Impact of Concurrent Use of Artificial Intelligence Tools on Radiologists Reading Time: A Prospective Feasibility Study

Felix C Müller,Henriette Raaschou,Naurien Akhtar,Mathias Brejnebøl,Lene Collatz,Michael Brun Andersen

doi:10.1016/j.acra.2021.10.008

Abstract

This study investigated how an AI tool impacted radiologists reading time for non-contrast chest CT exams. An AI tool was implemented into the PACS reading workflow of non-contrast chest CT exams between April and May 2020. The reading time was recorded for one CONSULTANT RADIOLOGIST and one RADIOLOGY RESIDENT by an external observer. After each case radiologists answered questions regarding additional findings and perceived case overview. Reading times were recorded for 25 cases without and 20 cases with AI tool assistance for each reader. Differences in reading time with and without the AI tool were assessed using Welch's t-test for non-inferiority with non-inferiority limits defined as 100 seconds for the consultant and 200 seconds for the resident. The mean reading time for the radiology resident was not significantly affected by the AI tool (without AI 370s vs with AI 437s; +67s 95% CI -28s to +163s, p = 0.16). The reading time for the radiology consultant was also not significantly affected by the AI tool (without AI 366s vs with AI 380s; +13s (95% CI - -57s to 84s, p = 0.70). The AI tool led to additional actionable findings in 5/40 (12.5%) studies and better overview in 18/20 (90%) of studies for the resident. A PACS based implementation of an AI tool for concurrent reading of chest CT exams did not increase reading time with additional actionable findings made as well as a perceived better case overview for the radiology resident.

Highlights

The number of commercially available Artificial Intelligence (AI) tools in radiology is rapidly rising
The consultant radiologists stated in 5/20 cases that additional findings were made by the AI tool, while the resident noted no additional findings
Yes No Equivocal Yes No Equivocal Yes No Equivocal Yes No Equivocal Decreased Unchanged Increased Equivocal too many series in one case, picture archiving and communications system (PACS) problems not attributable to the AI tool in one case, and other reasons in two cases. In this prospective feasibility study we assessed the influence of a PACS integrated AI tool on the workflow of two radiologists

Summary

Introduction

The number of commercially available Artificial Intelligence (AI) tools in radiology is rapidly rising. In this manuscript the term AI tool refers to programs or algorithms, which automatically and independently assess imaging studies and inform the radiologists about findings. One of these AI tools, recently introduced at our institution, allows simultaneous reporting of multiple findings in non-contrast low-dose CT scans of the chest. At our institution, this type of scan is primarily used for follow-up of pulmonary nodules identified on previous CT scans or radiographs of the chest

Methods

Results

Conclusion