Diffusion-weighted imaging with histogram analysis of the apparent diffusion coefficient maps in the diagnosis of parotid tumours |
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| Institution: | 1. Department of Diagnostic Radiology, Mansoura Faculty of Medicine, Mansoura, Egypt;2. Surgical Oncology, Mansoura Oncology Centre, Mansoura Faculty of Medicine, Mansoura, Egypt;3. Department of Diagnosis and Oral Radiology, Mansoura Faculty of Dentistry, Mansoura, Egypt;1. Faculty of Health, Social Care and Medicine, Edge Hill University, Ormskirk, UK;2. Liverpool Head and Neck Centre, Liverpool University Hospital Aintree, Liverpool, UK;3. Astraglobe Ltd, Congleton, Cheshire, UK;4. Department of Sport & Physical Activity, Edge Hill University, Ormskirk, UK;1. Department of Oral and Maxillofacial Surgery, Universitätsklinikum Knappschaftskrankenhaus Bochum, Bochum, Germany;2. Department of Diagnostic and Interventional Radiology and Nuclear Medicine, Universitätsklinikum Knappschaftskrankenhaus Bochum, Bochum, Germany;1. Department of Oral and Maxillofacial Surgery, Second Xiangya Hospital of Central South University, Changsha, Hunan, China;2. Department of Oral and Maxillofacial Surgery, Hainan Western Central Hospital, Danzhou, Hainan, China;3. Department of Oral and Maxillofacial & Head and Neck Oncology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China;4. Department of Oral and Maxillofacial Surgery, Affiliated Hospital of Guilin Medical University, Guilin, Guangxi Zhuang Autonomous Region, China |
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| Abstract: | The aim of this study was to investigate the role of diffusion-weighted imaging (DWI) with histogram analysis of apparent diffusion coefficient (ADC) maps in the characterization of parotid tumours. This prospective study included 39 patients with parotid tumours. All patients underwent magnetic resonance imaging with DWI, and ADC maps were generated. The whole lesion was selected to obtain histogram-related parameters, including the mean (ADCmean), minimum (ADCmin), maximum (ADCmax), skewness, and kurtosis of the ADC. The final diagnosis included pleomorphic adenoma (PA; n = 18), Warthin tumour (WT; n = 12), and salivary gland malignancy (SGM; n = 9). ADCmean (×10?3 mm2/s) was 1.93 ± 0.34 for PA, 1.01 ± 0.11 for WT, and 1.26 ± 0.54 for SGM. There was a significant difference in whole lesion ADCmean among the three study groups. Skewness had the best diagnostic performance in differentiating PA from WT (P = 0.001; best detected cut-off 0.41, area under the curve (AUC) 0.990) and in discriminating WT from SGM (P = 0.03; best detected cut-off 0.74, AUC 0.806). The whole lesion ADCmean value had best diagnostic performance in differentiating PA from SGM (P = 0.007; best detected cut-off 1.16 × 10?3 mm2/s, AUC 0.948). In conclusion, histogram analysis of ADC maps may offer added value in the differentiation of parotid tumours. |
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| Keywords: | magnetic resonance imaging diffusion magnetic resonance imaging parotid gland salivary glands pleomorphic adenoma Warthin tumor |
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