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Clinical research of automated breast volume scanner and MRI in diagnosis of breast cancer / 中华超声影像学杂志
Chinese Journal of Ultrasonography ; (12): 687-692, 2017.
Article Dans Chinois | WPRIM | ID: wpr-666993
ABSTRACT
Objective To evaluate the effectiveness of automated breast volume scanner(ABVS) and magnetic resonance imaging(MRI) in the detection and diagnosis of breast cancer and to assess the value of these modalities as well as the joint use of the two.Methods In this study,a total of 50 breast lesions in 37 patients proved by surgery and pathology were included.Before operation,all patients were underwent both ABVS and dynamic contrast-enhanced (DCE-MRI) examinations,and classified into groups according to BI-RADS classification.Then the effectiveness of the two examinations were contrasted,the image features on the two techniques were analyzed,and their differential diagnosis in benign and malignant breast lesions were compared.Results The sensitivity,specificity,accuracy,positive predictive value (PPV) and negative predictive value(NPV) of ABVS and MRI for the diagnosis of breast cancer were 91.67% and 95.83%,88.46% and 80.77%,90.00% and 88.00%,88.00% and 82.14%,92.00% and 95.45%,respectively,and there was no statistical difference between ABVS and MRI(P >0.05);The sensitivity and specificity of the combination of the two were 99.65% and 97.78%,respectively.The difference of the ABVS coronal features and MRI dynamic enhancement curve types between malignant breast lesions and the benign were statistically significant (P < 0.05).Conclusions Both ABVS and MRI are effective to diagnose breast cancer well,while the combination of the two can improve the diagnosis more accurately.

Texte intégral: Disponible Indice: WPRIM (Pacifique occidental) Type d'étude: Etude diagnostique langue: Chinois Texte intégral: Chinese Journal of Ultrasonography Année: 2017 Type: Article

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Texte intégral: Disponible Indice: WPRIM (Pacifique occidental) Type d'étude: Etude diagnostique langue: Chinois Texte intégral: Chinese Journal of Ultrasonography Année: 2017 Type: Article