Differentiation of cystic lesions in the jaw by conventional magnetic resonance imaging and diffusion-weighted imaging

Author:

Wamasing Natnicha1,Watanabe Hiroshi1,Sakamoto Junichiro1,Tomisato Hiroshi2,Kurabayashi Tohru1

Affiliation:

1. Department of Oral and Maxillofacial Radiology, Graduate School, Tokyo Medical and Dental University, Tokyo, Japan

2. Dpartment of Oral Radiology, Dental Hospital, Tokyo Medical and Dental University, Tokyo, Japan

Abstract

Objectives: This study aimed to determine the discrimination power of apparent diffusion coefficient (ADC) for cystic lesions in the jaw using MRI. Methods: We selected 127 cystic lesions, comprising dentigerous cysts (DCs), odontogenic keratocysts (OKCs), and unicystic ameloblastomas (UABs), from our MRI database examined by 3T MRI, including diffusion-weighted imaging sequences, and we reviewed their imaging characteristics. We attempted to discriminate the three types of lesions by ADC values with receiver operator characteristic analysis; however, satisfactory results were not obtained for differentiation between DC and OKC. Therefore, we performed a decision tree analysis. Results: The imaging characteristics of the lesions were significantly different according to Fisher’s exact test, except for differences in sex. The ADC values statistically discriminated the lesions of DC and UAB, OKC and UAB, but not DC and OKC. Thus, differentiation was performed by a decision tree for DC and OKC by evaluating the following points: the attached tooth condition, signal intensity on the T1 weighted image (T1SI), ADC value, and the cyst site. However, cases showing hypo- or isointense T1SI with an ADC value under 1.168 × 10–3 mm2/s were difficult to differentiate. Conclusion: The ADC value helped distinguish UAB from both DC and OKC, but not DC from OKC. However, the decision tree based on ADC value, tooth contact status, and T1SI helped differentiate DC and OKC to some extent.

Publisher

British Institute of Radiology

Subject

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

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