MR imaging of the parotid gland in Sjögren's syndrome: A proposal for new diagnostic criteria

Masahiro Izumi, Katsumi Eguchi, Masafumi Ohki, Masataka Uetani, Kuniaki Hayashi, Masako Kita, Shigenobu Nagataki, Takashi Nakamura

Research output: Contribution to journalArticlepeer-review

90 Citations (Scopus)

Abstract

OBJECTIVE. Because classic diagnostic techniques for Sjögren's syndrome (SS) are invasive and require radiation exposure, a noninvasive diagnostic method might benefit patients with SS. The purpose of this study was to determine whether quantitative analysis of MR images of the parotid gland can differentiate patients with SS from normal subjects. SUBJECTS AND METHODS. We performed quantitative analysis of MR images of the parotid gland for 40 patients with definite and probable SS, for 30 normal subjects matched by age and sex to the SS patients, and for 10 patients with parotid inflammation. MR images of the parotid gland were assessed by calculating standard deviations (SD) of signal intensity. RESULTS. SD of signal intensity exclusively (p < .0001) separated MR images of the parotid glands of patients with definite SS from those of normal subjects. SD of signal intensity for the parotid glands of patients with probable SS also were significantly higher (p < .001) than those of normal subjects. Changes in signal intensity were specific for SS and did not occur with parotid inflammation. Tentative categorization on the basis of signal intensity patterns on MR images of the parotid glands of SS patients showed a high correlation with the results of labial gland biopsy (r = .834) and sialography (r = .936). CONCLUSION. Taken together, these results conclusively indicate that quantitative analysis of MR images for SD of signal intensity is a useful method for diagnosing SS and can replace classic methods, which are invasive.

Original languageEnglish
Pages (from-to)1483-1487
Number of pages5
JournalAmerican Journal of Roentgenology
Volume166
Issue number6
DOIs
Publication statusPublished - Jun 1996

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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