De rol van diffusie-gewogen MRI van het volledige lichaam bij patiënten met eierstokkanker

Ovarian cancer is the second most lethal gynaecological cancer in women and is often referred to as ‘the silent killer’ because it often spreads throughout the abdomen without causing symptoms. As a consequence, most patients are diagnosed with extensive peritoneal disease and/or distant metastases. Primary debulking surgery (PDS) is the main treatment for ovarian cancer with complete macroscopic tumour resection (R0 resection) as the most important prognostic factor. If disease extent precludes upfront radical surgery, neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS) represents an alternative for patients with advanced-stage disease. But despite high complete resection rates after surgical debulking, most patients ultimately suffer from tumour recurrence with a 5-year survival of only 40%. The diagnosis and follow-up of patients with ovarian cancer partly relies on medical imaging but there is an obvious unmet clinical need related to the imaging of ovarian cancer. In ovarian cancer, imaging should aim to identify patients unfit for surgery, either at primary diagnosis, after NACT and in the recurrent setting. In addition, pretreatment prognostic imaging biomarkers should aim to individualize therapeutic decisions. Although 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) has an incremental benefit over CT for the detection of lymphadenopathies and distant metastases, both may underestimate peritoneal disease load. In particular, mesenteric and serosal bowel disease dissemination which is necessary for operability assessment, is often underestimated with CT and FDG-PET/CT. Therefore often surgical staging with diagnostic open laparoscopy is necessary for prediction of complete resection. Diffusion-weighted imaging provides image contrast based on water molecule movement allowing functional characterization of reflecting tissue microstructural properties on a cellular level. This high image contrast with millimetric spatial resolution of DWI allow visual depiction of small tumour deposits. In addition, DWI can be quantified by the apparent diffusion coefficient (ADC). The combination of diffusion-weighted imaging (DWI) with contrast-enhanced magnetic resonance imaging (MRI) has already been demonstrated to show a high accuracy of detection of PC and staging. Because at least 11% of ovarian cancer patients present with distant metastases at primary diagnosis and up to 22% in the recurrent setting, the development of whole body diffusion-weighted MRI (WB-DWI/MRI) is justified. In this thesis work, we explored the potential of whole body diffusion-weighted MRI (WB-DWI/MRI) to improve the workup of patients with ovarian cancer in seven experiments. In a first study, we assessed the clinical feasibility of WB-DWI/MRI in 32 patients suspected for ovarian cancer, in comparison with CT and FDG-PET/CT. We prospectively validated the interpretation criteria and diagnostic value of WB-DWI/MRI with pathology after surgery as reference standard. We demonstrated that the main gains of using WB-DWI/MRI were the detection of bowel serosal and mesenteric disease, important towards operability, with a higher accuracy of detecting peritoneal disease compared with CT and FDG-PET/CT. In addition, we showed that distant metastases were detected by WB-DWI/MRI with equal accuracy to FDG-PET/CT. The proposed imaging protocol was afterwards implemented in the other clinical studies in this thesis work. In a second study, the reproducibility of WB-DWI/MRI for the assessment of primary tumour origin, tumour characterization, staging and prediction of complete resection was validated. We observed a fair to perfect interobserver agreement for WB-DWI/MRI with a minimal training of a general radiologist without previous experience in WB-DWI/MRI. In contrast, the interobserver agreement for CT between two abdominal radiologists was somewhat lower. We therewith demonstrated the applicability of and reproducibility of WB-DWI/MRI. Third, a prospective superiority study was conducted in 166 patients with suspected ovarian cancer for prediction of complete resection. As the goals for preoperative staging of ovarian cancer are [1] the confirmation of a malignant mass, [2] the exclusion of non-ovarian primary tumours, [3] the assessment of disease extent and [4] the prediction of R0 resection, we compared the diagnostic accuracy of WB-DWI/MRI compared to CT for these 4 aims. We showed that WB-DWI/MRI showed higher accuracy for characterization of malignancy, identification of patients with primary non-ovarian cancer, staging and prediction of R0 resection, compared to CT. We therefore concluded that WB-DWI/MRI has an incremental value for individualized preoperative staging in suspected ovarian cancer and can therefore be an alternative for CT. As it generally believed that the prediction of optimal surgery is difficult based on imaging alone, we set up a fourth prospective non-inferiority study to compare the diagnostic accuracies of WB-DWI/MRI versus CT in combination visual assessment during diagnostic open laparoscopy for assessment of primary tumour origin, tumour characterization, staging and prediction of R0 resection. The main finding this study was the non-inferiority of WB-DWI/MRI for accurate prediction of R0 resection compared to DOL-CT. This was accompanied with significantly non-inferior accuracy for assessment of primary tumour origin, tumour characterization, identification of patients with non-ovarian primary cancer and assessment of disease extent according to FIGO staging and suggests that WB-DWI/MRI can be considered for operability assessment in patients suspected with ovarian cancer. In a fifth experiment, the prognostic value of first –and second order statistics was compared to the average ADC derived from pretreatment WB-DWI/MRI ADC histogram towards disease free (DFS) and overall survival (OS) in advanced-stage ovarian cancer. We showed that first –and second order statistical features from the 2D histogram derived from WB-DWI/MRI images were associated with survival in advanced-stage ovarian cancer and could provide prognostic non-invasively derived biomarkers to tailor personalized medicine. In experiment 6, we evaluated WB-DWI/MRI after neoadjuvant chemotherapy to predict R0 resection and to discriminate long –and short-term survival among patients with extensive advanced-stage ovarian cancer. From this study, we concluded that WB-DWI/MRI could accurately predict R0 resection after NACT. The last part of this thesis work focused on the prospective evaluation of WB-DWI/MRI compared to CT for detection, restaging and operability assessment in patients with suspected ovarian cancer recurrence. We showed that besides a significantly higher accuracy for tumour detection and improved sensitivity for per-site analysis of disease extent, WB-DWI/MRI showed better sensitivity for assessing disease extent critical towards operability, particularly for mesenteric root infiltration, small bowel and colon carcinomatosis, high volume peritoneal disease and irresectable distant metastases, compared to CT. As a consequence, WB-DWI/MRI was superior for prediction of complete cytoreduction as compared to CT. Although the results of this thesis contribute to establish the role of WB-DWI/MRI in ovarian cancer, future research and further standardization is warranted to gain acceptance for WB-DWI/MRI as a clinically valid and applicable imaging technique.Acknowledgements List of abbreviations Preface Chapter 1: General introduction and aims 1.1 Clinical aspects of ovarian cancer 1.1.1 Epidemiology and classification 1.1.2 Symptoms and diagnosis 1.1.3 Treatment 1.1.3.1 Surgery 1.1.3.2 Chemotherapy 1.1.3.3 Recurrent disease 1.1.4 Prognosis 1.2 State-of-the art imaging in the diagnosis and follow-up of ovarian carcinoma 1.2.1 Ultrasound 1.2.2 Computed tomography (CT) 1.2.3 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) 1.2.4 Conventional MRI versus diffusion-weighted MRI 1.2.5 Rationale for whole body diffusion-weighted MRI 1.3 Aims and endpoints of the thesis Chapter 2: Patient population and imaging techniques 2.1 Patient population and power analyses 2.2 General principles of MRI 2.3 The biophysical basis of diffusion-weighted MRI 2.4 Concise review of the role of diffusion-weighted MRI in ovarian cancer 2.5 Whole body diffusion-weighted MRI Chapter 3: Whole-body diffusion-weighted MRI for staging of patients with suspected ovarian cancer: a clinical feasibility study in comparison to CT and FDG-PET/CT 3.1 Abstract 3.2 Introduction 3.3 Materials and Methods 3.3.1 Patients and selection of treatment 3.3.2 Imaging techniques 3.3.2.1 Computed tomography 3.3.2.2 FDG-PET/CT 3.3.2.3 WB-DWI/MRI 3.3.3 Interpretation of imaging 3.3.4 Reference standard 3.3.5 Statistical analysis 3.4 Results 3.4.1 Patients 3.4.2 Site-based analysis 3.4.3 Patient-based analysis and clinical impact 3.5 Discussion Chapter 4: Reproducibility of WB-DWI/MRI for assessment of primary tumour site, tumour characterization, staging and prediction of complete resection 4.1 Abstract 4.2 Introduction 4.3 Patients and Methods 4.3.1 Patients 4.3.2 Imaging techniques and interpretation criteria 4.3.3 Reference standard 4.3.4 Statistical analysis 4.4 Results 4.4.1 Patient characteristics 4.4.2 Interobserver reliability 4.5 Discussion Chapter 5: Whole body diffusion-weighted magnetic resonance imaging compared to computed tomography for prediction of complete resection in ovarian cancer: a prospective diagnostic study in 167 patients 5.1 Abstract 5.2 Introduction 5.3 Patients and methods 5.3.1 Participants 5.3.2 WB-DWI/MRI scanning 5.3.3 CT scanning 5.3.4 Image evaluation 5.3.5 Standard of reference 5.3.6 Statistical analyses 5.4 Results 5.4.1 WB-DWI/MRI versus CT: confirmation of malignant adnexal mass irrespective of origin 5.4.2 WB-DWI/MRI versus CT: exclusion of a primary site other than primary ovarian cancer 5.4.3 WB-DWI/MRI versus CT: FIGO staging and prediction of complete resection 5.5 Discussion Chapter 6: Whole body diffusion-weighted MRI is equally effective as laparoscopy in combination with CT for prediction of complete debulking surgery in ovarian carcinoma 6.1 Abstract 6.2 Introduction 6.3 Materials and methods 6.3.1 Patients 6.3.2 Whole body diffusion-weighted MRI 6.3.3 DOL-CT 6.3.4 Image analysis 6.3.5 Reference standard 6.3.6 Statistical analysis 6.4 Results 6.4.1 Patient characteristics 6.4.2 Assessment of primary tumour site and tumour characterization 6.4.3 Assessment of disease extent according to FIGO stage 6.4.4 Prediction of R0 resection 6.5 Discussion Chapter 7: The prognostic value of pretreatment ADC histogram analysis with first- and second order statistics in patients with advanced ovarian carcinoma: initial findings 7.1 Abstract 7.2 Introduction 7.3 Materials and methods 7.3.1 Patients 7.3.2 Documentation of clinical data 7.3.3 Imaging technique 7.3.5 Lesion evaluation and ADC histograms 7.3.6 Statistical analysis 7.4 Results 7.4.1 Patients 7.4.2 ROC analysis 7.4.3 Survival analysis 7.5 Discussion Chapter 8: Prospective evaluation of WB-DWI/MRI after neoadjuvant chemotherapy to predict complete resection in advanced stage ovarian carcinoma 8.1 Abstract 8.2 Introduction 8.3 Materials and methods 8.3.1 Patients 8.3.2 Imaging technique 8.3.3 WB-DWI/MRI interpretation 8.3.4 Standard reference 8.3.5 Statistical analysis 8.4 Results 8.4.1 Patients 8.4.2 Prediction of complete resection 8.5 Discussion Chapter 9: Whole body MRI including diffusion-weighted imaging for detection, staging and operability assessment of recurrent ovarian cancer: additional value to computed tomography 9.1 Abstract 9.2 Introduction 9.3 Patients and methods 9.3.1 Patients 9.3.2 CT scanning 9.3.3 WB-DWI/MRI scanning 9.3.4 CT image interpretation 9.3.5 WB-DWI/MRI image interpretation 9.3.6 Reference standard 9.3.7 Data analysis 9.4 Results 9.4.1 Patients 9.4.2 Detection of recurrence 9.4.3 Prediction of surgery to no residual tumour: WB-DWI/MRI versus CT 9.5 Discussion Chapter 10: General summary and future perspectives 10.1 Introduction 10.2 Summary of the main findings in this work 10.2.1 Assessment of primary tumour site, tumour characterization, staging and prediction of R0 resection in primary ovarian cancer 10.2.2 Reproducibility of WB-DWI/MRI for clinical applications 10.2.3 Predictive value of pretreatment ADC histogram parameters towards disease free and overall survival in advanced stage ovarian cancer 10.2.4 Prediction of R0 resection after neoadjuvant chemotherapy for stage III and IV ovarian cancer 10.2.5 Detection, restaging and operability assessment in recurrent ovarian cancer 10.3 Relevance, advantages and limitations of this work 10.4 Future perspectives 10.5 Conclusion Abstract Bibliography Curriculum Vitaenrpages: 248status: publishe