TY - JOUR AV - public JF - Current Opinion in Pulmonary Medicine KW - Quantitative CT analysis KW - Pulmonary function tests KW - Fibrosing lung disease IS - 5 SP - 426 SN - 1070-5287 VL - 25 UR - https://doi.org/10.1097/MCP.0000000000000589 A1 - Jacob, J EP - 433 N2 - Purpose of Review: Computer algorithms possess an intrinsic speed, objectivity, reproducibility and scalability unmatched by visual quantitation methods performed by trained readers. The question of how well quantitative CT (QCT) analysis methods compare to visual CT analysis to predict functional status in fibrosing lung diseases (FLDs) is of increasing relevance to understand the future role QCT may have in prognostication of FLD. Recent Findings: The latest computer algorithms demonstrate improved performance over visual CT analysis in predicting baseline disease severity as measured by correlations with functional indices of lung damage. QCT analysis may therefore have a role in aiding clinical decision making as well as in the enrichment of drug trial populations. Quantitative analysis on longitudinal CTs has also shown better correlations with changes in functional indices when compared to visual scores of change suggesting the potential of QCT analysis as an imaging biomarker of disease progression in FLD. Importantly, computer algorithms are now able to identify prognostic imaging biomarkers that cannot be quantified visually (e.g. vessel-related structures). Summary: QCT holds great promise for the evaluation of damage in FLD. Challenges for QCT include accommodating measurement noise from variation in CT acquisition techniques and developing patient-friendly visualisations of quantitative outputs. ID - discovery10072026 PB - Lippincott, Williams & Wilkins N1 - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions. TI - Visual vs Computer-based CT analysis for the identification of functional patterns in interstitial lung diseases Y1 - 2019/09/01/ ER -