Grant: Discovery Grants Program - Individual
University of Western Ontario
$36,000.00
Lung brachytherapy needle guidance technique using a neural network/biomechanical model
EF 2011-12
Résumé
BACKGROUND: Lung cancer is a major health problem worldwide. Surgical resection is is the most invasive form of lung cancer treatment with significant post-operative mortality and morbidity rates. One type of effective and minimally invasive treatment option for lung cancer patients is brachytherapy. In brachytherapy, low dose radioisotopes (seeds) are placed permanently in the tumour. To be effective, the seeds must be implanted within the tumour tissue uniformly. A significant hurdles of lung brachytherapy is the tumour mobility which renders placing the seeds at the proper locations extremely difficult.
OBJECTIVES: The main focus of this research is to develop software component of a brachytherapy system responsible for guiding the brachytherpay needle. This oftware determines needle orientation, forces and trajectory of needle tip within the tissue for accurate targeting. This component will be designed such that it can be integrated with a robotic brachytherapy system.
SCIENTIFIC APPROACH: The tumour tissue displacement and deformation are caused by lung tissue deformation resulting from needle insertion and respiration. A novel technique (SFEM) we developed will be employed to predict tissue deformation associated with needle insertion. To determine tumour displacement caused by respiration, a Neural Network (NN) will be employed.
NOVEL ASPECTS: Lung brachytherapy is a novel concept and brachytherapy system development is still in its infancy. The technique tackles needle insertion in moving and deformable tissue. Novel contributions include using lung biomechanical model to simulate needle insertion; and using efficient SFEM model for tissue deformation simulation to make real-time navigation possible.
SIGNIFICANCE: The proposed brachytherapy guidance software will result in an accurate system leading to a very effective minimally invasive technique of lung cancer treatment. The system is expected to significantly reduce mortality and morbidity rates currently observed post-operatively.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
298338-2009
Name nom
Samani, Abbas
Department département
Electrical and Computer Engineering
Organization id
36
Institution établissement
University of Western Ontario
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2011
Competition year année de concours
2009
Award amount
36000
Program id
RGPIN
Program nane en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1053
Committee name en
Mechanical Engineering - A
Committee name fr
Génie mécanique - A
Area of application code
1102
Area of application group en
Health, education and social services
Area of application group fr
Santé publique, éducation et services sociaux
Area of application en
Biomedical engineering
Area of application fr
Génie biomédical
Research subject code
1900
Research subject group en
Biomedical engineering
Research subject group fr
Génie biomédical
Research subject en
Biomedical engineering
Research subject fr
Génie biomédical
Partie
3
Nb partie
5
Application title
Lung brachytherapy needle guidance technique using a neural network/biomechanical model
Keyword
NSERC
Application summary
BACKGROUND: Lung cancer is a major health problem worldwide. Surgical resection is is the most invasive form of lung cancer treatment with significant post-operative mortality and morbidity rates. One type of effective and minimally invasive treatment option for lung cancer patients is brachytherapy. In brachytherapy, low dose radioisotopes (seeds) are placed permanently in the tumour. To be effective, the seeds must be implanted within the tumour tissue uniformly. A significant hurdles of lung brachytherapy is the tumour mobility which renders placing the seeds at the proper locations extremely difficult.
OBJECTIVES: The main focus of this research is to develop software component of a brachytherapy system responsible for guiding the brachytherpay needle. This oftware determines needle orientation, forces and trajectory of needle tip within the tissue for accurate targeting. This component will be designed such that it can be integrated with a robotic brachytherapy system.
SCIENTIFIC APPROACH: The tumour tissue displacement and deformation are caused by lung tissue deformation resulting from needle insertion and respiration. A novel technique (SFEM) we developed will be employed to predict tissue deformation associated with needle insertion. To determine tumour displacement caused by respiration, a Neural Network (NN) will be employed.
NOVEL ASPECTS: Lung brachytherapy is a novel concept and brachytherapy system development is still in its infancy. The technique tackles needle insertion in moving and deformable tissue. Novel contributions include using lung biomechanical model to simulate needle insertion; and using efficient SFEM model for tissue deformation simulation to make real-time navigation possible.
SIGNIFICANCE: The proposed brachytherapy guidance software will result in an accurate system leading to a very effective minimally invasive technique of lung cancer treatment. The system is expected to significantly reduce mortality and morbidity rates currently observed post-operatively.
