Evaluation of multiparametric MRI differentiating sinonasal angiomatous polyp from malignant tumors

Xinyan Wang1, Ying Liu2,3, Qinghua Chen1

  • 1Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China.

Neuroradiology
|May 24, 2019
PubMed
Abstract

Insights

Multiparametric MRI effectively differentiates sinonasal angiomatous polyps (SAPs) from malignant tumors. Progressive enhancement on dynamic contrast-enhanced MRI is a key indicator for SAPs, achieving 100% accuracy in this study.

Area of Science:

  • Radiology
  • Oncology
  • Pathology

Background:

  • Sinonasal angiomatous polyps (SAPs) can mimic malignant tumors due to aggressive behavior.
  • Accurate differentiation is crucial for appropriate patient management.

Purpose of the Study:

  • To assess the diagnostic accuracy of multiparametric MRI in distinguishing SAPs from malignant tumors.
  • To identify key MRI features differentiating these conditions.

Main Methods:

  • Retrospective analysis of 31 SAPs and 36 malignant tumors using 3T MRI.
  • Inclusion of conventional MRI, diffusion-weighted (DW) imaging, and dynamic contrast-enhanced (DCE) MRI.
  • Independent analysis of MR images by two authors.

Main Results:

  • Significant differences observed in T1 homogeneity, T2 signal intensity ratio, peripheral hypointense rim, and soft tissue infiltration.
  • SAPs typically exhibit heterogeneous T1, peripheral hypointense rim on T2WI, and higher T2 signal intensity ratio.
  • DCE-MRI revealed significant differences in parameters like Tpeak, CImax, WR, TIC types, and progressive enhancement, with 100% accuracy for progressive enhancement in SAPs.
  • Mean ADC values were significantly higher in SAPs compared to malignant tumors.

Conclusions:

  • Multiparametric MRI demonstrates high diagnostic performance for differentiating SAPs from malignant tumors.
  • Progressive enhancement on DCE-MRI is the most reliable feature for identifying SAPs.
  • Advanced MRI techniques are valuable tools in sinonasal lesion characterization.

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