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ArticleAnnals of surgical oncology2025

Differentiation Between Parotid Adenolymphoma and Malignant Tumor Based on Multimodal Functional MRI of Radiomics and Intratumoral Vascular ITSS Classification.

Baoting Yu, Chencui Huang, Xiaofei Fan, Dongyao Liu, Yuting Zhang, Jun Ding

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Article in Annals of surgical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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6 authors.

Baoting YuDepartment of Radiology, China-Japan Union Hospital of Jilin University, Changchun, China.
Chencui HuangDepartment of Research Collaboration, R&D Center, Beijing Deepwise and League of PHD Technology Co., Ltd, Beijing, China.
Xiaofei FanDepartment of Radiology, China-Japan Union Hospital of Jilin University, Changchun, China.
Dongyao LiuDepartment of Radiology, China-Japan Union Hospital of Jilin University, Changchun, China.
Yuting ZhangDepartment of Radiology, China-Japan Union Hospital of Jilin University, Changchun, China.
Jun DingDepartment of Radiology, China-Japan Union Hospital of Jilin University, Changchun, China. dingjun@jlu.edu.cn.

Funding

Department of Education Project of Jilin Province in 2020 JJKH20201057KJ
6 · The paper itself

Abstract

backgroundDifferentiating between parotid adenolymphoma and malignant tumors remains challenging. PURPOSE: This study aims to improve preoperative diagnosis accuracy by evaluating the role of multimodal functional magnetic resonance imaging (MRI) and advanced radiomics analysis.

methodsWe retrospectively analyzed 124 patients with adenolymphoma and malignant parotid tumors, divided into primary (n = 84) and test (n = 40) cohorts. Tumor regions were manually labeled on susceptibility-weighted imaging (SWI), diffusion-weighted imaging (DWI), and contrast-enhanced T1-weighted imaging (CE-T1WI). Seven radiomics models were constructed using logistic regression. We also incorporated intratumoral susceptibility signal (ITSS) grading and performed histogram analysis of apparent diffusion coefficient (ADC) maps.

resultsThe united radiomics model combining SWI, DWI, and CE-T1WI showed the highest diagnostic performance (area under the curve (AUC) = 0.95, accuracy = 0.93, specificity = 0.93) in the primary cohort, outperforming single-sequence and double-sequence models. The test set validated the model's good diagnostic performance (AUC = 0.9). ITSS grading significantly differed between adenolymphomas and malignant tumors (p < 0.001). ADC histogram analysis revealed significant differences in mean, 10th percentile, and kurtosis values between the two groups.

conclusionsThe multisequence radiomics model combining DWI, SWI, and CE-T1WI provides a comprehensive and accurate noninvasive approach for differentiating parotid adenolymphoma from malignant tumors. This method helps avoid the risks associated with invasive procedures, such as tumor cell implantation and metastasis, while guiding personalized surgical decision-making. By offering a novel diagnostic tool, this study enhances the precision of preoperative tumor characterization and supports more effective treatment planning and prognosis assessment for patients with parotid gland tumors.

Indexed as

AdenolymphomaDiffusion Magnetic Resonance ImagingMagnetic Resonance ImagingMultimodal ImagingParotid NeoplasmsAdultAgedDiagnosis, DifferentialFemaleFollow-Up StudiesHumansMaleMiddle AgedPrognosisRadiomicsRetrospective StudiesIntratumor susceptibility signal intensity (ITSS)Magnetic resonance imagingMalignant tumorParotid adenolymphomaRadiomics

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.