Observations Regarding the Detection of Abnormal Findings Following a Cancer Screening Whole-Body MRI in Asymptomatic Subjects: The Psychological Consequences and the Role of Personality Traits Over Time.

BACKGROUND: The use of whole-body MRI (WB-MRI) in oncology has uncovered frequent unexpected abnormal findings (AFs). However, the impact of AFs on the patients' mental well-being is still poorly examined. PURPOSE: To investigate the long-term psychological consequences of AF detection following WB-MRI for cancer screening in asymptomatic individuals. STUDY TYPE: Prospective, longitudinal. POPULATION: 121 consecutive subjects of the general population (mean age = 52.61 ± 11.39 years; 63% males) scheduled for cancer screening by WB-MRI. FIELD STRENGTH/SEQUENCE: 1.5-T and 3-T; protocol complied with Oncologically Relevant Findings Reporting and Data System (ONCO-RADS) guidelines. ASSESSMENT: Participants completed the first psychological investigation (T0) immediately after the WB-MRI. Subsequently, it was repeated after 1-year (T1), and 4-years (T2, subgroup of 61 participants) without an MRI exam, assessing personality traits, tumor risk perception, quality of life, depressive, and anxious symptoms. Radiologists directly reported WB-MRI findings to the participants, explaining the clinical implications and the location of the AFs. The number and severity of AFs were assessed. STATISTICAL TESTS: Pearson's correlations and analysis of variance with repeated measures assessed the psychological health variables' relationship and their changes over time. A P-value <0.05 was considered statistically significant. RESULTS: All participants presented AFs, with 101 individuals categorized as ONCO-RADS 2 and 19 as ONCO-RADS 3. The AFs were most prevalent in bones (31.5%). The overall participants showed only a slight increase in depressive symptoms at T1 [F(1,112) = 7.54]. The severity and the number of AFs were not significantly related to psychological changes [ranging from P = 0.503 to P = 0.997]. Depressive and anxious symptoms over time were significantly affected by the traits of conscientiousness [T1: F(1,112) = 7.87; T2: F(1.708,90.544) = 3.40] and openness [T1: F(1,112) = 4.41]. DATA CONCLUSION: Disclosing AFs by WB-MRI exams for cancer screening may not lead to long-term psychosocial consequences. Certain personality traits may, however, influence the psychological distress experienced by individuals with AFs after WB-MRI exams. TECHNICAL EFFICACY: Stage 5.

Evaluation of margins during radical prostatectomy: confocal microscopy vs frozen section analysis.

OBJECTIVES: To test the performance of ex vivo fluorescence confocal microscopy (FCM; Vivascope 2500M-G4), as compared to intra-operative frozen section (IFS) analysis, to evaluate surgical margins during robot-assisted radical prostatectomy (RARP), with final pathology as the reference standard. METHODS: Overall, 54 margins in 45 patients treated with RARP were analysed with: (1) ex vivo FCM; (2) IFS analysis; and (3) final pathology. FCM margins were evaluated by two different pathologists (experienced [M.I.: 10 years] vs highly experienced [G.R.: >30 years]) as strongly negative, probably negative, doubtful, probably positive, or strongly positive. First, inter-observer agreement (Cohen's κ) between pathologists was tested. Second, we reported the sensitivity, specificity, positive predictive (PPV) and negative predictive value (NPV) of ex vivo FCM. Finally, agreement between ex vivo FCM and IFS analysis (Cohen's κ) was reported. For all analyses, four combinations of FCM results were evaluated. RESULTS: At ex vivo FCM, the inter-observer agreement between pathologists ranged from moderate (κ = 0.74) to almost perfect (κ = 0.90), according to the four categories of results. Indeed, at ex vivo FCM, the highly experienced pathologist reached the best balance between sensitivity (70.5%) specificity (91.8%), PPV (80.0%) and NPV (87.1%). Conversely, on IFS analysis, the sensitivity, specificity, PPV and NPV were, respectively, 88.2% vs 100% vs 100% vs 94.8%. The agreement between the ex vivo FCM and IFS analyses ranged from moderate (κ = 0.62) to strong (κ = 0.86), according to the four categories of results. CONCLUSION: Evaluation of prostate margins at ex vivo FCM appears to be feasible and reliable. The agreement between readers encourages its widespread use in daily practice. Nevertheless, as of today, the performance of FCM seems to be sub-par when compared to the established standard of care (IFS analysis).

Extreme-hypofractionated RT with concomitant boost to the DIL in PCa: a 5-year update on oncological and patient-reported outcomes for the phase II trial "GIVE ME FIVE".

AIM: The present work reports updated oncological results and patients-reported outcomes at 5 years of phase II trial "Short-term high precision RT for early prostate cancer with SIB to the dominant intraprostatic lesion (DIL) for patients with early-stage PCa". METHODS: Data from patients enrolled within AIRC IG-13218 (NCT01913717) trial were analyzed. Clinical and GU/GI toxicity assessment and PSA measurements were performed every 3 months for at least 2 years after RT end. QoL of enrolled patients was assessed by IPSS, EORTC QLQ-C30, EORTC QLQ-PR25, and IIEF-5. Patients' score changes were calculated at the end of RT and at 1, 12, and 60 months after RT. RESULTS: A total of 65 patients were included. At a median follow-up of 5 years, OS resulted 86%. Biochemical and clinical progression-free survival at 5 years were 95%. The median PSA at baseline was 6.07 ng/ml, while at last follow-up resulted 0.25 ng/ml. IPSS showed a statistically significant variation in urinary function from baseline (p = 0.002), with the most relevant deterioration 1 month after RT, with a recovery toward baseline at 12 months (p ≤ 0.0001). A numerical improvement in QoL according to the EORTC QLQ-C30 has been reported although not statistically significant. No change in sexual activity was recorded after RT. CONCLUSIONS: The study confirms that extreme hypofractionation with a DIL boost is safe and effective, with no severe effects on the QoL. The increasing dose to the DIL does not worsen the RT toxicity, thus opening the possibility of an even more escalated treatment.

Image quality of whole-body diffusion MR images comparing deep-learning accelerated and conventional sequences.

OBJECTIVES: To compare the image quality of deep learning accelerated whole-body (WB) with conventional diffusion sequences. METHODS: Fifty consecutive patients with bone marrow cancer underwent WB-MRI. Two experts compared axial b900 s/mm2 and the corresponding maximum intensity projections (MIP) of deep resolve boost (DRB) accelerated diffusion-weighted imaging (DWI) sequences (time of acquisition: 6:42 min) against conventional sequences (time of acquisition: 14 min). Readers assessed paired images for noise, artefacts, signal fat suppression, and lesion conspicuity using Likert scales, also expressing their overall subjective preference. Signal-to-noise and contrast-to-noise ratios (SNR and CNR) and the apparent diffusion coefficient (ADC) values of normal tissues and cancer lesions were statistically compared. RESULTS: Overall, radiologists preferred either axial DRB b900 and/or corresponding MIP images in almost 80% of the patients, particularly in patients with a high body-mass index (BMI > 25 kg/m2). In qualitative assessments, axial DRB images were preferred (preferred/strongly preferred) in 56-100% of cases, whereas DRB MIP images were favoured in 52-96% of cases. DRB-SNR/CNR was higher in all normal tissues (p < 0.05). For cancer lesions, the DRB-SNR was higher (p < 0.001), but the CNR was not different. DRB-ADC values were significantly higher for the brain and psoas muscles, but not for cancer lesions (mean difference: + 53 µm2/s). Inter-class correlation coefficient analysis showed good to excellent agreement (95% CI 0.75-0.93). CONCLUSION: DRB sequences produce higher-quality axial DWI, resulting in improved MIPs and significantly reduced acquisition times. However, differences in the ADC values of normal tissues need to be considered. CLINICAL RELEVANCE STATEMENT: Deep learning accelerated diffusion sequences produce high-quality axial images and MIP at reduced acquisition times. This advancement could enable the increased adoption of Whole Body-MRI for the evaluation of patients with bone marrow cancer. KEY POINTS: Deep learning reconstruction enables a more than 50% reduction in acquisition time for WB diffusion sequences. DRB images were preferred by radiologists in almost 80% of cases due to fewer artefacts, improved background signal suppression, higher signal-to-noise ratio, and increased lesion conspicuity in patients with higher body mass index. Cancer lesion diffusivity from DRB images was not different from conventional sequences.

Can we predict pathology without surgery? Weighing the added value of multiparametric MRI and whole prostate radiomics in integrative machine learning models.

OBJECTIVE: To test the ability of high-performance machine learning (ML) models employing clinical, radiological, and radiomic variables to improve non-invasive prediction of the pathological status of prostate cancer (PCa) in a large, single-institution cohort. METHODS: Patients who underwent multiparametric MRI and prostatectomy in our institution in 2015-2018 were considered; a total of 949 patients were included. Gradient-boosted decision tree models were separately trained using clinical features alone and in combination with radiological reporting and/or prostate radiomic features to predict pathological T, pathological N, ISUP score, and their change from preclinical assessment. Model behavior was analyzed in terms of performance, feature importance, Shapley additive explanation (SHAP) values, and mean absolute error (MAE). The best model was compared against a naïve model mimicking clinical workflow. RESULTS: The model including all variables was the best performing (AUC values ranging from 0.73 to 0.96 for the six endpoints). Radiomic features brought a small yet measurable boost in performance, with the SHAP values indicating that their contribution can be critical to successful prediction of endpoints for individual patients. MAEs were lower for low-risk patients, suggesting that the models find them easier to classify. The best model outperformed (p ≤ 0.0001) clinical baseline, resulting in significantly fewer false negative predictions and overall was less prone to under-staging. CONCLUSIONS: Our results highlight the potential benefit of integrative ML models for pathological status prediction in PCa. Additional studies regarding clinical integration of such models can provide valuable information for personalizing therapy offering a tool to improve non-invasive prediction of pathological status. CLINICAL RELEVANCE STATEMENT: The best machine learning model was less prone to under-staging of the disease. The improved accuracy of our pathological prediction models could constitute an asset to the clinical workflow by providing clinicians with accurate pathological predictions prior to treatment. KEY POINTS: • Currently, the most common strategies for pre-surgical stratification of prostate cancer (PCa) patients have shown to have suboptimal performances. • The addition of radiological features to the clinical features gave a considerable boost in model performance. Our best model outperforms the naïve model, avoiding under-staging and resulting in a critical advantage in the clinic. •Machine learning models incorporating clinical, radiological, and radiomics features significantly improved accuracy of pathological prediction in prostate cancer, possibly constituting an asset to the clinical workflow.

Multiparametric MRI-based 5-year Risk Prediction Model for Biochemical Recurrence of Prostate Cancer after Radical Prostatectomy.

Background Current predictive tools to estimate the risk of biochemical recurrence (BCR) after treatment of prostate cancer do not consider multiparametric MRI (mpMRI) information. Purpose To develop a risk prediction tool that considers mpMRI findings to assess the risk of 5-year BCR after radical prostatectomy. Materials and Methods In this retrospective single-center analysis in 1459 patients with prostate cancer who underwent mpMRI before radical prostatectomy (in 2012-2015), the outcome of interest was 5-year BCR (two consecutive prostate-specific antigen [PSA] levels > 0.2 ng/mL [0.2 µg/L]). Patients were randomly divided into training (70%) and test (30%) sets. Kaplan-Meier plots were applied to the training set to estimate survival probabilities. Multivariable Cox regression models were used to test the relationship between BCR and different sets of exploratory variables. The C-index of the final model was calculated for the training and test sets and was compared with European Association of Urology, University of California San Francisco Cancer of the Prostate Risk Assessment, Memorial Sloan-Kettering Cancer Center, and Partin risk tools using the partial likelihood ratio test. Five risk categories were created. Results The median duration of follow-up in the whole cohort was 59 months (IQR, 32-81 months); 376 of 1459 (25.8%) patients had BCR. A multivariable Cox regression model (referred to as PIPEN, and composed of PSA density, International Society of Urological Pathology grade group, Prostate Imaging Reporting and Data System category, European Society of Urogenital Radiology extraprostatic extension score, nodes) fitted to the training data yielded a C-index of 0.74, superior to that of other predictive tools (C-index 0.70 for all models; P ≤ .01) and a median higher C-index on 500 test set replications (C-index, 0.73). Five PIPEN risk categories were identified with 5-year BCR-free survival rates of 92%, 84%, 71%, 56%, and 26% in very low-, low-, intermediate-, high-, and very high-risk patients, respectively (all P < .001). Conclusion A five-item model for predicting the risk of 5-year BCR after radical prostatectomy for prostate cancer was developed and internally verified, and five risk categories were identified. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Aguirre and Ortegón in this issue.

Multi-omics integrative modelling for stereotactic body radiotherapy in early-stage non-small cell lung cancer: clinical trial protocol of the MONDRIAN study.

BACKGROUND: Currently, main treatment strategies for early-stage non-small cell lung cancer (ES-NSCLC) disease are surgery or stereotactic body radiation therapy (SBRT), with successful local control rates for both approaches. However, regional and distant failure remain critical in SBRT, and it is paramount to identify predictive factors of response to identify high-risk patients who may benefit from more aggressive approaches. The main endpoint of the MONDRIAN trial is to identify multi-omic biomarkers of SBRT response integrating information from the individual fields of radiomics, genomics and proteomics. METHODS: MONDRIAN is a prospective observational explorative cohort clinical study, with a data-driven, bottom-up approach. It is expected to enroll 100 ES-NSCLC SBRT candidates treated at an Italian tertiary cancer center with well-recognized expertise in SBRT and thoracic surgery. To identify predictors specific to SBRT, MONDRIAN will include data from 200 patients treated with surgery, in a 1:2 ratio, with comparable clinical characteristics. The project will have an overall expected duration of 60 months, and will be structured into five main tasks: (i) Clinical Study; (ii) Imaging/ Radiomic Study, (iii) Gene Expression Study, (iv) Proteomic Study, (v) Integrative Model Building. DISCUSSION: Thanks to its multi-disciplinary nature, MONDRIAN is expected to provide the opportunity to characterize ES-NSCLC from a multi-omic perspective, with a Radiation Oncology-oriented focus. Other than contributing to a mechanistic understanding of the disease, the study will assist the identification of high-risk patients in a largely unexplored clinical setting. Ultimately, this would orient further clinical research efforts on the combination of SBRT and systemic treatments, such as immunotherapy, with the perspective of improving oncological outcomes in this subset of patients. TRIAL REGISTRATION: The study was prospectively registered at clinicaltrials.gov (NCT05974475).

Comparison of automated segmentation techniques for magnetic resonance images of the prostate.

BACKGROUND: Contouring of anatomical regions is a crucial step in the medical workflow and is both time-consuming and prone to intra- and inter-observer variability. This study compares different strategies for automatic segmentation of the prostate in T2-weighted MRIs. METHODS: This study included 100 patients diagnosed with prostate adenocarcinoma who had undergone multi-parametric MRI and prostatectomy. From the T2-weighted MR images, ground truth segmentation masks were established by consensus from two expert radiologists. The prostate was then automatically contoured with six different methods: (1) a multi-atlas algorithm, (2) a proprietary algorithm in the Syngo.Via medical imaging software, and four deep learning models: (3) a V-net trained from scratch, (4) a pre-trained 2D U-net, (5) a GAN extension of the 2D U-net, and (6) a segmentation-adapted EfficientDet architecture. The resulting segmentations were compared and scored against the ground truth masks with one 70/30 and one 50/50 train/test data split. We also analyzed the association between segmentation performance and clinical variables. RESULTS: The best performing method was the adapted EfficientDet (model 6), achieving a mean Dice coefficient of 0.914, a mean absolute volume difference of 5.9%, a mean surface distance (MSD) of 1.93 pixels, and a mean 95th percentile Hausdorff distance of 3.77 pixels. The deep learning models were less prone to serious errors (0.854 minimum Dice and 4.02 maximum MSD), and no significant relationship was found between segmentation performance and clinical variables. CONCLUSIONS: Deep learning-based segmentation techniques can consistently achieve Dice coefficients of 0.9 or above with as few as 50 training patients, regardless of architectural archetype. The atlas-based and Syngo.via methods found in commercial clinical software performed significantly worse (0.855[Formula: see text]0.887 Dice).

Patient centered radiology: investigating 3 Tesla whole body MRI acceptance in cancer patients.

INTRODUCTION: Whole body magnetic resonance imaging (WB-MRI) is a promising emerging imaging technology for detecting bone and soft tissue pathology, especially in the onco-hematological field. This study aims to evaluate cancer patients' experience of WB-MRI performed on a 3T scanner compared to other diagnostic total body examinations. MATERIAL AND METHOD: In this prospective committee-approved study, patients completed a questionnaire in person (n = 134) after undergoing a WB-MRI scan to collect data on their physical and psychological reactions during the scan, the global satisfaction level, and preference for other types of MRI or computed tomography (CT), or positron emission tomography (PET/CT). Of all patients who had performed a CT or PET/CT the previous year, 61.9% had already undergone an MRI. The most common symptoms reported were: 38.1% perceived a localized increase in temperature and 34.4% numbness and tingling of the limbs. The scan time averaged 45 min and was well tolerated by most patients (112, 85.5%). Overall, WB-MRI was appreciated by the majority (121/134-90.3%) of patients who said they would probably undergo the procedure again. Patients preferred the WB-MRI in 68.7% of cases (92/134), followed by CT in 15.7% of cases (21/134) and by PET/CT in 7.4% (10/134), with 8.4% (11/134) of patients without any preference. The preference for imaging modalities was age-dependent (p = 0.011), while (p > 0.05) was independent of sex and a primary cancer site. CONCLUSION: These results demonstrate a high degree of WB-MRI acceptance from a patient's point of view.

Psychological characteristics and satisfaction for the whole-body MRI in cancer screening.

Whole-body magnetic resonance imaging (WB-MRI) is an all-in-one non-invasive technique that can be used also in early cancer diagnosis in asymptomatic individuals. The aim of this work was to identify the personal characteristics predicting the satisfaction for the WB-MRI in a sample of healthy subjects. Before undergoing a WB-MRI examination, 154 participants completed a questionnaire covering sociodemographics (age, gender, education), personality traits (agreeableness, conscientiousness, emotional stability, extroversion, openness), and expectations about the procedure (expected usefulness, risks, noise, lack of air, duration). After the examination, participants reported their satisfaction with the WB-MRI. Results showed that agreeableness had a significant and positive effect on satisfaction. Expectations about its utility and the possible noise had a positive effect on satisfaction. Expectations of lack of air showed a negative significant effect on satisfaction. Sociodemographics showed no significant effects. Our study confirmed the important impact of individuals' personality and expectations on satisfaction with the procedure. Moreover, it provides useful insights for developing consultations aimed at increasing the acceptability of the procedure.

Advancements in Standardizing Radiological Reports: A Comprehensive Review.

Standardized radiological reports stimulate debate in the medical imaging field. This review paper explores the advantages and challenges of standardized reporting. Standardized reporting can offer improved clarity and efficiency of communication among radiologists and the multidisciplinary team. However, challenges include limited flexibility, initially increased time and effort, and potential user experience issues. The efforts toward standardization are examined, encompassing the establishment of reporting templates, use of common imaging lexicons, and integration of clinical decision support tools. Recent technological advancements, including multimedia-enhanced reporting and AI-driven solutions, are discussed for their potential to improve the standardization process. Organizations such as the ACR, ESUR, RSNA, and ESR have developed standardized reporting systems, templates, and platforms to promote uniformity and collaboration. However, challenges remain in terms of workflow adjustments, language and format variability, and the need for validation. The review concludes by presenting a set of ten essential rules for creating standardized radiology reports, emphasizing clarity, consistency, and adherence to structured formats.

Repeat MRI during active surveillance: natural history of prostatic lesions and upgrading rates.

OBJECTIVES: To assess upgrading rates in patients on active surveillance (AS) for prostate cancer (PCa) after serial multiparametric magnetic resonance imaging (mpMRI). METHODS: We conducted a retrospective analysis of 558 patients. Five different criteria for mpMRI progression were used: 1) a Prostate Imaging Reporting and Data System (PI-RADS) score increase; 2) a lesion size increase; 3) an extraprostatic extension score increase; 4) overall mpMRI progression; and 5) the number of criteria met for mpMRI progression (0 vs 1 vs 2-3). In addition, two definitions of PCa upgrading were evaluated: 1) International Society of Urological Pathology Grade Group (ISUP GG) ≥2 with >10% of pattern 4 and 2) ISUP GG ≥ 3. Estimated annual percent changes methodology was used to show the temporal trends of mpMRI progression criteria. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of mpMRI progression criteria were also analysed. Multivariable logistic regression models tested PCa upgrading rates. RESULTS: Lower rates over time for all mpMRI progression criteria were observed. The NPV of serial mpMRI scans ranged from 90.5% to 93.5% (ISUP GG≥2 with >10% of pattern 4 PCa upgrading) and from 98% to 99% (ISUP GG≥3 PCa upgrading), depending on the criteria used for mpMRI progression. A prostate-specific antigen density (PSAD) threshold of 0.15 ng/mL/mL was used to substratify those patients who would be able to skip a prostate biopsy. In multivariable logistic regression models assessing PCa upgrading rates, all five mpMRI progression criteria achieved independent predictor status. CONCLUSION: During AS, approximately 27% of patients experience mpMRI progression at first repeat MRI. However, the rates of mpMRI progression decrease over time at subsequent mpMRI scans. Patients with stable mpMRI findings and with PSAD < 0.15 ng/mL/mL could safely skip surveillance biopsies. Conversely, patients who experience mpMRI progression should undergo a prostate biopsy.

Association between previous negative biopsies and lower rates of progression during active surveillance for prostate cancer.

PURPOSE: To test any-cause discontinuation and ISUP GG upgrading rates during Active Surveillance (AS) in patients that underwent previous negative biopsies (PNBs) before prostate cancer (PCa) diagnosis vs. biopsy naive patients. METHODS: Retrospective analysis of 961 AS patients (2008-2020). Three definitions of PNBs were used: (1) PNBs status (biopsy naïve vs. PNBs); (2) number of PNBs (0 vs. 1 vs. ≥ 2); (3) histology at last PNB (no vs. negative vs. HGPIN/ASAP). Kaplan-Meier plots and multivariable Cox models tested any-cause and ISUP GG upgrading discontinuation rates. RESULTS: Overall, 760 (79.1%) vs. 201 (20.9%) patients were biopsy naïve vs. PNBs. Specifically, 760 (79.1%) vs. 138 (14.4%) vs. 63 (6.5%) patients had 0 vs. 1 vs. ≥ 2 PNBs. Last, 760 (79.1%) vs. 134 (13.9%) vs. 67 (7%) patients had no vs. negative PNB vs. HGPIN/ASAP. PNBs were not associated with any-cause discontinuation rates. Conversely, PNBs were associated with lower rates of ISUP GG upgrading: (1) PNBs vs. biopsy naïve (HR:0.6, p = 0.04); (2) 1 vs. 0 PNBs (HR:0.6, p = 0.1) and 2 vs. 0 PNBs, (HR:0.5, p = 0.1); (3) negative PNB vs. biopsy naïve (HR:0.7, p = 0.3) and HGPIN/ASAP vs. biopsy naïve (HR:0.4, p = 0.04). However, last PNB ≤ 18 months (HR:0.4, p = 0.02), but not last PNB > 18 months (HR:0.8, p = 0.5) were associated with lower rates of ISUP GG upgrading. CONCLUSION: PNBs status is associated with lower rates of ISUP GG upgrading during AS for PCa. The number of PNBs and time from last PNB to PCa diagnosis (≤ 18 months) appear also to be critical for patient selection.

Active surveillance for prostate cancer: comparison between incidental tumors vs. tumors diagnosed at prostate biopsies.

PURPOSE: To test discontinuation rates during Active Surveillance (AS) in patients diagnosed with incidental prostate cancers (IPCa) vs. tumors diagnosed at prostate biopsies (BxPCa). METHODS: Retrospective single center analysis of 961 vs. 121 BxPCa vs. IPCa patients (2008-2020). Kaplan-Meier plots and multivariable Cox regression models tested four different outcomes: (1) any-cause discontinuation; (2) discontinuation due to ISUP GG upgrading; (3) biopsy discontinuation due to ISUP GG upgrading or > 3 positive cores; (4) biopsy discontinuation or suspicious extraprostatic extension at surveillance mpMRI. Then, multivariable logistic regression models tested rates of clinically significant PCa (csPCa) (ISUP GG ≥ 3 or pT ≥ 3a or pN1) after radical prostatectomy (RP). RESULTS: Median time follow-up was 35 (19-64) months. IPCa patients were at lower risk of any-cause (3-year survival: 79.3 vs. 66%; HR: 0.5, p = 0.001) and biopsy/MRI AS discontinuation (3-year survival: 82.3 vs. 72.7%; HR: 0.5, p = 0.001), compared to BxPCa patients. Conversely, IPCa patients exhibited same rates of biopsy discontinuation and ISUP GG upgrading over time, relative to BxPCa. In multivariable logistic regression models, IPCa patients were associated with higher rates of csPCa at RP (OR: 1.4, p = 0.03), relative to their BxPCa counterparts. CONCLUSION: AS represents a safe management strategy for IPCa. Compared to BxPCa, IPCa patients are less prone to experience any-cause and biopsy/MRI AS discontinuation. However, the two mentioned groups present similar rates of biopsy discontinuation and ISUP GG upgrading over time. In consequence, tailored AS protocols with scheduled repeated surveillance biopsies should be offered to all newly diagnosed IPCa patients.

Correlation between radiological and biological features and clinical outcomes in early prostate cancer: an exploratory subgroup analysis.

PTEN deletion and Ki-67 expression are two of the most promising biomarkers in prostate cancer (PCa). In the same manner, multiparametric magnetic resonance imaging (mp-MRI) guided core biopsy is a powerful tool for PCa detection and staging. The aim of the study is to assess whether a correlation can be identified between the pathological stage defined by an mp-MRI-guided core biopsy and Ki-67 expression and PTEN deletion. Such correlation might be useful for staging and treatment personalization in PCa. This investigation was conducted in the context of phase II clinical study "Short-term radiotherapy for early prostate cancer with a concomitant boost to the dominant lesion" (AIRC IG-13218), ClinicalTrials.gov identifier: NCT01913717. Nineteen patients underwent a further in-bore MRI-targeted core biopsy (MRI-TBx) on the dominant intraprostatic lesion (DIL); on this basis, an additional Gleason Score (GS) was determined. PTEN loss and Ki-67 expression on these samples were analyzed and correlated with both risk categories modifications and oncological outcomes (overall survival, biochemical and clinical relapse). GS was upgraded in 5 cases, with 4 patients re-classified as intermediate-risk and 1 patient as high-risk. The latter experienced a clinical local relapse. No correlations between up/down-staging, PTEN deletion, and Ki-67 expression were observed in this cohort. Further investigations are needed towards the identification of a pattern in the tumor aggressiveness-response in PCa treated with ultra-hypofractionated radiotherapy. Moreover, a possible relationship between biomarker analysis and imaging textural features could be explored.

Oncologically Relevant Findings Reporting and Data System (ONCO-RADS): Guidelines for the Acquisition, Interpretation, and Reporting of Whole-Body MRI for Cancer Screening.

Acknowledging the increasing number of studies describing the use of whole-body MRI for cancer screening, and the increasing number of examinations being performed in patients with known cancers, an international multidisciplinary expert panel of radiologists and a geneticist with subject-specific expertise formulated technical acquisition standards, interpretation criteria, and limitations of whole-body MRI for cancer screening in individuals at higher risk, including those with cancer predisposition syndromes. The Oncologically Relevant Findings Reporting and Data System (ONCO-RADS) proposes a standard protocol for individuals at higher risk, including those with cancer predisposition syndromes. ONCO-RADS emphasizes structured reporting and five assessment categories for the classification of whole-body MRI findings. The ONCO-RADS guidelines are designed to promote standardization and limit variations in the acquisition, interpretation, and reporting of whole-body MRI scans for cancer screening. Published under a CC BY 4.0 license Online supplemental material is available for this article.

MRI-based radiomics signature for localized prostate cancer: a new clinical tool for cancer aggressiveness prediction? Sub-study of prospective phase II trial on ultra-hypofractionated radiotherapy (AIRC IG-13218).

OBJECTIVES: Radiomic involves testing the associations of a large number of quantitative imaging features with clinical characteristics. Our aim was to extract a radiomic signature from axial T2-weighted (T2-W) magnetic resonance imaging (MRI) of the whole prostate able to predict oncological and radiological scores in prostate cancer (PCa). METHODS: This study included 65 patients with localized PCa treated with radiotherapy (RT) between 2014 and 2018. For each patient, the T2-W MRI images were normalized with the histogram intensity scale standardization method. Features were extracted with the IBEX software. The association of each radiomic feature with risk class, T-stage, Gleason score (GS), extracapsular extension (ECE) score, and Prostate Imaging Reporting and Data System (PI-RADS v2) score was assessed by univariate and multivariate analysis. RESULTS: Forty-nine out of 65 patients were eligible. Among the 1702 features extracted, 3 to 6 features with the highest predictive power were selected for each outcome. This analysis showed that texture features were the most predictive for GS, PI-RADS v2 score, and risk class; intensity features were highly associated with T-stage, ECE score, and risk class, with areas under the receiver operating characteristic curve (ROC AUC) ranging from 0.74 to 0.94. CONCLUSIONS: MRI-based radiomics is a promising tool for prediction of PCa characteristics. Although a significant association was found between the selected features and all the mentioned clinical/radiological scores, further validations on larger cohorts are needed before these findings can be applied in the clinical practice. KEY POINTS: • A radiomic model was used to classify PCa aggressiveness. • Radiomic analysis was performed on T2-W magnetic resonance images of the whole prostate gland. • The most predictive features belong to the texture (57%) and intensity (43%) domains.

Whole-body magnetic resonance imaging (WB-MRI) for cancer screening: recommendations for use.

Whole-body magnetic resonance imaging (WB-MRI) is currently recommended for cancer screening in adult and paediatric subjects with cancer predisposition syndromes, representing a substantial aid for prolonging health and survival of these subjects with a high oncological risk. Additionally, the number of studies exploring the use of WB-MRI for cancer screening in asymptomatic subjects from the general population is growing. The primary aim of this review was to analyse the acquisition protocols found in the literature, in order to identify common sequences across published studies and to discuss the need of additional ones for specific populations. The secondary aim of this review was to provide a synthesis of current recommendations regarding the use of WB-MRI for cancer screening.

A novel nomogram to identify candidates for active surveillance amongst patients with International Society of Urological Pathology (ISUP) Grade Group (GG) 1 or ISUP GG2 prostate cancer, according to multiparametric magnetic resonance imaging findings.

OBJECTIVES: To develop a novel nomogram to identify candidates for active surveillance (AS) that combines clinical, biopsy and multiparametric magnetic resonance imaging (mpMRI) findings; and to compare its predictive accuracy to, respectively: (i) Prostate Cancer Research International: Active Surveillance (PRIAS) criteria, (ii) Johns Hopkins (JH) criteria, (iii) European Association of Urology (EAU) low-risk classification, and (iv) EAU low-risk or low-volume with International Society of Urological Pathology (ISUP) Grade Group (GG) 2 classification. PATIENTS AND METHODS: We selected 1837 patients with ISUP GG1 or GG2 prostate cancer (PCa), treated with radical prostatectomy (RP) between 2012 and 2018. The outcome of interest was the presence of unfavourable disease (i.e., clinically significant PCa [csPCa]) at RP, defined as: ISUP GG ≥ 3 and/or pathological T stage (pT) ≥3a and/or pathological N stage (pN) 1. First, logistic regression models including PRIAS, JH, EAU low-risk, and EAU low-risk or low-volume ISUP GG2 binary classifications (not eligible vs eligible) were used. Second, a multivariable logistic regression model including age, prostate-specific antigen density (PSA-D), ISUP GG, and the percentage of positive cores (Model 1) was fitted. Third, Prostate Imaging-Reporting and Data System (PI-RADS) score (Model 2), extracapsular extension (ECE) score (Model 3) and PI-RADS + ECE score (Model 4) were added to Model 1. Only variables associated with higher csPCa rates in Model 4 were retained in the final simplified Model 5. The area under the receiver operating characteristic curve (AUC), calibration plots and decision curve analyses were used. RESULTS: Of the 1837 patients, 775 (42.2%) had csPCa at RP. Overall, 837 (47.5%), 986 (53.7%), 348 (18.9%), and 209 (11.4%) patients were eligible for AS according to, respectively, the EAU low-risk, EAU low-risk or low-volume ISUP GG2, PRIAS, and JH criteria. The proportion of csPCa amongst the EAU low-risk, EAU low-risk or low-volume ISUP GG2, PRIAS and JH candidates was, respectively 28.5%, 29.3%, 25.6% and 17.2%. Model 4 and Model 5 (in which only PSA-D, ISUP GG, PI-RADS and ECE score were retained) had a greater AUC (0.84), compared to the four proposed AS criteria (all P < 0.001). The adoption of a 25% nomogram threshold increased the proportion of AS-eligible patients from 18.9% (PRIAS) and 11.4% (JH) to 44.4%. Moreover, the same 25% nomogram threshold resulted in significantly lower estimated risks of csPCa (11.3%), compared to PRIAS (Δ: -14.3%), JH (Δ: -5.9%), EAU low-risk (Δ: -17.2%), and EAU low-risk or low-volume ISUP GG2 classifications (Δ: -18.0%). CONCLUSION: The novel nomogram combining clinical, biopsy and mpMRI findings was able to increase by ~25% and 35% the absolute frequency of patients suitable for AS, compared to, respectively, the PRIAS or JH criteria. Moreover, this nomogram significantly reduced the estimated frequency of csPCa that would be recommended for AS compared to, respectively, the PRIAS, JH, EAU low-risk, and EAU low-risk or low-volume ISUP GG2 classifications.

Dynamic contrast-enhanced MRI in oncology: how we do it.

Magnetic resonance imaging (MRI) is particularly attractive for clinical application in perfusion imaging thanks to the absence of ionizing radiation and limited volumes of contrast agent (CA) necessary. Dynamic contrast-enhanced MRI (DCE-MRI) involves sequentially acquiring T1-weighted images through an organ of interest during the passage of a bolus administration of CA. It is a particularly flexible approach to perfusion imaging as the signal intensity time course allows not only rapid qualitative assessment, but also quantitative measures of intrinsic perfusion and permeability parameters. We examine aspects of the T1-weighted image series acquisition, CA administration, post-processing that constitute a DCE-MRI study in clinical practice, before considering some heuristics that may aid in interpreting the resulting contrast enhancement time series. While qualitative DCE-MRI has a well-established role in the diagnostic assessment of a range of tumours, and a central role in MR mammography, clinical use of quantitative DCE-MRI remains limited outside of clinical trials. The recent publication of proposals for standardized acquisition and analysis protocols for DCE-MRI by the Quantitative Imaging Biomarker Alliance may be an opportunity to consolidate and advance clinical practice.