Literature DB >> 27587037

Should regional ventilation function be considered during radiation treatment planning to prevent radiation-induced complications?

Fujun Lan1, Jean Jeudy1, Suresh Senan2, J R van Sornsen de Koste2, Warren D'Souza1, Huan-Hsin Tseng1, Jinghao Zhou1, Hao Zhang1.   

Abstract

PURPOSE: To investigate the incorporation of pretherapy regional ventilation function in predicting radiation fibrosis (RF) in stage III nonsmall cell lung cancer (NSCLC) patients treated with concurrent thoracic chemoradiotherapy.
METHODS: Thirty-seven patients with stage III NSCLC were retrospectively studied. Patients received one cycle of cisplatin-gemcitabine, followed by two to three cycles of cisplatin-etoposide concurrently with involved-field thoracic radiotherapy (46-66 Gy; 2 Gy/fraction). Pretherapy regional ventilation images of the lung were derived from 4D computed tomography via a density change-based algorithm with mass correction. In addition to the conventional dose-volume metrics (V20, V30, V40, and mean lung dose), dose-function metrics (fV20, fV30, fV40, and functional mean lung dose) were generated by combining regional ventilation and radiation dose. A new class of metrics was derived and referred to as dose-subvolume metrics (sV20, sV30, sV40, and subvolume mean lung dose); these were defined as the conventional dose-volume metrics computed on the functional lung. Area under the receiver operating characteristic curve (AUC) values and logistic regression analyses were used to evaluate these metrics in predicting hallmark characteristics of RF (lung consolidation, volume loss, and airway dilation).
RESULTS: AUC values for the dose-volume metrics in predicting lung consolidation, volume loss, and airway dilation were 0.65-0.69, 0.57-0.70, and 0.69-0.76, respectively. The respective ranges for dose-function metrics were 0.63-0.66, 0.61-0.71, and 0.72-0.80 and for dose-subvolume metrics were 0.50-0.65, 0.65-0.75, and 0.73-0.85. Using an AUC value = 0.70 as cutoff value suggested that at least one of each type of metrics (dose-volume, dose-function, dose-subvolume) was predictive for volume loss and airway dilation, whereas lung consolidation cannot be accurately predicted by any of the metrics. Logistic regression analyses showed that dose-function and dose-subvolume metrics were significant (P values ≤ 0.02) in predicting volume airway dilation. Likelihood ratio test showed that when combining dose-function and/or dose-subvolume metrics with dose-volume metrics, the achieved improvements of prediction accuracy on volume loss and airway dilation were significant (P values ≤ 0.04).
CONCLUSIONS: The authors' results demonstrated that the inclusion of regional ventilation function improved accuracy in predicting RF. In particular, dose-subvolume metrics provided a promising method for preventing radiation-induced pulmonary complications.

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Year:  2016        PMID: 27587037     DOI: 10.1118/1.4960367

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  9 in total

1.  Functional-guided radiotherapy using knowledge-based planning.

Authors:  Austin M Faught; Lindsey Olsen; Leah Schubert; Chad Rusthoven; Edward Castillo; Richard Castillo; Jingjing Zhang; Thomas Guerrero; Moyed Miften; Yevgeniy Vinogradskiy
Journal:  Radiother Oncol       Date:  2018-04-05       Impact factor: 6.280

2.  Evaluating the Toxicity Reduction With Computed Tomographic Ventilation Functional Avoidance Radiation Therapy.

Authors:  Austin M Faught; Yuya Miyasaka; Noriyuki Kadoya; Richard Castillo; Edward Castillo; Yevgeniy Vinogradskiy; Tokihiro Yamamoto
Journal:  Int J Radiat Oncol Biol Phys       Date:  2017-04-26       Impact factor: 7.038

3.  Evaluating Which Dose-Function Metrics Are Most Critical for Functional-Guided Radiation Therapy.

Authors:  Austin M Faught; Tokihiro Yamamoto; Richard Castillo; Edward Castillo; Jingjing Zhang; Moyed Miften; Yevgeniy Vinogradskiy
Journal:  Int J Radiat Oncol Biol Phys       Date:  2017-04-08       Impact factor: 7.038

4.  Interim Analysis of a Two-Institution, Prospective Clinical Trial of 4DCT-Ventilation-based Functional Avoidance Radiation Therapy.

Authors:  Yevgeniy Vinogradskiy; Chad G Rusthoven; Leah Schubert; Bernard Jones; Austin Faught; Richard Castillo; Edward Castillo; Laurie E Gaspar; Jennifer Kwak; Timothy Waxweiler; Michele Dougherty; Dexiang Gao; Craig Stevens; Moyed Miften; Brian Kavanagh; Thomas Guerrero; Inga Grills
Journal:  Int J Radiat Oncol Biol Phys       Date:  2018-10-18       Impact factor: 7.038

5.  Correlation of Functional Lung Heterogeneity and Dosimetry to Radiation Pneumonitis using Perfusion SPECT/CT and FDG PET/CT Imaging.

Authors:  Howard J Lee; Jing Zeng; Hubert J Vesselle; Shilpen A Patel; Ramesh Rengan; Stephen R Bowen
Journal:  Int J Radiat Oncol Biol Phys       Date:  2018-06-01       Impact factor: 7.038

6.  Four-dimensional computed tomography-based biomechanical measurements of pulmonary function and their correlation with clinical outcome for lung stereotactic body radiation therapy patients.

Authors:  Hoda Sharifi; Gary C McDonald; Joon Kyu Lee; Munther I Ajlouni; Indrin J Chetty; Hualiang Zhong
Journal:  Quant Imaging Med Surg       Date:  2019-07

7.  Variations Between Dose-Ventilation and Dose-Perfusion Metrics in Radiation Therapy Planning for Lung Cancer.

Authors:  Yujiro Nakajima; Noriyuki Kadoya; Tomoki Kimura; Kazunari Hioki; Keiichi Jingu; Tokihiro Yamamoto
Journal:  Adv Radiat Oncol       Date:  2020-03-20

Review 8.  CT-based ventilation imaging in radiation oncology.

Authors:  Yevgeniy Vinogradskiy
Journal:  BJR Open       Date:  2019-04-05

9.  A pilot study of function-based radiation therapy planning for lung cancer using hyperpolarized xenon-129 ventilation MRI.

Authors:  Yi Ding; Lu Yang; Qian Zhou; Jianping Bi; Ying Li; Guoliang Pi; Wei Wei; Desheng Hu; Qiuchen Rao; Haidong Li; Li Zhao; An Liu; Dongsu Du; Xiao Wang; Xin Zhou; Guang Han; Kun Qing
Journal:  J Appl Clin Med Phys       Date:  2022-01-19       Impact factor: 2.102

  9 in total

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