Takuya Yagi1, Motohiko Yamazaki2, Riuko Ohashi3, Rei Ogawa1, Hiroyuki Ishikawa1, Norihiko Yoshimura1, Masanori Tsuchida4, Yoichi Ajioka5, Hidefumi Aoyama1. 1. Department of Radiology and Radiation Oncology, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-dori, Chuo-ku, Niigata, 951-8510, Japan. 2. Department of Radiology and Radiation Oncology, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-dori, Chuo-ku, Niigata, 951-8510, Japan. xackey2001@gmail.com. 3. Histopathology Core Facility, Niigata University Faculty of Medicine, Niigata, Japan. 4. Division of Thoracic and Cardiovascular Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan. 5. Division of Molecular and Diagnostic Pathology, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan.
Abstract
PURPOSE: To distinguish between adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) showing pure or part-solid ground-glass nodules (GGNs) by high-resolution computed tomography (HRCT) texture analysis. MATERIALS AND METHODS: This retrospective study included 101 consecutive patients with 115 pure or part-solid GGNs ≤ 3 cm diameter, which were surgically resected and pathologically diagnosed with AIS, MIA, or IAC (48 AIS-MIA and 67 IAC) between April 2011 and March 2015. Each tumor was manually segmented on axial CT images, and the following texture features were calculated: volume, mass, mean CT value, variance, skewness, kurtosis, entropy, uniformity, and percentile CT numbers (10th, 25th, 50th, 75th, 90th, 95th percentiles). The differences between AIS-MIA and IAC were statistically evaluated using univariate, multivariate, and receiver operating characteristic analysis. RESULTS: Compared with IAC, AIS-MIA had significantly greater skewness, kurtosis, and uniformity, whereas in the other parameters, AIS-MIA demonstrated significantly lower values than those of IAC. Multivariate analysis revealed that independent differentiators were the 90th percentile CT numbers (P < 0.001) and entropy (P = 0.005) with an excellent accuracy (area under the curve, 0.90). CONCLUSIONS: The 90th percentile CT numbers and entropy can accurately distinguish AIS-MIA from IAC.
PURPOSE: To distinguish between adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) showing pure or part-solid ground-glass nodules (GGNs) by high-resolution computed tomography (HRCT) texture analysis. MATERIALS AND METHODS: This retrospective study included 101 consecutive patients with 115 pure or part-solid GGNs ≤ 3 cm diameter, which were surgically resected and pathologically diagnosed with AIS, MIA, or IAC (48 AIS-MIA and 67 IAC) between April 2011 and March 2015. Each tumor was manually segmented on axial CT images, and the following texture features were calculated: volume, mass, mean CT value, variance, skewness, kurtosis, entropy, uniformity, and percentile CT numbers (10th, 25th, 50th, 75th, 90th, 95th percentiles). The differences between AIS-MIA and IAC were statistically evaluated using univariate, multivariate, and receiver operating characteristic analysis. RESULTS: Compared with IAC, AIS-MIA had significantly greater skewness, kurtosis, and uniformity, whereas in the other parameters, AIS-MIA demonstrated significantly lower values than those of IAC. Multivariate analysis revealed that independent differentiators were the 90th percentile CT numbers (P < 0.001) and entropy (P = 0.005) with an excellent accuracy (area under the curve, 0.90). CONCLUSIONS: The 90th percentile CT numbers and entropy can accurately distinguish AIS-MIA from IAC.
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