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CT 放射组学分析良性肾上腺偶发瘤是否提示需要进一步内分泌评估?

Could CT Radiomic Analysis of Benign Adrenal Incidentalomas Suggest the Need for Further Endocrinological Evaluation?

机构信息

Department of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.

Endocrinology Unit, Department of Medicine (DIMED), University of Padova, 35122 Padua, Italy.

出版信息

Curr Oncol. 2024 Aug 25;31(9):4917-4926. doi: 10.3390/curroncol31090364.

Abstract

We studied the application of CT texture analysis in adrenal incidentalomas with baseline characteristics of benignity that are highly suggestive of adenoma to find whether there is a correlation between the extracted features and clinical data. Patients with hormonal hypersecretion may require medical attention, even if it does not cause any symptoms. A total of 206 patients affected by adrenal incidentaloma were retrospectively enrolled and divided into non-functioning adrenal adenomas (NFAIs, n = 115) and mild autonomous cortisol secretion (MACS, n = 91). A total of 136 texture parameters were extracted in the unenhanced phase for each volume of interest (VOI). Random Forest was used in the training and validation cohorts to test the accuracy of CT textural features and cortisol-related comorbidities in identifying MACS patients. Twelve parameters were retained in the Random Forest radiomic model, and in the validation cohort, a high specificity (81%) and positive predictive value (74%) were achieved. Notably, if the clinical data were added to the model, the results did not differ. Radiomic analysis of adrenal incidentalomas, in unenhanced CT scans, could screen with a good specificity those patients who will need a further endocrinological evaluation for mild autonomous cortisol secretion, regardless of the clinical information about the cortisol-related comorbidities.

摘要

我们研究了 CT 纹理分析在具有高度提示腺瘤的良性基线特征的肾上腺偶发瘤中的应用,以发现提取的特征与临床数据之间是否存在相关性。即使没有引起任何症状,荷尔蒙分泌过多的患者可能需要医疗关注。共回顾性纳入 206 例肾上腺偶发瘤患者,分为无功能肾上腺腺瘤(NFAIs,n=115)和轻度自主皮质醇分泌(MACS,n=91)。对每个感兴趣区(VOI)的未增强相提取了总共 136 个纹理参数。随机森林(Random Forest)在训练和验证队列中用于测试 CT 纹理特征和皮质醇相关合并症在识别 MACS 患者中的准确性。随机森林放射组学模型中保留了 12 个参数,在验证队列中,获得了较高的特异性(81%)和阳性预测值(74%)。值得注意的是,如果将临床数据添加到模型中,结果并没有差异。在未增强 CT 扫描中,对肾上腺偶发瘤进行放射组学分析,可以特异性地筛选出那些需要进一步进行内分泌评估以确定轻度自主皮质醇分泌的患者,而无需考虑与皮质醇相关合并症的临床信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c21/11431504/dd972c44e507/curroncol-31-00364-g001.jpg

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