Improved efficiency of CT interpretation using an automated lung nodule matching program. Academic Article uri icon

Overview

abstract

  • OBJECTIVE: The purpose of this study was to assess the impact of an automated program on improvement in lung nodule matching efficiency. MATERIALS AND METHODS: Four thoracic radiologists independently reviewed two serial chest CT examinations from each of 57 patients. Each radiologist performed timed manual lung nodule matching. After 6 weeks, all radiologists independently repeated the timed matching portion using an automated nodule matching program. The time required for manual and automated matching was compared. The impact of nodule size and number on matching efficiency was determined. RESULTS: An average of 325 (range, 244-413) noncalcified solid pulmonary nodules was identified. Nodule matching was significantly faster with the automated program irrespective of the interpreting radiologist (p < 0.0001 for each). The maximal time saved with automated matching was 11.4 minutes (mean, 2.3 ± 2.0 minutes). Matching was faster in 56 of 57 cases (98.2%) for three readers and in 46 of 57 cases (80.7%) for one reader. There were no differences among readers with respect to the mean time saved per matched nodule (p > 0.5). The automated program achieved 90%, 90%, 79%, and 92% accuracy for the four readers. The improvement in efficiency for a given patient using the automated technique was proportional to the number of matched nodules (p < 0.0001) and inversely proportional to nodule size (p < 0.05). CONCLUSION: Use of the automated lung nodule matching program significantly improves diagnostic efficiency. The time saved is proportionate to the number of nodules identified and inversely proportional to nodule size. Adoption of such a program should expedite CT examination interpretation and improve report turnaround time.

publication date

  • July 1, 2012

Research

keywords

  • Lung Neoplasms
  • Radiographic Image Interpretation, Computer-Assisted
  • Solitary Pulmonary Nodule
  • Tomography, X-Ray Computed

Identity

Scopus Document Identifier

  • 84863702011

Digital Object Identifier (DOI)

  • 10.2214/AJR.11.7522

PubMed ID

  • 22733898

Additional Document Info

volume

  • 199

issue

  • 1