Pricing and cost-saving potential for deep-learning computer-aided lung nodule detection software in CT lung cancer screening.

ABSTRACT:

Objective

An increasing number of commercial deep learning computer-aided detection (DL-CAD) systems are available but their cost-saving potential is largely unknown. This study aimed to gain insight into appropriate pricing for DL-CAD in different reading modes to be cost-saving and to determine the potentially most cost-effective reading mode for lung cancer screening.

Methods

In three representative settings, DL-CAD was evaluated as a concurrent, pre-screening, and second reader. Scoping review was performed to estimate radiologist reading time with and without DL-CAD. Hourly cost of radiologist time was collected for the USA (€196), UK (€127), and Poland (€45), and monetary equivalence of saved time was calculated. The minimum number of screening CTs to reach break-even

SUBMITTER: Du Y 

PROVIDER: S-EPMC10682324 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature