Literature DB >> 29600047

Evaluation of the 95% limits of agreement of the volumes of 5-year clinically stable solid nodules for the development of a follow-up system for indeterminate solid nodules in CT lung cancer screening.

Ryutaro Kakinuma1,2,3, Yukio Muramatsu1,4, Junta Yamamichi1,5, Shiho Gomi1,6, Estanislao Oubel7, Noriyuki Moriyama1,8.   

Abstract

BACKGROUND: This study sought to evaluate the 95% limits of agreement of the volumes of 5-year clinically stable solid nodules for the development of a follow-up system for indeterminate solid nodules.
METHODS: The volumes of 226 solid nodules that had been clinically stable for 5 years were measured in 186 patients (53 female never-smokers, 36 male never-smokers, 51 males with <30 pack-years, and 46 males with ≥30 pack-years) using a three-dimensional semiautomated method. Volume changes were evaluated using three methods: percent change, proportional change and growth rate. The 95% limits of agreement were evaluated using the Bland-Altman method.
RESULTS: The 95% limits of agreement were as follows: range of percent change, from ±34.5% to ±37.8%; range of proportional change, from ±34.1% to ±36.8%; and range of growth rate, from ±39.2% to ±47.4%. Percent change-based, proportional change-based, and growth rate-based diagnoses of an increase or decrease in ten solid nodules were made at a mean of 302±402, 367±455, and 329±496 days, respectively, compared with a clinical diagnosis made at 809±616 days (P<0.05).
CONCLUSIONS: The 95% limits of agreement for volume change in 5-year stable solid nodules may enable the detection of an increase or decrease in the solid nodule at an earlier stage than that enabled by a clinical diagnosis, possibly contributing to the development of a follow-up system for reducing the number of additional Computed tomography (CT) scans performed during the follow-up period.

Entities:  

Keywords:  Computed tomography (CT); follow-up; indeterminate solid nodule; lung cancer screening; volumetry

Year:  2018        PMID: 29600047      PMCID: PMC5863174          DOI: 10.21037/jtd.2017.11.142

Source DB:  PubMed          Journal:  J Thorac Dis        ISSN: 2072-1439            Impact factor:   2.895


  29 in total

1.  Pulmonary nodules: preliminary experience with three-dimensional evaluation.

Authors:  Marie-Pierre Revel; Catherine Lefort; Alvine Bissery; Marie Bienvenu; Laetitia Aycard; Gilles Chatellier; Guy Frija
Journal:  Radiology       Date:  2004-05       Impact factor: 11.105

2.  Volumetric measurements of pulmonary nodules at multi-row detector CT: in vivo reproducibility.

Authors:  Dag Wormanns; Gerhard Kohl; Ernst Klotz; Anke Marheine; Florian Beyer; Walter Heindel; Stefan Diederich
Journal:  Eur Radiol       Date:  2003-11-13       Impact factor: 5.315

3.  Detection and size measurements of pulmonary nodules in ultra-low-dose CT with iterative reconstruction compared to low dose CT.

Authors:  Xin Sui; Felix G Meinel; Wei Song; Xiaoli Xu; Zixing Wang; Yuyan Wang; Zhengyu Jin; Jiuhong Chen; Rozemarijn Vliegenthart; U Joseph Schoepf
Journal:  Eur J Radiol       Date:  2015-12-21       Impact factor: 3.528

4.  Variability of semiautomated lung nodule volumetry on ultralow-dose CT: comparison with nodule volumetry on standard-dose CT.

Authors:  Patrick A Hein; Valentina C Romano; Patrik Rogalla; Christian Klessen; Alexander Lembcke; Lars Bornemann; Volker Dicken; Bernd Hamm; Hans-Christian Bauknecht
Journal:  J Digit Imaging       Date:  2008-09-05       Impact factor: 4.056

5.  Optimisation of volume-doubling time cutoff for fast-growing lung nodules in CT lung cancer screening reduces false-positive referrals.

Authors:  Marjolein A Heuvelmans; Matthijs Oudkerk; Geertruida H de Bock; Harry J de Koning; Xueqian Xie; Peter M A van Ooijen; Marcel J W Greuter; Pim A de Jong; Harry J M Groen; Rozemarijn Vliegenthart
Journal:  Eur Radiol       Date:  2013-03-19       Impact factor: 5.315

6.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
Journal:  Lancet       Date:  1986-02-08       Impact factor: 79.321

7.  Pulmonary Nodules: growth rate assessment in patients by using serial CT and three-dimensional volumetry.

Authors:  Jane P Ko; Erika J Berman; Manmeen Kaur; James S Babb; Elan Bomsztyk; Alissa K Greenberg; David P Naidich; Henry Rusinek
Journal:  Radiology       Date:  2011-12-09       Impact factor: 11.105

8.  Pulmonary nodules detected at lung cancer screening: interobserver variability of semiautomated volume measurements.

Authors:  Hester A Gietema; Ying Wang; Dongming Xu; Rob J van Klaveren; Harry de Koning; Ernst Scholten; Johny Verschakelen; Gerhard Kohl; Matthijs Oudkerk; Mathias Prokop
Journal:  Radiology       Date:  2006-08-14       Impact factor: 11.105

Review 9.  A practical approach to radiological evaluation of CT lung cancer screening examinations.

Authors:  Xueqian Xie; Marjolein A Heuvelmans; Peter M A van Ooijen; Matthijs Oudkerk; Rozemarijn Vliegenthart
Journal:  Cancer Imaging       Date:  2013-09-23       Impact factor: 3.909

10.  Evaluation of a cloud-based local-read paradigm for imaging evaluations in oncology clinical trials for lung cancer.

Authors:  Naoko Sueoka-Aragane; Naomi Kobayashi; Eric Bonnard; Colette Charbonnier; Junta Yamamichi; Hideaki Mizobe; Shinya Kimura
Journal:  Acta Radiol Open       Date:  2015-11-27
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  1 in total

1.  Resectable lung lesions malignancy assessment and cancer detection by ultra-deep sequencing of targeted gene mutations in plasma cell-free DNA.

Authors:  Muyun Peng; Yuancai Xie; Xiaohua Li; Youhui Qian; Xiaonian Tu; Xumei Yao; Fangsheng Cheng; Feiyue Xu; Deju Kong; Bing He; Chaoyu Liu; Fengjun Cao; Haoxian Yang; Fenglei Yu; Chuanbo Xu; Geng Tian
Journal:  J Med Genet       Date:  2019-04-13       Impact factor: 6.318

  1 in total

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