Zhi-Kai Lei1, Ming-Kui Li2, Ding-Cun Luo3, Zhi-Jiang Han4. 1. Department of Ultrasonic Imaging, The First Peoples Hospital of Hangzhou City, Hangzhou, China. 2. Department of Ultrasound Intervention, Zhejiang Xiaoshan Hospital, Hangzhou, China. 3. Department of Oncology Surgery, The First Peoples Hospital of Hangzhou City, Hangzhou, China. 4. Department of Radiology, The First Peoples Hospital of Hangzhou City, Hangzhou, China.
Abstract
PURPOSE: This study explored ultrasound grayscale ratios (USGRs) for differentiating markedly hypoechoic and anechoic minimal thyroid nodules. MATERIALS AND METHODS: Longitudinal scan images of 193 markedly hypoechoic papillary thyroid microcarcinoma (PTMC) lesions from 184 patients were retrospectively reviewed using RADinfo and compared with 123 anechoic micronodular goiters (MNGs) from 110 patients. Final diagnosis was validated by pathological examination; MNGs predominantly manifested with cyst formation. Grayscale values of PTMC, MNG, and normal surrounding tissues were obtained from grayscale histograms; USGRs (grayscale ratios of pathologic tissue to surrounding normal tissue) of PTMC and MNG were calculated. Optimal USGRs for differentiating PTMC and MNG were determined with receiver operating characteristic (ROC) curves. RESULTS: Among 193 PTMC and 123 MNG lesions, USGRs were 0.24-0.51 (mean ± standard deviation [SD]: 0.41 ± 0.07) and 0.01-0.38 (mean ± SD: 0.12 ± 0.08), respectively. The area under the ROC curve for distinguishing markedly hypoechoic PTMC and anechoic MNG was 0.992. As USGRs decreased, sensitivity decreased and specificity increased for MNG diagnosis. At a USGR of 0.26, the Youden index was high (0.933), corresponding to 94.3% sensitivity and 99% specificity for predicting anechoic MNG. At a USGR of 0.23, sensitivity and specificity for diagnosing anechoic MNG were 92.7% and 100%, respectively. In contrast, as USGR increased, sensitivity decreased and specificity increased for predicting PTMC. At a USGR of 0.38, sensitivity and specificity for diagnosing markedly hypoechoic PTMC were 68.4% and 100%, respectively. CONCLUSIONS: USGRs could objectively quantize grayscale values of markedly hypoechoic and anechoic lesions, enabling accurate and quantitative determination of nodular properties.
PURPOSE: This study explored ultrasound grayscale ratios (USGRs) for differentiating markedly hypoechoic and anechoic minimal thyroid nodules. MATERIALS AND METHODS: Longitudinal scan images of 193 markedly hypoechoic papillary thyroid microcarcinoma (PTMC) lesions from 184 patients were retrospectively reviewed using RADinfo and compared with 123 anechoic micronodular goiters (MNGs) from 110 patients. Final diagnosis was validated by pathological examination; MNGs predominantly manifested with cyst formation. Grayscale values of PTMC, MNG, and normal surrounding tissues were obtained from grayscale histograms; USGRs (grayscale ratios of pathologic tissue to surrounding normal tissue) of PTMC and MNG were calculated. Optimal USGRs for differentiating PTMC and MNG were determined with receiver operating characteristic (ROC) curves. RESULTS: Among 193 PTMC and 123 MNG lesions, USGRs were 0.24-0.51 (mean ± standard deviation [SD]: 0.41 ± 0.07) and 0.01-0.38 (mean ± SD: 0.12 ± 0.08), respectively. The area under the ROC curve for distinguishing markedly hypoechoic PTMC and anechoic MNG was 0.992. As USGRs decreased, sensitivity decreased and specificity increased for MNG diagnosis. At a USGR of 0.26, the Youden index was high (0.933), corresponding to 94.3% sensitivity and 99% specificity for predicting anechoic MNG. At a USGR of 0.23, sensitivity and specificity for diagnosing anechoic MNG were 92.7% and 100%, respectively. In contrast, as USGR increased, sensitivity decreased and specificity increased for predicting PTMC. At a USGR of 0.38, sensitivity and specificity for diagnosing markedly hypoechoic PTMC were 68.4% and 100%, respectively. CONCLUSIONS: USGRs could objectively quantize grayscale values of markedly hypoechoic and anechoic lesions, enabling accurate and quantitative determination of nodular properties.