A new method for predicting CT lung nodule volume measurement performance

Ricardo S. Avila, Artit Jirapatnakul, Raja Subramaniam, David Yankelevitz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


Purpose: To evaluate a new approach for predicting nodule volume measurement bias and variability when scanning with a specific CT scanner and acquisition protocol. Methods: A GE LightSpeed VCT scanner was used to scan 3 new rolls of 3M 3/4 x 1000 Inch Scotch Magic tape with a routine chest protocol (120 kVp, 100 mA, 0.4 s rotation,.98 pitch, STANDARD kernel) at three different slice thicknesses and spacings. Each tape scan was independently analyzed by fully automated image quality assessment software, producing fundamental image quality characteristics and simulated lung nodule volume measurements for a range of sphere diameters. The same VCT scanner and protocol was then used to obtain 10 repeat CT scans of an anthropomorphic chest phantom containing multiple Teflon spheres embedded in foam (diameters = 4.76mm, 6.25mm, and 7.94mm). The observed volume of the spheres in the 30 (3 reconstructions per scan) repeat scans was provided by independently developed nodule measurement software. Results: The predicted vs observed mean volume (mm3) and CV for 3 slice thicknesses and sphere sizes was obtained. For 0.625mm slice thickness scans the predicted vs observed values were (44.3,0.91)-vs-(48.2,1.17), (110.4,0.51)-vs-(124.1,0.47), and (219.9,0.29)-vs-(250.1,0.34), for 4.76mm, 6.25mm, and 7.94mm spheres respectively. For 1.25mm slice thickness the corresponding values were (42.1,0.98)-vs-(47.6,1.35), (106.9,0.56)-vs-(123.1,0.61), and (214.8,0.32)-vs-(248.8,0.41). For 2.5mm slice thickness the corresponding values were (23.9,9.53)-vs-(36.8,12.50), (77.6,3.84)-vs-(110.5,3.20), and (173.0,1.57)-vs-(233.9,1.32). Conclusion: Volume measurement bias and variability for lung nodules based on nodule size and acquisition protocol can potentially be predicted using a new method that utilizes fundamental image characteristics and simulation.

Original languageEnglish
Title of host publicationMedical Imaging 2017
Subtitle of host publicationComputer-Aided Diagnosis
EditorsNicholas A. Petrick, Samuel G. Armato
ISBN (Electronic)9781510607132
StatePublished - 2017
EventMedical Imaging 2017: Computer-Aided Diagnosis - Orlando, United States
Duration: 13 Feb 201716 Feb 2017

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (Print)1605-7422


ConferenceMedical Imaging 2017: Computer-Aided Diagnosis
Country/TerritoryUnited States


  • Calibration
  • Computed tomography
  • Image quality
  • Lung nodule
  • Quantitative imaging


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