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

2021 ◽  
Author(s):  
Rossano Girometti ◽  
Gianluca Giannarini ◽  
Valeria Panebianco ◽  
Silvio Maresca ◽  
Lorenzo Cereser ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Operating Characteristic ◽  
Area Under The Curve ◽  
Net Benefit ◽  
Characteristic Analysis ◽  
Prostate Imaging ◽  
Psa Density ◽  
Group 2 ◽  
Clinically Significant ◽  
Sensitivity Specificity

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.

The ability of free to total prostate-specific antigen and prostate-specific antigen density to detect clinically significant prostate cancer in men undergoing transperineal template biopsy

2017 ◽  
Vol 10 (6) ◽  
pp. 529-534 ◽  
Author(s):  
Surayne V Segaran ◽  
Amr M Emara ◽  
Tharani Mahesan ◽  
Joshua Silverman ◽  
Hashim U Ahmed ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Prostate Specific Antigen ◽  
Operating Characteristic ◽  
Receiver Operating Characteristic Analysis ◽  
Specific Antigen ◽  
Area Under The Curve ◽  
Characteristic Analysis ◽  
Total Prostate Specific Antigen ◽  
Prostate Specific Antigen Density ◽  
Clinically Significant

Objective: The purpose of this study was to determine the ability of the ratio of free to total prostate-specific antigen and prostate-specific antigen density to predict the presence of clinically significant prostate cancer on template biopsies. The value of these tests may be underestimated as they were previously validated against sextant transrectal biopsy of the prostate, which has been proved to miss a large proportion of significant prostate cancers. The ability of these tests to specifically detect clinically significant cancers has not previously been studied. Patients and methods: A retrospective analysis was performed of patients undergoing transperineal template biopsy who also had free to total prostate-specific antigen and prostate-specific antigen density. Receiver-operating characteristic analysis was performed to determine the comparative utility of each test in the detection of all cancers as well as clinically significant cancers, by means of the area under the curve. Results: Data from 293 patients were analysed. Prostate cancer was detected in 72% of patients, of which 62% of this group had clinically significant disease. Receiver-operating characteristic analysis demonstrated the superiority of prostate-specific antigen density and free to total prostate-specific antigen over standard prostate-specific antigen in the overall detection of cancer (area under the curve 0.662 and 0.674 vs 0.534, p=0.003 and 0.02 respectively). Both tests were even more effective in the detection of clinically significant cancers (area under the curve 0.755 and 0.715 vs 0.572, p<0.0001 and 0.009 respectively). Conclusion: The free to total prostate-specific antigen and prostate-specific antigen density both appear to perform well at detecting clinically significant prostate cancer in our population of men undergoing template biopsy. The potential role of these inexpensive tests should not be overlooked as they may be of value when deciding which patients require biopsy following an initial magnetic resonance imaging scan and also for those on surveillance protocols.

scholarly journals Head-to-Head Comparison of Two Nomograms Predicting Probability of Lymph Node Invasion in Prostate Cancer and the Therapeutic Impact of Higher Nomogram Threshold

2021 ◽  
Vol 10 (5) ◽  
pp. 999
Author(s):  
Zilvinas Venclovas ◽  
Tim Muilwijk ◽  
Aivaras J. Matjosaitis ◽  
Mindaugas Jievaltas ◽  
Steven Joniau ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Lymph Node ◽  
Area Under The Curve ◽  
Pelvic Lymph Node ◽  
Cancer Center ◽  
Study Cohort ◽  
Net Benefit ◽  
Characteristic Analysis ◽  
Therapeutic Impact ◽  
Mskcc Nomogram

Introduction: The aim of the study was to compare the performance of the 2012 Briganti and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms as a predictor for pelvic lymph node invasion (LNI) in men who underwent radical prostatectomy (RP) with pelvic lymph node dissection (PLND), to examine their performance and to analyse the therapeutic impact of using 7% nomogram cut-off. Materials and Methods: The study cohort consisted of 807 men with clinically localised prostate cancer (PCa) who underwent open RP with PLND between 2001 and 2019. The area under the curve (AUC) of the receiver operator characteristic analysis was used to quantify the accuracy of the 2012 Briganti and MSKCC nomograms to predict LNI. Calibration plots were used to visualise over or underestimation by the models and a decision curve analysis (DCA) was performed to evaluate the net benefit associated with the used nomograms. Results: A total of 97 of 807 patients had LNI (12%). The AUC of 2012 Briganti and MSKCC nomogram was 80.6 and 79.2, respectively. For the Briganti nomogram using the cut-off value of 7% would lead to reduce PLND in 47% (379/807), while missing 3.96% (15/379) cases with LNI. For the MSKCC nomogram using the cut-off value of 7% a PLND would be omitted in 44.5% (359/807), while missing 3.62% (13/359) of cases with LNI. Conclusions: Both analysed nomograms demonstrated high accuracy for prediction of LNI. Using a 7% nomogram cut-off would allow the avoidance up to 47% of PLNDs, while missing less than 4% of patients with LNI.

Comparison of prostate imaging reporting and data system v2.1 and 2 in transition and peripheral zones: evaluation of interreader agreement and diagnostic performance in detecting clinically significant prostate cancer

2021 ◽  
pp. 20201434
Author(s):  
Yasuyo Urase ◽  
Yoshiko Ueno ◽  
Tsutomu Tamada ◽  
Keitaro Sofue ◽  
Satoru Takahashi ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diagnostic Performance ◽  
Area Under The Curve ◽  
Data System ◽  
Transition Zones ◽  
Prostate Imaging ◽  
Institutional Review ◽  
3.0 T ◽  
Clinically Significant ◽  
Interreader Agreement

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.

scholarly journals Comparison of Likert and PI-RADS version 2 MRI scoring systems for the detection of clinically significant prostate cancer

2020 ◽  
Vol 93 (1112) ◽  
pp. 20200298 ◽  
Author(s):  
Jeries P Zawaideh ◽  
Evis Sala ◽  
Maria Pantelidou ◽  
Nadeem Shaida ◽  
Brendan Koo ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Area Under The Curve ◽  
Scoring Systems ◽  
Detection Rates ◽  
Prostate Imaging ◽  
Prostate Biopsies ◽  
Threshold Score ◽  
Lesion Level ◽  
Clinically Significant ◽  
Histological Results

Objective: To compare the performance of Likert and Prostate Imaging–Reporting and Data System (PI-RADS) multiparametric (mp) MRI scoring systems for detecting clinically significant prostate cancer (csPCa). Methods: 199 biopsy-naïve males undergoing prostate mpMRI were prospectively scored with Likert and PI-RADS systems by four experienced radiologists. A binary cut-off (threshold score ≥3) was used to analyze histological results by three groups: negative, insignificant disease (Gleason 3 + 3; iPCa), and csPCa (Gleason ≥3 +4). Lesion-level results and prostate zonal location were also compared. Results: 129/199 (64.8%) males underwent biopsy, 96 with Likert or PI-RADS score ≥3, and 21 with negative MRI. A further 12 patients were biopsied during follow-up (mean 507 days). Prostate cancer was diagnosed in 87/199 (43.7%) patients, 65 with (33.6%) csPCa. 30/92 (32.6%) patients with negative MRI were biopsied, with an NPV of 83.3% for cancer and 86.7% for csPCa. Likert and PI-RADS score differences were observed in 92 patients (46.2%), but only for 16 patients (8%) at threshold score ≥3. Likert scoring had higher specificity than PI-RADS (0.77 vs 0.66), higher area under the curve (0.92 vs 0.87, p = 0.002) and higher PPV (0.66 vs 0.58); NPV and sensitivity were the same. Likert had more five score results (58%) compared to PI-RADS (36%), but with similar csCPa detection (81.0 and 80.6% respectively). Likert demonstrated lower proportion of false positive in the predominately AFMS-involving lesions. Conclusion: Likert and PI-RADS systems both demonstrate high cancer detection rates. Likert scoring had a higher AUC with moderately higher specificity and lower positive call rate and could potentially help to reduce the number of unnecessary biopsies performed. Advances in knowledge: This paper illustrates that the Likert scoring system has potential to help urologists reduce the number of prostate biopsies performed.

Is PI-RADS 3/total lesion ratio associated with clinically-significant prostate cancer in patients with equivocal-risk lesions on multi-parametric MRI?

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 149-149
Author(s):  
Kamyar Ghabili ◽  
Matthew Swallow ◽  
Alfredo Suarez-Sarmiento ◽  
Jamil Syed ◽  
Michael Leapman ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Prostate Volume ◽  
Area Under The Curve ◽  
Lesion Volume ◽  
Fusion Biopsy ◽  
Grade Group ◽  
Psa Density ◽  
Increased Risk ◽  
Positive Core ◽  
Clinically Significant

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.

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

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Lili Xu ◽  
Gumuyang Zhang ◽  
Bing Shi ◽  
Yanhan Liu ◽  
Tingting Zou ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diagnostic Accuracy ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Multiparametric Mri ◽  
Dce Mri ◽  
Prostate Imaging ◽  
The Difference ◽  
Sensitivity Specificity

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.

scholarly journals Evaluation of PSA and PSA Density in a Multiparametric Magnetic Resonance Imaging-Directed Diagnostic Pathway for Suspected Prostate Cancer: The INNOVATE Trial

Cancers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1985
Author(s):  
Hayley Pye ◽  
Saurabh Singh ◽  
Joseph M. Norris ◽  
Lina M. Carmona Echeverria ◽  
Vasilis Stavrinides ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Prostate Biopsy ◽  
False Negative ◽  
Future Application ◽  
Prostate Imaging ◽  
Diagnostic Pathway ◽  
Psa Density ◽  
Novel Biomarkers ◽  
Clinically Significant ◽  
Set Up

Objectives: To assess the clinical outcomes of mpMRI before biopsy and evaluate the space remaining for novel biomarkers. Methods: The INNOVATE study was set up to evaluate the validity of novel fluidic biomarkers in men with suspected prostate cancer who undergo pre-biopsy mpMRI. We report the characteristics of this clinical cohort, the distribution of clinical serum biomarkers, PSA and PSA density (PSAD), and compare the mpMRI Likert scoring system to the Prostate Imaging–Reporting and Data System v2.1 (PI-RADS) in men undergoing biopsy. Results: 340 men underwent mpMRI to evaluate suspected prostate cancer. 193/340 (57%) men had subsequent MRI-targeted prostate biopsy. Clinically significant prostate cancer (csigPCa), i.e., overall Gleason ≥ 3 + 4 of any length OR maximum cancer core length (MCCL) ≥4 mm of any grade including any 3 + 3, was found in 96/195 (49%) of biopsied patients. Median PSA (and PSAD) was 4.7 (0.20), 8.0 (0.17), and 9.7 (0.31) ng/mL (ng/mL/mL) in mpMRI scored Likert 3,4,5 respectively for men with csigPCa on biopsy. The space for novel biomarkers was shown to be within the group of men with mpMRI scored Likert3 (178/340) and 4 (70/350), in whom an additional of 40% (70/178) men with mpMRI-scored Likert3, and 37% (26/70) Likert4 could have been spared biopsy. PSAD is already considered clinically in this cohort to risk stratify patients for biopsy, despite this 67% (55/82) of men with mpMRI-scored Likert3, and 55% (36/65) Likert4, who underwent prostate biopsy had a PSAD below a clinical threshold of 0.15 (or 0.12 for men aged <50 years). Different thresholds of PSA and PSAD were assessed in mpMRI-scored Likert4 to predict csigPCa on biopsy, to achieve false negative levels of ≤5% the proportion of patients whom who test as above the threshold were unsuitably high at 86 and 92% of patients for PSAD and PSA respectively. When PSA was re tested in a sub cohort of men repeated PSAD showed its poor reproducibility with 43% (41/95) of patients being reclassified. After PI-RADS rescoring of the biopsied lesions, 66% (54/82) of the Likert3 lesions received a different PI-RADS score. Conclusions: The addition of simple biochemical and radiological markers (Likert and PSAD) facilitate the streamlining of the mpMRI-diagnostic pathway for suspected prostate cancer but there remains scope for improvement, in the introduction of novel biomarkers for risk assessment in Likert3 and 4 patients, future application of novel biomarkers tested in a Likert cohort would also require re-optimization around Likert3/PI-RADS2, as well as reproducibility testing.

scholarly journals Detection of Dental Caries and Cracks with Quantitative Light-Induced Fluorescence in Comparison to Radiographic and Visual Examination: A Retrospective Case Study

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1741
Author(s):  
Song Hee Oh ◽  
Sae Rom Lee ◽  
Jin Young Choi ◽  
Yong Suk Choi ◽  
Seong Hun Kim ◽  
...  
Keyword(s):  
Dental Caries ◽  
Operating Characteristic ◽  
Area Under The Curve ◽  
Characteristic Analysis ◽  
Occlusal Caries ◽  
Retrospective Case ◽  
X Ray ◽  
Sensitivity Specificity ◽  
Retrospective Case Study

The aim of this study was to present an optimal diagnostic protocol by comparing and analyzing a conventional examination and the quantitative light-induced fluorescence (QLF) technique. Selected were 297 teeth of 153 patients to take QLF images and bitewing radiographs. Occlusal dental caries, proximal dental caries and cracks were evaluated and scored using QLF, X-ray and/or visual criteria. The sensitivity, specificity, and area under the curve (AUC) of a receiver operating characteristic analysis were calculated. Two fluorescence parameters (|ΔFmax| and ΔRmax) were utilized to evaluate the fluorescence pattern according to the severity of lesions based on QLF or X-ray criteria. QLF showed higher scores for detecting occlusal dental caries and cracks than the conventional method. ΔRmax increased more clearly than ΔFmax did with occlusal dental caries. The |ΔFmax| values of occlusal dental caries, proximal dental caries and cracks showed good AUC levels (0.84, 0.81 and 0.83, respectively). The ΔRmax of occlusal dental caries showed the highest AUC (0.91) and the ΔRmax of proximal dental caries showed a fail level (0.59) compared to bitewing radiographs. The QLF image could visualize and estimate the degree of occlusal dental caries or cracks. Consequently, the QLF technique may be an adjunct tool to conventional methods for the detection of occlusal caries and peripheral cracks.

scholarly journals Lesion-to-background ratio threshold value of SUVmax of simultaneous [68Ga]Ga-PSMA-11 PET/MRI imaging in patients with prostate cancer

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Jing Zhao ◽  
Bernd Hamm ◽  
Winfried Brenner ◽  
Marcus R. Makowski
Keyword(s):  
Prostate Cancer ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Absolute Threshold ◽  
Threshold Value ◽  
Imaging Findings ◽  
Characteristic Analysis ◽  
Psma Pet ◽  
The Absolute ◽  
Receiver Operating

Abstract Purpose This study aimed to calculate an applicable relative ratio threshold value instead of the absolute threshold value for simultaneous 68Ga prostate-specific membrane antigen/positron emission tomography ([68Ga]Ga-PSMA-11 PET) in patients with prostate cancer (PCa). Materials and methods Our study evaluated thirty-two patients and 170 focal prostate lesions. Lesions are classified into groups according to Prostate Imaging Reporting and Data System (PI-RADS). Standardized uptake values maximum (SUVmax), corresponding lesion-to-background ratios (LBRs) of SUVmax, and LBR distributions of each group were measured based on regions of interest (ROI). We examined LBR with receiver operating characteristic analysis to determine threshold values for differentiation between multiparametric magnetic resonance imaging (mpMRI)-positive and mpMRI-negative lesions. Results We analyzed a total of 170 focal prostate lesions. Lesions number of PI-RADS 2 to 5 was 70, 16, 46, and 38. LBR of SUVmax of each PI-RADS scores was 1.5 (0.9, 2.4), 2.5 (1.6, 3.4), 3.7 (2.6, 4.8), and 6.7 (3.5, 12.7). Based on an optimal threshold ratio of 2.5 to be exceeded, lesions could be classified into MRI-positive lesion on [68Ga]Ga-PSMA PET with a sensitivity of 85.2%, a specificity of 72.0%, with the corresponding area under the receiver operating characteristic curve (AUC) of 0.83, p < 0.001. This value matches the imaging findings better. Conclusion The ratio threshold value of SUVmax, LBR, has improved clinical and research applicability compared with the absolute value of SUVmax. A higher threshold value than the background’s uptake can dovetail the imaging findings on MRI better. It reduces the bias from using absolute background uptake value as the threshold value.

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