Department of Radiology, University of Washington, Box 357115, 1959 NE Pacific St, Seattle, WA 98195-7115.
Department of Radiology, University of Colorado, Aurora, CO.
AJR Am J Roentgenol. 2020 Oct;215(4):896-902. doi: 10.2214/AJR.19.22531. Epub 2020 Aug 18.
The purpose of this study is to determine whether gaussian-based histogram analysis without and with noise correction can characterize indeterminate adrenal nodules (those with attenuation greater than 10 HU on unenhanced CT) as lipid-poor adenomas. This retrospective study evaluated adrenal nodules larger than 1 cm on unenhanced CT using gaussian analysis without and with noise correction on intralesional ROIs. Two independent readers who were blinded to the final diagnoses evaluated the nodules. The final diagnosis for each nodule was determined on the basis of pathologic findings or accepted imaging criteria. Interreader agreement was assessed using the intraclass correlation coefficient. Algorithm performance was summarized using sensitivity, specificity, and the AUC. Ninety-four adrenal nodules in 85 patients were analyzed; 36 of these were metastases (34 of which were pathologically confirmed), and 58 were presumed adenomas. Interreader agreement was excellent for nodule size, mean attenuation, SD of attenuation, and the gaussian index. Noise-corrected gaussian analysis had significantly higher specificity (81.9% vs 55.6%; < 0.001) and lower sensitivity (36.2% vs 56.9%; < 0.001) for identifying adenomas than did the uncorrected gaussian analysis. The AUC of corrected gaussian analysis was 0.72, which is significantly greater than that of uncorrected gaussian analysis (0.51; ≤ 0.001) and similar to that of mean attenuation (0.77). Noise correction is necessary when using a gaussian analysis characterization of indeterminate adrenal nodules on modern unenhanced CT examinations. This method may be able to discriminate between adenomas and nonadenomas.
本研究旨在确定基于高斯分布的直方图分析（包括未校正噪声和校正噪声两种方法）能否用于对 CT 平扫时衰减值大于 10HU 的不确定性质肾上腺结节（即那些密度不均的结节）进行分类，判断其为乏脂性腺瘤。本回顾性研究使用高斯分析方法，对 CT 平扫时直径大于 1cm 的肾上腺结节进行分析，在病灶内感兴趣区进行未校正噪声和校正噪声两种方法的分析。两名独立的阅片者在不了解最终诊断的情况下对这些结节进行评估。根据病理结果或公认的影像学标准确定每个结节的最终诊断。使用组内相关系数评估两位阅片者之间的一致性。使用敏感性、特异性和 AUC 对算法性能进行总结。共分析了 85 例患者的 94 个肾上腺结节，其中 36 个为转移瘤（34 个经病理证实），58 个为假定的腺瘤。结节大小、平均衰减值、衰减标准差和高斯指数的两位阅片者之间的一致性非常好。校正噪声后的高斯分析对腺瘤的特异性（81.9%比 55.6%； ＜0.001）显著高于未校正高斯分析，敏感性（36.2%比 56.9%； ＜0.001）显著低于未校正高斯分析。校正高斯分析的 AUC 为 0.72，明显大于未校正高斯分析（0.51； ≤ 0.001），与平均衰减值（0.77）相似。在对现代 CT 平扫检查中的不确定性质肾上腺结节进行高斯分析特征描述时，需要进行噪声校正。这种方法可能能够区分腺瘤和非腺瘤。
