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Background <p>Differentiating between parotid adenolymphoma and malignant tumors remains challenging.</p> Purpose <p>This study aims to improve preoperative diagnosis accuracy by evaluating the role of multimodal functional magnetic resonance imaging (MRI) and advanced radiomics analysis.</p> Methods <p>We retrospectively analyzed 124 patients with adenolymphoma and malignant parotid tumors, divided into primary (<i>n</i> = 84) and test (<i>n</i> = 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.</p> Results <p>The 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 (<i>p</i> &lt; 0.001). ADC histogram analysis revealed significant differences in mean, 10th percentile, and kurtosis values between the two groups.</p> Conclusions <p>The 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.</p>

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

  • 期刊论文

  • 发表日期：

    2025年5月13日

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

摘要

Background

Differentiating 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.

Methods

We 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.

Results

The 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.

Conclusions

The 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.