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MR Relaxometry for Discriminating Malignant Ovarian Cystic Tumors: A Prospective Multicenter Cohort Study.
Kawahara, Naoki; Kobayashi, Hiroshi; Maehana, Tomoka; Iwai, Kana; Yamada, Yuki; Kawaguchi, Ryuji; Takahama, Junko; Marugami, Nagaaki; Nishi, Hirotaka; Sakai, Yosuke; Takano, Hirokuni; Seki, Toshiyuki; Yokosu, Kota; Hirata, Yukihiro; Yoshida, Koyo; Ujihira, Takafumi; Kimura, Fuminori.
Affiliation
  • Kawahara N; Department of Obstetrics and Gynecology, Nara Medical University, Kashihara 634-8522, Japan.
  • Kobayashi H; Department of Obstetrics and Gynecology, Nara Medical University, Kashihara 634-8522, Japan.
  • Maehana T; Department of Gynecology and Reproductive Medicine, Ms. Clinic MayOne, 871-1 Shijo-Cho, Kashihara 634-0813, Japan.
  • Iwai K; Department of Obstetrics and Gynecology, Nara Medical University, Kashihara 634-8522, Japan.
  • Yamada Y; Department of Obstetrics and Gynecology, Nara Medical University, Kashihara 634-8522, Japan.
  • Kawaguchi R; Department of Obstetrics and Gynecology, Nara Medical University, Kashihara 634-8522, Japan.
  • Takahama J; Department of Obstetrics and Gynecology, Nara Medical University, Kashihara 634-8522, Japan.
  • Marugami N; Department of Radiology, Higashiosaka City Medical Center, Higashiosaka 578-8588, Japan.
  • Nishi H; Department of Radiology and Nuclear Medicine, Nara Medical University, Kashihara 634-8522, Japan.
  • Sakai Y; Department of Obstetrics and Gynecology, Tokyo Medical University, Shinjuku-Ku, Tokyo 160-0023, Japan.
  • Takano H; Department of Obstetrics and Gynecology, Tokyo Medical University, Shinjuku-Ku, Tokyo 160-0023, Japan.
  • Seki T; Department of Obstetrics and Gynecology, The Jikei University Kashiwa Hospital, Kashiwa 277-8567, Japan.
  • Yokosu K; Department of Obstetrics and Gynecology, The Jikei University Kashiwa Hospital, Kashiwa 277-8567, Japan.
  • Hirata Y; Department of Obstetrics and Gynecology, The Jikei University Kashiwa Hospital, Kashiwa 277-8567, Japan.
  • Yoshida K; Department of Obstetrics and Gynecology, The Jikei University School of Medicine, Minato-Ku, Tokyo 105-8461, Japan.
  • Ujihira T; Department of Obstetrics and Gynecology, Juntendo University Urayasu Hospital, Urayasu 279-0021, Japan.
  • Kimura F; Department of Obstetrics and Gynecology, Juntendo University Urayasu Hospital, Urayasu 279-0021, Japan.
Diagnostics (Basel) ; 14(11)2024 May 21.
Article in En | MEDLINE | ID: mdl-38893596
ABSTRACT

BACKGROUND:

Endometriosis-associated ovarian cancer (EAOC) is a well-known type of cancer that arises from ovarian endometrioma (OE). OE contains iron-rich fluid in its cysts due to repeated hemorrhages in the ovaries. However, distinguishing between benign and malignant tumors can be challenging. We conducted a retrospective study on magnetic resonance (MR) relaxometry of cyst fluid to distinguish EAOC from OE and reported that this method showed good accuracy. The purpose of this study is to evaluate the accuracy of a non-invasive method in re-evaluating pre-surgical diagnosis of malignancy by a prospective multicenter cohort study.

METHODS:

After the standard diagnosis process, the R2 values were obtained using a 3T system. Data on the patients were then collected through the Case Report Form (CRF). Between December 2018 and March 2023, six hospitals enrolled 109 patients. Out of these, 81 patients met the criteria required for the study.

RESULTS:

The R2 values calculated using MR relaxometry showed good discriminating ability with a cut-off of 15.74 (sensitivity 80.6%, specificity 75.0%, AUC = 0.750, p < 0.001) when considering atypical or borderline tumors as EAOC. When atypical and borderline cases were grouped as OE, EAOC could be distinguished with a cut-off of 16.87 (sensitivity 87.0%, specificity 61.1%).

CONCLUSIONS:

MR relaxometry has proven to be an effective tool for discriminating EAOC from OE. Regular use of this method is expected to provide significant insights for clinical practice.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Diagnostics (Basel) Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Diagnostics (Basel) Year: 2024 Document type: Article