Clinical Validation of 4-Dimensional Computed Tomography Ventilation With Pulmonary Function Test Data

被引:57
|
作者
Brennan, Douglas [2 ]
Schubert, Leah [1 ]
Diot, Quentin [1 ]
Castillo, Richard [3 ]
Castillo, Edward [4 ]
Guerrero, Thomas [4 ]
Martel, Mary K. [5 ]
Linderman, Derek [1 ]
Gaspar, Laurie E. [1 ]
Miften, Moyed [1 ]
Kavanagh, Brian D. [1 ]
Vinogradskiy, Yevgeniy [1 ]
机构
[1] Dept Radiat Oncol, Aurora, CO USA
[2] Univ Colorado, Sch Med, Aurora, CO 80045 USA
[3] Univ Texas Med Branch, Dept Radiat Oncol, Galveston, TX 77555 USA
[4] William Beaumont Hosp, Dept Radiat Oncol, Royal Oak, MI 48072 USA
[5] Univ Texas MD Anderson Canc Ctr, Dept Radiat Phys, Houston, TX 77030 USA
基金
美国国家卫生研究院;
关键词
REGISTRATION-BASED MEASURES; LUNG-FUNCTION; CT; IMAGES; TISSUE; REPRODUCIBILITY; IMPACT;
D O I
10.1016/j.ijrobp.2015.01.019
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Purpose: A new form of functional imaging has been proposed in the form of 4-dimensional computed tomography (4DCT) ventilation. Because 4DCTs are acquired as part of routine care for lung cancer patients, calculating ventilation maps from 4DCTs provides spatial lung function information without added dosimetric or monetary cost to the patient. Before 4DCT-ventilation is implemented it needs to be clinically validated. Pulmonary function tests (PFTs) provide a clinically established way of evaluating lung function. The purpose of our work was to perform a clinical validation by comparing 4DCT-ventilation metrics with PFT data. Methods and Materials: Ninety-eight lung cancer patients with pretreatment 4DCT and PFT data were included in the study. Pulmonary function test metrics used to diagnose obstructive lung disease were recorded: forced expiratory volume in 1 second (FEV1) and FEV1/forced vital capacity. Four-dimensional CT data sets and spatial registration were used to compute 4DCT-ventilation images using a density change-based and a Jacobian-based model. The ventilation maps were reduced to single metrics intended to reflect the degree of ventilation obstruction. Specifically, we computed the coefficient of variation (SD/mean), ventilation V20 (volume of lung <= 20% ventilation), and correlated the ventilation metrics with PFT data. Regression analysis was used to determine whether 4DCT ventilation data could predict for normal versus abnormal lung function using PFT thresholds. Results: Correlation coefficients comparing 4DCT-ventilation with PFT data ranged from 0.63 to 0.72, with the best agreement between FEV1 and coefficient of variation. Four-dimensional CT ventilation metrics were able to significantly delineate between clinically normal versus abnormal PFT results. Conclusions: Validation of 4DCT ventilation with clinically relevant metrics is essential. We demonstrate good global agreement between PFTs and 4DCT-ventilation, indicating that 4DCT-ventilation provides a reliable assessment of lung function. Four-dimensional CT ventilation enables exciting opportunities to assess lung function and create functional avoidance radiation therapy plans. The present work provides supporting evidence for the integration of 4DCT-ventilation into clinical trials. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:423 / 429
页数:7
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