Pre-operative spine tumour embolization: Clinical outcomes and effect of embolization completeness.

INTRODUCTION: To assess the association between the impact of the completeness of pre-operative spine tumour embolisation and clinical outcomes, including estimated blood loss (EBL), neurological status and complications. METHODS: Retrospective chart review of all preoperative spine tumour embolisation procedures performed over 11 years by a single operator (2007-2018) at Vancouver General Hospital on 44 consecutive patients (mean age 57; 77% males) with 46 embolisation procedures, of which surgery was done en bloc in 26 cases and intralesional in the remaining 20. A multivariable negative binomial regression model was fit to examine the association between EBL and surgery type, tumour characteristics, embolisation completeness and operative duration. RESULTS: Among intralesional surgeries, complete versus incomplete embolisation was associated with reduced blood loss (772 vs 1428 mL, P < 0.01). There was no statistically significant difference in neurological outcomes or complications between groups. Highly vascular tumours correlated with greater blood loss than their less vascular counterparts, but tumour location did not have a statistically significant effect. CONCLUSION: This study provides evidence in support of our hypothesis that complete as opposed to incomplete tumour embolisation correlates with reduced blood loss in intralesional surgeries. Randomised control trials with larger samples are necessary to confirm this benefit and to ascertain other potential clinical benefits.

LI-RADS CT and MRI Ancillary Feature Association with Hepatocellular Carcinoma and Malignancy: An Individual Participant Data Meta-Analysis.

Background The independent contribution of each Liver Imaging Reporting and Data System (LI-RADS) CT or MRI ancillary feature (AF) has not been established. Purpose To evaluate the association of LI-RADS AFs with hepatocellular carcinoma (HCC) and malignancy while adjusting for LI-RADS major features through an individual participant data (IPD) meta-analysis. Materials and Methods Medline, Embase, Cochrane Central Register of Controlled Trials, and Scopus were searched from January 2014 to January 2022 for studies evaluating the diagnostic accuracy of CT and MRI for HCC using LI-RADS version 2014, 2017, or 2018. Using a one-step approach, IPD across studies were pooled. Adjusted odds ratios (ORs) and 95% CIs were derived from multivariable logistic regression models of each AF combined with major features except threshold growth (excluded because of infrequent reporting). Liver observation clustering was addressed at the study and participant levels through random intercepts. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2. Results Twenty studies comprising 3091 observations (2456 adult participants; mean age, 59 years ± 11 [SD]; 1849 [75.3%] men) were included. In total, 89% (eight of nine) of AFs favoring malignancy were associated with malignancy and/or HCC, 80% (four of five) of AFs favoring HCC were associated with HCC, and 57% (four of seven) of AFs favoring benignity were negatively associated with HCC and/or malignancy. Nonenhancing capsule (OR = 3.50 [95% CI: 1.53, 8.01]) had the strongest association with HCC. Diffusion restriction (OR = 14.45 [95% CI: 9.82, 21.27]) and mild-moderate T2 hyperintensity (OR = 10.18 [95% CI: 7.17, 14.44]) had the strongest association with malignancy. The strongest negative associations with HCC were parallels blood pool enhancement (OR = 0.07 [95% CI: 0.01, 0.49]) and marked T2 hyperintensity (OR = 0.18 [95% CI: 0.07, 0.45]). Seventeen studies (85%) had a high risk of bias. Conclusion Most LI-RADS AFs were independently associated with HCC, malignancy, or benignity as intended when adjusting for major features. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Crivellaro in this issue.

Comparative Performance of 2018 LI-RADS versus Modified LIRADS (mLI-RADS): An Individual Participant Data Meta-Analysis.

BACKGROUND: LI-RADS version 2018 (v2018) is used for non-invasive diagnosis of hepatocellular carcinoma (HCC). A recently proposed modification (known as mLI-RADS) demonstrated improved sensitivity while maintaining specificity and positive predictive value (PPV) of LI-RADS category 5 (definite HCC) for HCC. However, mLI-RADS requires multicenter validation. PURPOSE: To evaluate the performance of v2018 and mLI-RADS for liver lesions in a large, heterogeneous, multi-national cohort of patients at risk for HCC. STUDY TYPE: Systematic review and meta-analysis using individual participant data (IPD) [Study Protocol: https://osf.io/duys4]. POPULATION: 2223 observations from 1817 patients (includes all LI-RADS categories; females = 448, males = 1361, not reported = 8) at elevated risk for developing HCC (based on LI-RADS population criteria) from 12 retrospective studies. FIELD STRENGTH/SEQUENCE: 1.5T and 3T; complete liver MRI with gadoxetate disodium, including axial T2w images and dynamic axial fat-suppressed T1w images precontrast and in the arterial, portal venous, transitional, and hepatobiliary phases. Diffusion-weighted imaging was used when available. ASSESSMENT: Liver observations were categorized using v2018 and mLI-RADS. The diagnostic performance of each system's category 5 (LR-5 and mLR-5) for HCC were compared. STATISTICAL TESTS: The Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS-2 was applied to determine risk of bias and applicability. Diagnostic performances were assessed using the likelihood ratio test for sensitivity and specificity and the Wald test for PPV. The significance level was P < 0.05. RESULTS: 17% (2/12) of the studies were considered low risk of bias (244 liver observations; 164 patients). When compared to v2018, mLR-5 demonstrated higher sensitivity (61.3% vs. 46.5%, P < 0.001), similar PPV (85.3% vs. 86.3%, P = 0.89), and similar specificity (85.8% vs. 90.8%, P = 0.16) for HCC. DATA CONCLUSION: This study confirms mLR-5 has higher sensitivity than LR-5 for HCC identification, while maintaining similar PPV and specificity, validating the mLI-RADS proposal in a heterogeneous, international cohort. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Individual Participant Data Meta-Analysis of LR-5 in LI-RADS Version 2018 versus Revised LI-RADS for Hepatocellular Carcinoma Diagnosis.

Background A simplification of the Liver Imaging Reporting and Data System (LI-RADS) version 2018 (v2018), revised LI-RADS (rLI-RADS), has been proposed for imaging-based diagnosis of hepatocellular carcinoma (HCC). Single-site data suggest that rLI-RADS category 5 (rLR-5) improves sensitivity while maintaining positive predictive value (PPV) of the LI-RADS v2018 category 5 (LR-5), which indicates definite HCC. Purpose To compare the diagnostic performance of LI-RADS v2018 and rLI-RADS in a multicenter data set of patients at risk for HCC by performing an individual patient data meta-analysis. Materials and Methods Multiple databases were searched for studies published from January 2014 to January 2022 that evaluated the diagnostic performance of any version of LI-RADS at CT or MRI for diagnosing HCC. An individual patient data meta-analysis method was applied to observations from the identified studies. Quality Assessment of Diagnostic Accuracy Studies version 2 was applied to determine study risk of bias. Observations were categorized according to major features and either LI-RADS v2018 or rLI-RADS assignments. Diagnostic accuracies of category 5 for each system were calculated using generalized linear mixed models and compared using the likelihood ratio test for sensitivity and the Wald test for PPV. Results Twenty-four studies, including 3840 patients and 4727 observations, were analyzed. The median observation size was 19 mm (IQR, 11-30 mm). rLR-5 showed higher sensitivity compared with LR-5 (70.6% [95% CI: 60.7, 78.9] vs 61.3% [95% CI: 45.9, 74.7]; P < .001), with similar PPV (90.7% vs 92.3%; P = .55). In studies with low risk of bias (n = 4; 1031 observations), rLR-5 also achieved a higher sensitivity than LR-5 (72.3% [95% CI: 63.9, 80.1] vs 66.9% [95% CI: 58.2, 74.5]; P = .02), with similar PPV (83.1% vs 88.7%; P = .47). Conclusion rLR-5 achieved a higher sensitivity for identifying HCC than LR-5 while maintaining a comparable PPV at 90% or more, matching the results presented in the original rLI-RADS study. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Sirlin and Chernyak in this issue.

Point-of-care Ultrasound to Assess Hemodynamic Contributors to Acute Kidney Injury in Pediatric Patients With Cerebral Malaria: A Pilot Study.

BACKGROUND: Acute kidney injury is common in severe malaria and is independently associated with mortality. The pathogenesis of acute kidney injury (AKI) in severe malaria remains incompletely understood. Ultrasound-based tools such as point-of-care ultrasound (POCUS), ultrasound cardiac output monitors (USCOMs) and renal arterial resistive index (RRI) can be used to detect hemodynamic and renal blood flow abnormalities contributing to AKI in malaria. METHODS: We conducted a prospective study of Malawian children with cerebral malaria to determine the feasibility of using POCUS and USCOM to characterize hemodynamic contributors to severe AKI (Kidney Disease: Improving Global Outcomes stage 2 or 3). The primary outcome was feasibility (completion rate of study procedures). We also assessed for differences in POCUS and hemodynamic variables for patients with or without severe AKI. RESULTS: We enrolled 27 patients who had admission cardiac and renal ultrasounds and USCOM. Completion rates were high for cardiac (96%), renal (100%) and USCOM studies (96%). Severe AKI occurred in 13 of 27 patients (48%). No patients had ventricular dysfunction. Only 1 patient in the severe AKI group was determined to be hypovolemic ( P = 0.64). No significant differences in USCOM, RRI or venous congestion parameters were detected among patients with and without severe AKI. Mortality was 11% (3/27) with the 3 deaths occurring in the severe AKI group ( P = 0.056). CONCLUSIONS: Ultrasound-based cardiac, hemodynamic and renal blood flow measurements appear to be feasible in pediatric patients with cerebral malaria. We were unable to detect hemodynamic or renal blood flow abnormalities contributing to severe AKI in cerebral malaria. Larger studies are needed to corroborate these findings.

How to Critically Appraise and Interpret Systematic Reviews and Meta-Analyses of Diagnostic Accuracy: A User Guide.

Systematic reviews of diagnostic accuracy studies can provide the best available evidence to inform decisions regarding the use of a diagnostic test. In this guide, the authors provide a practical approach for clinicians to appraise diagnostic accuracy systematic reviews and apply their results to patient care. The first step is to identify an appropriate systematic review with a research question matching the clinical scenario. The user should evaluate the rigor of the review methods to evaluate its credibility (Did the review use clearly defined eligibility criteria, a comprehensive search strategy, structured data collection, risk of bias and applicability appraisal, and appropriate meta-analysis methods?). If the review is credible, the next step is to decide whether the diagnostic performance is adequate for clinical use (Do sensitivity and specificity estimates exceed the threshold that makes them useful in clinical practice? Are these estimates sufficiently precise? Is variability in the estimates of diagnostic accuracy across studies explained?). Diagnostic accuracy systematic reviews that are judged to be credible and provide diagnostic accuracy estimates with sufficient certainty and relevance are the most useful to inform patient care. This review discusses comparative, noncomparative, and emerging approaches to systematic reviews of diagnostic accuracy using a clinical scenario and examples based on recent publications.

Is There Evidence of P-Hacking in Imaging Research?

BACKGROUND: P-hacking, the tendency to run selective analyses until they become significant, is prevalent in many scientific disciplines. PURPOSE: This study aims to assess if p-hacking exists in imaging research. METHODS: Protocol, data, and code available here https://osf.io/xz9ku/?view_only=a9f7c2d841684cb7a3616f567db273fa. We searched imaging journals Ovid MEDLINE from 1972 to 2021. Text mining using Python script was used to collect metadata: journal, publication year, title, abstract, and P-values from abstracts. One P-value was randomly sampled per abstract. We assessed for evidence of p-hacking using a p-curve, by evaluating for a concentration of P-values just below .05. We conducted a one-tailed binomial test (α = .05 level of significance) to assess whether there were more P-values falling in the upper range (e.g., .045 < P < .05) than in the lower range (e.g., .04 < P < .045). To assess variation in results introduced by our random sampling of a single P-value per abstract, we repeated the random sampling process 1000 times and pooled results across the samples. Analysis was done (divided into 10-year periods) to determine if p-hacking practices evolved over time. RESULTS: Our search of 136 journals identified 967,981 abstracts. Text mining identified 293,687 P-values, and a total of 4105 randomly sampled P-values were included in the p-hacking analysis. The number of journals and abstracts that were included in the analysis as a fraction and percentage of the total number was, respectively, 108/136 (80%) and 4105/967,981 (.4%). P-values did not concentrate just under .05; in fact, there were more P-values falling in the lower range (e.g., .04 < P < .045) than falling just below .05 (e.g., .045 < P < .05), indicating lack of evidence for p-hacking. Time trend analysis did not identify p-hacking in any of the five 10-year periods. CONCLUSION: We did not identify evidence of p-hacking in abstracts published in over 100 imaging journals since 1972. These analyses cannot detect all forms of p-hacking, and other forms of bias may exist in imaging research such as publication bias and selective outcome reporting.

Chest CT Findings in Marijuana Smokers.

Background Global consumption of marijuana is increasing, but there is a paucity of evidence concerning associated lung imaging findings. Purpose To use chest CT to investigate the effects of marijuana smoking in the lung. Materials and Methods This retrospective case-control study evaluated results of chest CT examinations (from October 2005 to July 2020) in marijuana smokers, nonsmoker control patients, and tobacco-only smokers. We compared rates of emphysema, airway changes, gynecomastia, and coronary artery calcification. Age- and sex-matched subgroups were created for comparison with tobacco-only smokers older than 50 years. Results were analyzed using χ2 tests. Results A total of 56 marijuana smokers (34 male; mean age, 49 years ± 14 [SD]), 57 nonsmoker control patients (32 male; mean age, 49 years ± 14), and 33 tobacco-only smokers (18 male; mean age, 60 years ± 6) were evaluated. Higher rates of emphysema were seen among marijuana smokers (42 of 56 [75%]) than nonsmokers (three of 57 [5%]) (P < .001) but not tobacco-only smokers (22 of 33 [67%]) (P = .40). Rates of bronchial thickening, bronchiectasis, and mucoid impaction were higher among marijuana smokers compared with the other groups (P < .001 to P = .04). Gynecomastia was more common in marijuana smokers (13 of 34 [38%]) than in control patients (five of 32 [16%]) (P = .039) and tobacco-only smokers (two of 18 [11%]) (P = .040). In age-matched subgroup analysis of 30 marijuana smokers (23 male), 29 nonsmoker control patients (17 male), and 33 tobacco-only smokers (18 male), rates of bronchial thickening, bronchiectasis, and mucoid impaction were again higher in the marijuana smokers than in the tobacco-only smokers (P < .001 to P = .006). Emphysema rates were higher in age-matched marijuana smokers (28 of 30 [93%]) than in tobacco-only smokers (22 of 33 [67%]) (P = .009). There was no difference in rate of coronary artery calcification between age-matched marijuana smokers (21 of 30 [70%]) and tobacco-only smokers (28 of 33 [85%]) (P = .16). Conclusion Airway inflammation and emphysema were more common in marijuana smokers than in nonsmokers and tobacco-only smokers, although variable interobserver agreement and concomitant cigarette smoking among the marijuana-smoking cohort limits our ability to draw strong conclusions. © RSNA, 2022 See also the editorial by Galvin and Franks in this issue.

The Impact of Virtual Monoenergetic Imaging on Visualization of the Cervical Spinal Canal.

RATIONALE AND OBJECTIVES: Our purpose is to explore the role of dual-energy computed tomography (DECT) and virtual monoenergetic energy levels in reducing shoulder artifact to improve visualization of the cervical spinal canal. MATERIALS AND METHODS: A retrospective review of 171 consecutive DECT scans of the neck (95 male, 65 female; mean age, 60.9 years, ranging from 18 to 88 years; with 11 excluded because of nondiagnostic image quality) during an 8-month period was performed with postprocessing of monoenergetic images at 50, 70, 100, and 140 keV. Subjective comparisons and objective image noise between the monoenergetic images and standard computed tomography (CT) were analyzed by 1-way analysis of variance to determine the optimal DECT energy level with the highest image quality. RESULTS: Subjectively, 100-keV DECT best visualizes the spinal canal relative to standard CT, 50 and 70 keV ( P < 0.01), and was superior to 140 keV for reader 1 ( P < 0.01). Objectively, 100 keV demonstrated less noise relative to 50 keV (72.02; P < 0.01). There was no difference in noise between 100 keV and 70 keV, or between 100 keV and standard CT, which also demonstrated lower noise relative to 50-, 70-, and 140-keV levels (91.53, P < 0.01; 29.84, P < 0.01; and 22.66, P < 0.03). CONCLUSION: Dual-energy CT at 100 keV may be the preferred DECT monoenergetic level for soft tissue assessment. Increasing energy level is associated with reduction in shoulder artifact, with no difference in noise between 100 keV and standard CT, although 100-keV images may be subjectively better.

Radiomics artificial intelligence modelling for prediction of local control for colorectal liver metastases treated with radiotherapy.

Background and Purpose: Prognostic assessment of local therapies for colorectal liver metastases (CLM) is essential for guiding management in radiation oncology. Computed tomography (CT) contains liver texture information which may be predictive of metastatic environments. To investigate the feasibility of analyzing CT texture, we sought to build an automated model to predict progression-free survival using CT radiomics and artificial intelligence (AI). Materials and Methods: Liver CT scans and outcomes for N = 97 CLM patients treated with radiotherapy were retrospectively obtained. A survival model was built by extracting 108 radiomic features from liver and tumor CT volumes for a random survival forest (RSF) to predict local progression. Accuracies were measured by concordance indices (C-index) and integrated Brier scores (IBS) with 4-fold cross-validation. This was repeated with different liver segmentations and radiotherapy clinical variables as inputs to the RSF. Predictive features were identified by perturbation importances. Results: The AI radiomics model achieved a C-index of 0.68 (CI: 0.62-0.74) and IBS below 0.25 and the most predictive radiomic feature was gray tone difference matrix strength (importance: 1.90 CI: 0.93-2.86) and most predictive treatment feature was maximum dose (importance: 3.83, CI: 1.05-6.62). The clinical data only model achieved a similar C-index of 0.62 (CI: 0.56-0.69), suggesting that predictive signals exist in radiomics and clinical data. Conclusions: The AI model achieved good prediction accuracy for progression-free survival of CLM, providing support that radiomics or clinical data combined with machine learning may aid prognostic assessment and management.

Thoracic imaging tests for the diagnosis of COVID-19.

BACKGROUND: Our March 2021 edition of this review showed thoracic imaging computed tomography (CT) to be sensitive and moderately specific in diagnosing COVID-19 pneumonia. This new edition is an update of the review. OBJECTIVES: Our objectives were to evaluate the diagnostic accuracy of thoracic imaging in people with suspected COVID-19; assess the rate of positive imaging in people who had an initial reverse transcriptase polymerase chain reaction (RT-PCR) negative result and a positive RT-PCR result on follow-up; and evaluate the accuracy of thoracic imaging for screening COVID-19 in asymptomatic individuals. The secondary objective was to assess threshold effects of index test positivity on accuracy. SEARCH METHODS: We searched the COVID-19 Living Evidence Database from the University of Bern, the Cochrane COVID-19 Study Register, The Stephen B. Thacker CDC Library, and repositories of COVID-19 publications through to 17 February 2021. We did not apply any language restrictions. SELECTION CRITERIA: We included diagnostic accuracy studies of all designs, except for case-control, that recruited participants of any age group suspected to have COVID-19. Studies had to assess chest CT, chest X-ray, or ultrasound of the lungs for the diagnosis of COVID-19, use a reference standard that included RT-PCR, and report estimates of test accuracy or provide data from which we could compute estimates. We excluded studies that used imaging as part of the reference standard and studies that excluded participants with normal index test results. DATA COLLECTION AND ANALYSIS: The review authors independently and in duplicate screened articles, extracted data and assessed risk of bias and applicability concerns using QUADAS-2. We presented sensitivity and specificity per study on paired forest plots, and summarized pooled estimates in tables. We used a bivariate meta-analysis model where appropriate. MAIN RESULTS: We included 98 studies in this review. Of these, 94 were included for evaluating the diagnostic accuracy of thoracic imaging in the evaluation of people with suspected COVID-19. Eight studies were included for assessing the rate of positive imaging in individuals with initial RT-PCR negative results and positive RT-PCR results on follow-up, and 10 studies were included for evaluating the accuracy of thoracic imaging for imagining asymptomatic individuals. For all 98 included studies, risk of bias was high or unclear in 52 (53%) studies with respect to participant selection, in 64 (65%) studies with respect to reference standard, in 46 (47%) studies with respect to index test, and in 48 (49%) studies with respect to flow and timing. Concerns about the applicability of the evidence to: participants were high or unclear in eight (8%) studies; index test were high or unclear in seven (7%) studies; and reference standard were high or unclear in seven (7%) studies. Imaging in people with suspected COVID-19 We included 94 studies. Eighty-seven studies evaluated one imaging modality, and seven studies evaluated two imaging modalities. All studies used RT-PCR alone or in combination with other criteria (for example, clinical signs and symptoms, positive contacts) as the reference standard for the diagnosis of COVID-19. For chest CT (69 studies, 28285 participants, 14,342 (51%) cases), sensitivities ranged from 45% to 100%, and specificities from 10% to 99%. The pooled sensitivity of chest CT was 86.9% (95% confidence interval (CI) 83.6 to 89.6), and pooled specificity was 78.3% (95% CI 73.7 to 82.3). Definition for index test positivity was a source of heterogeneity for sensitivity, but not specificity. Reference standard was not a source of heterogeneity. For chest X-ray (17 studies, 8529 participants, 5303 (62%) cases), the sensitivity ranged from 44% to 94% and specificity from 24 to 93%. The pooled sensitivity of chest X-ray was 73.1% (95% CI 64. to -80.5), and pooled specificity was 73.3% (95% CI 61.9 to 82.2). Definition for index test positivity was not found to be a source of heterogeneity. Definition for index test positivity and reference standard were not found to be sources of heterogeneity. For ultrasound of the lungs (15 studies, 2410 participants, 1158 (48%) cases), the sensitivity ranged from 73% to 94% and the specificity ranged from 21% to 98%. The pooled sensitivity of ultrasound was 88.9% (95% CI 84.9 to 92.0), and the pooled specificity was 72.2% (95% CI 58.8 to 82.5). Definition for index test positivity and reference standard were not found to be sources of heterogeneity. Indirect comparisons of modalities evaluated across all 94 studies indicated that chest CT and ultrasound gave higher sensitivity estimates than X-ray (P = 0.0003 and P = 0.001, respectively). Chest CT and ultrasound gave similar sensitivities (P=0.42). All modalities had similar specificities (CT versus X-ray P = 0.36; CT versus ultrasound P = 0.32; X-ray versus ultrasound P = 0.89). Imaging in PCR-negative people who subsequently became positive For rate of positive imaging in individuals with initial RT-PCR negative results, we included 8 studies (7 CT, 1 ultrasound) with a total of 198 participants suspected of having COVID-19, all of whom had a final diagnosis of COVID-19. Most studies (7/8) evaluated CT. Of 177 participants with initially negative RT-PCR who had positive RT-PCR results on follow-up testing, 75.8% (95% CI 45.3 to 92.2) had positive CT findings. Imaging in asymptomatic PCR-positive people For imaging asymptomatic individuals, we included 10 studies (7 CT, 1 X-ray, 2 ultrasound) with a total of 3548 asymptomatic participants, of whom 364 (10%) had a final diagnosis of COVID-19. For chest CT (7 studies, 3134 participants, 315 (10%) cases), the pooled sensitivity was 55.7% (95% CI 35.4 to 74.3) and the pooled specificity was 91.1% (95% CI 82.6 to 95.7). AUTHORS' CONCLUSIONS: Chest CT and ultrasound of the lungs are sensitive and moderately specific in diagnosing COVID-19. Chest X-ray is moderately sensitive and moderately specific in diagnosing COVID-19. Thus, chest CT and ultrasound may have more utility for ruling out COVID-19 than for differentiating SARS-CoV-2 infection from other causes of respiratory illness. The uncertainty resulting from high or unclear risk of bias and the heterogeneity of included studies limit our ability to confidently draw conclusions based on our results.

Impact of Reference Standard on CT, MRI, and Contrast-enhanced US LI-RADS Diagnosis of Hepatocellular Carcinoma: A Meta-Analysis.

See also the editorial by Ronot in this issue. Online supplemental material is available for this article.

Evaluating the Impact of Peer Review on the Completeness of Reporting in Imaging Diagnostic Test Accuracy Research.

BACKGROUND: Despite the nearly ubiquitous reported use of peer review among reputable medical journals, there is limited evidence to support the use of peer review to improve the quality of biomedical research and in particular, imaging diagnostic test accuracy (DTA) research. PURPOSE: To evaluate whether peer review of DTA studies published by imaging journals is associated with changes in completeness of reporting, transparency for risk of bias assessment, and spin. STUDY TYPE: Retrospective cross-sectional study. STUDY SAMPLE: Cross-sectional study of articles published in Journal of Magnetic Resonance Imaging (JMRI), Canadian Association of Radiologists Journal (CARJ), and European Radiology (EuRad) before March 31, 2020. ASSESSMENT: Initial submitted and final versions of manuscripts were evaluated for completeness of reporting using the Standards for Reporting Diagnostic Accuracy Studies (STARD) 2015 and STARD for Abstracts guidelines, transparency of reporting for risk of bias assessment based on Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2), and actual and potential spin using modified published criteria. STATISTICAL TESTS: Two-tailed paired t-tests and paired Wilcoxon signed-rank tests were used for comparisons. A P value <0.05 was considered to be statistically significant. RESULTS: We included 84 diagnostic accuracy studies accepted by three journals between 2014 and 2020 (JMRI = 30, CARJ = 23, and EuRad = 31) of the 692 which were screened. Completeness of reporting according to STARD 2015 increased significantly between initial submissions and final accepted versions (average reported items: 16.67 vs. 17.47, change of 0.80 [95% confidence interval 0.25-1.17]). No significant difference was found for the reporting of STARD for Abstracts (5.28 vs. 5.25, change of -0.03 [-0.15 to 0.11], P = 0.74), QUADAS-2 (6.08 vs. 6.11, change of 0.03 [-1.00 to 0.50], P = 0.92), actual "spin" (2.36 vs. 2.40, change of 0.04 [0.00 to 1.00], P = 0.39) or potential "spin" (2.93 vs. 2.81, change of -0.12 [-1.00 to 0.00], P = 0.23) practices. CONCLUSION: Peer review is associated with a marginal improvement in completeness of reporting in published imaging DTA studies, but not with improvement in transparency for risk of bias assessment or reduction in spin. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 1.

Association of Accuracy, Conclusions, and Reporting Completeness With Acceptance by Radiology Conferences and Journals.

BACKGROUND: Preferential publication of studies with positive findings can lead to overestimation of diagnostic test accuracy (i.e. publication bias). Understanding the contribution of the editorial process to publication bias could inform interventions to optimize the evidence guiding clinical decisions. PURPOSE/HYPOTHESIS: To evaluate whether accuracy estimates, abstract conclusion positivity, and completeness of abstract reporting are associated with acceptance to radiology conferences and journals. STUDY TYPE: Meta-research. POPULATION: Abstracts submitted to radiology conferences (European Society of Gastrointestinal and Abdominal Radiology (ESGAR) and International Society for Magnetic Resonance in Medicine (ISMRM)) from 2008 to 2018 and manuscripts submitted to radiology journals (Radiology, Journal of Magnetic Resonance Imaging [JMRI]) from 2017 to 2018. Primary clinical studies evaluating sensitivity and specificity of a diagnostic imaging test in humans with available editorial decisions were included. ASSESSMENT: Primary variables (Youden's index [YI > 0.8 vs. <0.8], abstract conclusion positivity [positive vs. neutral/negative], number of reported items on the Standards for Reporting of Diagnostic Accuracy Studies [STARD] for Abstract guideline) and confounding variables (prospective vs. retrospective/unreported, sample size, study duration, interobserver agreement assessment, subspecialty, modality) were extracted. STATISTICAL TESTS: Multivariable logistic regression to obtain adjusted odds ratio (OR) as a measure of the association between the primary variables and acceptance by radiology conferences and journals; 95% confidence intervals (CIs) and P-values were obtained; the threshold for statistical significance was P < 0.05. RESULTS: A total of 1000 conference abstracts (500 ESGAR and 500 ISMRM) and 1000 journal manuscripts (505 Radiology and 495 JMRI) were included. Conference abstract acceptance was not significantly associated with YI (adjusted OR = 0.97 for YI > 0.8; CI = 0.70-1.35), conclusion positivity (OR = 1.21 for positive conclusions; CI = 0.75-1.90) or STARD for Abstracts adherence (OR = 0.96 per unit increase in reported items; CI = 0.82-1.18). Manuscripts with positive abstract conclusions were less likely to be accepted by radiology journals (OR = 0.45; CI = 0.24-0.86), while YI (OR = 0.85; CI = 0.56-1.29) and STARD for Abstracts adherence (OR = 1.06; CI = 0.87-1.30) showed no significant association. Positive conclusions were present in 86.7% of submitted conference abstracts and 90.2% of journal manuscripts. DATA CONCLUSION: Diagnostic test accuracy studies with positive findings were not preferentially accepted by the evaluated radiology conferences or journals. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Tweeting Bias in Diagnostic Test Accuracy Research: Does Title or Conclusion Positivity Influence Dissemination?

PURPOSE: To examine if tweeting bias exists within imaging literature by determining if diagnostic test accuracy (DTA) studies with positive titles or conclusions are tweeted more than non-positive studies. METHODS: DTA studies published between October 2011 to April 2016 were included. Positivity of titles and conclusions were assessed independently and in duplicate, with disagreements resolved by consensus. A negative binomial regression analysis controlling for confounding variables was performed to assess the relationship between title or conclusion positivity and tweets an article received in the 100 days post-publication. RESULTS: 354 DTA studies were included. Twenty-four (7%) titles and 300 (85%) conclusions were positive (or positive with qualifier); 1 (0.3%) title and 23 (7%) conclusions were negative; and 329 (93%) titles and 26 (7%) conclusions were neutral. Studies with positive, negative, and neutral titles received a mean of 0.38, 0.00, and 0.45 tweets per study; while those with positive, negative, and neutral conclusions received a mean of 0.44, 0.61, and 0.38 tweets per study. Regression coefficients were -0.05 (SE 0.46) for positive relative to non-positive titles, and -0.09 (SE 0.31) for positive relative to non-positive conclusions. The positivity of the title (P = 0.91) or conclusion (P = 0.76) was not significantly associated with the number of tweets an article received. CONCLUSIONS: The positivity of the title or conclusion for DTA studies does not influence the amount of tweets it receives suggesting that tweet bias is not present among imaging diagnostic accuracy studies. Study protocol available at https://osf.io/hdk2m/.

CT/MRI and CEUS LI-RADS Major Features Association with Hepatocellular Carcinoma: Individual Patient Data Meta-Analysis.

Background The Liver Imaging Reporting and Data System (LI-RADS) assigns a risk category for hepatocellular carcinoma (HCC) to imaging observations. Establishing the contributions of major features can inform the diagnostic algorithm. Purpose To perform a systematic review and individual patient data meta-analysis to establish the probability of HCC for each LI-RADS major feature using CT/MRI and contrast-enhanced US (CEUS) LI-RADS in patients at high risk for HCC. Materials and Methods Multiple databases (MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Scopus) were searched for studies from January 2014 to September 2019 that evaluated the accuracy of CT, MRI, and CEUS for HCC detection using LI-RADS (CT/MRI LI-RADS, versions 2014, 2017, and 2018; CEUS LI-RADS, versions 2016 and 2017). Data were centralized. Clustering was addressed at the study and patient levels using mixed models. Adjusted odds ratios (ORs) with 95% CIs were determined for each major feature using multivariable stepwise logistic regression. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) (PROSPERO protocol: CRD42020164486). Results A total of 32 studies were included, with 1170 CT observations, 3341 MRI observations, and 853 CEUS observations. At multivariable analysis of CT/MRI LI-RADS, all major features were associated with HCC, except threshold growth (OR, 1.6; 95% CI: 0.7, 3.6; P = .07). Nonperipheral washout (OR, 13.2; 95% CI: 9.0, 19.2; P = .01) and nonrim arterial phase hyperenhancement (APHE) (OR, 10.3; 95% CI: 6.7, 15.6; P = .01) had stronger associations with HCC than enhancing capsule (OR, 2.4; 95% CI: 1.7, 3.5; P = .03). On CEUS images, APHE (OR, 7.3; 95% CI: 4.6, 11.5; P = .01), late and mild washout (OR, 4.1; 95% CI: 2.6, 6.6; P = .01), and size of at least 20 mm (OR, 1.6; 95% CI: 1.04, 2.5; P = .04) were associated with HCC. Twenty-five studies (78%) had high risk of bias due to reporting ambiguity or study design flaws. Conclusion Most Liver Imaging Reporting and Data System major features had different independent associations with hepatocellular carcinoma; for CT/MRI, arterial phase hyperenhancement and washout had the strongest associations, whereas threshold growth had no association. © RSNA, 2021 Online supplemental material is available for this article.