Synthetic MRI for the quantitative and morphologic assessment of head and neck tumors: a preliminary study

Author:

Zhang Zanxia1,Li Shujian1,Wang Weijian1,Zhang Yong1,Wang Kaiyu2,Cheng Jingliang1,Wen Baohong1

Affiliation:

1. Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China

2. MR Research China, GE Healthcare, Beijing, China

Abstract

Objectives: To evaluate the feasibility of synthetic MRI for quantitative and morphologic assessment of head and neck tumors and compare the results with the conventional MRI approach. Methods and materials: A total of 92 patients with different head and neck tumor histology who underwent conventional and synthetic MRI were retrospectively recruited. The quantitative T1, T2, proton density (PD), and apparent diffusion coefficient (ADC) values of 38 benign and 54 malignant tumors were measured and compared. Diagnostic efficacy for differentiating malignant and benign tumors was evaluated with receiver operating characteristic (ROC) analysis and integrated discrimination index. The image quality of conventional and synthetic T1W/T2W images on a 5-level Likert scale was also compared with Wilcoxon signed rank test. Results: T1, T2 and ADC values of malignant head and neck tumors were smaller than those of benign tumors (all p < 0.05). T2 and ADC values showed better diagnostic efficacy than T1 for distinguishing malignant tumors from benign tumors (both p < 0.05). Adding the T2 value to ADC increased the area under the curve from 0.839 to 0.886, with an integrated discrimination index of 4.28% (p < 0.05). In terms of overall image quality, synthetic T2W images were comparable to conventional T2W images, while synthetic T1W images were inferior to conventional T1W images. Conclusions: Synthetic MRI can facilitate the characterization of head and neck tumors by providing quantitative relaxation parameters and synthetic T2W images. T2 values added to ADC values may further improve the differentiation of tumors.

Publisher

Oxford University Press (OUP)

Subject

General Dentistry,Radiology, Nuclear Medicine and imaging,General Medicine,Otorhinolaryngology

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