Image Registration Algorithm Research Articles

Evaluation of a commercial deformable image registration algorithm for dual-energy CT processing.

PurposeSeveral dual‐energy computed tomography (DECT) techniques require a deformable image registration to correct for motion between the acquisition of low and high energy data. However, current DECT software does not provide tools to assess registration accuracy or allow the user to export deformed images, presenting a unique challenge for image registration quality assurance (QA). This work presents a methodology to evaluate the accuracy of DECT deformable registration and to quantify the impact of registration errors on end‐product images.MethodsThe deformable algorithm implemented in Siemen Healthineers's Syngo was evaluated using a deformable abdomen phantom and a rigid phantom to mimic sliding motion in the thorax. Both phantoms were imaged using sequential 80 and 140 kVp scans with motion applied between the two scans. Since Syngo does not allow the export of the deformed images, this study focused on quantifying the accuracy of various end‐product, dual‐energy images resulting from processing of deformed images.ResultsThe Syngo algorithm performed well for the abdomen phantom with a mean registration error of 0.4 mm for landmark analysis, Dice similarity coefficients (DSCs) > 0.90 for five organs contoured, and mean iodine concentrations within 0.2 mg/mL of values measured on static images. For rigid sliding motion, the algorithm performed poorer and resulted in noticeable registration errors toward the superior and inferior scan extents and DSCs as low as 0.41 for iodine rods imaged in the phantom. Additionally, local iodine concentration errors in areas of misregistration exceeded 3 mg/mL.ConclusionsThis work represents the first methodology for DECT image registration QA using commercial software. Our data support the clinical use of the Syngo algorithm for abdominal sites with limited motion (i.e., pancreas and liver). However, dual‐energy images generated with this algorithm should be used with caution for quantitative measurements in areas with sliding motion.

Dosimetric evaluation of MRI-to-ultrasound automated image registration algorithms for prostate brachytherapy

PurposeIdentifying dominant intraprostatic lesions (DILs) on transrectal ultrasound (TRUS) images during prostate high-dose-rate brachytherapy treatment planning remains a significant challenge. Multiparametric MRI (mpMRI) is the tool of choice for DIL identification; however, the geometry of the prostate on mpMRI and on the TRUS may differ significantly, requiring image registration. This study assesses the dosimetric impact attributed to differences in DIL contours generated using commonly available MRI to TRUS automated registration: rigid, semi-rigid, and deformable image registration, respectively. Methods and MaterialsTen patients, each with mpMRI and TRUS data sets, were included in this study. Five radiation oncologists with expertise in TRUS-based high-dose-rate brachytherapy were asked cognitively to transfer the DIL from the mpMRI images of each patient to the TRUS image. The contours were analyzed for concordance using simultaneous truth and performance level estimation (STAPLE) algorithm. The impact of DIL contour differences due to registration variability was evaluated by comparing the STAPLE-DIL dosimetry from the reference (STAPLE) plan with that from the evaluation plans (manual and automated registration) for each patient. The dosimetric impact of the automatic registration approach was also validated using a margin expansion that normalizes the volume of the autoregistered DILs to the volumes of the STAPLE-DILs. Dose metrics including D90, Dmean, V150, and V200 to the prostate and DIL were reported. For urethra and rectum, D10 and V80 were reported. ResultsSignificant differences in DIL coverage between reference and evaluation plans were found regardless of the algorithm methodology. No statistical difference was reported in STAPLE-DIL dosimetry when manual registration was used. A margin of 1.5 ± 0.8 mm, 1.1 ± 0.8 mm, and 2.5 ± 1.6 mm was required to be added for rigid, semi-rigid, and deformable registration, respectively, to mitigate the difference in STAPLE-DIL coverage between the evaluation and reference plans. ConclusionThe dosimetric impact of integrating an MRI-delineated DIL into a TRUS-based brachytherapy workflow has been validated in this study. The results show that rigid, semi-rigid, and deformable registration algorithms lead to a significant undercoverage of the DIL D90 and Dmean. A margin of at least 1.5 ± 0.8 mm, 1.1 ± 0.8 mm, and 2.5 ± 1.6 mm is required to be added to the rigid, semi-rigid, and deformable DIL registration to be suitable for DIL-boosting during prostate brachytherapy.

Retrospective dose reconstruction of prostate stereotactic body radiotherapy using cone-beam CT and a log file during VMAT delivery with flattening-filter-free mode.

This study aimed to reconstruct the dose distribution of single fraction of stereotactic body radiotherapy for patients with prostate cancer using cone-beam computed tomography (CBCT) and a log file during volumetric-modulated arc therapy (VMAT) delivery with flattening-filter-free (FFF) mode. Twenty patients with clinically localized prostate cancer were treated with FFF-VMAT, and projection images for in-treatment CBCT (iCBCT) imaging were concomitantly acquired with a log file. A D95 dose of 36.25Gy in five fractions was prescribed to each planning target volume (PTV) on each treatment planning CT (pCT). Deformed pCT (dCT) was obtained from the iCBCT using a hybrid deformable image registration algorithm. Dose distributions on the dCT were calculated using Pinnacle3 v9.10 by converting the log file data to Pinnacle3 data format using an in-house software. Dose warping was performed by referring to deformation vector fields calculated from pCT and dCT. Reconstructed dose distribution was compared with that of the original plan. Dose differences between the original and reconstructed dose distributions were within 3% at the isocenter and observed in PTV and organ-at-risk (OAR) regions. Differences in OAR regions were relatively larger than those in the PTV, presumably because OARs were more deformed than the PTV. Therefore, our method can be used successfully to reconstruct the dose distributions of one fraction using iCBCT and a log file during FFF-VMAT delivery.

Feature Point Registration Model of Farmland Surface and Its Application Based on a Monocular Camera.

In this study, an image registration algorithm was applied to calculate the rotation angle of objects when matching images. Some commonly used image feature detection algorithms such as features from accelerated segment test (FAST), speeded up robust features (SURF) and maximally stable extremal regions (MSER) algorithms were chosen as feature extraction components. Comparing the running time and accuracy, the image registration algorithm based on SURF has better performance than the other algorithms. Accurately obtaining the roll angle is one of the key technologies to improve the positioning accuracy and operation quality of agricultural equipment. To acquire the roll angle of agriculture machinery, a roll angle acquisition model based on the image registration algorithm was built. Then, the performance of the model with a monocular camera was tested in the field. The field test showed that the average error of the rolling angle was 0.61°, while the minimum error was 0.08°. The field test indicated that the model could accurately obtain the attitude change trend of agricultural machinery when it was working in irregular farmlands. The model described in this paper could provide a foundation for agricultural equipment navigation and autonomous driving.

Systematic feasibility analysis of performing elastography using reduced dose CT lung image pairs.

Elastography using computer tomography (CT) is a promising methodology that can provide patient-specific regional distributions of lung biomechanical properties. The purpose of this paper is to investigate the feasibility of performing elastography using simulated lower dose CT scans. A cohort of eight patient CT image pairs were acquired with a tube current-time product of 40mAs for estimating baseline lung elastography results. Synthetic low mAs CT scans were generated from the baseline scans to simulate the additional noise that would be present in acquisitions at 30, 25, and 20mAs, respectively. For the simulated low mAs scans, exhalation and inhalation datasets were registered using an in-house optical flow deformable image registration algorithm. The registered deformation vector fields (DVFs) were taken to be ground truth for the elastography process. A model-based elasticity estimation was performed for each of the reduced mAs datasets, in which the goal was to optimize the elasticity distribution that best represented their respective DVFs. The estimated elasticity and the DVF distributions of the reduced mAs scans were then compared with the baseline elasticity results for quantitative accuracy purposes. The DVFs for the low mAs and baseline scans differed from each other by an average of 1.41mm, which can be attributed to the noise added by the simulated reduction in mAs. However, the elastography results using the DVFs from the reduced mAs scans were similar from the baseline results, with an average elasticity difference of 0.65, 0.71, and 0.76kPa, respectively. This illustrates that elastography can provide equivalent results using low-dose CT scans. Elastography can be performed equivalently using CT image pairs acquired with as low as 20mAs. This expands the potential applications of CT-based elastography.

Validation of Diffeomorphic Registration on Cine Cardiac MR via Direct Frame-to-Frame Comparison with HARP Tracking on Tagged MR.

Cardiac magnetic resonance (MR) tissue tagging offers an excellent solution for tracking deformation and is considered the reference standard for the quantification of strain. However, due to the requirements for a dedicated acquisition sequence and post-processing software, tagged MR acquisitions are performed much less frequently in routine clinical practice than the anatomical cine MR sequence. Using tagged MR as the reference standard, this study proposes an approach to evaluate a diffeomorphic image registration algorithm applied on cine MR images to compute the cardiac deformation. In contrast to previous evaluation methods that compared the final results, such as strain, computed from cine and tagged MR sequences, the proposed method performs a direct frame-to-frame comparison in the evaluation. To overcome the problem of misalignment between the tagged and cine MR images, the proposed approach performs transformations to and from the two-dimensional image pixel coordinates and three-dimensional space using the meta-information encoded in the MR images. Linear temporal interpolation is performed using the frame acquisition time since the last R-wave peak value of the electrocardiogram signal recorded in the meta-information. Several statistic measures are computed and reported for the registration error using the Euclidean distances between the corresponding set of points obtained using cine and tagged MR images.

Comparison of CBCT conversion methods for dose calculation in the head and neck region

The purpose of this study was to compare different methods of CBCT conversion respect to dose calculation accuracy. Twelve head and neck cancer patients treated with VMAT using simultaneous integrated boost technique were selected for the study. For each patient a planning CT (pCT), a control. CT acquired in the fourth week of treatment and a CBCT scan acquired on the closest day with the control CT were used. In order to re-calculate dose directly on CBCT image sets, a population based approach (CBCTPop) and a Histogram Matching (HM) approach based on rigid (CBCTHM-R) and deformable registration (CBCTHM-D) were used. Additionally, virtual CTs (vCTs) were generated using two deformable image registration algorithms (CTELX and CTANC) of the planning CT to the CBCT by using two different deformable image registration (DIR) algorithms. The corresponding control CTs were selected as ground truth and dose distributions on CBCT were analyzed using 3D global gamma index analysis applying a threshold of 10% with respect to the prescribed dose. Using the 2%/2mm gamma criterion, the results were 89.9%(±8.3%), 94.1%(±5.0%), 94.3%(±5.7%), 96.1%(±3.9%), 93.4%(±6.3%) for the CBCTPop, CBCTHM-R, CBCTHM-D, CTELX and CTANC, respectively. On average, the HM and DIR techniques showed a higher accuracy compared to the population based approach, but Kruskal–Wallis test did not show significant difference among the investigated dose calculation techniques assuming p<0.05. More sophisticated CBCT dose calculation methods seem to improve the dose calculation accuracy, but statistical significance remains to be demonstrated.

Development and Evaluation of CT-to-3D Ultrasound Image Registration Algorithm in Vertebral Phantoms for Spine Surgery.

Posterior spinal fusion surgery requires careful insertion of screws into the spine to avoid neurologic injury. While current systems use CT-scans, three-dimensional ultrasound (3DUS) could provide guidance by reconstructing the vertebral surface, and then registering a pre-operative vertebral model to that surface for localization. The aim of this study was to evaluate the accuracy and processing time of a custom CT-3DUS registration algorithm. A phantom human vertebra was 3D-printed and scanned with a motion capture-based 3D ultrasound (3DUS) system. Image registration was performed that included a pre-alignment phase using vertebral symmetry information, and then comparing Gaussian pyramid intensity-based registration with iterative-closest-point registration for final transformations. Image registration was performed 192 times while surgical registration between CT and real-world position was performed 84 times. The accuracy of image registration (CT-to-3DUS) was 0.3 ± 0.2mm and 0.9 ± 0.8° completed in 13.3 ± 2.9s. The surgical navigation accuracy (CT model to real-world position) of the system was 1.2 ± 0.5mm and 2.2 ± 2.0° completed in 16.2 ± 3.0s. Both meet accuracy thresholds of < 2mm and < 5° required for the surgery. A feasibility study on porcine spine qualitatively showed appropriate overlapping anatomy in CT-3DUS registrations. The usage of 3D ultrasound for navigation has demonstrated accuracy to provide radiation-free image guidance for spine surgery.

Analysis and Research of Subclinical Diabetic Peripheral Vascular Lesions Based on Mutual Information-based Medical Image Registration Algorithm and Colour Ultrasound Imaging (Preprint)

Analysis and Research of Subclinical Diabetic Peripheral Vascular Lesions Based on Mutual Information-based Medical Image Registration Algorithm and Colour Ultrasound Imaging (Preprint)

A DIRECT-type global optimization algorithm for image registration

Image registration is an important component of many image processing problems which often require optimizing over some set of parameters. In the image registration problem, one attempts to determine the best transformation for aligning similar images. Such problems typically require minimizing a dissimilarity measure with multiple local minima. We describe a global optimization algorithm and apply it to the problem of identifying the best transformation for aligning two images.

Organ motion quantification and margins evaluation in carbon ion therapy of abdominal lesions

PurposeIn image-guided particle radiotherapy of abdominal lesions, respiratory motion hinders treatment accuracy. In this study, 2D cineMRI data were used to quantify the tumor (GTV) motion and to evaluate the clinical approach based on deriving an internal target volume (ITV) from a planning 4DCT for gating treatments. MethodsSeven patients with abdominal lesions were treated with carbon-ion therapy at the National Centre of Oncological Hadron-therapy (Italy). The MR scan was performed on the same day of the 4DCT acquisition. For four patients, an additional MR was acquired approximately after 1 week. The cineMRI combined with deformable image registration algorithm was used to quantify tumor motion. Afterwards, two ITVs were defined considering (1) all phases (ITVFB) and (2) only phases within the gating window (ITVG), and then compared with the clinical (4DCT-derived) ITVs (ITVCG and ITVCFB). ResultsTumor residual motion estimated by cineMRI data in the two MRI sessions resulted not significantly different from 4DCT, although cineMRI accounted for cycle-to-cycle variations. The ITV normalized for the GTV median values were higher for ITVFB with respect to ITVG, ITVCFB and ITVCG. The Hausdorff distances with respect to the GTV were up to 10.55 mm, 3.13 mm, 5.56 mm and 2.51 mm, for ITVFB, ITVG, ITVCFB and ITVCG, respectively. According to both metrics, ITVCG and ITVG were not found significantly different. ConclusionsCineMRI acquisitions allowed to quantify organ motion without delivering additional dose to the patient and to verify treatment margins in gated carbon-ion therapy of abdominal lesions.

Influence of different urinary bladder filling levels and controlling regions of interest selection on deformable image registration algorithms

PurposeEvaluation of Raystation ANAtomically CONstrained Deformation Algorithm (ANACONDA) performance to different urinary bladder filling levels in male pelvis anatomic site varying the controlling Regions Of Interest (ROIs). MethodsDifferent image datasets were obtained with ImSimQA (Oncology System Limited, Shrewsbury, UK) to evaluate ANACONDA performances (RaySearch Laboratories, Stockholm, Sweden). Deformation vector fields were applied to a synthetic man pelvis and a real patient computed tomography (CT) dataset (reference CTs) resulting in deformed CTs (target CTs) with various bladder filling levels. Different deformable image registrations (DIRs) were generated between each target CTs and reference CTs varying the controlling ROIs subset. Deformed ROIs were mapped from target CT to reference CT and then compared to reference ROIs. Evaluation was performed by Dice Similarity Coefficient (DSC), Correlation Coefficient (CC), Mean Distance to Agreement (MDA), maximum Distance to Agreement (maxDA) and with the introduction of global DSC (global_DSC) and global CC (global_CC) parameters. ResultsIn both synthetic and real patient CT cases, DSC scored less than 0.75 and MDA greater than 3 mm when no ROIs or only bladder were exploited as controlling ROI. DSC and CC increased by increasing the number of controlling ROIs selected whereas, an opposite behavior was observed for MDA and maxDA. ConclusionsANACONDA performances can be influenced by bladder filling fluctuation if no controlling ROIs are selected. Global_DSC and global_CC are useful parameters to quantitatively compare DIR algorithms. DIR performances improve by increasing the number of controlling ROIs selected, reaching a saturation level after a defined ROIs subset selection.

Free-to-use DIR solutions in radiotherapy: Benchmark against commercial platforms through a contour-propagation study

PurposeA contour propagation study has been conducted to benchmark three algorithms for Deformable Image Registration (DIR) freely available online against well-established commercial solutions. MethodsElastiX, BRAINS and Plastimach, available as modules in the open source platform 3DSlicer, were tested as the recent AAPM Task group 132 guidelines proposes. The overlap of the DIR-mapped ROIs in four computational anthropomorphic phantoms was measured. To avoid bias every algorithm was left to run without any human interaction nor particular registration strategy. The accuracy of the algorithms was measured using the Dice Similarity Coefficient (DSC) and Mean Distance to Conformity (MDC) metrics. The registration quality was compared to the recommended geometrical accuracy suggested by AAPM TG132 and to the results of a large population-based study performed with commercial DIR solutions. ResultsThe considered free-to-use DIR solutions generally meet acceptable accuracy and good overlap (DSC > 0.85). Mild failures (DSC < 0.75) were detected only for the smallest structures. In case of extremely severe deformations acceptable accuracy was not met (MDC > 3 mm). The morphing capability of the tested algorithms equals those of commercial systems when the user interaction is avoided. Underperformances were detected only in cases where a specific registration strategy is mandatory to obtain a satisfying match. ConclusionsAll of the considered algorithms show performances not inferior to previously published data and have the potential to be good candidates for use in the clinical routine. The results and conclusions only apply to the considered phantoms and should not be considered to be generally applicable and extendable to patient cases.

Adaptive Strategy for External Beam Radiation Therapy in Prostate Cancer: Management of the Geometrical Uncertainties With Robust Optimization

PurposeWe aim to develop and validate a new adaptive method for prostate cancer radiation therapy (RT), using an offline strategy to improve treatment personalization by modeling the internal target volume on individual basis and account for the residual set-up uncertainties by robust optimization. Methods and MaterialsTwenty patients with intermediate-high prostate cancer treated with radical radiation therapy were enrolled. The first step of the offline adaptive RT strategy is the identification of a patient-specific internal target volume based on the kV cone beam computed tomography (kV-CBCT) data sets acquired during the first 5 fractions. The deformable image registration algorithm ANACONDA was used to propagate the clinical target volumes (CTVs) from the reference-planning computed tomography to the CBCTs; these contours were assessed by a radiation oncologist. In the second step, the internal target volume was used to replan the treatment using a min-max robust algorithm based on the worst scenario optimization. The CTV coverage and organs-at-risk sparing achieved with the robust plan (RP) were analyzed and compared with the original standard plan, calculating the dose distributions on the residual CBCTs. ResultsThe RP was shown to achieve optimal coverage of the CTV even in the worst scenario, with significantly lower doses to the rectum and bladder. CTV coverage of the RP was statistically better than the standard plan in terms of D99 (P = .008) and D98 (P = .02). Statistically significant mean dose reduction and D2 reduction were noted for the rectum (P < .05) and bladder (P < .009). Moreover, the RP appeared to be less sensitive to bladder and rectal filling. ConclusionsThis adaptive strategy in prostate cancer radiation therapy is feasible and safe; it may be used to adapt the treatment with better target coverage and organs-at-risk sparing than standard planning target volume–based planning.

Improving 3D ultrasound prostate localisation in radiotherapy through increased automation of interfraction matching

Background and purposeDaily image guidance is standard care for prostate radiotherapy. Innovations which improve the accuracy and efficiency of ultrasound guidance are needed, particularly with respect to reducing interobserver variation. This study explores automation tools for this purpose, demonstrated on the Elekta Clarity Autoscan®. The study was conducted as part of the Clarity-Pro trial (NCT02388308). Materials and methodsUltrasound scan volumes were collected from 32 patients. Prostate matches were performed using two proposed workflows and the results compared with Clarity’s proprietary software. Gold standard matches derived from manually localised landmarks provided a reference. The two workflows incorporated a custom 3D image registration algorithm, which was benchmarked against a third-party application (Elastix). ResultsSignificant reductions in match errors were reported from both workflows compared to standard protocol. Median (IQR) absolute errors in the left–right, anteroposterior and craniocaudal axes were lowest for the Manually Initiated workflow: 0.7(1.0) mm, 0.7(0.9) mm, 0.6(0.9) mm compared to 1.0(1.7) mm, 0.9(1.4) mm, 0.9(1.2) mm for Clarity. Median interobserver variation was ≪0.01 mm in all axes for both workflows compared to 2.2 mm, 1.7 mm, 1.5 mm for Clarity in left–right, anteroposterior and craniocaudal axes. Mean matching times was also reduced to 43 s from 152 s for Clarity. Inexperienced users of the proposed workflows attained better match precision than experienced users on Clarity. ConclusionAutomated image registration with effective input and verification steps should increase the efficacy of interfraction ultrasound guidance compared to the current commercially available tools.

Airborne high-resolution image motion target detection combined with hyperspectral features

Aiming at moving object detection in Airborne Hyperspectral Remote Sensing Images under complex background, this paper proposes a background removal method based on Mixture Gauss Model. Firstly, in order to eliminate the influence of the dithering of airborne platform on remote sensing image, this paper uses affine transform-based image registration algorithm to achieve the image registration of 3D data. Then, this paper selects specific spectral images, establishes the Mixture Gauss background model, and subtracts the background to achieve the extraction of moving objects. The experimental results show that the method can extract moving objects in Airborne Hyperspectral Remote Sensing Images effectively.

Enhanced Monomodal Image Registration Process With Cuckoo Search Algorithm

Medical image registration is one of the processes involved in medical image analysis. During the process, an image will be computed and transform it for mapping the reference image to the target image to analyze the similarity merits as to help in diagnosis the situation in the medical field. However, the accuracy of the image registration is in question, might be improved if we can make use some optimization during the image registration process. In this research, we propose an enhancement of image registration algorithms based on monomodal registration by incorporating Cuckoo Search (CS) method for Lévy flight generation while simultaneously modifying and optimizing it to work on MRI image scanners, specifically to detect brain cancer. The performance of the proposed monomodal registration with CS algorithm was compared with basic traditional monomodal registration. The experimental results were validated by measuring the Normalized Mutual Information (NMI) and CPU run-time for all cases investigated. Our results show that the proposed monomodal registration with CS algorithm achieved the best 2% improved in NMI results and 42% reduced in CPU run-time. The method evolved to be more promising and computationally efficient for medical image registration.

Performance of a deformable image registration algorithm for CT and cone beam CT using physical multi-density geometric and digital anatomic phantoms

To study the accuracy of deformable registration algorithm for CT and cone beam CT (CBCT) using a combination of physical and digital phantoms. The physical phantoms consisted of objects over a range of electron densities, shape and sizes. The system was tested for simple and complex scenarios including performance in the presence of metallic artefacts. Clinically present deformations were simulated using a set of five geometric and anatomic virtual phantoms. The system could not account for large changes in size, shape and Hounsfield units. Deformations of low intensity structures and small objects were highly inaccurate, and errors were prominent for volume reduction scenario than volume growth. The presence of artefacts did alter the performance of the algorithm. Objects of low density and that close to artefacts were affected the most. Overall, deformations to CBCT were poor. In virtual phantoms, the system could not handle gas pockets and deformation errors in inverse direction were higher than that in forward direction. The algorithm was tested for several non-clinical and clinical scenarios. The performance was acceptable for realistic and clinically present deformations. However, it is necessary to tread cautiously for structures with small volumes and large reductions in volume.

Evaluation of an x-ray CT polymer gel dosimetry system in the measurement of deformed dose

This study is an evaluation of the use of a N-isopropylacrylamide (NIPAM)-based x-ray CT polymer gel dosimetry (PGD) system in the measurement of deformed dose. This work also compares dose that is measured by the gel dosimetry system to dose calculated by a novel deformable dose accumulation algorithm, defDOSXYZnrc, that uses direct voxel tracking. Deformable gels were first irradiated using a single 3.5 × 5 cm2 open field and the static dose was compared to defDOSXYZnrc as a control measurement. Gel measurement was found to be in excellent agreement with defDOSXYZnrc in the static case with gamma passing rates of 94.5% using a 3%/3 mm criterion and 93.3% using a 3%/2 mm criterion. Following the static measurements, a deformable gel was irradiated with the same single field under an external compression of 25 mm and then released from this compression for dosimetric read out. The measured deformed dose was then compared to deformed dose calculated by defDOSXYZnrc based on deformation vectors produced by the Velocity AI deformable image registration (DIR) algorithm. In the deformed dose distribution there were differences in the measured and calculated field position of up to 0.8 mm and differences in the measured in calculated field size of up to 11.9 mm. Gamma pass rates were 60.0% using a 3%/3 mm criterion and 56.8% using a 3%/2 mm criterion for the deforming measurements representing a decrease in agreement compared to the control measurements. Further analysis showed that passing rates increased to 86.5% using a 3%/3 mm criterion and 70.5% using a 3%/2 mm criterion in voxels within 5 mm of fiducial markers used to guide the deformable image registration. This work represents the first measurement of deformed dose using x-ray CT polymer gel dosimetry. Overall these results highlight some of the challenges in the calculation and measurement of deforming dose and provide insight into possible strategies for improvement.

Clinical feasibility of MR-assisted CT-based cervical brachytherapy using MR-to-CT deformable image registration

PurposeThe purpose of this study is to evaluate the feasibility of using deformable image registration algorithms to improve high-dose-rate high-risk clinical target volume (HR-CTV) delineation between preapplicator implantation MRI (pre-MRI) and postapplicator implantation CT (post-CT) in the treatment of locally advanced cervical cancer (LACC). Method and materialsTwenty-six patients were identified for the study. Regions of interest were segmented on MRI and CT. A HR-CTV was delineated on pre-MRI and compared with the previously contoured HR-CTV on the post-CT. Two commercially available algorithms, ANACONDA (anatomically constrained) and MORFEUS (biomechanical model based) with various controlling structure settings, including the cervix, uterus, etc., were used to deform pre-MRI to post-CT. MRI-to-CT deformed targets are denoted as HR-CTV’. Quantitative deformation metrics include Dice index, distance to agreement, and center of mass displacement. Qualitative clinical usefulness of deformations was scored based on HR-CTV identification on CT images. ResultsFor ANACONDA and MORFEUS deformations, using a cervix controlling region of interest resulted in the highest Dice, lowest distance to agreement, and lowest center of mass displacement for HR-CTV′. With MORFEUS deformations, the deformed HR-CTV’ proved clinically useful in 23 patients. ConclusionsPrebrachytherapy implantation MRI can aid target contours for CT-based brachytherapy through ANACONDA or MORFEUS algorithms with appropriate parameter selection for LACC patients.