Preoperative (3-dimensional) computed tomography lung reconstruction before anatomic segmentectomy or lobectomy for stage I non–small cell lung cancer

Abstract Objectives Accurate cancer localization and negative resection margins are necessary for successful segmentectomy. In this study, we evaluate a newly developed software package that permits automated segmentation of the pulmonary parenchyma, allowing 3-dimensional assessment of tumor size,...

Full description

Saved in:
Bibliographic Details
Published inThe Journal of thoracic and cardiovascular surgery Vol. 150; no. 3; pp. 523 - 528
Main Authors Chan, Ernest G., MD, Landreneau, James R., BS, Schuchert, Matthew J., MD, Odell, David D., MD, MSSc, Gu, Suicheng, PhD, Pu, Jiantao, PhD, Luketich, James D., MD, Landreneau, Rodney J., MD
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.09.2015
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Abstract Objectives Accurate cancer localization and negative resection margins are necessary for successful segmentectomy. In this study, we evaluate a newly developed software package that permits automated segmentation of the pulmonary parenchyma, allowing 3-dimensional assessment of tumor size, location, and estimates of surgical margins. Methods A pilot study using a newly developed 3-dimensional computed tomography analytic software package was performed to retrospectively evaluate preoperative computed tomography images of patients who underwent segmentectomy (n = 36) or lobectomy (n = 15) for stage 1 non–small cell lung cancer. The software accomplishes an automated reconstruction of anatomic pulmonary segments of the lung based on bronchial arborization. Estimates of anticipated surgical margins and pulmonary segmental volume were made on the basis of 3-dimensional reconstruction. Results Autosegmentation was achieved in 72.7% (32/44) of preoperative computed tomography images with slice thicknesses of 3 mm or less. Reasons for segmentation failure included local severe emphysema or pneumonitis, and lower computed tomography resolution. Tumor segmental localization was achieved in all autosegmented studies. The 3-dimensional computed tomography analysis provided a positive predictive value of 87% in predicting a marginal clearance greater than 1 cm and a 75% positive predictive value in predicting a margin to tumor diameter ratio greater than 1 in relation to the surgical pathology assessment. Conclusions This preoperative 3-dimensional computed tomography analysis of segmental anatomy can confirm the tumor location within an anatomic segment and aid in predicting surgical margins. This 3-dimensional computed tomography information may assist in the preoperative assessment regarding the suitability of segmentectomy for peripheral lung cancers.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Undefined-1
ObjectType-Feature-3
content type line 23
ISSN:0022-5223
1097-685X
DOI:10.1016/j.jtcvs.2015.06.051