Diffusion‐Weighted Magnetic Resonance Imaging and Morphological Characteristics Evaluation for Outcome Prediction of Primary Debulking Surgery for Advanced High‐Grade Serous Ovarian Carcinoma

Background Preoperative assessment of whether a successful primary debulking surgery (PDS) can be performed in patients with advanced high‐grade serous ovarian carcinoma (HGSOC) remains a challenge. A reliable model to precisely predict resectability is highly demanded. Purpose To investigate the value of diffusion‐weighted MRI (DW‐MRI) combined with morphological characteristics to predict the PDS outcome in advanced HGSOC patients. Study Type Prospective. Subjects A total of 95 consecutive patients with histopathologically confirmed advanced HGSOC (ranged from 39 to 77 years). Fields Strength/Sequence A 3.0 T, readout‐segmented echo‐planar DWI . Assessment The MRI morphological characteristics of the primary ovarian tumor, a peritoneal carcinomatosis index (PCI) derived from DWI (DWI‐PCI) and histogram analysis of the primary ovarian tumor and the largest peritoneal carcinomatosis were assessed by three radiologists. Three different models were developed to predict the resectability, including a clinicoradiologic model combing MRI morphological characteristic with ascites and CA125 level; DWI‐PCI alone; and a fusion model combining the clinical‐morphological information and DWI‐PCI. Statistical Tests Multivariate logistic regression analyses, receiver operating characteristic (ROC) curve, net reclassification index (NRI) and integrated discrimination improvement (IDI) were used. A P < 0.05 was considered to be statistically significant. Results Sixty‐seven cases appeared as a definite mass, whereas 28 cases as an infiltrative mass. The morphological characteristics and DWI‐PCI were independent factors for predicting the resectability, with an AUC of 0.724 and 0.824, respectively. The multivariable predictive model consisted of morphological characteristics, CA‐125, and the amount of ascites, with an incremental AUC of 0.818. Combining the application of a clinicoradiologic model and DWI‐PCI showed significantly higher AUC of 0.863 than the ones of each of them implemented alone, with a positive NRI and IDI. Data Conclusions The combination of two clinical factors, MRI morphological characteristics and DWI‐PCI provide a reliable and valuable paradigm for the noninvasive prediction of the outcome of PDS. Evidence Level 2 Technical Efficacy Stage 2