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A multiparametric analysis based on DCE-MRI to improve the accuracy of parotid tumor discrimination

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European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

A Correction to this article was published on 04 February 2020

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Abstract

Background

Recently, semiquantitative time-intensity curve (TIC) analysis based on DCE-MRI and apparent diffusion coefficient (ADC) value-based diffusion-weighted imaging (DWI) were used to improve the diagnostic efficiency when diagnosing parotid tumors (PTs). However, quantitative DCE-MRI biomarkers have not been emphasized previously.

Purpose

To explore the diagnostic efficiency of perfusion parameters alone or in combination based on quantitative DCE-MRI and DWI in the differential diagnosis of PTs.

Methods

In total, 112 patients with parotid masses were prospectively recruited in our hospital from August 2013 to March 2017. All patients were evaluated with DCE-MRI and DWI before surgery. TIC and quantitative parameters based on DCE MRI and ADCs were analyzed. Receiver operating characteristic analysis and linear discriminant analysis (LDA) was used to determine their diagnostic performance.

Results

In total, 87% (27/31) of pleomorphic adenoma (PA) showed type A TIC, 74% (65/88) of Warthin’s tumors showed type B TIC, and 95% (19/20) of malignant tumors showed TIC type C. Pearson X2 test showed a significant difference between TIC patterns in benign and malignant tumors (X2 = 38.78, p < 0.001). ROC analysis revealed that ADC achieved the best diagnostic performance for distinguishing PA and Warthin’s tumor from others, with area under the curve (AUC) values of 0.945 and 0.925 (p < 0.01), respectively. Furthermore, the TIC type was the only useful biomarker for distinguishing malignant from benign PTs, with an AUC of 0.846 (p < 0.01). Concerning the accuracy of the combined application of multiple parameters of DCE-MRI and ADC values, a combination of TIC pattern and extracellular volume ratio (Ve) provided the best results among five protocols, producing the highest accuracy of 0.75, followed by the combined use of the TIC pattern and ADC (accuracy was 0.70).

Conclusion

TIC pattern in combination with the Ve biomarker based on DCE-MRI could achieve optimal diagnostic accuracy in the differential diagnosis of PTs.

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Change history

  • 04 February 2020

    Figure captions of Figures 2, 3, and 4 were incorrect in the original version of this article.

  • 04 February 2020

    Figure captions of Figures��2, 3, and 4 were incorrect in the original version of this article.

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Acknowledgments

The authors thank Jin-Yabin from the First People’s Hospital of Foshan for the help in figure editing.

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Authors and Affiliations

  1. Department of Radiology, The First People’s Hospital of Foshan, Foshan, Guangdong, China

    Zhifeng Xu, Aizhen Pan & Mingyong Gao

  2. Department of MR, Shantou Central Hospital, Shantou, Guangdong, China

    Shaoyan Zheng

  3. Department of Radiology, Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou, People’s Republic of China

    Xiaofang Cheng

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  1. Zhifeng Xu
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  2. Shaoyan Zheng
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  3. Aizhen Pan
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Correspondence to Zhifeng Xu.

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The authors declare that they have no conflict of interest.

Ethical approval

This prospective study was approved by the institutional review board (Ethics committee of Foshan First People’s Hospital and Ethics Committee of Shantou Central Hospital) and performed between August 2013 and March 2017. Informed consent was obtained from all individual participants included in the study.

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This article is part of the Topical Collection on Oncology—Head and Neck

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Xu, Z., Zheng, S., Pan, A. et al. A multiparametric analysis based on DCE-MRI to improve the accuracy of parotid tumor discrimination. Eur J Nucl Med Mol Imaging 46, 2228–2234 (2019). https://doi.org/10.1007/s00259-019-04447-9

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  • DOI: https://doi.org/10.1007/s00259-019-04447-9

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