower risk and shorter intervals for those at higher risk. Overdiagnosis and unnecessary biopsies can be reduced using reflex tests. Magnetic resonance imaging in the pre-diagnostic setting holds promise in pilot studies and large-scale prospective studies are ongoing.

The Heterogeneity of Prostate Cancer: A Practical Approach

Prostate cancer is a paradigm tumor model for heterogeneity in almost every sense. Its clinical, spatial, and morphological heterogeneity divided by the high-level molecular genetic diversity outline the complexity of this disease in the clinical and research settings. In this review, we summarize the main aspects of prostate cancer heterogeneity at different levels, with special attention given to the spatial heterogeneity within the prostate, and to the standard morphological heterogeneity, with respect to tumor grading and modern classifications. We also cover the complex issue of molecular genetic heterogeneity, discussing it in the context of the current evidence of the genetic characterization of prostate carcinoma; the interpatient, intertumoral (multifocal disease), and intratumoral heterogeneity; tumor clonality; and metastatic disease. Clinical and research implications are summarized and serve to address the most pertinent problems stemming from the extreme heterogeneity of prostate cancer.

Ultra-high b-value diffusion-weighted imaging features of the prostatic leiomyoma-case report

Background

Leiomyoma of the prostate is a rare benign tumor arising from smooth muscle fibers. Most cases are incidental findings observed during pathological examinations after resection of the prostate. To the best of our knowledge, only few studies have reported the conventional magnetic resonance imaging (MRI) findings of such tumors; however, no reports have described the ultra-high b-value diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) findings of prostatic leiomyomas.

Case presentation

We report MR imaging characteristics and surgical pathologic findings of a case of prostatic leiomyoma treated by robot-assisted transperitoneal laparoscopic approach. Typical MR features showed a homogeneous lesion with slightly hypointense signal compared to the skeletal muscle on T2-weighted images, and isointense signal relative to the muscle on T1-weighted images with fat suppression, which collectively demonstrate apparent homogeneous enhancement with a non-enhanced envelope. A slightly hyperintense signal compared to the skeletal muscle was observed on ultra-high b-value DWI, and higher ADC values were observed as compared to the prostate cancer.

Conclusions

Prostatic leiomyoma is a benign tumor. This case indicates that MRI features of prostatic leiomyoma are helpful for the differential diagnosis of prostate cancer.

A systematic review on multiparametric MR imaging in prostate cancer detection

BACKGROUND

Literature data suggest that multi-parametric Magnetic Resonance Imaging (MRI), including morphologic T2-weigthed images (T2-MRI) and functional approaches such as Dynamic Contrast Enhanced-MRI (DCE-MRI), Diffusion Weighted Imaging (DWI) and Magnetic Resonance Spectroscopic Imaging (MRSI), give an added value in the prostate cancer localization and local staging.

METHODS

We performed a systematic review of literature about the role and the potentiality of morphological and functional MRI in prostate cancer, also in a multimodal / multiparametric approach, and we reported the diagnostic accuracy results for different imaging modalities and for different MR coil settings: endorectal coil (ERC) and phased array coil (PAC). Forest plots and receiver operating characteristic curves were performed. Risk of bias and the applicability at study level were calculated.

RESULTS

Thirty three papers were identified for the systematic review. Sensitivity and specificity values were, respectively, for T2-MRI of 75% and of 60%, for DCE-MRI of 80% and of 72%, for MRSI of 89% and of 69%, for combined T2-MRI and DCE-MRI of 87% and of 46%, for combined T2-MRI and MRSI of 79% and of 57%, for combined T2-MRI, DWI and DCE-MRI of 81% and of 84%, and for combined MRSI and DCE-MRI of 83% and of 83%. For MRI studies performed with ERC we obtained a pooled sensitivity and specificity of 81% and of 66% while the pooled values for MRI studies performed with PAC were of 78% and of 64%, respectively (p>0.05 at McNemar test). No studies were excluded from the analysis based on the quality assessment.

CONCLUSIONS

ERC use yielded no additional benefit in terms of prostate cancer detection accuracy compared to multi-channel PAC use (71% versus 68%) while the use of additional functional imaging techniques (DCE-MRI, DWI and MRSI) in a multiparametric MRI protocol improves the accuracy of prostate cancer detection allowing both the early cure and the guidance of biopsy.

Diffusion weighted imaging of the prostate-principles, application, and advances

This review article aims to provide an overview on the principles of diffusion-weighted magnetic resonance imaging (DW-MRI) and its applications in the imaging of the prostate. DW-MRI with regards to different applications for prostate cancer (PCa) detection and characterization, local staging as well as for active surveillance (AS) and tumor recurrence after radical prostatectomy (RP) will be discussed. Furthermore, advances in DW-MRI techniques like diffusion kurtosis imaging (DKI) will be presented.

Restriction spectrum imaging: An evolving imaging biomarker in prostate MRI

Restriction spectrum imaging (RSI) is a novel diffusion-weighted MRI technique that uses the mathematically distinct behavior of water diffusion in separable microscopic tissue compartments to highlight key aspects of the tissue microarchitecture with high conspicuity. RSI can be acquired in less than 5 min on modern scanners using a surface coil. Multiple field gradients and high b-values in combination with postprocessing techniques allow the simultaneous resolution of length-scale and geometric information, as well as compartmental and nuclear volume fraction filtering. RSI also uses a distortion correction technique and can thus be fused to high resolution T2-weighted images for detailed localization, which improves delineation of disease extension into critical anatomic structures. In this review, we discuss the acquisition, postprocessing, and interpretation of RSI for prostate MRI. We also summarize existing data demonstrating the applicability of RSI for prostate cancer detection, in vivo characterization, localization, and targeting.

LEVEL OF EVIDENCE

5 J. Magn. Reson. Imaging 2017;45:323-336.