Distinguishing early bronchiolitis obliterans syndrome after hematopoietic cell transplantation using novel lung strain metrics from chest ct scans

SESSION TITLE: Transplantation Posters 2 SESSION TYPE: Original Investigation Posters PRESENTED ON: 10/10/2023 12:00 pm - 12:45 pm PURPOSE: Bronchiolitis obliterans syndrome (BOS) after allogeneic hematopoietic cell transplantation (HCT) carries high morbidity and mortality but can be difficult to identify in its earliest stages, often resulting in substantial disease progression prior to diagnosis and initiation of therapy. While formal NIH pulmonary function test (PFT) criteria are defined for BOS, these stringent criteria may contribute to delayed diagnosis. Quantitative lung strain measurements from conventional inspiratory/expiratory (biphasic) CT chest scans have been used to diagnose obstructive airway diseases such as asthma but have not been applied to detect BOS after HCT. METHODS: Biphasic chest CT scans of HCT recipients from MD Anderson Cancer Center and Stanford University were analyzed. Patients were categorized as typical BOS by NIH criteria, early BOS (irreversible >= 10% forced expiratory volume in 1 second (FEV1) decline not meeting NIH criteria); atypical BOS with restrictive physiology; transient impairment (>= 10% FEV1 decline resolving within 6 months); and controls with non-pulmonary graft-versus-host-disease (GVHD). Quantitative measures of air trapping, Jacobian Index (degree of lung strain), and Anisotropic Deformation Index (ADI, isotropy of lung strain) were analyzed by Wilcoxon rank sum and by K-means clustering to distinguish between controls, transient impairment, and different forms of BOS. RESULTS: Eighty patients were included: 43 typical BOS, 15 early BOS, 6 atypical BOS, 7 transient impairment, and 9 GVHD controls. Early BOS was distinguished from controls and from transient impairment, respectively, by air trapping (p=0.007); mean Jacobian (p=0.01); and Jacobian standard deviation (SD) (p=0.002). Mean ADI (p=0.002) and ADI SD (p=0.004) distinguished early BOS from transient impairment. K-means clustering was optimized to 4 clusters, with cluster 1 capturing 81% (n=13) of controls and transient impairment and cluster 2 capturing 66% (n=10) of patients with Early BOS. Of patients with typical or atypical BOS, 71% (n=12) were in clusters 3 and 4. Air trapping (28%), Jacobian (1.7), and ADI (0.35) of cluster 2 were intermediate between cluster 1 (air trapping 8.4%, Jacobian 2.3, ADI 0.50) and clusters 3 and 4 (air trapping 66.1% and 45.5%, Jacobian 1.3 and 1.5, ADI 0.25 and 0.23). CONCLUSIONS: Lung strain metrics and machine learning can distinguish early BOS from patients with transient impairment and from patients without lung disease. CLINICAL IMPLICATIONS: Diagnosis of early BOS by quantitative biphasic CT prior to meeting NIH criteria for BOS by PFT can potentially guide treatment decisions. 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