Technical Note: The impact of deformable image registration methods on dose warping

Qin, An; Liang, Jian; Han, Xiao; O’Connell, Nicolette; Yan, Di

doi:10.1002/mp.12741

Cited by 21 publications

(23 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This underscores that the requirements for faithful contour propagation are not synonymous to, and may in fact be disparate from, the requirements for volumetric spatial accuracy of image registration . Hybrid DIR models are being proposed to address this issue . In our case, the DIR algorithm appears to be adequate for contour propagation but is questionable at best for applications requiring the fidelity of the volumetric DVF, such as deformable dose accumulation .…”

Section: Discussionmentioning

confidence: 94%

“…Hybrid DIR models are being proposed to address this issue . In our case, the DIR algorithm appears to be adequate for contour propagation but is questionable at best for applications requiring the fidelity of the volumetric DVF, such as deformable dose accumulation . Finally, it is fair to say that DIR evaluations with physical phantoms are not practically feasible in the majority of the radiotherapy clinics.…”

Section: Discussionmentioning

confidence: 98%

See 1 more Smart Citation

Practical quantification of image registration accuracy following the AAPM TG‐132 report framework

Latifi

Caudell

Zhang

et al. 2018

J Applied Clin Med Phys

View full text Add to dashboard Cite

The AAPM TG 132 Report enumerates important steps for validation of the medical image registration process. While the Report outlines the general goals and criteria for the tests, specific implementation may be obscure to the wider clinical audience. We endeavored to provide a detailed step‐by‐step description of the quantitative tests’ execution, applied as an example to a commercial software package (Mirada Medical, Oxford, UK), while striving for simplicity and utilization of readily available software. We demonstrated how the rigid registration data could be easily extracted from the DICOM registration object and used, following some simple matrix math, to quantify accuracy of rigid translations and rotations. The options for validating deformable image registration (DIR) were enumerated, and it was shown that the most practically viable ones are comparison of propagated internal landmark points on the published datasets, or of segmented contours that can be generated locally. The multimodal rigid registration in our example did not always result in the desired registration error below ½ voxel size, but was considered acceptable with the maximum errors under 1.3 mm and 1°. The DIR target registration errors in the thorax based on internal landmarks were far in excess of the Report recommendations of 2 mm average and 5 mm maximum. On the other hand, evaluation of the DIR major organs’ contours propagation demonstrated good agreement for lung and abdomen (Dice Similarity Coefficients, DSC, averaged over all cases and structures of 0.92 ± 0.05 and 0.91 ± 0.06, respectively), and fair agreement for Head and Neck (average DSC = 0.73 ± 0.14). The average for head and neck is reduced by small volume structures such as pharyngeal constrictor muscles. Even these relatively simple tests show that commercial registration algorithms cannot be automatically assumed sufficiently accurate for all applications. Formalized task‐specific accuracy quantification should be expected from the vendors.

show abstract

Section: Discussionmentioning

confidence: 94%

Section: Discussionmentioning

confidence: 98%

Practical quantification of image registration accuracy following the AAPM TG‐132 report framework

Latifi

Caudell

Zhang

et al. 2018

J Applied Clin Med Phys

View full text Add to dashboard Cite

show abstract

“…If the patient position had been adjusted, the treatment isocenter was moved accordingly before recalculation of dose. The new dose distribution file was mapped back to the planning CT using a deformable deformation vector field (DVF), created with software validated for this purpose (Admire 1.04, Elekta AB, Stockholm, SE) [12]. In the planning CT, the original contours were used to calculate the daily dose to that organ.…”

Section: Methodsmentioning

confidence: 99%

Differences between planned and delivered dose for head and neck cancer, and their consequences for normal tissue complication probability and treatment adaptation

Heukelom

Kantor

Mohamed

et al. 2020

Radiotherapy and Oncology

View full text Add to dashboard Cite

Background and purpose: Anatomical changes induce differences between planned and delivered dose. Adaptive radiotherapy (ART) may reduce these differences but the optimal implementation is insufficiently clear. The aims of this study were to quantify the difference between planned and delivered dose in HNC patients, assess the consequential difference in normal tissue complication probability (DNTCP) and to explore the value of DNTCP as an objective selection strategy for ART. Materials and methods: For 52 patients, daily doses were accumulated to estimate the delivered dose. The difference from planned dose was analyzed for CTVs and 9 organs-at-risk (OAR). DNTCP was calculated for xerostomia, dysphagia, parotid gland dysfunction and tube feeding dependency at 6 months. ART was deemed necessary if DNTCP was >5%. The positive predicted value (PPV) was calculated for identification of ART-patients by clinical judgement, and DNTCP at fraction 10 and 15. Results: DNTCP >5% was seen five times for dysphagia and twice for the other toxicities. Only 5/9 patients with any DNTCP >5% clinically received ART, although ART had been done for 13/52 patients (PPV: 0.38). PPV was 0.86 and 0.75 for accumulated dose at fraction 10 and 15, respectively, using a DNTCP cutoff for the allocation of ART of 5%. Using other DNTCP cutoffs did not substantially improve PPV. With this cutoff the negative predictive value was 0.93 for DNTCP method of fraction 10 and fraction 15, and 0.90 for clinical judgement. Conclusion: To identify patients accurately for ART, NTCP calculations based on the dose differences between planned and delivered dose at fraction 10 are superior to clinical judgement.

show abstract

“…Due to the intrinsic lack of proper physical modelling, they may generate unrealistic deformation especially when organs undergo large deformation and there are few distinctive image features available to follow [ 12 – 14 ]. While problematic internal deformation may not negatively impact contour propagation accuracy, it could lead to significant discrepancy when used to wrap dose or functional image [ 15 – 18 ].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2018

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Technical Note: The impact of deformable image registration methods on dose warping

Cited by 21 publications

References 32 publications

Practical quantification of image registration accuracy following the AAPM TG‐132 report framework

Practical quantification of image registration accuracy following the AAPM TG‐132 report framework

Differences between planned and delivered dose for head and neck cancer, and their consequences for normal tissue complication probability and treatment adaptation

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

Contact Info

Product

Resources

About