The evaluation of a hybrid biomechanical deformable registration method on a multistage physical phantom with reproducible deformation

Abstract

BackgroundAdvanced clinical applications, such as dose accumulation and adaptive radiation therapy, require deformable image registration (DIR) algorithms capable of voxel-wise accurate mapping of treatment dose or functional imaging. By utilizing a multistage deformable phantom, the authors investigated scenarios where biomechanical refinement method (BM-DIR) may be better than the pure image intensity based deformable registration (IM-DIR).MethodsThe authors developed a biomechanical-model based DIR refinement method (BM-DIR) to refine the deformable vector field (DVF) from any initial intensity-based DIR (IM-DIR). The BM-DIR method was quantitatively evaluated on a novel phantom capable of ten reproducible gradually-increasing deformation stages using the urethra tube as a surrogate. The internal DIR accuracy was inspected in term of the Dice similarity coefficient (DSC), Hausdorff and mean surface distance as defined in of the urethra structure inside the phantom and compared with that of the initial IM-DIR under various stages of deformation. Voxel-wise deformation vector discrepancy and Jacobian regularity were also inspected to evaluate the output DVFs. In addition to phantom, two pairs of Head&Neck patient MR images with expert-defined landmarks inside parotids were utilized to evaluate the BM-DIR accuracy with target registration error (TRE).ResultsThe DSC and surface distance measures of the inner urethra tube indicated the BM-DIR method can improve the internal DVF accuracy on masked MR images for the phases of a large degree of deformation. The smoother Jacobian distribution from the BM-DIR suggests more physically-plausible internal deformation. For H&N cancer patients, the BM-DIR improved the TRE from 0.339 cm to 0.210 cm for the landmarks inside parotid on the masked MR images.ConclusionsWe have quantitatively demonstrated on a multi-stage physical phantom and limited patient data that the proposed BM-DIR can improve the accuracy inside solid organs with large deformation where distinctive image features are absent.

Head and Neck Cancer Adaptive Radiation Therapy (ART): Conceptual Considerations for the Informed Clinician

“…A similar observation is seen in DIR algorithms that maintain "mass conservation" whereby additional structures (such as a mouth stent or flap reconstruction) are overfitted by intensity matchingor similarity-driven DIR approaches (32). Biomechanical models, which include prior knowledge of relational data in addition to intensity data can mitigate this effect (31,33,34). However, as the original authors note, caution must be used when large proportional volumetric changes are encountered in either tumor or tissue, and careful algorithm selection for particular applications and quality assurance thereof is thus de rigueur.…”

Factual survey of the clinical use of deformable image registration software for radiotherapy in Japan

“…In addition, a physical phantom is also useful to do the commissioning and quality assurance of the DIR software because this phantom can be used for the end-to-end quality assurance test, which ensures accurate data representation, image transfer and integrity verification between image acquisition devices, image registration systems and other radiotherapy systems that use the image registration results [8]. A physical phantom has the great potential for evaluating the accuracy of DIR-based dose accumulation directly [17–21]. We recommend that comprehensive commissioning and quality assurance should use these three data: physical phantom, digital phantom and clinical patient data due to different advantages and disadvantages of each method.…”

An international survey on the clinical use of rigid and deformable image registration in radiotherapy

“…This could be linked to multi-institutional scientific study of DIR performance based on shared datasets where DIR corrections range from being beneficial to contraindicated. 31,46 While promising research such as deformable physical phantoms [47][48][49][50] and automated deformable vector field analysis 51,52 offer technical solutions, practical validation of registration 4 may require a combination of qualitative with quantitative approaches. 4,6 Similarly, it may be prudent to focus in parallel on optimizing the safe use of commercially available solutions for achievable improvements now, as well as development for increasingly complex registration techniques, such as predictive models of dose accumulation, online replanning, and functional guidance.…”