Assessing the use of 4DCT-ventilation in pre-operative surgical lung cancer evaluation:

Yevgeniy Vinogradskiy, Matthew Jackson, Leah Schubert, Bernard Jones, Richard Castillo, Edward Castillo, Thomas Guerrero, John Mitchell, Chad Rusthoven, Moyed Miften, Brian Kavanagh

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

Purpose: A primary treatment option for lung cancer patients is surgical resection. Patients who have poor lung function prior to surgery are at increased risk of developing serious and life-threatening complications after surgical resection. Surgeons use nuclear medicine ventilation-perfusion (VQ) scans along with pulmonary function test (PFT) information to assess a patient's pre-surgical lung function. The nuclear medicine images and pre-surgery PFTs are used to calculate percent predicted postoperative (%PPO) PFT values by estimating the amount of functioning lung tissue that would be lost with surgical resection. Nuclear medicine imaging is currently considered the standard of care when evaluating the amount of ventilation that would be lost due to surgery. A novel lung function imaging modality has been developed in radiation oncology that uses 4-Dimensional computed tomography data to calculate ventilation maps (4DCT-ventilation). Compared to nuclear medicine, 4DCT-ventilation is cheaper, does not require a radioactive contrast agent, provides a faster imaging procedure, and has improved spatial resolution. In this work we perform a retrospective study to assess the use of 4DCT-ventilation as a pre-operative surgical lung function evaluation tool. Specifically, the purpose of our study was to compare %PPO PFT values calculated with 4DCT-ventilation and %PPO PFT values calculated with nuclear medicine ventilation-perfusion imaging. Methods: The study included 16 lung cancer patients that had undergone 4DCT imaging, nuclear medicine imaging, and had Forced Expiratory Volume in 1 second (FEV1) acquired as part of a standard PFT. The 4DCT datasets, spatial registration, and a density-change-based model were used to compute 4DCT-ventilation maps. Both 4DCT-ventilation and nuclear medicine images were used to calculate %PPO FEV1. The %PPO FEV1 was calculated by scaling the pre-surgical FEV1 by (1-fraction of total resected ventilation); where the resected ventilation was determined using either the 4DCT-ventilation or nuclear medicine imaging. Calculations were done assuming both lobectomy and pneumonectomy resections. The %PPO FEV1 values were compared between the 4DCT-ventilation-based calculations and the nuclear medicine-based calculations using correlation coefficients, average differences, and Receiver Operating Characteristic (ROC) analysis. Results: Overall the 4DCT-ventilation derived %PPO FEV1 values agreed well with nuclear medicine-derived %PPO FEV1 data with correlations of 0.99 and 0.81 for lobectomy and pneumonectomy, respectively. The average differences between the 4DCT-ventilation and nuclear medicine-based calculation for %PPO FEV1 were less than 5%. ROC analysis revealed predictive accuracy that ranged from 87.5% to 100% when assessing the ability of 4DCT-ventilation to predict for nuclear medicine-based %PPO FEV1 values. Conclusions: 4DCT-ventilation is an innovative technology developed in radiation oncology that has great potential to translate to the surgical domain. The high correlation results when comparing 4DCT-ventilation to the current standard of care provide a strong rationale for a prospective clinical trial assessing 4DCT-ventilation in the clinical setting. 4DCT-ventilation can reduce the cost and imaging time for patients while providing improved spatial accuracy and quantitative results for surgeons.

Original languageEnglish (US)
Pages (from-to)200-208
Number of pages9
JournalMedical Physics
Volume44
Issue number1
DOIs
StatePublished - Jan 2017

Keywords

  • CT Ventilation
  • functional imaging
  • lung cancer
  • quantitative imaging
  • surgical evaluation

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

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