Pre-operative evaluation of epithelial ovarian cancer patients: Role of whole body diffusion weighted imaging MR and CT scans in the selection of patients suitable for primary debulking surgery. A single-centre study

PURPOSE

to evaluate the accuracy of Whole Body MRI including Diffusion-Weighted Imaging sequences (WB DWI MR) in the assessment of sites of disease in epithelial ovarian cancer (EOC), in comparison to CT; to evaluate whether a clinical-radiological score may predict suboptimal cytoreductive surgery.

METHODS

patients with suspected EOC who underwent pre-operative WB DWI MR were included; CT scans were recorded. Data recorded included: age, staging, dates of examinations and surgery; tumour markers; sites of disease at imaging scans and at surgery. For calculation of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of WB DWI MR and CT, surgical evaluation represented the gold standard. The accuracy of WB DWI MR and CT was compared. The association between clinical and radiological criteria with sub-optimal cytoreduction was tested to identify a final model to predict sub-optimal cytoreduction.

RESULTS

92 patients were included; 77/92 (83.7 %) were optimally cytoreduced. Sixty-six CT and 92 MR examinations were evaluated. WB DWI MR showed overall higher accuracy than CT in assessing all sites, but it performed significantly better than CT specifically for involvement of mesentery, lumbo-aortic lymph nodes, pelvis, large bowel, sigmoid-rectum. The predicting score for suboptimal cytoreduction included: mesenteric carcinomatosis; mesenteric retraction; large bowel carcinomatosis.

CONCLUSIONS

In pre-operative evaluation of EOC patients, WB DW MRI is accurate for assessment of multiple sites and it is significantly more accurate than CT for specific unresectable sites. In our series, significant sites of disease for suboptimal cytoreduction were mesenteric carcinomatosis, mesenteric retraction and large bowel carcinomatosis.

Endometrial cancer: an overview of novelties in treatment and related imaging keypoints for local staging

Endometrial cancer is the most common gynaecologic malignancy in developed countries and its incidence is increasing. First-level treatment, if no contraindicated, is based on surgery. Pre-operative imaging is needed for evaluation of local extent and detection of distant metastases in order to guide treatment planning. Radiological evaluation, based on transvaginal ultrasound, MR and CT, can make the difference in disease management, paying special attention to assessment of entity of myometrial invasion, cervical stromal extension, and assessment of lymph nodal involvement and distant metastases.

Radiomics of high-grade serous ovarian cancer: association between quantitative CT features, residual tumour and disease progression within 12 months

OBJECTIVES

To determine if radiomic features, alone or combined with clinical data, are associated with residual tumour (RT) at surgery, and predict the risk of disease progression within 12 months (PD12) in ovarian cancer (OC) patients.

METHODS

This retrospective study enrolled 101 patients according to the following inclusion parameters: cytoreductive surgery performed at our institution (9 May 2007-23 February 2016), assessment of BRCA mutational status, preoperative CT available. Radiomic features of the ovarian masses were extracted from 3D structures drawn on CT images. A phantom experiment was performed to assess the reproducibility of radiomic features. The final radiomic features included in the analysis (n = 516) were grouped into clusters using a hierarchical clustering procedure. The association of each cluster's representative radiomic feature with RT and PD12 was assessed by chi-square test. Multivariate analysis was performed using logistic regression models. P values < 0.05 were considered significant.

RESULTS

Patients with values of F2-Shape/Compactness1 below the median, of F1- GrayLevelCooccurenceMatrix25/0-1InformationMeasureCorr2 below the median and of F1-GrayLevelCooccurenceMatrix25/-333-1InverseVariance above the median showed higher risk of RT (36%, 36% and 35%, respectively, as opposed to 18%, 18% and 18%). Patients with values of F4-GrayLevelRunLengthMatrix25/-333RunPercentage above the median, of F2 shape/Max3DDiameter below the median and F1-GrayLevelCooccurenceMatrix25/45-1InverseVariance above the median showed higher risk of PD12 (22%, 24% and 23%, respectively, as opposed to 6%, 5% and 6%). At multivariate analysis F2-Shape/Max3DDiameter remained significant (odds ratio (95% CI) = 11.86 (1.41-99.88)). To predict PD12, a clinical radiomics model performed better than a base clinical model.

CONCLUSION

This study demonstrated significant associations between radiomic features and prognostic factors such as RT and PD12.

KEY POINTS

• No residual tumour (RT) at surgery is the most important prognostic factor in OC. • Radiomic features related to mass size, randomness and homogeneity were associated with RT. • Progression of disease within 12 months (PD12) indicates worse prognosis in OC. • A model including clinical and radiomic features performed better than only-clinical model to predict PD12.