Comparing Micro-Ultrasound to mpMRI in Detecting Clinically Significant Prostate Cancer

2022 ◽  
Vol 3 (1) ◽  
Author(s):  
Guan Hee Tan ◽  
Brian Wodlinger ◽  
Christian Pavlovich ◽  
Laurence Klotz

Objectives To compare the performance of micro-ultrasound (mUS) with multi-parametric magnetic resonance imaging (mpMRI) in detecting clinically significant prostate cancer. Materials and Methods Retrospective data from consecutive patients with any indication for prostate biopsy in 2 academic institutions were included. The operator, blinded to mpMRI, would first scan the prostate and annotate any mUS lesions. All mUS lesions were biopsied. Any mpMRI lesions that did not correspond to mUS lesion upon unblinding were additionally biopsied. Grade group (GG) ≥ 2 was considered clinically significant cancer. The Jeffreys interval method was used to compare performance of mUS with mpMRI with the non-inferiority limit set at −5%. Results Imaging and biopsy were performed in 82 patients with 153 lesions. mUS had similar sensitivity to mpMRI (per-lesion analysis: 78.4% versus 72.5%), but lower specificity, positive predictive value, negative predictive value, and area under the curve. Micro-ultrasound found GG ≥ 2 in 13% of cases missed by mpMRI, while mpMRI found GG ≥ 2 in 11% of cases missed by mUS. The difference 0.020 (95% CI −0.070 to 0.110) was not statistically significant (P = 0.33). Conclusion The sensitivity of mUS in detecting GG ≥ 2 disease was similar to that of mpMRI, but the specificity was lower. Further evaluation with a larger sample size and experienced operators is warranted.

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 149-149
Author(s):  
Kamyar Ghabili ◽  
Matthew Swallow ◽  
Alfredo Suarez-Sarmiento ◽  
Jamil Syed ◽  
Michael Leapman ◽  
...  

149 Background: Prostate imaging reporting and data system (PI-RADS) category 3 (P3) provides an equivocal assessment of prostate cancer (PCa). We aimed to investigate imaging parameters including the ratio of P3-to-total regions of interest (ROI) that may assist in identifying P3 lesions harboring clinically-significant PCa (csPCa). Methods: We retrospectively queried our institutional MRI-ultrasound fusion biopsy database to identify patients without a prior diagnosis of PCa and with at least one P3 lesion on multi-parametric MRI (mpMRI) who underwent fusion biopsy during Feb 2015-Oct 2017. mpMRI findings were assessed, including prostate and P3 volumes, number of ROIs, and P3-to-total ROIs ratio (P3 lesion volume/total ROIs volumes). Logistic regression and area under the curve (AUC) were used to assess the ability of clinical and mpMRI characteristics to predict csPCa, defined as any grade group (GG)≥2 cancer or GG 1 cancer in > 2 cores or > 50% of any positive core from targeted biopsy of the P3 lesion. Results: Of 127 men with at least one P3 lesion, 29 (22.8%) had csPCa on the biopsy of P3 lesions. Patients with csPCa in P3 lesions had smaller prostate volumes (42.1mL vs 56mL, p = 0.003), lower P3/total ROIs ratios (0.46 vs 1.00, p < 0.001), and higher numbers of total ROIs (2 vs 1, p = 0.004). Compared with patients who had a P3/total ROIs ratio > 0.58, men with ratios < 0.58 were more likely to be diagnosed with csPCa in a P3 lesion (57.1% vs 9%, p < 0.001). Using a threshold of 0.58, P3/total ROIs ratio was 76.1% sensitive and 80.6% specific for csPCa in a P3 lesion. On multivariate analysis, smaller prostate volume (OR1.04, 95%CI 1.01-1.07, p = 0.01) and lower P3/total ROIs ratio (OR1.04, 95%CI 1.02-1.07, p = 0.003) were associated with an increased risk of csPCa in P3 lesions. P3/total ROIs ratio (AUC 0.73) and prostate volume (AUC 0.70) were superior to PSA density (AUC 0.65) for the prediction of csPCa in P3 lesions. Conclusions: Our data indicated that prostate volume and P3/total ROIs ratio outperformed PSA density in and were associated with detecting csPCa in P3 lesions. P3/total ROIs ratio could be used to avoid 80.6% of unnecessary biopsies of a P3 lesion in men with multiple ROIs.


2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Lili Xu ◽  
Gumuyang Zhang ◽  
Bing Shi ◽  
Yanhan Liu ◽  
Tingting Zou ◽  
...  

Abstract 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.


2021 ◽  
pp. 20210509
Author(s):  
Chau Hung Lee ◽  
Balamurugan Vellayappan ◽  
Cher Heng Tan

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.


2021 ◽  
pp. 205141582110237
Author(s):  
Enrico Checcucci ◽  
Sabrina De Cillis ◽  
Daniele Amparore ◽  
Diletta Garrou ◽  
Roberta Aimar ◽  
...  

Objectives: To determine if standard biopsy still has a role in the detection of prostate cancer or clinically significant prostate cancer in biopsy-naive patients with positive multiparametric magnetic resonance imaging. Materials and methods: We extracted, from our prospective maintained fusion biopsy database, patients from March 2014 to December 2018. The detection rate of prostate cancer and clinically significant prostate cancer and complication rate were analysed in a cohort of patients who underwent fusion biopsy alone (group A) or fusion biopsy plus standard biopsy (group B). The International Society of Urological Pathology grade group determined on prostate biopsy with the grade group determined on final pathology among patients who underwent radical prostatectomy were compared. Results: Prostate cancer was found in 249/389 (64.01%) and 215/337 (63.8%) patients in groups A and B, respectively ( P=0.98), while the clinically significant prostate cancer detection rate was 57.8% and 55.1% ( P=0.52). No significant differences in complications were found. No differences in the upgrading rate between biopsy and final pathology finding after radical prostatectomy were recorded. Conclusions: In biopsy-naive patients, with suspected prostate cancer and positive multiparametric magnetic resonance imaging the addition of standard biopsy to fusion biopsy did not increase significantly the detection rate of prostate cancer or clinically significant prostate cancer. Moreover, the rate of upgrading of the cancer grade group between biopsy and final pathology was not affected by the addition of standard biopsy. Level of evidence: Not applicable for this multicentre audit.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mads Ryø Jochumsen ◽  
Jens Sörensen ◽  
Lars Poulsen Tolbod ◽  
Bodil Ginnerup Pedersen ◽  
Jørgen Frøkiær ◽  
...  

Abstract Background Both prostate-specific membrane antigen (PSMA) uptake and tumour blood flow (TBF) correlate with International Society of Urological Pathology (ISUP) Grade Group (GG) and hence prostate cancer (PCa) aggressiveness. The aim of the present study was to evaluate the potential synergistic benefit of combining the two physiologic parameters for separating significant PCa from insignificant findings. Methods From previous studies of [82Rb]Rb positron emission tomography (PET) TBF in PCa, the 43 patients that underwent clinical [68Ga]Ga-PSMA-11 PET were selected for this retrospective study. Tumours were delineated on [68Ga]Ga-PSMA-11 PET or magnetic resonance imaging. ISUP GG was recorded from 52 lesions. Results [68Ga]Ga-PSMA-11 maximum standardized uptake value (SUVmax) and [82Rb]Rb SUVmax correlated moderately with ISUP GG (rho = 0.59 and rho = 0.56, both p < 0.001) and with each other (r = 0.65, p < 0.001). A combined model of [68Ga]Ga-PSMA-11 and [82Rb]Rb SUVmax separated ISUP GG > 2 from ISUP GG 1–2 and benign with an area-under-the-curve of 0.85, 96% sensitivity, 74% specificity, and 95% negative predictive value. The combined model performed significantly better than either tracer alone did (p < 0.001), primarily by reducing false negatives from five or six to one (p ≤ 0.025). Conclusion PSMA uptake and TBF provide complementary information about tumour aggressiveness. We suggest that a combined analysis of PSMA uptake and TBF could significantly improve the negative predictive value and allow non-invasive separation of significant from insignificant PCa.


2021 ◽  
pp. 20201434
Author(s):  
Yasuyo Urase ◽  
Yoshiko Ueno ◽  
Tsutomu Tamada ◽  
Keitaro Sofue ◽  
Satoru Takahashi ◽  
...  

Objectives: To evaluate the interreader agreement and diagnostic performance of the Prostate Imaging Reporting and Data System (PI-RADS) v2.1, in comparison with v2. Methods: Institutional review board approval was obtained for this retrospective study. Seventy-seven consecutive patients who underwent a prostate multiparametric magnetic resonance imaging at 3.0 T before radical prostatectomy were included. Four radiologists (two experienced uroradiologists and two inexperienced radiologists) independently scored eight regions [six peripheral zones (PZ) and two transition zones (TZ)] using v2.1 and v2. Interreader agreement was assessed using κ statistics. To evaluate diagnostic performance for clinically significant prostate cancer (csPC), area under the curve (AUC) was estimated. Results 228 regions were pathologically diagnosed as positive for csPC. With a cutoff ≥3, the agreement among all readers was better with v2.1 than v2 in TZ, PZ, or both zones combined (κ-value: TZ, 0.509 vs 0.414; PZ, 0.686 vs 0.568; both zones combined, 0.644 vs 0.531). With a cutoff ≥4, the agreement among all readers was also better with v2.1 than v2 in the PZ or both zones combined (κ-value: PZ, 0.761 vs 0.701; both zones combined, 0.756 vs 0.709). For all readers, AUC with v2.1 was higher than with v2 (TZ, 0.826–0.907 vs 0.788–0.856; PZ, 0.857–0.919 vs 0.853–0.902). Conclusions: Our study suggests that the PI-RADS v2.1 could improve the interreader agreement and might contribute to improved diagnostic performance compared with v2. Advances in knowledge: PI-RADS v2.1 has a potential to improve interreader variability and diagnostic performance among radiologists with different levels of expertise.


2021 ◽  
Author(s):  
Allison Y Zhong ◽  
Leonardino A Digma ◽  
Troy Hussain ◽  
Christine H Feng ◽  
Christopher C Conlin ◽  
...  

Purpose: Multiparametric MRI (mpMRI) improves detection of clinically significant prostate cancer (csPCa), but the qualitative PI-RADS system and quantitative apparent diffusion coefficient (ADC) yield inconsistent results. An advanced Restrictrion Spectrum Imaging (RSI) model may yield a better quantitative marker for csPCa, the RSI restriction score (RSIrs). We evaluated RSIrs for patient-level detection of csPCa. Materials and Methods: Retrospective analysis of men who underwent mpMRI with RSI and prostate biopsy for suspected prostate cancer from 2017-2019. Maximum RSIrs within the prostate was assessed by area under the receiver operating characteristic curve (AUC) for discriminating csPCa (grade group ≥2) from benign or grade group 1 biopsies. Performance of RSIrs was compared to minimum ADC and PI-RADS v2-2.1via bootstrap confidence intervals and bootstrap difference (two-tailed α=0.05). We also tested whether the combination of PI-RADS and RSIrs (PI-RADS+RSIrs) was superior to PI-RADS, alone. Results: 151 patients met criteria for inclusion. AUC values for ADC, RSIrs, and PI-RADS were 0.50 [95% confidence interval: 0.41, 0.60], 0.76 [0.68, 0.84], and 0.78 [0.71, 0.85], respectively. RSIrs (p=0.0002) and PI-RADS (p<0.0001) were superior to ADC for patient-level detection of csPCa. The performance of RSIrs was comparable to that of PI-RADS (p=0.6). AUC for PI-RADS+RSIrs was 0.84 [0.77, 0.90], superior to PI-RADS or RSIrs, alone (p=0.008, p=0.009). Conclusions: RSIrs was superior to conventional ADC and comparable to (routine, clinical) PI-RADS for patient-level detection of csPCa. The combination of PI-RADS and RSIrs was superior to either alone. RSIrs is a promising quantitative marker worthy of prospective study in the setting of csPCa detection.


2021 ◽  
Author(s):  
Dong Gyun Kim ◽  
Jeong Woo Yoo ◽  
Kyo Chul Koo ◽  
Byung Ha Chung ◽  
Kwang Suk Lee

Abstract INTRODUCTION: To analyze grayscale values for hypoechoic lesions matched with target lesions evaluated using prebiopsy magnetic resonance imaging (MRI). METHODS We collected data on 420 target lesions in patients who underwent MRI/transrectal ultrasound fusion biopsies. Images of hypoechoic lesions that matched the target lesions on MRI were stored in a picture archiving and communication system, and their grayscale values were estimated using the red/green/blue scoring method through an embedded function. We analyzed imaging data using grayscale values. RESULTS Of the 420 lesions, 261 (62.1%) were prostate cancer lesions. Grayscale ranges (42.6–91.8) were significant predictors of clinically significant prostate cancer (csPC) in multivariable logistic regression analyses. Area under the curve for detecting csPC using grayscale values along with conventional variables was 0.839, which was significantly higher than that for detecting csPC using only conventional variables (0.828; p = 0.036). Subgroup analysis revealed a significant difference for PI-RADS 3 lesions between grayscale values for benign and cancerous lesions (p = 0.008). Grayscale values were the only significant predictive factor (p = 0.005) for csPC. CONCLUSIONS Distribution of grayscale values according to PI-RAD 3 scores was useful, and the grayscale range (42.6–91.8) was an important factor for csPC diagnosis.


Cancers ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1064 ◽  
Author(s):  
Sebastian Chakrit Bhakdi ◽  
Prapat Suriyaphol ◽  
Ponpan Thaicharoen ◽  
Sebastian Tobias Karl Grote ◽  
Chulaluk Komoltri ◽  
...  

Even though more than 350,000 men die from prostate cancer every year, broad-based screening for the disease remains a controversial topic. Guidelines demand that the only commonly accepted screening tool, prostate-specific antigen (PSA) testing, must be followed by prostate biopsy if results are elevated. Due to the procedure’s low positive predictive value (PPV), however, over 80% of biopsies are performed on healthy men or men with clinically insignificant cancer—prompting calls for new ways of vetting equivocal PSA readings prior to the procedure. Responding to the challenge, the present study investigated the diagnostic potential of tumour-associated circulating endothelial cells (tCECs), which have previously been described as a novel, blood-based biomarker for clinically significant cancers. Specifically, the objective was to determine the diagnostic accuracy of a tCEC-based blood test to detect clinically significant prostate cancer (defined as Gleason score ≥ 3 + 4) in high-risk patients. Performed in a blinded, prospective, single-centre set-up, it compared a novel tCEC index test with transrectal ultrasound-guided biopsy biopsy as a reference on a total of 170 patients and found that a tCEC add-on test will almost double the PPV of a standalone PSA test (32% vs. 17%; p = 0.0012), while retaining a negative predictive value above 90%.


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