A comparison between 2- and 3-dimensional approaches to solid component measurement as radiological criteria for sublobar resection in lung adenocarcinoma ≤ 2 cm in size
- 8 Downloads
We compared three-dimensional (3D) and two-dimensional (2D) measurements of the solid component to determine radiological criteria for sublobar resection of lung adenocarcinoma ≤ 2 cm in size.
We included 233 surgical cases. The maximum size of the solid component for 3D measurement was calculated by delineating the solid component on successive axial images and reconstructing the 3D surface model.
The predictive performance for adenocarcinoma in situ (n = 43) and minimally invasive adenocarcinoma (n = 77) were equivalent to areas under the curve of 0.871 and 0.857 for 2D and 3D measurements (p = 0.229), respectively. A solid component of 5 mm had a prognostic impact on both measurements ( ≤ 5 mm versus > 5 mm; p = 0.003 for 2D and p = 0.002 for 3D, log-rank test). Survival rates at 5 years were 94.7–96.9% following lobectomy and sublobar resection among patients with a solid component ≤ 5 mm in size. Sublobar resection resulted in worse survival rates, with declines at 5 years of 15.8% on 2D and 11.5% on 3D measurements, than lobectomy in patients with a solid component > 5 mm in size.
A solid component ≤ 5 mm in size is an appropriate criterion for sublobar resection for both measurements. In addition, 2D measurement is justified because of its simple implementation.
KeywordsAdenocarcinoma Computed tomography Pathology Solid component
We would like to thank Editage (www.editage.jp) for the English language editing.
This work was supported by the Japan Surgical Society [Young Researcher Award].
Compliance with ethical standards
Conflict of interest
- 1.Ginsberg RJ, Rubinstein LV, Lung Cancer Study Group. Randomized trial of lobectomy versus limited resection for T1 N0 non-small cell lung cancer. Ann Thorac Surg. 1995;60:615-622.Google Scholar
- 2.Travis WD, Brambilla E, Noguchi M, Nicholson AG, Geisinger KR, Yatabe Y, et al. International association for the study of lung cancer/american thoracic society/european respiratory society international multidisciplinary classification of lung adenocarcinoma. J Thorac Oncol. 2011;6:244–85.CrossRefGoogle Scholar
- 3.Travis WD, Brambilla E, Burke AP, Marx A, Nicholson AG. WHO Classification of Tumours of the Lung, Pleura, Thymus and Heart. 1st ed. Lyon: International Agency for Research on Cancer; 2015.Google Scholar
- 5.Travis WD, Asamura H, Bankier AA, Beasley MB, Detterbeck F, Flieder DB et al. The IASLC Lung Cancer Staging Project: Proposals for Coding T categories for subsolid nodules and assessment of tumor size in part-solid tumors in the forthcoming Eighth Edition of the TNM Classification of Lung Cancer. J Thorac Oncol. 2016;11:1204–1223.Google Scholar
- 6.Rami-Porta R, Bolejack V, Crowley J, Ball D, Kim J, Lyons G et al. The IASLC Lung Cancer Staging Project: Proposals for the Revisions of the T descriptors in the forthcoming Eighth Edition of the TNM Classification for Lung Cancer. J Thorac Oncol. 2015;10:990–1003.Google Scholar
- 8.Suzuki K, Koike T, Asakawa T, Kusumoto M, Asamura H, Nagai K, et al. A prospective radiological study of thin-section computed tomography to predict pathological noninvasiveness in peripheral clinical IA lung cancer (Japan Clinical Oncology Group 0201). J Thorac Oncol. 2011;6:751–6.CrossRefGoogle Scholar
- 9.Abramoff MD, Magelhaes PJ, Ram SJ. Image Processing with ImageJ. Biophoton Int. 2004;11:36–42.Google Scholar
- 11.Delaunay BN. [On the empty sphere]. Bull Acad Sci URSS. 1934;6:793–800.Google Scholar
- 13.Henzler T, Goldstraw P, Wenz F, Pirker R, Weder W, Apfaltrer P, et al. Perspectives of novel imaging techniques for staging, therapy response assessment, and monitoring of surveillance in lung cancer: Summary of the Dresden 2013 Post WCLC-IASLC State-of-the-Art Imaging Workshop. J Thorac Oncol. 2015;10:237–49.CrossRefGoogle Scholar