ACR Appropriateness Criteria® Acute Pelvic Pain in the Reproductive Age Group: 2023 Update.

This review focuses on the initial imaging in the reproductive age adult population with acute pelvic pain, including patients with positive and negative beta-human chorionic gonadotropin (ß-hCG) levels with suspected gynecological and nongynecological etiology. For all patients, a combination of transabdominal and transvaginal pelvic ultrasound with Doppler is usually appropriate as an initial imaging study. If nongynecological etiology in patients with negative ß-hCG is suspected, then CT of the abdomen and pelvis with or without contrast is also usually appropriate. In patients with positive ß-hCG and suspected nongynecological etiology, CT of the abdomen and pelvis with contrast and MRI of the abdomen and pelvis without contrast may be appropriate. In patients with negative ß-hCG and suspected gynecological etiology, CT of the abdomen and pelvis with contrast, MRI of pelvis without contrast, or MRI of pelvis with and without contrast may be appropriate. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

ACR Appropriateness Criteria® Clinically Suspected Adnexal Mass, No Acute Symptoms: 2023 Update.

Asymptomatic adnexal masses are commonly encountered in daily radiology practice. Although the vast majority of these masses are benign, a small subset have a risk of malignancy, which require gynecologic oncology referral for best treatment outcomes. Ultrasound, using a combination of both transabdominal, transvaginal, and duplex Doppler technique can accurately characterize the majority of these lesions. MRI with and without contrast is a useful complementary modality that can help characterize indeterminate lesions and assess the risk of malignancy is those that are suspicious. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

ACR Appropriateness Criteria® Pretreatment Evaluation and Follow-Up of Invasive Cancer of the Cervix: 2023 Update.

Cervical cancer is a common gynecological malignancy worldwide. Cervical cancer is staged based on the International Federation of Gynecology and Obstetrics (FIGO) classification system, which was revised in 2018 to incorporate radiologic and pathologic data. Imaging plays an important role in pretreatment assessment including initial staging and treatment response assessment of cervical cancer. Accurate determination of tumor size, local extension, and nodal and distant metastases is important for treatment selection and for prognostication. Although local recurrence can be diagnosed by physical examination, imaging plays a critical role in detection and follow-up of local and distant recurrence and subsequent treatment selection. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Utility of ADC Values for Differentiating Uterine Sarcomas From Leiomyomas: Systematic Review and Meta-Analysis.

Background: Uterine sarcomas are rare; however, they display imaging features that overlap those of leiomyomas. The potential for undetected uterine sarcomas is clinically relevant because minimally invasive treatment of leiomyomas may lead to cancer dissemination. ADC values have shown potential for differentiating benign and malignant uterine masses. Objective: The purpose of this study was to perform a systematic review of the diagnostic performance of ADC values in differentiating uterine sarcomas from leiomyomas. Evidence acquisition: We searched three electronic databases (MEDLINE, EMBASE, and Cochrane databases) for studies distinguishing uterine sarcomas from leiomyomas using MRI, including ADC, with pathologic tissue confirmation or imaging follow-up as the reference standard. Data extraction and QUADAS-2 quality assessment were performed. Sensitivity and specificity were pooled using hierarchic models, including bivariate and hierarchic summary ROC models. Metaregression was used to assess the impact of various factors on heterogeneity. Evidence synthesis: Twenty-one studies met study inclusion criteria. Pooled sensitivity and specificity were 89% (95% CI, 82-94%) and 86% (95% CI, 78-92%), respectively. Area under the summary ROC curve was 94% (95% CI, 92-96%). Context of ADC interpretation (i.e., standalone vs part of multiparametric MRI [mpMRI]) was the only factor found to account significantly for heterogeneity (p = .01). Higher specificity (95% [95% CI, 92-99%] vs 82% [95% CI, 75-89%]) and similar sensitivity (94% [95% CI, 89-99%] vs 88% [95% CI, 82-93%]) were observed when ADC was evaluated among mpMRI features as compared with standalone ADC assessment. ADC cutoff values ranged (0.87-1.29 × 10-3 mm2/s) but were not associated with statistically different performance (p = .37). Pooled mean ADC values in sarcomas and leiomyomas were 0.904 × 10-3 mm2/s and 1.287 × 10-3 mm2/s, respectively. Conclusion: As part of mpMRI evaluation of uterine masses, mass ADC value less than 0.904 × 10-3 mm2/s may be a useful test-positive threshold for uterine sarcoma, consistent with a prior expert consensus statement. Institutional protocols may influence locally selected ADC values. Clinical Impact: Using ADC as part of mpMRI assessment improves detection of uterine sarcoma, which could influence candidate selection for minimally invasive treatments.

Evaluation of GPT-4 ability to identify and generate patient instructions for actionable incidental radiology findings.

OBJECTIVES: To evaluate the proficiency of a HIPAA-compliant version of GPT-4 in identifying actionable, incidental findings from unstructured radiology reports of Emergency Department patients. To assess appropriateness of artificial intelligence (AI)-generated, patient-facing summaries of these findings. MATERIALS AND METHODS: Radiology reports extracted from the electronic health record of a large academic medical center were manually reviewed to identify non-emergent, incidental findings with high likelihood of requiring follow-up, further sub-stratified as "definitely actionable" (DA) or "possibly actionable-clinical correlation" (PA-CC). Instruction prompts to GPT-4 were developed and iteratively optimized using a validation set of 50 reports. The optimized prompt was then applied to a test set of 430 unseen reports. GPT-4 performance was primarily graded on accuracy identifying either DA or PA-CC findings, then secondarily for DA findings alone. Outputs were reviewed for hallucinations. AI-generated patient-facing summaries were assessed for appropriateness via Likert scale. RESULTS: For the primary outcome (DA or PA-CC), GPT-4 achieved 99.3% recall, 73.6% precision, and 84.5% F-1. For the secondary outcome (DA only), GPT-4 demonstrated 95.2% recall, 77.3% precision, and 85.3% F-1. No findings were "hallucinated" outright. However, 2.8% of cases included generated text about recommendations that were inferred without specific reference. The majority of True Positive AI-generated summaries required no or minor revision. CONCLUSION: GPT-4 demonstrates proficiency in detecting actionable, incidental findings after refined instruction prompting. AI-generated patient instructions were most often appropriate, but rarely included inferred recommendations. While this technology shows promise to augment diagnostics, active clinician oversight via "human-in-the-loop" workflows remains critical for clinical implementation.

A cytomics-on-a-chip platform and diagnostic model stratifies risk for oral lichenoid conditions.

OBJECTIVE: A small fraction of oral lichenoid conditions (OLC) have potential for malignant transformation. Distinguishing OLCs from other oral potentially malignant disorders (OPMDs) can help prevent unnecessary concern or testing, but accurate identification by nonexpert clinicians is challenging due to overlapping clinical features. In this study, the authors developed a 'cytomics-on-a-chip' tool and integrated predictive model for aiding the identification of OLCs. STUDY DESIGN: All study subjects underwent both scalpel biopsy for histopathology and brush cytology. A predictive model and OLC Index comprising clinical, demographic, and cytologic features was generated to discriminate between subjects with lichenoid (OLC+) (N = 94) and nonlichenoid (OLC-) (N = 237) histologic features in a population with OPMDs. RESULTS: The OLC Index discriminated OLC+ and OLC- subjects with area under the curve (AUC) of 0.76. Diagnostic accuracy of the OLC Index was not significantly different from expert clinician impressions, with AUC of 0.81 (P = .0704). Percent agreement was comparable across all raters, with 83.4% between expert clinicians and histopathology, 78.3% between OLC Index and expert clinician, and 77.3% between OLC Index and histopathology. CONCLUSIONS: The cytomics-on-a-chip tool and integrated diagnostic model have the potential to facilitate both the triage and diagnosis of patients presenting with OPMDs and OLCs.

Functional Connectivity Changes on Resting-State fMRI after Mild Traumatic Brain Injury: A Systematic Review.

BACKGROUND: Mild traumatic brain injury is theorized to cause widespread functional changes to the brain. Resting-state fMRI may be able to measure functional connectivity changes after traumatic brain injury, but resting-state fMRI studies are heterogeneous, using numerous techniques to study ROIs across various resting-state networks. PURPOSE: We systematically reviewed the literature to ascertain whether adult patients who have experienced mild traumatic brain injury show consistent functional connectivity changes on resting-state -fMRI, compared with healthy patients. DATA SOURCES: We used 5 databases (PubMed, EMBASE, Cochrane Central, Scopus, Web of Science). STUDY SELECTION: Five databases (PubMed, EMBASE, Cochrane Central, Scopus, and Web of Science) were searched for research published since 2010. Search strategies used keywords of "functional MR imaging" and "mild traumatic brain injury" as well as related terms. All results were screened at the abstract and title levels by 4 reviewers according to predefined inclusion and exclusion criteria. For full-text inclusion, each study was evaluated independently by 2 reviewers, with discordant screening settled by consensus. DATA ANALYSIS: Data regarding article characteristics, cohort demographics, fMRI scan parameters, data analysis processing software, atlas used, data characteristics, and statistical analysis information were extracted. DATA SYNTHESIS: Across 66 studies, 80 areas were analyzed 239 times for at least 1 time point, most commonly using independent component analysis. The most analyzed areas and networks were the whole brain, the default mode network, and the salience network. Reported functional connectivity changes varied, though there may be a slight trend toward decreased whole-brain functional connectivity within 1 month of traumatic brain injury and there may be differences based on the time since injury. LIMITATIONS: Studies of military, sports-related traumatic brain injury, and pediatric patients were excluded. Due to the high number of relevant studies and data heterogeneity, we could not be as granular in the analysis as we would have liked. CONCLUSIONS: Reported functional connectivity changes varied, even within the same region and network, at least partially reflecting differences in technical parameters, preprocessing software, and analysis methods as well as probable differences in individual injury. There is a need for novel rs-fMRI techniques that better capture subject-specific functional connectivity changes.

Chronic kidney disease and risk of kidney or urothelial malignancy: systematic review and meta-analysis.

BACKGROUND: Chronic kidney disease (CKD) is highly prevalent, affecting approximately 11% of U.S. adults. Multiple studies have evaluated a potential association between CKD and urinary tract malignancies. Summary estimates of urinary tract malignancy risk in CKD patients with and without common co-existing conditions may guide clinical practice recommendations. METHODS: Four electronic databases were searched for original cohort studies evaluating the association between CKD and urinary tract cancers (kidney cancer and urothelial carcinoma) through May 25, 2023, in persons with at least moderate CKD and no dialysis or kidney transplantation. Quality assessment was performed for studies meeting inclusion criteria using the Newcastle-Ottawa Scale. Meta-analysis with a random-effects model was performed for unadjusted incidence rate ratios (IRR) as well as adjusted hazard ratios (aHR) for confounding conditions (diabetes, hypertension, and/or tobacco use), shown to have association with kidney cancer and urothelial carcinoma. Sub-analysis was conducted for estimates associated with CKD stages separately. RESULTS: Six cohort studies with 8 617 563 persons were included. Overall, methodological quality of the studies was good. CKD was associated with both higher unadjusted incidence and adjusted hazard of kidney cancer (IRR, 3.36; 95% confidence interval [CI], 2.32-4.88; aHR, 2.04; 95% CI, 1.77-2.36) and urothelial cancer (IRR, 3.96; 95% CI, 2.44-6.40; aHR, 1.40; 95% CI, 1.22-1.68) compared with persons without CKD. Examining incident urinary tract cancers by CKD severity, risks were elevated in stage 3 CKD (kidney aHR, 1.89; 95% CI, 1.56-2.30; urothelial carcinoma aHR, 1.40; 95% CI, 1.18-1.65) as well as in stages 4/5 CKD (kidney cancer aHR, 2.30; 95% CI, 2.00-2.66, UC aHR, 1.24; 95% CI, 1.04-1.49). CONCLUSIONS: Even moderate CKD is associated with elevated risk of kidney cancer and UC. Providers should consider these elevated risks when managing individuals with CKD, particularly when considering evaluation for the presence and etiology of hematuria.

Evaluation of Socioeconomic Disparities in Follow-Up Completion for Incidental Pulmonary Nodules.

PURPOSE: The aim of this study was to evaluate the association between census tract-level measures of social vulnerability and residential segregation and incidental pulmonary nodule (IPN) follow-up. METHODS: This retrospective cohort study included patients with IPNs ≥6 mm in size or multiple subsolid or ground-glass IPNs <6 mm (with nonoptional follow-up recommendations) diagnosed between January 1, 2018, and December 30, 2019, at a large urban tertiary center and followed for ≥2 years. Geographic sociodemographic context was characterized by the 2018 Centers for Disease Control and Prevention Social Vulnerability Index (SVI) and the index of concentration at the extremes (ICE), categorized in quartiles. Multivariable binomial regression models were used, with a primary outcome of inappropriate IPN follow-up (late or no follow-up). Models were also stratified by nodule risk. RESULTS: The study consisted of 2,492 patients (mean age, 65.6 ± 12.6 years; 1,361 women). Top-quartile SVI patients were more likely to have inappropriate follow-up (risk ratio [RR], 1.24; 95% confidence interval [CI], 1.12-1.36) compared with the bottom quartile; risk was also elevated in top-quartile SVI subcategories of socioeconomic status (RR, 1.23; 95% CI, 1.13-1.34), Minority status and language (RR, 1.24; 95% CI, 1.03-1.48), housing and transportation (RR, 1.13; 95% CI, 1.02-1.26), and ICE (RR, 1.20; 95% CI, 1.11-1.30). Furthermore, top-quartile ICE was associated with greater risk for inappropriate follow-up among high-risk versus lower risk IPNs (RR, 1.33 [95% CI, 1.18-1.50] versus 1.13 [95% CI, 1.02-1.25]), respectively; P for interaction = .017). CONCLUSIONS: Local social vulnerability and residential segregation are associated with inappropriate IPN follow-up and may inform policy or interventions tailored for neighborhoods.

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.

How to Perform Economic Evaluation in Implementation Studies: Imaging-Specific Considerations and Comparison of Financial Models.

Economic evaluation for implementation science merits unique considerations for a local context, including the main audience of local decision makers. This local context is in contrast with traditional methods for developing coverage policy for medical tests and interventions, which typically emphasize benefits and costs more broadly, for society. Regardless of the strength of evidence backing the efficacy or effectiveness of a clinical intervention, local context is paramount when implementing evidence-based practices. Understanding the costs throughout the processes of implementing a program will inform the decision of whether to plan for and adopt the program, how to sustain the program, and whether to scale up widely. To guide economic evaluation for implementation of evidence-based imaging practices, we describe approaches that consider local stakeholders' needs and connect these with outcomes of cost and clinical utility. Illustrative examples of implementation strategies and economic evaluation are explored in areas of cancer screening and care delivery.

White Paper: Best Practices in the Communication and Management of Actionable Incidental Findings in Emergency Department Imaging.

PURPOSE: Actionable incidental findings (AIFs) are common in radiologic imaging. Imaging is commonly performed in emergency department (ED) visits, and AIFs are frequently encountered, but the ED presents unique challenges for communication and follow-up of these findings. The authors formed a multidisciplinary panel to seek consensus regarding best practices in the reporting, communication, and follow-up of AIFs on ED imaging tests. METHODS: A 15-member panel was formed, nominated by the ACR and American College of Emergency Physicians, to represent radiologists, emergency physicians, patients, and those involved in health care systems and quality. A modified Delphi process was used to identify areas of best practice and seek consensus. The panel identified four areas: (1) report elements and structure, (2) communication of findings with patients, (3) communication of findings with clinicians, and (4) follow-up and tracking systems. A survey was constructed to seek consensus and was anonymously administered in two rounds, with a priori agreement requiring at least 80% consensus. Discussion occurred after the first round, with readministration of questions where consensus was not initially achieved. RESULTS: Consensus was reached in the four areas identified. There was particularly strong consensus that AIFs represent a system-level issue, with need for approaches that do not depend on individual clinicians or patients to ensure communication and completion of recommended follow-up. CONCLUSIONS: This multidisciplinary collaboration represents consensus results on best practices regarding the reporting and communication of AIFs in the ED setting.

Improving breast cancer diagnostics with deep learning for MRI.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has a high sensitivity in detecting breast cancer but often leads to unnecessary biopsies and patient workup. We used a deep learning (DL) system to improve the overall accuracy of breast cancer diagnosis and personalize management of patients undergoing DCE-MRI. On the internal test set (n = 3936 exams), our system achieved an area under the receiver operating characteristic curve (AUROC) of 0.92 (95% CI: 0.92 to 0.93). In a retrospective reader study, there was no statistically significant difference (P = 0.19) between five board-certified breast radiologists and the DL system (mean ΔAUROC, +0.04 in favor of the DL system). Radiologists' performance improved when their predictions were averaged with DL's predictions [mean ΔAUPRC (area under the precision-recall curve), +0.07]. We demonstrated the generalizability of the DL system using multiple datasets from Poland and the United States. An additional reader study on a Polish dataset showed that the DL system was as robust to distribution shift as radiologists. In subgroup analysis, we observed consistent results across different cancer subtypes and patient demographics. Using decision curve analysis, we showed that the DL system can reduce unnecessary biopsies in the range of clinically relevant risk thresholds. This would lead to avoiding biopsies yielding benign results in up to 20% of all patients with BI-RADS category 4 lesions. Last, we performed an error analysis, investigating situations where DL predictions were mostly incorrect. This exploratory work creates a foundation for deployment and prospective analysis of DL-based models for breast MRI.

Development and Pilot Evaluation of a Decision Aid for Small Kidney Masses.

OBJECTIVE: To develop and pilot test a patient decision aid (DA) describing small kidney masses and risks and benefits of treatment for the masses. METHODS: An expert committee iteratively designed a small kidney mass DA, incorporating evidence-based risk communication and informational needs for treatment options and shared decision-making. After literature review and drafting content with the feedback of urologists, radiologists, and an internist, a rapid qualitative assessment was conducted using two patient focus groups to inform user-centered design. In a pilot study, 30 patients were randomized at the initial urologic consultation to receive the DA or existing institutional patient educational material (PEM). Preconsultation questionnaires captured patient knowledge and shared decision-making preferences. After review of the DA and subsequent clinician consultation, patients completed questionnaires on discussion content and satisfaction. Proportions between arms were compared using Fisher exact tests, and decision measures were compared using Mann-Whitney tests. RESULTS: Patient informational needs included risk of tumor growth during active surveillance and ablation, significance of comorbidities, and posttreatment recovery. For the DA, 84% of patients viewed all content, and mean viewing time was 20 min. Significant improvements in knowledge about small mass risks and treatments were observed (mean total scores: 52.6% DA versus 22.3% PEM, P < .001). DA use also increased the proportion of patients discussing ablation (66.7% DA versus 18.2% PEM, P = .02). Decision satisfaction measures were similar in both arms. DISCUSSION: Patients receiving a small kidney mass DA are likely to gain knowledge and preparedness to discuss all treatment options over standard educational materials.

Does histologic subtype impact overall survival in observed T1a kidney cancers compared with competing risks? Implications for biopsy as a risk stratification tool.

OBJECTIVES: We sought to assess if adding a biopsy proven histologic subtype to a model that predicts overall survival that includes variables representing competing risks in observed, biopsy proven, T1a renal cell carcinomas, enhances the model's performance. METHODS: The National Cancer Database was assessed (years 2004-2015) for patients with observed T1a renal cell carcinoma who had undergone renal mass biopsy. Kaplan-Meier curves were utilized to estimate overall survival stratified by histologic subtype. We utilized C-index from a Cox proportional hazards model to evaluate the impact of adding histologic subtypes to a model to predict overall survival for each stage. RESULTS: Of 132 958 T1a renal masses identified, 1614 had biopsy proven histology and were managed non-operatively. Of those, 61% were clear cell, 33% papillary, and 6% chromophobe. Adjusted Kaplan-Meier curves demonstrated a difference in overall survival between histologic subtypes (P = 0.010) with greater median overall survival for patients with chromophobe (85.1 months, hazard rate 0.45, P = 0.005) compared to clear cell (64.8 months, reference group). Adding histology to a model with competing risks alone did not substantially improve model performance (C-index 0.65 vs 0.64 respectively). CONCLUSIONS: Incorporation of histologic subtype into a risk stratification model to determine prognostic overall survival did not improve modeling of overall survival compared with variables representing competing risks in patients with T1a renal cell carcinoma managed with observation. These results suggest that performing renal mass biopsy in order to obtain tumor histology may have limited utility. Future studies should further investigate the overall utility of renal mass biopsy for observed T1a kidney cancers.

18F-Fluciclovine versus PSMA PET Imaging in Primary Tumor Detection during Initial Staging of High-Risk Prostate Cancer: A Systematic Review and Meta-Analysis.

Purpose Fluorine 18 (18F)-fluciclovine and prostate-specific membrane antigen (PSMA) tracers are commonly used for localizing biochemical recurrence of prostate cancer, but their accuracy in primary tumor detection in the initial staging of high-risk prostate cancer has not been established. Materials and Methods A systematic review was performed of the electronic databases for original studies published between 2012 and 2020. Included studies were those in which 18F-fluciclovine or PSMA PET was used for initial staging of patients with high-risk prostate cancer. The diagnostic performance data were collected for primary tumor with histopathologic results as reference standard. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was used for quality appraisal. A random-effects model was used to summarize the effect sizes and to evaluate the difference between two groups. Results Overall, 28 studies met the eligibility criteria, and 17 were included in the meta-analysis (18F-fluciclovine = 4, PSMA = 13). Of these 17 studies, 12 (70%) were judged to have high risk of bias in one of the evaluated domains, and nine studies were deemed to have applicability concerns. The pooled sensitivity, specificity, and diagnostic odds ratio for 18F-fluciclovine versus PSMA were 85% (95% CI: 73%, 92%) versus 84% (95% CI: 77%, 89%) (P = .78), 77% (95% CI: 60%, 88%) versus 83% (95% CI: 76%, 89%) (P = .40), and 18.88 (95% CI: 5.01, 71.20) versus 29.37 (95% CI: 13.35, 64.60) (P = .57), respectively, with no significant difference in diagnostic test accuracy. Conclusion 18F-fluciclovine and PSMA PET demonstrated no statistically significant difference in diagnostic accuracy in primary tumor detection during initial staging of high-risk prostate cancer. Keywords: PET, Prostate, Molecular Imaging-Cancer, Staging Supplemental material is available for this article. © RSNA, 2022.

Outcomes of Incidental Lung Nodules With Structured Recommendations and Electronic Tracking.

OBJECTIVE: To evaluate the impact of structured recommendations on follow-up completion for incidental lung nodules (ILNs). METHODS: Patients with ILNs before and after implementation of structured Fleischner recommendations and electronic tracking were sampled randomly. The cohorts were compared for imaging follow-up. Multivariable logistic regression was used to assess appropriate follow-up and loss to follow-up, with independent variables including use of structured recommendations or tracking, age, sex, race, ethnicity, setting of the index test (inpatient, outpatient, emergency department), smoking history, and nodule features. RESULTS: In all, 1,301 patients met final inclusion criteria, including 255 patients before and 1,046 patients after structured recommendations or tracking. Baseline differences were found in the pre- and postintervention groups, with smaller ILNs and younger age after implementing structured recommendations. Comparing pre- versus postintervention outcomes, 40.0% (100 of 250) versus 29.5% (309 of 1,046) of patients had no follow-up despite Fleischner indications for imaging (P = .002), and among the remaining patients, 56.6% (82 of 145) versus 75.0% (553 of 737) followed up on time (P < .001). Delayed follow-up was more frequent before intervention. Differences postintervention were mostly accounted for by nodules ≤8 mm in the outpatient setting (P < .001). In multivariable analysis, younger age, White race, outpatient setting, and larger nodule size showed significant association with appropriate follow-up completion (P < .015), but structured recommendations did not. Similar results applied for loss to follow-up. DISCUSSION: Consistent use of structured reporting is likely key to mitigate selection bias when benchmarking rates of appropriate follow-up of ILN. Emergency department patients and inpatients are at high risk of missed or delayed follow-up despite structured recommendations.

ACR Appropriateness Criteria® Staging and Follow-up of Primary Vaginal Cancer.

Primary vaginal cancer is rare, comprising 1% to 2% of gynecologic malignancies and 20% of all malignancies involving the vagina. More frequently, the vagina is involved secondarily by direct invasion from malignancies originating in adjacent organs or by metastases from other pelvic or extrapelvic primary malignancies. Data on the use of imaging in vaginal cancer are sparse. Insights are derived from the study of imaging in cervical cancer and have reasonable generalizability to vaginal cancer due to similar tumor biology. Given the trend toward definitive chemoradiation for both cancers in all but early stage lesions, principles of postchemoradiation tumor response evaluation are largely analogous. Accordingly, many of the recommendations outlined here are informed by principles translated from the literature on cervical cancer. For pretreatment assessment of local tumor burden and in the case of recurrent vaginal cancer, MRI is the preferred imaging modality. PET/CT has demonstrated utility for the detection of nodal metastatic and unexpected distant metastatic disease. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.