Accuracy of Computer Aided Diagnosis in Predicting Malignant Thyroid Nodule

Introduction: The thyroid nodule is an abnormal growth of thyroid cells which forms a lump within the thyroid gland. The vast majority of thyroid nodules are benign & a small proportion may have malignancy. It may have solitary or multiple, unilateral or bilateral, focal or diffuse enlargement. The physical examination & blood test only are not helpful to detect benign from malignant nodules & needs thyroid ultrasonography and fine needle biopsy for early detection & treatment. In a suspicious cases, FNA is needed to confirmed benign, from malignant nodules. CAD is a kind of software used in the Sonographic image of thyroid nodule to differentiate benign from malignant condition. CAD software, is non- invasive, no ionizing radiation procedure. It recommend follow up study for benign & FNA for suspicious of malignancy. Objective: To assess the clinical use of Computer Aided Diagnosis (CAD) software to correlate the biopsy report with thyroid nodules. Method: The prospective analytical study was conducted at end of 2018 in department of radio-diagnosis & imaging in tertiary health care system, Nepal in 103 patients of 128 nodules who were presented with thyroid nodule, Routine with Color Doppler ultrasound was done. Computer aided diagnosis (CAD) software applied & guided FNA from different nodules were obtained & correlated with Cyto-pathology study. Result: A total of 103 patients, male 26(24%) & female 78(76%) in the age group of 20-82 years having a solitary or multiple nodules in unilateral or bilateral thyroid lobe (128 nodules) were evaluated. A total of 87.34% were benign &12.66% were malignant nodule Most of the benign nodule was colloid goiter & commonest neoplasm was papillary carcinoma, which is similar to CAD recommendation. CAD can predict the nature of thyroid nodule as benign or malignant with the sensitivity of 94% & specificity 88% & PPV 47 % as a compare with FNAC (Gold standard). Conclusion: CAD effectively & objectively helps to determine which nodule needs to take FNA from different nodules in the same patient whenever needed.