Detecting out-of-phase ventilation using 4DCT to improve radiation therapy for lung cancer

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Abstract

Functional avoidance radiation therapy (RT) uses lung function images to identify and minimize irradiation of high-function lung tissue. Lung function can be estimated by local expansion ratio (LER) of the lung, which we define in this paper as the ratio of the maximum to the minimum local lung volume in a breathing cycle. LER is computed using deformable image registration. The end exhale (0EX) and the end inhale (100IN) phases of four-dimensional computed tomography (4DCT) are often used to estimate LER, which we refer to as LER3D. However, the lung may have out-of-phase ventilation, i.e., local lung volume change is out of phase with respect to global lung expansion and contraction. We propose the LER4D measure which estimates the LER measure using all phases of 4DCT. The purpose of this paper is to quantify the amount of out-of-phase ventilation of the lung. Out-of-phase ventilation is defined to occur when the LER4D measure is 5% or more than the LER3D measure. 4DCT scans of 14 human subjects were used in this study. Low-function (high-function) regions are defined as regions that have less (greater) than 10% expansion. Our results show that on average 19.3% of the lung had out-of-phase ventilation; 3.8% of the lung had out-of-phase ventilation and is labeled as low-function by both LER3D and LER4D; 9.6% of the lung is labeled as low-function by LER3D while high-function by LER4D; and 5.9% of the lung had out-of-phase ventilation and is labeled as high-function by both LER3D and LER4D. We conclude that out-of-phase ventilation is common in all 14 human subjects we have investigated.

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Shao, W., Patton, T. J., Gerard, S. E., Pan, Y., Reinhardt, J. M., Bayouth, J. E., … Christensen, G. E. (2018). Detecting out-of-phase ventilation using 4DCT to improve radiation therapy for lung cancer. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11040 LNCS, pp. 251–259). Springer Verlag. https://doi.org/10.1007/978-3-030-00946-5_25

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