Pierre-Yves Le Roux1, Shankar Siva2, Daniel P Steinfort3, Jason Callahan4, Peter Eu4, Lou B Irving3, Rodney J Hicks2, Michael S Hofman5. 1. Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, East Melbourne, Australia Department of Nuclear Medicine, Brest University Hospital, EA3878 (GETBO) IFR 148, Brest, France pierre-yves.leroux@chu-brest.fr michael.hofman@petermac.org. 2. Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, East Melbourne, Australia The University of Melbourne, Parkville, Australia; and. 3. The University of Melbourne, Parkville, Australia; and Respiratory Medicine, Peter MacCallum Cancer Centre and Royal Melbourne Hospital, Melbourne, Australia. 4. Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, East Melbourne, Australia. 5. Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, East Melbourne, Australia The University of Melbourne, Parkville, Australia; and pierre-yves.leroux@chu-brest.fr michael.hofman@petermac.org.
Abstract
UNLABELLED: Pulmonary function tests (PFTs) are routinely used to assess lung function, but they do not provide information about regional pulmonary dysfunction. We aimed to assess correlation of quantitative ventilation-perfusion (V/Q) PET/CT with PFT indices. METHODS: Thirty patients underwent V/Q PET/CT and PFT. Respiration-gated images were acquired after inhalation of (68)Ga-carbon nanoparticles and administration of (68)Ga-macroaggregated albumin. Functional volumes were calculated by dividing the volume of normal ventilated and perfused (%NVQ), unmatched and matched defects by the total lung volume. These functional volumes were correlated with forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, and diffusing capacity for carbon monoxide (DLCO). RESULTS: All functional volumes were significantly different in patients with chronic obstructive pulmonary disease (P < 0.05). FEV1/FVC and %NVQ had the highest correlation (r = 0.82). FEV1 was also best correlated with %NVQ (r = 0.64). DLCO was best correlated with the volume of unmatched defects (r = -0.55). Considering %NVQ only, a cutoff value of 90% correctly categorized 28 of 30 patients with or without significant pulmonary function impairment. CONCLUSION: Our study demonstrates strong correlations between V/Q PET/CT functional volumes and PFT parameters. Because V/Q PET/CT is able to assess regional lung function, these data support the feasibility of its use in radiation therapy and preoperative planning and assessing pulmonary dysfunction in a variety of respiratory diseases.
UNLABELLED: Pulmonary function tests (PFTs) are routinely used to assess lung function, but they do not provide information about regional pulmonary dysfunction. We aimed to assess correlation of quantitative ventilation-perfusion (V/Q) PET/CT with PFT indices. METHODS: Thirty patients underwent V/Q PET/CT and PFT. Respiration-gated images were acquired after inhalation of (68)Ga-carbon nanoparticles and administration of (68)Ga-macroaggregated albumin. Functional volumes were calculated by dividing the volume of normal ventilated and perfused (%NVQ), unmatched and matched defects by the total lung volume. These functional volumes were correlated with forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, and diffusing capacity for carbon monoxide (DLCO). RESULTS: All functional volumes were significantly different in patients with chronic obstructive pulmonary disease (P < 0.05). FEV1/FVC and %NVQ had the highest correlation (r = 0.82). FEV1 was also best correlated with %NVQ (r = 0.64). DLCO was best correlated with the volume of unmatched defects (r = -0.55). Considering %NVQ only, a cutoff value of 90% correctly categorized 28 of 30 patients with or without significant pulmonary function impairment. CONCLUSION: Our study demonstrates strong correlations between V/Q PET/CT functional volumes and PFT parameters. Because V/Q PET/CT is able to assess regional lung function, these data support the feasibility of its use in radiation therapy and preoperative planning and assessing pulmonary dysfunction in a variety of respiratory diseases.
Authors: Pierre-Yves Le Roux; Amir Iravani; Jason Callahan; Kate Burbury; Peter Eu; Daniel P Steinfort; Eddie Lau; Beverly Woon; Pierre-Yves Salaun; Rodney J Hicks; Michael S Hofman Journal: Eur J Nucl Med Mol Imaging Date: 2019-05-01 Impact factor: 9.236
Authors: Zhuorui Li; Pierre-Yves Le Roux; Jason Callahan; Nicholas Hardcastle; Michael S Hofman; Shankar Siva; Tokihiro Yamamoto Journal: Phys Imaging Radiat Oncol Date: 2022-04-11
Authors: Paul Leong; Pierre-Yves Le Roux; Jason Callahan; Shankar Siva; Michael S Hofman; Daniel P Steinfort Journal: Respirol Case Rep Date: 2017-08-10
Authors: Asha Bonney; Carrie-Anne Wagner; Shankar Siva; Jason Callahan; Pierre-Yves Le Roux; Diane M Pascoe; Louis Irving; Michael S Hofman; Daniel P Steinfort Journal: EJNMMI Res Date: 2020-07-28 Impact factor: 3.138
Authors: Nicholas Bucknell; Nicholas Hardcastle; Price Jackson; Michael Hofman; Jason Callahan; Peter Eu; Amir Iravani; Rhonda Lawrence; Olga Martin; Mathias Bressel; Beverley Woon; Benjamin Blyth; Michael MacManus; Keelan Byrne; Daniel Steinfort; Tomas Kron; Gerard Hanna; David Ball; Shankar Siva Journal: BMJ Open Date: 2020-12-10 Impact factor: 2.692
Authors: Pierre-Yves Le Roux; Tracy L Leong; Stephen A Barnett; Rodney J Hicks; Jason Callahan; Peter Eu; Renee Manser; Michael S Hofman Journal: Cancer Imaging Date: 2016-08-20 Impact factor: 3.909
Authors: Pierre-Yves Le Roux; Shankar Siva; Jason Callahan; Yannis Claudic; David Bourhis; Daniel P Steinfort; Rodney J Hicks; Michael S Hofman Journal: EJNMMI Res Date: 2017-10-10 Impact factor: 3.138
Authors: David Bourhis; Philippe Robin; Marine Essayan; Ronan Abgral; Solène Querellou; Cécile Tromeur; Pierre-Yves Salaun; Pierre-Yves Le Roux Journal: Front Med (Lausanne) Date: 2020-04-28