CT perfusion imaging for predicting tiny lymph nodes metastasis of squamous cell carcinoma in cervix after neoadjuvant chemotherapy / 中国医学影像技术
Chinese Journal of Medical Imaging Technology
; (12): 428-432, 2017.
Article
Dans Zh
| WPRIM
| ID: wpr-608748
Responsable en Bibliothèque :
WPRO
ABSTRACT
Objective To explore the application value of CT perfusion imaging for predicting the tiny lymph nodes metastasis and micrometastasis of squamous cell carcinoma in cervix after neoadjuvant chemotherapy.Methods The clinical data and CT perfusion parameters of 46 patients with cervical squamous cell carcinoma who underwent neoadjuvant chemotherapy followed by surgery were enrolled in the study.Based on the surgical pathology findings and short-term follow up,the cases were divided into without tiny lymph nodes metastasis (short axle diameter of lymph nodes<10 mm) group (n=32) and with tiny lymph nodes metastasis group (n=14).All perfusion data were analyzed retrospectively and the diagnostic value were investigated.Results Blood flow (BF),blood volume (BV) and the maximum diameter of tumor per-chemotherapy in with tiny lymph nodes metastasis group were higher than those in without tiny lymph nodes metastasis group (all P<0.05).The differences of the maximum diameter of tumor after chemotherapy,permeability,time to peak (TTP) between two groups were not statistically significant (all P>0.05).Multivariate Logistic regression analysis showed BF and the maximum diameter of tumor per-chemotherapy were independent predictors of the tiny lymph nodes metastasis in cervix after neoadjuvant chemotherapy.ROC showed BF (AUC=0.86,P<0.001,95%CI [0.75,0.96]) had higher predictive value than maximum diameter of tumor per-chemotherapy (AUC=0.70,P=0.02,95 % CI [0.54,0.88]).Conclusion CT perfusion imaging shows the significant predictive value for the tiny lymph nodes metastasis of squamous cell carcinoma in cervix after neoadjuvant chemotherapy.
Texte intégral:
1
Indice:
WPRIM
Type d'étude:
Prognostic_studies
langue:
Zh
Texte intégral:
Chinese Journal of Medical Imaging Technology
Année:
2017
Type:
Article