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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Cancer Imaging and Image-directed Interventions
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1339671
This article is part of the Research Topic Artificial Intelligence and Imaging for Oncology View all 18 articles

Differentiation of pheochromocytoma and adrenal lipoid adenoma by radiomics: Are enhanced CT scanning images necessary?

Provisionally accepted
Shi he Liu Shi he Liu 1Pei Nie Pei Nie 1Shun li Liu Shun li Liu 1*Dapeng Hao Dapeng Hao 1Juntao Zhang Juntao Zhang 2Rui Sun Rui Sun 1*Zhi tao Yang Zhi tao Yang 1*Chuan yu Zhang Chuan yu Zhang 1*Qing Fu Qing Fu 1*
  • 1 The Affiliated Hospital of Qingdao University, Qingdao, China
  • 2 GE Healthcare,PDx GMS Advanced Analytics,China, Shanghai, China

The final, formatted version of the article will be published soon.

    Purpose: To establish various radiomics models based on conventional CT scan images and enhanced CT images, explore their value in the classification of pheochromocytoma (PHEO) and lipid-poor adrenal adenoma (LPA) and screen the most parsimonious and efficient model.The clinical and imaging data of 332 patients (352 lesions) with PHEO or LPA confirmed by surgical pathology in the Affiliated Hospital of Qingdao University were retrospectively analyzed. The region of interest (ROI) on conventional and enhanced CT images was delineated using ITK-SNAP software. Different radiomics signatures were constructed from the radiomics features extracted from conventional and enhanced CT images, and a radiomics score (Rad score) was calculated. A clinical model was established using demographic features and CT findings, while radiomics nomograms were established using multiple logistic regression analysis.The predictive efficiency of different models was evaluated using the area under curve (AUC) and receiver operating characteristic (ROC) curve. The Delong test was used to evaluate whether there were statistical differences in predictive efficiency between different models.The radiomics signature based on conventional CT images showed AUCs of 0.97 (training cohort, 95% CI: 0.95 ～ 1.00) and 0.97 (validation cohort, 95% CI: 0.92 ～ 1.00). The AUCs of the nomogram model based on conventional scan CT images and enhanced CT images in the training cohort and the validation cohort were 0.97 (95% CI: 0.95～ 1.00) and 0.97 (95% CI: 0.94～1.00) and 0.98 (95% CI: 0.97～1.00) and 0.97 (95% CI: 0.94 ～ 1.00), respectively. The prediction efficiency of models based on enhanced CT images was slightly higher than that of models based on conventional CT images, but these differences were statistically insignificant(P>0.05). Conclusions: CT-based radiomics signatures and radiomics nomograms can be used to predict and identify PHEO and LPA. The model established based on conventional CT images has great identification and prediction efficiency, and it can also enable patients to avoid harm from radiation and contrast agents caused by the need for further enhancement scanning in traditional image examinations.

    Keywords: Adrenal adenoma, Pheochromocytoma, CT, Radiomics, Classification

    Received: 16 Nov 2023; Accepted: 26 Aug 2024.

    Copyright: © 2024 Liu, Nie, Liu, Hao, Zhang, Sun, Yang, Zhang and Fu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Shun li Liu, The Affiliated Hospital of Qingdao University, Qingdao, China
    Rui Sun, The Affiliated Hospital of Qingdao University, Qingdao, China
    Zhi tao Yang, The Affiliated Hospital of Qingdao University, Qingdao, China
    Chuan yu Zhang, The Affiliated Hospital of Qingdao University, Qingdao, China
    Qing Fu, The Affiliated Hospital of Qingdao University, Qingdao, China

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