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

Characteristic Mean Kurtosis Values in Simple Diffusion Kurtosis Imaging of Dentigerous Cysts

We evaluated the usefulness of simple diffusion kurtosis (SD) imaging, which was developed to generate diffusion kurtosis images simultaneously with an apparent diffusion coefficient (ADC) map for 27 cystic disease lesions in the head and neck region. The mean kurtosis (MK) and ADC values were calculated for the cystic space. The MK values were dentigerous cyst (DC): 0.74, odontogenic keratocyst (OKC): 0.86, ranula (R): 0.13, and mucous cyst (M): 0, and the ADC values were DC: 1364 × 10-6 mm2/s, OKC: 925 × 10-6 mm2/s, R: 2718 × 10-6 mm2/s, and M: 2686 × 10-6 mm2/s. The MK values of DC and OKC were significantly higher than those of R and M, whereas their ADC values were significantly lower. One reason for the characteristic signal values in diffusion-weighted images of DC may be related to content components such as fibrous tissue and exudate cells. When imaging cystic disease in the head and neck region using SD imaging, the maximum b-value setting at the time of imaging should be limited to approximately 1200 s/mm2 for accurate MK value calculation. This study is the first to show that the MK values of DC are characteristically higher than those of other cysts.

Central vascular malformations of the mandible: Characteristic findings in computed tomography and magnetic resonance imaging

Central vascular malformations (CVMs) of the mandible are rare and can have varied clinical and radiological characteristics, thus making differential diagnosis difficult. We retrospectively reviewed 5 patients with proven CVM who underwent computed tomography (CT) and magnetic resonance imaging (MRI), including diffusion-weighted imaging (DWI) (and magnetic resonance angiography (MRA) for one patient), to assess the characteristic imaging findings of this lesion. CT revealed multilocularity in 3 lesions. All CVMs produced fine, irregular borders and low-to-intermediate density. Lesion continuity with the mandibular canal was discovered in 4 cases and enlarged feeding and outflow vessels in 3 lesions. Bone overgrowth was observed in 2 patients. CT values ranged from 30.84 to 52.87 Hounsfield units (HU). MRI exhibited low to intermediate signals on T1-weighted imaging (T1WI), signals ranging from low to intermediate-to-high on T2WI, and low to high signal intensity on short-tau inversion recovery (STIR) images, with flow voids in all patients and no inflammation in surrounding tissues. As calculated with DWI, the apparent diffusion coefficient (ADC) ranged from 0.69 to 1.74 × 10^-3 mm²/s. MRA showed the presence of feeding vessels in 1 lesion. Interexaminer agreement on image interpretation ranged from moderate to excellent. These typical CVM imaging findings may aid in the differential diagnosis of this lesion.

Diagnostic efficacy of apparent diffusion coefficient, texture features, and their combination for differential diagnosis of odontogenic cysts and tumors

OBJECTIVE

This study assessed the diagnostic efficacy of apparent diffusion coefficient (ADC), texture features, and their combination for the differential diagnosis of odontogenic cysts and tumors with cyst-like features.

STUDY DESIGN

In total, 14 dentigerous cysts (DCs), 12 odontogenic keratocysts (OKCs), and 6 unicystic ameloblastomas (UABs) were used as predictor variables in 32 outpatients who underwent magnetic resonance imaging. The outcome variables were ADC, texture features, and their combination for each lesion. Texture features including histogram and gray-level co-occurrence matrix (GLCM) were measured on ADC maps. Ten features were selected by using the Fisher coefficient method. The Kruskal-Wallis test and post hoc Mann-Whitney test with Bonferroni adjustment were used to analyze trivariate statistics. Statistical significance was established at P < .05. Receiver operating characteristic analysis was used to evaluate the diagnostic effect of ADC, texture features, and their combination in distinguishing the lesions from each other.

RESULTS

Apparent diffusion coefficient, 1 histogram feature, 9 GLCM features, and their combination demonstrated significant differences between DC, OKC, and UAB (P ≤ .01). Receiver operating characteristic analysis revealed a high area under the curve of .95 to 1.00 for ADC, 10 texture features, and their combination. Sensitivity, specificity, and accuracy ranged from .86 to 1.00.

CONCLUSIONS

Apparent diffusion coefficient and texture features, alone or in combination, can be clinically important in facilitating the distinction between these odontogenic lesions.

The magnetic resonance imaging characteristics of radicular cysts and granulomas

OBJECTIVES

Limited studies have differentiated radicular cysts and granulomas with MRI. Therefore, we investigated the MRI characteristics of the two lesions and clarified features for distinguishing between them.

METHODS

We collected data of 27 radicular cysts and 9 granulomas definitively diagnosed by histopathology and reviewed the fat-saturated T2 weighted, T1 weighted, and contrast-enhanced fat-saturated T1 weighted images. We measured the maximum diameter and apparent diffusion coefficient values of the lesions. We employed Fisher's exact test, the Mann-Whitney U test, and independent t-tests to compare the two lesions and created a decision tree for discriminating between them.

RESULTS

There were significant differences between radicular cysts and granulomas with respect to five imaging characteristics-signal intensity of the lesion centre on fat-saturated T2 weighted images; signal intensity, texture, and contrast enhancement of the lesion centre on contrast-enhanced fat-saturated T1 weighted images; and maximum diameter of the lesion. The cut-off diameter for radicular cysts was 15.9 mm. The area under the receiver operating characteristic curve, sensitivity, and specificity were 0.971, 85.2%, and 100%, respectively.

CONCLUSIONS

From the decision tree analysis, maximum diameter, lesion centre contrast enhancement on contrast-enhanced fat-saturated T1 weighted images, and lesion centre signal intensity on fat-saturated T2 weighted images were important for discriminating between radicular cysts and granulomas.