OBJECT: To assess the diagnostic value of dynamic contrast-enhanced (DCE) perfusion-magnetic resonance imaging (MRI) in detection, characterization and grading of endometrial cancer, using histopathological analysis as the standard of reference. MATERIALS AND METHODS: Eighty patients with histologically proven endometrial carcinoma who underwent MRI (1.5 T magnet) of the pelvis for staging purposes were enrolled in the study. Each MR examination consisted of multiplanar T2 and T1-weighted turbo spin echo (TSE) sequences and T1-weighted gradient echo sequences before, during and after the administration of contrast medium. For each patient colour perfusion maps were derived from the dynamic sequences using a dedicated workstation. On the maps a region of interest was manually drawn both on normal myometrium and on the endometrial lesion. Then the following perfusion parameters were automatically calculated: relative enhancement (RE, %), maximum enhancement (ME, %), maximum relative enhancement (MRE, %) and time to peak (TTP, s). RESULTS: All patients underwent total hysterectomy. Histopathological analysis documented: G1 tumour in 21 patients, G2 tumour in 44 patients, G3 tumour in 14 patients and one squamous cell carcinoma. The following mean value perfusion parameters, with corresponding mean standard deviation, were obtained for endometrial cancer: RE (%) = 59.3 ± 36.3; ME (%) = 862.7 ± 475.9; MRE (%) = 75.3 ± 37.6 and TTP (s) = 164.7 ± 78. RE, ME and MRE were lower in tumour lesions than in normal myometrium (p < 0.001) and significantly higher values (p < 0.001) of perfusion parameters were obtained for G1 (well-differentiated) tumours as compared to those in G2 and G3 (moderately and poorly differentiated) lesions. CONCLUSION: DCE perfusion-MRI can provide quantitative information on tissue vascularity, which may be of help in detecting endometrial cancer and in the assessment of tumour grading.
OBJECT: To assess the diagnostic value of dynamic contrast-enhanced (DCE) perfusion-magnetic resonance imaging (MRI) in detection, characterization and grading of endometrial cancer, using histopathological analysis as the standard of reference. MATERIALS AND METHODS: Eighty patients with histologically proven endometrial carcinoma who underwent MRI (1.5 T magnet) of the pelvis for staging purposes were enrolled in the study. Each MR examination consisted of multiplanar T2 and T1-weighted turbo spin echo (TSE) sequences and T1-weighted gradient echo sequences before, during and after the administration of contrast medium. For each patient colour perfusion maps were derived from the dynamic sequences using a dedicated workstation. On the maps a region of interest was manually drawn both on normal myometrium and on the endometrial lesion. Then the following perfusion parameters were automatically calculated: relative enhancement (RE, %), maximum enhancement (ME, %), maximum relative enhancement (MRE, %) and time to peak (TTP, s). RESULTS: All patients underwent total hysterectomy. Histopathological analysis documented: G1 tumour in 21 patients, G2 tumour in 44 patients, G3 tumour in 14 patients and one squamous cell carcinoma. The following mean value perfusion parameters, with corresponding mean standard deviation, were obtained for endometrial cancer: RE (%) = 59.3 ± 36.3; ME (%) = 862.7 ± 475.9; MRE (%) = 75.3 ± 37.6 and TTP (s) = 164.7 ± 78. RE, ME and MRE were lower in tumour lesions than in normal myometrium (p < 0.001) and significantly higher values (p < 0.001) of perfusion parameters were obtained for G1 (well-differentiated) tumours as compared to those in G2 and G3 (moderately and poorly differentiated) lesions. CONCLUSION:DCE perfusion-MRI can provide quantitative information on tissue vascularity, which may be of help in detecting endometrial cancer and in the assessment of tumour grading.
Authors: L D Zuurendonk; R A Smit; B W J Mol; H W H Feijen; J de Graaff; D Sykora; K A J de Winter; A vd Wurff; M P M L Snijders; R F P M Kruitwagen Journal: Eur J Surg Oncol Date: 2006-03-20 Impact factor: 4.424
Authors: Defeng Liu; Linsha Yang; Dan Du; Tao Zheng; Lanxiang Liu; Zhanqiu Wang; Juan Du; Yanchao Dong; Huiling Yi; Yujie Cui Journal: Front Oncol Date: 2022-03-31 Impact factor: 6.244