eprintid: 25709 rev_number: 18 eprint_status: archive userid: 4146 dir: disk0/00/02/57/09 datestamp: 2018-12-11 13:23:57 lastmod: 2019-01-18 10:35:54 status_changed: 2018-12-11 13:23:57 type: doctoralThesis metadata_visibility: show creators_name: Jiménez Franco, Luis David title: Development of a treatment planning algorithm for peptide-receptor radionuclide therapy considering multiple tumour lesions and organs at risk subjects: ddc-530 subjects: ddc-610 divisions: i-63500 adv_faculty: af-06 cterms_swd: Treatment Planning cterms_swd: PRRT cterms_swd: PBPK modelling cterms_swd: Molecular radiotherapy abstract: Peptide-receptor radionuclide therapy (PRRT) is a modality of molecular radiotherapy in which patients are administered with radiolabelled peptides targeting peptide-receptors overexpressed in some types of tumours. PRRT has shown promising results in the treatment of tumours with high expression of somatostatin receptors (e.g. neuroendocrine tumours (NETs) and meningioma). However, this therapeutic modality is limited by radiotoxicity in the kidneys and in the red bone marrow (RM). Therefore, to safely apply PRRT to patients, individualised treatment planning is required. Recently, it was shown that individually choosing an optimal combination of radiopharmaceutical amount and activity may lead to higher therapeutic indices (i.e. the ratio between the tumour dose and the dose in the dose-limiting organ). However, some additional features are required during treatment planning to achieve clinical applicability in PRRT: 1. Multiple tumour lesions/metastases need to be considered simultaneously. 2. Multiple potentially dose-limiting organs need to be included. 3. Constraints in the radiopharmaceutical synthesis need to be accounted for. Therefore, the aim of this work was to develop a clinically applicable treatment planning algorithm for PRRT. Furthermore, an in silico (i.e. based on computational simulations) clinical trial was conducted to demonstrate the applicability and advantages of the developed algorithm. The developed algorithm can be applied to patients with multiple metastases by using the developed concept of overall biologically effective dose (oBED). The tumour oBED, as developed in this work, is a biologically effective dose (BED) value representing the total number of killed tumour cells after radiotherapy. Therefore, maximising the tumour oBED during treatment planning will derive plans producing the maximum number of killed tumour cells among the considered tumour lesions. Additionally, the developed algorithm simultaneously incorporates multiple potentially dose-limiting organs and considers the maximum molar activity (i.e. the ratio between activity and amount) which can be achieved during the radiopharmaceutical synthesis. Thus, the developed treatment planning algorithm derives plans which maximise the total number of tumour cells within tolerated dose values for multiple organs at risk (OARs) while considering the maximum achievable molar activity in the radiopharmaceutical synthesis. An in silico clinical trial was conducted for 177Lu-DOTATATE using nine virtual patients (i.e. a physiologically-based pharmacokinetic (PBPK) model fitted to measured patient data). In this trial, plans individually derived with the developed algorithm were compared with the routinely delivered plan for 177Lu-DOTATATE. Comparison between the optimal plans and the typical plan showed that the optimal plans can produce much higher tumour control probability (oTCP) than the typical plan. Therefore, based on the expected advantages, the developed algorithm is proposed for clinical validation and potential future implementation. date: 2018 id_scheme: DOI id_number: 10.11588/heidok.00025709 fp7_project_id: 602306 ppn_swb: 1653711752 own_urn: urn:nbn:de:bsz:16-heidok-257090 date_accepted: 2018-09-10 advisor: HASH(0x55a9a6308008) language: eng bibsort: JIMENEZFRADEVELOPMEN2018 full_text_status: public citation: Jiménez Franco, Luis David (2018) Development of a treatment planning algorithm for peptide-receptor radionuclide therapy considering multiple tumour lesions and organs at risk. [Dissertation] document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/25709/1/PhD%20Thesis%20-%20Luis%20David%20Jimenez%20Franco.pdf