{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T02:47:42Z","timestamp":1784256462836,"version":"3.55.0"},"reference-count":46,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T00:00:00Z","timestamp":1748390400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development  Program","award":["2022YFC2409405"],"award-info":[{"award-number":["2022YFC2409405"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Objectives: Differentiation of adrenal incidentalomas (AIs) remains a challenge in the oncological setting. The aim of the study was to explore the diagnostic efficacy of [18F]Fluorodeoxyglucose (FDG) positron emission tomography combined with computed tomography (PET\/CT)-based radiomics in identifying adrenal metastases and to compare it with that of conventional PET\/CT parameters. Materials: Retrospective analysis was performed on 195 AIs for model construction, nomogram drawing, and internal validation. An additional 30 AIs were collected for external validation of the radiomics model and nomogram. Logistic regression analysis was employed to build models based on clinical and PET\/CT routine parameters. The open-source software Python (version 3.7.11) was utilized to process the regions of interest (ROI) delineated by ITK-SNAP, extracting radiomic features. Least absolute shrinkage and selection operator (LASSO) regression analysis was applied for feature selection. Based on the selected features, the optimal model was chosen from ten machine learning algorithms, and the nomogram was constructed. Results: The area under the curve (AUC), sensitivity, specificity, and accuracy of conventional parameters of PET\/CT were 0.919, 0.849, 0.892, and 0.844, respectively. XGBoost demonstrated superior diagnostic efficiency among the radiomics models, outperforming those constructed using independent predictors. The AUC, accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of XGBoost\u2019s internal and external validation were 0.945, 0.932, 0.930, 0.960, 0.970, 0.890 and 0.910, 0.900, 0.860, 1, 1, 0.750. The accuracy, sensitivity, specificity, PPV, and NPV of the nomogram in external validation were 0.870, 0.952, 0.667, 0.870, and 0.857. Conclusions: The radiomics model and conventional PET\/CT parameters both showed high diagnostic performance (AUC p &gt; 0.05) in discriminating adrenal metastases from benign lesions, offering a practical, non-invasive approach for clinical assessment.<\/jats:p>","DOI":"10.3390\/diagnostics15111356","type":"journal-article","created":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T10:21:13Z","timestamp":1748427673000},"page":"1356","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["The Value of PET\/CT-Based Radiomics in Predicting Adrenal Metastases in Patients with Cancer"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-1126-6140","authenticated-orcid":false,"given":"Qiujun","family":"He","sequence":"first","affiliation":[{"name":"Department of Nuclear Medicine, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangxing","family":"Kong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, Beijing Key Laboratory of Carcinogenesis and Translational Research, National Medical Products Administration (NMPA) Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing 100142, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6590-011X","authenticated-orcid":false,"given":"Xiangxi","family":"Meng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, Beijing Key Laboratory of Carcinogenesis and Translational Research, National Medical Products Administration (NMPA) Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing 100142, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiuling","family":"Shen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, Beijing Key Laboratory of Carcinogenesis and Translational Research, National Medical Products Administration (NMPA) Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing 100142, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nan","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, Beijing Key Laboratory of Carcinogenesis and Translational Research, National Medical Products Administration (NMPA) Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing 100142, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"G1","DOI":"10.1530\/EJE-16-0467","article-title":"Management of adrenal incidentalomas: European Society of Endocrinology Clinical Practice Guideline in collaboration with the European Network for the Study of Adrenal Tumor","volume":"175","author":"Fassnacht","year":"2016","journal-title":"Eur. J. Endocrinol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1542","DOI":"10.1056\/NEJMcp2031112","article-title":"Adrenal Incidentaloma","volume":"384","author":"Kebebew","year":"2021","journal-title":"N. Engl. J. Med."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"e30856","DOI":"10.1097\/MD.0000000000030856","article-title":"Radiomics approach based on biphasic CT images well differentiate \u201cearly stage\u201d of adrenal metastases from lipid-poor adenomas: A STARD Compliant Artice","volume":"101","author":"Cao","year":"2022","journal-title":"Medicine"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"775","DOI":"10.1210\/endrev\/bnaa008","article-title":"Adrenal incidentaloma","volume":"41","author":"Sherlock","year":"2020","journal-title":"Endocr. Rev."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1530\/EJE-10-1147","article-title":"AME Position Statement on adrenal incidentaloma","volume":"164","author":"Terzolo","year":"2011","journal-title":"Eur. J. Endocrinol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"298","DOI":"10.1007\/BF03344099","article-title":"Prevalence of adrenal incidentaloma in a contemporary computerized tomography series","volume":"29","author":"Bovio","year":"2006","journal-title":"J. Endocrinol. Investig."},{"key":"ref_7","first-page":"2013","article-title":"Adrenalectomy may increase survival of patients with adrenal metastases","volume":"11","author":"Zheng","year":"2021","journal-title":"Quant. Imaging Med. Surg."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Yuan, H., Kang, B., Sun, K., Qin, S., Ji, C., and Wang, X. (2023). CT-based radiomics nomogram for differentiation of adrenal hyperplasia from lipid-poor adenoma: An exploratory study. BMC Med. Imaging, 23.","DOI":"10.1186\/s12880-022-00951-x"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"e200011","DOI":"10.1148\/rycan.2020200011","article-title":"Utility of T2-weighted MRI to Differentiate Adrenal Metastases from Lipid-Poor Adrenal Adenomas","volume":"2","author":"Tu","year":"2020","journal-title":"Radiol. Imaging Cancer"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1590\/0100-3984.2019.0095","article-title":"The value of signal intensity on T1-weighted chemical shift magnetic resonance imaging combined with proton magnetic resonance spectroscopy for the diagnosis of adrenal adenomas","volume":"53","author":"Dalavia","year":"2020","journal-title":"Radiol. Bras."},{"key":"ref_11","unstructured":"Cingam, S.R., Mukkamalla, S.K.R., and Karanchi, H. (2023). Adrenal Metastasis. StatPearls [Internet], StatPearls Publishing."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.rcl.2012.02.009","article-title":"Adrenal imaging: A comprehensive review","volume":"50","author":"Taffel","year":"2012","journal-title":"Radiol. Clin. N. Am."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1148\/radiol.2223010766","article-title":"Adrenal masses: Characterization with combined unenhanced and delayed enhanced CT","volume":"22","author":"Caoili","year":"2002","journal-title":"Radiology"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1206","DOI":"10.2214\/AJR.16.17758","article-title":"Update on CT and MRI of Adrenal Nodules","volume":"208","author":"Schieda","year":"2017","journal-title":"Am. J. Roentgenol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2756","DOI":"10.1245\/s10434-020-09329-1","article-title":"A critical analysis of computed tomography washout in lipid-poor adrenal incidentalomas","volume":"28","author":"Akbulut","year":"2021","journal-title":"Ann. Surg. Oncol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2013","DOI":"10.21037\/qims-20-875","article-title":"Role of 18F-FDG PET\/CT in the differential diagnosis of primary benign and malignant unilateral adrenal tumors","volume":"11","author":"Ma","year":"2021","journal-title":"Quant. Imaging Med. Surg."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.canlet.2020.03.032","article-title":"Machine Learning in oncology: A clinical appraisal","volume":"481","author":"Cuocolo","year":"2020","journal-title":"Cancer Lett."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.mri.2021.03.009","article-title":"Handcrafted MRI radiomics and machine learning: Classification of indeterminate solid adrenal lesions","volume":"79","author":"Stanzione","year":"2021","journal-title":"Magn. Reson. Imaging"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Zerunian, M., Laghi, A., and Caruso, D. (2023). Radiomics in Oncology III. Diagnostics, 13.","DOI":"10.3390\/diagnostics13010149"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Ismail, M., Craig, S., Ahmed, R., de Blank, P., and Tiwari, P. (2023). Opportunities and Advances in Radiomics and Radiogenomics for Pediatric Medulloblastoma Tumors. Diagnostics, 13.","DOI":"10.3390\/diagnostics13172727"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Zhang, H., Meng, X., Wang, Z., Zhou, X., Liu, Y., and Li, N. (2025). Predicting PD-L1 in Lung Adenocarcinoma Using 18F-FDG PET\/CT Radiomic Features. Diagnostics, 15.","DOI":"10.3390\/diagnostics15050543"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"208","DOI":"10.5152\/dir.2022.21691","article-title":"Differentiation of adrenal adenomas from adrenal metastases in single-phased staging dual-energy CT and radiomics","volume":"28","author":"Winkelmann","year":"2022","journal-title":"Diagn. Interv. Radiol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"e711","DOI":"10.1016\/j.crad.2022.06.015","article-title":"Can radiomic feature analysis differentiate adrenal metastases from lipid-poor adenomas on single-phase contrast-enhanced CT abdomen?","volume":"77","author":"Shea","year":"2022","journal-title":"Clin. Radiol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.ejca.2008.10.026","article-title":"New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)","volume":"45","author":"Eisenhauer","year":"2009","journal-title":"Eur. J. Cancer"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Chen, J., He, Y., Zeng, X., Zhu, S., and Li, F. (2022). Distinguishing between metastatic and benign adrenal masses in patients with extra-adrenal malignancies. Front. Endocrinol., 13.","DOI":"10.3389\/fendo.2022.978730"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"213875","DOI":"10.1155\/2015\/213875","article-title":"Value of 18-F-FDG PET\/CT and CT in the Diagnosis of Indeterminate Adrenal Masses","volume":"2015","author":"Launay","year":"2015","journal-title":"Int. J. Endocrinol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2273","DOI":"10.1007\/s00259-014-2844-1","article-title":"What parameters from 18F-FDG PET\/CT are useful in evaluation of adrenal lesions?","volume":"41","author":"Kunikowska","year":"2014","journal-title":"Eur. J. Nucl. Med. Mol. Imaging"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"147","DOI":"10.3803\/EnM.2016.31.1.147","article-title":"Radiographic Characteristics of Adrenal Masses in Oncologic Patients","volume":"31","author":"Lee","year":"2016","journal-title":"Endocrinol. Metab."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1097\/SLA.0000000000003876","article-title":"Adrenalectomy for Secondary Malignancy: Patients, Outcomes, and Indications","volume":"274","author":"Wachtel","year":"2021","journal-title":"Ann. Surg."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1177\/107327481101800206","article-title":"Management of isolated Adrenal Lesions in Cancer Patients","volume":"18","author":"McLean","year":"2011","journal-title":"Cancer Control"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.jasc.2020.08.004","article-title":"Adrenal gland fine needle aspiration: A multi-institutional analysis of 139 cases","volume":"10","author":"Alwelaie","year":"2021","journal-title":"J. Am. Soc. Cytopathol."},{"key":"ref_32","first-page":"117","article-title":"Characterization of adrenal masses by using FDG PET: A systematic review and meta-analysis of diagnostic test performance","volume":"259","author":"Boland","year":"2011","journal-title":"Radiolog"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1271","DOI":"10.1002\/jso.25272","article-title":"Predictive factors for adrenal metastasis in extra-adrenal malignancy patients with solitary adrenal mass","volume":"118","author":"Byeon","year":"2018","journal-title":"J. Surg. Oncol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"8","DOI":"10.5334\/aogh.2419","article-title":"Global Epidemiology of Lung Cancer","volume":"85","author":"Barta","year":"2019","journal-title":"Ann. Glob. Health"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"109874","DOI":"10.1016\/j.ejrad.2021.109874","article-title":"Radiomics and functional imaging in lung cancer: The importance of radiological heterogeneity beyond FDG PET\/CT and lung biopsy","volume":"142","author":"Caruso","year":"2021","journal-title":"Eur. J. Radiol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2770","DOI":"10.1007\/s00259-019-04418-0","article-title":"Integrating manual diagnosis into radiomics for reducing the false positive rate of 18 F-FDG PET\/CT diagnosis in patients with suspected lung cancer","volume":"46","author":"Kang","year":"2019","journal-title":"Eur. J. Nucl. Med. Mol. Imaging"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1364","DOI":"10.1200\/JCO.2007.12.9791","article-title":"How to build and interpret a nomogram for cancer prognosis","volume":"26","author":"Iasonos","year":"2008","journal-title":"J. Clin. Oncolgy"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"e173","DOI":"10.1016\/S1470-2045(14)71116-7","article-title":"Nomograms in oncology: More than meets the eye","volume":"16","author":"Balachandran","year":"2015","journal-title":"Lancet Oncol."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Liu, C., Zhao, W., Xie, J., Lin, H., Hu, X., Li, C., Shang, Y., Wang, Y., Jiang, Y., and Ding, M. (2023). Development and validation of a radiomics-based nomogram for predicting a major pathological response to neoadjuvant immunochemotherapy for patients with potentially resectable non-small cell lung cancer. Front. Immunol., 14.","DOI":"10.3389\/fimmu.2023.1115291"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"e29068","DOI":"10.1097\/MD.0000000000029068","article-title":"Construction and validation of a robust ferroptosis-associated gene signature predictive of prognosis in lung adenocarcinoma","volume":"101","author":"Zhou","year":"2022","journal-title":"Medicine"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1093\/ajcp\/aqac041","article-title":"Tumor-Infiltrating Lymphocytes Improve Magee Equation-Based Prediction of Pathologic Complete Response in HR-Positive\/HER2-Negative Breast Cancer","volume":"158","author":"Li","year":"2022","journal-title":"Am. J. Clin. Pathol."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Zhang, W., Ji, L., Wang, X., Zhu, S., Luo, J., Zhang, Y., Tong, Y., Feng, F., Kang, Y., and Bi, Q. (2022). Nomogram Predicts Risk and Prognostic Factors for Bone Metastasis of Pancreatic Cancer: A Population-Based Analysis. Front. Endocrinol., 12.","DOI":"10.3389\/fendo.2021.752176"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Yu, C., and Zhang, Y. (2020). Establishment of prognostic nomogram for elderly colorectal cancer patients: A SEER database analysis. BMC Gastroenterol., 20.","DOI":"10.1186\/s12876-020-01464-z"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1186\/s12957-021-02445-6","article-title":"A nomogram model for predicting prognosis of obstructive colorectal cancer","volume":"19","author":"Lv","year":"2021","journal-title":"World J. Surg. Oncol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"916","DOI":"10.1111\/bju.14503","article-title":"A novel nomogram for predicting ECE of prostate cancer","volume":"122","author":"Rocco","year":"2018","journal-title":"Bju Int."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"820","DOI":"10.1007\/s10278-021-00498-3","article-title":"Effects of Interobserver Variability on 2D and 3D CT- and MRI-Based Texture Feature Reproducibility of Cartilaginous Bone Tumors","volume":"34","author":"Gitto","year":"2021","journal-title":"J. Digit. Imaging"}],"container-title":["Diagnostics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-4418\/15\/11\/1356\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:42:19Z","timestamp":1760031739000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-4418\/15\/11\/1356"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,28]]},"references-count":46,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2025,6]]}},"alternative-id":["diagnostics15111356"],"URL":"https:\/\/doi.org\/10.3390\/diagnostics15111356","relation":{},"ISSN":["2075-4418"],"issn-type":[{"value":"2075-4418","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,28]]}}}