title: Quantitative stratification of diffuse parenchymal lung diseases.
abstract: Diffuse parenchymal lung diseases (DPLDs) are characterized by widespread pathological changes within the pulmonary tissue that impair the elasticity and gas exchange properties of the lungs. Clinical-radiological diagnosis of these diseases remains challenging and their clinical course is characterized by variable disease progression. These challenges have hindered the introduction of robust objective biomarkers for patient-specific prediction based on specific phenotypes in clinical practice for patients with DPLD. Therefore, strategies facilitating individualized clinical management, staging and identification of specific phenotypes linked to clinical disease outcomes or therapeutic responses are urgently needed. A classification schema consistently reflecting the radiological, clinical (lung function and clinical outcomes) and pathological features of a disease represents a critical need in modern pulmonary medicine. Herein, we report a quantitative stratification paradigm to identify subsets of DPLD patients with characteristic radiologic patterns in an unsupervised manner and demonstrate significant correlation of these self-organized disease groups with clinically accepted surrogate endpoints. The proposed consistent and reproducible technique could potentially transform diagnostic staging, clinical management and prognostication of DPLD patients as well as facilitate patient selection for clinical trials beyond the ability of current radiological tools. In addition, the sequential quantitative stratification of the type and extent of parenchymal process may allow standardized and objective monitoring of disease, early assessment of treatment response and mortality prediction for DPLD patients.
authors.affiliation: Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, United States of America.
authors.forename: Sushravya
authors.initials: S
authors.lastname: Raghunath
authors.affiliation: Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, United States of America.
authors.forename: Srinivasan
authors.initials: S
authors.lastname: Rajagopalan
authors.affiliation: Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, United States of America.
authors.forename: Ronald A
authors.initials: RA
authors.lastname: Karwoski
authors.affiliation: Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota, United States of America.
authors.forename: Fabien
authors.initials: F
authors.lastname: Maldonado
authors.affiliation: Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota, United States of America.
authors.forename: Tobias
authors.initials: T
authors.lastname: Peikert
authors.affiliation: Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota, United States of America.
authors.forename: Teng
authors.initials: T
authors.lastname: Moua
authors.affiliation: Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota, United States of America.
authors.forename: Jay H
authors.initials: JH
authors.lastname: Ryu
authors.affiliation: Department of Radiology, Mayo Clinic, Rochester, Minnesota, United States of America.
authors.forename: Brian J
authors.initials: BJ
authors.lastname: Bartholmai
authors.affiliation: Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, United States of America.
authors.forename: Richard A
authors.initials: RA
authors.lastname: Robb
mesh_terms: D003937:Diagnosis, Differential; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D008168:Lung / Q000473:pathology; D017563:Lung Diseases, Interstitial / Q000175:diagnosis* / Q000503:physiopathology; D012129:Respiratory Function Tests; D014057:Tomography, X-Ray Computed