OBJECTIVE: To compare the diagnostic accuracy of diffusion-weighted magnetic resonance imaging (DWI) and frozen-section analysis in assessing myometrial invasion in endometrial cancer to guide surgery. METHODS: In this prospective study, 51 women with diagnosed endometrial cancer were examined using magnetic resonance imaging (MRI) and subsequently underwent hysterectomy with intraoperative frozen-section assessment. The MRI protocol included T2-weighted images (T2WI), a dynamic T1-weighted post-gadolinium series, and DWI sequences acquired with b values of 0, 150, and 800 s/mm(2). Apparent diffusion coefficient (ADC) maps were obtained in all the studies. Deep myometrial invasion was defined as involvement of ≥50% of the thickness of the myometrium. The final postoperative pathological evaluation was considered as the reference standard. RESULTS: The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of DWI for detecting deep invasion of the myometrium were 90.2%, 77.8%, 97%, 93.3%, and 88.9%, respectively. For the intraoperative frozen section, these figures were 90.2%, 73.7%, 100%, 100%, and 86.5%. The precision for both tests was the same using McNemar's test (p = 1). CONCLUSION: In assessing the depth of myometrial invasion, ADC maps show the same accuracy as intraoperative histological studies in endometrial cancers. They also allow for a more precise assessment than conventional MRI sequences. Frozen-section analysis can be avoided if the preoperative MRI study includes DWI sequences and ADC maps.
OBJECTIVE: To compare the diagnostic accuracy of diffusion-weighted magnetic resonance imaging (DWI) and frozen-section analysis in assessing myometrial invasion in endometrial cancer to guide surgery. METHODS: In this prospective study, 51 women with diagnosed endometrial cancer were examined using magnetic resonance imaging (MRI) and subsequently underwent hysterectomy with intraoperative frozen-section assessment. The MRI protocol included T2-weighted images (T2WI), a dynamic T1-weighted post-gadolinium series, and DWI sequences acquired with b values of 0, 150, and 800 s/mm(2). Apparent diffusion coefficient (ADC) maps were obtained in all the studies. Deep myometrial invasion was defined as involvement of ≥50% of the thickness of the myometrium. The final postoperative pathological evaluation was considered as the reference standard. RESULTS: The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of DWI for detecting deep invasion of the myometrium were 90.2%, 77.8%, 97%, 93.3%, and 88.9%, respectively. For the intraoperative frozen section, these figures were 90.2%, 73.7%, 100%, 100%, and 86.5%. The precision for both tests was the same using McNemar's test (p = 1). CONCLUSION: In assessing the depth of myometrial invasion, ADC maps show the same accuracy as intraoperative histological studies in endometrial cancers. They also allow for a more precise assessment than conventional MRI sequences. Frozen-section analysis can be avoided if the preoperative MRI study includes DWI sequences and ADC maps.
Authors: Nicole Concin; Carien L Creutzberg; Ignace Vergote; David Cibula; Mansoor Raza Mirza; Simone Marnitz; Jonathan A Ledermann; Tjalling Bosse; Cyrus Chargari; Anna Fagotti; Christina Fotopoulou; Antonio González-Martín; Sigurd F Lax; Domenica Lorusso; Christian Marth; Philippe Morice; Remi A Nout; Dearbhaile E O'Donnell; Denis Querleu; Maria Rosaria Raspollini; Jalid Sehouli; Alina E Sturdza; Alexandra Taylor; Anneke M Westermann; Pauline Wimberger; Nicoletta Colombo; François Planchamp; Xavier Matias-Guiu Journal: Virchows Arch Date: 2021-02 Impact factor: 4.064
Authors: Brentley Q Smith; Jonathan D Boone; Eric D Thomas; Taylor B Turner; Gerald McGwin; Amanda M Stisher; Charles A Leath; Lea Novak; Warner K Huh Journal: Am J Clin Oncol Date: 2020-02 Impact factor: 2.787
Authors: Sushant K Das; Xiang K Niu; Jing L Wang; Li C Zeng; Wen X Wang; Anup Bhetuwal; Han F Yang Journal: Cancer Imaging Date: 2014-11-12 Impact factor: 3.909
Authors: Lei Deng; Qiu-Ping Wang; Rui Yan; Xiao-Yi Duan; Lu Bai; Nan Yu; You-Min Guo; Quan-Xin Yang Journal: Cancer Imaging Date: 2018-07-03 Impact factor: 3.909