High resolution computed tomography guided anatomico-pathological scoring system for stratifying and prognosticating pulmonary manifestations of COVID-19

Abstract

Computed Tomography (CT) chest plays a critical role in early identification & stratification of disease burden and prognostication of COVID-19 disease. We compared in-house created CT based scoring system based on ground glass opacities (G-Score), consolidation (C- Score), and atelectasis A-score (i.e. GCA score) with contemporary CT severity scores & validated it against world health organization (WHO) COVID-19 disease severity scale. Patients confirmed with real time polymerase chain reaction confirmed COVID-19 infections that underwent CT chest investigations as a part of standard of care were recruited. A compound GCA score based on the lung involvement was developed and validated. Five-hundred patients of which 249 had mild, 220 with moderate, and 31 with severe COVID-19 disease were recruited.Most involved segments were superior (65%), lateral basal (56%) and posterior basal segments (64%) of right lower lobe and anteromedial (62%) and posterior basal segments (57%) of left lower lobe.Patchy non-confluent peripheral ground-glass opacities with apicobasal gradient is the most common finding (47%) in mild cases. Bilateral lower lobes were most commonly involved (72%).In moderate cases ground-glass opacities with consolidation is the predominant finding (82%).In severe cases ground-glass opacity, consolidation as well as linear platelike atelectasis and reticular opacities may represent with apicobasal gradient (80%).HRCT Chest has certainly come up as a versatile aid for our war against COVID -19. Firstly it helps to diagnose the pulmonary involvement of the disease and when complimented with a good scoring system furthermore it stratifies the disease burden.