2020
DOI: 10.12701/yujm.2019.00353
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Usefulness of subtraction pelvic magnetic resonance imaging for detection of ovarian endometriosis

Abstract: Background: To minimize damage to the ovarian reserve, it is necessary to evaluate the follicular density in the ovarian tissue surrounding endometriosis on preoperative imaging. The purpose of the present study was to evaluate the usefulness of subtraction pelvic magnetic resonance imaging (MRI) to detect ovarian reserve. Methods: A subtracted T1-weighted image ( sub T1WI) was obtained by subtracting unenhanced T1WI from contrast-enhanced T1WI ( ce T1WI) with similar parameters in 22 patients with ovarian end… Show more

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Cited by 3 publications
(2 citation statements)
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“…However, this study focused on the role of contrast agents in the evaluation of adjacent surviving ovarian tissue invaded by endometriosis. The perfusion map could be used for the analysis of viable tissue within this subset of cystic ovarian masses according to the severity of endometriosis for preoperative evaluation [14][15][16].…”
Section: Discussionmentioning
confidence: 99%
“…However, this study focused on the role of contrast agents in the evaluation of adjacent surviving ovarian tissue invaded by endometriosis. The perfusion map could be used for the analysis of viable tissue within this subset of cystic ovarian masses according to the severity of endometriosis for preoperative evaluation [14][15][16].…”
Section: Discussionmentioning
confidence: 99%
“…Because of the advantages of multiparameter and multisequence imaging and high tissue resolution, a plain scan of MRI is very suitable for the diagnosis and staging of deep infiltrating endometriosis. It helps a lot to find vaginal rectal septum or rectal mass and identify the relationship between the mass and the surrounding organs like the intestine and bladder clearly, but there are still limitations in image noise and image detail imaging [ 11 ]. In addition, traditional MRI diagnosis often requires a comprehensive diagnosis by professional physicians, with effective information in the images and various characteristics of the patients.…”
Section: Introductionmentioning
confidence: 99%