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已发表论文
基于 CT 成像的肾上腺腺瘤影像组学模型用于评估骨量变化的机会性筛查
Authors Jia C, Jiang L, Zhang Y, Yang T, Su D, Song M, Yang H, Qin J, Li C, Yang H
Received 19 June 2025
Accepted for publication 31 October 2025
Published 15 November 2025 Volume 2025:17 Pages 539—552
DOI https://doi.org/10.2147/ORR.S548365
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Professor Clark Hung
Cheng Jia,1,* Ling Jiang,2,* Yue Zhang,1 Tiantian Yang,3 Datian Su,1 Mingxin Song,1 Heqi Yang,1 Jian Qin,1 Changqin Li,1 Hui Yang1
1Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, Shandong, People’s Republic of China; 2Department of Medical Engineering, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, Shandong, People’s Republic of China; 3Department of Radiology, Central Hospital Affiliated to Shandong First Medical University University, Ji’nan, Shandong, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Hui Yang, Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, Shandong, People’s Republic of China, Tel +86 15550826993, Email yhty1129@126.com
Purpose: There was a strong correlation between adrenal adenoma and osteoporosis, the primary objective of this research was to establish and authenticate a radiomics nomogram using CT scan of adrenal adenoma to screen abnormal bone mineral density (BMD) opportunistically.
Methods and Materials: A total of 161 patients with adrenal adenomas who underwent thoracoabdominal CT and quantitative CT (QCT) were enrolled retrospectively. The radiomics features were chosen from the cross-sectional CT images of adrenal adenomas and the nomogram models that including patient’s clinical and radiomics features were then established. The receiver operating characteristic (ROC) curve was performed to evaluate the performance of the model and the decision curve analysis (DCA) was used to assess the clinical usefulness.
Results: To build a radiomics model, 11 radiomics features based on CT scans of adrenal adenomas were selected and showed good performance in distinguishing abnormal BMD from normal BMD. Moreover, the radiomics nomogram model demonstrated excellent ability to identify abnormal BMD of adrenal adenoma patients with area under the curve (AUC) of 0.87 (95% CI, 0.80– 0.93) in training cohort and 0.85 (95% CI, 0.74– 0.96) in validation cohort. The accuracy, sensitivity, specificity of the nomogram model were 79.7%, 78.3%, 81.1% in training cohort, and 72.9%, 67.7%, 82.4% in validation cohort respectively.
Conclusion: The radiomics nomogram based on clinical and radiomics features of adrenal adenoma CT images had a satisfying predictive ability and can be an opportunistic effective tool for identifying bone mass change.
Keywords: osteoporosis, adrenal adenoma, QCT, radiomics, nomogram
1Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, Shandong, People’s Republic of China; 2Department of Medical Engineering, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, Shandong, People’s Republic of China; 3Department of Radiology, Central Hospital Affiliated to Shandong First Medical University University, Ji’nan, Shandong, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Hui Yang, Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, Shandong, People’s Republic of China, Tel +86 15550826993, Email yhty1129@126.com
Purpose: There was a strong correlation between adrenal adenoma and osteoporosis, the primary objective of this research was to establish and authenticate a radiomics nomogram using CT scan of adrenal adenoma to screen abnormal bone mineral density (BMD) opportunistically.
Methods and Materials: A total of 161 patients with adrenal adenomas who underwent thoracoabdominal CT and quantitative CT (QCT) were enrolled retrospectively. The radiomics features were chosen from the cross-sectional CT images of adrenal adenomas and the nomogram models that including patient’s clinical and radiomics features were then established. The receiver operating characteristic (ROC) curve was performed to evaluate the performance of the model and the decision curve analysis (DCA) was used to assess the clinical usefulness.
Results: To build a radiomics model, 11 radiomics features based on CT scans of adrenal adenomas were selected and showed good performance in distinguishing abnormal BMD from normal BMD. Moreover, the radiomics nomogram model demonstrated excellent ability to identify abnormal BMD of adrenal adenoma patients with area under the curve (AUC) of 0.87 (95% CI, 0.80– 0.93) in training cohort and 0.85 (95% CI, 0.74– 0.96) in validation cohort. The accuracy, sensitivity, specificity of the nomogram model were 79.7%, 78.3%, 81.1% in training cohort, and 72.9%, 67.7%, 82.4% in validation cohort respectively.
Conclusion: The radiomics nomogram based on clinical and radiomics features of adrenal adenoma CT images had a satisfying predictive ability and can be an opportunistic effective tool for identifying bone mass change.
Keywords: osteoporosis, adrenal adenoma, QCT, radiomics, nomogram