Establishment and validation of predictive model for lymph node metastasis of ovarian cancer based on pre-operative MRI imaging featuresand clinical characteristics
Objective To investigate the risk factors of lymph node metastasis of ovarian cancer,and to construct a nomo-gram of lymph node metastasis of ovarian cancer based on preoperative MRI imaging featuresand clinical characteristics.Methods 225 patients with ovarian cancer who came to our hospital from February 2018 to July 2021 were selected as research objects,and were divided into the lymph node metastasis group and the non-lymph node metastasis group according to the lymph node metastasis.Logistic regression analysis was used to screen the risk factors of lymph node metastasis of ovarian cancer.The MRI imaging features of ovarian cancer patients before surgery were extracted by LIFEx software,and the linear combination of these selected MRI imaging featuresand their corresponding non-zero coefficientswas used to determine the MRI im-aging score.To establish the model of MRI imaging features and clini-cal characteristics.By integrating the optimized modal of MRI imaging features and clinical characteristics,R(R4.2.0)software was used to establish the nomogram of ovarian cancer lymph node metastasis,and the model was internally validated.Results Among 225 cases of ovarian cancer,95 patients had lymph node metastasis,and the incidence of lymph node metastasis was 42.22%(95/225).Logsitc regression analysis showed that clinical stage,focus location,differentiation degree and diabetes were risk factors for lymph node metastasis of ovarian cancer(P＜0.05).Combined with the results of multiple factors and the extraction of MRI imageomics parameters,three prediction models were constructed,including one clinical model,one MRI imageomics model,and one combined model(clinical MRI imageomics model).Among the three prediction models,it was found that the area under curve(AUC)(0.862)of the clinical MRI imageomics model was the highest.The results of the no-mogram model of clinical MRI imaging features on ovarian cancer lymph node metastasis showed that the correction curve showed that the predicted value had a good fit with the actual value;The area under the ROC curve of the model was 0.862(95%CI:0.790-0.934);The decision curve showed that when the threshold probability was 22%-80%,the net benefit value of nomogram in predic-ting lymph node metastasis of ovarian cancer was high.Conclusion The nomograph model of lymph node metastasis of ovarian canc-er based on preoperative MRI imaging featuresand clinical characteristics has a high accuracy and good clinical application value,and can be used for preoperative identification of lymph node metastasis of ovarian cancer.
nuclear magnetic resonanceimaging histologyoophoromalymph node metastasisrisk factorsnomogram
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