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107 Image, Dose and Anatomy Processing for Adaptive Radiotherapy
$58
Tuesday, September 27, 2005 Proffered Papers Imaging
for RT I
107 Image, Dose and Anatomy Processing for Adaptive Radiotherapy M. Kessler, W. Keranen, M. Roberson, D. McShan The University of Michigan Medical School, Radiation Oncology, Ann Arbor, MI, USA Introduction:
Adaptive radiotherapy involves the acquisition and registration of multiple 3D/4D image datasets, delineation of relevant anatomy from these data and the computation of cumulative dose distributions that incorporate changes in anatomy. In order to address the challenges of managing this explosion of data and new processing requirements, we have developed a system to automate and streamline many aspects of the adaptive radiotherapy process. Methods: The system consists of set of independent components with well-defined data interfaces and a flow executive that sequences the processing of data across components. The major components of the system include data access, rigid and deformable image registration, data mapping, dose accumulation and a knowledge base to maintain a consistent and up-to-date representation of the patient data. The data access/prep component retrieves and pushes information to and from a variety of data stores and other components. The image registration component supports various transformation models (rotate-translate, full affine, and spline-based deformations) and intensity-based similarity metrics (sum-of-squared differences and mutual information) and can handle both global and multi-regional registrations. Initialization steps for registrations can be automated using both site-specific protocols and data-driven image processing. In order to overcome limitations in current standards-based data representations (e.g. DICOM), a generalized transformation representation was developed to provide interoperability between processing components. The data mapping component operates on geometry and voxel-based information such as tissue boundaries, computed doses and image volumes. The dose accumulation component accommodates different re-sampling and summing schemes. Many of these components use a common toolkit of algorithms and data structures which was originally developed as part of our in-house treatment planning system, UMPlan. Results: A flexible system that automates many of the steps involved in adaptive radiotherapy has been designed and implemented. This system has been used to map and integrate dose and geometric information from a variety of image studies (serial and 4D CT, multimodality data) and clinical sites (brain, lung, liver, and prostate). Conclusions: Automation of data processing to support the adaptive radiotherapy process is possible for a wide variety of clinical sites and imaging situations, This automation should make more widespread adoption of adaptive radiotherapy possible, Supported by NIH P01-CA59827
108 An investigation into the efficacy of automatic marker detection methods applied to intra-fractional prostate motion tracking, H. McNairI, E. Harris 2, P. Evans 2 1Royal Marsden Hospital, Department of Radiotherapy, Sutton, UK 2Institute of Cancer Research, Joint Physics Department, Sutton, UK This work summarises the results of an investigation into the
feasibility of automatically extracting the position of gold 'seeds' implanted into the prostate for automated 'on-line' correction of patient set-up errors and real-time tracking of intra-fractional prostate movement. To date 26 patients have had up to 3 cylindrical gold 'seeds' (length: 8mm, diameter: l m m ) implanted into their prostate. Lateral and AP electronic portal images were taken prior to the first 4 fractions and once weekly thereafter. Lateral and AP movie loop images were also acquired during these treatments. Images were acquired using Elekta iView, a flat panel based portal imaging system. Four methods, for the automatic extraction of gold seeds were used. The first uses a seed template or "marker extraction kernel" based upon work published by Nederveen et al. (IJROBP 47(5), 2000). Similarly, the second method uses a template that is derived from a 2D cylindrical Mexican hat filter. Both methods have been adapted to incorporate a-priory knowledge of the seed orientation and locality taken from patient DRRs. These templates are convolved with the image and the positions of local maxima that correspond to the greatest match between the template and the image are found. The third technique has been adapted from work described by Aubin et al. (Med. Phys. 30(7), 2003) in which the image is subject to local histogram equalisation and a contrast filter to enhance marker contrast before locating local m i n i m a , The minima that represent the seeds are then selected on the basis of knowledge of the spatial relationship between the seeds obtained from the DRR. Finally, detection of the gold seeds was performed using templates extracted from the initial patient set up images. Three small regions of interest containing one gold seed are identified and extracted from the set up image. These are then cross-correlated with an image in order to find the seed position. To date 56 lateral and 30 AP movie frames and 36 set-up images from 5 patients have been processed in this manner. Work is continuing to obtain detection efficiencies across the entire data set. The first three methods gave detection efficiencies of up to 91% for AP images and less than 50% for lateral images. These methods are therefore unsuitable for the automatic extraction of gold seeds and tracking the gold seeds during radiotherapy. Using templates from patient set-up images, detection efficiencies of 100% (AP) and 97% (tAT) were obtained in which the position of the marker can be found with to an accuracy of +/- 0.86mm. This work indicates that for the first treatment fraction a truly automated calculation of patient set-up errors is currently unrealistic. However, using templates extracted from set-up images acquired at the beginning of treatment, detection efficiencies are much higher, therefore showing that this method can be applied to the tracking of intra-fraction prostate movement. 109
Improved procedure for automatic prostate localization on cone-beam CT scans M. Smitsmans 1, J. de Bois I, J. Sonke 1, A. Betgen I, L. Zijp I, D.
Jaffra;, J. Lebesque 1, M. van Herk 1 1The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Radiation Oncology, Amsterdam, The Netherlands 2princess Margaret Hospital - Ontario Cancer Institute, Radiation Medicine Programme, Toronto, Canada
Introduction:
We previously developed an algorithm for automatic prostate localization based on gray value registration (GR) of CT scans. In combination with an on-line cone-beam CT (CBCT) scan this method provides an opportunity to efficiently detect and correct for the prostate position prior to radiotherapy treatment. The aim of this study was to test the algorithm and optimize the procedure for CBCTs.
Tuesday, September 27, 2005 Proffered Papers Imaging
for RT I
107 Image, Dose and Anatomy Processing for Adaptive Radiotherapy M. Kessler, W. Keranen, M. Roberson, D. McShan The University of Michigan Medical School, Radiation Oncology, Ann Arbor, MI, USA Introduction:
Adaptive radiotherapy involves the acquisition and registration of multiple 3D/4D image datasets, delineation of relevant anatomy from these data and the computation of cumulative dose distributions that incorporate changes in anatomy. In order to address the challenges of managing this explosion of data and new processing requirements, we have developed a system to automate and streamline many aspects of the adaptive radiotherapy process. Methods: The system consists of set of independent components with well-defined data interfaces and a flow executive that sequences the processing of data across components. The major components of the system include data access, rigid and deformable image registration, data mapping, dose accumulation and a knowledge base to maintain a consistent and up-to-date representation of the patient data. The data access/prep component retrieves and pushes information to and from a variety of data stores and other components. The image registration component supports various transformation models (rotate-translate, full affine, and spline-based deformations) and intensity-based similarity metrics (sum-of-squared differences and mutual information) and can handle both global and multi-regional registrations. Initialization steps for registrations can be automated using both site-specific protocols and data-driven image processing. In order to overcome limitations in current standards-based data representations (e.g. DICOM), a generalized transformation representation was developed to provide interoperability between processing components. The data mapping component operates on geometry and voxel-based information such as tissue boundaries, computed doses and image volumes. The dose accumulation component accommodates different re-sampling and summing schemes. Many of these components use a common toolkit of algorithms and data structures which was originally developed as part of our in-house treatment planning system, UMPlan. Results: A flexible system that automates many of the steps involved in adaptive radiotherapy has been designed and implemented. This system has been used to map and integrate dose and geometric information from a variety of image studies (serial and 4D CT, multimodality data) and clinical sites (brain, lung, liver, and prostate). Conclusions: Automation of data processing to support the adaptive radiotherapy process is possible for a wide variety of clinical sites and imaging situations, This automation should make more widespread adoption of adaptive radiotherapy possible, Supported by NIH P01-CA59827
108 An investigation into the efficacy of automatic marker detection methods applied to intra-fractional prostate motion tracking, H. McNairI, E. Harris 2, P. Evans 2 1Royal Marsden Hospital, Department of Radiotherapy, Sutton, UK 2Institute of Cancer Research, Joint Physics Department, Sutton, UK This work summarises the results of an investigation into the
feasibility of automatically extracting the position of gold 'seeds' implanted into the prostate for automated 'on-line' correction of patient set-up errors and real-time tracking of intra-fractional prostate movement. To date 26 patients have had up to 3 cylindrical gold 'seeds' (length: 8mm, diameter: l m m ) implanted into their prostate. Lateral and AP electronic portal images were taken prior to the first 4 fractions and once weekly thereafter. Lateral and AP movie loop images were also acquired during these treatments. Images were acquired using Elekta iView, a flat panel based portal imaging system. Four methods, for the automatic extraction of gold seeds were used. The first uses a seed template or "marker extraction kernel" based upon work published by Nederveen et al. (IJROBP 47(5), 2000). Similarly, the second method uses a template that is derived from a 2D cylindrical Mexican hat filter. Both methods have been adapted to incorporate a-priory knowledge of the seed orientation and locality taken from patient DRRs. These templates are convolved with the image and the positions of local maxima that correspond to the greatest match between the template and the image are found. The third technique has been adapted from work described by Aubin et al. (Med. Phys. 30(7), 2003) in which the image is subject to local histogram equalisation and a contrast filter to enhance marker contrast before locating local m i n i m a , The minima that represent the seeds are then selected on the basis of knowledge of the spatial relationship between the seeds obtained from the DRR. Finally, detection of the gold seeds was performed using templates extracted from the initial patient set up images. Three small regions of interest containing one gold seed are identified and extracted from the set up image. These are then cross-correlated with an image in order to find the seed position. To date 56 lateral and 30 AP movie frames and 36 set-up images from 5 patients have been processed in this manner. Work is continuing to obtain detection efficiencies across the entire data set. The first three methods gave detection efficiencies of up to 91% for AP images and less than 50% for lateral images. These methods are therefore unsuitable for the automatic extraction of gold seeds and tracking the gold seeds during radiotherapy. Using templates from patient set-up images, detection efficiencies of 100% (AP) and 97% (tAT) were obtained in which the position of the marker can be found with to an accuracy of +/- 0.86mm. This work indicates that for the first treatment fraction a truly automated calculation of patient set-up errors is currently unrealistic. However, using templates extracted from set-up images acquired at the beginning of treatment, detection efficiencies are much higher, therefore showing that this method can be applied to the tracking of intra-fraction prostate movement. 109
Improved procedure for automatic prostate localization on cone-beam CT scans M. Smitsmans 1, J. de Bois I, J. Sonke 1, A. Betgen I, L. Zijp I, D.
Jaffra;, J. Lebesque 1, M. van Herk 1 1The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Radiation Oncology, Amsterdam, The Netherlands 2princess Margaret Hospital - Ontario Cancer Institute, Radiation Medicine Programme, Toronto, Canada
Introduction:
We previously developed an algorithm for automatic prostate localization based on gray value registration (GR) of CT scans. In combination with an on-line cone-beam CT (CBCT) scan this method provides an opportunity to efficiently detect and correct for the prostate position prior to radiotherapy treatment. The aim of this study was to test the algorithm and optimize the procedure for CBCTs.