Evaluation of deformable image registration accuracy for CT images of the thorax region

Quantifying dose uncertainties resulting from cardiorespiratory motion in intensity-modulated proton therapy for cardiac stereotactic body radiotherapy

Background

Cardiac stereotactic body radiotherapy (CSBRT) with photons efficaciously and safely treats cardiovascular arrhythmias. Proton therapy, with its unique physical and radiobiological properties, can offer advantages over traditional photon-based therapies in certain clinical scenarios, particularly pediatric tumors and those in anatomically challenging areas. However, dose uncertainties induced by cardiorespiratory motion are unknown.

Objective

This study investigated the effect of cardiorespiratory motion on intensity-modulated proton therapy (IMPT) and the effectiveness of motion-encompassing methods.

Methods

We retrospectively included 12 patients with refractory arrhythmia who underwent CSBRT with four-dimensional computed tomography (4DCT) and 4D cardiac CT (4DcCT). Proton plans were simulated using an IBA accelerator based on the 4D average CT. The prescription was 25 Gy in a single fraction, with all plans normalized to ensure that 95% of the target volume received the prescribed dose. 4D dose reconstruction was performed to generate 4D accumulated and dynamic doses. Furthermore, dose uncertainties due to the interplay effect of the substrate target and organs at risk (OARs) were assessed. The differences between internal organs at risk volume (IRV) and OARreal (manually contoured on average CT) were compared. In 4D dynamic dose, meeting prescription requirements entails V25 and D95 reaching 95% and 25 Gy, respectively.

Results

The 4D dynamic dose significantly differed from the 3D static dose. The mean V25 and D95 were 89.23% and 24.69 Gy, respectively, in 4DCT and 94.35% and 24.99 Gy, respectively, in 4DcCT. Eleven patients in 4DCT and six in 4DcCT failed to meet the prescription requirements. Critical organs showed varying dose increases. All metrics, except for Dmean and D50, significantly changed in 4DCT; in 4DcCT, only D50 remained unchanged with regards to the target dose uncertainties induced by the interplay effect. The interplay effect was only significant for the Dmax values of several OARs. Generally, respiratory motion caused a more pronounced interplay effect than cardiac pulsation. Neither IRV nor OARreal effectively evaluated the dose discrepancies of the OARs.

Conclusions

Complex cardiorespiratory motion can introduce dose uncertainties during IMPT. Motion-encompassing techniques may mitigate but cannot entirely compensate for the dose discrepancies. Individualized 4D dose assessments are recommended to verify the effectiveness and safety of CSBRT.

The Investigating Image Registration Accuracy and Contour Propagation for Adaptive Radiotherapy Purposes in Line with the Task Group No. 132 Recommendation

Purpose

Image registration is a crucial component of the adaptive radiotherapy workflow. This study investigates the accuracy of the deformable image registration (DIR) and contour propagation features of SmartAdapt, an application in the Eclipse treatment planning system (TPS) version 16.1.

Materials and Methods

The registration accuracy was validated using the Task Group No. 132 (TG-132) virtual phantom, which features contour evaluation and landmark analysis based on the quantitative criteria recommended in the American Association of Physicists in Medicine TG-132 report. The target registration error, Dice similarity coefficient (DSC), and center of mass displacement were used as quantitative validation metrics. The performance of the contour propagation feature was evaluated using clinical datasets (head and neck, pelvis, and chest) and an additional four-dimensional computed tomography (CT) dataset from TG-132. The primary planning and the second CT images were appropriately registered and deformed. The DSC was used to find the volume overlapping between the deformed contours and the radiation oncologist (RO)-drawn contour. The clinical value of the DIR-generated structure was reviewed and scored by an experienced RO to make a qualitative assessment.

Results

The registration accuracy fell within the specified tolerances. SmartAdapt exhibited a reasonably propagated contour for the chest and head-and-neck regions, with DSC values of 0.80 for organs at risk. Misregistration is frequently observed in the pelvic region, which is specified as a low-contrast region. However, 78% of structures required no modification or minor modification, demonstrating good agreement between contour comparison and the qualitative analysis.

Conclusions

SmartAdapt has adequate efficiency for image registration and contour propagation for adaptive purposes in various anatomical sites. However, there should be concern about its performance in regions with low contrast and small volumes.

Review and recommendations on deformable image registration uncertainties for radiotherapy applications

Deformable image registration (DIR) is a versatile tool used in many applications in radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment planning systems providing accessible and easy-to-use solutions. However, the geometric uncertainty of DIR can be large and difficult to quantify, resulting in barriers to clinical practice. Currently, there is no agreement in the RT community on how to quantify these uncertainties and determine thresholds that distinguish a good DIR result from a poor one. This review summarises the current literature on sources of DIR uncertainties and their impact on RT applications. Recommendations are provided on how to handle these uncertainties for patient-specific use, commissioning, and research. Recommendations are also provided for developers and vendors to help users to understand DIR uncertainties and make the application of DIR in RT safer and more reliable.

The application of multiple metrics in deformable image registration for target volume delineation of breast tumor bed

BACKGROUND AND PURPOSE

For postoperative breast cancer patients, deformable image registration (DIR) is challenged due to the large deformations and non-correspondence caused by tumor resection and clip insertion. To deal with it, three metrics (fiducial-, region-, and intensity-based) were jointly used in DIR algorithm for improved accuracy.

MATERIALS AND METHODS

Three types of metrics were combined to form a single-objective function in DIR algorithm. Fiducial-based metric was used to minimize the distance between the corresponding point sets of two images. Region-based metric was used to improve the overlap between the corresponding areas of two images. Intensity-based metric was used to maximize the correlation between the corresponding voxel intensities of two images. The two CT images, one before surgery and the other after surgery, were acquired from the same patient in the same radiotherapy treatment position. Twenty patients who underwent breast-conserving surgery and postoperative radiotherapy were enrolled in this study.

RESULTS

For target registration error, the difference between the proposed and the conventional registration methods was statistically significant for soft tissue (2.06 vs. 7.82, p = 0.00024 < 0.05) and body boundary (3.70 vs. 6.93, p = 0.021 < 0.05). For visual assessment, the proposed method achieved better matching result for soft tissue and body boundary.

CONCLUSIONS

Comparing to the conventional method, the registration accuracy of the proposed method was significantly improved. This method provided a feasible way for target volume delineation of tumor bed in postoperative radiotherapy of breast cancer patients.

Evaluation of DIR algorithm performance in real patients for radiotherapy treatments: A systematic review of operator-dependent strategies

PURPOSE

The performance of deformable medical image registration (DIR) algorithms has become a major concern.

METHODS

We aimed to obtain updated information on DIR algorithm performance quantification through a literature review of articles published between 2010 and 2022. We focused only on studies using operator-based methods to treat real patients. The PubMed, Google Scholar and Embase databases were searched following PRISMA guidelines.

RESULTS

One hundred and seven articles were identified. The mean number of patients and registrations per publication was 20 and 63, respectively. We found 23 different geometric metrics appearing at least twice, and the dosimetric impact of DIR was quantified in 32 articles. Forty-eight different at-risk organs were described, and target volumes were studied in 43 publications. Prostate, head-and-neck and thoracic locations represented more than ¾ of the studied locations. We summarized the type of DIR and the images used, and other key elements. Intra/interobserver variability, threshold values and the correlation between metrics were also discussed.

CONCLUSIONS

This literature review covers the past decade and should facilitate the implementation of DIR algorithms in clinical practice by providing practical and pertinent information to quantify their performance on real patients.

Rigid and Deformable Image Registration for Radiation Therapy: A Self-Study Evaluation Guide for NRG Oncology Clinical Trial Participation

PURPOSE

The registration of multiple imaging studies to radiation therapy computed tomography simulation, including magnetic resonance imaging, positron emission tomography-computed tomography, etc. is a widely used strategy in radiation oncology treatment planning, and these registrations have valuable roles in image guidance, dose composition/accumulation, and treatment delivery adaptation. The NRG Oncology Medical Physics subcommittee formed a working group to investigate feasible workflows for a self-study credentialing process of image registration commissioning.

METHODS AND MATERIALS

The American Association of Physicists in Medicine (AAPM) Task Group 132 (TG132) report on the use of image registration and fusion algorithms in radiation therapy provides basic guidelines for quality assurance and quality control of the image registration algorithms and the overall clinical process. The report recommends a series of tests and the corresponding metrics that should be evaluated and reported during commissioning and routine quality assurance, as well as a set of recommendations for vendors. The NRG Oncology medical physics subcommittee working group found incompatibility of some digital phantoms with commercial systems. Thus, there is still a need to provide further recommendations in terms of compatible digital phantoms, clinical feasible workflow, and achievable thresholds, especially for future clinical trials involving deformable image registration algorithms. Nine institutions participated and evaluated 4 commonly used commercial imaging registration software and various versions in the field of radiation oncology.

RESULTS AND CONCLUSIONS

The NRG Oncology Working Group on image registration commissioning herein provides recommendations on the use of digital phantom/data sets and analytical software access for institutions and clinics to perform their own self-study evaluation of commercial imaging systems that might be employed for coregistration in radiation therapy treatment planning and image guidance procedures. Evaluation metrics and their corresponding values were given as guidelines to establish practical tolerances. Vendor compliance for image registration commissioning was evaluated, and recommendations were given for future development.

Improving deformable image registration with point metric and masking technique for postoperative breast cancer radiotherapy

Background

Deformable image registration (DIR) is increasingly used for target volume definition in radiotherapy. However, this method is challenging for postoperative breast cancer patients due to the large deformations and non-correspondence caused by tumor resection and clip insertion. In this study, an improved B-splines based DIR method was developed to address this issue for higher registration accuracy.

Methods

The conventional B-splines based DIR method was improved with the introduction of point metric and masking technique. The point metric minimizes the distance between 2 point sets with known correspondence for regularization of intensity-based B-splines registration. The masking technique reduces the influence of non-corresponding regions in breast computed tomography (CT) images. Two sets of CT images before and after breast surgery were used for image registration. One set was the diagnostic CT image acquired before surgery, and another set was the planning CT image acquired after surgery for breast cancer radiotherapy. A total of 26 sets of CT images from 13 patients were collected retrospectively for the test. The improved DIR method's registration accuracy was evaluated by target registration error (TRE), the Jacobian determinant, and visual assessment.

Results

For soft tissue, the difference in the median TRE between the improved DIR method and the conventional DIR method was statistically significant (2.27 vs. 5.88, P<0.05). The Jacobian determinant of the deformation field was positive for all patients. For visual assessment, the improved DIR method with point metric achieved better matching for soft tissue.

Conclusions

The improved DIR method's registration accuracy was higher than the conventional DIR method based on the preliminary results. With point metric and masking technique, the influence of large deformations and non-correspondence on registration between pre- and post-operative CT images can be effectively reduced. Therefore, this method provides a feasible way for target volume definition in postoperative breast cancer radiotherapy treatment planning.

Evaluation of Varian's SmartAdapt for clinical use in radiation therapy for patients with thoracic lesions

INTRODUCTION

Deformable image registration (DIR) is a required tool in any adaptive radiotherapy program to help account for anatomical changes that occur during a multifraction treatment. SmartAdapt is a DIR tool from Varian incorporated within the eclipse treatment planning system, that can be used for contour propagation and transfer of PET, MRI, or computed tomography (CT) data. The purpose of this work is to evaluate the registration and contour propagation accuracy of SmartAdapt for thoracic CT studies using the guidelines from AAPM TG 132.

METHODS

To evaluate the registration accuracy of SmartAdapt the mean target registration error (TRE) was measured for ten landmarked 4DCT images from the https://www.dir-labs.com/ which included 300 landmarks matching the inspiration and expiration phase images. To further characterize the registration accuracy, the magnitude of deformation for each 4DCT was measured and compared against the mean TRE for each study. Contour propagation accuracy was evaluated using 22 randomly selected lung cancer cases from our center where there was either a replan, or the patient was treated for a new lesion within the lung. Contours evaluated included the right and left lung, esophagus, spinal canal, heart and the GTV and the results were quantified using the DICE similarity coefficient.

RESULTS

The mean TRE from all ten cases was 1.89 mm, the maximum mean TRE per case was 3.8 mm from case #8, which also had the most landmark pairs with displacements >2 cm. For contour propagation accuracy, the DICE coefficient results for left lung, right lung, heart, esophagus, and spinal canal were 0.93, 0.94, 0.90, 0.61, and 0.82 respectively.

CONCLUSION

The results from our study demonstrate that for thoracic images SmartAdapt in most cases will be accurate to below 2 mm in registration error unless there is deformation greater than 2 cm.

Adaptive radiotherapy based on statistical process control for oropharyngeal cancer

PURPOSE

The purpose of this study is to quantify dosimetric changes throughout the delivery of oropharyngeal cancer treatment and to investigate the application of statistical process control (SPC) for the management of significant deviations during the course of radiotherapy.

METHODS

Thirteen oropharyngeal cancer patients with daily cone beam computed tomography (CBCT) were retrospectively reviewed. Cone beam computed tomography images of every other fraction were imported to the Velocity software and registered to planning CT using the 6 DOF (degrees of freedom) couch shifts generated during patient setup. Using Velocity "Adaptive Monitoring" module, the setup-corrected CBCT was matched to planning CT using a deformable registration. Volumes and dose metrics at each fraction were calculated and rated with plan values to evaluate interfractional dosimetric variations using a SPC framework. T-tests between plan and fraction volumes were performed to find statistically insignificant fractions. Average upper and lower process capacity limits (UCL, LCL) of each dose metric were derived from these fractions using conventional SPC guidelines.

RESULTS

Gross tumor volume (GTV) and organ at risk (OAR) volumes in the first 13 fractions had no significant changes from the pretreatment planning CT. The GTV and the parotid glands subsequently decreased by 10% at the completion of treatment. There were 3-4% increases in parotid mean doses, but no significant differences in dose metrics of GTV and other OARs. The changes were organ and patient dependent. Control charts for various dose metrics were generated to assess the metrics at each fraction for individual patient.

CONCLUSIONS

Daily CBCT could be used to monitor dosimetric variations of targets and OARs resulting from volume changes and tissue deformation in oropharyngeal cancer radiotherapy. Treatment review with the guidance of a SPC tool allows for an objective and consistent clinical decision to apply adaptive radiotherapy.

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

PURPOSE

A contour propagation study has been conducted to benchmark three algorithms for Deformable Image Registration (DIR) freely available online against well-established commercial solutions.

METHODS

ElastiX, 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.

RESULTS

The 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.

CONCLUSIONS

All 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.

Investigation of 4D dose in volumetric modulated arc therapy-based stereotactic body radiation therapy: does fractional dose or number of arcs matter?

The aim of this study was to assess the impact of fractional dose and the number of arcs on interplay effects when volumetric modulated arc therapy (VMAT) is used to treat lung tumors with large respiratory motions. A three (fractional dose of 4, 7.5 or 12.5 Gy) by two (number of arcs, one or two) VMAT plan was created for 10 lung cancer cases. The median 3D tumor motion was 17.9 mm (range: 8.2-27.2 mm). Ten phase-specific subplans were generated by calculating the dose on each respiratory phase computed tomography (CT) scan using temporally assigned VMAT arcs. We performed temporal assignment of VMAT arcs using respiratory information obtained from infrared markers placed on the abdomens of the patients during CT simulations. Each phase-specific dose distribution was deformed onto exhale phase CT scans using contour-based deformable image registration, and a 4D plan was created by dose accumulation. The gross tumor volume dose of each 4D plan (4D GTV dose) was compared with the internal target volume dose of the original plan (3D ITV dose). The near-minimum 4D GTV dose (D99%) was higher than the near-minimum 3D internal target volume (ITV) dose, whereas the near-maximum 4D GTV dose (D1%) was lower than the near-maximum 3D ITV dose. However, the difference was negligible, and thus the 4D GTV dose corresponded well with the 3D ITV dose, regardless of the fractional dose and number of arcs. Therefore, interplay effects were negligible in VMAT-based stereotactic body radiation therapy for lung tumors with large respiratory motions.

Dosimetric study of three-dimensional static and dynamic SBRT radiotherapy for hepatocellular carcinoma based on 4DCT image deformable registration

The purpose of this work was to determine the actual dose received by normal tissues during four‐dimensional radiation therapy (4DRT) composed of ten phases of four‐dimensional computer tomography (4DCT) images. The analysis was performed by tracking the hepatocellular carcinoma SBRT. Data were acquired from the tracking of each phase with the beam aperture for 28 hepatocellular carcinoma patients, and the data were used to generate a cumulative plan, which was compared to a three‐dimensional (3D) plan formed from a merged target volume based on 4DCT images in a radiation treatment planning system (TPS). The change in normal tissue dose was evaluated in the plan using the parameters V5, V10, V15, V20, V25, V30, V35, and V40 (volumes receiving 5, 10, 15, 20, 25, 30, 35, and 40 Gy, respectively) in the dose‐volume histogram for the liver; the mean dose was analyzed for the following tissues: liver, left kidney, and right kidney. The maximum dose was analyzed for the following tissues: bowel, duodenum, esophagus, stomach, and heart. There was a significant difference in the dose between the 4D planning target volume (PTV) (average 115.71 cm³) and ITV (169.86 cm³). The planning objective was for 95% of the volume of the PTV to be covered by the prescription dose, but the mean dose for the liver, left kidney and right kidney had an average decrease of 23.13%, 49.51%, and 54.38%, respectively. The maximum dose for the bowel, duodenum, esophagus, stomach, and heart had an average decrease of 16.77%, 28.07%, 24.28%, 4.89%, and 4.45%, respectively. Compared to 3D RT, the radiation volume for the liver V5, V10, V15, V20, V25, V30, V35, and V40 using the 4D plans had a significant decrease (P ﹤ 0.05). The 4D method creates plans that permit sparing of the normal tissues more than the commonly used ITV method, which delivers the same dosimetric effects to the target.

"Après Mois, Le Déluge": Preparing for the Coming Data Flood in the MRI-Guided Radiotherapy Era

Magnetic resonance imaging provides a sea of quantitative and semi-quantitative data. While radiation oncologists already navigate a pool of clinical (semantic) and imaging data, the tide will swell with the advent of hybrid MRI/linear accelerator devices and increasing interest in MRI-guided radiotherapy (MRIgRT), including adaptive MRIgRT. The variety of MR sequences (of greater complexity than the single parameter Hounsfield unit of CT scanning routinely used in radiotherapy), the workflow of adaptive fractionation, and the sheer quantity of daily images acquired are challenges for scaling this technology. Biomedical informatics, which is the science of information in biomedicine, can provide helpful insights for this looming transition. Funneling MRIgRT data into clinically meaningful information streams requires committing to the flow of inter-institutional data accessibility and interoperability initiatives, standardizing MRIgRT dosimetry methods, streamlining MR linear accelerator workflow, and standardizing MRI acquisition and post-processing. This review will attempt to conceptually ford these topics using clinical informatics approaches as a theoretical bridge.

Evaluation of Intensity- and Contour-Based Deformable Image Registration Accuracy in Pancreatic Cancer Patients

We aimed to clarify the accuracy of rigid image registration and deformable image registration (DIR) in carbon-ion radiotherapy (CIRT) for pancreatic cancer. Six patients with pancreatic cancer who were treated with passive irradiation CIRT were enrolled. Three registration patterns were evaluated: treatment planning computed tomography images (TPCT) to CT images acquired in the treatment room (IRCT) in the supine position, TPCT to IRCT in the prone position, and TPCT in the supine position to the prone position. After warping the contours of the original CT images to the destination CT images using deformation matrices from the registration, the warped delineated contours on the destination CT images were compared with the original ones using mean displacement to agreement (MDA). Four contours (clinical target volume (CTV), gross tumor volume (GTV), stomach, duodenum) and four registration algorithms (rigid image registration [RIR], intensity-based DIR [iDIR], contour-based DIR [cDIR], and a hybrid iDIR-cDIR ([hDIR]) were evaluated. The means ± standard deviation of the MDAs of all contours for RIR, iDIR, cDIR, and hDIR were 3.40 ± 3.30, 2.2 1± 2.48, 1.46 ± 1.49, and 1.46 ± 1.37 mm, respectively. There were significant differences between RIR and iDIR, and between RIR/iDIR and cDIR/hDIR. For the pancreatic cancer patient images, cDIR and hDIR had better accuracy than RIR and iDIR.

Prospective quantitative quality assurance and deformation estimation of MRI-CT image registration in simulation of head and neck radiotherapy patients

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MRI-CT deformable image registration was not superior to rigid registration.

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Dice similarity coefficients were 0.65, 0.62, and 0.63 for deformable registrations.

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Dice similarity coefficient was 0.63 for rigid registration.

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Registration quality was superior in muscle and gland compared to bone and vessel.

Background

MRI-guided radiotherapy planning (MRIgRT) may be superior to CT-guided planning in some instances owing to its improved soft tissue contrast. However, MR images do not communicate tissue electron density information necessary for dose calculation and therefore must either be co-registered to CT or algorithmically converted to synthetic CT. No robust quality assessment of commercially available MR-CT registration algorithms is yet available; thus we sought to quantify MR-CT registration formally.

Methods

Head and neck non-contrast CT and T2 MRI scans acquired with standard treatment immobilization techniques were prospectively acquired from 15 patients. Per scan, 35 anatomic regions of interest (ROIs) were manually segmented. MRIs were registered to CT rigidly (RIR) and by three commercially available deformable registration algorithms (DIR). Dice similarity coefficient (DSC), Hausdorff distance mean (HD mean) and Hausdorff distance max (HD max) metrics were calculated to assess concordance between MRI and CT segmentations. Each DIR algorithm was compared to DIR using the nonparametric Steel test with control for individual ROIs (n = 105 tests) and for all ROIs in aggregate (n = 3 tests). The influence of tissue type on registration fidelity was assessed using nonparametric Wilcoxon pairwise tests between ROIs grouped by tissue type (n = 12 tests). Bonferroni corrections were applied for multiple comparisons.

Results

No DIR algorithm improved the segmentation quality over RIR for any ROI nor all ROIs in aggregate (all p values >0.05). Muscle and gland ROIs were significantly more concordant than vessel and bone, but DIR remained non-different from RIR.

Conclusions

For MR-CT co-registration, our results question the utility and applicability of commercially available DIR over RIR alone. The poor overall performance also questions the feasibility of translating tissue electron density information to MRI by CT registration, rather than addressing this need with synthetic CT generation or bulk-density assignment.

Phantom tumor of the lung in patient with pneumonia

Introduction: Localized interlobar effusions in congestive heart failure (phantom or vanishing lung tumor/s) are infrequent, but widely recognized entities. Case report: A 80-years-old woman affected by progressive dyspnea over the previous three months, with productive cough. She was treated hypertension and had a pace maker implanted due to bradycardia. Chest X ray has shown right side pneumonia with high positive inflammatory markers. After resolution of pneumonia, phantom tumor of the lung was revealed, which disappear with intensive loop diuretics. Conclusions: The diagnosis of the phantom tumor ought to be pondered as a possibility in any patient with congestive heart failure and lung mass. The patient at hand featured no prior history of congestive heart failure, hence indicating that phantom tumor may occur in non-chronic heart failure patients. Albeid the reliable diagnosis of the phantom tumor through the utilization of imaging modalities in patients without congestive heart failure can be rather challenging, such possibility must be considered in a patient with a lung mass in the major fissure of the lungs. Due to accelerated expansion of the geriatric population and subsequent spread of the congestive heart failure, a rise in the incidence of vanishing tumors of the lung may be anticipated.