An integrated nomogram combining deep learning, Prostate Imaging-Reporting and Data System (PI-RADS) scoring, and clinical variables for identification of clinically significant prostate cancer on biparametric MRI: a retrospective multicentre study.
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SUBMITTER: Hiremath A
PROVIDER: S-EPMC8261599 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description: Not available
| S-EPMC10839314 | biostudies-literature
Project description:PurposeTo develop and validate a PI-RADS-based nomogram for predicting the probability of clinically significant prostate cancer (csPCa) at initial prostate biopsy.Patients and MethodsFrom February 2015 to October 2018, 573 consecutive patients made up the development cohort (DC), and another 253 patients were included as an independent validation cohort (VC). Univariate and multivariate analysis were used for determining the dependent clinical risk factors for csPCa. Prediction model1 was constructed by integrating independent clinical risk factors. T?hen added the PI-RADS score to model1 to develop the prediction model2 and present it in the form of a nomogram. The performance of the nomogram was assessed by receiver operating characteristic curve, net reclassification improvement analysis, calibration curve, and decision curve.ResultsAll clinical candidate factors were significantly different between csPCa and non-csPCa in both the DC and VC. Age, PSA density (PSAD), and free-to-total PSA ratio (f/t) were ultimately determined as dependent clinical risk factors for csPCa and integrated into prediction model1. Then, prediction model2 was developed and presented in a nomogram. In the DC, the nomogram (AUC=0.894) was superior to model1, PI-RADS score, or other clinical factors alone in detecting csPCa. Similar result (AUC=0.891) was obtained in the VC. NRI analysis showed that the nomogram improved the classification of patients significantly compared with model1. Furthermore, the nomogram showed favorable calibration and great clinical usefulness.ConclusionThis study developed and validated a nomogram that integrates PI-RADS score with other independent clinical risk factors to facilitate prebiopsy individualized prediction in high-risk patients with csPCa.
| S-EPMC7245434 | biostudies-literature
Project description:ObjectiveTo 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).Methods199 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.Results129/199 (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.ConclusionLikert 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 knowledgeThis paper illustrates that the Likert scoring system has potential to help urologists reduce the number of prostate biopsies performed.
| S-EPMC7446003 | biostudies-literature
Project description:BackgroundThis study attempted to develop a nomogram for predicting clinically significant prostate cancer (cs-PCa) in the transition zone (TZ) with the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) score based on biparametric magnetic resonance imaging (bp-MRI) and clinical indicators.MethodsWe retrospectively reviewed 383 patients with suspicious prostate lesions in the TZ as a training cohort and 128 patients as the validation cohort from January 2015 to March 2020. Multivariable logistic regression analysis was performed to determine independent predictors for building a nomogram, and the performance of the nomogram was assessed by the area under the receiver operating characteristic curve (AUC), the calibration curve and decision curve.ResultsThe PI-RADS v2.1 score and prostate-specific antigen density (PSAD) were independent predictors of TZ cs-PCa. The prediction model had a significantly higher AUC (0.936) than the individual predictors (0.914 for PI-RADS v2.1 score, P=0.045, 0.842 for PSAD, P<0.001). The nomogram showed good discrimination (AUC of 0.936 in the training cohort and 0.963 in the validation cohort) and favorable calibration. When the PI-RADS v2.1 score was combined with PSAD, the diagnostic sensitivity and specificity were 80.7% and 93.8%, respectively, which were better than those of the PI-RADS v2.1 score (sensitivity, 74.2%; specificity, 92.5%) and PSAD (sensitivity, 66.1%; specificity, 88.2%).ConclusionsThe newly constructed nomogram exhibits satisfactory predictive accuracy and consistency for TZ cs-PCa. PI-RADS v2.1 based on bp-MRI is a strong predictor in the detection of TZ cs-PCa. Adding PSAD to PI-RADS v2.1 could improve its diagnostic performance, thereby avoiding unnecessary biopsies.
| S-EPMC8261422 | biostudies-literature
Project description:BackgroundBiparametric MRI (bpMRI) is a faster, contrast-free, and less expensive MRI protocol that facilitates the detection of prostate cancer. The aim of this study is to determine whether a biparametric MRI PI-RADS v2.1 score-based model could reduce unnecessary biopsies in patients with suspected prostate cancer (PCa).MethodsThe patients who underwent MRI-guided biopsies and systematic biopsies between January 2020 and January 2022 were retrospectively analyzed. The development cohort used to derive the prediction model consisted of 275 patients. Two validation cohorts included 201 patients and 181 patients from 2 independent institutions. Predictive models based on the bpMRI PI-RADS v2.1 score (bpMRI score) and clinical parameters were used to detect clinically significant prostate cancer (csPCa) and compared by analyzing the area under the curve (AUC) and decision curves. Spearman correlation analysis was utilized to determine the relationship between International Society of Urological Pathology (ISUP) grade and clinical parameters/bpMRI score.ResultsLogistic regression models were constructed using data from the development cohort to generate nomograms. By applying the models to the all cohorts, the AUC for csPCa was significantly higher for the bpMRI PI-RADS v2.1 score-based model than for the clinical model in both cohorts (p < 0.001). Considering the test trade-offs, urologists would agree to perform 10 fewer bpMRIs to avoid one unnecessary biopsy, with a risk threshold of 10-20% in practice. Correlation analysis showed a strong correlation between the bpMRI score and ISUP grade.ConclusionA predictive model based on the bpMRI score and clinical parameters significantly improved csPCa risk stratification, and the bpMRI score can be used to determine the aggressiveness of PCa prior to biopsy.
| S-EPMC10426075 | biostudies-literature
Project description:PurposeThis study aimed to develop and validate a model based on biparametric magnetic resonance imaging (bpMRI) for the detection of clinically significant prostate cancer (csPCa) in biopsy-naïve patients.MethodThis retrospective study included 324 patients who underwent bpMRI and MRI targeted fusion biopsy (MRGB) and/or systematic biopsy, of them 217 were randomly assigned to the training group and 107 were assigned to the validation group. We assessed the diagnostic performance of three bpMRI-based scorings in terms of sensitivity and specificity. Subsequently, 3 models (Model 1, Model 2, and Model 3) combining bpMRI scorings with clinical variables were constructed and compared with each other using the area under the receiver operating characteristic (ROC) curves (AUC). The statistical significance of differences among these models was evaluated using DeLong's test.ResultsIn the training group, 68 of 217 patients had pathologically proven csPCa. The sensitivity and specificity for Scoring 1 were 64.7% (95% CI 52.2%-75.9%) and 80.5% (95% CI 73.3%-86.6%); for Scoring 2 were 86.8% (95% CI 76.4%-93.8%) and 73.2% (95% CI 65.3%-80.1%); and for Scoring 3 were 61.8% (95% CI 49.2%-73.3%) and 80.5% (95% CI 73.3%-86.6%), respectively. Multivariable regression analysis revealed that scorings based on bpMRI, age, and prostate-specific antigen density (PSAD) were independent predictors of csPCa. The AUCs for the 3 models were 0.88 (95% CI 0.83-0.93), 0.90 (95% CI 0.85-0.94), and 0.88 (95% CI 0.83-0.93), respectively. Model 2 showed significantly higher performance than Model 1 (P = 0.03) and Model 3 (P < 0.01).ConclusionAll three scorings had favorite diagnostic accuracy. While in conjunction with age and PSAD the prediction power was significantly improved, and the Model 2 that based on Scoring 2 yielded the highest performance.
| S-EPMC10478308 | biostudies-literature
Project description:Our aim was to assess the value of adding standard biopsy to targeted biopsy in cases of suspicious multiparametric magnetic resonance imaging (mp-MRI) and also to evaluate when a biopsy of a PI-RADS 3 lesion could be avoided. A retrospective study of patients who underwent targeted biopsy plus standard systematic biopsy between 2016-2019 was performed. All the 1.5 T magnetic resonance images were evaluated according to PI-RADSv.2. An analysis focusing on the clinical scenario, lesion location, and PI-RADS score was performed. A total of 483 biopsies were evaluated. The mean age was 65 years, with a PSA density of 0.12 ng/mL/cc. One-hundred and two mp-MRIs were categorized as PI-RADS-3. Standard biopsy was most helpful in detecting clinically significant prostate cancer (csPCa) in patients in the active surveillance (AS) cohort (increasing the detection rate 12.2%), and in peripheral lesions (6.5%). Adding standard biopsy showed no increase in the detection rate for csPCa in patients with PI-RADS-5 lesions. Considering targeted biopsy in patients with PI-RADS 3 lesions, a higher detection rate was shown in biopsy-naïve patients versus AS and in patients with a previous negative biopsy (p = 0.002). Furthermore, in these patients, the highest rate of csPCa detection was in anterior lesions [42.9% (p = 0.067)]. Our results suggest that standard biopsy could be safely omitted in patients with anterior lesions and in those with PI-RADS-5 lesions. Targeted biopsy for PI-RADS-3 lesions would be less effective in peripheral lesions with a previous negative biopsy.
| S-EPMC8392157 | biostudies-literature
Project description:The purposeAssessing the accuracy of multi parametric magnetic resonance (mp-MRI) after application of PI-RADS V2 for diagnosis of prostate cancer as comparison to pathological results of trans rectal ultra-sound (TRUS) guided biopsy.Patients and methods138 prostatic lesions in 23 patients were retrospectively assessed and analyzed with Trans rectal ultra-sound (TRUS) guided biopsy results. Those patients underwent multi parametric magnetic resonance (mp-MRI) with application of PI-RADS V2 reporting system. The sensitivity, specificity, validity, negative predictive value and positive predictive value were calculated for PI-RADS V2 reporting system compared to biopsy-proven pathological results.Results92 out of 138 lesions were positive for Peripheral zone cancer prostate. PI-RADS V2 reporting system proved 88.04% sensitive & 93.4% specific for diagnosis of prostate cancer with negative predictive value & positive predictive value of 100%.ConclusionOur results proved that mp-MRI of prostate using PI-RADS v2 scoring system had high sensitivity and specificity in diagnosis of prostate cancer and PI-RADS V2 scoring system using mp-MRI is recommended as a non-invasive diagnostic tool compared to TRUS guided biopsy.
| S-EPMC5369010 | biostudies-literature
Project description:IntroductionObjective of our study was to determine the agreement between version 1 (v1) and v2 of the Prostate Imaging Reporting and Data System (PI-RADS) for evaluation of multiparametric prostate MRI (mpMRI) and to compare their diagnostic accuracy, their inter-observer agreement and practicability.Material and methodsmpMRI including T2-weighted imaging, diffusion-weighted imaging (DWI) and dynamic contrast-enhanced imaging (DCE) of 54 consecutive patients, who subsequently underwent MRI-guided in-bore biopsy were re-analyzed according to PI-RADS v1 and v2 by two independent readers. Diagnostic accuracy for detection of prostate cancer (PCa) was assessed using ROC-curve analysis. Agreement between PI-RADS versions and observers was calculated and the time needed for scoring was determined.ResultsMRI-guided biopsy revealed PCa in 31 patients. Diagnostic accuracy for detection of PCa was equivalent with both PI-RADS versions for reader 1 with sensitivities and specificities of 84%/91% (AUC = 0.91 95%CI[0.8-1]) for PI-RADS v1 and 100%/74% (AUC = 0.92 95% CI[0.8-1]) for PI-RADS v2. Reader 2 achieved similar diagnostic accuracy with sensitivity and specificity of 74%/91% (AUC = 0.88 95%CI[0.8-1]) for PI-RADS v1 and 81%/91% (AUC = 0.91 95%CI[0.8-1]) for PI-RADS v2. Agreement between scores determined with different PI-RADS versions was good (reader 1: ? = 0.62, reader 2: ? = 0.64). Inter-observer agreement was moderate with PI-RADS v2 (? = 0.56) and fair with v1 (? = 0.39). The time required for building the PI-RADS score was significantly lower with PI-RADS v2 compared to v1 (24.7±2.3 s vs. 41.9±2.6 s, p<0.001).ConclusionAgreement between PI-RADS versions was high and both versions revealed high diagnostic accuracy for detection of PCa. Due to better inter-observer agreement for malignant lesions and less time demand, the new PI-RADS version could be more practicable for clinical routine.
| S-EPMC5033350 | biostudies-literature
Project description: Not available
| S-EPMC10951302 | biostudies-literature