Chronic lung allograft dysfunction (CLAD) limits long-term survival after lung transplantation (LTx). Early detection or prediction of CLAD can lead to changes in patient management that, in turn, may improve prognosis. The purpose of this study was to investigate the utility of quantitative computed tomography (CT) lung density analysis in early prediction of CLAD.
This retrospective cohort was drawn from all consecutive adult, first LTxs performed between 2006 and 2011. Post-transplant monitoring included scheduled surveillance bronchoscopies with concurrent pulmonary-functions tests and low-dose chest CT. Quantitative density metrics (QDM) derived from CT scans obtained at the time of 10%–19% decline in forced expiratory volume in 1 second (FEV1) were evaluated: 114 bilateral LTx recipients (66 with CLAD and 48 stable) and 23 single LTx recipients (11 with CLAD, 12 stable) were included in the analysis.
In both single and double LTx, at the time of 10%–19% drop in FEV1 from baseline, the QDM was higher in patients who developed CLAD within 3 years compared with those patients who remained stable for at least 3.5 years. The area under the receiver operating characteristic curve (AUC) was 0.89 for predicting CLAD in single LTx and 0.63 in bilateral LTx. A multipredictor AUC accounting for FEV1, QDM, presence of consolidation, and ground glass opacities increased the AUC to 0.74 in double LTx.
QDM derived from a CT histogram at the time of early drop in FEV1 may allow prediction of CLAD in patients after single or double LTx.
1 Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, ON.
2 Institute for Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON.
3 Latner Thoracic Surgery Research Laboratories, Toronto General Research Institute, University Health Network, University of Toronto, Toronto, ON.
4 Toronto Lung Transplant Program, University Health Network, University of Toronto, ON.
5 Vital Images, Minnetonka, MN.
6 Department of Thoracic Surgery, Kansai Medical University, Hirakata, Japan.
7 QIPCM, Techna Institute, University Health Network, University of Toronto, ON.
8 Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX.
9 Department of Medical Imaging, London Health Sciences Centre, London, ON.
Received 14 December 2018. Revision received 18 March 2019.
Accepted 5 April 2019.
T.S. was supported by research fellowships from the Japan Society for Promotion of Science for Young Scientists. N.P. and M.H. were supported by educational grants from Canon Medical Systems. P.S. is an employee of Vital Images. Canon Medical Systems and Vital Images did not participate in study design, result interpretation, or article preparation. The other authors declare no conflicts of interest.
This study was presented in part at the annual meeting of the Radiological Society of North America; December 2017.
M.H. designed the study, analyzed the data, and wrote the article. L.L. collected clinical data and edited the article. C.H., C.B., and S.S. performed analysis of CT scan data. P.S. performed statistical analysis. T.S., S.K., N.P., K.Y., K.B., and M.P. contributed to supervision, experimental design, and interpretation of results. T.M. designed and supervised the study, collected and analyzed data, and wrote the article.
Supplemental digital content (SDC) is available for this article. Direct URL citations appear in the printed text, and links to the digital files are provided in the HTML text of this article on the journal’s Web site (www.transplantjournal.com).
Correspondence: Tereza Martinu, MD, Toronto Lung Transplant Program, University Health Network, University of Toronto, 585 University Avenue, PMB 11-128, Toronto, ON M5G 2N4, Canada. (email@example.com).