Clinical validation of 4-dimensional computed tomography ventilation with pulmonary function test data

Douglas Brennan, Leah Schubert, Quentin Diot, Richard Castillo, Edward Castillo, Thomas Guerrero, Mary K. Martel, Derek Linderman, Laurie E. Gaspar, Moyed Miften, Brian D. Kavanagh, Yevgeniy Vinogradskiy

    Research output: Contribution to journalArticle

    29 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish (US)
    Pages (from-to)423-429
    Number of pages7
    JournalInternational Journal of Radiation Oncology Biology Physics
    Volume92
    Issue number2
    DOIs
    StatePublished - Jun 1 2015

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    pulmonary functions
    ventilation
    Respiratory Function Tests
    Ventilation
    tomography
    Tomography
    lungs
    Four-Dimensional Computed Tomography
    Lung
    Forced Expiratory Volume
    Lung Neoplasms
    Obstructive Lung Diseases
    cancer

    ASJC Scopus subject areas

    • Oncology
    • Radiology Nuclear Medicine and imaging
    • Radiation
    • Cancer Research

    Cite this

    Clinical validation of 4-dimensional computed tomography ventilation with pulmonary function test data. / Brennan, Douglas; Schubert, Leah; Diot, Quentin; Castillo, Richard; Castillo, Edward; Guerrero, Thomas; Martel, Mary K.; Linderman, Derek; Gaspar, Laurie E.; Miften, Moyed; Kavanagh, Brian D.; Vinogradskiy, Yevgeniy.

    In: International Journal of Radiation Oncology Biology Physics, Vol. 92, No. 2, 01.06.2015, p. 423-429.

    Research output: Contribution to journalArticle

    Brennan, D, Schubert, L, Diot, Q, Castillo, R, Castillo, E, Guerrero, T, Martel, MK, Linderman, D, Gaspar, LE, Miften, M, Kavanagh, BD & Vinogradskiy, Y 2015, 'Clinical validation of 4-dimensional computed tomography ventilation with pulmonary function test data', International Journal of Radiation Oncology Biology Physics, vol. 92, no. 2, pp. 423-429. https://doi.org/10.1016/j.ijrobp.2015.01.019
    Brennan, Douglas ; Schubert, Leah ; Diot, Quentin ; Castillo, Richard ; Castillo, Edward ; Guerrero, Thomas ; Martel, Mary K. ; Linderman, Derek ; Gaspar, Laurie E. ; Miften, Moyed ; Kavanagh, Brian D. ; Vinogradskiy, Yevgeniy. / Clinical validation of 4-dimensional computed tomography ventilation with pulmonary function test data. In: International Journal of Radiation Oncology Biology Physics. 2015 ; Vol. 92, No. 2. pp. 423-429.
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    abstract = "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.",
    author = "Douglas Brennan and Leah Schubert and Quentin Diot and Richard Castillo and Edward Castillo and Thomas Guerrero and Martel, {Mary K.} and Derek Linderman and Gaspar, {Laurie E.} and Moyed Miften and Kavanagh, {Brian D.} and Yevgeniy Vinogradskiy",
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    AU - Brennan, Douglas

    AU - Schubert, Leah

    AU - Diot, Quentin

    AU - Castillo, Richard

    AU - Castillo, Edward

    AU - Guerrero, Thomas

    AU - Martel, Mary K.

    AU - Linderman, Derek

    AU - Gaspar, Laurie E.

    AU - Miften, Moyed

    AU - Kavanagh, Brian D.

    AU - Vinogradskiy, Yevgeniy

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    N2 - 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.

    AB - 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.

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