IMPROVED STRATEGIES FOR RADIOTHERAPY OF PROSTATE CANCER UTILIZING PROTON THERAPY AND ADVANCED IMAGING MODALITIES
Prosjekt
- Prosjektnummer
- 90289400
- Ansvarlig person
- Kajsa Maria Linnéa Fridström
- Institusjon
- NTNU, NV-fakultetet, Institutt for fysikk
- Prosjektkategori
- Doktorgradsstipend, kjent kandidat
- Helsekategori
- Cancer
- Forskningsaktivitet
- 5. Treatment Developement, 6. Treatment Evaluation
Rapporter
The aim of this project is to imporove treatment of prostate cancer patients using advanced imaging techniques and biological modelling. The improved treatment will be done by giving different parts of the prostate different dose levels depending on tumor density. The treatment will be planned with state of the art photon and proton radiotherapyA model predicting Normal Tissue Complication Probability (NTCP) for rectal bother, based on available 3-year follow up data for prostate cancer patients, was developed. The model was fitted, based on the traditional Lyman-Kutcher-Burman (LKB) NTCP model.
The aim of the ongoing last sub-project is to perform a treatment planning study for high risk prostate cancer patients, where a customized MRI imaging procedure for this purpose is used. State of the art photon and proton radiotherapy treatment is used to investigate which treatment plan is beneficial in the given scenario. The treatment volume and aggressive subvolumes inside the prostate where local reoccurrence often appear, will be defined based on acquired image information for each patient. The dose to these subvolumes will be increased to higher dose than routinely used today, in order to increase Tumor Control Probability (TCP), and hence increased probability for local control, without compromising NTCP.
A subsidiary aim of the project was to test a MRI only workflow for radiotherapy treatment in the clinic today and to develop and evaluate a robust imaging procedure for additional treatment modalities to be used in planning of radiotherapy treatment for prostate cancer patients in the clinic. This included treatment planning on MRI instead of CT images that are more commonly used today. MRI only workflow is used clinically for photon prostate cancer treatment today but has not yet been established and dosimetrically verified for proton radiation. A MRI only workflow would remove registration errors between imaging modalities and reduce uncertainties for the defined treatment volumes. This project has been completed and results showed no clinically significant dose calculation errors for proton dose and that MRI-only therefor is feasible for the treatment field setup examined.
The aim of this project is to improve treatment of prostate cancer patients using advanced imaging techniques and biological modelling. The improved treatment will be done by giving different parts of the tumor different dose levels, so called dose painting. The treatment will be planned with state of the art photon and proton radiation treatmentAn aim of the project is to create a model predicting Normal Tissue Complication Probability (NTCP) based on available 3 year follow up data for prostate cancer patients. A model has been developed and parameters has been fitted, based on the traditional Lyman-Kutcher-Burman (LKB) NTCP model.
Another aim is to perform a treatment planning study for prostate cancer patients, where a customized PET and MRI imaging procedure for this purpose is used. The inclusion of patients is now 11 out of 20 patients. State of the art photon and proton radiotherapy treatment will be used to investigate which treatment plan is beneficial in the given scenario. The treatment volume, and aggressive subvolumes inside the prostate, will be defined based acquired image information for each patient. The subvolumes will be dose painted to a higher dose than routinely used today, to increase Tumor Control Probability (TCP) without compromising NTCP. A subsidiary aim of the project is to test MRI only workflow for radiotherapy treatment in the clinic today and to develop and evaluate a robust imaging procedure for additional treatment modalities to be used in planning of radiotherapy treatment for prostate cancer patients in the clinic. This includes treatment planning on MRI instead of CT images, that are commonly used today. MRI only workflow is used clinically for photon prostate cancer treatment today but has not been established and dosimetrically verified for protons. A MRI only workflow would remove registration errors between imaging modalities and reduce uncertainties for the defined treatment volumes.
The aim of this project is to improve treatment of prostate cancer patients using advanced imaging techniques and biological modelling. The improved treatment will be done by giving different parts of the tumor different dose levels, so called dose painting. The treatment will be planned with state of the art photon and proton radiation treatmentAn aim of the project is to create a model predicting tumor control probability (TCP) and Normal Tissue Complication Probability (NTCP) based on available 3 year follow up data for prostate cancer patients. A model has been developed and parameters has been fitted, based on the traditional Lyman-Kutcher-Burman (LKB) NTCP model. A framework has also partly been developed to relate patient reported side effects to radiotherapy dose and where it is administered in the patient.
The model will later be used to evaluate treatment plans in a treatment planning study for prostate cancer patients, where a customized PET and MRI imaging procedure for this purpose is used. The inclusion of patients for this study has started. State of the art photon and proton radiotherapy treatment will be used to investigate which treatment plan is beneficial in the given scenario. The treatment volume, and aggressive subvolumes inside the prostate, will be defined based acquired image information. The subvolumes will be dose painted to a higher dose than routinely used today, to increase TCP without compromising NTCP. A subsidiary aim of the project is to test and MRI only workflow for radiotherapy treatment in the clinic today and to develop and evaluate a robust imaging procedure for additional treatment modalities to be used in planning of radiotherapy treatment for prostate cancer patients in the clinic. This includes treatment planning on MRI instead of CT images, that are commonly used today. This would remove registration errors between imaging modalities and reduce uncertainties for the defined treatment volumes.
The aim of this project is to improve treatment of prostate cancer patients using advanced imaging techniques and biological modelling. The improved treatment will be done by giving different parts of the tumor different dose levels, so called dose painting. The treatment will be planned with state of the art photon and proton radiation treatmentAn aim of this project is to create a model predicting tumour control probability (TCP) and Normal Tissue Complication Probability (NTCP) based on available 3 year follow up data for prostate cancer patients. A model has been developed and parameters has been fitted, based on the traditional Lyman-Kutcher-Burman (LKB) NTCP model. The model will be further developed to include information about how dose in each voxel will influence the outcome of the patients.
The model will later be used to evaluate treatment plans in a treatment planning study for prostate cancer patients. The study will use state of the art photon and proton radiotherapy treatment in order to investigate which one is most beneficial in the given scenario. The treatment volume, and aggressive subvolumes inside the prostate, will be defined based on MRI and PET information. The subvolumes will be dose painted to a higher dose than routinely used today, in order increase TCP. A subsidiary aim of this project is to develop a robust imaging procedure for additional treatment modalities to be used in planning of radiotherapy treatment for prostate cancer patients in the clinic. This includes treatment planning on MRI instead of CT images, that are commonly used today. This would remove registration errors between modalities and reduce uncertainties for the treatment volumes
The aim of this project is to improve treatment of prostate cancer patients using advanced imaging techniques and biological modelling. The improved treatment will be done by giving different parts of the tumor different dose levels, so called dose painting. The treatment will be planned with state of the art photon and proton radiation treatment.At St.Olavs hospital today, treatment volumes for prostate cancer are mainly based on CT-images. The downside of CT images compared to MRI, is that soft tissue components are not as visible on CT as on MRI. A part of this project aims to use MR-only workflow and to exclude the use of CT in the radiotherapy treatment planning chain for prostate cancer, in order to get rid of registration errors. It will also be investigate how MRI-only workflow can improve the delivery of radiotherapy in each step. This will include investigations of the potential for dose painting and escalating the total dose to aggressive subvolumes of the prostate tumor. In order to only use MRI without CT, some issues need to be addressed, like inherent geometric uncertainty in MRI. In radiotherapy the geometry needs to be accurate in order to plan the radiation dose in the right location, especially relevant in this project where we intend to dosepaint small subvolumes inside the tumor. Preparations to address this problem has been made, and the geometry of the MRI has been validated. Further, the planning process on MRI is not straightforward and the correctness of the radiation dose has therefore been investigated with two different approaches for the available systems.
The aim of this project is to improve treatment of prostate cancer patients using advanced imaging techniques and biological modelling. The improved treatment will be done by giving different parts of the tumor different dose levels, dose painting. The treatment will be planned with state of the art photon and proton radiation treatment.The primary aim of this project is to improve radiotherapy of prostate cancer patients, which constitute a significant proportion of the group of patients receiving radiotherapy, by using advanced imaging modalities. Reliable models for predicting tumor control and normal tissue side- effects (early and late effects) of radiotherapy treatment techniques will be developed and used to evaluate the potential benefit of improved radiotherapy strategies. First, based on clinical and radiotherapy data already collected at St. Olavs hospital, we will estimate required input parameters for developing such models. Second, the models will be applied in a feasibility study for prostate cancer to predict probabilities for tumor control and risk of side-effects based on treatment plans for photon- and proton radiotherapy. This will provide a basis for evaluating the potential benefit from proton therapy in prostate cancer.
A subsidiary aim is to investigate improvements of radiotherapy delivery by optimizing the target volume based on MRI instead of CT. This will include investigations of the potential for escalating the total dose to aggressive subvolumes of the prostate tumor, and increased fraction doses for more focal treatment. In an ongoing prostate cancer study, functional MRI (diffusion-weighted MRI and dynamic contrast-enhanced MRI) are performed in addition to the conventional morphologic MRI sequences. This subsidiary aim will include investigations of the potential added value of these MR sequences to identify aggressive subvolumes within the prostate cancer that should receive increased doses. The use of MRI in treatment planning will also be implemented into the prediction models in order to enable investigations of the benefit of protons versus photons in the context of both CT- and MR-guided radiotherapy.
The work so far has primary been concentrated to the first aim to develop evaluation models to predict tumor control and normal tissue side- effects. Litterature and Methods has been investigated and discussed to find a suitable and inovative approach to achive results
Deltagere
- Kajsa Maria Linn Fridström Doktorgradsstipendiat
- Kathrine Redalen Hovedveileder
- Signe Danielsen Medveileder, biveileder
- Torgrim Tandstad Medveileder, biveileder
- Pål Erik Goa Medveileder, biveileder
- Sigrun Saur Almberg Medveileder, biveileder
eRapport er utarbeidet av Sølvi Lerfald og Reidar Thorstensen, Regionalt kompetansesenter for klinisk forskning, Helse Vest RHF, og videreutvikles av de fire RHF-ene i fellesskap, med støtte fra Helse Vest IKT
Alle henvendelser rettes til Helse Midt-Norge RHF - Samarbeidsorganet og FFU