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Emergency Radiology

, Volume 26, Issue 6, pp 609–614 | Cite as

Integration of fully automated computer-aided pulmonary nodule detection into CT pulmonary angiography studies in the emergency department: effect on workflow and diagnostic accuracy

  • Amirhossein Mozaffary
  • Tugce Agirlar Trabzonlu
  • Pamela Lombardi
  • Adeel R. Seyal
  • Rishi Agrawal
  • Vahid YaghmaiEmail author
Original Article
  • 38 Downloads

Abstract

Purpose

To assess the feasibility of implementing fully automated computer-aided diagnosis (CAD) for detection of pulmonary nodules on CT pulmonary angiography (CTPA) studies in emergency setting.

Materials and methods

CTPA of 48 emergency patients was retrospectively reviewed. Fully automated CAD nodule detection was performed at the scanner and results were automatically submitted to PACS. A third-year radiology resident (RAD1) and a cardiothoracic radiologist with 6 years’ experience (RAD2) reviewed the scans independently to detect pulmonary nodules in two different sessions 8 weeks apart: session 1, CAD was reviewed first and then all images were reviewed; session 2, CAD was reviewed last after all images were reviewed. Time spent by RAD to evaluate image sets was measured for each case. Fisher’s exact test and t test were used.

Results

There were 17 male and 31 female patients with mean ± SD age of 48.7 ± 16.4 years. Using CAD at the beginning was associated with lower average reading time for both readers. However, difference in reading time did not reach statistical significance for RAD1 (RAD1 94.6 s vs. 102.7 s, P > 0.05; RAD2 61.1 s vs. 76.5 s, P < 0.05). Using CAD at the end significantly increased rate of RAD1 and RAD2 nodule detection by 34% (2.52 vs. 2.12 nodule/scan, P < 0.05) and 27% (2.23 vs. 1.81 nodule/scan, P < 0.05), respectively.

Conclusion

Routine utilization of CAD in emergency setting is feasible and can improve detection rate of pulmonary nodules significantly. Different methods of incorporating CAD in detecting pulmonary nodules can improve both the rate of detection and interpretation speed.

Keywords

Computer-aided diagnosis Pulmonary nodule Computed tomography 

Notes

Compliance with ethical standards

Disclosures/grants

Amirhossein Mozaffary – educational grant from Siemens Healthineers; Tugce Agirlar Trabzonlu – educational grant from Siemens Healthineers; Pamela Lombardi – nothing to disclose; Rishi Agrawal – nothing to disclose; Vahid Yaghmai – nothing to disclose.

Conflict of interest

The authors declare that they have no conflict of interest.

IRB statement

This Health Insurance Portability and Accountability Act (HIPAA) compliant study was approved by the Institutional Review Board (IRB). Patient informed consent was waived.

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Copyright information

© American Society of Emergency Radiology 2019

Authors and Affiliations

  • Amirhossein Mozaffary
    • 1
  • Tugce Agirlar Trabzonlu
    • 1
  • Pamela Lombardi
    • 1
  • Adeel R. Seyal
    • 1
  • Rishi Agrawal
    • 1
  • Vahid Yaghmai
    • 1
    Email author
  1. 1.Department of Radiology, Northwestern Memorial HospitalNorthwestern University-Feinberg School of MedicineChicagoUSA

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