# Radiomics Analysis in Ovarian Cancer: A Narrative Review
## 7 Computed Tomography CT  
CT is a standard preoperative evaluation of OC patients for disease staging [75]. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Author** & **Year** & **Population** & **Radiomic Platform** & **Radiomics** & **ML Algorithms** & **Outcome** & **Study Design** \\ \hline [PERSON] et al. [72] & 2018 & 286 & MATLAB software & 1714 & LASSO & \begin{tabular}{c} Benign/malignant OMs \\ Type I/type II subtypes \\ \end{tabular} & Retrospective \\ \hline [PERSON] et al. [73] & 2020 & 104 & \begin{tabular}{c} ITK-SNAP software \\ (version 4.7.2) \\ \end{tabular} & 960 & \begin{tabular}{c} Logistic \\ regression \\ \end{tabular} & \
\begin{tabular}{c} Benign/borderline/ \\ malignant OMs \\ \end{tabular} & Prospective \\ \hline [PERSON] et al. [74] & 2020 & 294 &
\begin{tabular}{c} ITK-SNAP software \\ (version 4.7.2) \\ \end{tabular} & 851 & LASSO & Type I/type II subtypes & Retrospective \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Technical characteristics of reviewed MRI studies deploying radiomic analysis. CT has an accuracy between 70 and 90% for implant detection [75; 76; 77; 78] but quite a limited sensitivity (25% to 50%) for implants less than 1 cm, especially in locations such as the bowel or mesenterry. Reformatted images in coronal and sagittal planes are very useful for evaluating the subphrenic space [75]. Aside from pre-treatment staging, another aim of the CT exam is the response evaluation to chemotherapy, which, until now, has had some challenges. As it relies only on macroscopic changes such as tumor size--for example, by using the Response Evaluation Criteria in Solid Tumors (RECIST) [79]--CT does not provide a quantitative assessment of disease response to cytotoxic therapy and does not reflect molecular events in tumor-like apoptosis and necrosis. The presence of carcinomas, consisting of many sub-centimeter nodules with poorly defined margins, makes the use of RECIST impossible to achieve. Functional imaging using diffusion-weighted imaging (DWI) has been assessed in this field of research. The use of apparent diffusion coefficient (ADC) histograms may increase the efficacy in the monitoring of responses to treatment in peritoneal carcinomas [80]. We report CT studies deploying radiomic analysis and their technical characteristics (Table 3). A study of [PERSON] et al. extracted the radiomic features from staging CT in OC patients to evaluate if the radiomic features, alone or in combination with clinical data, may be associated with residual tumor (KT) at surgery and to forecast the risk of disease progression within a 12-month duration. This study showed a good correlation between some radiomic features and prognosis, verifying an AUC of 0.87 [81]. To evaluate an 18-month follow-up in advanced HGSC patients, [PERSON] et al. analyzed radiomic signatures of preoperative CT. According to the timing of their surgery and hospital stay, all patients were divided into cohorts, three in total--the training cohort (TC) and internal validation cohort (IVC) were from one hospital, and the independent external validation cohort (IEVC) was from a different hospital. The TC showed the most reliable accuracy for forecasting recurrence risk within 18 months and 3 years--82.4% (95% CI, 77.8-87.0%) and 83.4% (95%CI, 77.3-89.6%), respectively. Patients affected with recurrent OC who were enrolled in prospective immunotherapeutic trials were evaluated by [PERSON] et al., analyzing their baseline CT scans. The