Literature DB >> 32305166

Prospective Study of Spatial Distribution of Missed Lung Nodules by Readers in CT Lung Screening Using Computer-assisted Detection.

Soichiro Miki1, Yukihiro Nomura2, Naoto Hayashi1, Shouhei Hanaoka3, Eriko Maeda1, Takeharu Yoshikawa1, Yoshitaka Masutani4, Osamu Abe3.   

Abstract

PURPOSE: To evaluate the spatial patterns of missed lung nodules in a real-life routine screening environment.
MATERIALS AND METHODS: In a screening institute, 4,822 consecutive adults underwent chest CT, and each image set was independently interpreted by two radiologists in three steps: (1) independently interpreted without computer-assisted detection (CAD) software, (2) independently referred to the CAD results, (3) determined by the consensus of the two radiologists. The locations of nodules and the detection performance data were semi-automatically collected using a CAD server integrated into the reporting system. Fisher's exact test was employed for evaluating findings in different lung divisions. Probability maps were drawn to illustrate the spatial distribution of radiologists' missed nodules.
RESULTS: Radiologists significantly tended to miss lung nodules in the bilateral hilar divisions (p < 0.01). Some radiologists had their own spatial pattern of missed lung nodules.
CONCLUSION: Radiologists tend to miss lung nodules present in the hilar regions significantly more often than in the rest of the lung.
Copyright © 2020 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Keywords:  Computer-assisted detection; Lung cancer screening; Lung nodule

Mesh:

Year:  2020        PMID: 32305166     DOI: 10.1016/j.acra.2020.03.015

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  1 in total

1.  Paraneoplastic Cerebellar Degeneration and Lambert-Eaton Myasthenic Syndrome with SOX-1 Antibodies.

Authors:  Shinichi Wada; Mayu Kamei; Naoko Uehara; Koji Tsuzaki; Toshiaki Hamano
Journal:  Intern Med       Date:  2020-12-15       Impact factor: 1.271

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.