Discussion

We prospectively enrolled 40 patients with OC to study whether ADCs measured by 3.0T DWI imaging associated with histological severity of OC or predicted the clinical outcome. Our results illustrate that measurement of ADCs is a valuable tool for characterizing OC. In our cohort, reduced ADCs were associated with traditional histopathological prognostic markers, such as poorly differentiated tumours and high Ki-67 expression. ADCs also significantly correlated with VEGF protein expression in primary tumours epithelial cells and with VEGF receptor expression in metastases. Importantly, lower ADCs predicted significantly poorer OS at 3 years.

Analysis of ADCs has shown promise in increasing the precision of diagnosis, prognosis assessment, and predicting the therapeutic response in different cancers (Arponent et al., 2015; Harry et al., 2010; Kyriazi et al., 2010; Vargas et al., 2013), paralleling the results in preclinical studies (L, 2013). In our cohort, ADCs measured with WLsp-ROI were lower in poorly differentiated primary tumours, an observation consistent with early studies (Bae et al., 2014; Oh et al., 2015). Grade is a significant predictor of OC outcome (Bois et al., 2009; Friedlander, 1998). Ki-67 is a nuclear protein associated with cellular proliferation, and high Ki-67 expression is associated with more aggressive disease (Khouja et al., 2007). In primary tumours, ADCs were inversely associated with Ki-67 protein expression measured with both WLsp- and S-ROI. Similar results have been published for prostate (Bae et al., 2014) and breast cancer (Mori et al., 2015).

ADC measurements were extracted from both larger ROIs covering the entire tumour at a single plane (WLsp-ROI) and defined subareas within tumours (S-ROI).

ADCs measured from the entire tumour at a single plane were higher than the values with small subregions. In this cohort, ADC-values from S-ROIs proved to be inferior to WLsp-ROI in the prediction of OC histopathology and survival. Our results indicate that ADC values measured from WLsp-ROI are sufficient to be used as prognostic biomarkers in DWI-MRI of OC. The correlation of ADC measurements between two readers was excellent in primary tumours. In Bland-Altman analysis the 95% limits of agreement were slightly wider for S-ROI measurements in comparison to WLsp-ROI measurements (Fig. 2). The mean ADCs for the primary tumours were lower in our study than in many earlier studies (Katayama et al.;

Moteki and Ishizaka, 2000). However, there are studies in which the ADCs are consistent with our results (Fan et al., 2015; Oh et al., 2015; Sala et al., 2012).

Conflicting ADCs in the literature could be caused by differences in ROI placement, scanners, diffusion gradients, the b values used and fitting of ADC data.

Interestingly, we observed a significant correlation between the ADCs measured with WLsp-ROI and 3-year OS in Cox regression analysis. However, there was no difference in 1- or 2-year survival. ADCs did not correlate with recurrence-free survival. There are no previous reports on the significance of ADC in the prediction

of OC, but in cervical cancer lower ADCs significantly associate with worse survival (Miccò et al., 2014).

In our cohort, higher ADCs were associated with high VEGF protein expression in endothelial cells. Previously, it has been shown that VEGF expression is high already in the early stage of disease; it is not growing exponentially when the tumour grows (Martins et al., 2011). This could be a reason for the positive correlation between VEGF and ADC in our study. One previous study had shown that VEGF expression determined already in the early stage of disease showed prognostic value (Paley et al., 1997). In a study of colorectal cancer, increased VEGF expression was associated with well-differentiated tumours (Martins et al.).

VEGF expression has been shown to be higher in metastases than in primary tumours (Gadducci et al.). This is in line with our results; in this study VEGF protein expression was higher in metastases. The present study also shows that VEGF-C, VEGFR-1, -2, and -3 mRNA expression is higher in metastases than in related primary tumours. In a previous study, levels of VEGF-C, VEGF-D and VEGFR-3 proteins significantly increased in the presence of peritoneal metastases of OC outside the pelvis (Yokoyama et al., 2003). The presence of more mRNAs for angiogenic factors and their receptors may be expected when there is a need for accelerated neovascularization at metastatic sites. VEGF-C and its receptor VEGFR-3 are mediators of lymphangiogenesis (Joukov et al., 1996), and higher expression in metastatic lesions compared to primary tumours reveals the possible role of lymphangiogenesis in metastatic tumour spread.

The strength of the present study is the prospectively collected OC cohort with DWI-MRI and multiple histopathological and angiogenesis markers analysed immunohistochemically and with qRT-PCR. Interobserver correlations of the analyses used were substantial. However, there are no consistent guidelines for DWI-MR imaging of patients with OC. The imaging protocol of the present study generated ADC maps from three b values (including b = 0). Intravoxel incoherent motion (IVIM) is an imaging technique that makes separate estimations of tissue perfusion and diffusivity using multi-b-value DWI. Recently, implementation of IVIM with DWI has been studied, for example, in patients with cervical cancer (Zhou et al., 2016) and breast cancer (Cho et al., 2016) and has shown promise in improving the specificity of MRI. Unfortunately, our imaging protocol did not contain IVIM parameters. Additional limitations were the small study population and heterogeneous histological types of epithelial OC. However, in clinical situations, the cancer histology is not known pre-operatively, and it would be very beneficial if ADCs were useful in all histological types. We had to exclude four patients due to technical reasons in DWI-MRI and five from histological and qRT-PCR analyses due to neoadjuvant chemotherapy, which may have affected our results.

DWI, which is easily incorporated into standard MRI protocols, is a new promising tool for the diagnosis and follow-up of OC patients. In our cohort, there was a correlation between ADCs and histopathological prognostic markers and outcome. Our results indicate that WLsp-ROI can reproducibly be used to measure

ADC values, and that it can be used as a prognostic biomarker in OC. Larger scale studies are needed to confirm our observations and to clarify the prognostic value of DWI in patients with OC.

Acknowledgements

We thank Antti Lindgren, Eija Myöhänen, Helena Kemiläinen, and Tuomas Selander for their skillful technical assistance

5 PROGNOSTIC VALUE OF PREOPERATIVE DYNAMIC CONTRAST-ENHANCED

MAGNETIC RESONANCE IMAGING IN EPITHELIAL OVARIAN CANCER

5.1 ABSTRACT

Objectives

To investigate whether semi-quantitative and pharmacokinetic perfusion dynamic contrast-enhanced (DCE) parameters are associated with traditional prognostic factors and can predict clinical outcome in ovarian cancer (OC).

Methods

This prospective study, approved by local ethical committee, enrolled 38 patients with primary OC, 2011–2014. After preoperative DCE-MRI (3.0 T), two observers measured perfusion (K^trans, K^ep, V^e, V^p) and semi-quantitative parameters (area under the curve, peak, time-to-peak) by drawing regions of interest (ROIs) covering the large solid lesion (L-ROI) and the most enhancing small area (S-ROI) (NordicICE platform). Kruskal–Wallis was used to analyze associations between MRI parameters and classified prognostic factors.

Results

Mean K^trans values were higher in high-grade serous OC than in other types (L-ROI, P = 0.041; S-ROI, P = 0.018), and lower mean K^trans values predicted residual tumor (L-ROI P = .030; S-(L-ROI, P = 0.012). Higher minimum V^p values were associated with higher International Federation of Gynecology and Obstetrics (FIGO) stage (S-ROI, P = 0.023).Shorter recurrence-free survival was predicted by higher V^e (minimum L-ROI, P = 0.035; maximum S-ROI, P = 0.046), Vp (maximum S-ROI, P = 0.033), and lower time-to-peak (maximum S-ROI, P = 0.047) in Kaplan–Meier analysis. Multiparametric MRI variables combining DCE and diffusion weighted data were also predictive for survival.

Conclusion

DCE-MRI parameters may represent imaging biomarkers for predicting tumor aggressiveness and prognosis in OC. Higher K^trans levels were associated with better results in cytoreductive surgery but with earlier recurrence.

2Adapted with permission of European Journal of Radiology. A Lindgren, M Anttila, O Arponen et al. Eur J Radiol 2019, Prognostic Value of Preoperative Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Epithelial Ovarian Cancer. The tables and figures are modified from the original to correspond sequential numbers of this thesis.

5.2 INTRODUCTION

Ovarian cancer (OC) is the fifth most common cancer and fourth most common cause of cancer mortality in women (Ledermann et al., 2013). Characterizing ovarian masses as precisely as possible is important because treatment modalities are tailored individually, and especially during a woman’s reproductive years, conservative surgery for fertility-sparing can be crucial. Vaginal ultrasonography is the initial modality for investigating ovarian tumors, and the International Ovarian Tumor Analysis group guideline can be used to estimate the malignancy risks of ovarian tumors (Kaijser et al., 2013). Approximately 20% of ovarian tumors remain indeterminate after an ultrasound conducted by a specialist. Also the risk of malignancy index (RMI) helps physicians differentiate benign from malignant lesions (Tingulstad et al., 1996). Magnetic resonance imaging (MRI) is valuable especially in diagnostics of this indeterminate group in US and intermediate- and low-risk ovarian tumors (RMI < 200), giving better soft tissue contrast than computed tomography (CT). Also in ovarian cancer diagnostics MRI can yield more robust information than CT. Diffusion weighted imaging (DWI) has shown promise in tumor staging, predicting the aggressiveness of tumor and clinical outcome (Lindgren et al., 2017; Michielsen et al., 2017). Cancer treatment is becoming individualised, so it is important to further study the possibilities to obtain more information also in diagnostic imaging. If it was possible to identify patients who can be operated optimally in sytoreductive surgery and define the patient group with most aggressive tumors with preoperative imaging, it could be very valuable in the decision-making of treatment options.

Dynamic contrast-enhanced (DCE) MRI is used to improve the diagnostic accuracy of conventional MRI, with proven importance in differential diagnostics and preoperative evaluation for breast, prostate, and kidney tumors, among others (Ho et al., 2007; Koo et al., 2012; Ren et al., 2008). DCE-MRI can distinguish malignant from benign tumors based on differences in contrast agent behavior; in malignant tumors, the microcirculation is different because of neoangiogenesis (Paweletz and Knierim, 1989; Tofts et al., 1995). Most DCE-MRI studies of ovarian tumors have targeted differentiating among benign, borderline, and malignant tumors (Bernardin et al., 2012; Li et al., 2017; Thomassin-Naggara et al., 2008, 2012), and studies often have used semi-quantitative and time intensity curve–based parameters (Bernardin et al., 2012; Li et al., 2017; Thomassin-Naggara et al., 2008). European Society of Urogenital Radiology guidelines advocate inclusion of DCE time intensity curve analysis to specify indeterminate ovarian masses (Forstner et al., 2017).

Because the volume of transfer constant (K^trans) level is influenced by blood flow and vessel permeability properties, it has been under active investigation to be used as a biomarker of tumor perfusion and permeability in DCE-MRI cancer studies (Dickie et al., 2017; S. H. Kim et al., 2016; Li et al., 2011; Mitchell et al., 2010; Ovrebo et al., 2013; Taxt et al., 2012), with contradictory results. Also other pharmacokinetic

perfusion parameters reflect the physiology of circulation in the microvasculature and can be quantitatively compared among different patients and investigators (Cuenod and Balvay, 2013; Tofts et al., 1995). Therefore, DCE imaging might provide more extensive prognostic information in OC, as well.

We hypothesized that DCE parameters will differ between highly aggressive OC and less severe disease. The main objectives of the present study were to investigate whether semi-quantitative and perfusion DCE parameters are associated with traditional prognostic factors and able to predict the clinical course of OC. Our secondary objectives were to investigate the possible inter-technique differences related to ROI size and analyze interobserver variability in DCE measurements.