The Journal of Practical Medicine >
Value of conventional radiological features and ct radiomics features in differentiating parotid adenolymphoma from malignant tumors
Received date: 2025-07-30
Online published: 2025-11-13
Objective To investigate the value of conventional radiological features and CT radiomics features to differentiate parotid adenolymphoma from malignant tumor. Methods Radiological data from 128 patients with adenolymphoma and 39 patients with parotid malignancy were collected between December 2018 and October 2023. Radiomics features were extracted to obtain Rad?score and construct a radiomics model. Conventional radiological features were analyzed to obtain independent predictors， and a conventional radiological model was constructed. Model performance was compared by the DeLong test， and the Rad?score was combined with radiological features to establish a comprehensive model and plot a nomogram. Results Based on CT venous phase images， 9 optimal radiomic features were selected. Conventional radiological features were analyzed by univariate and multivariate logistic regression analysis and found that shape and degree of enhancement were independent predictors of adenolymphoma and malignant parotid tumors. The CT radiomics model is superior to the conventional radiological model（P < 0.05）. The area under the curve （AUC） of the radiomics model was 0.938 （95% CI： 0.887 ~ 0.988）， and the specificity and sensitivity were 0.856 and 0.923， respectively. Conventional radiological features and Rad?score were analyzed by univariate and multivariate logistic regression analysis and found that Rad?score and degree of enhancement were independent predictors of adenolymphoma and malignant parotid tumors. The difference between the diagnostic efficacy of the comprehensive model created by the Rad?score combined with the degree of enhancement and the diagnostic efficacy of the radiomics model was not statistically significant （P > 0.05）. Conclusion The CT radiomics model performed better than the conventional radiological model in discriminating parotid gland adenolymphoma from malignant tumors. The diagnostic performance of the comprehensive model has improved， aiding in clinical decision?making.
Key words： parotid gland; adenolymphoma; malignant tumor; radiomics
Guoliang WEN , Hang FANG , Wei. ZHANG . Value of conventional radiological features and ct radiomics features in differentiating parotid adenolymphoma from malignant tumors[J]. The Journal of Practical Medicine, 2025 , 41(21) : 3442 -3448 . DOI: 10.3969/j.issn.1006-5725.2025.21.021
| [1] | LIU S， YU B， ZHENG X， et al. Construction and Application of a Nomogram for Predicting Benign and Malignant Parotid Tumors［J］. J Comput Assist Tomogr，2024，48（1）：143-149. doi:10.1097/rct.0000000000001522 |
| [2] | QUER M， HERNANDEZ-PRERA J C， SILVER C E， et al. Current Trends and Controversies in the Management of Warthin Tumor of the Parotid Gland［J］. Diagnostics （Basel），2021，11（8）：1467. doi:10.3390/diagnostics11081467 |
| [3] | 陈飞，王利伟，布静秋. 腮腺沃辛瘤555例临床分析［J］. 北京口腔医学，2022，30（4）：284-286. |
| [4] | DI SANTO D， DERETTI A， VANDER POORTEN V. Current surgical management of malignant parotid tumors［J］. Curr Opin Otolaryngol Head Neck Surg，2025，33（2）：79-84. doi:10.1097/moo.0000000000001039 |
| [5] | GEIGER J L， ISMAILA N， BEADLE B， et al. Management of Salivary Gland Malignancy： ASCO Guideline［J］. J Clin Oncol，2021，39（17）：1909-1941. doi:10.1200/jco.21.00449 |
| [6] | ESPINOZA S， FELTER A， MALINVAUD D， et al. Warthin's tumor of parotid gland： Surgery or follow-up？ Diagnostic value of a decisional algorithm with functional MRI［J］. Diagn Interv Imaging，2016，97（1）：37-43. doi:10.1016/j.diii.2014.11.024 |
| [7] | CENGIZ A B， TANSUKER H D， GUL R， et al. Comparison of preoperative diagnostic accuracy of fine needle aspiration and core needle biopsy in parotid gland neoplasms［J］. Eur Arch Otorhinolaryngol，2021，278（10）：4067-4074. doi:10.1007/s00405-021-07022-x |
| [8] | LAMBIN P， RIOS-VELAZQUEZ E， LEIJENAAR R， et al. Radiomics： Extracting more information from medical images using advanced feature analysis［J］. Eur J Cancer，2012，48（4）：441-446. doi:10.1016/j.ejca.2011.11.036 |
| [9] | 何尚鹏，黄炜贤，江燕辉，等. 超声特征与超声影像组学对Bethesda Ⅲ类甲状腺结节良恶性再评价的价值［J］. 实用医学杂志，2025，41（12）：1892-1898. |
| [10] | YE J， CHEN Y， PAN J， et al. US-based Radiomics Analysis of Different Machine Learning Models for Differentiating Benign and Malignant BI-RADS 4A Breast Lesions［J］. Acad Radiol，2025，32（1）：67-78. doi:10.1016/j.acra.2024.08.024 |
| [11] | 黄忠江，姜增誉，李健丁，等. 基于增强CT影像组学联合机器学习鉴别均质性肾透明细胞癌与肾乏脂肪血管平滑肌脂肪瘤［J］. 实用医学杂志，2021，37（17）：2266-2270. doi:10.3969/j.issn.1006-5725.2021.17.020 |
| [12] | CHEN F， GE Y， LI S， et al. Enhanced CT-based texture analysis and radiomics score for differentiation of pleomorphic adenoma， basal cell adenoma， and Warthin tumor of the parotid gland［J］. Dentomaxillofac Radiol，2023，52（2）：20220009. doi:10.1259/dmfr.20220009 |
| [13] | HU Z， GUO J， FENG J， et al. Value of T2-weighted-based radiomics model in distinguishing Warthin tumor from pleomorphic adenoma of the parotid［J］. Eur Radiol，2023，33（6）：4453-4463. doi:10.1007/s00330-022-09295-0 |
| [14] | FISHER R， RONEN O. Cytologic diagnosis of parotid gland Warthin tumor： Systematic review and meta-analysis［J］. Head Neck，2022，44（10）：2277-2287. doi:10.1002/hed.27099 |
| [15] | 王张嵩，谢舒乐，张汉卿，等. 2456例唾液腺肿瘤临床病理分析［J］. 口腔疾病防治，2020，28（5）：298-302. |
| [16] | LEE D H， JUNG E K， LEE J K， et al. Comparative analysis of benign and malignant parotid gland tumors： A retrospective study of 992 patients［J］. Am J Otolaryngol，2023，44（2）：103690. doi:10.1016/j.amjoto.2022.103690 |
| [17] | 张亮，张莉，刘华，等. 312例腮腺区肿瘤临床回顾性分析［J］. 临床口腔医学杂志，2022，38（9）：534-537. |
| [18] | YU H， CALDWELL C， MAH K， et al. Automated radiation targeting in head-and-neck cancer using region-based texture analysis of PET and CT images［J］. Int J Radiat Oncol Biol Phys，2009，75（2）：618-625. doi:10.1016/j.ijrobp.2009.04.043 |
| [19] | LIU Y， ZHENG J， LU X， et al. Radiomics-based comparison of MRI and CT for differentiating pleomorphic adenomas and Warthin tumors of the parotid gland： A retrospective study［J］. Oral Surg Oral Med Oral Pathol Oral Radiol，2021，131（5）：591-599. doi:10.1016/j.oooo.2021.01.014 |
| [20] | ZHENG Y， ZHOU D， LIU H， et al. CT-based radiomics analysis of different machine learning models for differentiating benign and malignant parotid tumors［J］. Eur Radiol，2022，32（10）：6953-6964. doi:10.1007/s00330-022-08830-3 |
| [21] | LI Q， JIANG T， ZHANG C， et al. A nomogram based on clinical information， conventional ultrasound and radiomics improves prediction of malignant parotid gland lesions［J］. Cancer Lett，2022，527：107-114. doi:10.1016/j.canlet.2021.12.015 |
| [22] | MUNTEAN D D， DUDEA S M， B?CIU? M， et al. The Role of an MRI-Based Radiomic Signature in Predicting Malignancy of Parotid Gland Tumors［J］. Cancers （Basel），2023，15（13）：3319. doi:10.3390/cancers15133319 |
| [23] | ZHAO F， HUANG X， HE J， et al. A nomogram for distinguishing benign and malignant parotid gland tumors using clinical data and preoperative blood markers： Development and validation［J］. J Cancer Res Clin Oncol，2023，149（13）：11719-11733. doi:10.1007/s00432-023-05032-2 |
| [24] | 陈函，陈贤明，王茂鑫，等. 外周血中性粒细胞/淋巴细胞比值在腮腺恶性肿瘤诊断中的价值［J］. 中国耳鼻咽喉头颈外科，2021，28（7）：419-422. |
| [25] | 秦硕，李冉，李春梅，等. 术前外周血炎症指标在腮腺恶性肿瘤中的诊断及预后价值分析［J］. 口腔颌面外科杂志，2022，32（6）：362-367. |
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