CT strain metrics allow for earlier diagnosis of bronchiolitis obliterans syndrome after hematopoietic cell transplant.

Autor:	Sharifi H; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA., Bertini CD; Division of Pulmonary and Critical Care Medicine, University of Texas Health Science Center, Houston, TX., Alkhunaizi M; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA., Hernandez M; Division of Hospital Medicine, Northwestern University, Chicago, IL., Musa Z; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA., Borges C; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA., Turk I; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA., Bashoura L; Department of Pulmonary Medicine, MD Anderson Cancer Center, Houston, TX., Dickey BF; Department of Pulmonary Medicine, MD Anderson Cancer Center, Houston, TX., Cheng GS; Division of Pulmonary, Critical Care and Sleep Medicine, Fred Hutchinson Cancer Center, Seattle, WA., Yanik G; Blood and Marrow Transplant Division, University of Michigan Health, Ann Arbor, MI., Galban CJ; Department of Radiology, Blood and Marrow Transplant Division, University of Michigan Health, Ann Arbor, MI., Guo HH; Department of Radiology, Stanford University School of Medicine, Stanford, CA., Godoy MCB; Department of Pulmonary Medicine, MD Anderson Cancer Center, Houston, TX., Reinhardt JM; Department of Radiology, University of Iowa, Iowa City, IA., Hoffman EA; Department of Radiology, University of Iowa, Iowa City, IA., Castro M; Division of Pulmonary, Critical Care and Sleep Medicine, Kansas University Medical Center, Kansas City, KS., Rondon G; Department of Pulmonary Medicine, MD Anderson Cancer Center, Houston, TX., Alousi AM; Department of Pulmonary Medicine, MD Anderson Cancer Center, Houston, TX., Champlin RE; Department of Pulmonary Medicine, MD Anderson Cancer Center, Houston, TX., Shpall EJ; Department of Pulmonary Medicine, MD Anderson Cancer Center, Houston, TX., Lu Y; Department of Biomedical Data Sciences, Stanford University, Stanford, CA., Peterson S; VIDA Diagnostics, Inc, Coralville, IA., Datta K; Department of Radiology, Stanford University School of Medicine, Stanford, CA., Nicolls MR; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA., Hsu J; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA., Sheshadri A; Division of Pulmonary and Critical Care Medicine, University of Texas Health Science Center, Houston, TX.
Jazyk:	angličtina
Zdroj:	Blood advances [Blood Adv] 2024 Oct 08; Vol. 8 (19), pp. 5156-5165.
DOI:	10.1182/bloodadvances.2024013748
Abstrakt:	Abstract: Bronchiolitis obliterans syndrome (BOS) after hematopoietic cell transplantation (HCT) is associated with substantial morbidity and mortality. Quantitative computed tomography (qCT) can help diagnose advanced BOS meeting National Institutes of Health (NIH) criteria (NIH-BOS) but has not been used to diagnose early, often asymptomatic BOS (early BOS), limiting the potential for early intervention and improved outcomes. Using pulmonary function tests (PFTs) to define NIH-BOS, early BOS, and mixed BOS (NIH-BOS with restrictive lung disease) in patients from 2 large cancer centers, we applied qCT to identify early BOS and distinguish between types of BOS. Patients with transient impairment or healthy lungs were included for comparison. PFTs were done at month 0, 6, and 12. Analysis was performed with association statistics, principal component analysis, conditional inference trees (CITs), and machine learning (ML) classifier models. Our cohort included 84 allogeneic HCT recipients, 66 with BOS (NIH-defined, early, or mixed) and 18 without BOS. All qCT metrics had moderate correlation with forced expiratory volume in 1 second, and each qCT metric differentiated BOS from those without BOS (non-BOS; P < .0001). CITs distinguished 94% of participants with BOS vs non-BOS, 85% of early BOS vs non-BOS, 92% of early BOS vs NIH-BOS. ML models diagnosed BOS with area under the curve (AUC) of 0.84 (95% confidence interval [CI], 0.74-0.94) and early BOS with AUC of 0.84 (95% CI, 0.69-0.97). qCT metrics can identify individuals with early BOS, paving the way for closer monitoring and earlier treatment in this vulnerable population. (© 2024 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)
Databáze:	MEDLINE
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