Recommendations For Additional Imaging Research Articles

Society of Radiologists in Ultrasound Consensus on Routine Pelvic US for Endometriosis.

Endometriosis is a prevalent and potentially debilitating condition that mostly affects individuals of reproductive age, and often has a substantial diagnostic delay. US is usually the first-line imaging modality used when patients report chronic pelvic pain or have issues of infertility, both common symptoms of endometriosis. Other than the visualization of an endometrioma, sonologists frequently do not appreciate endometriosis on routine transvaginal US images. Given a substantial body of literature describing techniques to depict endometriosis at US, the Society of Radiologists in Ultrasound convened a multidisciplinary panel of experts to make recommendations aimed at improving the screening process for endometriosis. The panel was composed of experts in the imaging and management of endometriosis, including radiologists, sonographers, gynecologists, reproductive endocrinologists, and minimally invasive gynecologic surgeons. A comprehensive literature review combined with a modified Delphi technique achieved a consensus. This statement defines the targeted screening population, describes techniques for augmenting pelvic US, establishes direct and indirect observations for endometriosis at US, creates an observational grading and reporting system, and makes recommendations for additional imaging and patient management. The panel recommends transvaginal US of the posterior compartment, observation of the relative positioning of the uterus and ovaries, and the uterine sliding sign maneuver to improve the detection of endometriosis. These additional techniques can be performed in 5 minutes or less and could ultimately decrease the delay of an endometriosis diagnosis in at-risk patients.

Editorial Comment: More Guidelines Needed to Address High Variability in Recommendations for Additional Imaging in Head and Neck Examinations.

Editorial Comment: More Guidelines Needed to Address High Variability in Recommendations for Additional Imaging in Head and Neck Examinations.

Recommendations for Additional Imaging on Head and Neck Imaging Examinations: Interradiologist Variation and Associated Factors.

Background: A paucity of relevant guidelines may lead to pronounced variation among radiologists in issuing recommendations for additional imaging (RAI) for head and neck imaging. Objective: To explore associations of RAI for head and neck imaging examinations with examination, patient, and radiologist factors, and to assess the role of individual radiologist-specific behavior in issuing such RAI. Methods: This retrospective study included 39,200 patients (median age, 58 years; 21,855 female, 17,315 male, 30 with missing sex information) who underwent 39,200 head and neck CT or MRI examinations, interpreted by 61 radiologists, from June 1, 2021 through May 31, 2022. A natural language processing (NLP) tool with manual review of NLP results was used to identify RAI in report impressions. Interradiologist variation in RAI rates was assessed. A generalized mixed-effects model was used to assess associations between RAI and examination, patient, and radiologist factors. Results: A total of 2946 (7.5%) reports contained an RAI. Individual radiologist RAI rates ranged from 0.8% to 22.0% (median 7.1%, IQR 5.2%-10.2%), representing 27.5-fold difference between minimum and maximum values and 1.8-fold difference between 25th and 75th percentiles. In multivariable analysis, RAI likelihood was higher for CTA than for CT examinations (OR: 1.32), for examinations that included a trainee in report generation (OR: 1.23), and for patients with self-identified race of Black or African American than of White (OR: 1.25); lower for male than female patients (OR: 0.90); and associated with increasing patient age (OR: 1.09 per decade) and inversely associated with radiologist years since training (OR: 0.90 per 5 years). The model accounted for 10.9% of the likelihood of RAI. Of explainable likelihood of RAI, 25.7% was attributable to examination, patient, and radiologist factors; 74.3% was attributable to radiologist-specific behavior. Conclusion: Interradiologist variation in RAI rates for head and neck imaging was substantial. RAI appeared to be more substantially associated with individual radiologist-specific behavior than with measurable systemic factors. Clinical Impact: Quality improvement initiatives, incorporating best practices for incidental findings management, may help reduce radiologist preference-sensitive decision-making in issuing RAI for head and neck imaging and associated care variation.

Actionability of Recommendations for Additional Imaging in Head and Neck Radiology

PurposeThe aims of this study were to measure the actionability of recommendations for additional imaging (RAIs) in head and neck CT and MRI, for which there is a near complete absence of best practices or guidelines; to identify the most common recommendations; and to assess radiologist factors associated with actionability. MethodsAll head and neck CT and MRI radiology reports across a multi-institution, multipractice health care system from June 1, 2021, to May 31, 2022, were retrospectively reviewed. The actionability of RAIs was scored using a validated taxonomy. The most common RAIs were identified. Actionability association with radiologist factors (gender, years out of training, fellowship training, practice type) and with trainees was measured using a mixed-effects model. ResultsTwo hundred nine radiologists generated 60,543 reports, of which 7.2% (n = 4,382) contained RAIs. Only 3.9% of RAIs (170 of 4,382) were actionable. More than 60% of RAIs were for eight examinations: thyroid ultrasound (14.1%), neck CT (12.6%), brain MRI (6.9%), chest CT (6.5%), neck CT angiography (5.5%), temporal bone CT (5.3%), temporal bone MRI (5.2%), and pituitary MRI (4.6%). Radiologists >23 years out of training (odds ratio, 0.39; 95% confidence interval, 0.15-1.02; P = .05) and community radiologists (odds ratio, 0.53; 95% confidence interval, 0.22-1.31; P = .17) had substantially lower estimated odds of making actionable RAIs than radiologists <7 years out of training and academic radiologists, respectively. ConclusionsThe studied radiologists rarely made actionable RAIs, which makes it difficult to identify and track clinically necessary RAIs to timely performance. Multifaceted quality improvement initiatives including peer comparisons, clinical decision support at the time of reporting, and the development of evidence-based best practices, may help improve tracking and timely performance of clinically necessary RAIs.

Financial Impact of a Radiology Safety Net Program for Resolution of Clinically Necessary Follow-up Imaging Recommendations

ObjectiveHealth care safety net (SN) programs can potentially improve patient safety and decrease risk associated with missed or delayed follow-up care, although they require financial resources. This study aimed to assess whether the revenue generated from completion of clinically necessary recommendations for additional imaging (RAI) made possible by an IT-enabled SN program could fund the required additional labor resources. MethodsClinically necessary RAI generated October 21, 2019, to September 24, 2021, were tracked to resolution as of April 13, 2023. A new radiology SN team worked with existing schedulers and care coordinators, performing chart review and patient and provider outreach to ensure RAI resolution. We applied relevant Current Procedural Terminology, version 4 codes of the completed imaging examinations to estimate total revenue. Coprimary outcomes included revenue generated by total performed examinations and estimated revenue attributed to SN involvement. We used Student’s t test to compare the secondary outcome, RAI time interval, for higher versus lower revenue-generating modalities. ResultsIn all, 24% (3,243) of eligible follow-up recommendations (13,670) required SN involvement. Total estimated revenue generated by performed recommended examinations was $6,116,871, with $980,628 attributed to SN. Net SN-generated revenue per 1.0 full-time equivalent was an estimated $349,768. Greatest proportion of performed examinations were cross-sectional modalities (CT, MRI, PET/CT), which were higher revenue-generating than non-cross-sectional modalities (x-ray, ultrasound, mammography), and had shorter recommendation time frames (153 versus 180 days, P < .001). DiscussionThe revenue generated from completion of RAI facilitated by an IT-enabled quality and safety program supplemented by an SN team can fund the required additional labor resources to improve patient safety. Realizing early revenue may require 5 to 6 months postimplementation.

Development and External Validation of an Artificial Intelligence Model for Identifying Radiology Reports Containing Recommendations for Additional Imaging.

BACKGROUND. Reported rates of recommendations for additional imaging (RAIs) in radiology reports are low. Bidirectional encoder representations from transformers (BERT), a deep learning model pretrained to understand language context and ambiguity, has potential for identifying RAIs and thereby assisting large-scale quality improvement efforts. OBJECTIVE. The purpose of this study was to develop and externally validate an artificial intelligence (AI)-based model for identifying radiology reports containing RAIs. METHODS. This retrospective study was performed at a multisite health center. A total of 6300 radiology reports generated at one site from January 1, 2015, to June 30, 2021, were randomly selected and split by 4:1 ratio to create training (n = 5040) and test (n = 1260) sets. A total of 1260 reports generated at the center's other sites (including academic and community hospitals) from April 1 to April 30, 2022, were randomly selected as an external validation group. Referring practitioners and radiologists of varying sub-specialties manually reviewed report impressions for presence of RAIs. A BERT-based technique for identifying RAIs was developed by use of the training set. Performance of the BERT-based model and a previously developed traditional machine learning (TML) model was assessed in the test set. Finally, performance was assessed in the external validation set. The code for the BERT-based RAI model is publicly available. RESULTS. Among a total of 7419 unique patients (4133 women, 3286 men; mean age, 58.8 years), 10.0% of 7560 reports contained RAI. In the test set, the BERT-based model had 94.4% precision, 98.5% recall, and an F1 score of 96.4%. In the test set, the TML model had 69.0% precision, 65.4% recall, and an F1 score of 67.2%. In the test set, accuracy was greater for the BERT-based than for the TML model (99.2% vs 93.1%, p < .001). In the external validation set, the BERT-based model had 99.2% precision, 91.6% recall, an F1 score of 95.2%, and 99.0% accuracy. CONCLUSION. The BERT-based AI model accurately identified reports with RAIs, outperforming the TML model. High performance in the external validation set suggests the potential for other health systems to adapt the model without requiring institution-specific training. CLINICAL IMPACT. The model could potentially be used for real-time EHR monitoring for RAIs and other improvement initiatives to help ensure timely performance of clinically necessary recommended follow-up.

Editorial Comment: Meet BERT-The Newest Artificial Intelligence-Based Radiologist Extender.

This Editorial Comment discusses the following AJR article: Development and External Validation of an Artificial Intelligence Model for Identifying Radiology Reports Containing Recommendations for Additional Imaging.

Impact of an Automated Closed-Loop Communication and Tracking Tool on the Rate of Recommendations for Additional Imaging in Thoracic Radiology Reports

ObjectiveAssess the effects of feedback reports and implementing a closed-loop communication system on rates of recommendations for additional imaging (RAIs) in thoracic radiology reports. MethodsIn this retrospective, institutional review board–approved study at an academic quaternary care hospital, we analyzed 176,498 thoracic radiology reports during a pre-intervention (baseline) period from April 1, 2018, to November 30, 2018; a feedback report only period from December 1, 2018, to September 30, 2019; and a closed-loop communication system plus feedback report (IT intervention) period from October 1, 2019, to December 31, 2020, promoting explicit documentation of rationale, time frame, and imaging modality for RAI, defined as complete RAI. A previously validated natural language processing tool was used to classify reports with an RAI. Primary outcome of rate of RAI was compared using a control chart. Multivariable logistic regression determined factors associated with likelihood of RAI. We also estimated the completeness of RAI in reports comparing IT intervention to baseline using χ2 statistic. ResultsThe natural language processing tool classified 3.2% (5,682 of 176,498) reports as having an RAI; 3.5% (1,783 of 51,323) during the pre-intervention period, 3.8% (2,147 of 56,722) during the feedback report only period (odds ratio: 1.1, P = .03), and 2.6% (1,752 of 68,453) during the IT intervention period (odds ratio: 0.60, P < .001). In subanalysis, the proportion of incomplete RAI decreased from 84.0% (79 of 94) during the pre-intervention period to 48.5% (47 of 97) during the IT intervention period (P < .001). DiscussionFeedback reports alone increased RAI rates, and an IT intervention promoting documentation of complete RAI in addition to feedback reports led to significant reductions in RAI rate, incomplete RAI, and improved overall completeness of the radiology recommendations.

Development and Assessment of an Information Technology Intervention to Improve the Clarity of Radiologist Follow-up Recommendations

It is challenging to ensure timely performance of radiologist-recommended additional imaging when radiologist recommendation language is incomplete or ambiguous. To evaluate whether voluntary use of an information technology tool with forced structured entry of recommendation attributes was associated with improved completeness of recommendations for additional imaging over time. This cohort study of imaging report data was performed at an academic quaternary care center in Boston, Massachusetts, and included consecutive adults with radiology examinations performed from September 12 to 13, 2019 (taxonomy validation), October 14 to 17, 2019 (before intervention), April 5 to 7, 2021 (1 week after intervention), and April 4 to 7, 2022 (1 year after intervention), with reports containing recommendations for additional imaging. A radiologist scored the 3 groups (preintervention group, 1-week postintervention group, and 1-year postintervention group) of 336 consecutive radiology reports (n = 1008) with recommendations for additional imaging. Final implementation on March 27, 2021, of a voluntary closed-loop communication tool embedded in radiologist clinical workflow that required structured entry of recommendation attributes. The a priori primary outcome was completeness of recommendations for additional imaging, defined in a taxonomy created by a multidisciplinary expert panel. To validate the taxonomy, 2 radiologists independently reviewed and scored language attributes as present or absent in 247 consecutive radiology reports containing recommendations for additional imaging. Agreement was assessed with Cohen κ. Recommendation completeness over time was compared with with 1-sided Fisher exact tests and significance set at P < .05. Radiology-related information for consecutive radiology reports from the 4 time periods was collected from the radiology department data warehouse, which does not include data on patient demographic characteristics or other nonimaging patient medical information. The panel defined 5 recommendation language attributes: complete (contains imaging modality, time frame, and rationale), ambiguous (equivocal, vague language), conditional (qualifying language), multiplicity (multiple options), and alternate (language favoring a different examination to that ordered). Two radiologists had more than 90% agreement (κ > 0.8) for these attributes. Completeness with use of the tool increased more than 3-fold, from 14% (46 of 336) before the intervention to 46% (153 of 336) (P < .001) 1 year after intervention; completeness in the corresponding free-text report language increased from 14% (46 of 336) before the intervention to 25% (85 of 336) (P < .001) 1 year after the intervention. This study suggests that supplementing free-text dictation with voluntary use of a structured entry tool was associated with improved completeness of radiologist recommendations for additional imaging as assessed by an internally validated taxonomy. Future research is needed to assess the association with timely performance of clinically necessary recommendations and diagnostic errors. The taxonomy can be used to evaluate and build interventions to modify radiologist reporting behaviors.

Recommendations for additional magnetic resonance imaging in abdominal computed tomography.

Reporting the findings from radiologic images is an important method for radiologists to communicate with referring physicians. The purpose of this study was to evaluate the effectiveness of the recommendations for additional imaging (RAIs) after abdominal computed tomography (CT) studies for abdominal magnetic resonance (MR) imaging. The institutional review board approved this retrospective study, which includes data collected from the radiology information system (RIS) database of a tertiary medical referral center. Associations between abdominal CT and subsequent abdominal MR were recorded. The effectiveness of RAIs in an abdominal report was determined. The influence of the wording and the location of the RAIs were also analyzed. The presence of RAIs in an abdominal CT report for an abdominal MR examination was more likely to result in a subsequent MR examination within 120 days (36.7% vs. 4.0%). RAIs were also associated with a reduction in the time interval between the CT and MR examinations (29.0 days vs. 39.0 days). The most effective recommendations included wording that advocated for further evaluation and were mentioned in both the context and conclusion of the report. RAIs have a significant influence on clinical decisions. Radiologists should be aware of the power of RAIs and be prudent and conscientious when making recommendations in radiology reports.

Factors Affecting Adherence to Recommendations for Additional Imaging of Incidental Findings in Radiology Reports

To determine the rate at which recommendations for additional imaging (RAIs) of incidental findings on CT are adhered to at a tertiary-care medical center and what factors influence adherence. We used a radiology clinical informatics tool (mPower, Nuance Communications Inc, Burlington, Massachusetts) to identify RAIs in reports from all CT examinations performed at a tertiary-care medical center during a 6-month period. For those studies in which the RAI was for incidental findings, we reviewed the patients' charts to determine if there was appropriate follow-up of the lesion in question. The overall rate of adherence to RAIs was 39.1%, and in patients with a same-institution primary care provider (PCP), 56.8% (P < .0001). Adherence was higher in studies ordered in the outpatient setting (P < .0001) and in patients with a same-institution PCP (P < .0001). Among patients with a same-institution PCP, adherence was highest for outpatients (66.7%), followed by patients seen in the emergency department (46.0%) and inpatients (36.0%). Among outpatients, adherence was highest with PCPs (67%) followed by internal medicine subspecialties (50%) and surgery (38%). The rate of adherence to recommendations for additional imaging of incidental findings was 39.1% in this study and higher for patients with a same-institution PCP, studies ordered in the outpatient setting, and in studies ordered by PCPs.

EPITHELIAL MYOEPITHELIAL CARCINOMA: A RARE CAUSE OF ENDOBRONCHIAL OBSTRUCTION

SESSION TITLE: Monday Fellow Case Report Posters SESSION TYPE: Fellow Case Report Posters PRESENTED ON: 10/21/2019 02:30 PM - 03:15 PM INTRODUCTION: Endobronchial tumors have been reported in numerous benign and malignant conditions. Epithelial myoepithelial carcinoma is a rare malignant cause of endobronchial obstruction for which guidelines for management are lacking. CASE PRESENTATION: A 74 y/o female presented with a complaints of wheezing and hemoptysis. A CT chest revealed an 8 mm obstructing lesion in the distal left main stem bronchus. A bronchoscopy with endobronchial biopsy was performed by the patient's general pulmonologist which showed a low grade salivary gland tumor. She was then referred to Interventional Pulmonology for further removal and management of the tumor. Rigid and flexible bronchoscopy were performed with debridement of the tumor using the bevel of the rigid bronchoscope followed by mechanical debridement with forceps. Due to residual tumor which appeared embedded within the bronchial wall, laser debridement was performed using a 600 nm diode laser fiber at 14W, pulse 1, 0.7s. Additional endobronchial biopsy specimens were consistent with an epithelial myoepithelial carcinoma. The case was reviewed by our institution's Tumor Board with recommendations for additional imaging including CT head and neck which were negative for further evidence of malignancy. Symptoms resolved following resection of the tumor. DISCUSSION: Epithelial myoepithelial carcinoma is a rare malignant tumor seen most frequently in the salivary glands. There are a small number of case reports of primary lung tumors consistent with the same pathology as these salivary gland tumors which are believed to originate from the submucosal bronchial glands. As additional imaging in our patient was negative for malignancy, this is presumed to be a rare, primary lung malignancy. Following local resection and laser debridement, our patient will be monitored closely with surveillance bronchoscopy and imaging for evidence of recurrence. CONCLUSIONS: Given the rarity of epithelial myoepithelial carcinoma, long term follow up is required in order to provide improved recommendations regarding both management and prognosis. Reference #1: Latife Doganay, Selcuk Bilgi, Asli Ozdil, Yener Yoruk, Semsi Altaner, and Kemal Kutlu (2003) Epithelial-Myoepithelial Carcinoma of the Lung. Archives of Pathology & Laboratory Medicine: April 2003, Vol. 127, No. 4, pp. e177-e180. DISCLOSURES: No relevant relationships by Sara Greenhill, source=Web Response No relevant relationships by Jessica Johnson, source=Web Response

Recommendations for additional imaging of abdominal imaging examinations: frequency, benefit, and cost

ObjectivesTo investigate the frequency, determinants, clinical implications, and costs of recommendations for additional imaging (RAIs) in secondary interpretations of abdominal imaging examinations.MethodsThis retrospective study included 2225 abdominal imaging examinations from outside institutions that were reinterpreted as part of standard clinical care at a tertiary care center in a one-year time frame.ResultsTwo hundred forty-six RAIs were present in 231 of 2225 reports (10.4%) of secondary abdominal imaging interpretations. Patient age and experience of the radiologist who performed the secondary interpretation were independently significantly associated with the presence of an RAI (both p = 0.002), with odds ratios of 0.99 per year increase in patient age (95% confidence interval [CI], 0.98–1.00) and 1.06 per year increase in experience of the radiologist (95% CI, 1.02–1.10). If followed, RAIs changed clinical management in 31.2%. Total costs of all 246 RAIs, whether performed or not by the referring physicians, amounted to €71,032.21, thus resulting in €31.92 per secondary abdominal imaging interpretation. Total costs of the 140 RAIs that were actually performed by the referring physicians amounted to €42,683.08, resulting in €19.18 per secondary abdominal imaging interpretation.ConclusionsThe frequency of RAIs in reports of secondary interpretations of abdominal imaging examinations (which appear to be affected by patients’ age and radiologists’ experience) and associated costs are non-negligible. However, RAIs not infrequently change clinical management. The presented data may be helpful to radiology departments and healthcare policy makers to make well-informed decisions on the value and facilitation of the practice of secondary interpretations.Key Points• Frequency of recommendations for additional imaging (RAIs) in secondary interpretations of abdominal imaging examinations at a tertiary care center is approximately 10.4%.• RAIs appear to be more frequently issued in younger patients and by more experienced radiologists, and if followed by referring clinicians, change clinical management in about one third of cases.• RAI costs per secondary interpretation in the Dutch Healthcare system are €31.92 (considering all RAIs) or €19.18 (considering only those RAIs that are actually performed).

Variation in Follow-up Imaging Recommendations in Radiology Reports: Patient, Modality, and Radiologist Predictors.

Background:Variation between radiologists when making recommendations for additional imaging and associated factors are unknown. Clear identification of factors that account for variation in follow-up recommendations might prevent unnecessary tests for incidental or ambiguous image findings.Purpose:Determine incidence and identify factors associated with follow-up recommendations in radiology reports from multiple modalities, patient care settings, and imaging divisions.Material and Methods:This retrospective study analyzed 318,366 reports obtained from diagnostic imaging exams performed at a large urban quaternary care from 1/1/2016 to 12/31/2016, excluding breast and ultrasound reports. A subset of 1000 reports were randomly selected and manually annotated to train and validate a machine learning algorithm to predict whether a report included a follow-up imaging recommendation (training and validation set consisted of 850 reports and test set of 150 reports). The trained algorithm was used to classify 318,366 reports. Multivariable logistic regression was used to determine the likelihood of follow-up recommendation. Additional analysis by imaging subspecialty division was performed and intra-division, inter-radiologist variability quantified.Results:The machine learning algorithm classified 38,745 of 318,366 (12.2%) reports as containing follow-up recommendations. The average patient age was 59 years (SD ±17 years); 45.2% (143,767/318,366) of reports were from male patients. Among 65 radiologists, 56.9% (37/65) were male. In multivariable analysis, older patients had higher rates of follow-up recommendations (OR: 1.01 [1.01–1.01] for each additional year), male patients had lower rates (OR: 0.9 [0.9–1.0]), and follow-up recommendations were most common among CT studies (OR: 4.2 [4.0–4.4] compared to X-ray). Radiologist sex (p=0.54), presence of a trainee (p=0.45), and years in practice (p=0.49) were not significant predictors overall. A division-level analysis showed 2.8-fold to 6.7-fold inter-radiologist variation.Conclusions:Substantial inter-radiologist variation exists in the probability of recommending a follow-up exam in a radiology report, after adjusting for patient, exam and radiologist factors.

Frequency, Determinants, and Costs of Recommendations for Additional Imaging in Clinical 18F-FDG PET/CT Reports.

Our purpose was to determine the frequency, determinants, and costs of recommendations for additional imaging (RAIs) in clinical 18F-FDG PET/CT reports. Methods: This retrospective study included a random sample of 2,643 18F-FDG PET/CT scans that were performed for various clinical reasons at a tertiary-care academic medical center without financial incentives for self-referral, within a 1.5-y period. Results: Ninety-eight (3.7%) of 2,643 18F-FDG PET/CT reports contained an RAI. None of the investigated variables (patient age, hospital status [inpatient or outpatient], indication for 18F-FDG PET/CT scanning [oncologic, infection/inflammation, or miscellaneous], type of 18F-FDG PET/CT scan [low-dose 18F-FDG PET/CT or low-dose 18F-FDG PET/CT combined with diagnostic CT of any body region], or years of experience of the [most senior] signing author) was univariately associated with the presence of an RAI in the 18F-FDG PET/CT report. The hypothesis that RAIs more frequently occur when the anatomic area to which the RAI relates is not covered by a diagnostic CT scan (as part of the 18F-FDG PET/CT examination) was also rejected (P = 0.419). The total costs of all RAIs (regardless of whether they were actually performed by the referring clinicians) were €23,922.21 ($27,065.47), which corresponds to an average of €9.08 ($10.27) RAI costs per 18F-FDG PET/CT exam. The total costs of all RAIs that were actually performed by the referring clinicians were €16,498.62 ($18,666.46), which corresponds to an average of €6.26 ($7.08) RAI costs per 18F-FDG PET/CT exam. Conclusion: RAIs in 18F-FDG PET/CT reports in a European tertiary-care academic medical center without financial incentives for self-referral are infrequent, cannot be anticipated, and result in relatively low overall costs.

Radiologists' recommendations for additional imaging (RAI) in the inpatient setting.

The aim of our study was to measure the rate of radiologists' additional recommended imaging examinations (RAI) at a hospital-based inpatient setting and to estimate the influence on RAI of clinical variables. This retrospective study was approved by the institutional review board. Inpatients CT and US examinations interpreted by fifteen radiologists between October and December 2016 were studied. Information about RAI from radiology report texts was extracted manually. The analytic data set included the interpreting radiologists' years of experience, patient age, patient gender, radiologist gender, ordering service and "clinical question to be answered" as collected from the radiology request forms. Of the 1996 US and CT examinations performed between October and December 2016 in the inpatient setting, 34% (683 examinations) had a radiologists' RAI. The largest proportion of RAI was for chest CT, followed by PET-CT, abdominal CT and abdominal MRI. Patient age and gender had no impact on RAI. Radiologists' years of experience were inversely correlated to RAI. "Pneumonia" showed the highest rate of RAI due to follow-up of lung nodules. A high percentage of RAI resulted from CT and US radiologists' reports. The largest proportion of RAI was for chest CT, followed by PET-CT, abdominal CT, and abdominal MRI. Radiologists' years of experience play an important role in the number of the requested RAI. Further studies with a larger cohort of radiologists are needed to confirm the role of radiologists' experience in RAI. Also, follow-up studies are warranted to assess the number of RAI that are actually acted upon by the referring physicians.

Avoid “Short-Term”: Use Units of Time for Follow-Up Recommendations

An important part of a radiologist’s job is to provide recommendations for follow-up imaging. Imaging findings at a later time point help confirm or exclude a diagnosis. Stability of a vertebral fracture over months would favor an osteoporotic fracture. A pathologic fracture from metastasis is more likely to increase in its extent or be accompanied by new lesions. Recommendations for additional imaging should include the study type, the reason for follow-up, and the time frame in which to perform the follow-up.

Incidental findings in emergency imaging: frequency, recommendations, and compliance with consensus guidelines.

The purpose of this study was to evaluate the frequency of incidental findings (IFs) in emergency department (ED) imaging reports and evaluate the adherence of imaging recommendations to consensus societal guidelines for IFs. A retrospective review of consecutive ED computed tomography (CT) and ultrasonography (US) reports from two university-affiliated EDs over a 2-month period was performed. Each imaging report was reviewed in its entirety, and incidental findings were documented along with recommendations for additional imaging. Imaging recommendations were compared to published societal guidelines from the American College of Radiology (ACR) and Fleischner Society. Three thousand one hundred thirty-one total cases consisting of 1967 CTs and 1164 US contained 514 incidental findings (16.4 %), with 329 CT IFs (64 %) and 185 US IFs (36 %). The ovary was the most common organ for an IF (n = 214, 42 %). Of all IFs, 347 (67.5 %) recommendations were concordant with societal guidelines and 167 (32.5 %) were discordant. 39.8 % of CT recommendations were discordant, while 19.5 % of US recommendations were discordant (p < 0.0001). Incidental findings are commonly encountered in the emergent setting. Variable adherence to societal guidelines is noted. Targeted radiologist education and technological solutions may decrease rates of discordance.

Factors Associated With Rates of False-Positive and False-Negative Results From Digital Mammography Screening: An Analysis of Registry Data

Women screened with digital mammography may receive false-positive and false-negative results and subsequent imaging and biopsies. How these outcomes vary by age, time since the last screening, and individual risk factors is unclear. To determine factors associated with false-positive and false-negative digital mammography results, additional imaging, and biopsies among a general population of women screened for breast cancer. Analysis of registry data. Participating facilities at 5 U.S. Breast Cancer Surveillance Consortium breast imaging registries with linkages to pathology databases and tumor registries. 405,191 women aged 40 to 89 years screened with digital mammography between 2003 and 2011. A total of 2963 were diagnosed with invasive cancer or ductal carcinoma in situ within 12 months of screening. Rates of false-positive and false-negative results and recommendations for additional imaging and biopsies from a single screening round; comparisons by age, time since the last screening, and risk factors. Rates of false-positive results (121.2 per 1000 women [95% CI, 105.6 to 138.7]) and recommendations for additional imaging (124.9 per 1000 women [CI, 109.3 to 142.3]) were highest among women aged 40 to 49 years and decreased with increasing age. Rates of false-negative results (1.0 to 1.5 per 1000 women) and recommendations for biopsy (15.6 to 17.5 per 1000 women) did not differ greatly by age. Results did not differ by time since the last screening. False-positive rates were higher for women with risk factors, particularly family history of breast cancer; previous benign breast biopsy result; high breast density; and, for younger women, low body mass index. Confounding by variation in patient-level characteristics and outcomes across registries and regions may have been present. Some factors, such as numbers of first- and second-degree relatives with breast cancer and diagnoses associated with previous benign biopsy results, were not examined. False-positive mammography results and additional imaging are common, particularly for younger women and those with risk factors, whereas biopsies occur less often. Rates of false-negative results are low. Agency for Healthcare Research and Quality and National Cancer Institute.

Correlation of the Strength of Recommendations for Additional Imaging to Adherence Rate and Diagnostic Yield

PurposeThe aim of this study was to evaluate the association between the wording of radiologist recommendations for chest CT with the likelihood of recommendation adherence and the diagnostic yield of the recommended follow-up CT imaging. MethodsThis HIPAA-compliant retrospective study had institutional review board approval, including waiver of the requirement for patient consent. All outpatient chest radiographic (CXR) studies performed at a tertiary care academic medical center in 2008 (n = 29,138) were searched to identify examinations with recommendations for chest CT. The wording of chest CT recommendations was classified as conditional or absolute, on the basis of whether the recommendation stood independent of the clinical judgment of the ordering clinician. Using the radiology information system, patients who underwent chest CT within 90 days of the index CXR study containing the recommendation were determined, and the CT studies were evaluated to determine if there were abnormalities corresponding to the CXR abnormalities that prompted the recommendations. Corresponding abnormalities were categorized as clinically relevant or not, on the basis of whether further workup or treatment was warranted. Groups were compared using t tests and Fisher exact tests. ResultsRecommendations for chest CT appeared in 4.5% of outpatient CXR studies (1,316 of 29,138; 95% confidence interval [CI], 4.3%–4.8%); 39.4% (519 of 1,316; 95% CI, 36.8%–42.0%) were conditional and 60.6% (797 of 1,316; 95% CI, 58.0%–63.2%) were absolute. Patients with absolute recommendations were significantly more likely to undergo follow-up chest CT within 90 days than patients with conditional recommendations (67.8% vs 45.8%, respectively, P < .001). Despite this difference in provider adherence, there was no significant difference between the conditional and absolute recommendation groups with regard to the incidence of clinically relevant corresponding findings (P = .16) or malignancy (P = .08) on follow-up CT. ConclusionsConditional radiologist recommendations are associated with decreased provider adherence, though the likelihood of a clinically relevant finding on follow-up CT is no different than with absolute recommendations.