Expert landmark correspondences are widely reported for evaluating deformable image registration (DIR) spatial accuracy. In this report, we present a framework for objective evaluation of DIR spatial accuracy using large sets of expert-determined landmark point pairs. Large samples (>1100) of pulmonary landmark point pairs were manually generated for five cases. Estimates of inter- and intra-observer variation were determined from repeated registration. Comparative evaluation of DIR spatial accuracy was performed for two algorithms, a gradient-based optical flow algorithm and a landmark-based moving least-squares algorithm. The uncertainty of spatial error estimates was found to be inversely proportional to the square root of the number of landmark point pairs and directly proportional to the standard deviation of the spatial errors. Using the statistical properties of this data, we performed sample size calculations to estimate the average spatial accuracy of each algorithm with 95% confidence intervals within a 0.5 mm range. For the optical flow and moving least-squares algorithms, the required sample sizes were 1050 and 36, respectively. Comparative evaluation based on fewer than the required validation landmarks results in misrepresentation of the relative spatial accuracy. This study demonstrates that landmark pairs can be used to assess DIR spatial accuracy within a narrow uncertainty range.

https://iopscience.iop.org/article/10.1088/0031-9155/54/7/001/pdf

A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets.

Image registration and fusion algorithms exist in almost every software system that creates or uses images in radiotherapy. Most treatment planning systems support some form of image registration and fusion to allow the use of multimodality and time-series image data and even anatomical atlases to assist in target volume and normal tissue delineation. Treatment delivery systems perform registration and fusion between the planning images and the in-room images acquired during the treatment to assist patient positioning. Advanced applications are beginning to support daily dose assessment and enable adaptive radiotherapy using image registration and fusion to propagate contours and accumulate dose between image data taken over the course of therapy to provide up-to-date estimates of anatomical changes and delivered dose. This information aids in the detection of anatomical and functional changes that might elicit changes in the treatment plan or prescription.

As the output of the image registration process is always used as the input of another process for planning or delivery, it is important to understand and communicate the uncertainty associated with the software in general and the result of a specific registration. Unfortunately, there is no standard mathematical formalism to perform this for real-world situations where noise, distortion, and complex anatomical variations can occur. Validation of the software systems performance is also complicated by the lack of documentation available from commercial systems leading to use of these systems in undesirable ‘black-box’ fashion.

In view of this situation and the central role that image registration and fusion play in treatment planning and delivery, the Therapy Physics Committee of the American Association of Physicists in Medicine commissioned Task Group 132 to review current approaches and solutions for image registration (both rigid and deformable) in radiotherapy and to provide recommendations for quality assurance and quality control of these clinical processes.

https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/mp.12256

Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the AAPM Radiation Therapy Committee Task Group No. 132.

EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform for fair and meaningful comparison of registration algorithms which are applied to a database of intra patient thoracic CT image pairs. Evaluation of nonrigid registration techniques is a nontrivial task. This is compounded by the fact that researchers typically test only on their own data, which varies widely. For this reason, reliable assessment and comparison of different registration algorithms has been virtually impossible in the past. In this work we present the results of the launch phase of EMPIRE10, which comprised the comprehensive evaluation and comparison of 20 individual algorithms from leading academic and industrial research groups. All algorithms are applied to the same set of 30 thoracic CT pairs. Algorithm settings and parameters are chosen by researchers expert in the con figuration of their own method and the evaluation is independent, using the same criteria for all participants. All results are published on the EMPIRE10 website (http://empire10.isi.uu.nl). The challenge remains ongoing and open to new participants. Full results from 24 algorithms have been published at the time of writing. This paper details the organization of the challenge, the data and evaluation methods and the outcome of the initial launch with 20 algorithms. The gain in knowledge and future work are discussed.

/pdf/evaluation-of-registration-methods-on-thoracic-ct-the-cy212a9z4o.pdf

Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge

Purpose To assess the accuracy, reproducibility, and computational performance of deformable image registration algorithms under development at multiple institutions on common datasets. Methods and Materials Datasets from a lung patient (four-dimensional computed tomography [4D-CT]), a liver patient (4D-CT and magnetic resonance imaging [MRI] at exhale), and a prostate patient (repeat MRI) were obtained. Radiation oncologists localized anatomic structures for accuracy assessment. Algorithm accuracy was determined by comparing the computer-predicted displacement at each bifurcation point with the displacement computed from the oncologists' annotations. Thirty-seven academic institutions and medical device manufacturers with published evidence of active deformable image registration capabilities were invited to participate. Results Twenty-seven groups agreed to participate; 6 did not return results. Sixteen completed the liver 4D-CT, 12 the lung 4D-CT, 3 the prostate MRI, and 3 the liver MRI-CT. The range of average absolute error for the lung 4D-CT was 0.6–1.2 mm (left–right [LR]), 0.5–1.8 mm (anterior–posterior [AP]), and 0.7–2.0 mm (superior–inferior [SI]); the liver 4D-CT was 0.8–1.5 mm (LR), 1.0–5.2 mm (AP), and 1.0–5.9 mm (SI); the liver MRI-CT was 1.1–2.6 mm (LR), 2.0–5.0 mm (AP), and 2.2–2.6 mm (SI); and the repeat prostate MRI prostate datasets was 0.5–6.2 mm (LR), 3.1–3.7 mm (AP), and 0.4–2.0 mm (SI). Conclusions An infrastructure was developed to assess multi-institution deformable registration accuracy. The results indicate large discrepancies in reported shifts, although the majority of deformable registration algorithms performed at an accuracy equivalent to the voxel size, promising to improve treatment planning, delivery, and assessment.

/pdf/results-of-a-multi-institution-deformable-registration-s09fo5pzub.pdf

Results of a multi-institution deformable registration accuracy study (MIDRAS).

A four-dimensional deformable image registration (4D DIR) algorithm, referred to as 4D local trajectory modeling (4DLTM), is presented and applied to thoracic 4D computed tomography (4DCT) image sets. The theoretical framework on which this algorithm is built exploits the incremental continuity present in 4DCT component images to calculate a dense set of parameterized voxel trajectories through space as functions of time. The spatial accuracy of the 4DLTM algorithm is compared with an alternative registration approach in which component phase to phase (CPP) DIR is utilized to determine the full displacement between maximum inhale and exhale images. A publically available DIR reference database (http://www.dir-lab.com) is utilized for the spatial accuracy assessment. The database consists of ten 4DCT image sets and corresponding manually identified landmark points between the maximum phases. A subset of points are propagated through the expiratory 4DCT component images. Cubic polynomials were found to provide sufficient flexibility and spatial accuracy for describing the point trajectories through the expiratory phases. The resulting average spatial error between the maximum phases was 1.25 mm for the 4DLTM and 1.44 mm for the CPP. The 4DLTM method captures the long-range motion between 4DCT extremes with high spatial accuracy.

/pdf/four-dimensional-deformable-image-registration-using-3aowto0wup.pdf

Four-dimensional deformable image registration using trajectory modeling.

Deformable registration is needed for a variety of tasks in establishing the voxel correspondence between respiratory phases Most registration algorithms assume or imply that the deformation field is smooth and continuous everywhere However, the lungs are contained within closed invaginated sacs called pleurae and are allowed to slide almost independently along the chest wall This sliding motion is characterized by a discontinuous vector field, which cannot be generated using standard deformable registration methods The authors have developed a registration method that can create discontinuous vector fields at the boundaries of anatomical subregions Registration is performed independently on each subregion, with a boundary-matching penalty used to prevent gaps This method was implemented and tested using both the B-spline and Demons registration algorithms in the Insight Segmentation and Registration Toolkit The authors have validated this method on four patient 4DCT data sets for registration of the end-inhalation and end-exhalation volumes Multiple experts identified homologous points in the lungs and along the ribs in the two respiratory phases Statistical analyses of the mismatch of the homologous points before and after registration demonstrated improved overall accuracy for both algorithms

https://www.creatis.insa-lyon.fr/~dsarrut/mybib/2008/wu-medphys2008.pdf

Evaluation of deformable registration of patient lung 4DCT with subanatomical region segmentations

The purpose of this study was to investigate if interfraction and intrafraction motion in free-breathing and gated lung IMRT can lead to systematic dose differences between 3DCT and 4DCT. Dosimetric effects were studied considering the breathing pattern of three patients monitored during the course of their treatment and an in-house developed 4D Monte Carlo framework. Imaging data were taken in free-breathing and in cine mode for both 3D and 4D acquisition. Treatment planning for IMRT delivery was done based on the free-breathing data with the corvus (North American Scientific, Chatsworth, CA) planning system. The dose distributions as a function of phase in the breathing cycle were combined using deformable image registration. The study focused on (a) assessing the accuracy of the corvus pencil beam algorithm with Monte Carlo dose calculation in the lung, (b) evaluating the dosimetric effect of motion on the individual breathing phases of the respiratory cycle, and (c) assessing intrafraction and interfraction motion effects during free-breathing or gated radiotherapy. The comparison between (a) the planning system and the Monte Carlo system shows that the pencil beam algorithm underestimates the dose in low-density regions, such as lung tissue, and overestimates the dose in high-density regions, such as bone, by 5% or more of the prescribed dose (corresponding to approximately 3–5 Gy for the cases considered). For the patients studied this could have a significant impact on the dose volume histograms for the target structures depending on the margin added to the clinical target volume (CTV) to produce either the planning target (PTV) or internal target volume (ITV). The dose differences between (b) phases in the breathing cycle and the free-breathing case were shown to be negligible for all phases except for the inhale phase, where an underdosage of the tumor by as much as 9.3 Gy relative to the free-breathing was observed. The large difference was due to breathing-induced motion/deformation affecting the soft/lung tissue density and motion of the bone structures (such as the rib cage) in and out of the beam. Intrafraction and interfraction dosimetric differences between (c) free-breathing and gated delivery were found to be small. However, more significant dosimetric differences, of the order of 3%–5%, were observed between the dose calculations based on static CT (3DCT) and the ones based on time-resolved CT (4DCT). These differences are a consequence of the larger contribution of the inhale phase in the 3DCT data than in the 4DCT.

/pdf/dosimetric-impact-of-motion-in-free-breathing-and-gated-lung-lxjwrsjcqo.pdf

Dosimetric impact of motion in free-breathing and gated lung radiotherapy: a 4D Monte Carlo study of intrafraction and interfraction effects.

An image-based re-registration scheme has been developed and evaluated that uses fiducial registration as a starting point to maximize the normalized mutual information (nMI) between intraoperative ultrasound (iUS) and preoperative magnetic resonance images (pMR). We show that this scheme significantly (p⪡0.001) reduces tumor boundary misalignment between iUS pre-durotomy and pMR from an average of 2.5 mm to 1.0 mm in six resection surgeries. The corrected tumor alignment before dural opening provides a more accurate reference for assessing subsequent intraoperative tumor displacement, which is important for brain shift compensation as surgery progresses. In addition, we report the translational and rotational capture ranges necessary for successful convergence of the nMI registration technique (5.9 mm and 5.2 deg, respectively). The proposed scheme is automatic, sufficiently robust, and computationally efficient (<2 min), and holds promise for routine clinical use in the operating room during image-guided neurosurgical procedures.

Mutual‐information‐based image to patient re‐registration using intraoperative ultrasound in image‐guided neurosurgery

Dose calculation methods which incorporate tissue motion are an important tool for evaluating the effect of respiratory motion on the delivered dose distribution. 4D dose calculation methods use a sum of remapped doses calculated on 4D CT images of the patient at different respiratory phases to determine the cumulative dose received over the entire respiratory cycle. A number of methods for remapping the dose to the reference phase have been proposed, including center-of-mass (COM) tracking and trilinear (TL) interpolation. In this work we compare calculations of dose distributions remapped between extreme breathing phases against a 4D Monte Carlo dose code defDOSXYZ for three planning scenarios. No clinically significant differences were noted between dose distributions calculated by the three methods with the exception of an extreme motion evaluation case where TL and COM remapping underestimated the 95% target dose coverage by up to 16%. The accuracy of these dose calculation methods is significantly affected by the continuity of the deformation fields from non-linear image registration.

A comparison of dose warping methods for 4D Monte Carlo dose calculations in lung

This paper presents a new interactive method for analyzing 4D Computed Tomography (4DCT) datasets for patient care and research. Deformable registration algorithms are commonly used to observe the trajectories of individual voxels from one respiratory phase to another. Our system provides users with the capability to visualize these trajectories while simultaneously rendering anatomical volumes, which can greatly improve the accuracy of deformable registration.

https://repository.library.northeastern.edu/files/neu:1336/fulltext.pdf

Ziji Wu

Papers

Evaluation of deformable registration of patient lung 4DCT with subanatomical region segmentations

Dosimetric impact of motion in free-breathing and gated lung radiotherapy: a 4D Monte Carlo study of intrafraction and interfraction effects.

Mutual‐information‐based image to patient re‐registration using intraoperative ultrasound in image‐guided neurosurgery

A comparison of dose warping methods for 4D Monte Carlo dose calculations in lung

Interactive deformable registration visualization and analysis of 4D computed tomography