Computer-aided differentiation of malignant from benign solitary pulmonary nodules imaged by high-resolution CT

✍ Scribed by Shingo Iwano; Tatsuya Nakamura; Yuko Kamioka; Mitsuru Ikeda; Takeo Ishigaki

• Publisher: Elsevier Science
• Year: 2008
• Tongue: English
• Weight: 864 KB
• Volume: 32
• Category: Article
• ISSN: 0895-6111
• DOI: 10.1016/j.compmedimag.2008.04.001

✦ Synopsis

We investigated the possibility of using computer analysis of high-resolution CT images to radiologically classify the shape of pulmonary nodules. From a total of 107 HRCT images of solid, solitary pulmonary nodules with prior differentiation as benign (n = 55) or malignant (n = 52), we extracted the desired pulmonary nodules and calculated two quantitative parameters for characterizing nodules: circularity and second central moment. Using discriminant analysis for two thresholds in differentiating malignant from benign states resulted in a sensitivity of 76.9%, a specificity of 80%, a positive predictive value of 78.4%, and a negative predictive value of 78.6%.