METHODS: Overall, 612 patients (306 COVID-19 and 306 non-COVID-19 pneumonia) were recruited. Twenty radiological features were extracted from CT images to evaluate the pattern, location, and distribution of lesions of patients in both groups. All significant CT features were fed in five classifiers namely decision tree, K-nearest neighbor, naïve Bayes, support vector machine, and ensemble to evaluate the best performing CAD system in classifying COVID-19 and non-COVID-19 cases.
RESULTS: Location and distribution pattern of involvement, number of the lesion, ground-glass opacity (GGO) and crazy-paving, consolidation, reticular, bronchial wall thickening, nodule, air bronchogram, cavity, pleural effusion, pleural thickening, and lymphadenopathy are the significant features to classify COVID-19 from non-COVID-19 groups. Our proposed CAD system obtained the sensitivity, specificity, and accuracy of 0.965, 93.54%, 90.32%, and 91.94%, respectively, using ensemble (COVIDiag) classifier.
CONCLUSIONS: This study proposed a COVIDiag model obtained promising results using CT radiological routine features. It can be considered an adjunct tool by the radiologists during the current COVID-19 pandemic to make an accurate diagnosis.
KEY POINTS: • Location and distribution of involvement, number of lesions, GGO and crazy-paving, consolidation, reticular, bronchial wall thickening, nodule, air bronchogram, cavity, pleural effusion, pleural thickening, and lymphadenopathy are the significant features between COVID-19 from non-COVID-19 groups. • The proposed CAD system, COVIDiag, could diagnose COVID-19 pneumonia cases with an AUC of 0.965 (sensitivity = 93.54%; specificity = 90.32%; and accuracy = 91.94%). • The AUC, sensitivity, specificity, and accuracy obtained by radiologist diagnosis are 0.879, 87.10%, 88.71%, and 87.90%, respectively.
LEARNING POINTS: There is a broad range of differential diagnosis for acromegaloid features such as acromegaly, pseudoacromegaly with severe insulin resistance, Marfan's syndrome, McCune-Albright and a rare condition called pachydermoperiostosis.Once a patient is suspected to have acromegaly, the first step is biochemical testing to confirm the clinical diagnosis, followed by radiologic testing to determine the cause of the excess growth hormone (GH) secretion. The cause is a somatotroph adenoma of the pituitary in over 95 percent of cases.The first step is measurement of a serum insulin-like growth factor 1 (IGF1). A normal serum IGF1 concentration is strong evidence that the patient does not have acromegaly.If the serum IGF1 concentration is high (or equivocal), serum GH should be measured after oral glucose administration. Inadequate suppression of GH after a glucose load confirms the diagnosis of acromegaly.Once the presence of excess GH secretion is confirmed, the next step is pituitary magnetic resonance imaging (MRI).Atypical presentation warrants revision of the diagnosis. This patient presented with clubbing with no gigantism, which is expected in adolescent acromegalics as the growth spurt and epiphyseal plate closure have not taken place yet.