Objective 1. Multimodal imaging for fast radioembolisation therapy of liver cancer (addressed by WP1, WP2, WP6): The software that will support the application of the current hybrid C-arm prototype (for the IXSI-2 study) is nearing completion. During the next reporting period, the software will undergo intensive testing. The first steps were taken to solve the limitations of the combined X-ray imager/gamma camera used in the current hybrid C-arm prototype. A detailed simulation model of the hybrid C-arm was performed and tested with the standard scintillator, as well as a long list of low-afterglow scintillation materials that could potentially be used instead of the standard scintillator – leading to a shortlist of the most promising material candidates. A clinical study has been prepared to generate evidence on the potential of angiotensin injection to further improve the efficiency of radioembolisation.
Objective 2. Multimodal thermal ablation therapy for liver cancer (addressed by WP1, WP3, WP6): A systematic literature review was performed to develop computational models supporting optimal treatment decisions and prediction of re-occurrence. A large European observational cohort study (A-IMAGIO) with retro- and prospective data has been set up and undergoing approval at several clinical sites. Research has been performed on tools to predict the ablation zone accurately. The effectiveness of the BioXmark markers in determining the actual tissue shrinkage was tested. LUMC developed a method based on deep learning segmentation algorithms to automatically evaluate the ablation treatment success, trained with existing data. For the same purpose, UM investigated using a multimodality method combining pre-ablation MRI of the tumour and post-ablation CT (post-operatively ablated volumes).
Objective 3. Multimodal diagnosis and therapy for early-stage lung cancer (addressed by WP1, WP4): A first design has been made to support eliciting the values individuals attach to different diagnostic and therapeutic strategies and the corresponding expected health outcomes. PMS developed novel imaging protocols and intra-operative guidance to improve the imaging capabilities of the CBCT-guided navigation bronchoscopy procedure. JPNV delivered prototype steerable catheters, further successfully evaluated and validated for usability and accuracy with the Radboud in two cadaver labs. A study initiation package was prepared for its clinical validation (ACTIFLEX). Progress has been made towards developing instant, detailed, and 3D histologic analysis of pathology through higher harmonic generation (HHG) microscopy and artificial intelligence (AI). Data collection to validate HHG images against HE images started in VU and Radboud (VALIDIAG study, >100 biopsy specimens). An AI algorithm for malignancy detection was developed using an existing dataset from the VU. A novel multiplex immunohistochemistry (IHC) staining methodology is being developed by ETHZ, to enable further analysis of the tumour microenvironment for novel biomarkers. Immuno-PET imaging will be developed to evaluate the patients' response to immune therapies. A delay in the regulatory strategy regarding the IO treatment arm initially planned for the study caused a re-evaluation of possible treatment substrates. Slight timeline adjustments were brought to the initial plan (GA amendment).
Objective 4. Multimodal MR-HIFU-enabled therapy for sarcoma (addressed by WP1, WP5, WP6): A prototype for a versatile and flexible MR-HIFU platform was developed and built and initial tests for the delivery of ablation have been performed. A tool for automated segmentation of the subcutaneous fat from MR images has been developed and tested. Motion fields from MR acquisitions that feed into motion correction strategies were assessed. In addition, research into improved 4D sampling strategies was started to support more accurate treatment planning. Initial preclinical experiments in phantoms and ex-vivo tissue have been performed, and in-vivo animal experiments have been prepared. The clinical study is in preparation.
