The accuracy of DIR algorithms was quantitatively evaluated using a tissue equivalent, mass, and density conserving DEFGEL phantom. For the model studied, optical flow algorithms performed better than demons algorithms, with the original Horn and Schunck performing best. The degree of error is influenced more by the magnitude of displacement than the geometric complexity of the deformation. As might be expected, deformation is estimated less accurately for low-contrast regions than for high-contrast features, and the method presented here allows quantitative analysis of the differences. The evaluation of registration accuracy through observation of the same high contrast features that drive the DIR calculation is shown to be circular and hence misleading.
Introduction: Additive manufacturing or 3-dimensional printing has become a widespread technology with many applications in medicine. We have conducted a systematic review of its application in radiation oncology with a particular emphasis on the creation of phantoms for image quality assessment and radiation dosimetry. Traditionally used phantoms for quality assurance in radiotherapy are often constraint by simplified geometry and homogenous nature to perform imaging analysis or pretreatment dosimetric verification. Such phantoms are limited due to their ability in only representing the average human body, not only in proportion and radiation properties but also do not accommodate pathological features. These limiting factors restrict the patient-specific quality assurance process to verify image-guided positioning accuracy and/or dose accuracy in “water-like” condition. Methods and Results: English speaking manuscripts published since 2008 were searched in 5 databases (Google Scholar, Scopus, PubMed, IEEE Xplore, and Web of Science). A significant increase in publications over the 10 years was observed with imaging and dosimetry phantoms about the same total number (52 vs 50). Key features of additive manufacturing are the customization with creation of realistic pathology as well as the ability to vary density and as such contrast. Commonly used printing materials, such as polylactic acid, acrylonitrile butadiene styrene, high-impact polystyrene and many more, are utilized to achieve a wide range of achievable X-ray attenuation values from −1000 HU to 500 HU and higher. Not surprisingly, multimaterial printing using the polymer jetting technology is emerging as an important printing process with its ability to create heterogeneous phantoms for dosimetry in radiotherapy. Conclusion: Given the flexibility and increasing availability and low cost of additive manufacturing, it can be expected that its applications for radiation medicine will continue to increase.
We have confirmed that, for a range of mass and density conserving deformations representative of those observable in anatomical targets, DIR-based dose-warping can yield accurate predictions of the dose distribution. Substantial differences can be seen between the results of different algorithms indicating that DIR performance should be scrutinized before application todose-warping. We have demonstrated that the DEFGEL deformable dosimeter can be used to evaluate DIR performance and the accuracy of dose-warping results by direct measurement.
This paper describes the first use of a tissue-equivalent, 3D dose-integrating deformable phantom that yields integrated or redistributed dosimetric information. The proposed methodology readily yields three-dimensional (3D) dosimetric data from radiation delivery to the DEFGEL phantom in deformed and undeformed states. The impacts of deformation on dose distributions were readily seen in the isodose contours and line profiles from the three arrangements. It is demonstrated that the system is potentially capable of reproducibly emulating the physical deformation of an organ, and therefore can be used to evaluate absorbed doses to deformable targets and organs at risk in three dimensions and to validate deformation algorithms applied to dose distributions.
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