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Interchangeability between real and three-dimensional simulated lung tumors in computed tomography: an interalgorithm volumetry study.

Publication ,  Journal Article
Robins, M; Solomon, J; Hoye, J; Smith, T; Zheng, Y; Ebner, L; Choudhury, KR; Samei, E
Published in: J Med Imaging (Bellingham)
July 2018

Using hybrid datasets consisting of patient-derived computed tomography (CT) images with digitally inserted computational tumors, we establish volumetric interchangeability between real and computational lung tumors in CT. Pathologically-confirmed malignancies from 30 thoracic patient cases from the RIDER database were modeled. Tumors were either isolated or attached to lung structures. Patient images were acquired on one of two CT scanner models (Lightspeed 16 or VCT; GE Healthcare) using standard chest protocol. Real tumors were segmented and used to inform the size and shape of simulated tumors. Simulated tumors developed in Duke Lesion Tool (Duke University) were inserted using a validated image-domain insertion program. Four readers performed volume measurements using three commercial segmentation tools. We compared the volume estimation performance of segmentation tools between real tumors in actual patient CT images and corresponding simulated tumors virtually inserted into the same patient images (i.e., hybrid datasets). Comparisons involved (1) direct assessment of measured volumes and the standard deviation between simulated and real tumors across readers and tools, respectively, (2) multivariate analysis, involving segmentation tools, readers, tumor shape, and attachment, and (3) effect of local tumor environment on volume measurement. Volume comparison showed consistent trends (9% volumetric difference) between real and simulated tumors across all segmentation tools, readers, shapes, and attachments. Across all cases, readers, and segmentation tools, an intraclass correlation coefficient = 0.99 indicates that simulated tumors correlated strongly with real tumors ( p = 0.95 ). In addition, the impact of the local tumor environment on tumor volume measurement was found to have a segmentation tool-related influence. Strong agreement between simulated tumors modeled in this study compared to their real counterparts suggests a high degree of similarity. This indicates that, volumetrically, simulated tumors embedded into patient CT data can serve as reasonable surrogates to real patient data.

Duke Scholars

Published In

J Med Imaging (Bellingham)

DOI

ISSN

2329-4302

Publication Date

July 2018

Volume

5

Issue

3

Start / End Page

035504

Location

United States

Related Subject Headings

  • 4003 Biomedical engineering
  • 3202 Clinical sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Robins, M., Solomon, J., Hoye, J., Smith, T., Zheng, Y., Ebner, L., … Samei, E. (2018). Interchangeability between real and three-dimensional simulated lung tumors in computed tomography: an interalgorithm volumetry study. J Med Imaging (Bellingham), 5(3), 035504. https://doi.org/10.1117/1.JMI.5.3.035504
Robins, Marthony, Justin Solomon, Jocelyn Hoye, Taylor Smith, Yuese Zheng, Lukas Ebner, Kingshuk Roy Choudhury, and Ehsan Samei. “Interchangeability between real and three-dimensional simulated lung tumors in computed tomography: an interalgorithm volumetry study.J Med Imaging (Bellingham) 5, no. 3 (July 2018): 035504. https://doi.org/10.1117/1.JMI.5.3.035504.
Robins M, Solomon J, Hoye J, Smith T, Zheng Y, Ebner L, et al. Interchangeability between real and three-dimensional simulated lung tumors in computed tomography: an interalgorithm volumetry study. J Med Imaging (Bellingham). 2018 Jul;5(3):035504.
Robins, Marthony, et al. “Interchangeability between real and three-dimensional simulated lung tumors in computed tomography: an interalgorithm volumetry study.J Med Imaging (Bellingham), vol. 5, no. 3, July 2018, p. 035504. Pubmed, doi:10.1117/1.JMI.5.3.035504.
Robins M, Solomon J, Hoye J, Smith T, Zheng Y, Ebner L, Choudhury KR, Samei E. Interchangeability between real and three-dimensional simulated lung tumors in computed tomography: an interalgorithm volumetry study. J Med Imaging (Bellingham). 2018 Jul;5(3):035504.

Published In

J Med Imaging (Bellingham)

DOI

ISSN

2329-4302

Publication Date

July 2018

Volume

5

Issue

3

Start / End Page

035504

Location

United States

Related Subject Headings

  • 4003 Biomedical engineering
  • 3202 Clinical sciences