Towards the Definition of Radiomic Features and Clinical Indices to Enhance the Diagnosis of Clinically Significant Cancers in PI-RADS 4 and 5 Lesions.

Prostate cancer (PC) is the most frequently diagnosed cancer among adult men, and its incidence is increasing worldwide [...].

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.

Diagnostic accuracy of multiparametric magnetic resonance imaging combined with clinical parameters in the detection of clinically significant prostate cancer: A novel diagnostic model.

OBJECTIVES: To evaluate the diagnostic accuracy of multiparametric magnetic resonance imaging in the detection of prostate cancer, according to Prostate Imaging Reporting and Data System, and the usefulness of combining clinical parameters to improve patients' risk assessment. METHODS: Overall, 201 patients underwent multiparametric magnetic resonance imaging investigation with a 3-T magnet and a 32-channel body coil based on triplanar high-resolution T2-weighted, diffusion-weighted and T1-weighted dynamic contrast-enhanced imaging before, during and after intravenous administration of paramagnetic contrast agent. Random transrectal ultrasound-guided biopsy was carried out for all eligible patients. If a Prostate Imaging Reporting and Data System ≥3 lesion was present, a targeted biopsy with magnetic resonance imaging-transrectal ultrasound fusion-guided system was carried out. RESULTS: Sensitivity, specificity, positive predictive value and negative predictive value of Prostate Imaging Reporting and Data System ≥3 lesions for the detection of prostate cancer were 65.1%, 54.9%, 43.1% and 75.0% respectively, with an accuracy of 64.2% (55.1-72.7%). At uni- and multivariate analysis, age ≥70 years and prostate-specific antigen density ≥0.15 ng/mL/mL were significantly associated with prostate cancer. A new risk model named "modified Prostate Imaging Reporting and Data System" was created considering age and prostate-specific antigen density in addition to the Prostate Imaging Reporting and Data System score showing an improved correlation with prostate cancer compared with the Prostate Imaging Reporting and Data System alone (area under curve 71.4%, 95% confidence interval 62.2-80.5 vs area under curve 62.6%, 95% confidence interval 52.1-73; P ≤ 0.0001). CONCLUSIONS: The accuracy of Prostate Imaging Reporting and Data System alone in the diagnosis of prostate cancer might be suboptimal, whereas a novel risk model based on the combination of multiparametric magnetic resonance imaging data with clinical parameters could offer higher discrimination and improve the ability of diagnosing clinically significant disease.

The Use of Multiparametric Magnetic Resonance Imaging for Follow-up of Patients Included in Active Surveillance Protocol. Can PSA Density Discriminate Patients at Different Risk of Reclassification?

INTRODUCTION: The objective of this study was to test Prostate Imaging Reporting and Data System (PI-RADS) classification on multiparametric magnetic resonance imaging (mpMRI) and MRI-derived prostate-specific antigen density (PSAD) in predicting the risk of reclassification in men in active surveillance (AS), who underwent confirmatory or per-protocol follow-up biopsy. MATERIALS AND METHODS: Three hundred eighty-nine patients in AS underwent mpMRI before confirmatory or follow-up biopsy. Patients with negative (-) mpMRI underwent systematic random biopsy. Patients with positive (+) mpMRI underwent targeted fusion prostate biopsies + systematic random biopsies. Different PSAD cutoff values were tested (< 0.10, 0.10-0.20, ≥ 0.20). Multivariable analyses assessed the risk of reclassification, defined as clinically significant prostate cancer of grade group 2 or more, during follow-up according to PSAD, after adjusting for covariates. RESULTS: One hundred twenty-seven (32.6%) patients had mpMRI(-); 72 (18.5%) had PI-RADS 3, 150 (38.6%) PI-RADS 4, and 40 (10.3%) PI-RADS 5 lesions. The rate of reclassification to grade group 2 PCa was 16%, 22%, 31%, and 39% for mpMRI(-) and PI-RADS 3, 4, and 5, respectively, in case of PSAD < 0.10 ng/mL2; 16%, 25%, 36%, and 44%, in case of PSAD 0.10 to 0.19 ng/mL2; and 25%, 42%, 55%, and 67% in case of PSAD ≥ 0.20 ng/mL2. PSAD ≥ 0.20 ng/mL2 (odds ratio [OR], 2.45; P = .007), PI-RADS 3 (OR, 2.47; P = .013), PI-RADS 4 (OR, 2.94; P < .001), and PI-RADS 5 (OR, 3.41; P = .004) were associated with a higher risk of reclassification. CONCLUSION: PSAD ≥ 0.20 ng/mL2 may improve predictive accuracy of mpMRI results for reclassification of patients in AS, whereas PSAD < 0.10 ng/mL2 may help selection of patients at lower risk of harboring clinically significant prostate cancer. However, the risk of reclassification is not negligible at any PSAD cutoff value, also in the case of mpMRI(-).

Multiparametric magnetic resonance imaging and clinical variables: Which is the best combination to predict reclassification in active surveillance patients?

INTRODUCTION & OBJECTIVES: We tested the role of multiparametric magnetic resonance imaging (mpMRI) in disease reclassification and whether the combination of mpMRI and clinicopathological variables could represent the most accurate approach to predict the risk of reclassification during active surveillance. MATERIALS & METHODS: Three-hundred eighty-nine patients (pts) underwent mpMRI and subsequent confirmatory or follow-up biopsy according to the Prostate Cancer Research International Active Surveillance (PRIAS) protocol. Pts with negative (-) mpMRI underwent systematic random biopsy. Pts with positive (+) mpMRI [Prostate Imaging Reporting and Data System, version 2 (PI-RADS-V2) score ≥3] underwent targeted + systematic random biopsies. Multivariate analyses were used to create three models predicting the probability of reclassification [International Society of Urological Pathology ≥ Grade Group 2 (GG2)]: a basic model including only clinical variables (age, prostate-specific antigen density, and number of positive cores at baseline), an Magnetic resonance imaging (MRI) model including only the PI-RADS score, and a full model including both the previous ones. The predictive accuracy (PA) of each model was quantified using the area under the curve. RESULTS: mpMRI negative (-) was recorded in 127 (32.6%) pts; mpMRI positive (+) was recorded in 262 pts: 72 (18.5%) had PI-RADS 3, 150 (38.6%) PI-RADS 4, and 40 (10.3%) PI-RADS 5 lesions. At a median follow-up of 12 months, 125 pts (32%) were reclassified to GG2 prostate cancer. The rate of reclassification to GG2 prostate cancer was 17%, 35%, 38%, and 52% for mpMRI (-), PI-RADS 3, 4, and 5, respectively (P < 0.001). The PA was 69% and 64% in the basic and MRI models, respectively. The full model had the best PA of 74%: older age (P = 0.023; Odds ratio (OR) = 1.040), prostate-specific antigen density (P = 0.037; OR = 1.324), number of positive cores at baseline (P = 0.001; OR = 1.441), and PI-RADS 3, 4, and 5 (overall P = 0.001; OR = 2.458, 3.007, and 3.898, respectively) were independent predictors of reclassification. CONCLUSIONS: Disease reclassification increased according to the PI-RADS score increase, at confirmatory or follow-up biopsy. However, a no-negligible rate of reclassification was found also in cases of mpMRI (-). The combination of mpMRI and clinicopathological variables still represents the most accurate approach to pts on active surveillance.

Patient dose evaluation for the whole-body low-dose multidetector CT (WBLDMDCT) skeleton study in multiple myeloma (MM).

OBJECTIVE: This study aimed at estimating the patient effective dose during whole-body low-dose multi detector computed tomography with a scanner Philips Brillance 64, and to compare it with those reported in literature for the same procedure and with the dose of the conventional X-ray examination in our institution. MATERIALS AND METHODS: WBLDMDCT effective dose was evaluated for 29 MM patients, using Dose Length Product values. Conventional X-ray examination dose was estimated using a Rando Phantom and Dose Area Product indexes. ICRP Publication 103 based coefficients were used. RESULTS: Mean WBLDMDCT effective dose values-estimated using sex-specific conversion coefficients and body weight factors-were 3.6 and 2.8 mSv for females and males, respectively. The effective dose for the conventional method was 1.2 mSv for Rando phantom. CONCLUSION: The WBLDMDCT effective dose in our institution is consistent with the values reported in previous studies. Such a dose is about 2.5- to 3-fold higher than the mean radiation dose of the conventional X-ray study. Nevertheless, considering the improved diagnostic accuracy of the CT investigation, the comfort of the patient and the old age of the MM population, dose/quality ratio can be considered favourable.