Utilization of Chest and Abdominopelvic CT for Traumatic Injury From 2011 to 2018: Evaluation Using a National Commercial Database

Trends in CT examination utilization in the emergency department during and after the COVID-19 pandemic

BACKGROUND

The increasing use of CT imaging in emergency departments, despite efforts of reducing low-value imaging, is not fully understood, especially during and after the COVID-19 pandemic. The aim of this study was to investigate the impact of COVID-19 pandemic related measures on trends and volume in CT examinations requested in the emergency department.

METHODS

CT examinations of the head, chest, and/or abdomen-pelvis (n = 161,008), and chest radiographs (n = 113,240) performed at our tertiary care hospital between 01/2014 and 12/2023 were retrospectively analyzed. CT examinations (head, chest, abdomen, dual-region and polytrauma) and chest radiographs requested by the emergency department during (03/2020-03/2022) and after the COVID-19 pandemic (04/2022-12/2023) were compared to a pre-pandemic control period (02/2018-02/2020). Analyses included CT examinations per emergency department visit, and prediction models based on pre-pandemic trends and inpatient data. A regular expressions text search algorithm determined the most common clinical questions.

RESULTS

The usage of dual-region and chest CT examinations were higher during (+ 116,4% and + 115.8%, respectively; p < .001) and after the COVID-19 pandemic (+ 88,4% and + 70.7%, respectively; p < .001), compared to the control period. Chest radiograph usage decreased (-54.1% and - 36.4%, respectively; p < .001). The post-pandemic overall CT examination rate per emergency department visit increased by 4.7%. The prediction model underestimated (p < .001) the growth (dual-region CT: 22.3%, chest CT: 26.7%, chest radiographs: -30.4%), and the rise (p < .001) was higher compared to inpatient data (dual-region CT: 54.8%, chest CT: 52.0%, CR: -32.3%). Post-pandemic, the number of clinical questions to rule out "pulmonary infiltrates", "abdominal pain" and "infection focus" increased up to 235.7% compared to the control period.

CONCLUSIONS

Following the COVID-19 pandemic, chest CT and dual-region CT usage in the emergency department experienced a disproportionate and sustained surge compared to pre-pandemic growth.

Quality assessment of expedited AI generated reformatted images for ED acquired CT abdomen and pelvis imaging

PURPOSE

Retrospectively compare image quality, radiologist diagnostic confidence, and time for images to reach PACS for contrast enhanced abdominopelvic CT examinations created on the scanner console by technologists versus those generated automatically by thin-client artificial intelligence (AI) mechanisms.

METHODS

A retrospective PACS search identified adults who underwent an emergency department contrast-enhanced abdominopelvic CT in 07/2022 (Console Cohort) and 07/2023 (Server Cohort). Coronal and sagittal multiplanar reformatted images (MPR) were created by AI software in the Server cohort. Time to completion of MPR images was compared using 2-sample t-tests for all patients in both cohorts. Two radiologists qualitatively assessed image quality and diagnostic confidence on 5-point Likert scales for 50 consecutive examinations from each cohort. Additionally, they assessed for acute abdominopelvic findings. Continuous variables and qualitative scores were compared with the Mann-Whitney U test. A p < .05 indicated statistical significance.

RESULTS

Mean[SD] time to exam completion in PACS was 8.7[11.1] minutes in the Console cohort (n = 728) and 4.6[6.6] minutes in the Server cohort (n = 892), p < .001. 50 examinations in the Console Cohort (28 women 22 men, 51[19] years) and Server cohort (27 women 23 men, 57[19] years) were included for radiologist review. Age, sex, CTDlvol, and DLP were not statistically different between the cohorts (all p > .05). There was no significant difference in image quality or diagnostic confidence for either reader when comparing the Console and Server cohorts (all p > .05).

CONCLUSION

Examinations utilizing AI generated MPRs on a thin-client architecture were completed approximately 50% faster than those utilizing reconstructions generated at the console with no statistical difference in diagnostic confidence or image quality.

Time trend analysis of Injury Severity score of adult trauma patients with emergent CT examination

PURPOSE

Controversy exists about whole-body computed tomography (CT) as a primary screening modality for suspected multiple trauma patients. Therefore, the aim of this study was to analyze time trends of CT examinations for trauma patients in relation to the Injury Severity Score (ISS).

METHODS

We retrospectively analyzed 561 adult trauma patients (mean age = 54 years) who were admitted to the trauma room of our hospital, immediately followed by a CT examination, in 2009, 2013 und 2017. Review of electronic patient charts was performed to determine the cause of injury. ISS was either calculated upon hospital charts and CT imaging reports or documented in the TraumaRegister DGU® for trauma patients with ICU treatment or ISS ≥ 16.

RESULTS

An increasing number of CT examinations of acute trauma patients were performed at our hospital with 117 patients in 2009 compared to 192 in 2013 and 252 in 2017. Their mean age increased (50 years in 2009, 54 in 2013 and 55 in 2017;p = 0.046), whereas their mean ISS decreased over time (15.2 in 2009 compared to 12.1 in 2013 and 10.6 in 2017;p = 0.001), especially in women (15.1 in 2009, 11.8 in 2013 and 7.4 in 2017;p = 0.001 both), younger age groups (18 to 24 years:15.6 in 2009, 6.5 in 2013 and 8.9 in 2017; p = 0.033 and 25 to 49 years:15.0 in 2009, 11.2 in 2013 and 8.3 in 2017;p = 0.001) as well as motor vehicle collision (MVC) victims (16.2 in 2009, 11.8 in 2013 and 6.1 in 2017; p < 0.001). Trauma patients with a high ISS were especially more likely of older age (OR 1.02,p < 0.001) and with the type of incident being a fall (< 3 m: OR3.84,p < 0.001;>3 m: OR6.22,p < 0.001) compared to MVC.

CONCLUSION

Previous studies suggesting a benefit of primary whole-body CT for trauma patients might not reflect the current patient population with decreasing ISS. Especially females, younger age groups and MVC patients might benefit from stricter selection criteria for receiving whole-body CT. Our results also emphasize the importance of prevention of fall or tumble for elderly people.

Turning radiology reports into epidemiological data to track seasonal pulmonary infections and the COVID-19 pandemic

OBJECTIVES

To automatically label chest radiographs and chest CTs regarding the detection of pulmonary infection in the report text, to calculate the number needed to image (NNI) and to investigate if these labels correlate with regional epidemiological infection data.

MATERIALS AND METHODS

All chest imaging reports performed in the emergency room between 01/2012 and 06/2022 were included (64,046 radiographs; 27,705 CTs). Using a regular expression-based text search algorithm, reports were labeled positive/negative for pulmonary infection if described. Data for regional weekly influenza-like illness (ILI) consultations (10/2013-3/2022), COVID-19 cases, and hospitalization (2/2020-6/2022) were matched with report labels based on calendar date. Positive rate for pulmonary infection detection, NNI, and the correlation with influenza/COVID-19 data were calculated.

RESULTS

Between 1/2012 and 2/2020, a 10.8-16.8% per year positive rate for detecting pulmonary infections on chest radiographs was found (NNI 6.0-9.3). A clear and significant seasonal change in mean monthly detection counts (102.3 winter; 61.5 summer; p < .001) correlated moderately with regional ILI consultations (weekly data r = 0.45; p < .001). For 2020-2021, monthly pulmonary infection counts detected by chest CT increased to 64-234 (23.0-26.7% per year positive rate, NNI 3.7-4.3) compared with 14-94 (22.4-26.7% positive rate, NNI 3.7-4.4) for 2012-2019. Regional COVID-19 epidemic waves correlated moderately with the positive pulmonary infection CT curve for 2020-2022 (weekly new cases: r = 0.53; hospitalizations: r = 0.65; p < .001).

CONCLUSION

Text mining of radiology reports allows to automatically extract diagnoses. It provides a metric to calculate the number needed to image and to track the trend of diagnoses in real time, i.e., seasonality and epidemic course of pulmonary infections.

CLINICAL RELEVANCE

Digitally labeling radiology reports represent previously neglected data and may assist in automated disease tracking, in the assessment of physicians' clinical reasoning for ordering radiology examinations and serve as actionable data for hospital workflow optimization.

KEY POINTS

• Radiology reports, commonly not machine readable, can be automatically labeled with the contained diagnoses using a regular-expression based text search algorithm. • Chest radiograph reports positive for pulmonary infection moderately correlated with regional influenza-like illness consultations (weekly data; r = 0.45; p < .001) and chest CT reports with the course of the regional COVID-19 pandemic (new cases: r = 0.53; hospitalizations: r = 0.65; p < 0.001). • Rendering radiology reports into data labels provides a metric for automated disease tracking, the assessment of ordering physicians clinical reasoning and can serve as actionable data for workflow optimization.

Diagnostic Imaging Utilization in the Emergency Department: Recent Trends in Volume and Radiology Work Relative Value Units

PURPOSE

The aim of this study was to quantify and characterize the recent trend in emergency department (ED) imaging volumes and radiology work relative value units (wRVUs) at level I and level III trauma centers.

METHODS

Total annual diagnostic radiology imaging volumes and wRVUs were obtained from level I and level III trauma centers from January 2014 to December 2021. Imaging volumes were analyzed by modality type, examination code, and location. Total annual patient ED encounters (EDEs), annual weighted Emergency Severity Index, and patient admissions from the ED were obtained. Data were analyzed using annual imaging volume or wRVUs per EDE, and percentage change was calculated.

RESULTS

At the level I trauma center, imaging volumes per EDE increased for chest radiography (5.5%), CT (35.5%), and MRI (56.3%) and decreased for ultrasound (-5.9%) from 2014 to 2021. Imaging volumes per EDE increased for ultrasound (10.4%), CT (74.6%), and MRI (2.0%) and decreased for chest radiography (-4.4%) at the level III trauma center over the same 8-year period. Total wRVUs per EDE increased at both the level I (34.9%) and level III (76.6%) trauma centers over the study period.

CONCLUSIONS

ED imaging utilization increased over the 8-year study period at both level I and level III trauma centers, with an increase in total wRVUs per EDE. There was a disproportionate increased utilization of advanced imaging, such as CT, over time. ED utilization trends suggest that there will be a continued increase in demand for advanced imaging interpretation, including at lower acuity hospitals, so radiology departments should prepare for this increased work demand.