Noninvasive risk stratification of lung adenocarcinoma using quantitative computed tomography

Sushravya Raghunath, Fabien Maldonado, Srinivasan Rajagopalan, Ronald A. Karwoski, Zackary S. DePew, Brian Jack Bartholmai, Tobias D Peikert, Richard A. Robb

Research output: Contribution to journalArticle

26 Citations (Scopus)

Abstract

Introduction: Lung cancer remains the leading cause of cancer-related deaths in the United States and worldwide. Adenocarcinoma is the most common type of lung cancer and encompasses lesions with widely variable clinical outcomes. In the absence of noninvasive risk stratification, individualized patient management remains challenging. Consequently a subgroup of pulmonary nodules of the lung adenocarcinoma spectrum is likely treated more aggressively than necessary. Methods: Consecutive patients with surgically resected pulmonary nodules of the lung adenocarcinoma spectrum (lesion size ≤3 cm, 2006-2009) and available presurgical high-resolution computed tomography (HRCT) imaging were identified at Mayo Clinic Rochester. All cases were classified using an unbiased Computer-Aided Nodule Assessment and Risk Yield (CANARY) approach based on the quantification of presurgical HRCT characteristics. CANARY-based classification was independently correlated to postsurgical progression-free survival. Results: CANARY analysis of 264 consecutive patients identified three distinct subgroups. Independent comparisons of 5-year disease-free survival (DFS) between these subgroups demonstrated statistically significant differences in 5-year DFS, 100%, 72.7%, and 51.4%, respectively (p = 0.0005). Conclusions: Noninvasive CANARY-based risk stratification identifies subgroups of patients with pulmonary nodules of the adenocarcinoma spectrum characterized by distinct clinical outcomes. This technique may ultimately improve the current expert opinion-based approach to the management of these lesions by facilitating individualized patient management.

Original languageEnglish (US)
Pages (from-to)1698-1703
Number of pages6
JournalJournal of Thoracic Oncology
Volume9
Issue number11
DOIs
StatePublished - Nov 1 2014

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Tomography
Disease-Free Survival
Lung Neoplasms
Lung
Expert Testimony
Adenocarcinoma
Adenocarcinoma of lung
Neoplasms

ASJC Scopus subject areas

  • Oncology
  • Pulmonary and Respiratory Medicine

Cite this

Raghunath, S., Maldonado, F., Rajagopalan, S., Karwoski, R. A., DePew, Z. S., Bartholmai, B. J., ... Robb, R. A. (2014). Noninvasive risk stratification of lung adenocarcinoma using quantitative computed tomography. Journal of Thoracic Oncology, 9(11), 1698-1703. https://doi.org/10.1097/JTO.0000000000000319

Noninvasive risk stratification of lung adenocarcinoma using quantitative computed tomography. / Raghunath, Sushravya; Maldonado, Fabien; Rajagopalan, Srinivasan; Karwoski, Ronald A.; DePew, Zackary S.; Bartholmai, Brian Jack; Peikert, Tobias D; Robb, Richard A.

In: Journal of Thoracic Oncology, Vol. 9, No. 11, 01.11.2014, p. 1698-1703.

Research output: Contribution to journalArticle

Raghunath, Sushravya ; Maldonado, Fabien ; Rajagopalan, Srinivasan ; Karwoski, Ronald A. ; DePew, Zackary S. ; Bartholmai, Brian Jack ; Peikert, Tobias D ; Robb, Richard A. / Noninvasive risk stratification of lung adenocarcinoma using quantitative computed tomography. In: Journal of Thoracic Oncology. 2014 ; Vol. 9, No. 11. pp. 1698-1703.
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