PI-RADS Steering Committee: The PI-RADS Multiparametric MRI and MRI-directed Biopsy Pathway

Prospective Evaluation of PI-RADS Version 2.1 for Prostate Cancer Detection and Investigation of Multiparametric MRI-derived Markers

Background Data regarding the prospective performance of Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 alone and in combination with quantitative MRI features for prostate cancer detection is limited. Purpose To assess lesion-based clinically significant prostate cancer (csPCa) rates in different PI-RADS version 2.1 categories and to identify MRI features that could improve csPCa detection. Materials and Methods This single-center prospective study included men with suspected or known prostate cancer who underwent multiparametric MRI and MRI/US-guided biopsy from April 2019 to December 2021. MRI scans were prospectively evaluated using PI-RADS version 2.1. Atypical transition zone (TZ) nodules were upgraded to category 3 if marked diffusion restriction was present. Lesions with an International Society of Urological Pathology (ISUP) grade of 2 or higher (range, 1-5) were considered csPCa. MRI features, including three-dimensional diameter, relative lesion volume (lesion volume divided by prostate volume), sphericity, and surface to volume ratio (SVR), were obtained from lesion contours delineated by the radiologist. Univariable and multivariable analyses were conducted at the lesion and participant levels to determine features associated with csPCa. Results In total, 454 men (median age, 67 years [IQR, 62-73 years]) with 838 lesions were included. The csPCa rates for lesions categorized as PI-RADS 1 (n = 3), 2 (n = 170), 3 (n = 197), 4 (n = 319), and 5 (n = 149) were 0%, 9%, 14%, 37%, and 77%, respectively. csPCa rates of PI-RADS 4 lesions were lower than PI-RADS 5 lesions (P < .001) but higher than PI-RADS 3 lesions (P < .001). Upgraded PI-RADS 3 TZ lesions were less likely to harbor csPCa compared with their nonupgraded counterparts (4% [one of 26] vs 20% [20 of 99], P = .02). Predictors of csPCa included relative lesion volume (odds ratio [OR], 1.6; P < .001), SVR (OR, 6.2; P = .02), and extraprostatic extension (EPE) scores of 2 (OR, 9.3; P < .001) and 3 (OR, 4.1; P = .02). Conclusion The rates of csPCa differed between consecutive PI-RADS categories of 3 and higher. MRI features, including lesion volume, shape, and EPE scores of 2 and 3, predicted csPCa. Upgrading of PI-RADS category 3 TZ lesions may result in unnecessary biopsies. ClinicalTrials.gov registration no. NCT03354416 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Goh in this issue.

[Systematic or targeted fusion-guided biopsy]

BACKGROUND

Early detection of prostate cancer (PCa) is associated with a high risk for detecting low-risk disease. In the primary biopsy indication, systematic biopsy leads to an increased detection of clinically insignificant PCa, and significant prostate cancers are not detected with sufficient sensitivity, especially without prior magnetic resonance imaging (MRI). Similar data have recently become available for PCa screening.

OBJECTIVES

In light of the current literature, this article aims to discuss the data on systematic and combined targeted and systematic multiparametric MRI (mpMRI)-guided fusion biopsy to improve PCa diagnosis in clinically suspected cancer even in screening using multivariable risk stratification.

MATERIALS AND METHODS

Literature review on mpMRI and MRI/TRUS fusion biopsy (TRUS: transrectal ultrasonography) for tumor detection in suspected prostate cancer and PCa screening was performed.

RESULTS

Multiparametric MRI as a reflex test after prostate-specific antigen (PSA) determination (PSA cut-off 4 ng/ml) in combination with targeted biopsy alone reduces the detection of clinically nonsignificant tumors in early detection by half. On the other hand, in the form of a target saturation or in combination with a systematic biopsy, the sensitivity for the detection of cancers of International Society of Urogenital Pathology (ISUP) grade groups 2 or higher can be improved. Similar results are also shown in PCa screening with a PSA cut-off of 3 ng/ml.

CONCLUSIONS

The evidence for performing a targeted fusion biopsy alone is currently insufficient. Therefore, the combination of mpMRI-guided targeted and systematic biopsy continues to be the recommended standard for prostate cancer diagnosis.

Reverse encoding distortion correction for diffusion-weighted MRI: Efficacy for improving image quality and ADC evaluation for differentiating malignant from benign areas in suspected prostatic cancer patients

PURPOSE

The purpose of this study was to determine the influenceof reverse encoding distortion correction (RDC) on ADC measurement and its efficacy for improving image quality and diagnostic performance for differentiating malignant from benign prostatic areas on prostatic DWI.

METHODS

Forty suspected prostatic cancer patients underwent DWI with or without RDC (i.e. RDC DWI or DWI) using a 3 T MR system as well as pathological examinations. The pathological examination results indicated 86 areas were malignant while 86 out of 394 areas were computationally selected as benign. SNR for benign areas and muscle and ADCs for malignant and benign areas were determined by ROI measurements on each DWI. Moreover, overall image quality was assessed with a 5-point visual scoring system on each DWI. Paired t-test or Wilcoxon's signed rank test was performed to compare SNR and overall image quality for DWIs. ROC analysis was then used to compare the diagnostic performance, and sensitivity (SE), specificity (SP) and accuracy (AC) of ADC were compared between two DWI by means of McNemar's test.

RESULTS

SNR and overall image quality of RDC DWI showed significant improvements when compared with those of DWI (p < 0.05). Areas under the curve (AUC), SP and AC of DWI RDC DWI (AUC: 0.85, SP: 72.1%, AC: 79.1%) were significantly better than those of DWI (AUC: 0.79, p = 0.008; SP: 64%, p = 0.02; AC: 74.4%, p = 0.008).

CONCLUSION

RDC technique has the potential to improve image quality and ability to differentiate malignant from benign prostatic areas on DWIs of suspected prostatic cancer patients.

CROPro: a tool for automated cropping of prostate magnetic resonance images

Purpose

To bypass manual data preprocessing and optimize deep learning performance, we developed and evaluated CROPro, a tool to standardize automated cropping of prostate magnetic resonance (MR) images.

Approach

CROPro enables automatic cropping of MR images regardless of patient health status, image size, prostate volume, or pixel spacing. CROPro can crop foreground pixels from a region of interest (e.g., prostate) with different image sizes, pixel spacing, and sampling strategies. Performance was evaluated in the context of clinically significant prostate cancer (csPCa) classification. Transfer learning was used to train five convolutional neural network (CNN) and five vision transformer (ViT) models using different combinations of cropped image sizes ( 64 × 64 , 128 × 128 , and 256 × 256  pixels2), pixel spacing ( 0.2 × 0.2 , 0.3 × 0.3 , 0.4 × 0.4 , and 0.5 × 0.5    mm 2 ), and sampling strategies (center, random, and stride cropping) over the prostate. T2-weighted MR images ( N = 1475 ) from the online available PI-CAI challenge were used to train ( N = 1033 ), validate ( N = 221 ), and test ( N = 221 ) all models.

Results

Among CNNs, SqueezeNet with stride cropping (image size: 128 × 128 , pixel spacing: 0.2 × 0.2    mm 2 ) achieved the best classification performance ( 0.678 ± 0.006 ). Among ViTs, ViT-H/14 with random cropping (image size: 64 × 64 and pixel spacing: 0.5 × 0.5    mm 2 ) achieved the best performance ( 0.756 ± 0.009 ). Model performance depended on the cropped area, with optimal size generally larger with center cropping ( ∼ 40    cm 2 ) than random/stride cropping ( ∼ 10    cm 2 ).

Conclusion

We found that csPCa classification performance of CNNs and ViTs depends on the cropping settings. We demonstrated that CROPro is well suited to optimize these settings in a standardized manner, which could improve the overall performance of deep learning models.

Surveillance Value of Apparent Diffusion Coefficient Maps: Multiparametric MRI in Active Surveillance of Prostate Cancer

BACKGROUND

This study aims to establish the value of apparent diffusion coefficient maps and other magnetic resonance sequences for active surveillance of prostate cancer. The study included 530 men with an average age of 66, who were under surveillance for prostate cancer. We have used multiparametric magnetic resonance imaging with subsequent transperineal biopsy (TPB) to verify the imaging findings.

RESULTS

We have observed a level of agreement of 67.30% between the apparent diffusion coefficient (ADC) maps, other magnetic resonance sequences, and the biopsy results. The sensitivity of the apparent diffusion coefficient is 97.14%, and the specificity is 37.50%. According to our data, apparent diffusion coefficient is the most accurate sequence, followed by diffusion imaging in prostate cancer detection.

CONCLUSIONS

Based on our findings we advocate that the apparent diffusion coefficient should be included as an essential part of magnetic resonance scanning protocols for prostate cancer in at least bi-parametric settings. The best option will be apparent diffusion coefficient combined with diffusion imaging and T2 sequences. Further large-scale prospective controlled studies are required to define the precise role of multiparametric and bi-parametric magnetic resonance in the active surveillance of prostate cancer.

Detection of Clinically Significant Prostate Cancer Using Targeted Biopsy with Four Cores Versus Target Saturation Biopsy with Nine Cores in Transperineal Prostate Fusion Biopsy: A Prospective Randomized Trial

BACKGROUND

Multiparametric magnetic resonance imaging (mpMRI) and targeted biopsy (TB) facilitate accurate detection of clinically significant prostate cancer (csPC). However, it remains unclear how targeted cores should be applied for accurate diagnosis of csPC.

OBJECTIVE

To assess csPC detection rates for two target-directed MRI/transrectal ultrasonography (TRUS) fusion biopsy approaches, conventional TB and target saturation biopsy (TS).

DESIGN, SETTING, AND PARTICIPANTS

This was a prospective single-center study of outcomes for transperineal MRI/TRUS fusion biopsies for 170 men. Half of the men (n = 85) were randomized to conventional TB with four cores per lesion and half (n = 85) to TS with nine cores. Biopsies were performed by three experienced board-certified urologists.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

PC and csPC (International Society of Urological Pathology grade group ≥2) detection rates for systematic biopsy (SB), TB, and TS were analyzed using McNemar's test for intrapatient comparisons and Fisher's exact test for TS versus TB. A combination of targeted biopsy (TS or TB) and SB served as the reference.

RESULTS AND LIMITATIONS

According to the reference, csPC was diagnosed for 57 men in the TS group and 36 men in the TB group. Of these, TS detected 57/57 csPC cases and TB detected 33/36 csPC cases (p = 0.058). Detection of Gleason grade group 1 disease was 10/12 cases with TS and 8/17 cases with TB (p = 0.055). In addition, TS detected 97% of 63 csPC lesions, compared to 86% with TB (p = 0.1). Limitations include the single-center design, the limited generalizability owing to the transperineal biopsy route, the lack of central review of pathology and radical prostatectomy correlation, and uneven distributions of csPC prevalence, Prostate Imaging-Reporting and Data System (PI-RADS) 5 lesions, men with two or more PI-RADS ≥3 lesions, and prostate-specific antigen density between the groups, which may have affected the results.

CONCLUSIONS

In our study, rates of csPC detection did not significantly differ between TS and TB.

PATIENT SUMMARY

In this study, we investigated two targeted approaches for taking prostate biopsy samples after observation of suspicious lesions on prostate scans. We found that the rates of detection of prostate cancer did not significantly differ between the two approaches.

Biopsy-Integrated 3D Magnetic Resonance Imaging Modeling of Prostate Cancer and Its Application for Gleason Grade and Tumor Laterality Assessment

CONTEXT.—

Grade Group assessed using Gleason combined score and tumor extent is a main determinant for risk stratification and therapeutic planning of prostate cancer.

OBJECTIVE.—

To develop a 3-dimensional magnetic resonance imaging (MRI) model regarding Grade Group and tumor extent in collaboration with uroradiologists and uropathologists for optimal treatment planning for prostate cancer.

DESIGN.—

We studied the data from 83 patients with prostate cancer who underwent multiparametric MRI and subsequent MRI-transrectal ultrasound fusion biopsy and radical prostatectomy. A 3-dimensional MRI model was constructed by integrating topographic information of MRI-based segmented lesions, biopsy paths, and histopathologic information of biopsy specimens. The multiparametric MRI-integrated Grade Group and laterality were assessed by using the 3-dimensional MRI model and compared with the radical prostatectomy specimen.

RESULTS.—

The MRI-defined index tumor was concordant with radical prostatectomy in 94.7% (72 of 76) of cases. The multiparametric MRI-integrated Grade Group revealed the highest agreement (weighted κ, 0.545) and a significantly higher concordance rate (57.9%) than the targeted (47.8%, P = .008) and systematic (39.4%, P = .01) biopsies. The multiparametric MRI-integrated Grade Group showed significantly less downgrading rates than the combined biopsy (P = .001), without significant differences in upgrading rate (P = .06). The 3-dimensional multiparametric MRI model estimated tumor laterality in 66.2% (55 of 83) of cases, and contralateral clinically significant cancer was missed in 9.6% (8 of 83) of cases. The tumor length measured by multiparametric MRI best correlated with radical prostatectomy as compared with the biopsy-defined length.

CONCLUSIONS.—

The 3-dimensional model incorporating MRI and MRI-transrectal ultrasound fusion biopsy information easily recognized the spatial distribution of MRI-visible and MRI-nonvisible cancer and provided better Grade Group correlation with radical prostatectomy specimens but still requires validation.

Monoparametric high-resolution diffusion weighted MRI as a possible first step in an MRI-directed diagnostic pathway for men with suspicion of prostate cancer

Purpose

To explore if a high-resolution diffusion weighted MRI sequence (DWI-only) could be used as a first step in an MRI-directed diagnostic pathway.

Methods

Prospective single center study that between December 2017 and August 2018 included 129 consecutive patients with suspicion of prostate cancer into a PI-RADS-based MRI-directed diagnostic pathway. All patients had multiparametric MRI (mpMRI). Based on only the transversal high-resolution DWI images two consultant radiologists prospectively categorized the findings as positive, equivocal, or negative for clinically significant cancer. The radiologists then interpreted the mpMRI and assigned a PI-RADS score. A third independent reader retrospectively categorized the DWI-only exams without access to the mpMRI. The interpretations of DWI-only were compared to the PI-RADS classification from mpMRI and the histopathology from the biopsies. Non-biopsied patients were followed in a safety net monitoring for 56 months.

Results

Based on DWI-only, 29 (22.5%) of the exams were categorized as negative, 38 (29.5%) as equivocal and 62 (48.1%) as positive. Of the 56 patients with PI-RADS 4-5 at mpMRI, 55 were also categorized as positive at DWI-only. All patients diagnosed with clinically significant cancer were identified using DWI-only. 56 months of safety net monitoring did not reveal any clinically significant cancers among patients with exams categorized as negative or equivocal. There was high inter-reader agreement on positive findings, but less agreement on negative and equivocal findings.

Conclusions

In this concept study, the monoparametric DWI-only identified all patients with clinically significant cancer in a mpMRI-directed diagnostic pathway.

Quality checkpoints in the MRI-directed prostate cancer diagnostic pathway

Multiparametric MRI of the prostate is now recommended as the initial diagnostic test for men presenting with suspected prostate cancer, with a negative MRI enabling safe avoidance of biopsy and a positive result enabling MRI-directed sampling of lesions. The diagnostic pathway consists of several steps, from initial patient presentation and preparation to performing and interpreting MRI, communicating the imaging findings, outlining the prostate and intra-prostatic target lesions, performing the biopsy and assessing the cores. Each component of this pathway requires experienced clinicians, optimized equipment, good inter-disciplinary communication between specialists, and standardized workflows in order to achieve the expected outcomes. Assessment of quality and mitigation measures are essential for the success of the MRI-directed prostate cancer diagnostic pathway. Quality assurance processes including Prostate Imaging-Reporting and Data System, template biopsy, and pathology guidelines help to minimize variation and ensure optimization of the diagnostic pathway. Quality control systems including the Prostate Imaging Quality scoring system, patient-level outcomes (such as Prostate Imaging-Reporting and Data System MRI score assignment and cancer detection rates), multidisciplinary meeting review and audits might also be used to provide consistency of outcomes and ensure that all the benefits of the MRI-directed pathway are achieved.

Radiologists' Contribution to Variation in Detecting Clinically Significant Prostate Cancer in Men With Prostate MRI

OBJECTIVE

Assess radiologists' contribution to variation in clinically significant prostate cancer (csPCa) detection in patients with elevated prostate-specific antigen (PSA) and multiparametric MRI (mpMRI).

METHODS

This institutional review board-approved, retrospective cohort study was performed at a tertiary, academic, National Cancer Institute-designated Comprehensive Cancer Center with a multidisciplinary prostate cancer program. Men undergoing mpMRI examinations from January 1, 2015, to December 31, 2019, with elevated PSA (≥4 ng/mL) and biopsy within 6 months pre- or post-MRI or prostatectomy within 6 months post-mpMRI were included. Univariate and multivariable hierarchical logistic regression assessed impact of patient, provider, mpMRI examination, mpMRI report, and pathology factors on the diagnosis of Grade Group ≥ 2 csPCa.

RESULTS

Study cohort included 960 MRIs in 928 men, mean age 64.0 years (SD ± 7.4), and 59.8% (555 of 928) had csPCa. Interpreting radiologist was not significant individually (P > .999) or combined with mpMRI ordering physician and physician performing biopsy or prostatectomy (P = .41). Prostate Imaging Reporting and Data System (PI-RADS) category 2 (odds ratio [OR] 0.18, P = .04), PI-RADS category 4 (OR 2.52, P < .001), and PI-RADS category 5 (OR 4.99, P < .001) assessment compared with no focal lesion; PSA density of 0.1 to 0.15 ng/mL/cc (OR 2.46, P < .001), 0.15 to 0.2 ng/mL/cc (OR 2.77, P < .001), or ≥0.2 ng/mL/cc (OR 4.52, P < .001); private insurance (reference = Medicare, OR 0.52, P = .001), and unambiguous extraprostatic extension on mpMRI (OR 2.94, P = .01) were independently associated with csPCa. PI-RADS 3 assessment (OR 1.18, P = .56), age (OR 0.99, P = .39), and African American race (OR 0.90, P = .75) were not.

DISCUSSION

Although there is known in-practice variation in radiologists' interpretation of mpMRI, in our multidisciplinary prostate cancer program we found no significant radiologist-attributable variation in csPCa detection.

Diagnosis and Pathologic Reporting of Prostate Cancer in the Era of MRI-Targeted Prostate Biopsy

Historically, the detection of prostate cancer relied upon a systematic yet random sampling of the prostate by transrectal ultrasound guided biopsy. This approach was a nontargeted technique that led to the under detection of cancers at biopsy and the upgrading of cancers at radical prostatectomy. Multiparametric MRI-targeted prostate biopsy allows for an image-directed approach to the identification of prostate cancer. MRI-targeted biopsy of the prostate is superior for the detection of clinically significant prostate cancer. As this technique has become more prevalent among urologists, pathologists need to recognize how this development impacts cancer diagnosis and reporting.

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.

Amide Proton Transfer Could Provide More Accurate Lesion Characterization in the Transition Zone of the Prostate

BACKGROUND

There is an overlap comparing transition zone prostate cancer (TZ PCa) and benign prostatic hyperplasia (BPH) on T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI), creating additional challenges for assessment of TZ tumors on MRI.

PURPOSE

To evaluate whether amide proton transfer-weighted (APTw) imaging provides new diagnostic ideas for TZ PCa.

STUDY TYPE

Prospective.

POPULATION

A total of 51 TZ PCa patients (age, 49-89), 44 stromal BPH (age, 57-92), and 45 glandular BPH patients (age, 56-92).

FIELD STRENGTH/SEQUENCE

A 3 T; T2WI turbo spin echo (TSE), quantitative T2*-weighted imaging, DWI echo planar imaging, 3D APTw TSE.

ASSESSMENT

Differences in APTw, apparent diffusion coefficient (ADC), and T2* among three lesions were compared by one-way analysis of variance (ANOVA). Regions of interest were drawn by two radiologists (X.Q.Z. and X.Y.Q., with 21 and 15 years of experience, respectively).

STATISTICAL TESTS

Multivariable logistic regression analyses; ANOVA with post hoc testing; receiver operator characteristic curve analysis; Delong test. Significance level: P < 0.05.

RESULTS

APTw among TZ PCa, stromal BPH, and glandular BPH (3.48% ± 0.83% vs. 2.76% ± 0.49% vs. 2.72% ± 0.45%, respectively) were significantly different except between stromal BPH and glandular BPH (P > 0.99). Significant differences were found in ADC (TZ PCa 0.76 ± 0.16 × 10^-3  mm² /sec vs. stromal BPH 0.91 ± 0.14 × 10^-3  mm² /sec vs. glandular BPH 1.08 ± 0.18 × 10^-3  mm² /sec) among three lesions. APTw (OR = 12.18, 11.80, respectively) and 1/ADC (OR = 703.87, 181.11, respectively) were independent predictors of TZ PCa from BPH and stromal BPH. The combination of APTw and ADC had better diagnostic performance in the identification of TZ PCa from BPH and stromal BPH.

DATA CONCLUSION

APTw imaging has the potential to be of added value to ADC in differentiating TZ PCa from BPH and stromal BPH.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Comparing Radiologist Performance in Diagnosing Clinically Significant Prostate Cancer with Multiparametric versus Hybrid Multidimensional MRI

Background Variability of acquisition and interpretation of prostate multiparametric MRI (mpMRI) persists despite implementation of the Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 due to the range of reader experience and subjectivity of lesion characterization. A quantitative method, hybrid multidimensional MRI (HM-MRI), may introduce objectivity. Purpose To compare performance, interobserver agreement, and interpretation time of radiologists using mpMRI versus HM-MRI to diagnose clinically significant prostate cancer. Materials and Methods In this retrospective analysis, men with prostatectomy or MRI-fused transrectal US biopsy-confirmed prostate cancer underwent mpMRI (triplanar T2-weighted, diffusion-weighted, and dynamic contrast-enhanced imaging) and HM-MRI (with multiple echo times and b value combinations) from August 2012 to February 2020. Four readers with 1-20 years of experience interpreted mpMRI and HM-MRI examinations independently, with a 4-week washout period between interpretations. PI-RADS score, lesion location, and interpretation time were recorded. mpMRI and HM-MRI interpretation time, interobserver agreement (Cronbach alpha), and performance of area under the receiver operating characteristic curve (AUC) analysis were compared for each radiologist with use of bootstrap analysis. Results Sixty-one men (mean age, 61 years ± 8 [SD]) were evaluated. Per-patient AUC was higher for HM-MRI for reader 4 compared with mpMRI (AUCs for readers 1-4: 0.61, 0.71, 0.59, and 0.64 vs 0.66, 0.60, 0.50, and 0.46; P = .57, .20, .32, and .04, respectively). Per-patient specificity was higher for HM-MRI for readers 2-4 compared with mpMRI (specificity for readers 1-4: 48%, 78%, 48%, and 46% vs 37%, 26%, 0%, and 7%; P = .34, P < .001, P < .001, and P < .001, respectively). Diagnostic performance improved for the reader least experienced with HM-MRI, reader 4 (AUC, 0.64 vs 0.46; P = .04). HM-MRI interobserver agreement (Cronbach alpha = 0.88 [95% CI: 0.82, 0.92]) was higher than that of mpMRI (Cronbach alpha = 0.26 [95% CI: 0.10, 0.52]; α > .60 indicates reliability; P = .03). HM-MRI mean interpretation time (73 seconds ± 43 [SD]) was shorter than that of mpMRI (254 seconds ± 133; P = .03). Conclusion Radiologists had similar or improved diagnostic performance, higher interobserver agreement, and lower interpretation time for clinically significant prostate cancer with hybrid multidimensional MRI than multiparametric MRI. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Turkbey in this issue.

Directional and inter-acquisition variability in diffusion-weighted imaging and editing for restricted diffusion

PURPOSE

To evaluate and quantify inter-directional and inter-acquisition variation in diffusion-weighted imaging (DWI) and emphasize signals that report restricted diffusion to enhance cancer conspicuity, while reducing the effects of local microscopic motion and magnetic field fluctuations.

METHODS

Ten patients with biopsy-proven prostate cancer were studied under an Institutional Review Board-approved protocol. Individual acquisitions of DWI signal intensities were reconstructed to calculate inter-acquisition distributions and their statistics, which were compared for healthy versus cancer tissue. A method was proposed to detect and filter the acquisitions affected by motion-induced signal loss. First, signals that reflect restricted diffusion were separated from the acquisitions that suffer from signal loss, likely due to microscopic motion, by imposing a cutoff value. Furthermore, corrected apparent diffusion coefficient maps were calculated by employing a weighted sum of the multiple acquisitions, instead of conventional averaging. These weights were calculated by applying a soft-max function to the set of acquisitions per-voxel, making the analysis immune to acquisitions with significant signal loss, even if the number of such acquisitions is high.

RESULTS

Inter-acquisition variation is much larger than the Rician noise variance, local spatial variations, and the estimates of diffusion anisotropy based on the current data, as well as the published values of anisotropy. The proposed method increases the contrast for cancers and yields a sensitivity of98 . 8 % $$ 98.8\% $$ with a false positive rate of3 . 9 % $$ 3.9\% $$ .

CONCLUSION

Motion-induced signal loss makes conventional signal-averaging suboptimal and can obscure signals from areas with restricted diffusion. Filtering or weighting individual acquisitions prior to image analysis can overcome this problem.

Prostate MRI Qualification: AJR Expert Panel Narrative Review

Prostate MRI is now established as a first-line investigation for individuals presenting with suspected localized or locally advanced prostate cancer. Successful delivery of the MRI-directed pathway for prostate cancer diagnosis relies on high-quality imaging as well as the interpreting radiologist's experience and expertise. Radiologist certification in prostate MRI may help limit interreader variability, optimize outcomes, and provide individual radiologists with documentation of meeting predefined standards. This AJR Expert Panel Narrative Review summarizes existing certification proposals, recognizing variable progress across regions in establishing prostate MRI certification programs. To our knowledge, Germany is the only country with a prostate MRI certification process that is currently available for radiologists. However, prostate MRI certification programs have also recently been proposed in the United States and United Kingdom and by European professional society consensus panels. Recommended qualification processes entail a multifaceted approach, incorporating components such as minimum case numbers, peer learning, course participation, continuing medical education credits, and feedback from pathology results. Given the diversity in health care systems, including in the provision and availability of MRI services, national organizations will likely need to take independent approaches to certification and accreditation. The relevant professional organizations should begin developing these programs or continue existing plans for implementation.

Radiomics in PI-RADS 3 Multiparametric MRI for Prostate Cancer Identification: Literature Models Re-Implementation and Proposal of a Clinical-Radiological Model

PI-RADS 3 prostate lesions clinical management is still debated, with high variability among different centers. Identifying clinically significant tumors among PI-RADS 3 is crucial. Radiomics applied to multiparametric MR (mpMR) seems promising. Nevertheless, reproducibility assessment by external validation is required. We retrospectively included all patients with at least one PI-RADS 3 lesion (PI-RADS v2.1) detected on a 3T prostate MRI scan at our Institution (June 2016-March 2021). An MRI-targeted biopsy was used as ground truth. We assessed reproducible mpMRI radiomic features found in the literature. Then, we proposed a new model combining PSA density and two radiomic features (texture regularity (T2) and size zone heterogeneity (ADC)). All models were trained/assessed through 100-repetitions 5-fold cross-validation. Eighty patients were included (26 with GS ≥ 7). In total, 9/20 T2 features (Hector's model) and 1 T2 feature (Jin's model) significantly correlated to biopsy on our dataset. PSA density alone predicted clinically significant tumors (sensitivity: 66%; specificity: 71%). Our model obtained a sensitivity of 80% and a specificity of 76%. Standard-compliant works with detailed methodologies achieve comparable radiomic feature sets. Therefore, efforts to facilitate reproducibility are needed, while complex models and imaging protocols seem not, since our model combining PSA density and two radiomic features from routinely performed sequences appeared to differentiate clinically significant cancers.

COMPARISON OF GRADING ACCURACY OF PROSTATE CANCER IN SAMPLES ACQUIRED BY A TARGETED AND SYSTEMIC PROSTATE BIOPSY

Introduction

All malignancies, including prostate cancer, require accurate diagnosing and staging before making a treatment decision. The introduction of targeted biopsies based on prostate MRI findings has raised prostate biopsy accuracy. Guided biopsies target the tumor itself during the biopsy instead of the most common tumor sites as is the case with a systemic biopsy. Some studies report that targeted biopsies should lower prostate cancer biopsy undergrading and overgrading.

Goals

To determine the incidence of prostate cancer biopsy undergrading in patients who underwent a classic systemic biopsy compared to patients who underwent a mpMRI cognitive targeted biopsy.

Materials and methods

We identified the patients from our database who underwent a radical prostatectomy at our institution from January 1st, 2021, to June 30th, 2021.There were 112 patients identified. Patients were stratified into two groups based on the type of biopsy that confirmed prostate cancer. The mpMRI (N=50) group had a mpMRI cognitive guided transrectal ultrasound (TRUS) prostate biopsy performed, and the non-mpMRI group (N=62) received a classic, systemic TRUS biopsy. We compared the biopsy results with the final pathological results, and searched for undergrading or overgrading in the biopsies compared to the final histological report.

Results

The undergrading was found in 17,7% (N=11) cases in the non-mpMRI group and in 12,0% (N=6) of cases in the mpMRI group (p=0,02, Mann-Whitney U test). No overgrading was found in our cohort. All cases of undergrading had Grade Group 1 in the biopsy report and Grade Group 2 in the final specimen report. The charasteristics of patients are listed in Table 1.

Discussion and conclusion

In our cohort, the patients who underwent a mpMRI targeted biopsy had a lower undergrading incidence. During a systemic TRUS biopsy, the urologist targets the areas of the prostate where cancer is most commonly located, which is usually the peripheral zone of the prostate. Since different areas of the tumor have different areas of differentiation, only a low-grade part of the tumor is sometimes biopsied, which results in a sampling error. Once the prostate is removed, the whole tumor is analyzed, so the obtained pathological results related to the removed prostate are far more accurate than the analysis of prostate cores obtained by biopsy.

Comparative Performance of Deep Learning and Radiologists for the Diagnosis and Localization of Clinically Significant Prostate Cancer at MRI: A Systematic Review

Background: Deep learning (DL)-based models have demonstrated an ability to automatically diagnose clinically significant prostate cancer (PCa) on MRI scans and are regularly reported to approach expert performance. The aim of this work was to systematically review the literature comparing deep learning (DL) systems to radiologists in order to evaluate the comparative performance of current state-of-the-art deep learning models and radiologists. Methods: This systematic review was conducted in accordance with the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Studies investigating DL models for diagnosing clinically significant (cs) PCa on MRI were included. The quality and risk of bias of each study were assessed using the checklist for AI in medical imaging (CLAIM) and QUADAS-2, respectively. Patient level and lesion-based diagnostic performance were separately evaluated by comparing the sensitivity achieved by DL and radiologists at an identical specificity and the false positives per patient, respectively. Results: The final selection consisted of eight studies with a combined 7337 patients. The median study quality with CLAIM was 74.1% (IQR: 70.6–77.6). DL achieved an identical patient-level performance to the radiologists for PI-RADS ≥ 3 (both 97.7%, SD = 2.1%). DL had a lower sensitivity for PI-RADS ≥ 4 (84.2% vs. 88.8%, p = 0.43). The sensitivity of DL for lesion localization was also between 2% and 12.5% lower than that of the radiologists. Conclusions: DL models for the diagnosis of csPCa on MRI appear to approach the performance of experts but currently have a lower sensitivity compared to experienced radiologists. There is a need for studies with larger datasets and for validation on external data.

Canadian Association of Radiologists Prostate MRI White Paper

Prostate cancer is the most common malignancy and the third most common cause of death in Canadian men. In light of evolving diagnostic pathways for prostate cancer and the increased use of MRI, which now includes its use in men prior to biopsy, the Canadian Association of Radiologists established a Prostate MRI Working Group to produce a white paper to provide recommendations on establishing and maintaining a Prostate MRI Programme in the context of the Canadian healthcare system. The recommendations, which are based on available scientific evidence and/or expert consensus, are intended to maintain quality in image acquisition, interpretation, reporting and targeted biopsy to ensure optimal patient care. The paper covers technique, reporting, quality assurance and targeted biopsy considerations and includes appendices detailing suggested reporting templates, quality assessment tools and sample image acquisition protocols relevant to the Canadian healthcare context.

The role of MRI in prostate cancer: current and future directions

There has been an increasing role of magnetic resonance imaging (MRI) in the management of prostate cancer. MRI already plays an essential role in the detection and staging, with the introduction of functional MRI sequences. Recent advancements in radiomics and artificial intelligence are being tested to potentially improve detection, assessment of aggressiveness, and provide usefulness as a prognostic marker. MRI can improve pretreatment risk stratification and therefore selection of and follow-up of patients for active surveillance. MRI can also assist in guiding targeted biopsy, treatment planning and follow-up after treatment to assess local recurrence. MRI has gained importance in the evaluation of metastatic disease with emerging technology including whole-body MRI and integrated positron emission tomography/MRI, allowing for not only better detection but also quantification. The main goal of this article is to review the most recent advances on MRI in prostate cancer and provide insights into its potential clinical roles from the radiologist's perspective. In each of the sections, specific roles of MRI tailored to each clinical setting are discussed along with its strengths and weakness including already established material related to MRI and the introduction of recent advancements on MRI.

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.

VI-RADS score system - A primer for urologists

Bladder cancer (BCa) is one of the most common cancers worldwide and is also considered to be one of the most relapsing and aggressive neoplasms. About 30% of patients will present with muscle invasive disease, which is associated with a higher risk for metastatic disease. The aim of this article is to review the state of art imaging in Radiology, while providing a complete guide to urologists, with case examples, for the rationale of the development of the Vesical Imaging Reporting and Data System (VI-RADS), a scoring system emphasizing a standardized approach to multiparametric Magnetic Resonance Imaging (mpMRI) acquisition, interpretation, and reporting for BCa. Also, we examine relevant external validation studies and the consolidated literature of mpMRI for bladder cancer. In addition, this article discusses some of the potential clinical implications of this scoring system for disease management and follow-up.

Prostate MRI quality: clinical impact of the PI-QUAL score in prostate cancer diagnostic work-up

OBJECTIVE

To assess the reproducibility and impact of prostate imaging quality (PI-QUAL) scores in a clinical cohort undergoing prostate multiparametric MRI.

METHODS

PI-QUAL scores were independently recorded by three radiologists (two senior, one junior). Readers also recorded whether MRI was sufficient to rule-in/out cancer and if repeat imaging was required. Inter-reader agreement was assessed using Cohen's κ. PI-QUAL scores were further correlated to PI-RADS score, number of biopsy procedures, and need for repeat imaging.

RESULTS

Image quality was sufficient (≥PI-QUAL-3) in 237/247 (96%) and optimal (≥PI-QUAL-4) in 206/247 (83%) of males undergoing 3T-MRI. Overall PI-QUAL scores showed moderate inter-reader agreement for senior (K = 0.51) and junior-senior readers (K = 0.47), with DCE showing highest agreement (K = 0.47). With PI-QUAL-5 studies, the negative MRI calls increased from 50 to 87% and indeterminate PI-RADS-3 rates decreased from 31.8. to 10.4% compared to lower quality PI-QUAL-3 studies. More patients with PI-QUAL scores 1-3 underwent biopsy for negative (47%) and indeterminate probability (100%) MRIs compared to PI-QUAL score 4-5 (30 and 75%, respectively). Ability to rule-in cancer increased with PI-QUAL score, from 50% at PI-QUAL 1-2 to 90% for PI-QUAL 4-5, with a similarly, but greater effect for ruling-out cancer and at a lower threshold, from 0% for scans of PI-QUAL 1-2 to 67.1% for PI-QUAL 4 and 100% for PI-QUAL-5.

CONCLUSION

Higher PI-QUAL scores for image quality are associated with decreased uncertainty in MRI decision-making and improved efficiency of diagnostic pathway delivery.

ADVANCES IN KNOWLEDGE

This study demonstrates moderate inter-reader agreement for PI-QUAL scoring and validates the score in a clinical setting, showing correlation of image quality to certainty of decision making and clinical outcomes of repeat imaging and biopsy of low-to-intermediate risk cases.

A prognostic hypoxia gene signature with low heterogeneity within the dominant tumour lesion in prostate cancer patients

BACKGROUND

Gene signatures measured in a biopsy have been proposed as hypoxia biomarkers in prostate cancer. We assessed a previously developed signature, and aimed to determine its relationship to hypoxia and its heterogeneity within the dominant (index) lesion of prostate cancer.

METHODS

The 32-gene signature was assessed from gene expression data of 141 biopsies from the index lesion of 94 patients treated with prostatectomy. A gene score calculated from the expression levels was applied in the analyses. Hypoxic fraction from pimonidazole immunostained whole-mount and biopsy sections was used as reference standard for hypoxia.

RESULTS

The gene score was correlated with pimonidazole-defined hypoxic fraction in whole-mount sections, and the two parameters showed almost equal association with clinical markers of tumour aggressiveness. Based on the gene score, incorrect classification according to hypoxic fraction in whole-mount sections was seen in one third of the patients. The incorrect classifications were apparently not due to intra-tumour heterogeneity, since the score had low heterogeneity compared to pimonidazole-defined hypoxic fraction in biopsies. The score showed prognostic significance in uni-and multivariate analysis in independent cohorts.

CONCLUSIONS

Our signature from the index lesion reflects tumour hypoxia and predicts prognosis in prostate cancer, independent of intra-tumour heterogeneity in pimonidazole-defined hypoxia.

Utility of Clinical-Radiomic Model to Identify Clinically Significant Prostate Cancer in Biparametric MRI PI-RADS V2.1 Category 3 Lesions

Purpose

To determine the predictive performance of the integrated model based on clinical factors and radiomic features for the accurate identification of clinically significant prostate cancer (csPCa) among Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions.

Materials and Methods

A retrospective study of 103 patients with PI-RADS 3 lesions who underwent pre-operative 3.0-T MRI was performed. Patients were randomly divided into the training set and the testing set at a ratio of 7:3. Radiomic features were extracted from axial T2WI, diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) images of each patient. The minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) feature selection methods were used to identify the radiomic features and construct a radiomic model for csPCa identification. Moreover, multivariable logistic regression analysis was used to integrate the clinical factors with radiomic feature model to further improve the accuracy of csPCa identification, and the two are presented in the form of normogram. The performance of the integrated model was compared with radiomic model and clinical model on testing set.

Results

A total of four radiomic features were selected and used for radiomic model construction producing a radiomic score (Radscore). Radscore was significantly different between the csPCa and the non-csPCa patients (training set: p < 0.001; testing set: p = 0.035). Multivariable logistic regression analysis showed that age and PSA could be used as independent predictors for csPCa identification. The clinical–radiomic model produced the receiver operating characteristic (ROC) curve (AUC) in the testing set was 0.88 (95%CI, 0.75–1.00), which was similar to clinical model (AUC = 0.85; 95%CI, 0.52–0.90) (p = 0.048) and higher than the radiomic model (AUC = 0.71; 95%CI, 0.68–1.00) (p < 0.001). The decision curve analysis implies that the clinical–radiomic model could be beneficial in identifying csPCa among PI-RADS 3 lesions.

Conclusion

The clinical–radiomic model could effectively identify csPCa among biparametric PI-RADS 3 lesions and thus could help avoid unnecessary biopsy and improve the life quality of patients.

MRI-detectability and histological factors of prostate cancer including intraductal carcinoma and cribriform pattern

BACKGROUND

Histopathological characteristics affecting the detectability of clinically significant prostate cancer (csPCa) on magnetic resonance imaging (MRI) remain unclear. This study aimed to compare the histopathology between MRI-detectable and MRI-undetectable cancers, emphasizing intraductal carcinoma of the prostate (IDC-P) and predominant Gleason pattern 4 subtype.

METHODS

This single-center retrospective study enrolled 153 consecutive patients with 191 lesions who underwent preoperative multiparametric MRI and subsequent radical prostatectomy. MRI/histopathological findings and area fractions of histological components (cancer cells, stroma, and luminal spaces) of MRI-detectable and MRI-undetectable cancers were compared. Data were analyzed using Fisher's exact, independent t, or Mann-Whitney U tests.

RESULTS

Overall, 148 (77%) and 43 (23%) cancers were MRI-detectable and MRI-undetectable, respectively. MRI-detectable cancers were significantly larger than MRI-undetectable cancers (p = 0.03). The percentage of lesions in Grade Group 3 or higher was significantly higher among MRI-detectable cancers than among MRI-undetectable cancers (p = 0.02). MRI detectability of csPCa was associated with increases in relative area fractions of cancer cells (p < 0.001) and decreases in those of stroma (p < 0.001) and luminal spaces (p < 0.001) in prostate cancer (PCa) than the percentage of Gleason pattern 4 (p = 0.09). The percentage of lesions containing IDC-P was similar for MRI-detectable and MRI-undetectable cancers (40% vs. 33%; p = 0.48). The distribution of cribriform gland subtypes was not significantly different between MRI-detectable and MRI-undetectable Gleason pattern 4 subtype cancers (p > 0.99). Contrarily, the ratio of fused gland subtype was significantly higher in MRI-detectable than in MRI-undetectable cancers (p = 0.03). Furthermore, the ratio of poorly-formed gland subtype was significantly higher in MRI-undetectable than in MRI-detectable cancers (p = 0.01).

CONCLUSIONS

MRI detectability of csPCa is strongly associated with the relative area fractions of cancer cells, stroma, and luminal spaces in PCa rather than conventional histopathological parameters. Neither the presence nor the percentage of IDC-P affected MRI detectability.

Comparison of diagnostic performance and inter-reader agreement between PI-RADS v2.1 and PI-RADS v2: systematic review and meta-analysis

OBJECTIVES

To perform a systematic review and meta-analysis comparing diagnostic performance and inter reader agreement between PI-RADS v. 2.1 and PI-RADS v. 2 in the detection of clinically significant prostate cancer (csPCa).

METHODS

A systematic review was performed, searching the major biomedical databases (Medline, Embase, Scopus), using the keywords "PIRADS 2.1" or "PI RADS 2.1" or "PI-RADS 2.1". Studies reporting on head-to-head diagnostic comparison between PI-RADS v. 2.1 and v. 2 were included. Pooled sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were compared between PI-RADS v. 2.1 and v. 2. Summary receiver operator characteristic graphs were plotted. Analysis was performed for whole gland, and pre-planned subgroup analysis was performed by tumour location (whole gland vs transition zone (TZ)), high b-value DWI (b-value ≥1400 s/mm2), and reader experience (<5 years vs ≥5 years with prostate MRI interpretation). Inter-reader agreement and pooled rates of csPCa for PI-RADS 1-3 lesions were compared between PI-RADS v. 2.1 and v. 2. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool v. 2 (QUADAS-2).

RESULTS

Eight studies (1836 patients, 1921 lesions) were included. Pooled specificity for PI-RADS v. 2.1 was significantly lower than PI-RADS v. 2 for whole gland (0.62 vs 0.66, p = 0.02). Pooled sensitivities, PPVs and NPVs were not significantly different (p = 0.17, 0.31, 0.41). Pooled specificity for PI-RADS v. 2.1 was significantly lower than PI-RADS v. 2 for TZ only (0.67 vs 0.72, p = 0.01). Pooled sensitivities, PPVs and NPVs were not significantly different (p = 0.06, 0.36, 0.17). Amongst studies utilising diffusion-weighted imaging with highest b-value of ≥1400 s/mm2, pooled sensitivities, specificities, PPVs and NPVs were not significantly different (p = 0.52, 0.4, 0.5, 0.47). There were no significant differences in pooled sensitivities, specificities, PPVs and NPVs between PI-RADS v. 2.1 and PI-RADS v. 2 for less-experienced readers (p = 0.65, 0.37, 0.65, 0.81) and for more experienced readers (p = 0.57, 0.90, 0.91, 0.65). For PI-RADS v. 2.1 alone, there were no significant differences in pooled sensitivity, specificity, PPV and NPV between less and more experienced readers (p = 0.38, 0.70, 1, 0.48). Inter-reader agreement was moderate to substantial for both PI-RADS v. 2.1 and v. 2. There were no significant differences between pooled csPCa rates between PI-RADS v. 2.1 and v. 2 for PI-RADS 1-2 lesions (6.6% vs  7.3%, p = 0.53), or PI-RADS 3 lesions (24.1% vs  26.8%, p = 0.28).

CONCLUSIONS

Diagnostic performance and inter-reader agreement for PI-RADS v. 2.1 is comparable to PI-RADS v. 2, however the significantly lower specificity of PI-RADS v. 2.1 may result in increased number of unnecessary biopsies.

ADVANCES IN KNOWLEDGE

1. Compared to PI-RADS v. 2, PI-RADS v. 2.1 has a non-significantly higher sensitivity but a significantly lower specificity for detection of clinically significant prostate cancer.2. PI-RADS v. 2.1 could potentially result in considerable increase in number of negative targeted biopsy rates for PI-RADS 3 lesions, which could have been potentially avoided.

A narrative review of MRI acquisition for MR-guided-radiotherapy in prostate cancer

Magnetic resonance guided radiotherapy (MRgRT), enabled by the clinical introduction of the integrated MRI and linear accelerator (MR-LINAC), is a novel technique for prostate cancer (PCa) treatment, promising to further improve clinical outcome and reduce toxicity. The role of prostate MRI has been greatly expanded from the traditional PCa diagnosis to also PCa screening, treatment and surveillance. Diagnostic prostate MRI has been relatively familiar in the community, particularly with the development of Prostate Imaging - Reporting and Data System (PI-RADS). But, on the other hand, the use of MRI in the emerging clinical practice of PCa MRgRT, which is substantially different from that in PCa diagnosis, has been so far sparsely presented in the medical literature. This review attempts to give a comprehensive overview of MRI acquisition techniques currently used in the clinical workflows of PCa MRgRT, from treatment planning to online treatment guidance, in order to promote MRI practice and research for PCa MRgRT. In particular, the major differences in the MRI acquisition of PCa MRgRT from that of diagnostic prostate MRI are demonstrated and explained. Limitations in the current MRI acquisition for PCa MRgRT are analyzed. The future developments of MRI in the PCa MRgRT are also discussed.

Deep Learning Reconstruction of Diffusion-weighted MRI Improves Image Quality for Prostatic Imaging

Background Deep learning reconstruction (DLR) may improve image quality. However, its impact on diffusion-weighted imaging (DWI) of the prostate has yet to be assessed. Purpose To determine whether DLR can improve image quality of diffusion-weighted MRI at b values ranging from 1000 sec/mm² to 5000 sec/mm² in patients with prostate cancer. Materials and Methods In this retrospective study, images of the prostate obtained at DWI with a b value of 0 sec/mm², DWI with a b value of 1000 sec/mm² (DWI₁₀₀₀), DWI with a b value of 3000 sec/mm² (DWI₃₀₀₀), and DWI with a b value of 5000 sec/mm² (DWI₅₀₀₀) from consecutive patients with biopsy-proven cancer from January to June 2020 were reconstructed with and without DLR. Image quality was assessed using signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) from region-of-interest analysis and qualitatively assessed using a five-point visual scoring system (1 [very poor] to 5 [excellent]) for each high-b-value DWI sequence with and without DLR. The SNR, CNR, and visual score for DWI with and without DLR were compared with the paired t test and the Wilcoxon signed rank test with Bonferroni correction, respectively. Apparent diffusion coefficients (ADCs) from DWI with and without DLR were also compared with the paired t test with Bonferroni correction. Results A total of 60 patients (mean age, 67 years; age range, 49-79 years) were analyzed. DWI with DLR showed significantly higher SNRs and CNRs than DWI without DLR (P < .001); for example, with DWI₁₀₀₀ the mean SNR was 38.7 ± 0.6 versus 17.8 ± 0.6, respectively (P < .001), and the mean CNR was 18.4 ± 5.6 versus 7.4 ± 5.6, respectively (P < .001). DWI with DLR also demonstrated higher qualitative image quality than DWI without DLR (mean score: 4.8 ± 0.4 vs 4.0 ± 0.7, respectively, with DWI₁₀₀₀ [P = .001], 3.8 ± 0.7 vs 3.0 ± 0.8 with DWI₃₀₀₀ [P = .002], and 3.1 ± 0.8 vs 2.0 ± 0.9 with DWI₅₀₀₀ [P < .001]). ADCs derived with and without DLR did not differ substantially (P > .99). Conclusion Deep learning reconstruction improves the image quality of diffusion-weighted MRI scans of prostate cancer with no impact on apparent diffusion coefficient quantitation with a 3.0-T MRI system. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Turkbey in this issue.

Risk-based MRI-directed diagnostic pathway outperforms non-risk-based pathways in suspected prostate cancer biopsy-naïve men: a large cohort validation study

OBJECTIVES

To investigate and compare the performance of different proposed diagnostic pathways in a cohort of biopsy-naïve men at risk for prostate cancer (PCa), in terms of biopsy avoidance, accurate diagnosis of clinically significant prostate cancer (csPCa), and reduction in overdiagnosis of clinically insignificant cancer (cisPCa), with particular focus on a recently suggested "risk-based" MRI-directed diagnostic pathway.

METHODS

Single-center, retrospective cohort study, including 499 biopsy-naïve men at risk for PCa. All men underwent PI-RADS-compliant prostate MRI, transrectal ultrasound fusion-guided targeted (TBx), and systematic biopsy (SBx). Five diagnostic pathways were retrospectively evaluated and compared for. Outcome measures were biopsy avoidance, combined with missed csPCa and detected cisPCa. csPCa and cisPCa were defined as ISUP grade group ≥ 2 and grade = 1, respectively. Chi-square test was used for statistical analysis. Decision curve analyses were used to compare the benefits of the pathways across a range of biopsy thresholds.

RESULTS

The prevalence (detection-focused [reference] pathway) of csPCa and cisPCa was 52.9% (264/499) and 23.0% (115/499). MRI-focused pathway (no biopsy in PI-RADS 1-2 men) did not significantly reduce ISUP ≥ 2 cancer detection (52.1% (260/499); p = 0.13), but significantly reduced ISUP 1 cancers diagnosed (20.6% (103/499); p < 0.01), and biopsy avoidance was 11.8% (59/499). The risk-based MRI-directed pathway (no biopsy in low-risk PI-RADS 1-3 men) resulted in a small reduction of ISUP ≥ 2 diagnosed (51.7% (258/499); p = 0.04), however non-significant when compared to MRI-focused pathway (p = 0.625). Moreover, the risk-based pathway further reduced detection of ISUP 1 (18.6% (93/499); p < 0.01), and biopsy avoidance was 19.2% (96/499). Decision curve analysis showed maximized net benefit of the risk-based pathway, for the range of threshold probabilities between 6.25 and 65%.

CONCLUSION

The risk-based MRI-directed pathway for prostate cancer diagnosis was optimal in balancing accurate diagnosis, reducing overdiagnosis, and maximizing biopsy avoidance. This substantial evidence should inform guideline recommendations towards using "risk-based" MRI-directed biopsy decisions in biopsy-naïve men at risk of significant prostate cancer.

KEY POINTS

• Our study recognizes the added value of prostate MRI and MR-targeted biopsies in order to propose clinical diagnostic pathways for prostate cancer, towards maximizing the potential avoidance of unnecessary biopsies, while maintaining optimal detection rate of clinically significant prostate cancer. • The risk-based MRI-directed pathway incorporates risk factors such as PSA density, digital rectal examination, and family history to further refine the initial stratification of patients based on PI-RADS scores. • In this study, the risk-based pathway had the most optimal performance in terms of combination of outcomes, with the highest rate of biopsy avoidance (19.2%), while keeping a high detection rate of clinically significant prostate cancer (51.7%), when compared to the reference standard (52.9%).

Investigating the heterogeneity of viscoelastic properties in prostate cancer using MR elastography at 9.4T in fresh prostatectomy specimens

PURPOSE

To quantify the heterogeneity of viscoelastic tissue properties in prostatectomy specimens from men with prostate cancer (PC) using MR elastography (MRE) with histopathology as reference.

METHODS

Twelve fresh prostatectomy specimens were examined in a preclinical 9.4T MRI scanner. Maps of the complex shear modulus (|G*| in kPa) with its real and imaginary part (G' and G" in kPa) were calculated at 500 Hz. Prostates were divided into 12 segments for segment-wise measurement of viscoelastic properties and histopathology. Coefficients of variation (CVs in %) were calculated for quantification of heterogeneity.

RESULTS

Group-averaged values of cancerous vs. benign segments were significantly increased: |G*| of 12.13 kPa vs. 6.14 kPa, G' of 10.84 kPa vs. 5.44 kPa and G" of 5.45 kPa vs. 2.92 kPa, all p < 0.001. In contrast, CVs were significantly increased for benign segments: 23.59% vs. 26.32% (p = 0.014) for |G*|, 27.05% vs. 37.84% (p < 0.003) for G', and 36.51% vs. 50.37% (p = 0.008) for G".

DISCUSSION

PC is characterized by a stiff yet homogeneous biomechanical signature, which may be due to the unique nondestructive growth pattern of PC with intervening stroma, providing a rigid scaffold in the affected area. In turn, increased heterogeneity in benign prostate segments may be attributable to the presence of different prostate zones with involvement by specific nonmalignant pathology.

Minimally Invasive Procedures in the Diagnosis and Treatment of Localized Prostate Cancer: an Interventional Radiologist's Perspective

PURPOSE OF REVIEW

Minimal invasive procedures, including targeted biopsy (TB) and focal therapy (FT), are increasingly used in diagnosis and treatment of localized prostate cancer. Here, we review the current role of these procedures, from a perspective of an interventional radiologist.

RECENT FINDINGS

TB is an established part of current guidelines for diagnosis of PCa. Several modalities of FT are gaining prevalence in recent years, as a tissue-preserving alternative for definitive treatment of localized PCa. FT is currently at early research stages, offered to selected patients in clinical trials settings. TB and FT are minimally invasive procedures used by multidisciplinary teams for diagnosis and treatment of localized PCa.

Classification of Clinically Significant Prostate Cancer on Multi-Parametric MRI: A Validation Study Comparing Deep Learning and Radiomics

The computer-aided analysis of prostate multiparametric MRI (mpMRI) could improve significant-prostate-cancer (PCa) detection. Various deep-learning- and radiomics-based methods for significant-PCa segmentation or classification have been reported in the literature. To be able to assess the generalizability of the performance of these methods, using various external data sets is crucial. While both deep-learning and radiomics approaches have been compared based on the same data set of one center, the comparison of the performances of both approaches on various data sets from different centers and different scanners is lacking. The goal of this study was to compare the performance of a deep-learning model with the performance of a radiomics model for the significant-PCa diagnosis of the cohorts of various patients. We included the data from two consecutive patient cohorts from our own center (n = 371 patients), and two external sets of which one was a publicly available patient cohort (n = 195 patients) and the other contained data from patients from two hospitals (n = 79 patients). Using multiparametric MRI (mpMRI), the radiologist tumor delineations and pathology reports were collected for all patients. During training, one of our patient cohorts (n = 271 patients) was used for both the deep-learning- and radiomics-model development, and the three remaining cohorts (n = 374 patients) were kept as unseen test sets. The performances of the models were assessed in terms of their area under the receiver-operating-characteristic curve (AUC). Whereas the internal cross-validation showed a higher AUC for the deep-learning approach, the radiomics model obtained AUCs of 0.88, 0.91 and 0.65 on the independent test sets compared to AUCs of 0.70, 0.73 and 0.44 for the deep-learning model. Our radiomics model that was based on delineated regions resulted in a more accurate tool for significant-PCa classification in the three unseen test sets when compared to a fully automated deep-learning model.

Utility of machine learning of apparent diffusion coefficient (ADC) and T2-weighted (T2W) radiomic features in PI-RADS version 2.1 category 3 lesions to predict prostate cancer diagnosis

PURPOSE

To evaluate if machine learning (ML) of radiomic features extracted from apparent diffusion coefficient (ADC) and T2-weighted (T2W) MRI can predict prostate cancer (PCa) diagnosis in Prostate Imaging-Reporting and Data System (PI-RADS) version 2.1 category 3 lesions.

METHODS

This multi-institutional review board-approved retrospective case-control study evaluated 158 men with 160 PI-RADS category 3 lesions (79 peripheral zone, 81 transition zone) diagnosed at 3-Tesla MRI with histopathology diagnosis by MRI-TRUS-guided targeted biopsy. A blinded radiologist confirmed PI-RADS v2.1 score and segmented lesions on axial T2W and ADC images using 3D Slicer, extracting radiomic features with an open-source software (Pyradiomics). Diagnostic accuracy for (1) any PCa and (2) clinically significant (CS; International Society of Urogenital Pathology Grade Group ≥ 2) PCa was assessed using XGBoost with tenfold cross -validation.

RESULTS

From 160 PI-RADS 3 lesions, there were 50.0% (80/160) PCa, including 36.3% (29/80) CS-PCa (63.8% [51/80] ISUP 1, 23.8% [19/80] ISUP 2, 8.8% [7/80] ISUP 3, 3.8% [3/80] ISUP 4). The remaining 50.0% (80/160) lesions were benign. ML of all radiomic features from T2W and ADC achieved area under receiver operating characteristic curve (AUC) for diagnosis of (1) CS-PCa 0.547 (95% Confidence Intervals 0.510-0.584) for T2W and 0.684 (CI 0.652-0.715) for ADC and (2) any PCa 0.608 (CI 0.579-0.636) for T2W and 0.642 (CI 0.614-0.0.670) for ADC.

CONCLUSION

Our results indicate ML of radiomic features extracted from T2W and ADC achieved at best moderate accuracy for determining which PI-RADS category 3 lesions represent PCa.

Results from a PI-RADS-based MRI-directed diagnostic pathway for biopsy-naive patients in a non-university hospital

Purpose

To assess the safety and performance of a MRI-directed diagnostic pathway for patients with first-time suspicion of prostate cancer in a non-university hospital.

Methods

Between May 2017 and December 2018 all biopsy-naive patients examined in our hospital followed a MRI-directed diagnostic work-up algorithm based on PI-RADS score. In short, PI-RADS 1–2 was generally not biopsied and PI-RADS 3–5 was reviewed by a multidisciplinary team. Patients with PI-RADS 4-5 were all referred to biopsy, either transrectal ultrasound-guided biopsy or MRI in-bore biopsy for small tumors and for sites difficult to access. PI-RADS scores were compared to the histopathology from biopsies and surgical specimens for patients who had prostatectomy. Non-biopsied patients were referred to a safety net monitoring regimen.

Results

Two hundred and ninety-eight men were enrolled. 97 (33%) had PI-RADS 1–2, 44 (15%) had PI-RADS 3, and 157 (53%) had PI-RADS 4–5. 116 (39%) of the patients avoided biopsy. None of these were diagnosed with significant cancer within 2–3.5 years of safety net monitoring. Almost all high ISUP grade groups (≥ 3) were in the PI-RADS 4–5 category (98%). Prostatectomy specimens and systematic biopsies from MRI-negative areas indicated that very few clinically significant cancers were missed by the MRI-directed diagnostic pathway.

Conclusion

Our findings add to evidence that a MRI-directed diagnostic pathway can be safely established in a non-university hospital. The pathway reduced the number of biopsies and reliably detected the site of the most aggressive cancers.

Graphic abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s00261-021-03249-8.

Fast T2-Weighted Imaging With Deep Learning-Based Reconstruction: Evaluation of Image Quality and Diagnostic Performance in Patients Undergoing Radical Prostatectomy

BACKGROUND

Deep learning-based reconstruction (DLR) can potentially improve image quality by reduction of noise, thereby enabling fast acquisition of magnetic resonance imaging (MRI). However, a systematic evaluation of image quality and diagnostic performance of MRI using short acquisition time with DLR has rarely been investigated in men with prostate cancer.

PURPOSE

To assess the image quality and diagnostic performance of MRI using short acquisition time with DLR for the evaluation of extraprostatic extension (EPE).

STUDY TYPE

Retrospective.

POPULATION

One hundred and nine men.

FIELD STRENGTH/SEQUENCE

3 T; turbo spin echo T2-weighted images (T2WI), echo-planar diffusion-weighted, and spoiled gradient echo dynamic contrast-enhanced images.

ASSESSMENT

To compare image quality, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) and subjective analysis using Likert scales on three T2WIs (MRI using conventional acquisition time, MRI using short acquisition time [fast MRI], and fast MRI with DLR) were performed. The diagnostic performance for EPE was evaluated by three independent readers.

STATISTICAL TESTS

SNR, CNR, and image quality scores across the three imaging protocols were compared using Friedman tests. The diagnostic performance for EPE was assessed using the area under receiver operating characteristic curves (AUCs). P < 0.05 was considered statistically significant.

RESULTS

Fast MRI with DLR demonstrated significantly higher SNR (mean ± SD, 14.7 ± 6.8 vs. 8.8 ± 4.9) and CNR (mean ± SD, 6.5 ± 6.3 vs. 3.4 ± 3.6) values and higher image quality scores (median, 4.0 vs. 3.0 for three readers) than fast MRI. The AUCs for EPE were significantly higher with the use of DLR (0.86 vs. 0.75 for reader 2 and 0.82 vs. 0.73 for reader 3) compared with fast MRI, whereas differences were not significant for reader 1 (0.81 vs. 0.74; P = 0.09).

DATA CONCLUSION

DLR may be useful in reducing the acquisition time of prostate MRI without compromising image quality or diagnostic performance.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 3.

Comparison of different thresholds of PSA density for risk stratification of PI-RADSv2.1 categories on prostate MRI

OBJECTIVES

To compare the effect of different PSA density (PSAD) thresholds on the accuracy for clinically significant prostate cancer (csPCa) of the Prostate Imaging Reporting And Data System v.2.1 (PI-RADSv2.1).

METHODS

We retrospectively included 123 biopsy-naïve men who underwent multiparametric magnetic resonance imaging (mpMRI) and transperineal mpMRI-targeted and systematic prostate biopsy between April 2019 and October 2020. mpMRI, obtained on a 3.0T magnet with a PI-RADSv2.1-compliant protocol, was read by two radiologists (>1500/>500 mpMRI examinations). csPCa was defined as International Society of Urogenital Pathology grading group ≥2. Receiver operating characteristic analysis was used to calculate per-index lesion sensitivity, specificity, and area under the curve (AUC) of PI-RADSv.2.1 categories after adjusting for PSAD ≥0.10,≥0.15, and ≥0.20 ng/mL ml^-1. Per-adjusted category cancer detection rate (CDR) was calculated, and decision analysis performed to compare PSAD-adjusted PI-RADSv.2.1 categories as a biopsy trigger.

RESULTS

csPCa prevalence was 43.9%. PSAD-adjustment increased the CDR of PI-RADSv2.1 category 4. Sensitivity/specificity/AUC were 92.6%/53.6%/0.82 for unadjusted PI-RADS, and 85.2%/72.4%/0.84, 62.9%/85.5%/0.83, and 92.4%/53.6%/0.82 when adjusting PI-RADS categories for a 0.10, 0.15, and 0.20 ng/ml ml^-1 PSAD threshold, respectively. Triggering biopsy for PI-RADS four lesions and PSAD ≥0.10 ng/mL ml^-1 was the strategy with greatest net benefit at 30 and 40% risk probability (0.307 and 0.271, respectively).

CONCLUSIONS

PI-RADSv2.1 category four with PSAD ≥0.10 ng/mL ml^-1 was the biopsy-triggering cut-off with the highest net benefit in the range of expected prevalence for csPCa.

ADVANCES IN KNOWLEDGE

0.10 ng/mL ml^-1 is the PSAD threshold with higher clinical utility in stratifying the risk for prostate cancer of PI-RADSv.2.1 categories.

Prostate heterogeneity correlates with clinical features on multiparametric MRI

BACKGROUND

Prostate heterogeneity on multi-parametric MRI (mpMRI) may confound image interpretation by obscuring lesions; systematic biopsy may have a role in this context.

PURPOSE

To determine if prostate heterogeneity (1) correlates with clinical risk factors for prostate cancer and (2) associates with higher-grade tumor in systematic biopsy (SB), compared with MRI-directed target biopsy (MDTB), i.e., SB > MDTB, thus providing a rationale for combined biopsy.

METHODS

IRB-approved retrospective study included men who underwent mpMRI, SB, and MDTB between 2015 and 2017. Regions of interest were applied to the entire transition zone (TZ) and peripheral zone (PZ) on T2-weighted imaging (T2WI), apparent diffusion coefficient maps (ADC), and early dynamic contrast-enhanced (DCE) images on the midgland slice. Mean signal intensities and standard deviation (SD) of each zone were calculated. SD served as a measure of heterogeneity. Spearman's rank correlation analysis of clinical and imaging variables was performed. Univariate logistic regression was used to determine if any imaging variable associated with SB > MDTB.

RESULTS

93 patients were included. Significant correlations included age and TZ ADC heterogeneity (rho = 0.34, p = 0.013), PSA density, and mean TZ ADC (rho = - 0.29, p = 0.049). PZ T2WI heterogeneity correlated with PZ ADC heterogeneity (rho = 0.48, p < 0.001). PZ DCE heterogeneity correlated with TZ DCE heterogeneity (rho = 0.46, p < 0.001). TZ ADC heterogeneity was associated with SB > MDTB prior to multiple comparison correction (p = 0.032). p value after correction was 0.24.

CONCLUSION

TZ ADC heterogeneity correlated with age and may reflect prostatic hyperplasia and/or prostate cancer. PZ heterogeneity, possibly a measure of prostatitis, correlated with TZ hyperplasia and/or inflammation. TZ ADC heterogeneity was associated with SB > MDTB with p value of < 0.05 prior to multiple correction; future investigation is needed to further elucidate significance of ADC heterogeneity in prostate imaging.

Localization of primary prostate cancer: FACBC PET/CT compared with multiparametric MRI using histopathology as reference standard

FACBC (anti-1-amino-3-¹⁸F-fluorocyclobutane-1-carboxylic acid) is a FDA-approved PET-tracer in patients with suspected recurrent prostate cancer. In the diagnostic work-up of primary prostate cancer, accurate localization of the index tumor is needed for image-guidance of biopsies. We therefore assessed the performance of FACBC PET/CT to detect and localize the index tumor and compared it to multiparametric MRI (mpMRI) using whole-mount histopathology as reference standard. Twenty-three patients with biopsy-proven prostate cancer had FACBC PET/CT and mpMRI within two weeks prior to prostatectomy. FACBC PET/CT was acquired as 14 minutes list-mode and re-binned into seven 2-minutes intervals. Static FACBC was the acquired data from 4-6 minutes, whereas the dynamic FACBC included all seven intervals. Two radiologists and two nuclear medicine physicians independently interpreted the images and consensus was reached in case of discrepancy. Static PET detected 15 of 23 (65%) of the index tumors, dynamic PET detected 14 of 22 (64%), and MRI detected 20 of 23 (87%). To assess the extent of the tumor, the interpreters delineated the tumor in a 12-regions sector-based template. True positive, true negative, false positive and false negative sectors were recorded based on the template drawings and whole-mount histopathology. Both static and dynamic FACBC PET had sensitivity of 40% and specificity of 99%, whereas MRI had sensitivity of 81% and specificity of 100%. Our data indicate that FACBC PET/CT may be useful but that mpMRI is better for localizing the index tumor in patients with prostate cancer.

[Integration of structured reporting into the routine radiological workflow]

Klinisches/methodisches Problem

Strukturierte Befundung ist seit Jahren eines der meist diskutierten Themen in der Radiologie. Aktuell herrscht ein Mangel an nutzerfreundlichen Softwarelösungen, welche in die bestehende IT-Infrastruktur der Kliniken und Praxen integriert sind und effiziente Dateneingaben erlauben.

Radiologische Standardverfahren

Radiologische Befunde werden meist als Freitext über Spracherkennungssysteme diktiert oder per Tastatur eingegeben. Zudem werden Textbausteine für die Erstellung von Normalbefunden verwendet und bei Bedarf durch Freitextinhalte ergänzt.

Methodische Innovationen

Softwarebasierte Befundungssysteme können Spracherkennungssysteme mit radiologischen Befundvorlagen in Form von interaktiven Entscheidungsbäumen vereinen. Eine technische Integration in RIS(Radiologieinformationssystem)-, PACS(„picture archiving and communication system“)- und AV(„advanced visualization“)-Systeme über Programmierschnittstellen und Interoperabilitätsstandards ermöglicht effiziente Prozesse und die Generierung maschinenlesbarer Befunddaten.

Leistungsfähigkeit

Strukturierte, semantisch annotierte klinische Daten, die über ein strukturiertes Befundungssystem erhoben werden, stehen unmittelbar für epidemiologische Datenauswertungen und kontinuierliches KI(Künstliche Intelligenz)-Training zur Verfügung.

Bewertung

Der Einsatz der strukturierten Befundung in der radiologischen Routinediagnostik ist mit einer initialen Umstellungsphase verbunden. Eine erfolgreiche Implementierung setzt eine enge Verzahnung der technischen Infrastruktur mehrerer Systeme voraus.

Empfehlung für die Praxis

Durch die Nutzung einer hybriden, softwarebasierten Befundungslösung können radiologische Befunde mit unterschiedlichen Stufen der Struktur generiert werden. Klinische Fragestellungen oder Informationen können aus klinischen Subsystemen semiautomatisch übertragen werden, um vermeidbare Fehler zu eliminieren und die Produktivität zu erhöhen.

Diagnostic Yield of Incremental Biopsy Cores and Second Lesion Sampling for In-Gantry MRI-Guided Prostate Biopsy

BACKGROUND. In-gantry MRI-guided biopsy (MRGB) of the prostate has been shown to be more accurate than other targeted prostate biopsy methods. However, the optimal number of cores to obtain during in-gantry MRGB remains undetermined. OBJECTIVE. The purpose of this study was to assess the diagnostic yield of obtaining an incremental number of cores from the primary lesion and of second lesion sampling during in-gantry MRGB of the prostate. METHODS. This retrospective study included 128 men with 163 prostate lesions who underwent in-gantry MRGB between 2016 and 2019. The men had a total of 163 lesions sampled with two or more cores, 121 lesions sampled with three or more cores, and 52 lesions sampled with four or more cores. A total of 40 men underwent sampling of a second lesion. Upgrade on a given core was defined as a greater International Society of Urological Pathology (ISUP) grade group (GG) relative to the previously obtained cores. Clinically significant prostate cancer (csPCa) was defined as ISUP GG 2 or greater. RESULTS. The frequency of any upgrade was 12.9% (21/163) on core 2 versus 10.7% (13/121) on core 3 (p = .29 relative to core 2) and 1.9% (1/52) on core 4 (p = .03 relative to core 3). The frequency of upgrade to csPCa was 7.4% (12/163) on core 2 versus 4.1% (5/121) on core 3 (p = .13 relative to core 2) and 0% (0/52) on core 4 (p = .07 relative to core 3). The frequency of upgrade on core 2 was higher for anterior lesions (p < .001) and lesions with a higher PI-RADS score (p = .007); the frequency of upgrade on core 3 was higher for apical lesions (p = .01) and lesions with a higher PI-RADS score (p = .01). Sampling of a second lesion resulted in an upgrade in a single patient (2.5%; 1/40); both lesions were PI-RADS category 4 and showed csPCa. CONCLUSION. When performing in-gantry MRGB of the prostate, obtaining three cores from the primary lesion is warranted to optimize csPCa diagnosis. Obtaining a fourth core from the primary lesion or sampling a second lesion has very low yield in upgrading cancer diagnoses. CLINICAL IMPACT. To reduce patient discomfort and procedure times, operators may refrain from obtaining more than three cores or second lesion sampling.