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Magnetic resonance imaging (MRI) misses a proportion of "clinically significant" prostate cancers (csPC) as defined by histopathology criteria. The aim of this study was to analyze whether long-term oncologic outcomes differ between MRI-detectable and MRI-occult csPC.Retrospective analysis of 1449 patients with pre-prostatectomy MRI and csPC on prostatectomy specimens (ie, Grade group ≥2 or extraprostatic spread) between 2001-2006. T2-weighted MRIs were classified according to the Prostate Imaging Reporting and Data System into MRI-occult (categories 1, 2), MRI-equivocal (category 3), and MRI-detectable (categories 4, 5). Cumulative incidence of biochemical recurrence (BCR), metastatic disease, and cancer-specific mortality, estimated with competing risk models. The median follow-up in survivors was 11.0 years (IQR: 8.9-13.1).In 188 (13%) cases, csPC was MRI-occult, 435 (30%) MRIs were equivocal, and 826 (57%) csPC were MRI-detectable. The 15-year cumulative incidence [95% CI] of BCR was 8.3% [2.2, 19.5] for MRI-occult cases, 17.4% [11.1, 24.8] for MRI-equivocal cases, and 43.3% [38.7, 47.8] for MRI-detectable cases (P.001). The cumulative incidences of metastases were 0.61% [0.06, 3.1], 3.5% [1.5, 6.9], and 19.6% [15.4, 24.2] for MRI-occult, MRI-equivocal, and MRI-detectable cases, respectively (P.001). There were no deaths from prostate cancer observed in patients with MRI-occult csPC, compared to an estimated 1.9% [0.54, 4.9], and 7.1 % [4.5, 10.6] for patients with MRI-equivocal and MRI-detectable cancer, respectively (P.001).Oncologic outcomes after prostatectomy for csPC differ between MRI-occult and MRI-detectable lesions. Judging the clinical significance of a negative prostate MRI based on histopathologic surrogates alone might be misleading.Among 1449 patients with pre-prostatectomy MRI and clinically significant prostate cancer on prostatectomy histopathology, MRI-occult cancers (n = 188, 13%) were less likely to recur biochemically (8% vs. 43%, P.001), metastasize (0.6% vs. 20%, P.001), or lead to prostate cancer mortality (0% vs. 7%, P.001) than MRI-detectable cancers (n = 826, 57%). MRI-occult cancers constitute a prognostically distinct subgroup among higher-grade prostate cancers.

Patient Demographics.

Purpose: To investigate whether tumor volume derived from apparent diffusion coefficient (ADC) maps (VolumeADC) and tumor mean ADC value (ADCmean) are independent predictors of prostate tumor Gleason score (GS).Experimental Design: Tumor volume and GS were recorded from whole-mount histopathology for 131 men (median age, 60 years) who underwent endorectal diffusion-weighted MRI for local staging of prostate cancer before prostatectomy. VolumeADC and ADCmean were derived from ADC maps and correlated with histopathologic tumor volume and GS. Univariate and multivariate analyses were performed to evaluate prediction of tumor aggressiveness. Areas under receiver-operating characteristics curves (AUC) were calculated to evaluate the performance of VolumeADC and ADCmean in discriminating tumors of GS 6 and GS ≥7.Results: Histopathology identified 116 tumor foci >0.5 mL. VolumeADC correlated significantly with histopathologic tumor volume (ρ = 0.683). The correlation increased with increasing GS (ρ = 0.453 for GS 6 tumors; ρ = 0.643 for GS 7 tumors; ρ = 0.980 for GS ≥8 tumors). Both VolumeADC (ρ = 0.286) and ADCmean (ρ = −0.309) correlated with GS. At univariate analysis, both VolumeADC (P = 0.0325) and ADCmean (P = 0.0033) could differentiate GS = 6 from GS ≥7 tumor foci. However, at multivariate analysis, only ADCmean (P = 0.0156) was a significant predictor of tumor aggressiveness (i.e., GS 6 vs. GS ≥7). For differentiating GS 6 from GS ≥7 tumors, AUCs were 0.644 and 0.704 for VolumeADC and ADCmean, respectively, and 0.749 for both parameters combined.Conclusion: In patients with prostate cancer, ADCmean is an independent predictor of tumor aggressiveness, but VolumeADC is not. The latter parameter adds little to the ADCmean in predicting tumor GS. Clin Cancer Res; 20(14); 3705–11. ©2014 AACR.

Results of receiver operating characteristic (ROC) analysis for the identification of tumors with a Gleason score {greater than or equal to} 7. A model combining mean tumor ADC value (ADCmean) and tumor volume derived from ADC maps (VolumeADC) performed only slightly better than ADCmean alone. (Note: AUC = area under ROC curve.)

Lesion Characteristics.

BACKGROUND: It is unknown how the imperfect accuracy of MRI for local staging of prostate cancer relates to oncologic outcomes. PURPOSE: To analyze how staging discordances between MRI and histopathologic evaluation relate to recurrence and survival after radical prostatectomy. MATERIALS AND METHODS: Health Insurance Portability and Accountability Act–compliant retrospective analysis of preprostatectomy T2-weighted prostate MRI (January 2001 to December 2006). Extraprostatic extension and seminal vesicle invasion were assessed by using five-point Likert scales; scores of 4 or higher were classified as positive. Biochemical recurrence (BCR), metastases, and prostate cancer–specific mortality rates were estimated with Kaplan-Meier and Cox models. RESULTS: A total of 2160 patients (median age, 60 years; interquartile range, 55–64 years) were evaluated. Among patients with histopathologic extraprostatic (pT3) disease (683 of 2160; 32%), those with organ-confined disease at MRI (384 of 683; 56%) experienced better outcomes than those with concordant extraprostatic disease at MRI and pathologic analysis: 15-year risk for BCR, 30% (95% CI: 22, 40) versus 68% (95% CI: 60, 75); risk for metastases, 14% (95% CI: 8.4, 24) versus 32% (95% CI: 26, 39); risk for prostate cancer–specific mortality, 3% (95% CI: 1, 6) versus 15% (95% CI: 9.5, 23) (P < .001 for all comparisons). Among patients with histopathologic organ-confined disease (pT2) (1477 of 2160; 68%), those with extraprostatic disease at MRI (102 of 1477; 7%) were at higher risk for BCR (27% [95% CI: 19, 37] vs 10% [95% CI: 8, 14]; P < .001), metastases (19% [95% CI: 6, 48] vs 3% [95% CI: 1, 6]; P < .001), and prostate cancer–specific mortality (2% [95% CI: 1, 9] vs 1% [95% CI: 0, 5]; P = .009) than those with concordant organ-confined disease at MRI and pathologic analysis. At multivariable analyses, tumor extent at MRI (hazard ratio range, 4.1–5.2) and histopathologic evaluation (hazard ratio range, 3.6–6.7) was associated with the risk for BCR, metastases, and prostate cancer–specific mortality (P < .001 for all analyses). CONCLUSION: The local extent of prostate cancer at MRI is associated with oncologic outcomes after prostatectomy, independent of pathologic tumor stage. This might inform a strategy on how to integrate MRI into a clinical staging algorithm. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Gottlieb in this issue.

Background Intradiverticular bladder tumors (IDBT) are rare but clinically important, as they are difficult to assess endoscopically due to limited anatomic access and risk of perforation. MRI may be helpful in assessing IDBT and providing relevant staging and prognostic information. Purpose To assess MRI findings of IDBT and their relationship with overall survival. Methods This retrospective study included 31 consecutive patients with IDBT undergoing MRI from 2008 to 2018 identified through electronic medical records and PACS database search. Two radiologists independently assessed the following MRI features: size (>3 vs ≤3 cm), diverticular neck involvement, Vesical Imaging-Reporting and Data System (VI-RADS) score (>3 vs ≤3), perivesical fat infiltration, additional tumors and suspicious pelvic lymph nodes. Overall survival was estimated using Kaplan-Meier analysis; and the relationship with clinicopathological and MRI features was determined using the Cox proportional-hazards regression model. Inter-reader agreement was assessed using intraclass correlation coefficients (ICC) and Cohen's kappa (K). Results Median follow-up was 1044 days (interquartile range, 474–1952 days). Twenty-six (83.9%) patients underwent surgical treatment with or without neoadjuvant chemotherapy. On MRI, greater tumor size (>3 cm), diverticular neck involvement, perivesical extension, and suspicious lymph nodes were associated with lower overall survival (HR = 3.6–8.1 and 4.3–6.3 for the 2 radiologists, p ≤ 0.03). Other clinicopathological or MRI findings were not associated with survival (p = 0.27–0.65). Inter-reader agreement was excellent for tumor size (ICC = 0.991; 95% CI 0.982–0.996), fair for VI-RADS (K = 0.52, 95% CI, 0.22–0.82), and moderate for others (K = 0.61–0.79). Conclusion In patients with IDBT, several MRI features were significantly associated with overall survival. Utilizing all available clinicopathological and imaging information may improve estimation of prognosis.

The aim of the study was to evaluate the performance of the Prophet forecasting procedure, part of the Facebook open-source Artificial Intelligence portfolio, for forecasting variations in radiological examination volumes. Daily CT and MRI examination volumes from our institution were extracted from the radiology information system (RIS) database. Data from January 1, 2015, to December 31, 2019, was used for training the Prophet algorithm, and data from January 2020 was used for validation. Algorithm performance was then evaluated prospectively in February and August 2020. Total error and mean error per day were evaluated, and computational time was logged using different Markov chain Monte Carlo (MCMC) samples. Data from 610,570 examinations were used for training; the majority were CTs (82.3%). During retrospective testing, prediction error was reduced from 19 to

BACKGROUND: Patterns of metastasis in cancer are increasingly relevant to prognostication and treatment planning but have historically been documented by means of autopsy series. PURPOSE: To show the feasibility of using natural language processing (NLP) to gather accurate data from radiology reports for assessing spatial and temporal patterns of metastatic spread in a large patient cohort. MATERIALS AND METHODS: In this retrospective longitudinal study, consecutive patients who underwent CT from July 2009 to April 2019 and whose CT reports followed a departmental structured template were included. Three radiologists manually curated a sample of 2219 reports for the presence or absence of metastases across 13 organs; these manually curated reports were used to develop three NLP models with an 80%-20% split for training and test sets. A separate random sample of 448 manually curated reports was used for validation. Model performance was measured by accuracy, precision, and recall for each organ. The best-performing NLP model was used to generate a final database of metastatic disease across all patients. For each cancer type, statistical descriptive reports were provided by analyzing the frequencies of metastatic disease at the report and patient levels. RESULTS: In 91 665 patients (mean age ± standard deviation, 61 years ± 15; 46 939 women), 387 359 reports were labeled. The best-performing NLP model achieved accuracies from 90% to 99% across all organs. Metastases were most frequently reported in abdominopelvic (23.6% of all reports) and thoracic (17.6%) nodes, followed by lungs (14.7%), liver (13.7%), and bones (9.9%). Metastatic disease tropism is distinct among common cancers, with the most common first site being bones in prostate and breast cancers and liver among pancreatic and colorectal cancers. CONCLUSION: Natural language processing may be applied to cancer patients’ CT reports to generate a large database of metastatic phenotypes. Such a database could be combined with genomic studies and used to explore prognostic imaging phenotypes with relevance to treatment planning. © RSNA, 2021 Online supplemental material is available for this article.

Summary Background Female breast cancer is the most commonly diagnosed cancer in the world, with wide variations in reported survival by country. Women in low-income and middle-income countries (LMICs) in particular face several barriers to breast cancer services, including diagnostics and treatment. We aimed to estimate the potential impact of scaling up the availability of treatment and imaging modalities on breast cancer survival globally, together with improvements in quality of care. Methods For this simulation-based analysis, we used a microsimulation model of global cancer survival, which accounts for the availability and stage-specific survival impact of specific treatment modalities (chemotherapy, radiotherapy, surgery, and targeted therapy), imaging modalities (ultrasound, x-ray, CT, MRI, PET, and single-photon emission computed tomography [SPECT]), and quality of cancer care, to simulate 5-year net survival for women with newly diagnosed breast cancer in 200 countries and territories in 2018. We calibrated the model to empirical data on 5-year net breast cancer survival in 2010–14 from CONCORD-3. We evaluated the potential impact of scaling up specific imaging and treatment modalities and quality of care to the mean level of high-income countries, individually and in combination. We ran 1000 simulations for each policy intervention and report the means and 95% uncertainty intervals (UIs) for all model outcomes. Findings We estimate that global 5-year net survival for women diagnosed with breast cancer in 2018 was 67·9% (95% UI 62·9–73·4) overall, with an almost 25-times difference between low-income (3·5% [0·4–10·0]) and high-income (87·0% [85·6–88·4]) countries. Among individual treatment modalities, scaling up access to surgery alone was estimated to yield the largest survival gains globally (2·7% [95% UI 0·4–8·3]), and scaling up CT alone would have the largest global impact among imaging modalities (0·5% [0·0–2·0]). Scaling up a package of traditional modalities (surgery, chemotherapy, radiotherapy, ultrasound, and x-ray) could improve global 5-year net survival to 75·6% (95% UI 70·6–79·4), with survival in low-income countries improving from 3·5% (0·4–10·0) to 28·6% (4·9–60·1). Adding concurrent improvements in quality of care could further improve global 5-year net survival to 78·2% (95% UI 74·9–80·4), with a substantial impact in low-income countries, improving net survival to 55·3% (42·2–67·8). Comprehensive scale-up of access to all modalities and improvements in quality of care could improve global 5-year net survival to 82·3% (95% UI 79·3–85·0). Interpretation Comprehensive scale-up of treatment and imaging modalities, and improvements in quality of care could improve global 5-year net breast cancer survival by nearly 15 percentage points. Scale-up of traditional modalities and quality-of-care improvements could achieve 70% of these total potential gains, with substantial impact in LMICs, providing a more feasible pathway to improving breast cancer survival in these settings even without the benefits of future investments in targeted therapy and advanced imaging. Funding Harvard T H Chan School of Public Health, National Cancer Institute P30 Cancer Center Support Grant to Memorial Sloan Kettering Cancer Center, and Breast Cancer Research Foundation.

PURPOSE To evaluate whether a custom programmatic workflow manager reduces reporting turnaround times (TATs) from a body oncologic imaging workflow at a tertiary cancer center. METHODS A custom software program was developed and implemented in the programming language R. Other aspects of the workflow were left unchanged. TATs were measured over a 12-month period (June-May). The same prior 12-month period served as a historical control. Median TATs of magnetic resonance imaging (MRI) and computed tomography (CT) examinations were compared with a Wilcoxon test. A chi-square test was used to compare the numbers of examinations reported within 24 hours and after 72 hours as well as the proportions of examinations assigned according to individual radiologist preferences. RESULTS For all MRI and CT examinations (124,507 in 2019/2020 and 138,601 in 2020/2021), the median TAT decreased from 4 (interquartile range: 1-22 hours) to 3 hours (1-17 hours). Reports completed within 24 hours increased from 78% (124,127) to 89% (138,601). For MRI, TAT decreased from 22 (5-49 hours) to 8 hours (2-21 hours), and reports completed within 24 hours increased from 55% (14,211) to 80% (23,744). For CT, TAT decreased from 3 (1-19 hours) to 2 hours (1-13 hours), and reports completed within 24 hours increased from 84% (82,342) to 92% (99,922). Delayed reports (with a TAT > 72 hours) decreased from 17.0% (4,176) to 2.2% (649) for MRI and from 2.5% (2,500) to 0.7% (745) for CT. All differences were statistically significant ( P < .001). CONCLUSION The custom workflow management software program significantly decreased MRI and CT report TATs.

Vaccination-associated adenopathy is a frequent imaging finding after administration of COVID-19 vaccines that may lead to a diagnostic conundrum in patients with manifest or suspected cancer, in whom it may be indistinguishable from malignant nodal involvement. To help the medical community address this concern in the absence of studies and evidence-based guidelines, this paper offers recommendations developed by a multidisciplinary panel of experts from three of the leading tertiary care cancer centers in the United States. According to these recommendations, some routine imaging examinations, such as those for screening, should be scheduled before or at least 6 weeks after the final vaccination dose to allow for any reactive adenopathy to resolve. However, there should be no delay of other clinically indicated imaging (e.g., for acute symptoms, short-interval treatment monitoring, urgent treatment planning or complications) due to prior vaccination. The vaccine should be administered on the side contralateral to the primary or suspected cancer, and both doses should be administered in the same arm. Vaccination information (date(s) administered, injection site(s), laterality, and type of vaccine) should be included in every pre-imaging patient questionnaire, and this information should be made readily available to interpreting radiologists. Clear and effective communication between patients, radiologists, referring physician teams and the general public should be considered of the highest priority when managing adenopathy in the setting of COVID-19 vaccination. Summary COVID-19-vaccination–related adenopathy is a frequent imaging finding that may lead to a diagnostic conundrum in patients with manifest or suspected cancer, in whom it may be indistinguishable from malignant nodal involvement. This special report offers recommendations developed by a multidisciplinary panel of experts from three of the leading tertiary care cancer centers in the United States.

To explore ways to improve O-RADS MRI scoring for fat-containing adnexal masses, by investigating methods for quantifying solid tissue volume and fat distribution and evaluating their associations with malignancy.This retrospective, single-center study included patients with fat-containing adnexal masses on MRI during 2008-2021. Two radiologists independently reviewed overall size (Size188 women (median age 35 years) with 163 benign and 25 malignant lesions were included. SizeOverall size, size of (any or non-Rokitansky-nodule) solid tissue, and fat distribution differed between benign and malignant fat-containing adnexal masses. Incorporating these would constitute simple and practical approaches to refining O-RADS MRI scoring.

Purpose:We investigated whether T2-weighted magnetic resonance imaging findings could improve upon established prognostic indicators of metastatic disease and prostate cancer specific survival.Mate...

Radiation therapy (RT) continues to be one of the mainstays of cancer treatment. Considerable efforts have been recently devoted to integrating MRI into clinical RT planning and monitoring. This integration, known as MRI-guided RT, has been motivated by the superior soft-tissue contrast, organ motion visualization, and ability to monitor tumor and tissue physiologic changes provided by MRI compared with CT. Offline MRI is already used for treatment planning at many institutions. Furthermore, MRI-guided linear accelerator systems, allowing use of MRI during treatment, enable improved adaptation to anatomic changes between RT fractions compared with CT guidance. Efforts are underway to develop real-time MRI-guided intrafraction adaptive RT of tumors affected by motion and MRI-derived biomarkers to monitor treatment response and potentially adapt treatment to physiologic changes. These developments in MRI guidance provide the basis for a paradigm change in treatment planning, monitoring, and adaptation. Key challenges to advancing MRI-guided RT include real-time volumetric anatomic imaging, addressing image distortion because of magnetic field inhomogeneities, reproducible quantitative imaging across different MRI systems, and biologic validation of quantitative imaging. This review describes emerging innovations in offline and online MRI-guided RT, exciting opportunities they offer for advancing research and clinical care, hurdles to be overcome, and the need for multidisciplinary collaboration. (C) RSNA, 2020

RATIONALE: New biomarkers for metastatic prostate cancer are needed. The aim of this study was to evaluate the prognostic value of FDG-PET whole body tumor burden parameters in patients with metastatic prostate cancer who received first line abiraterone or enzalutamide therapy. METHODS: Retrospective study of patients with metastatic castration-sensitive (mCSPC, n = 25) and metastatic castration-resistant prostate cancer (mCRPC, n = 71) who underwent 18F-FDG-PET/CT within 90 days before first-line treatment with abiraterone or enzalutamide at a tertiary care academic cancer center. Whole-body tumor burden on PET/CT was quantified as metabolic tumor volume (MTV) and total lesion glycolysis (TLG) and correlated with overall survival (OS) probabilities using Kaplan-Meier curves and Cox models. RESULTS: The median follow-up in survivors was 56.3 months (IQR: 37.7, 66.8); the median OS for patients with mCRPC and mCSPC was 27.8 and 76.1 months (p

Abstract Women in Focus: Be Inspired was a unique programme held at the 2019 European Congress of Radiology that was structured to address a range of topics related to gender and healthcare, including leadership, mentoring and the generational progression of women in medicine. In most countries, women constitute substantially fewer than half of radiologists in academia or private practice despite frequently accounting for at least half of medical school enrolees. Furthermore, the proportion of women decreases at higher academic ranks and levels of leadership, a phenomenon which has been referred to as a “leaky pipeline”. Gender diversity in the radiologic workplace, including in academic and leadership positions, is important for the present and future success of the field. It is a tool for excellence that helps to optimize patient care and research; moreover, it is essential to overcome the current shortage of radiologists. This article reviews the current state of gender diversity in academic and leadership positions in radiology internationally and explores a wide range of potential reasons for gender disparities, including the lack of role models and mentorship, unconscious bias and generational changes in attitudes about the desirability of leadership positions. Strategies for both individuals and institutions to proactively increase the representation of women in academic and leadership positions are suggested. Key Points • Gender-diverse teams perform better. Thus, gender diversity throughout the radiologic workplace, including in leadership positions, is important for the current and future success of the field. • Though women now make up roughly half of medical students, they remain underrepresented among radiology trainees, faculty and leaders. • Factors leading to the gender gap in academia and leadership positions in Radiology include a lack of role models and mentors, unconscious biases, other societal barriers and generational changes.

BACKGROUND: Cancers of unknown primary (CUP) have traditionally been treated empirically, with a dismal prognosis. Compared with standard diagnostic tests, including CT and MRI, imaging with (18)F-fluorodeoxyglucose (FDG) PET or PET/CT has shown the capacity to better identify the primary tumor site and detect additional sites of metastasis. However, its clinical impact is not well established. We performed a systematic review and meta-analysis of prior studies to assess the impact of FDG-PET or PET/CT on the management of patients with CUP. MATERIALS AND METHODS: Pubmed and EMBASE databases were searched up to February 4, 2021. Studies that reported the proportion of patients with CUP who experienced a management change after FDG-PET or PET/CT were included, and the proportions were pooled using the random-effects model. Study quality was assessed using QUADAS-2. Subgroup analysis was conducted to explore heterogeneity. RESULTS: Thirty-eight studies (involving 2795 patients) were included. The pooled proportion of patients with management changes was 35% (95% confidence interval 31%–40%). There was substantial heterogeneity among the studies (Q-test, p

Prostate gland volume (PGV) should be routinely included in MRI reports of the prostate. The recently updated Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 includes a change in the recommended measurement method for PGV compared to version 2.0. The purpose of this study was to evaluate the agreement of MRI-based PGV calculations with the volumetric manual slice-by-slice prostate segmentation as a reference standard using the linear measurements per PI-RADS versions 2.0 and 2.1. Furthermore, to assess inter-reader agreement for the different measurement approaches, determine the influence of an enlarged transition zone on measurement accuracy and to assess the value of the bullet formula for PGV calculation.Ninety-five consecutive treatment-naive patients undergoing prostate MRI were retrospectively analyzed. Prostates were manually contoured and segmented on axial T2-weighted images. Four different radiologists independently measured the prostate in three dimensions according to PI-RADS v2.0 and v2.1, respectively. MRI-based PGV was calculated using the ellipsoid and bullet formulas. Calculated volumes were compared to the reference manual segmentations using Wilcoxon signed-rank test. Inter-reader agreement was calculated using intraclass correlation coefficient (ICC).Inter-reader agreement was excellent for the ellipsoid and bullet formulas using PI-RADS v2.0 (ICC 0.985 and 0.987) and v2.1 (ICC 0.990 and 0.994), respectively. The median difference from the reference standard using the ellipsoid formula derived PGV was 0.4 mL (interquartile range, -3.9 to 5.1 mL) for PI-RADS v2.0 (p = 0.393) and 2.6 mL (interquartile range, -1.6 to 7.3 mL) for v2.1 (p0.001) with a median difference of 2.2 mL. The bullet formula overestimated PGV by a median of 13.3 mL using PI-RADS v2.0 (p0.001) and 16.0 mL using v2.1 (p0.001). In the presence of an enlarged transition zone the PGV tended to be higher than the reference standard for PI-RADS v2.0 (median difference of 4.7 mL; p = 0.018) and for v2.1 (median difference of 5.7 mL, p0.001) using the ellipsoid formula.Inter-reader agreement was excellent for the calculated PGV for both methods. PI-RADS v2.0 measurements with the ellipsoid formula yielded the most accurate volume estimates. The differences between PI-RADS v2.0 and v2.1 were statistically significant although small in absolute numbers but may be of relevance in specific clinical scenarios like prostate-specific antigen density calculation. These findings validate the use of the ellipsoid formula and highlight that the bullet formula should not be used for prostate volume estimation due to systematic overestimation.

There has been an increasing role of magnetic resonance imaging (MRI) in the management of prostate cancer. MRI already plays an essential role in the detection and staging, with the introduction of functional MRI sequences. Recent advancements in radiomics and artificial intelligence are being tested to potentially improve detection, assessment of aggressiveness, and provide usefulness as a prognostic marker. MRI can improve pretreatment risk stratification and therefore selection of and follow-up of patients for active surveillance. MRI can also assist in guiding targeted biopsy, treatment planning and follow-up after treatment to assess local recurrence. MRI has gained importance in the evaluation of metastatic disease with emerging technology including whole-body MRI and integrated positron emission tomography/MRI, allowing for not only better detection but also quantification. The main goal of this article is to review the most recent advances on MRI in prostate cancer and provide insights into its potential clinical roles from the radiologist's perspective. In each of the sections, specific roles of MRI tailored to each clinical setting are discussed along with its strengths and weakness including already established material related to MRI and the introduction of recent advancements on MRI.

1038 Introduction: Gold nanostar (AuNS) displays a high photothermal conversion efficiency and has been applied for in vitro and in vivo photothermal therapy (PTT) of various tumors. Single photon emission computed tomography (SPECT) and positron emission tomography (PET) provide a powerful tool for in vivo tracking of nanoparticles. In this study, we synthesized PEGylated AuNS (pAuNS) and its radioactive surrogate to evaluate its biological characteristics. The results of biodistribution and SPECT images may be adopted in designing the procedure of cancer treatment. The potential of pAuNS-mediated PTT was evaluated in a SKOV-3 human ovarian tumor-bearing mouse model. Methods: AuNS with a maximal plasma absorption peak at ~790 nm and an average size of 46.8±3.6 nm was synthesized by HEPES-reduction method, and then PEGylated to obtain pAuNS. The temperature rise of pAuNS in different buffers after 793 nm near infrared (NIR) laser irradiation was recorded with a thermal camera. DTPA-conjugated pAuNS was labeled with indium-111 to obtain 111In-DTPA-pAuNS with high radiolabeling efficiency (94.8±1.4%) and good in vitro stability (>95% after 72 h of incubation in serum). The biological characterizations of 111In-DTPA-pAuNS were conducted in mice bearing SKOV-3 human ovarian xenografts. The tumor gold concentration was estimated based on the results of biodistribution and validated by the inductively coupled plasma mass spectrometry (ICP-MS). The anti-tumor effect of pAuNS-mediated PTT was also evaluated in the same animal tumor model. Results: The heat generation after NIR irradiation (1.0 and 1.5 W/cm2) of pAuNS-containing normal saline and fetal bovine serum increased in a dose-dependent manner. MicroSPECT/CT images revealed that most of 111In-DTPA-pAuNS after intravenous injection retained in liver and spleen in the tumor-bearing mice. The gold content in tumor determined by 111In-radioactivity and ICP-MS was considerably correlated (R2 >0.7), indicated that 111In-DTPA-pAuNS is a suitable radioactive surrogate of pAuNS. At 24 h post-injection of 111In-DTPA-pAuNS, the tumor-to-muscle ratio reached plateau and was selected as the time point for pAuNS-mediated PTT. Comparing to NIR irradiation only, the tumor temperature rise was more remarkable, accompanied with a significantly inhibited tumor growth, in pAuNS-mediated PTT treatment group. No pathological changes or injuries were detected in main organs following pAuNS administration. Conclusions: We demonstrated the anti-tumor effect of pAuNS-mediated PTT in treating ovarian cancer. 111In-labeled pAuNS (i.e. 111In-DTPA-pAuNS) was successfully synthesized and used for investigating the biological behaviors of pAuNS, which hence facilitated the selection of the appropriate time point for pAuNS-mediated PTT.

We thank the speakers and participants for their contributions to the workshop. The activities of the National Cancer Policy Forum are supported by its sponsoring members, which currently include the Centers for Disease Control and Prevention, the National Institutes of Health/National Cancer Institute, the American Association for Cancer Research, the American Cancer Society, the American College of Radiology, the American Society of Clinical Oncology, the Association of American Cancer Institutes, the Association of Community Cancer Centers, Bristol-Myers Squibb, the Cancer Support Community, the CEO Roundtable on Cancer, Flatiron Health, Helsinn Therapeutics (U.S.) Inc., the LIVESTRONG Foundation, Merck, the National Comprehensive Cancer Network, Novartis Oncology, the Oncology Nursing Society, and Pfizer Inc. The responsibility for the content of this article rests with the authors and does not necessarily represent the views of the National Academies of Sciences, Engineering, and Medicine, its committees, its sponsors, or its convening activities.

Introduction/Background: Radiographic progression-free survival (rPFS) based on Prostate Cancer Working Group 2 (PCWG2) has been increasingly used as a meaningful imaging-based intermediate endpoint (IBIE) for overall survival (OS) in patients with metastatic castration-resistant prostate cancer (mCRPC). In randomized phase III trials, rPFS showed good correlation with OS at the individual trial level. We aimed to assess the correlation between the hazard ratios (HR) of IBIE and OS among PCWG2-based randomized trials. Materials and Methods: Pubmed and EMBASE databases were systematically searched for randomized trials evaluating systemic treatments on mCRPC using PCWG2 up to April 15, 2020. Hazard ratios for OS and IBIEs were extracted and their correlation was assessed using weighted linear regression. Subgroup analyses were performed according to various clinical settings: prior chemotherapy, drug category, type of IBIE (rPFS vs composite IBIE, latter defined as progression by imaging and one or a combination of PSA, pain, skeletal-related events, and performance status), and publication year. Results: Twenty-eight phase II-III randomized trials (16,511 patients) were included. Correlation between OS and IBIE was good (R2=0.57, 95%CI 0.35–0.78). Trials using rPFS showed substantially higher correlation than those using a composite IBIE (R2=0.58, 95%CI 0.32–0.82 vs 0.00, 95%CI -0.01–0.01). Correlations between OS and IBIE in other subgroups were at least moderate in nearly all subgroups (R2=0.32–0.91). Conclusion: IBIEs in the era of PCWG2 correlate well with OS in randomized trials for systemic drugs in patients with mCRPC. PCWG2-based rPFS should be used instead of a composite IBIE that includes PSA and other clinical variables.

Background To assess the spectrum and frequency of modalities used for emergency room (ER) imaging and their findings in pediatric cancer patients and assess their relationship with survival. Methods Consecutive pediatric cancer patients that underwent imaging during an ER visit at our tertiary cancer center over a 5-year period were retrospectively analyzed. Imaging findings were considered positive when they were relevant to the ER presenting complaint. Imaging positivity was correlated with inpatient admission. Overall survival (OS) was assessed with Kaplan-Meier curves and uni- and multi-variate Cox proportional hazards model was used to identify significant factors associated with OS. Results Two hundred sixty-one patients (135 males and 126 females; median age 11 years [interquartile range 5–16 years] with 348 visits and a total of 406 imaging studies were included. Common chief complaints were related to the chest (100 [28.7 %]) and fever (99 [28.4 %]). ER imaging was positive in 207 visits (59.5 %), commonly revealing increased metastases (50 [14.4 %]), pneumonia (47 [13.5 %]), and other lung problems (12 [2.9 %]). Positive ER imaging was associated with inpatient admission (69.3 % [133/192] vs. 40.4 % [63/156], p p p p Conclusions Imaging was able to delineate the cause for ER visits in children with cancer in over half of the cases. Positive ER imaging was associated with admission and worse survival.

Purpose To retrospectively analyze the nature and extent of oncology-related errors accounting for malpractice allegations in diagnostic radiology. Methods The Comparative Benchmarking System of the Controlled Risk Insurance Company, a database containing roughly 30% of medical malpractice claims in the United States, was searched retrospectively for the period 2008 to 2017. Claims naming radiology as a primary service were identified and were stratified and compared by oncologic versus nononcologic status, allegation type (diagnostic versus nondiagnostic), and imaging modality. Results Over the 10-year period, radiology was the primary responsible service for 3.9% of all malpractice claims (2,582 of 66,061) and 12.8% of claims with diagnostic allegations (1,756 of 13,695). Oncology (neoplasms) accounted for 44.0% of radiology cases with diagnostic allegations, a larger share than any other category of medical condition. Among radiology cases with diagnostic allegations, high-severity harm occurred in 79% of oncologic but just 42% of nononcologic cases. Of all oncologic radiology cases, 97.4% had diagnostic allegations, and just 55.0% of nononcologic radiology cases had diagnostic allegations. Imaging misinterpretation was a contributing factor for a large majority (80.7% [623 of 772]) of oncologic radiology cases with diagnostic allegations. The modalities most commonly used in oncologic radiology cases with diagnostic allegations involving misinterpretation were mammography and CT. Conclusion Oncology represents the largest source of radiology malpractice cases with diagnostic allegations. Oncologic radiology malpractice cases are more likely than nononcologic radiology cases to be due to diagnostic errors. Furthermore, compared with those that are nononcologic, oncologic radiology cases with diagnostic allegations are more likely to be associated with high-severity harm. Efforts are warranted to reduce misinterpretations of oncologic imaging.

The diagnosis and treatment of patients with cancer requires access to imaging to ensure accurate management decisions and optimal outcomes. Our global assessment of imaging and nuclear medicine resources identified substantial shortages in equipment and workforce, particularly in low-income and middle-income countries (LMICs). A microsimulation model of 11 cancers showed that the scale-up of imaging would avert 3·2% (2·46 million) of all 76·0 million deaths caused by the modelled cancers worldwide between 2020 and 2030, saving 54·92 million life-years. A comprehensive scale-up of imaging, treatment, and care quality would avert 9·55 million (12·5%) of all cancer deaths caused by the modelled cancers worldwide, saving 232·30 million life-years. Scale-up of imaging would cost US$6·84 billion in 2020-30 but yield lifetime productivity gains of $1·23 trillion worldwide, a net return of $179·19 per $1 invested. Combining the scale-up of imaging, treatment, and quality of care would provide a net benefit of $2·66 trillion and a net return of $12·43 per $1 invested. With the use of a conservative approach regarding human capital, the scale-up of imaging alone would provide a net benefit of $209·46 billion and net return of $31·61 per $1 invested. With comprehensive scale-up, the worldwide net benefit using the human capital approach is $340·42 billion and the return per dollar invested is $2·46. These improved health and economic outcomes hold true across all geographical regions. We propose actions and investments that would enhance access to imaging equipment, workforce capacity, digital technology, radiopharmaceuticals, and research and training programmes in LMICs, to produce massive health and economic benefits and reduce the burden of cancer globally.

Summary Background In addition to increased availability of treatment modalities, advanced imaging modalities are increasingly recommended to improve global cancer care. However, estimates of the costs and benefits of investments to improve cancer survival are scarce, especially for low-income and middle-income countries (LMICs). In this analysis, we aimed to estimate the costs and lifetime health and economic benefits of scaling up imaging and treatment modality packages on cancer survival, both globally and by country income group. Methods Using a previously developed model of global cancer survival, we estimated stage-specific cancer survival and life-years gained (accounting for competing mortality) in 200 countries and territories for patients diagnosed with one of 11 cancers (oesophagus, stomach, colon, rectum, anus, liver, pancreas, lung, breast, cervix uteri, and prostate) representing 60% of all cancer diagnoses between 2020 and 2030 (inclusive of full years). We evaluated the costs and health and economic benefits of scaling up packages of treatment (chemotherapy, surgery, radiotherapy, and targeted therapy), imaging modalities (ultrasound, x-ray, CT, MRI, PET, single-photon emission CT), and quality of care to the mean level of high-income countries, separately and in combination, compared with no scale-up. Costs and benefits are presented in 2018 US$ and discounted at 3% annually. Findings For the 11 cancers studied, we estimated that without scale-up (ie, with current availability of treatment, imaging, and quality of care) there will be 76·0 million cancer deaths (95% UI 73·9–78·6) globally for patients diagnosed between 2020 and 2030, with more than 70% of these deaths occurring in LMICs. Comprehensive scale-up of treatment, imaging, and quality of care could avert 12·5% (95% UI 9·0–16·3) of these deaths globally, ranging from 2·8% (1·8–4·3) in high-income countries to 38·2% (32·6–44·5) in low-income countries. Globally, we estimate that comprehensive scale-up would cost an additional $232·9 billion (95% UI 85·9–422·0) between 2020 and 2030 (representing a 6·9% increase in cancer treatment costs), but produce $2·9 trillion (1·8–4·0) in lifetime economic benefits, yielding a return of $12·43 (6·47–33·23) per dollar invested. Scaling up treatment and quality of care without imaging would yield a return of $6·15 (2·66–16·71) per dollar invested and avert 7·0% (3·9–10·3) of cancer deaths worldwide. Interpretation Simultaneous investment in cancer treatment, imaging, and quality of care could yield substantial health and economic benefits, especially in LMICs. These results provide a compelling rationale for the value of investing in the global scale-up of cancer care. Funding Harvard TH Chan School of Public Health and National Cancer Institute.

New biomarkers for metastatic prostate cancer are needed. The aim of this study was to evaluate the prognostic value of (18)F-FDG PET whole-body tumor burden parameters in patients with metastatic prostate cancer who received first-line abiraterone or enzalutamide therapy. Methods: This was a retrospective study of patients with metastatic castration-sensitive prostate cancer (mCSPC, n = 25) and metastatic castration-resistant prostate cancer (mCRPC, n = 71) who underwent (18)F-FDG PET/CT within 90 d before first-line treatment with abiraterone or enzalutamide at a tertiary-care academic cancer center. Whole-body tumor burden on PET/CT was quantified as metabolic tumor volume (MTV) and total lesion glycolysis (TLG) and correlated with overall survival (OS) probabilities using Kaplan–Meier curves and Cox models. Results: The median follow-up in survivors was 56.3 mo (interquartile range, 37.7–66.8 mo); the median OSs for patients with mCRPC and mCSPC were 27.8 and 76.1 mo, respectively (P < 0.001). On univariate analysis, the OS probability of mCRPC patients was significantly associated with plasma levels of alkaline phosphatase (hazard ratio [HR], 1.90; P < 0.001), plasma levels of lactate dehydrogenase (HR, 1.01; P < 0.001), hemoglobin levels (HR, 0.80; P = 0.013), whole-body SUV(max) (HR, 1.14; P < 0.001), the number of (18)F-FDG–avid metastases (HR, 1.08; P < 0.001), whole-body metabolic tumor volume (HR, 1.86; P < 0.001), and TLG (HR, 1.84; P < 0.001). On multivariable analysis with stepwise variable selection, hemoglobin levels (HR, 0.81; P = 0.013) and whole-body TLG (HR, 1.88; P < 0.001) were independently associated with OS. In mCSPC patients, no significant association was observed between these variables and OS. Conclusion: In patients with mCRPC receiving first-line treatment with abiraterone or enzalutamide, (18)F-FDG PET WB TLG is independently associated with OS and might be used as a quantitative prognostic imaging biomarker.

Purpose Prostate-specific membrane antigen positron emission tomography (PSMA-PET) has shown promise for detecting nodal and distant prostate cancer (PCa) metastases. However, its performance for local tumor staging is not as well established. The purpose of this study was to review the diagnostic performance of PSMA-PET for determining seminal vesical invasion (SVI) and extraprostatic extension (EPE). Methods Pubmed and Embase databases were searched until January 12, 2020. Studies assessing accuracy of PSMA-PET in determining SVI and EPE were included. Study quality was evaluated with the revised Quality Assessment of Diagnostic Accuracy Studies-2 tool. Pooled sensitivity and specificity were calculated using hierarchical summary receiver operating characteristics modeling. Heterogeneity was explored using meta-regression analyses for anatomical imaging component (MRI vs CT) and by testing for a threshold effect. Results Twelve studies (615 patients) were included. Pooled sensitivity and specificity were 0.68 (95% CI 0.53-0.81) and 0.94 (95% CI 0.90-0.96) for SVI and 0.72 (95% CI 0.56-0.84) and 0.87 (95% CI 0.72-0.94) for EPE. Meta-regression analyses showed that for SVI, PET/MRI demonstrated greater sensitivity than PET/CT (0.87 [95% CI 0.75-0.98] vs 0.60 [95% CI 0.47-0.74]; p = 0.02 for joint model) while specificity was comparable (0.91 [95% CI 0.84-0.97] vs. 0.96 [95% CI 0.93-0.99]) but not for EPE (p = 0.08). A threshold effect was present for studies assessing EPE (correlation coefficient = 0.563 [95% CI, −0.234-0.908] between sensitivity and false-positive rate). Conclusion PSMA-PET has moderate sensitivity and excellent specificity for assessing local tumor extent in patients with PCa. PET/MRI showed potential for greater sensitivity than PET/CT in assessing SVI.

Summary Background Accurate survival estimates are important for cancer control planning. Although observed survival estimates are unavailable for many countries, where they are available, wide variations are reported. Understanding the impact of specific treatment and imaging modalities can help decision makers to effectively allocate resources to improve cancer survival in their local context. Methods We developed a microsimulation model of stage-specific cancer survival in 200 countries and territories for 11 cancers (oesophagus, stomach, colon, rectum, anus, liver, pancreas, lung, breast, cervix uteri, and prostate) comprising 60% of global diagnosed cancer cases. The model accounts for country-specific availability of treatment (chemotherapy, surgery, radiotherapy, and targeted therapy) and imaging modalities (ultrasound, x-ray, CT, MRI, PET, single-photon emission CT), as well as quality of care. We calibrated the model to reported survival estimates from CONCORD-3 (which reports global trends in cancer survival in 2000–14). We estimated 5-year net survival for diagnosed cancers in each country or territory and estimated potential survival gains from increasing the availability of individual treatment and imaging modalities, and more comprehensive packages of scale-up of these interventions. We report the mean and 95% uncertainty intervals (UIs) for all outcomes, calculated as the 2·5 and 97·5 percentiles of the simulation results. Findings The estimated global 5-year net survival for all 11 cancers combined is 42·6% (95% uncertainty interval 40·3–44·3), with survival in high-income countries being an average of 12 times (range 4–17) higher than that in low-income countries. Expanding availability of surgery or radiotherapy or improving quality of care would yield the largest survival gains in low-income (2·5–3·4 percentage point increase in survival) and lower-middle-income countries (2·4–6·1 percentage point increase), whereas upper-middle-income and high-income countries are more likely to benefit from improved availability of targeted therapy (0·7 percentage point increase for upper-middle income and 0·4 percentage point increase for high income). Investing in medical imaging will also be necessary to achieve substantial survival gains, with traditional modalities estimated to provide the largest gains in low-income settings, while MRI and PET would yield the largest gains in higher-income countries. Simultaneous expansion of treatment, imaging, and quality of care could improve 5-year net survival by more than ten times in low-income countries (3·8% [95% UI 0·5–9·2] to 45·2% [40·2–52·1]) and could more than double 5-year net survival in lower-middle-income countries (20·1% [7·2–31·7] to 47·1% [42·8–50·8]). Interpretation Scaling up both treatment and imaging availability could yield synergistic survival gains for patients with cancer. Expanding traditional modalities in lower-income settings might be a feasible pathway to improve survival before scaling up more modern technologies. Funding Harvard T H Chan School of Public Health.

To characterize national trends in oncologic imaging (OI) utilization.This retrospective cross-sectional study used 2004 and 2016 CMS 5% Carrier Claims Research Identifiable Files. Radiologist-performed, primary noninvasive diagnostic imaging examinations were identified from billed Current Procedural Terminology codes; CT, MRI, and PET/CT examinations were categorized as "advanced" imaging. OI examinations were identified from imaging claims' primary International Classification of Diseases-9 and International Classification of Diseases-10 codes. Imaging services were stratified by academic practice status and place of service. State-level correlations of oncologic advanced imaging utilization (examinations per 1,000 beneficiaries) with cancer prevalence and radiologist supply were assessed by Spearman correlation coefficient.The national Medicare sample included 5,051,095 diagnostic imaging examinations (1,220,224 of them advanced) in 2004 and 5,023,115 diagnostic imaging examinations (1,504,608 of them advanced) in 2016. In 2004 and 2016, OI represented 4.3% and 3.9%, respectively, of all imaging versus 10.8% and 9.5%, respectively, of advanced imaging. The percentage of advanced OI done in academic practices rose from 18.8% in 2004 to 34.1% in 2016, leaving 65.9% outside academia. In 2016, 58.0% of advanced OI was performed in the hospital outpatient setting and 23.9% in the physician office setting. In 2016, state-level oncologic advanced imaging utilization correlated with state-level radiologist supply (r = +0.489, P.001) but not with state-level cancer prevalence (r = -0.139, P = .329).OI usage varied between practice settings. Although the percentage of advanced OI done in academic settings nearly doubled from 2004 to 2016, the majority remained in nonacademic practices. State-level oncologic advanced imaging utilization correlated with radiologist supply but not cancer prevalence.

Importance There is an enormous and growing amount of data available from individual cancer cases, which makes the work of clinical oncologists more demanding. This data challenge has attracted engineers to create software that aims to improve cancer diagnosis or treatment. However, the move to use computers in the oncology clinic for diagnosis or treatment has led to instances of premature or inappropriate use of computational predictive systems. Objective To evaluate best practices for developing and assessing the clinical utility of predictive computational methods in oncology. Evidence Review The National Cancer Policy Forum and the Board on Mathematical Sciences and Analytics at the National Academies of Sciences, Engineering, and Medicine hosted a workshop to examine the use of multidimensional data derived from patients with cancer and the computational methods used to analyze these data. The workshop convened diverse stakeholders and experts, including computer scientists, oncology clinicians, statisticians, patient advocates, industry leaders, ethicists, leaders of health systems (academic and community based), private and public health insurance carriers, federal agencies, and regulatory authorities. Key characteristics for successful computational oncology were considered in 3 thematic areas: (1) data quality, completeness, sharing, and privacy; (2) computational methods for analysis, interpretation, and use of oncology data; and (3) clinical infrastructure and expertise for best use of computational precision oncology. Findings Quality control was found to be essential across all stages, from data collection to data processing, management, and use. Collecting a standardized parsimonious data set at every cancer diagnosis and restaging could enhance reliability and completeness of clinical data for precision oncology. Data completeness refers to key data elements such as information about cancer diagnosis, treatment, and outcomes, while data quality depends on whether appropriate variables have been measured in valid and reliable ways. Collecting data from diverse populations can reduce the risk of creating invalid and biased algorithms. Computational systems that aid clinicians should be classified as software as a medical device and thus regulated according to the potential risk posed. To facilitate appropriate use of computational methods that interpret high-dimensional data in oncology, treating physicians need access to multidisciplinary teams with broad expertise and deep training among a subset of clinical oncology fellows in clinical informatics. Conclusions and Relevance Workshop discussions suggested best practices in demonstrating the clinical utility of predictive computational methods for diagnosing or treating cancer.

The 2019 European Congress of Radiology program, “Women in Focus: Be Inspired,” offered insights from successful women and men for overcoming a number of everyday work and personal life challenges. With regard to balancing career and personal life and achieving well-being, the advice of female and male radiology leaders on the front lines, throughout the world, shares common themes. This paper highlights and expands on points of advice and encouragement from the “Women in Focus” program. The first step is to know yourself, so you can set priorities. Then, take charge, be brave, and follow your dreams, which may not be the same as other people’s. Finding balance requires examining your goals and acknowledging that you may not be able to get everything you want all at once. Receiving effective mentorship from numerous sources is key, as is finding an environment that supports your growth. It is important to surround yourself both at work and at home with people who support your ideas and give you a sense of peace, well-being, and resilience. If the culture does not fit, have the courage to move on. Current leaders should reach out to ensure the diversity of future teams. Society benefits, radiology benefits, and our patients benefit from a specialty that values equity, diversity, and inclusiveness.

To review the diagnostic performance of contemporary imaging modalities for determining local disease extent and nodal metastasis in patients with newly diagnosed cervical cancer. Pubmed and Embase databases were searched for studies published from 2000 to 2019 that used ultrasound (US), CT, MRI, and/or PET for evaluating various aspects of local extent and nodal metastasis in patients with newly diagnosed cervical cancer. Sensitivities and specificities from the studies were meta-analytically pooled using bivariate and hierarchical modeling. Of 1311 studies identified in the search, 115 studies with 13,999 patients were included. MRI was the most extensively studied modality (MRI, CT, US, and PET were evaluated in 78, 12, 9, and 43 studies, respectively). Pooled sensitivities and specificities of MRI for assessing all aspects of local extent ranged between 0.71–0.88 and 0.86–0.95, respectively. In assessing parametrial invasion (PMI), US demonstrated pooled sensitivity and specificity of 0.67 and 0.94, respectively—performance levels comparable with those found for MRI. MRI, CT, and PET performed comparably for assessing nodal metastasis, with low sensitivity (0.29–0.69) but high specificity (0.88–0.98), even when stratified to anatomical location (pelvic or paraaortic) and level of analysis (per patient vs. per site). MRI is the method of choice for assessing any aspect of local extent, but where not available, US could be of value, particularly for assessing PMI. CT, MRI, and PET all have high specificity but poor sensitivity for the detection of lymph node metastases. • Magnetic resonance imaging is the method of choice for assessing local extent. • Ultrasound may be helpful in determining parametrial invasion, especially in lower-resourced countries. • Computed tomography, magnetic resonance imaging, and positron emission tomography perform similarly for assessing lymph node metastasis, with high specificity but low sensitivity.

The aim of this study was to test an interactive up-to-date meta-analysis (iu-ma) of studies on MRI in the management of men with suspected prostate cancer. Based on the findings of recently published systematic reviews and meta-analyses, two freely accessible dynamic meta-analyses (https://iu-ma.org) were designed using the programming language R in combination with the package “shiny.” The first iu-ma compares the performance of the MRI-stratified pathway and the systematic transrectal ultrasound-guided biopsy pathway for the detection of clinically significant prostate cancer, while the second iu-ma focuses on the use of biparametric versus multiparametric MRI for the diagnosis of prostate cancer. Our iu-mas allow for the effortless addition of new studies and data, thereby enabling physicians to keep track of the most recent scientific developments without having to resort to classical static meta-analyses that may become outdated in a short period of time. Furthermore, the iu-mas enable in-depth subgroup analyses by a wide variety of selectable parameters. Such an analysis is not only tailored to the needs of the reader but is also far more comprehensive than a classical meta-analysis. In that respect, following multiple subgroup analyses, we found that even for various subgroups, detection rates of prostate cancer are not different between biparametric and multiparametric MRI. Secondly, we could confirm the favorable influence of MRI biopsy stratification for multiple clinical scenarios. For the future, we envisage the use of this technology in addressing further clinical questions of other organ systems. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10278-019-00312-1) contains supplementary material, which is available to authorized users.

Purpose: To investigate associations between imaging features of tumors and age, gender and body mass index (BMI) in patients with renal cell carcinoma. Method: This IRB-approved, HIPAA-compliant study included 1348 patients with histopathologically confirmed renal cell carcinoma of the clear cell subtype (ccRCC, n = 904) or non-clear cell subtype (n = 444), who underwent pre-treatment CT imaging less than 180 days before nephrectomy between 1999 and 2011. Two radiologists independently, retrospectively analyzed all imaging studies and identified features (necrosis, renal vein invasion, contact with renal sinus fat, multicystic appearance and nodular enhancement), which were then correlated with patient age, gender and BMI at time of surgery. Results: Inter-reader agreement on imaging features ranged from substantial to excellent (kappa: 0.688 to 0.982). In the ccRCC group, multicystic tumor appearance was significantly associated with lower patient age (p < 0.05) and lower BMI (p < 0.05); the presence of renal vein invasion was significantly associated with lower BMI in males (p < 0.05); and both tumor contact with the renal sinus and nodular enhancement were significantly associated with greater patient age (p < 0.05). In the non-clear cell RCC group, necrosis was associated with lower BMI for females (p < 0.05). Conclusions: This study demonstrated significant associations between imaging features of RCC and patient age and BMI, hinting an influence of these factors on tumor biology and genomic make-up. These findings could aid future studies in selecting patients while investigating genomic, molecular and metabolic variables in RCC and might potentially impact on future stratification and therapy of patients.