Application of diffusion kurtosis imaging to odontogenic lesions: Analysis of the cystic component

Junichiro Sakamoto, Ami Kuribayashi, Shinya Kotaki, Mamiko Fujikura, Shin Nakamura, Tohru Kurabayashi

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Purpose: To assess the feasibility of applying diffusion kurtosis imaging (DKI) to common odontogenic lesions and to compare its diagnostic ability versus that of the apparent diffusion coefficient (ADC) for differentiating keratocystic odontogenic tumors (KCOTs) from odontogenic cysts. Materials and Methods: Altogether, 35 odontogenic lesions were studied: 24 odontogenic cysts, six KCOTs, and five ameloblastomas. The diffusion coefficient (D) and excessive kurtosis (K) were obtained from diffusion-weighted images at b-values of 0, 500, 1000, and 1500 s/mm2 on 3T magnetic resonance imaging (MRI). The combination of D and K values showing the maximum density of the probable density function was estimated. The ADC was obtained (0 and 1000 s/mm2). Values for odontogenic cysts, KCOTs, and ameloblastomas were compared. Multivariate logistic regression modeling was performed to assess the combination of D and K model versus ADC for differentiating KCOTs from odontogenic cysts. Results: The mean D and ADC were significantly higher for ameloblastomas than for odontogenic cysts or KCOTs (P < 0.05). The mean K was significantly lower for ameloblastomas than for odontogenic cysts or KCOTs (P < 0.05). The mean values of all parameters for odontogenic cysts and KCOTs showed no significant differences (P = 0.369 for ADC, 0.133 for D, and 0.874 for K). The accuracy of the combination of D and K model (76.7%) was superior to that of ADC (66.7%). Conclusion: Use of DKI may be feasible for common odontogenic lesions. A combination of DKI parameters can be expected to increase the accuracy of its diagnostic ability compared with ADC. J. Magn. Reson. Imaging 2016;44:1565–1571.

Original languageEnglish
Pages (from-to)1565-1571
Number of pages7
JournalJournal of Magnetic Resonance Imaging
Volume44
Issue number6
DOIs
Publication statusPublished - Dec 1 2016
Externally publishedYes

Keywords

  • diffusion magnetic resonance imaging/methods*
  • head and neck neoplasms
  • image processing; computer-assisted/methods*
  • magnetic resonance imaging/methods*
  • odontogenic cysts
  • odontogenic tumors

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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