Real-World Experience With the Angio-Seal Closure Device: Insights From Manufacturer and User Facility Device Experience Database.

PURPOSE: Angio-Seal (Terumo Medical Corporations, Somerset, New Jersey) device is indicated for femoral arteriotomy closure. Real-world published data on complications are limited. We present 1 year of safety events involving Angio-Seal from the US Food and Drug Administration's post-market surveillance database of Manufacturer and User Facility Device Experience (MAUDE). Steps for managing frequent device-related problems are discussed. MATERIALS AND METHODS: Angio-Seal MAUDE data from November 2019 to December 2020 was classified according to (1) mode of device failure, (2) complication, (3) treatment, and (4) Cardiovascular and Interventional Radiological Society of Europe (CIRSE) adverse event classification system. RESULTS: There were 715 safety events, involving Angio-Seal VIP (93.1%), Evolution (5.7%), STS Plus (1.1%), and sizes 6F (62.5%) and 8F (37.5%). Failure mode involved unrecognized use of a damaged device (43.4%), failed deployment (20.1%), failed arterial advancement (6.3%), detachment of device component (4.9%), failed retraction (3.6%), operator error (1.1%), and indeterminate (20.6%). Of total, 44.8% of events were associated with patient harm. Complications involved minor blood loss (34.1%), hematoma (5.6%), significant blood loss (1.4%), and pseudoaneurysm (1.4%). Of total, 43.3% of cases required manual compression (MC), whereas 8.8% required more advanced intervention. Interventions included surgical repair (49.2%), thrombin injection (9.5%), balloon tamponade (6.3%), covered stent (4.8%), and unspecified (30.2%). Majority of safety events were CIRSE grade 1 (92.0%), followed by grades 2 (3.1%), 3 (4.6%), and 6 (deaths, 0.3%). Minority of devices were returned for manufacturer analysis (27.8%). CONCLUSIONS: The majority of safety events were associated with minor blood loss or local hematoma and could be addressed with MC alone. Most events were attributed to damaged device; however, very few devices were returned to manufacturer for analysis. This should be encouraged to allow for root cause analysis in order to improve safety profile of devices. System-level strategies for addressing barriers to under-reporting of safety events may also be considered. CLINICAL IMPACT: Our study highlights important safety events encountered in real-world practice with Angio-Seal closure device. The MAUDE database captures real-world device malfunctions not typically appreciated in conventional clinical trials. Our study provides valuable insight for clinician-users on anticipating and managing the most common device malfunctions. Additionally, our data provide feedback for manufactures to optimize product design and direct manufacturer user training to improve safety. Finally, we hope that the study promotes system-level strategies that foster reporting of safety events and undertaking of root cause analysis.

Development of a Radiomics-Based Model to Predict Graft Fibrosis in Liver Transplant Recipients: A Pilot Study.

Liver Transplantation is complicated by recurrent fibrosis in 40% of recipients. We evaluated the ability of clinical and radiomic features to flag patients at risk of developing future graft fibrosis. CT scans of 254 patients at 3-6 months post-liver transplant were retrospectively analyzed. Volumetric radiomic features were extracted from the portal phase using an Artificial Intelligence-based tool (PyRadiomics). The primary endpoint was clinically significant (≥F2) graft fibrosis. A 10-fold cross-validated LASSO model using clinical and radiomic features was developed. In total, 75 patients (29.5%) developed ≥F2 fibrosis by a median of 19 (4.3-121.8) months. The maximum liver attenuation at the venous phase (a radiomic feature reflecting venous perfusion), primary etiology, donor/recipient age, recurrence of disease, brain-dead donor, tacrolimus use at 3 months, and APRI score at 3 months were predictive of ≥F2 fibrosis. The combination of radiomics and the clinical features increased the AUC to 0.811 from 0.793 for the clinical-only model (p = 0.008) and from 0.664 for the radiomics-only model (p < 0.001) to predict future ≥F2 fibrosis. This pilot study exploring the role of radiomics demonstrates that the addition of radiomic features in a clinical model increased the model's performance. Further studies are required to investigate the generalizability of this experimental tool.

Predicting the recurrence risk of renal cell carcinoma after nephrectomy: potential role of CT-radiomics for adjuvant treatment decisions.

OBJECTIVES: Previous trial results suggest that only a small number of patients with non-metastatic renal cell carcinoma (RCC) benefit from adjuvant therapy. We assessed whether the addition of CT-based radiomics to established clinico-pathological biomarkers improves recurrence risk prediction for adjuvant treatment decisions. METHODS: This retrospective study included 453 patients with non-metastatic RCC undergoing nephrectomy. Cox models were trained to predict disease-free survival (DFS) using post-operative biomarkers (age, stage, tumor size and grade) with and without radiomics selected on pre-operative CT. Models were assessed using C-statistic, calibration, and decision curve analyses (repeated tenfold cross-validation). RESULTS: At multivariable analysis, one of four selected radiomic features (wavelet-HHL_glcm_ClusterShade) was prognostic for DFS with an adjusted hazard ratio (HR) of 0.44 (p = 0.02), along with American Joint Committee on Cancer (AJCC) stage group (III versus I, HR 2.90; p = 0.002), grade 4 (versus grade 1, HR 8.90; p = 0.001), age (per 10 years HR 1.29; p = 0.03), and tumor size (per cm HR 1.13; p = 0.003). The discriminatory ability of the combined clinical-radiomic model (C = 0.80) was superior to that of the clinical model (C = 0.78; p < 0.001). Decision curve analysis revealed a net benefit of the combined model when used for adjuvant treatment decisions. At an exemplary threshold probability of ≥ 25% for disease recurrence within 5 years, using the combined versus the clinical model was equivalent to treating 9 additional patients (per 1000 assessed) who would recur without treatment (i.e., true-positive predictions) with no increase in false-positive predictions. CONCLUSION: Adding CT-based radiomic features to established prognostic biomarkers improved post-operative recurrence risk assessment in our internal validation study and may help guide decisions regarding adjuvant therapy. KEY POINTS: In patients with non-metastatic renal cell carcinoma undergoing nephrectomy, CT-based radiomics combined with established clinical and pathological biomarkers improved recurrence risk assessment. Compared to a clinical base model, the combined risk model enabled superior clinical utility if used to guide decisions on adjuvant treatment.

Typology, Severity, and Outcomes of Adverse Events Related to Angiographic Equipment-A Ten-Year Analysis of the FDA MAUDE Database.

Purpose: Angiographic equipment is a key component of healthcare infrastructure, used for endovascular procedures throughout the body. The literature on adverse events related to this technology is limited. The purpose of this study was to analyze adverse events related to angiographic devices from the US Food and Drug Administration's Manufacturer and User Facility Device Experience (MAUDE) database. Methods: MAUDE data on angiographic imaging equipment from July 2011 to July 2021 were extracted. Qualitative content analysis was performed, a typology of adverse events was derived, and this was used to classify the data. Outcomes were assessed using the Healthcare Performance Improvement (HPI) and Society of Interventional Radiology (SIR) adverse event classifications. Results: There were 651 adverse events reported. Most were near misses (67%), followed by precursor safety events (20.5%), serious safety events (11.2%), and unclassifiable (1.2%). Events impacted patients (42.1%), staff (3.2%), both (1.2%), or neither (53.5%). The most common events associated with patient harm were intra-procedure system shut down, foot pedal malfunction, table movement malfunction, image quality deterioration, patient falls, and fluid damage to system. Overall, 34 (5.2%) events were associated with patient death; 18 during the procedure and 5 during patient transport to another angiographic suite/hospital due to critical failure of equipment. Conclusion: Adverse events related to angiographic equipment are rare; however, serious adverse events and deaths have been reported. This study has defined a typology of the most common adverse events associated with patient and staff harm. Increased understanding of these failures may lead to improved product design, user training, and departmental contingency planning.

Combined autologous blood patch-immediate patient rollover does not reduce the pneumothorax or chest drain rate following CT-guided lung biopsy compared to immediate patient rollover alone.

PUPROSE: The purpose of this study was to evaluate a combined autologous blood-patch (ABP)-immediate patient rollover (IPR) technique compared with the IPR technique alone on the incidence of pneumothorax and chest drainage following CT-guided lung biopsy. METHODS: In this interventional cohort study of both prospectively and retrospectively acquired data, 652 patients underwent CT-guided lung biopsy. Patient demographics, lesion characteristics and technical biopsy variables including the combined ABP-IPR versus IPR alone were evaluated as predictors of pneumothorax and chest drain rates using regression analysis. RESULTS: The combined ABP-IPR technique was performed in 259 (39.7 %) patients whilst 393 (60.3 %) underwent IPR alone. There was no significant difference in pneumothorax rate or chest drains required between the combined ABP-IPR vs IPR groups (p =.08, p =.60 respectively). Predictors of pneumothorax adjusted for the combined ABP-IPR and IPR alone groups included age (p =.02), lesion size (p =.01), location (p =.005), patient position (p =.008), emphysema along the needle track (p =.005) and lesion distance from the pleura (p =.02). Adjusted predictors of chest drain insertion included lesion location (p =.09), patient position (p =.002), bullae crossed (p =.02) and lesion distance from the pleura (p =.02). CONCLUSION: The combined ABP-IPR technique does not reduce the pneumothorax or chest drain rate compared to the IPR technique alone. Utilising IPR without an ABP following CT-guided lung biopsy results in similar pneumothorax and chest drain rates while minimising the potential risk of systemic air embolism.

Correlation of transcriptional subtypes with a validated CT radiomics score in resectable pancreatic ductal adenocarcinoma.

OBJECTIVES: Transcriptional classifiers (Bailey, Moffitt and Collison) are key prognostic factors of pancreatic ductal adenocarcinoma (PDAC). Among these classifiers, the squamous, basal-like, and quasimesenchymal subtypes overlap and have inferior survival. Currently, only an invasive biopsy can determine these subtypes, possibly resulting in treatment delay. This study aimed to investigate the association between transcriptional subtypes and an externally validated preoperative CT-based radiomic prognostic score (Rad-score). METHODS: We retrospectively evaluated 122 patients who underwent resection for PDAC. All treatment decisions were determined at multidisciplinary tumor boards. Tumor Rad-score values from preoperative CT were dichotomized into high or llow categories. The primary endpoint was the correlation between the transcriptional subtypes and the Rad-score using multivariable linear regression, adjusting for clinical and histopathological variables (i.e., tumor size). Prediction of overall survival (OS) was secondary endpoint. RESULTS: The Bailey transcriptional classifier significantly associated with the Rad-score (coefficient = 0.31, 95% confidence interval [CI]: 0.13-0.44, p = 0.001). Squamous subtype was associated with high Rad-scores while non-squamous subtype was associated with low Rad-scores (adjusted p = 0.03). Squamous subtype and high Rad-score were both prognostic for OS at multivariable analysis with hazard ratios (HR) of 2.79 (95% CI: 1.12-6.92, p = 0.03) and 4.03 (95% CI: 1.42-11.39, p = 0.01), respectively. CONCLUSIONS: In patients with resectable PDAC, an externally validated prognostic radiomic model derived from preoperative CT is associated with the Bailey transcriptional classifier. Higher Rad-scores were correlated with the squamous subtype, while lower Rad-scores were associated with the less lethal subtypes (immunogenic, ADEX, pancreatic progenitor). KEY POINTS: • The transcriptional subtypes of PDAC have been shown to have prognostic importance but they require invasive biopsy to be assessed. • The Rad-score radiomic biomarker, which is obtained non-invasively from preoperative CT, correlates with the Bailey squamous transcriptional subtype and both are negative prognostic biomarkers. • The Rad-score is a promising non-invasive imaging biomarker for personalizing neoadjuvant approaches in patients undergoing resection for PDAC, although additional validation studies are required.

Prostate biopsy in the era of MRI-targeting: towards a judicious use of additional systematic biopsy.

OBJECTIVES: We aimed to develop and compare strategies that help optimize current prostate biopsy practice by identifying patients who may forgo concurrent systematic biopsy (SBx) in favor of MRI-targeted (TBx) alone. METHODS: Retrospective study on 745 patients who underwent combined MRI-TBx plus SBx. Primary outcome was the upgrade to clinically significant prostate cancer (csPCa; grade group ≥ 2) on SBx versus MRI-TBx. Variables (age, previous biopsy status, Prostate Imaging Reporting and Data System (PI-RADS) score, index lesion size/location, number of lesions, PSA, PSA density, prostate volume) associated with the primary outcome were identified by logistic regression and used for biopsy strategies. Clinical utility was assessed by decision curve analysis (DCA). RESULTS: SBx detected 47 (6%) additional men with csPCa. The risk of detecting csPCa uniquely on SBx was significantly lower in men with PI-RADS 5 (versus PI-RADS 3: OR 0.30, p = 0.03; versus PI-RADS 4: OR 0.33, p = 0.01), and previous negative biopsy (versus previous positive biopsy: OR 0.40, p = 0.007), and increased with age (per 10 years: OR 1.64, p = 0.016). No significant association was observed for other variables. DCA identified the following strategies as most useful: (a) avoid SBx in men with PI-RADS 5 and (b) additionally in those with previous negative biopsy, resulting in avoiding SBx in 201 (27%) and 429 (58%), while missing csPCa in 5 (1%) and 15 (2%) patients, respectively. CONCLUSION: Not all men benefit equally from the combination of SBx and MRI-TBx. SBx avoidance in men with PI-RADS 5 and/or previous negative biopsy may reduce the risk of excess biopsies with a low risk of missing csPCa. KEY POINTS: • In men undergoing MRI-targeted biopsy, the risk of detecting clinically significant prostate cancer (csPCa) only on additional systematic biopsy (SBx) decreased in men with PI-RADS 5, previous negative biopsy, and younger age. • Using these variables may help select men who could avoid the risk of excess SBx. • If missing csPCa in 5% was acceptable, forgoing SBx in men with PI-RADS 5 and/or previous negative biopsy enabled the highest net reduction in SBx.

Radiology artificial intelligence: a systematic review and evaluation of methods (RAISE).

OBJECTIVE: There has been a large amount of research in the field of artificial intelligence (AI) as applied to clinical radiology. However, these studies vary in design and quality and systematic reviews of the entire field are lacking.This systematic review aimed to identify all papers that used deep learning in radiology to survey the literature and to evaluate their methods. We aimed to identify the key questions being addressed in the literature and to identify the most effective methods employed. METHODS: We followed the PRISMA guidelines and performed a systematic review of studies of AI in radiology published from 2015 to 2019. Our published protocol was prospectively registered. RESULTS: Our search yielded 11,083 results. Seven hundred sixty-seven full texts were reviewed, and 535 articles were included. Ninety-eight percent were retrospective cohort studies. The median number of patients included was 460. Most studies involved MRI (37%). Neuroradiology was the most common subspecialty. Eighty-eight percent used supervised learning. The majority of studies undertook a segmentation task (39%). Performance comparison was with a state-of-the-art model in 37%. The most used established architecture was UNet (14%). The median performance for the most utilised evaluation metrics was Dice of 0.89 (range .49-.99), AUC of 0.903 (range 1.00-0.61) and Accuracy of 89.4 (range 70.2-100). Of the 77 studies that externally validated their results and allowed for direct comparison, performance on average decreased by 6% at external validation (range increase of 4% to decrease 44%). CONCLUSION: This systematic review has surveyed the major advances in AI as applied to clinical radiology. KEY POINTS: • While there are many papers reporting expert-level results by using deep learning in radiology, most apply only a narrow range of techniques to a narrow selection of use cases. • The literature is dominated by retrospective cohort studies with limited external validation with high potential for bias. • The recent advent of AI extensions to systematic reporting guidelines and prospective trial registration along with a focus on external validation and explanations show potential for translation of the hype surrounding AI from code to clinic.

Patient radiation dose during angiography and embolization for abdominal hemorrhage: the influence of CT angiography, fluoroscopy system, patient and procedural variables.

BACKGROUND: Angiography and embolization (AE) is a lifesaving, high radiation dose procedure for treatment of abdominal arterial hemorrhage (AAH). Interventional radiologists have utilized pre-procedure CT angiography (CTA) and newer fluoroscopic systems in an attempt to reduce radiation dose and procedure time. PURPOSE: To study the factors contributing to the radiation dose of AE for AAH and to compare to the reference standard. MATERIALS AND METHODS: This retrospective single-centre observational cohort study identified 154 consecutive AE procedures in 138 patients (median age 65 years; interquartile range 54-77; 103 men) performed with a C-arm fluoroscopic system (Axiom Artis DTA or Axiom Artis Q (Siemens Healthineers)), between January 2010 and December 2017. Parameters analysed included: demographics, fluoroscopy system, bleeding location, body mass index (BMI), preprocedural CT, air kerma-area product (PKA), reference air kerma (Ka,r), fluoroscopy time (FT) and the number of digital subtraction angiography (DSA) runs. Factors affecting dose were assessed using Mann-Whitney U, Kruskal-Wallis one-way ANOVA and linear regression. RESULTS: Patients treated with the new angiographic system (NS) had a median PKA, median Ka,r, Q3 PKA and Q3 Ka,r that were 74% (p < 0.0005), 66%(p < 0.0005), 55% and 52% lower respectively than those treated with the old system (OS). This dose reduction was consistent for each bleeding location (upper GI, Lower GI and extraluminal). There was no difference in PKA (p = 0.452), Ka,r (p = 0.974) or FT (p = 0.179), between those who did (n = 137) or did not (n = 17) undergo pre-procedure CTA. Other factors significantly influencing radiation dose were: patient BMI and number of DSA runs. A multivariate model containing these variables accounts for 15.2% of the variance in Ka,r (p < 0.005) and 45.9% of the variance of PKA (p < 0.005). CONCLUSION: Radiation dose for AE in AAH is significantly reduced by new fluoroscopic technology. Higher patient body mass index is an independent key parameter affecting patient dose. Radiation dose was not influenced by haemorrhage site or performance of pre-procedure CTA.

Pre-operative radiomics model for prognostication in resectable pancreatic adenocarcinoma with external validation.

OBJECTIVES: In resectable pancreatic ductal adenocarcinoma (PDAC), few pre-operative prognostic biomarkers are available. Radiomics has demonstrated potential but lacks external validation. We aimed to develop and externally validate a pre-operative clinical-radiomic prognostic model. METHODS: Retrospective international, multi-center study in resectable PDAC. The training cohort included 352 patients (pre-operative CTs from five Canadian hospitals). Cox models incorporated (a) pre-operative clinical variables (clinical), (b) clinical plus CT-radiomics, and (c) post-operative TNM model, which served as the reference. Outcomes were overall (OS)/disease-free survival (DFS). Models were assessed in the validation cohort from Ireland (n = 215, CTs from 34 hospitals), using C-statistic, calibration, and decision curve analyses. RESULTS: The radiomic signature was predictive of OS/DFS in the validation cohort, with adjusted hazard ratios (HR) 2.87 (95% CI: 1.40-5.87, p < 0.001)/5.28 (95% CI 2.35-11.86, p < 0.001), respectively, along with age 1.02 (1.01-1.04, p = 0.01)/1.02 (1.00-1.04, p = 0.03). In the validation cohort, median OS was 22.9/37 months (p = 0.0092) and DFS 14.2/29.8 (p = 0.0023) for high-/low-risk groups and calibration was moderate (mean absolute errors 7%/13% for OS at 3/5 years). The clinical-radiomic model discrimination (C = 0.545, 95%: 0.543-0.546) was higher than the clinical model alone (C = 0.497, 95% CI 0.496-0.499, p < 0.001) or TNM (C = 0.525, 95% CI: 0.524-0.526, p < 0.001). Despite superior net benefit compared to the clinical model, the clinical-radiomic model was not clinically useful for most threshold probabilities. CONCLUSION: A multi-institutional pre-operative clinical-radiomic model for resectable PDAC prognostication demonstrated superior net benefit compared to a clinical model but limited clinical utility at external validation. This reflects inherent limitations of radiomics for PDAC prognostication, when deployed in real-world settings. KEY POINTS: • At external validation, a pre-operative clinical-radiomics prognostic model for pancreatic ductal adenocarcinoma (PDAC) outperformed pre-operative clinical variables alone or pathological TNM staging. • Discrimination and clinical utility of the clinical-radiomic model for treatment decisions remained low, likely due to heterogeneity of CT acquisition parameters. • Despite small improvements, prognosis in PDAC using state-of-the-art radiomics methodology remains challenging, mostly owing to its low discriminative ability. Future research should focus on standardization of CT protocols and acquisition parameters.

Comparison of Inline R2* MRI versus FerriScan for liver iron quantification in patients on chelation therapy for iron overload: preliminary results.

OBJECTIVES: MRI quantification of liver iron concentration (LIC) using R2 or R2* relaxometry requires offline post-processing causing reporting delays, administrative overhead, and added costs. A prototype 3D multi-gradient-echo pulse sequence, with inline post-processing, allows immediate calculation of LIC from an R2* map (inline R2*-LIC) without offline processing. We compared inline R2*-LIC to FerriScan and offline R2* calibration methods. METHODS: Forty patients (25 women, 15 men; age 18-82 years), prospectively underwent FerriScan and the prototype sequence, which produces two R2* maps, with and without fat modeling, as well as an inline R2*-LIC map derived from the R2* map with fat modeling, with informed consent. For each map, the following contours were drawn: ROIs, whole-axial-liver contour, and an exact copy of contour utilized by FerriScan. LIC values from the FerriScan report and those calculated using an alternative R2 calibration were the reference standards. Results were compared using Pearson and interclass correlation coefficients (PCC, ICC), linear regression, Bland-Altman analysis, and estimation of area under the receiver operator curve (ROC-AUC). RESULTS: Inline R2*-LIC demonstrated good agreement with the reference standards. Compared to FerriScan, inline R2*-LIC with whole-axial-liver contour, ROIs, and FerriScan contour demonstrated PCC of 94.8%, 94.8%, and 92%; ICC 93%, 92.7%, and 90.2%; regression slopes 1.004, 0.974, and 1.031; mean bias 5.54%, 10.91%, and 0.36%; and ROC-AUC estimates 0.903, 0.906, and 0.890 respectively. Agreement was maintained when adjusted for sex, age, diagnosis, liver fat content, and fat-water swap. CONCLUSION: Inline R2*-LIC provides robust and comparable quantification of LIC compared to FerriScan, without the need for offline post-processing. KEY POINTS: • In patients being treated for iron overload with chelation therapy, liver iron concentration (LIC) is regularly assessed in order to monitor and adjust therapy. • Magnetic resonance imaging (MRI) is commonly used to quantify LIC. Several R2 and R2* methods are available, all of which require offline post-processing. • A novel R2* MRI method allows for immediate calculation of LIC and provides comparable quantification of LIC to the FerriScan and recently published alternative R2* methods.

Avoiding Unnecessary Biopsy: MRI-based Risk Models versus a PI-RADS and PSA Density Strategy for Clinically Significant Prostate Cancer.

Background In validation studies, risk models for clinically significant prostate cancer (csPCa; Gleason score ≥3+4) combining multiparametric MRI and clinical factors have demonstrated poor calibration (over- and underprediction) and limited use in avoiding unnecessary prostate biopsies. Purpose MRI-based risk models following local recalibration were compared with a strategy that combined Prostate Imaging Data and Reporting System (PI-RADS; version 2) and prostate-specific antigen density (PSAd) to assess the potential reduction of unnecessary prostate biopsies. Materials and Methods This retrospective study included 385 patients without prostate cancer diagnosis who underwent multipara-metric MRI (PI-RADS category ≥3) and MRI-targeted biopsy between 2015 and 2019. Recalibration and selection of the best-performing MRI model (MRI-European Randomized Study of Screening for Prostate Cancer [ERSPC], van Leeuwen, Radtke, and Mehralivand models) were undertaken in cohort C1 (n = 242; 2015-2017). The impact on biopsy decisions was compared with an alternative strategy (no biopsy for PI-RADS category 3 plus PSAd < 0.1 ng/mL per milliliter) in cohort C2 (n = 143; 2018-2019). Discrimination, calibration, and clinical utility were assessed by using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis, respectively. Results The prevalence of csPCa was 38% (93 of 242 patients) and 45% (64 of 143 patients) in cohorts C1 and C2, respectively. Decision curve analysis demonstrated the highest net benefit for the van Leeuwen and Mehralivand models in C1. Used for biopsy decisions in C2, van Leeuwen (AUC, 0.84; 95% CI: 0.77, 0.9) and Mehralivand (AUC, 0.79; 95% CI: 0.72, 0.86) enabled no net benefit at a risk threshold of 10%. Up to a risk threshold of 15%, net benefit remained inferior to the PI-RADS plus PSAd strategy, which avoided biopsy in 63 per 1000 men, without missing csPCa. Without prior recalibration in C1, three of four models (MRIERSPC, Radtke, Mehralivand) were poorly calibrated and not clinically useful in C2. Conclusion The number of unnecessary prostate biopsies in men with positive MRI may be safely reduced by using a prostate-specific antigen density-based strategy. In a risk-averse scenario, this strategy enabled better biopsy decisions compared with MRI-based risk models. ©RSNA, 2021 Online supplemental material is available for this article.

Prognostic value of early changes in CT-measured body composition in patients receiving chemotherapy for unresectable pancreatic cancer.

OBJECTIVES: Skeletal muscle mass is a prognostic factor in pancreatic ductal adenocarcinoma (PDAC). However, it remains unclear whether changes in body composition provide an incremental prognostic value to established risk factors, especially the Response Evaluation Criteria in Solid Tumors version 1.1 (RECISTv1.1). The aim of this study was to determine the prognostic value of CT-quantified body composition changes in patients with unresectable PDAC starting chemotherapy. METHODS: We retrospectively evaluated 105 patients with unresectable (locally advanced or metastatic) PDAC treated with FOLFIRINOX (n = 64) or gemcitabine-based (n = 41) first-line chemotherapy within a multicenter prospective trial. Changes (Δ) in skeletal muscle index (SMI), subcutaneous (SATI), and visceral adipose tissue index (VATI) between pre-chemotherapy and first follow-up CT were assessed. Cox regression models and covariate-adjusted survival curves were used to identify predictors of overall survival (OS). RESULTS: At multivariable analysis, adjusting for RECISTv1.1-response at first follow-up, ΔSMI was prognostic for OS with a hazard ratio (HR) of 1.2 (95% CI: 1.08-1.33, p = 0.001). No significant association with OS was observed for ΔSATI (HR: 1, 95% CI: 0.97-1.04, p = 0.88) and ΔVATI (HR: 1.01, 95% CI: 0.99-1.04, p = 0.33). At an optimal cutoff of 2.8 cm2/m2 per 30 days, the median survival of patients with high versus low ΔSMI was 143 versus 233 days (p < 0.001). CONCLUSIONS: Patients with a lower rate of skeletal muscle loss at first follow-up demonstrated improved survival for unresectable PDAC, regardless of their RECISTv1.1-category. Assessing ΔSMI at the first follow-up CT may be useful for prognostication, in addition to routine radiological assessment. KEY POINTS: • In patients with unresectable pancreatic ductal adenocarcinoma, change of skeletal muscle index (ΔSMI) in the early phase of chemotherapy is prognostic for overall survival, even after adjusting for Response Evaluation Criteria in Solid Tumors version 1.1 (RECISTv1.1) assessment at first follow-up. • Changes in adipose tissue compartments at first follow-up demonstrated no significant association with overall survival. • Integrating ΔSMI into routine radiological assessment may improve prognostic stratification and impact treatment decision-making at the first follow-up.

Radiology artificial intelligence, a systematic evaluation of methods (RAISE): a systematic review protocol.

INTRODUCTION: There has been a recent explosion of research into the field of artificial intelligence as applied to clinical radiology with the advent of highly accurate computer vision technology. These studies, however, vary significantly in design and quality. While recent guidelines have been established to advise on ethics, data management and the potential directions of future research, systematic reviews of the entire field are lacking. We aim to investigate the use of artificial intelligence as applied to radiology, to identify the clinical questions being asked, which methodological approaches are applied to these questions and trends in use over time. METHODS AND ANALYSIS: We will follow the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines and by the Cochrane Collaboration Handbook. We will perform a literature search through MEDLINE (Pubmed), and EMBASE, a detailed data extraction of trial characteristics and a narrative synthesis of the data. There will be no language restrictions. We will take a task-centred approach rather than focusing on modality or clinical subspecialty. Sub-group analysis will be performed by segmentation tasks, identification tasks, classification tasks, pegression/prediction tasks as well as a sub-analysis for paediatric patients. ETHICS AND DISSEMINATION: Ethical approval will not be required for this study, as data will be obtained from publicly available clinical trials. We will disseminate our results in a peer-reviewed publication. Registration number PROSPERO: CRD42020154790.

Differentiating combined pulmonary fibrosis and emphysema from pure emphysema: utility of late gadolinium-enhanced MRI.

BACKGROUND: Differentiating combined pulmonary fibrosis with emphysema (CPFE) from pure emphysema can be challenging on high-resolution computed tomography (HRCT). This has antifibrotic therapy implications. METHODS: Twenty patients with suspected CPFE underwent late gadolinium-enhanced (LGE) thoracic magnetic resonance imaging (LGE-MRI) and HRCT. Data from twelve healthy control subjects from a previous study who underwent thoracic LGE-MRI were included for comparison. Quantitative LGE signal intensity (SI) was retrospectively compared in regions of fibrosis and emphysema in CPFE patients to similar lung regions in controls. Qualitative comparisons for the presence/extent of reticulation, honeycombing, and traction bronchiectasis between LGE-MRI and HRCT were assessed by two readers in consensus. RESULTS: There were significant quantitative differences in fibrosis SI compared to emphysema SI in CPFE patients (25.8, IQR 18.4-31.0 versus 5.3, IQR 5.0-8.1, p < 0.001). Significant differences were found between LGE-MRI and HRCT in the extent of reticulation (12.5, IQR 5.0-20.0 versus 25.0, IQR 15.0-26.3, p = 0.038) and honeycombing (5.0, IQR 0.0-10.0 versus 20.0, IQR 10.6-20.0, p = 0.001) but not traction bronchiectasis (10.0, IQR 5-15 versus 15.0, IQR 5-15, p = 0.878). Receiver operator curve analysis of fibrosis SI compared to similarly located regions in control subjects showed an area under the curve of 0.82 (p = 0.002). A SI cutoff of 19 yielded a sensitivity of 75% and specificity of 86% in differentiating fibrosis from similarly located regions in control subjects. CONCLUSION: LGE-MRI can differentiate CPFE from pure emphysema and may be a useful adjunct test to HRCT in patients with suspected CPFE.

Conventional angiography findings in hemodynamically unstable patients with acute abdominal hemorrhage and a negative CT bleeding study.

BACKGROUND: CT bleeding study (CTA) is regularly requested in acute abdominal haemorrhage (AAH) with haemodynamic instability by clinical teams and interventional radiologists because CTA can; detect arterial bleeding at low rates of hemorrhage, accurately localize the bleeding point and characterize the etiology. How best to manage an unstable patient who has an AAH with a haematoma and no acute vascular findings on CTA represents a difficult clinical scenario for treating physicians and Interventional Radiologists. PURPOSE: To review the conventional angiography (CA) findings and clinical outcome of hemodynamically unstable patients with AAH who had a preceding negative CTA. MATERIALS AND METHODS: All patients who were hemodynamically unstable and underwent CTA and CA for acute arterial abdominal hemorrhage at our institution between 01/01/2010 and 31/12/2017 were identified. Patients with obstetric, penetrating trauma, abdominal aortic or venous sources of hemorrhage were excluded. Patients who had a negative CTA before CA were included. Patient medical records were reviewed for clinical outcome. RESULTS: In the study period 160 hemodynamically unstable patients underwent 178 CA procedures. 155 CA procedures were preceded by CTA. 141 CTAs demonstrated active bleeding or an abnormal artery. 14 CTAs in 13 patients demonstrated hematoma but no acute bleeding (mean age = 56-years; M:F, 12:1). Eight of the 14 CA studies demonstrated: active bleeding (n = 4), pseudoaneurysm (n = 1) or a truncated artery (n = 3). Cases of renal hemorrhage demonstrated a significantly higher proportion of false negative CTA studies (36%). Selective (n = 8) or empiric (n = 4) embolization was performed in twelve cases. All patients stopped bleeding and there were no mortalities. CONCLUSION: In a cohort of hemodynamically unstable patients, 57% (8/14) of cases with no acute vascular findings on CTA demonstrated a source of hemorrhage on CA. The false negative rate of CTA was significantly higher for renal tract hemorrhage compared to other sites of bleeding.

The Integration of Active Learning Teaching Strategies Into a Radiology Rotation for Medical Students Improves Radiological Interpretation Skills and Attitudes Toward Radiology.

PURPOSE: In recent years, there has been increased recognition of the benefits of teaching by active learning. However, there is a paucity of experimental studies utilizing active learning in undergraduate radiology rotations, which is traditionally a passive learning experience. We designed a new radiology rotation that integrated teaching by active learning. We prospectively examined the efficacy of this new rotation compared to our standard rotation in terms of students' radiological competency and attitudes toward radiology, as well as impact on departmental efficiency. METHODS: This was a prospective cohort study involving fourth year medical students completing a 1-week radiology rotation at our department between January and April 2018. One cohort completed a rotational model which incorporated active learning sessions (integrated cohort) while the remainder were taught using traditional passive learning methods (standard cohort). All participants completed a radiology examination before and after the rotation and were surveyed on their attitudes toward radiology. RESULTS: A total of 105 students enrolled in the study. The mean postrotation competency score obtained by the integrated cohort was significantly higher than that obtained by the standard cohort (82% vs 62%; P < 0.001). The integrated rotation freed up 7 hours of radiologists' time per week. While the students completing the integrated rotation had a more positive perception of radiology, they were no more likely to express a desire to pursue a career in radiology. CONCLUSIONS: The integration of active learning sessions into an undergraduate radiology rotation results in an improvement in students' postrotation radiological competency and attitudes toward radiology.