Lung cancer is the leading cause of cancer death in the Netherlands. For years chemotherapy was the only (palliative) treatment, with a short survival of only months. Since the introduction of... Show moreLung cancer is the leading cause of cancer death in the Netherlands. For years chemotherapy was the only (palliative) treatment, with a short survival of only months. Since the introduction of immunotherapy in 2015, this survival has increased significantly, with the first results showing a survival of even a few years. However, the response rate is relatively low, the treatment is expensive and the (low percentage of) side effects are severe. Therefore a biomarker is needed to predict which patients would benefit of immunotherapy.This thesis is about the search for a new biomarker. With the use of the RNA of platelets, proteins, tumor markers in blood and a an electronic nose for exhaled breath, we tried to find a non-invasive biomarker for the prediction of response on immunotherapy and for the (future) use in clinical practice, some of which are promising. Show less
This thesis consists of two sections. In Section I, (pre)clinical research investigating novel targets for pre- and intraoperative molecular imaging of pancreatic cancer are discussed. In Section... Show moreThis thesis consists of two sections. In Section I, (pre)clinical research investigating novel targets for pre- and intraoperative molecular imaging of pancreatic cancer are discussed. In Section II, various studies are described which lay the groundwork for further investigation into response monitoring and prediction in rectal cancer using various imaging modalities. Show less
Kalisvaart, G.M.; Berghe, T. van den; Grootjans, W.; Lejoly, M.; Huysse, W.C.J.; Bovée, J.V.M.G.; ... ; Bloem, J.L. 2023
ObjectiveTo identify which dynamic contrast-enhanced (DCE-)MRI features best predict histological response to neoadjuvant chemotherapy in patients with an osteosarcoma.MethodsPatients with... Show moreObjectiveTo identify which dynamic contrast-enhanced (DCE-)MRI features best predict histological response to neoadjuvant chemotherapy in patients with an osteosarcoma.MethodsPatients with osteosarcoma who underwent DCE-MRI before and after neoadjuvant chemotherapy prior to resection were retrospectively included at two different centers. Data from the center with the larger cohort (training cohort) was used to identify which method for region-of-interest selection (whole slab or focal area method) and which change in DCE-MRI features (time to enhancement, wash-in rate, maximum relative enhancement and area under the curve) gave the most accurate prediction of histological response. Models were created using logistic regression and cross-validated. The most accurate model was then externally validated using data from the other center (test cohort).ResultsFifty-five (27 poor response) and 30 (19 poor response) patients were included in training and test cohorts, respectively. Intraclass correlation coefficient of relative DCE-MRI features ranged 0.81–0.97 with the whole slab and 0.57–0.85 with the focal area segmentation method. Poor histological response was best predicted with the whole slab segmentation method using a single feature threshold, relative wash-in rate <2.3. Mean accuracy was 0.85 (95%CI: 0.75–0.95), and area under the receiver operating characteristic curve (AUC-index) was 0.93 (95%CI: 0.86–1.00). In external validation, accuracy and AUC-index were 0.80 and 0.80.ConclusionIn this study, a relative wash-in rate of <2.3 determined with the whole slab segmentation method predicted histological response to neoadjuvant chemotherapy in osteosarcoma. Consistent performance was observed in an external test cohort. Show less
Lubberink, M.; Direcks, W.; Emmering, J.; Tinteren, H. van; Hoekstra, O.S.; Hoeven, J.J. van der; ... ; Lammertsma, A.A. 2012
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