Pulmonary nodule characterization, including computer analysis and quantitative features

Brian Jack Bartholmai, Chi Wan Koo, Geoffrey B. Johnson, Darin B. White, Sushravya M. Raghunath, Srinivasan Rajagopalan, Michael R. Moynagh, Rebecca M. Lindell, Thomas E. Hartman

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

Pulmonary nodules are commonly detected in computed tomography (CT) chest screening of a high-risk population. The specific visual or quantitative features on CT or other modalities can be used to characterize the likelihood that a nodule is benign or malignant. Visual features on CT such as size, attenuation, location, morphology, edge characteristics, and other distinctive "signs" can be highly suggestive of a specific diagnosis and, in general, be used to determine the probability that a specific nodule is benign or malignant. Change in size, attenuation, and morphology on serial follow-up CT, or features on other modalities such as nuclear medicine studies or MRI, can also contribute to the characterization of lung nodules. Imaging analytics can objectively and reproducibly quantify nodule features on CT, nuclear medicine, and magnetic resonance imaging. Some quantitative techniques show great promise in helping to differentiate benign from malignant lesions or to stratify the risk of aggressive versus indolent neoplasm. In this article, we (1) summarize the visual characteristics, descriptors, and signs that may be helpful in management of nodules identified on screening CT, (2) discuss current quantitative and multimodality techniques that aid in the differentiation of nodules, and (3) highlight the power, pitfalls, and limitations of these various techniques.

Original languageEnglish (US)
Pages (from-to)139-156
Number of pages18
JournalJournal of Thoracic Imaging
Volume30
Issue number2
DOIs
StatePublished - Mar 6 2015

Fingerprint

Tomography
Lung
Nuclear Medicine
Magnetic Resonance Spectroscopy
Thorax
Magnetic Resonance Imaging
Population
Neoplasms

Keywords

  • attenuation
  • computed tomography
  • computer-Aided diagnosis
  • lung cancer
  • margin
  • pulmonary nodules
  • quantitative imaging
  • screening
  • shape
  • size

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Pulmonary and Respiratory Medicine

Cite this

Bartholmai, B. J., Koo, C. W., Johnson, G. B., White, D. B., Raghunath, S. M., Rajagopalan, S., ... Hartman, T. E. (2015). Pulmonary nodule characterization, including computer analysis and quantitative features. Journal of Thoracic Imaging, 30(2), 139-156. https://doi.org/10.1097/RTI.0000000000000137

Pulmonary nodule characterization, including computer analysis and quantitative features. / Bartholmai, Brian Jack; Koo, Chi Wan; Johnson, Geoffrey B.; White, Darin B.; Raghunath, Sushravya M.; Rajagopalan, Srinivasan; Moynagh, Michael R.; Lindell, Rebecca M.; Hartman, Thomas E.

In: Journal of Thoracic Imaging, Vol. 30, No. 2, 06.03.2015, p. 139-156.

Research output: Contribution to journalArticle

Bartholmai, BJ, Koo, CW, Johnson, GB, White, DB, Raghunath, SM, Rajagopalan, S, Moynagh, MR, Lindell, RM & Hartman, TE 2015, 'Pulmonary nodule characterization, including computer analysis and quantitative features', Journal of Thoracic Imaging, vol. 30, no. 2, pp. 139-156. https://doi.org/10.1097/RTI.0000000000000137
Bartholmai, Brian Jack ; Koo, Chi Wan ; Johnson, Geoffrey B. ; White, Darin B. ; Raghunath, Sushravya M. ; Rajagopalan, Srinivasan ; Moynagh, Michael R. ; Lindell, Rebecca M. ; Hartman, Thomas E. / Pulmonary nodule characterization, including computer analysis and quantitative features. In: Journal of Thoracic Imaging. 2015 ; Vol. 30, No. 2. pp. 139-156.
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