The addition of computed tomography (CT) findings maintains the predictive performance of an existing X-ray-based donor lung acceptability score

Yun Zhu Bai; C. Liu; Zhizhou Yang; Yan Yan Ma; SU-HSIN CHANG; Anjana Delhi; Witt CA; Rodrigo Vazquez Guillamet; Derek E. Byers; Gary F. Marklin; Bruce Nicely; Michael Harmon; Andrew J. Bierhals; Matthew G. Hartwig; Whitney S. Brandt; Ruben G. Nava; Bryan F. Meyers; Benjamin D. Kozower; Michael K. Pasque; G.Alexander Patterson; Daniel Kreisel; Varun Puri

doi:10.1016/j.jtcvs.2026.01.035

Key Points

Donor lung acceptance is significantly associated with computed tomography findings, enhancing predictive performance.
Integration of detailed CT results into the LUNDON model maintained its predictive ability for lung utilization.
The assessment confirms that CT findings do not drastically improve the model’s baseline performance in graft survival prediction.
Implications highlight the advantages of using CT in donor assessments for lung transplantation, though further development may be needed.

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Abstract

Undergoing CT was independently associated with donor lung acceptance. The incorporation of highly granular chest CT findings to the previously established LUNDON model maintained, but did not meaningfully improve, its excellent baseline ability to predict lung utilization and its association with graft survival.

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Bai et al. (2026) studied this question.

synapsesocial.com/papers/69a761a4c6e9836116a2fae7 https://doi.org/10.1016/j.jtcvs.2026.01.035

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The addition of computed tomography (CT) findings maintains the predictive performance of an existing X-ray-based donor lung acceptability score

Key Points

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Abstract

Discussion

Cite This Study

The addition of computed tomography (CT) findings maintains the predictive performance of an existing X-ray-based donor lung acceptability score

Key Points

Ask about this paper

Abstract

Discussion

Cite This Study

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