Literature DB >> 35284294

Volumetric analysis of pulmonary nodules: reducing the discrepancy between the diameter-based volume calculation and voxel-counting method.

Sung Hyun Yoon1, Jihang Kim1, Kyong Joon Lee1,2, Chang-Mo Nam2, Junghoon Kim1, Kyung Hee Lee1,3, Kyung Won Lee1.   

Abstract

Background: When assessing the volume of pulmonary nodules on computed tomography (CT) images, there is an inevitable discrepancy between values based on the diameter-based volume calculation and the voxel-counting method, which is derived from the Euclidean distance measurement method on pixel/voxel-based digital image. We aimed to evaluate the ability of a modified diameter measurement method to reduce the discrepancy, and we determined a conversion equation to equate volumes derived from different methods.
Methods: Two different anthropomorphic phantoms with subsolid and solid nodules were repeatedly scanned under various settings. Nodules in CT images were detected and segmented using a fully automated algorithm and the volume was calculated using three methods: the voxel-counting method (Vvc ), diameter-based volume calculation (Vd ), and a modified diameter-based volume calculation (Vd+ 1), in which one pixel spacing was added to the diameters in the three axes (x-, y-, and z-axis). For each nodule, Vd and Vd +1 were compared to Vvc by computing the absolute percentage error (APE) as follows: APE =100 × (V - Vvc )/Vvc . Comparisons between APEd and APEd+1 according to CT parameter setting were performed using the Wilcoxon signed-rank test. The Jonckheere-Terpstra test was used to evaluate trends across the four different nodule sizes.
Results: The deep learning-based computer-aided diagnosis (DL-CAD) successfully detected and segmented all nodules in a fully automatic manner. The APE was significantly less with Vd+1 than with Vd (Wilcoxon signed-rank test, P<0.05) regardless of CT parameters and nodule size. The APE median increased as the size of the nodule decreased. This trend was statistically significant (Jonckheere-Terpstra test, P<0.001) regardless of volume measurement method (diameter-based and modified diameter-based volume calculations). Conclusions: Our modified diameter-based volume calculation significantly reduces the discrepancy between the diameter-based volume calculation and voxel-counting method. 2022 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Entities:  

Keywords:  Pulmonary nodules; computer-aided diagnosis; volumetry

Year:  2022        PMID: 35284294      PMCID: PMC8899957          DOI: 10.21037/qims-21-485

Source DB:  PubMed          Journal:  Quant Imaging Med Surg        ISSN: 2223-4306


  18 in total

1.  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

2.  CT screening for lung cancer brings forward early disease. The randomised Danish Lung Cancer Screening Trial: status after five annual screening rounds with low-dose CT.

Authors:  Zaigham Saghir; Asger Dirksen; Haseem Ashraf; Karen Skjøldstrup Bach; John Brodersen; Paul Frost Clementsen; Martin Døssing; Hanne Hansen; Klaus Fuglsang Kofoed; Klaus Richter Larsen; Jann Mortensen; Jakob Fraes Rasmussen; Niels Seersholm; Birgit Guldhammer Skov; Hanne Thorsen; Philip Tønnesen; Jesper Holst Pedersen
Journal:  Thorax       Date:  2012-01-27       Impact factor: 9.139

3.  Development and validation of a prediction model for measurement variability of lung nodule volumetry in patients with pulmonary metastases.

Authors:  Eui Jin Hwang; Jin Mo Goo; Jihye Kim; Sang Joon Park; Soyeon Ahn; Chang Min Park; Yeong-Gil Shin
Journal:  Eur Radiol       Date:  2017-01-03       Impact factor: 5.315

4.  Variability of lung tumor measurements on repeat computed tomography scans taken within 15 minutes.

Authors:  Geoffrey R Oxnard; Binsheng Zhao; Camelia S Sima; Michelle S Ginsberg; Leonard P James; Robert A Lefkowitz; Pingzhen Guo; Mark G Kris; Lawrence H Schwartz; Gregory J Riely
Journal:  J Clin Oncol       Date:  2011-07-05       Impact factor: 44.544

5.  Evaluation of patients with pulmonary nodules: when is it lung cancer?: ACCP evidence-based clinical practice guidelines (2nd edition).

Authors:  Michael K Gould; James Fletcher; Mark D Iannettoni; William R Lynch; David E Midthun; David P Naidich; David E Ost
Journal:  Chest       Date:  2007-09       Impact factor: 9.410

6.  Management of lung nodules detected by volume CT scanning.

Authors:  Rob J van Klaveren; Matthijs Oudkerk; Mathias Prokop; Ernst T Scholten; Kristiaan Nackaerts; Rene Vernhout; Carola A van Iersel; Karien A M van den Bergh; Susan van 't Westeinde; Carlijn van der Aalst; Erik Thunnissen; Dong Ming Xu; Ying Wang; Yingru Zhao; Hester A Gietema; Bart-Jan de Hoop; Harry J M Groen; Geertruida H de Bock; Peter van Ooijen; Carla Weenink; Johny Verschakelen; Jan-Willem J Lammers; Wim Timens; Dik Willebrand; Aryan Vink; Willem Mali; Harry J de Koning
Journal:  N Engl J Med       Date:  2009-12-03       Impact factor: 91.245

7.  Segmentation-based partial volume correction for volume estimation of solid lesions in CT.

Authors:  Frank Heckel; Hans Meine; Jan H Moltz; Jan-Martin Kuhnigk; Johannes T Heverhagen; Andreas Kiessling; Boris Buerke; Horst K Hahn
Journal:  IEEE Trans Med Imaging       Date:  2013-10-28       Impact factor: 10.048

Review 8.  A computer-aided diagnosis for evaluating lung nodules on chest CT: the current status and perspective.

Authors:  Jin Mo Goo
Journal:  Korean J Radiol       Date:  2011-03-03       Impact factor: 3.500

9.  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

10.  UK Lung Cancer RCT Pilot Screening Trial: baseline findings from the screening arm provide evidence for the potential implementation of lung cancer screening.

Authors:  J K Field; S W Duffy; D R Baldwin; D K Whynes; A Devaraj; K E Brain; T Eisen; J Gosney; B A Green; J A Holemans; T Kavanagh; K M Kerr; M Ledson; K J Lifford; F E McRonald; A Nair; R D Page; M K B Parmar; D M Rassl; R C Rintoul; N J Screaton; N J Wald; D Weller; P R Williamson; G Yadegarfar; D M Hansell
Journal:  Thorax       Date:  2015-12-08       Impact factor: 9.139

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