Differentiation of submandibular sialadenitis based on apparent diffusion coefficient

Hirotaka Muraoka, Takashi Kaneda, Takumi Kondo, Naohisa Hirahara, Yuta Kohinata, Satoshi Tokunaga

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: This study aimed to quantify the submandibular gland in suppurative sialadenitis, primary Sjögren's syndrome (pSS) and radiation-induced sialadenitis using the apparent diffusion coefficient (ADC) for differential diagnosis. Subjects and Methods: This retrospective study included 16 patients with suppurative sialadenitis (n = 9), pSS (n = 3) and radiation-induced sialadenitis (n = 4) who underwent magnetic resonance imaging between June 2006 and May 2022. The ADC of the submandibular glands in each state was calculated, and the differences were analysed using a one-way analysis of variance and Tukey's post hoc test. Receiver operating characteristic curves were used to assess the ability of the ADC to distinguish each condition. Statistical significance was set at p < 0.05. Results: The mean ADC value (×10−3 mm2/s) ± standard deviation in the control (non-affected side of the suppurative sialadenitis group), suppurative sialadenitis, pSS and radiation-induced groups were 0.94 ± 0.16, 1.24 ± 0.16, 1.33 ± 0.13 and 1.5 ± 0.12, respectively (p < 0.001). The diagnostic value for distinguishing each group was ≥0.75. Conclusion: ADC values are useful for quantitatively assessing and distinguishing submandibular glands in suppurative sialadenitis, primary Sjögren's syndrome and radiation-induced sialadenitis.

Original languageEnglish
JournalOral Diseases
DOIs
Publication statusAccepted/In press - 2024

Keywords

  • apparent diffusion coefficient
  • diffusion-weighted imaging
  • sialadenitis
  • submandibular gland

Fingerprint

Dive into the research topics of 'Differentiation of submandibular sialadenitis based on apparent diffusion coefficient'. Together they form a unique fingerprint.

Cite this