Literature DB >> 15100543

Characterization of small nodules by automatic segmentation of X-ray computed tomography images.

Peng Tao1, Friederike Griess, Yelena Lvov, Mikhail Mineyev, Binsheng Zhao, David Levin, Leon Kaufman.   

Abstract

OBJECTIVE: To characterize the ability of an automatic lung nodule segmentation algorithm to measure small nodule dimensions and growth rates.
METHODS: A phantom of 20 sets of 6 balls each (11 different nylon balls and 9 acrylic balls) of 1 to 9.5 mm in diameter, in foam, was imaged using x-ray computed tomography with slice thicknesses of 5, 2.5, and 1.25 mm, pitches of 3 and 6, and standard and lung resolution. Measurements consisted of volume and maximum in-plane cross-sectional areas and their derived maximum and effective diameters. Growth rates were simulated using pairs of groups of balls.
RESULTS: Volume measurements overestimate volume, more so for thicker slices. For the largest balls, the error is 60% for 5-mm slices and 20% for 1.25-mm slices. Effective diameter calculated from volume better approximates actual diameter. For area measurements, errors are 0% to 5% for the largest balls, and the effective and actual diameters are closely matched.
CONCLUSIONS: Below 5 mm in diameter, changes in volume should reach 100% for reliable indication of growth. Above 6 mm, the threshold for detecting change is on the order of 25% growth. Even under ideal conditions, results indicate the need for caution when making a diagnosis of malignancy on the basis of volume change.

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Year:  2004        PMID: 15100543     DOI: 10.1097/00004728-200405000-00012

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


  4 in total

Review 1.  Noncalcified lung nodules: volumetric assessment with thoracic CT.

Authors:  Marios A Gavrielides; Lisa M Kinnard; Kyle J Myers; Nicholas Petrick
Journal:  Radiology       Date:  2009-04       Impact factor: 11.105

2.  Computer-aided diagnosis systems for lung cancer: challenges and methodologies.

Authors:  Ayman El-Baz; Garth M Beache; Georgy Gimel'farb; Kenji Suzuki; Kazunori Okada; Ahmed Elnakib; Ahmed Soliman; Behnoush Abdollahi
Journal:  Int J Biomed Imaging       Date:  2013-01-29

Review 3.  Volume versus diameter assessment of small pulmonary nodules in CT lung cancer screening.

Authors:  Daiwei Han; Marjolein A Heuvelmans; Matthijs Oudkerk
Journal:  Transl Lung Cancer Res       Date:  2017-02

4.  Sensitivity and accuracy of volumetry of pulmonary nodules on low-dose 16- and 64-row multi-detector CT: an anthropomorphic phantom study.

Authors:  Xueqian Xie; Yingru Zhao; Roland A Snijder; Peter M A van Ooijen; Pim A de Jong; Matthijs Oudkerk; Geertruida H de Bock; Rozemarijn Vliegenthart; Marcel J W Greuter
Journal:  Eur Radiol       Date:  2012-07-14       Impact factor: 5.315

  4 in total

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