Literature DB >> 8205857

Interbronchoscopist variability in the diagnosis of lung cancer by flexible bronchoscopy.

H Minami1, Y Ando, F Nomura, S Sakai, K Shimokata.   

Abstract

STUDY
OBJECTIVE: We evaluated the interbronchoscopist variability in the diagnosis of lung cancer by flexible bronchoscopy. DESIGN AND
SETTING: A retrospective review of the bronchoscopic records and clinical charts of patients at a university-affiliated hospital. PATIENTS AND MEASUREMENTS: All records of flexible bronchoscopic procedures performed for the diagnosis of lung cancer were retrospectively reviewed, and procedures that obtained histologic or cytologic evidence of malignancy were considered positive. Rates of positivity were compared according to the following factors: operator, operator experience, bronchoscopic findings, tumor location, and tumor laterality. Factors that affected the positivity rate were evaluated using logistic regression analysis.
RESULTS: Of 384 bronchoscopic procedures performed in 353 patients, 275 (72 percent) were positive. The positivity rate differed significantly depending on the operator (p = 0.003) and the bronchoscopic findings (p < 0.001). A difference between operators was noted in technically difficult cases without epithelial or subepithelial findings and when tumors were located in the upper lobe or the superior segment of the lower lobe. The bronchoscopic findings and the operator also emerged as factors significantly affecting the positivity rate in the logistic analysis.
CONCLUSIONS: The diagnostic yield of bronchoscopy for lung cancer is dependent on both the type of bronchial lesion present and the bronchoscopist.

Entities:  

Mesh:

Year:  1994        PMID: 8205857     DOI: 10.1378/chest.105.6.1658

Source DB:  PubMed          Journal:  Chest        ISSN: 0012-3692            Impact factor:   9.410


  14 in total

1.  Optimal route planning for image-guided EBUS bronchoscopy.

Authors:  Xiaonan Zang; Jason D Gibbs; Ronnarit Cheirsilp; Patrick D Byrnes; Jennifer Toth; Rebecca Bascom; William E Higgins
Journal:  Comput Biol Med       Date:  2019-07-26       Impact factor: 4.589

2.  Transbronchial biopsy catheter enhanced by a multisection continuum robot with follow-the-leader motion.

Authors:  Lenny Dupourqué; Fumitaro Masaki; Yolonda L Colson; Takahisa Kato; Nobuhiko Hata
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-07-09       Impact factor: 2.924

3.  Computer-based route-definition system for peripheral bronchoscopy.

Authors:  Michael W Graham; Jason D Gibbs; William E Higgins
Journal:  J Digit Imaging       Date:  2012-04       Impact factor: 4.056

Review 4.  Bronchoscopy for the diagnosis of peripheral lung lesions.

Authors:  Samjot Singh Dhillon; Kassem Harris
Journal:  J Thorac Dis       Date:  2017-09       Impact factor: 2.895

5.  Image-based reporting for bronchoscopy.

Authors:  Kun-Chang Yu; Jason D Gibbs; Michael W Graham; William E Higgins
Journal:  J Digit Imaging       Date:  2008-12-03       Impact factor: 4.056

6.  3D MDCT-based system for planning peripheral bronchoscopic procedures.

Authors:  Jason D Gibbs; Michael W Graham; William E Higgins
Journal:  Comput Biol Med       Date:  2009-02-12       Impact factor: 4.589

7.  Optimal procedure planning and guidance system for peripheral bronchoscopy.

Authors:  Jason D Gibbs; Michael W Graham; Rebecca Bascom; Duane C Cornish; Rahul Khare; William E Higgins
Journal:  IEEE Trans Biomed Eng       Date:  2013-10-17       Impact factor: 4.538

8.  3D CT-video fusion for image-guided bronchoscopy.

Authors:  William E Higgins; James P Helferty; Kongkuo Lu; Scott A Merritt; Lav Rai; Kun-Chang Yu
Journal:  Comput Med Imaging Graph       Date:  2007-12-21       Impact factor: 4.790

9.  Interactive CT-video registration for the continuous guidance of bronchoscopy.

Authors:  Scott A Merritt; Rahul Khare; Rebecca Bascom; William E Higgins
Journal:  IEEE Trans Med Imaging       Date:  2013-03-12       Impact factor: 10.048

10.  Computer-based System for the Virtual-Endoscopic Guidance of Bronchoscopy.

Authors:  J P Helferty; A J Sherbondy; A P Kiraly; W E Higgins
Journal:  Comput Vis Image Underst       Date:  2007-11       Impact factor: 3.876

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