Variability in commercially available deformable image registration: A multi-institution analysis using virtual head and neck phantoms

Creating patient-specific digital phantoms with a longitudinal atlas for evaluating deformable CT-CBCT registration in adaptive lung radiotherapy

BACKGROUND

Quality assurance of deformable image registration (DIR) is challenging because the ground truth is often unavailable. In addition, current approaches that rely on artificial transformations do not adequately resemble clinical scenarios encountered in adaptive radiotherapy.

PURPOSE

We developed an atlas-based method to create a variety of patient-specific serial digital phantoms with CBCT-like image quality to assess the DIR performance for longitudinal CBCT imaging data in adaptive lung radiotherapy.

METHODS

A library of deformations was created by extracting the longitudinal changes observed between a planning CT and weekly CBCT from an atlas of lung radiotherapy patients. The planning CT of an inquiry patient was first deformed by mapping the deformation pattern from a matched atlas patient, and subsequently appended with CBCT artifacts to imitate a weekly CBCT. Finally, a group of digital phantoms around an inquiry patient was produced to simulate a series of possible evolutions of tumor and adjacent normal structures. We validated the generated deformation vector fields (DVFs) to ensure numerically and physiologically realistic transformations. The proposed framework was applied to evaluate the performance of the DIR algorithm implemented in the commercial Eclipse treatment planning system in a retrospective study of eight inquiry patients.

RESULTS

The generated DVFs were inverse consistent within less than 3 mm and did not exhibit unrealistic folding. The deformation patterns adequately mimicked the observed longitudinal anatomical changes of the matched atlas patients. Worse Eclipse DVF accuracy was observed in regions of low image contrast or artifacts. The structure volumes exhibiting a DVF error magnitude of equal or more than 2 mm ranged from 24.5% (spinal cord) to 69.2% (heart) and the maximum DVF error exceeded 5 mm for all structures except the spinal cord. Contour-based evaluations showed a high degree of alignment with dice similarity coefficients above 0.8 in all cases, which underestimated the overall DVF accuracy within the structures.

CONCLUSIONS

It is feasible to create and augment digital phantoms based on a particular patient of interest using multiple series of deformation patterns from matched patients in an atlas. This can provide a semi-automated procedure to complement the quality assurance of CT-CBCT DIR and facilitate the clinical implementation of image-guided and adaptive radiotherapy that involve longitudinal CBCT imaging studies.

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.

An approach to generate synthetic 4DCT datasets to benchmark Mid-Position implementations

PURPOSE

The Mid-Position image is constructed from 4DCT data using Deformable Image Registration and can be used as planning CT with reduced PTV volumes. 4DCT datasets currently-available for testing do not provide the corresponding Mid-P images of the datasets. This work describes an approach to generate human-like synthetic 4DCT datasets with the associated Mid-P images that can be used as reference in the validation of Mid-P implementations.

METHODS

Twenty synthetic 4DCT datasets with the associated reference Mid-P images were generated from twenty clinical 4DCT datasets. Per clinical dataset, an anchor phase was registered to the remaining nine phases to obtain nine Deformable Vector Fields (DVFs). These DVFs were used to warp the anchor phase in order to generate the synthetic 4DCT dataset and the corresponding reference Mid-P image. Similarly, a reference 4D tumor mask dataset and its corresponding Mid-P tumor mask were generated. The generated synthetic datasets and masks were used to compare and benchmark the outcomes of three independent Mid-P implementations using a set of experiments.

RESULTS

The Mid-P images constructed by the three implementations showed high similarity scores when compared to the reference Mid-P images except for one noisy dataset. The biggest difference in the estimated motion amplitudes (-2.6 mm) was noticed in the Superior-Inferior direction. The statistical analysis showed no significant differences among the three implementations for all experiments.

CONCLUSION

The described approach and the proposed experiments provide an independent method that can be used in the validation of any Mid-P implementation being developed.

CBCT-based deformable dose accumulation of external beam radiotherapy in cervical cancer

Background: Delivered radiotherapy doses do not exactly match those planned for a course of treatment, largely due to inter-fraction changes in anatomy. In this study, accumulated delivered dose was calculated for a sample of cervical cancer patients, by deformably registering daily cone beam computed tomography (CBCT) images to the planning computed tomography (CT) scan. Planned and accumulated doses were compared for the clinical target volume (CTV), bladder, and rectum.Material and Methods: For 10 patients receiving 45 Gy in 25 fractions of external beam radiotherapy, daily dose distributions were calculated on CBCT. These images were deformed onto the planning CT and the dose was accumulated using Velocity 4.1 (Varian Medical Systems, Palo Alto, USA). The quality of deformable image registration was evaluated visually and by calculating Dice similarity coefficients and mean distance to agreement.Results: V95%>99% was achieved for the primary CTV in 9/10 patients for the planned dose distribution and 7/10 patients for the accumulated dose distribution. Primary CTV coverage by 95% of the prescription dose was reduced in one patient, due to an increase in anterior-posterior separation. Comparison of planned and accumulated dose volume histograms (DVHs) for the bladder and rectum found agreement within 5% at low and intermediate doses, but differences exceeded 20% at higher doses. Direct addition of CBCT DVHs was seen to be a poor estimate for the accumulated DVH at higher doses.Conclusion: Computation of delivered radiotherapy dose that accounts for inter-fraction anatomical changes is important for establishing dose-effect relationships. Updating delivered dose distributions after each fraction would support informed clinical decision making on any potential treatment interventions.

Comparison of Three Commercial Methods of Cone-Beam Computed Tomography-Based Dosimetric Analysis of Head-and-Neck Patients with Weight Loss

Purpose

This investigation compares three commercial methods of cone-beam computed tomography (CBCT)-based dosimetric analysis to a method based on repeat computed tomography (CT).

Materials and Methods

Seventeen head-and-neck patients treated in 2020, and with a repeat CT, were included in the analyses. The planning CT was deformed to anatomy in repeat CT to generate a reference plan. Two of the CBCT-based methods generated test plans by deforming the planning CT to CBCT of fraction N using VelocityAI™ and SmartAdapt®. The third method compared directly calculated doses on the CBCT for fraction 1 and fraction N, using PerFraction™. Maximum dose to spinal cord (Cord_dmax) and dose to 95% volume (D95) of planning target volumes (PTVs) were used to assess "need to replan" criteria.

Results

The VelocityAI™ method provided results that most accurately matched the reference plan in "need to replan" criteria using either Cord_dmax or PTV D95. SmartAdapt® method overestimated the change in Cord_dmax (6.77% vs. 3.85%, P < 0.01) and change in cord volume (9.56% vs. 0.67%, P < 0.01) resulting in increased false positives in "need to replan" criteria, and performed similarly to VelocityAI™ for D95, but yielded more false negatives. PerFraction™ method underestimated Cord_dmax, did not perform any volume deformation, and missed all "need to replan" cases based on cord dose. It also yielded high false negatives using the D95 PTV criteria.

Conclusions

The VelocityAI™-based method using fraction N CBCT is most similar to the reference plan using repeat CT; the other two methods had significant differences.

Evaluation and risk factors of volume and dose differences of selected structures in patients with head and neck cancer treated on Helical TomoTherapy by using Deformable Image Registration tool

Introduction: The aim of this study was the evaluation of volume and dose differences in selected structures in patients with head and neck cancer during treatment on Helical TomoTherapy (HT) using a commercially available deformable image registration (DIR) tool. We attempted to identify anatomical and clinical predictive factors for significant volume changes probability.

Material and methods: According to our institutional protocol, we retrospectively evaluated the group of 20 H&N cancer patients treated with HT who received Adaptive Radiotherapy (ART) due to soft tissue alterations spotted on daily MVCT. We compared volumes on initial computed tomography (iCT) and replanning computed tomography (rCT) for clinical target volumes (CTV) – CTV1 (the primary tumor) and CTV2 (metastatic lymph nodes), parotid glands (PG) and body contour (B-body). To estimate the planned and delivered dose discrepancy, the dose from the original plan was registered and deformed to create a simulation of dose distribution on rCT (DIR-rCT).

Results: The decision to replan was made at the 4th week of RT (N = 6; 30%). The average volume reduction in parotid right PG[R] and left PG[L] was 4.37 cc (18.9%) (p < 0.001) and 3.77 cc (16.8%) (p = 0.004), respectively. In N = 13/20 cases, the delivered dose was greater than the planned dose for PG[R] of mean 3 Gy (p < 0.001), and in N = 6/20 patients for PG[L] the mean of 3.6 Gy (p = 0.031). Multivariate regression analysis showed a very strong predictor explaining 88% (R2 = 0.88) and 83% (R2 = 0.83) of the variance based on the mean dose of iPG[R] and iPG[L] (p < 0.001), respectively. No statistically significant correlation between volume changes and risk factors was found.

Conclusions: Dosimetric changes to the target demonstrated the validity of replanning. A DIR tool can be successfully used for dose deformation and ART qualification, significantly reducing the workload of radiotherapy centers. In addition, the mean dose for PG was a significant predictor that may indicate the need for a replan.

Dosimetric variation in preoperative partial breast radiosurgery assessed by deformable image registrations

Objective

To assess dosimetric variation caused by breast deformation in breast radiosurgery based on deformable image registration.

Methods

This study included 30 patients who were treated in the prone position for preoperative partial breast radiosurgery. The biopsy clip in CBCT was aligned to the one from the planning CT. Deformable image registration (DIR) was performed to deform the planning CT into the CBCT, focusing on the breast shape. The treated plan (P_Tx) was recalculated based on the deformed CT. Thus, P_Tx represented the actual treatment delivered to the patient and was compared to the original plan (P_Org).

Results

The mean differences of target volumes covered by 95% and 100% of the prescribed dose between P_Org and P_Tx were less than 0.5%. The mean differences ± standard division for skin maximum dose (D_max), dose to 1cc (D_1cc) and D_10cc were 0.3 ± 0.7 Gy, 0.3 ± 0.6 Gy and 0.6 ± 0.6Gy between P_Org and P_Tx, respectively.

Conclusion

The treated plan was accurately recalculated based on the deformed CT. Despite slight variance in breast deformation, the dosimetric variation was very small, ensuring that adequate target coverage and skin dose were maintained during treatment as planned originally.