Abstract
To evaluate if structured reports (SR) of pelvic magnetic resonance imaging (MRI) scans using the PALM-COEIN FIGO (the International Federation of Gynecology & Obstetrics) uterine leiomyomas classification (SR-FIGO) contain adequate information for clinical decision making compared with narrative reports (NR).
Three reporting templates for pelvic MRI scans were compared: NR, SR without the PALM-COEIN FIGO classification of leiomyomas, and SR-FIGO, for presence of 19 key-features (KF) deemed relevant for leiomyoma management. Kruskal-Wallis test was used to evaluate KF distribution across the report types. One gynecologist and one gynecologist-in-training evaluated the reports and MRI scans to assess the presence of sufficient information to decide on: (1) treatment type (observation/medical treatment/surgery/uterine artery embolization); (2) surgical approach (hysteroscopic/laparoscopic/robotic/open); (3) surgery type (myomectomy/hysterectomy); (4) necessity to review MRI scans; and (5) time spent reviewing MRI scans. The responses of the gynecologist and gynecologist-in-training to points 1 to 5 among report types were compared using χ
test.
Twenty NR, 20 SR, and 20 SR-FIGO were reviewed. The number of KF was significantly different among reports (P < 0.001): SR-FIGO had the highest number of KF, followed by SR, and NR. In pairwise comparison, significant differences were observed between NR and SR (P = 0.001) and between NR and SR-FIGO (P = 0.001), but not between SR and SR-FIGO (P = 0.063). There were significant differences in answers to question 1 between the gynecologist and gynecologist-in-training for SR (P = 0.007) and SR-FIGO (P = 0.024), with the gynecologist deeming SR and SR-FIGO to provide enough information for treatment decisions more commonly than the gynecologist-in-training.
Although this investigation revealed that SR offers a greater wealth of information in contrast to NR, additional investigation is required to ascertain whether the integration of the PALM-COEIN FIGO classification in SR enhances the clinical decision making capacity of gynecologists.