A stochastic approach to estimate the uncertainty of dose mapping caused by uncertainties in b-spline registration

• Verfasst von: Hub, Martina [VerfasserIn]
• Verfasst von: Thieke, Christian [VerfasserIn]
• Verfasst von: Kessler, Marc L. [VerfasserIn]
• Verfasst von: Karger, Christian P. [VerfasserIn]
• Titel: A stochastic approach to estimate the uncertainty of dose mapping caused by uncertainties in b-spline registration
• Verf.angabe: Martina Hub, Christian Thieke, Marc L. Kessler, Christian P. Karger
• E-Jahr: 2012
• Jahr: April 2012
• Umfang: 7 S.
• Fussnoten: Gesehen am 08.11.2018
• Titel Quelle: Enthalten in: Medical physics
• Ort Quelle: Hoboken, NJ : Wiley, 1974
• Jahr Quelle: 2012
• Band/Heft Quelle: 39(2012), 4, Seite 2186-2192
• ISSN Quelle: 2473-4209
• ISSN Quelle: 1522-8541
• DOI: doi:10.1118/1.3697524
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: accuracy
• Sach-SW: b-spline registration
• Sach-SW: Computed tomography
• Sach-SW: deformation
• Sach-SW: Digital computing or data processing equipment or methods
• Sach-SW: dose accumulation
• Sach-SW: dose mapping
• Sach-SW: dosimetry
• Sach-SW: Dosimetry
• Sach-SW: Dosimetry/exposure assessment
• Sach-SW: fractionated radiation therapy
• Sach-SW: Image data processing or generation
• Sach-SW: Image guided radiation therapy
• Sach-SW: image registration
• Sach-SW: Image registration
• Sach-SW: in general
• Sach-SW: including brachytherapy
• Sach-SW: Lungs
• Sach-SW: medical image processing
• Sach-SW: Medical image spatial resolution
• Sach-SW: Medical imaging
• Sach-SW: Numerical modeling
• Sach-SW: physiological models
• Sach-SW: pneumodynamics
• Sach-SW: radiation therapy
• Sach-SW: Radiation therapy
• Sach-SW: Registration
• Sach-SW: specially adapted for specific applications
• Sach-SW: stochastic processes
• Sach-SW: Stochastic processes
• Sach-SW: Therapeutic applications
• Sach-SW: uncertainty
• Sach-SW: Vector fields
• K10plus-PPN: 1582696438

Abstract

Purpose: In fractionated radiation therapy, image guidance with daily tomographic imaging becomes more and more clinical routine. In principle, this allows for daily computation of the delivered dose and for accumulation of these daily dose distributions to determine the actually delivered total dose to the patient. However, uncertainties in the mapping of the images can translate into errors of the accumulated total dose, depending on the dose gradient. In this work, an approach to estimate the uncertainty of mapping between medical images is proposed that identifies areas bearing a significant risk of inaccurate dose accumulation. Methods: This method accounts for the geometric uncertainty of image registration and the heterogeneity of the dose distribution, which is to be mapped. Its performance is demonstrated in context of dose mapping based on b-spline registration. It is based on evaluation of the sensitivity of dose mapping to variations of the b-spline coefficients combined with evaluation of the sensitivity of the registration metric with respect to the variations of the coefficients. It was evaluated based on patient data that was deformed based on a breathing model, where the ground truth of the deformation, and hence the actual true dose mapping error, is known. Results: The proposed approach has the potential to distinguish areas of the image where dose mapping is likely to be accurate from other areas of the same image, where a larger uncertainty must be expected. Conclusions: An approach to identify areas where dose mapping is likely to be inaccurate was developed and implemented. This method was tested for dose mapping, but it may be applied in context of other mapping tasks as well.