Literature DB >> 28206951

Missed lung cancer: when, where, and why?

Annemilia Del Ciello1, Paola Franchi, Andrea Contegiacomo, Giuseppe Cicchetti, Lorenzo Bonomo, Anna Rita Larici.   

Abstract

Missed lung cancer is a source of concern among radiologists and an important medicolegal challenge. In 90% of the cases, errors in diagnosis of lung cancer occur on chest radiographs. It may be challenging for radiologists to distinguish a lung lesion from bones, pulmonary vessels, mediastinal structures, and other complex anatomical structures on chest radiographs. Nevertheless, lung cancer can also be overlooked on computed tomography (CT) scans, regardless of the context, either if a clinical or radiologic suspect exists or for other reasons. Awareness of the possible causes of overlooking a pulmonary lesion can give radiologists a chance to reduce the occurrence of this eventuality. Various factors contribute to a misdiagnosis of lung cancer on chest radiographs and on CT, often very similar in nature to each other. Observer error is the most significant one and comprises scanning error, recognition error, decision-making error, and satisfaction of search. Tumor characteristics such as lesion size, conspicuity, and location are also crucial in this context. Even technical aspects can contribute to the probability of skipping lung cancer, including image quality and patient positioning and movement. Albeit it is hard to remove missed lung cancer completely, strategies to reduce observer error and methods to improve technique and automated detection may be valuable in reducing its likelihood.

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Year:  2017        PMID: 28206951      PMCID: PMC5338577          DOI: 10.5152/dir.2016.16187

Source DB:  PubMed          Journal:  Diagn Interv Radiol        ISSN: 1305-3825            Impact factor:   2.630


  62 in total

1.  Improved detection of lung cancer arising in diffuse lung diseases on chest radiographs using temporal subtraction.

Authors:  Hiroko Okazaki; Katsumi Nakamura; Hideyuki Watanabe; Yuichi Matsuki; Toshimi Uozumi; Shingo Kakeda; Kouji Kamada; Nobuhiro Oda; Hajime Nakata; Shigehiko Katsuragawa; Kunio Doi
Journal:  Acad Radiol       Date:  2004-05       Impact factor: 3.173

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Journal:  Radiology       Date:  1979-05       Impact factor: 11.105

Review 3.  1976 Caldwell Lecture: varying manifestation of peripheral pulmonary neoplasms: a radiologic-pathologic correlative study.

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Journal:  AJR Am J Roentgenol       Date:  1977-06       Impact factor: 3.959

4.  Carcinoma of the lung. A retrospective study with special reference to pre-diagnosis period and roentgenographic signs.

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Journal:  Acta Radiol Diagn (Stockh)       Date:  1967

5.  Predilection of lung cancer for the upper lobes: an epidemiologic inquiry.

Authors:  T E Byers; J E Vena; T F Rzepka
Journal:  J Natl Cancer Inst       Date:  1984-06       Impact factor: 13.506

6.  Characteristics of lung cancers detected by computer tomography screening in the randomized NELSON trial.

Authors:  Nanda Horeweg; Carlijn M van der Aalst; Erik Thunnissen; Kristiaan Nackaerts; Carla Weenink; Harry J M Groen; Jan-Willem J Lammers; Joachim G Aerts; Ernst T Scholten; Joost van Rosmalen; Willem Mali; Matthijs Oudkerk; Harry J de Koning
Journal:  Am J Respir Crit Care Med       Date:  2013-04-15       Impact factor: 21.405

7.  Comparison of chest tomosynthesis and chest radiography for detection of pulmonary nodules: human observer study of clinical cases.

Authors:  Jenny Vikgren; Sara Zachrisson; Angelica Svalkvist; Ase A Johnsson; Marianne Boijsen; Agneta Flinck; Susanne Kheddache; Magnus Båth
Journal:  Radiology       Date:  2008-10-10       Impact factor: 11.105

8.  Features of non-small cell lung carcinomas overlooked at digital chest radiography.

Authors:  M-H Wu; M B Gotway; T J Lee; M-S Chern; H-C Cheng; J S-C Ko; M-H Sheu; C-Y Chang
Journal:  Clin Radiol       Date:  2008-01-14       Impact factor: 2.350

9.  Performance of computer-aided detection of pulmonary nodules in low-dose CT: comparison with double reading by nodule volume.

Authors:  Yingru Zhao; Geertruida H de Bock; Rozemarijn Vliegenthart; Rob J van Klaveren; Ying Wang; Luca Bogoni; Pim A de Jong; Willem P Mali; Peter M A van Ooijen; Matthijs Oudkerk
Journal:  Eur Radiol       Date:  2012-07-20       Impact factor: 5.315

Review 10.  Computer-aided detection system for lung cancer in computed tomography scans: review and future prospects.

Authors:  Macedo Firmino; Antônio H Morais; Roberto M Mendoça; Marcel R Dantas; Helio R Hekis; Ricardo Valentim
Journal:  Biomed Eng Online       Date:  2014-04-08       Impact factor: 2.819

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  30 in total

1.  Sensitivity of chest X-ray for detecting lung cancer in people presenting with symptoms: a systematic review.

Authors:  Stephen H Bradley; Sarah Abraham; Matthew Ej Callister; Adam Grice; William T Hamilton; Rocio Rodriguez Lopez; Bethany Shinkins; Richard D Neal
Journal:  Br J Gen Pract       Date:  2019-11-28       Impact factor: 5.386

2.  Undetected Lung Cancer at Posteroanterior Chest Radiography: Potential Role of a Deep Learning-based Detection Algorithm.

Authors:  Ju Gang Nam; Eui Jin Hwang; Da Som Kim; Seung-Jin Yoo; Hyewon Choi; Jin Mo Goo; Chang Min Park
Journal:  Radiol Cardiothorac Imaging       Date:  2020-12-10

3.  Validation of deep learning-based computer-aided detection software use for interpretation of pulmonary abnormalities on chest radiographs and examination of factors that influence readers' performance and final diagnosis.

Authors:  Naoki Toda; Masahiro Hashimoto; Yu Iwabuchi; Misa Nagasaka; Ryo Takeshita; Minoru Yamada; Yoshitake Yamada; Masahiro Jinzaki
Journal:  Jpn J Radiol       Date:  2022-09-19       Impact factor: 2.701

4.  Primary healthcare professionals' perspectives on patient help-seeking for lung cancer warning signs and symptoms: a qualitative study.

Authors:  Mohamad M Saab; Michelle O'Driscoll; Serena FitzGerald; Laura J Sahm; Patricia Leahy-Warren; Brendan Noonan; Caroline Kilty; Noreen Lyons; Heather E Burns; Una Kennedy; Áine Lyng; Josephine Hegarty
Journal:  BMC Prim Care       Date:  2022-05-18

5.  Training focal lung pathology detection using an eye movement modeling example.

Authors:  Stephanie Brams; Gal Ziv; Ignace Tc Hooge; Oron Levin; Johny Verschakelen; A Mark Williams; Johan Wagemans; Werner F Helsen
Journal:  J Med Imaging (Bellingham)       Date:  2021-03-13

6.  Long non-coding RNA FAM230B is a novel prognostic and diagnostic biomarker for lung adenocarcinoma.

Authors:  Yu Cao; Hong Zhang; Jianming Tang; Rui Wang
Journal:  Bioengineered       Date:  2022-03       Impact factor: 6.832

7.  Does effective gaze behavior lead to enhanced performance in a complex error-detection cockpit task?

Authors:  Stephanie Brams; Ignace T C Hooge; Gal Ziv; Siska Dauwe; Ken Evens; Tony De Wolf; Oron Levin; Johan Wagemans; Werner F Helsen
Journal:  PLoS One       Date:  2018-11-21       Impact factor: 3.240

8.  Efficiency and reporting confidence analysis of sequential dual-energy subtraction for thoracic x-ray examinations.

Authors:  Mehmet Can Gezer; Oktay Algin; Aytac Durmaz; Halil Arslan
Journal:  Qatar Med J       Date:  2019-09-23

9.  Evaluation of an AI-Powered Lung Nodule Algorithm for Detection and 3D Segmentation of Primary Lung Tumors.

Authors:  Thomas Weikert; Tugba Akinci D'Antonoli; Jens Bremerich; Bram Stieltjes; Gregor Sommer; Alexander W Sauter
Journal:  Contrast Media Mol Imaging       Date:  2019-07-01       Impact factor: 3.161

10.  Medical Image Data and Datasets in the Era of Machine Learning-Whitepaper from the 2016 C-MIMI Meeting Dataset Session.

Authors:  Marc D Kohli; Ronald M Summers; J Raymond Geis
Journal:  J Digit Imaging       Date:  2017-08       Impact factor: 4.056

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