Automatic quantification of multi-modal rigid registration accuracy using feature detectors

Hauler, Frida; Furtado, Hugo; Jurisic, Miro; Polanec, Stephan H.; Spick, Claudio; Laprie, Anne; Nestle, Ursula; Sabatini, Umberto; Birkfellner, Wolfgang

doi:10.1088/0031-9155/61/14/5198

Cited by 12 publications

(6 citation statements)

References 44 publications

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“…Whilst it has been previously attempted to determine the potential of local intensity metrics to assess registration accuracy, their application is not always effective [3]. Particular concern is given to the lack of independence, as conventional registration algorithms employ greyscale information for registration optimisation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identification and separation of rigid image registration error sources, demonstrated for MRI-only image guided radiotherapy

Tyyger¹,

Nix²,

Al-Qaisieh³

et al. 2020

Biomed. Phys. Eng. Express

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Purpose: Rigid image registration (RIR) accuracy is crucial for image guided radiotherapy (IGRT). However, existing clinical image registration assessment methods cannot separate and quantify RIR error sources. Herein, we develop an extension of the 'full circle method' for RIR consistency. Paired registration circuits are used to isolate sources of RIR error caused by reference dataset substitution, from those inherent to the underlying RIR. This approach was demonstrated in the context of MRI-only IGRT, assessing substitution of MRI-derived synthetic-CT (sCT) for conventional CT, in a cohort of rectal cancer patients. Materials and methods: Planning CT, MRI-derived sCT, and two CBCTs from seven rectal cancer patients were retrospectively registered with global and soft tissue clipbox based RIR. Paired registration circuits were constructed using two moving (cone beam CT) images and two reference images (CT and sCT), per patient. Differences between inconsistencies in registration circuits containing CT and sCT were used to determine changes in registration accuracy due to substitution of sCT for CT. Results: sCT was found to be equivalent to CT under global RIR, with median differences of 0.05 mm and 0.01°. Soft tissue clipbox based RIR with sCT exhibited gross misregistration (>5 mm or 3°) for 3 patients. Registration consistency was degraded compared to CT across the cohort, with median differences of 0.54 mm and 0.15°. Conclusion: A paired registration circuit methodology for assessing RIR accuracy without ground truth information was developed and demonstrated for MRI-only IGRT in rectal cancer. This highlighted a reduction in clipbox based RIR consistency when sCT was substituted for conventional CT. The developed method enabled separation of degraded registration accuracy, from other error sources within the overall registration inconsistency. This novel methodology is applicable to any RIR scenario and enables analysis of the change in RIR performance on modification of image data or process.

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Section: Introductionmentioning

confidence: 99%

“…Target registration error (TRE) analysis requires ground truth information, meaning this assessment metric requires phantoms [7,8] (physical or digital), fiducial markers (FMs) [9,10], or reproducible anatomical landmarks [3,11]. Phantoms provide global ground truth information and consequently global TRE measurements.…”

Section: Introductionmentioning

confidence: 99%

Identification and separation of rigid image registration error sources, demonstrated for MRI-only image guided radiotherapy

Tyyger¹,

Nix²,

Al-Qaisieh³

et al. 2020

Biomed. Phys. Eng. Express

View full text Add to dashboard Cite

show abstract

“…Given that no physician is required for manual inspection of the daily contours, e.g. by using automated QA algorithms for verification of the contours derived from DIR (Hauler et al 2016), a main advantage of dose-guided positioning is that it might be implemented without presence of a physician, since plan approval is not required. But since the decision on the applied couch shift is based on dosimetric parameters instead of anatomical features, the presence of a physician for shift approval should be debated for clinical implementation of dose-guided positioning.…”

Section: Discussionmentioning

confidence: 99%

A novel method for interactive multi-objective dose-guided patient positioning

et al. 2016

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In intensity-modulated radiation therapy (IMRT), 3D in-room imaging data is typically utilized for accurate patient alignment on the basis of anatomical landmarks. In the presence of non-rigid anatomical changes, it is often not obvious which patient position is most suitable. Thus, dose-guided patient alignment is an interesting approach to use available in-room imaging data for up-to-date dose calculation, aimed at finding the position that yields the optimal dose distribution. This contribution presents the first implementation of dose-guided patient alignment as multi-criteria optimization problem. User-defined clinical objectives are employed for setting up a multi-objective problem. Using pre-calculated dose distributions at a limited number of patient shifts and dose interpolation, a continuous space of Pareto-efficient patient shifts becomes accessible. Pareto sliders facilitate interactive browsing of the possible shifts with real-time dose display to the user. Dose interpolation accuracy is validated and the potential of multi-objective dose-guided positioning demonstrated for three head and neck (H&N) and three prostate cancer patients. Dose-guided positioning is compared to replanning for all cases. A delineated replanning CT served as surrogate for in-room imaging data. Dose interpolation accuracy was high. Using a [Formula: see text] dose difference criterion, a median pass-rate of 95.7% for H&N and 99.6% for prostate cases was determined in a comparison to exact dose calculations. For all patients, dose-guided positioning allowed to find a clinically preferable dose distribution compared to bony anatomy based alignment. For all H&N cases, mean dose to the spared parotid glands was below [Formula: see text] (up to [Formula: see text] with bony alignment) and clinical target volume (CTV) [Formula: see text] above 99.1% (compared to 95.1%). For all prostate patients, CTV [Formula: see text] was above 98.9% (compared to 88.5%) and [Formula: see text] to the rectum below [Formula: see text] (compared to 56.1%). Replanning yielded improved results for the H&N cases. For the prostate cases, differences to dose-guided positioning were minor.

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“…It was based on the construction of an image descriptor by means of a self-similarity measure, which could be adopted for the definition of corresponding feature points. An extension of SIFT was also investigated for CT/MRI 111 ; the proofof-concept study was, however, limited to a 2-D implementation of the descriptor. To our knowledge, automatic landmark identification between anatomic and functional imaging has not been deeply investigated in the literature.…”

Section: B Automatic Strategies: Image-basedmentioning

confidence: 99%

“Patient‐specific validation of deformable image registration in radiation therapy: Overview and caveats”

et al. 2018

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Over the last few decades, deformable image registration (DIR) has gained popularity in image-guided radiation therapy for a number of applications, such as contour propagation, dose warping, and accumulation. Although this raises promising perspectives for the improvement of treatment outcomes and quality of radiotherapy clinical practice, the variety of proposed DIR algorithms, combined with the lack of an effective quantitative quality control metric of the registration, is slowing the transfer of DIR into the clinical routine. Recently, a task group (AAPM TG132) report was published outlining the essential aspects of DIR for image guidance in radiotherapy. However, an accurate and efficient patient-specific validation is not yet defined, and appropriate metrics should be identified to achieve the definition of both geometric and dosimetric accuracy. In this respect, the use of a dense set of anatomical landmarks, along with additional evaluations on contours or deformation field analysis, are likely to drive patient-specific DIR validation in clinical image-guided radiotherapy applications to account for geometric inaccuracies. Automatic and efficient strategies able to provide spatial information of DIR uncertainties and to evaluate monomodal and multimodal image registration, as well as to describe homogenous and un-contrasted regions are believed to represent the future direction in DIR validation. But especially in the case of DIR applications for dose mapping and accumulation, the need of accurate patient-specific validation is not only limited to the evaluation of geometric accuracy. In fact, the need to account for dosimetric inaccuracies due to DIR represents another important area in the field of adaptive treatments. Different approaches are currently being investigated to quantify the effect of DIR error on dose analysis, mainly relying on clinically relevant dose metrics, or on the study of deformation field properties for a voxel-by-voxel evaluation. However, novel research is required for the definition of dedicated and personalized measures capable to relate the geometric and dosimetric inaccuracies, thus bearing useful information for a safe use of DIR by clinical end users. In this paper we provide insights on DIR results evaluation on a patient-specific basis, facing the issues of both geometric and dosimetric paradigms. Challenges on DIR validation are overviewed and discussed, in order to push preliminary clinical guidelines forward on this fundamental topic and boost the implementation of more robust and reliable patient-specific evaluation metrics.

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Automatic quantification of multi-modal rigid registration accuracy using feature detectors

Cited by 12 publications

References 44 publications

Identification and separation of rigid image registration error sources, demonstrated for MRI-only image guided radiotherapy

Identification and separation of rigid image registration error sources, demonstrated for MRI-only image guided radiotherapy

A novel method for interactive multi-objective dose-guided patient positioning

“Patient‐specific validation of deformable image registration in radiation therapy: Overview and caveats”

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