Preoperative (3-dimensional) computed tomography lung reconstruction before anatomic segmentectomy or lobectomy for stage i non-small cell lung cancer Read at the 40th Annual Meeting of the Western Thoracic Surgical Association, Dana Point, California, June 25-28, 2014.

Ernest G. Chan, James R. Landreneau, Matthew J. Schuchert*, David D. Odell, Suicheng Gu, Jiantao Pu, James D. Luketich, Rodney J. Landreneau

*Corresponding author for this work

Research output: Contribution to journalArticle

15 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)523-528
Number of pages6
JournalJournal of Thoracic and Cardiovascular Surgery
Volume150
Issue number3
DOIs
StatePublished - Sep 1 2015

Fingerprint

Segmental Mastectomy
Non-Small Cell Lung Carcinoma
Tomography
Lung
Software
Neoplasms
Surgical Pathology
Emphysema
Lung Neoplasms
Anatomy
Pneumonia
Margins of Excision

Keywords

  • computed tomography
  • lung cancer
  • lung reconstruction
  • segmentectomy

ASJC Scopus subject areas

  • Surgery
  • Pulmonary and Respiratory Medicine
  • Cardiology and Cardiovascular Medicine

Cite this

@article{5c467706faec461ab66ca61f31f08001,
title = "Preoperative (3-dimensional) computed tomography lung reconstruction before anatomic segmentectomy or lobectomy for stage i non-small cell lung cancer Read at the 40th Annual Meeting of the Western Thoracic Surgical Association, Dana Point, California, June 25-28, 2014.",
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.",
keywords = "computed tomography, lung cancer, lung reconstruction, segmentectomy",
author = "Chan, {Ernest G.} and Landreneau, {James R.} and Schuchert, {Matthew J.} and Odell, {David D.} and Suicheng Gu and Jiantao Pu and Luketich, {James D.} and Landreneau, {Rodney J.}",
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Preoperative (3-dimensional) computed tomography lung reconstruction before anatomic segmentectomy or lobectomy for stage i non-small cell lung cancer Read at the 40th Annual Meeting of the Western Thoracic Surgical Association, Dana Point, California, June 25-28, 2014. / Chan, Ernest G.; Landreneau, James R.; Schuchert, Matthew J.; Odell, David D.; Gu, Suicheng; Pu, Jiantao; Luketich, James D.; Landreneau, Rodney J.

In: Journal of Thoracic and Cardiovascular Surgery, Vol. 150, No. 3, 01.09.2015, p. 523-528.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Preoperative (3-dimensional) computed tomography lung reconstruction before anatomic segmentectomy or lobectomy for stage i non-small cell lung cancer Read at the 40th Annual Meeting of the Western Thoracic Surgical Association, Dana Point, California, June 25-28, 2014.

AU - Chan, Ernest G.

AU - Landreneau, James R.

AU - Schuchert, Matthew J.

AU - Odell, David D.

AU - Gu, Suicheng

AU - Pu, Jiantao

AU - Luketich, James D.

AU - Landreneau, Rodney J.

PY - 2015/9/1

Y1 - 2015/9/1

N2 - 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.

AB - 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.

KW - computed tomography

KW - lung cancer

KW - lung reconstruction

KW - segmentectomy

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JO - Journal of Thoracic and Cardiovascular Surgery

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