Researchers developed and validated a noninvasive model that has the potential to preoperatively predict early recurrence for perihilar cholangiocarcinoma (pCCA), a type of hepatobiliary tumor. This model uses a magnetic resonance imaging (MRI)-based radiomics signature combined with clinical variables to form the prediction.
Zhao et al developed these models during a retrospective study on 184 patients (115 men and 69 women) with pCCA. They developed 3 models from a training set of 128 patients and validated these models in a separate testing set of 56 patients. These models included Modelradiomic, Modelclinic, and Modelcombine.
Development of Prediction Models for pCCA
The investigators created the Modelradiomic using contrast-enhanced arterial and portal vein phase MRIs of the hepatobiliary system. To extract and model radiomics features from these MRIs, they applied correlation analysis, least absolute shrinkage and selection operator (LASSO) logistic regression (LR), and backward stepwise LR. Modelclinic consisted of preoperative clinical predictors selection and modeling and used univariate and multivariate backward stepwise LR. Lastly, Modelcombine combined the Modelradiomics and Modelclinic predictors using a multivariate LR method.
Validation of Prediction Models for pCCA
Next, the researchers validated these constructed models using the Delong test to compare the area under the curves in the training set. Both Modelclinic and Modelcombine demonstrated superior statistically significant performance when compared with the Modelradiomic and the Tumor-Node-Metastasis (TNM) system. The results from the training set were then compared with the validation testing. Both Modelclinic and Modelcombine demonstrated statistically significant performance compared with the TNM system; however, only the Modelcombine proved superior to Modelradiomic. Currently, the TNM system is the most widely used grading system to predict cancer recurrence and spread.
The authors suggest “preoperative accurate prediction of postoperative early recurrence can avoid unnecessary operation(s).” The driving purpose of developing this method of predicting early recurrence of pCCA is to provide advanced insights so that surgeons can make informed decisions based upon the poor prognosis that typically accompanies early recurrence following surgeries in these patients.
Zhao J, Zhang W, Zhu Y-Y, et al. Development and validation of noninvasive MRI-based signature for preoperative prediction of early recurrence in perihilar cholangiocarcinoma. J Magn Reson Imaging. Published online July 23, 2021. doi:10.1002/jmri.27846