Accurate, robust and harmonized implementation of morpho-functional imaging in treatment planning for personalized radiotherapy

Autor: E. Jimenez-Ortega, José Antonio Baeza, Antonio Leal, Ana Ureba, Amadeo Wals-Zurita, Francisco Javier García-Gómez, Marcin Balcerzyk, A.R. Barbeiro, Ángel Parrado-Gallego
Přispěvatelé: Junta de Andalucía, European Commission, Balcerzyk, Marcin, García Gómez, Francisco J., Leal, Antonio, Universidad de Sevilla. Departamento de Fisiología Médica y Biofísica, European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER), Balcerzyk, Marcin [0000-0001-6030-7416], García Gómez, Francisco J. [0000-0001-9307-5017], Leal, Antonio [0000-0002-0687-5305]
Rok vydání: 2018
Předmět:
Aperture
Computer science
medicine.medical_treatment
Science
Monte Carlo method
Computed tomography
Standardized uptake value
Image processing
Iterative reconstruction
computer.software_genre
030218 nuclear medicine & medical imaging
03 medical and health sciences
0302 clinical medicine
Robustness (computer science)
Fluorodeoxyglucose F18
Histogram
Positron Emission Tomography Computed Tomography
medicine
Humans
Precision Medicine
Radiation treatment planning
Image resolution
Multidisciplinary
medicine.diagnostic_test
Radiotherapy Planning
Computer-Assisted
Robust optimization
Radiotherapy Dosage
Cancer treatment
Radiation therapy
Functional imaging
Positron emission tomography
Head and Neck Neoplasms
030220 oncology & carcinogenesis
Medicine
Radiographic Image Interpretation
Computer-Assisted
Data mining
computer
Interpolation
Zdroj: Digital.CSIC. Repositorio Institucional del CSIC
instname
idUS. Depósito de Investigación de la Universidad de Sevilla
PLoS ONE, Vol 14, Iss 1, p e0210549 (2019)
ISSN: 1932-6203
Popis: In this work we present a methodology able to use harmonized PET/CT imaging in dose painting by number (DPBN) approach by means of a robust and accurate treatment planning system. Image processing and treatment planning were performed by using a Matlab-based platform, called CARMEN, in which a full Monte Carlo simulation is included. Linear programming formulation was developed for a voxel-by-voxel robust optimization and a specific direct aperture optimization was designed for an efficient adaptive radiotherapy implementation. DPBN approach with our methodology was tested to reduce the uncertainties associated with both, the absolute value and the relative value of the information in the functional image. For the same H&N case, a single robust treatment was planned for dose prescription maps corresponding to standardized uptake value distributions from two different image reconstruction protocols: One to fulfill EARL accreditation for harmonization of [18F]FDG PET/CT image, and the other one to use the highest available spatial resolution. Also, a robust treatment was planned to fulfill dose prescription maps corresponding to both approaches, the dose painting by contour based on volumes and our voxel-by-voxel DPBN. Adaptive planning was also carried out to check the suitability of our proposal. Different plans showed robustness to cover a range of scenarios for implementation of harmonizing strategies by using the highest available resolution. Also, robustness associated to discretization level of dose prescription according to the use of contours or numbers was achieved. All plans showed excellent quality index histogram and quality factors below 2%. Efficient solution for adaptive radiotherapy based directly on changes in functional image was obtained. We proved that by using voxel-by-voxel DPBN approach it is possible to overcome typical drawbacks linked to PET/CT images, providing to the clinical specialist confidence enough for routinely implementation of functional imaging for personalized radiotherapy.
This work was supported by the Junta de Andalucía (FISEVI, reference project CTS 2482) and the European Regional Development Fund (FEDER).
Databáze: OpenAIRE
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