A cone beam CT-guided online plan modification technique to correct interfractional anatomic changes for prostate cancer IMRT treatment

Online adaptive planning methods for intensity-modulated radiotherapy

Online adaptive radiation therapy aims at adapting a patient's treatment plan to their current anatomy to account for inter-fraction variations before daily treatment delivery. As this process needs to be accomplished while the patient is immobilized on the treatment couch, it requires time-efficient adaptive planning methods to generate a quality daily treatment plan rapidly. The conventional planning methods do not meet the time requirement of online adaptive radiation therapy because they often involve excessive human intervention, significantly prolonging the planning phase. This article reviews the planning strategies employed by current commercial online adaptive radiation therapy systems, research on online adaptive planning, and artificial intelligence's potential application to online adaptive planning.

Adaptive proton therapy

Radiation therapy treatments are typically planned based on a single image set, assuming that the patient's anatomy and its position relative to the delivery system remains constant during the course of treatment. Similarly, the prescription dose assumes constant biological dose-response over the treatment course. However, variations can and do occur on multiple time scales. For treatment sites with significant intra-fractional motion, geometric changes happen over seconds or minutes, while biological considerations change over days or weeks. At an intermediate timescale, geometric changes occur between daily treatment fractions. Adaptive radiation therapy is applied to consider changes in patient anatomy during the course of fractionated treatment delivery. While traditionally adaptation has been done off-line with replanning based on new CT images, online treatment adaptation based on on-board imaging has gained momentum in recent years due to advanced imaging techniques combined with treatment delivery systems. Adaptation is particularly important in proton therapy where small changes in patient anatomy can lead to significant dose perturbations due to the dose conformality and finite range of proton beams. This review summarizes the current state-of-the-art of on-line adaptive proton therapy and identifies areas requiring further research.

Toward MR-integrated proton therapy: modeling the potential benefits for liver tumors

Magnetic resonance imaging (MRI)-integrated proton therapy (MRiPT) is envisioned to improve treatment quality for many cancer patients. However, given the availability of alternative image-guided strategies, its clinical need is yet to be justified. This study aims to compare the expected clinical outcomes of MRiPT with standard of practice cone-beam CT (CBCT)-guided PT, and other MR-guided methods, i.e. offline MR-guided PT and MR-linac, for treatment of liver tumors. Clinical outcomes were assessed by quantifying the dosimetric and biological impact of target margin reduction enabled by each image-guided approach. Planning target volume (PTV) margins were calculated using random and systematic setup, delineation and motion uncertainties, which were quantified by analyzing longitudinal MRI data for 10 patients with liver tumors. Proton treatment plans were created using appropriate PTV margins for each image-guided PT method. Photon plans with margins equivalent to MRiPT were generated to represent MR-linac. Normal tissue complication probabilities (NTCP) of the uninvolved liver were compared. We found that PTV margin can be reduced by 20% and 40% for offline MR-guided PT and MRiPT, respectively, compared with CBCT-guided PT. Furthermore, clinical target volume expansion could be largely alleviated when delineating on MRI rather than CT. Dosimetric implications included decreased equivalent mean dose of the uninvolved liver, i.e. up to 24.4 Gy and 27.3 Gy for offline MR-guided PT and MRiPT compared to CBCT-guided PT, respectively. Considering Child-Pugh score increase as endpoint, NTCP of the uninvolved liver was significantly decreased for MRiPT compared to CBCT-guided PT (up to 48.4%,p < 0.01), offline MR-guided PT (up to 12.9%,p < 0.01) and MR-linac (up to 30.8%,p < 0.05). Target underdose was possible in the absence of MRI-guidance (D90 reduction up to 4.2 Gy in 20% of cases). In conclusion, MRiPT has the potential to significantly reduce healthy liver toxicities in patients with liver tumors. It is superior to other image-guided techniques currently available.

Pelvic multi-organ segmentation on cone-beam CT for prostate adaptive radiotherapy

BACKGROUND AND PURPOSE

The purpose of this study is to develop a deep learning-based approach to simultaneously segment five pelvic organs including prostate, bladder, rectum, left and right femoral heads on cone-beam CT (CBCT), as required elements for prostate adaptive radiotherapy planning.

MATERIALS AND METHODS

We propose to utilize both CBCT and CBCT-based synthetic MRI (sMRI) for the segmentation of soft tissue and bony structures, as they provide complementary information for pelvic organ segmentation. CBCT images have superior bony structure contrast and sMRIs have superior soft tissue contrast. Prior to segmentation, sMRI was generated using a cycle-consistent adversarial networks (CycleGAN), which was trained using paired CBCT-MR images. To combine the advantages of both CBCT and sMRI, we developed a cross-modality attention pyramid network with late feature fusion. Our method processes CBCT and sMRI inputs separately to extract CBCT-specific and sMRI-specific features prior to combining them in a late-fusion network for final segmentation. The network was trained and tested using 100 patients' datasets, with each dataset including the CBCT and manual physician contours. For comparison, we trained another two networks with different network inputs and architectures. The segmentation results were compared to manual contours for evaluations.

RESULTS

For the proposed method, dice similarity coefficients and mean surface distances between the segmentation results and the ground truth were 0.96 ± 0.03, 0.65 ± 0.67 mm; 0.91 ± 0.08, 0.93 ± 0.96 mm; 0.93 ± 0.04, 0.72 ± 0.61 mm; 0.95 ± 0.05, 1.05 ± 1.40 mm; and 0.95 ± 0.05, 1.08 ± 1.48 mm for bladder, prostate, rectum, left and right femoral heads, respectively. As compared to the other two competing methods, our method has shown superior performance in terms of the segmentation accuracy.

CONCLUSION

We developed a deep learning-based segmentation method to rapidly and accurately segment five pelvic organs simultaneously from daily CBCTs. The proposed method could be used in the clinic to support rapid target and organs-at-risk contouring for prostate adaptive radiation therapy.

Clinical implementation of magnetic resonance imaging guided adaptive radiotherapy for localized prostate cancer

Background and purpose

Magnetic resonance-guided radiation therapy (MRgRT) has recently become available in clinical practice and is expected to expand significantly in coming years. MRgRT offers marker-less continuous imaging during treatment delivery, use of small clinical target volume (CTV) to planning target volume (PTV) margins, and finally the option to perform daily plan re-optimization.

Materials and methods

A total of 140 patients (700 fractions) have been treated with MRgRT and online plan adaptation for localized prostate cancer since early 2016. Clinical workflow for MRgRT of prostate cancer consisted of patient selection, simulation on both MR- and computed tomography (CT) scan, inverse intensity-modulated radiotherapy (IMRT) treatment planning and daily plan re-optimization prior to treatment delivery with partial organs at risk (OAR) recontouring within the first 2 cm outside the PTV. For each adapted plan online patient-specific quality assurance (QA) was performed by means of a secondary Monte Carlo 3D dose calculation and gamma analysis comparison. Patient experiences with MRgRT were assessed using a patient-reported outcome questionnaire (PRO-Q) after the last fraction.

Results

In 97% of fractions, MRgRT was delivered using the online adapted plan. Intrafractional prostate drifts necessitated 2D-corrections during treatment in approximately 20% of fractions. The average duration of an uneventful fraction of MRgRT was 45 min. PRO-Q’s (N = 89) showed that MRgRT was generally well tolerated, with disturbing noise sensations being most commonly reported.

Conclusions

MRgRT with daily online plan adaptation constitutes an innovative approach for delivering SBRT for prostate cancer and appears to be feasible, although necessitating extended timeslots and logistical challenges.

[Field Shape Optimization Technique Based on Dose Volume Histogram Using Daily Cone-beam Computed Tomography in Three-dimensional Conformal Radiation Therapy for Localized Prostate Cancer: Develop and Evaluation]

This study aimed to develop and evaluate field shape optimization technique based on dose calculation using daily cone-beam computed tomography (CBCT) to compensate for interfractional anatomic changes in three-dimensional conformal radiation therapy (3D-CRT) for prostate cancer. For each of 10 patients, 9-10 CBCT images were obtained throughout the treatment course. The prostate, seminal vesicles, and rectum were manually contoured in all CBCT images. Subsequently, plan adaptation was performed with a program developed in-house. This program calculates dose distributions on CBCT images and optimizes field shape to minimize rectal dose while keeping the target at the optimal dose coverage (the planning target volume D_95% receives 95% of the prescription dose). To evaluate the adaptive planning approach, we re-calculated dose distributions on CBCT images based on the conventional and adaptive plans. For the entire cohort, plan adaptation improved rectal V_{50 Gy}, V_{60 Gy}, V_{65 Gy}, and V_{70 Gy} by -7.71±8.43%, -8.30±8.90%, -7.91±8.51% and -7.03±7.70% on average (±SD), respectively. Our results demonstrate that adaptive planning approach is superior to the conventional planning approach for optimizing dose distribution, and this adaptive approach can optimize field shape in 3 min. The proposed approach can be an effective solution for the problem of interfractional anatomic changes in 3D-CRT for prostate cancer.

Magnetic Resonance Imaging-Guided Adaptive Radiation Therapy: A "Game Changer" for Prostate Treatment?

Radiation therapy to the prostate involves increasingly sophisticated delivery techniques and changing fractionation schedules. With a low estimated α/β ratio, a larger dose per fraction would be beneficial, with moderate fractionation schedules rapidly becoming a standard of care. The integration of a magnetic resonance imaging (MRI) scanner and linear accelerator allows for accurate soft tissue tracking with the capacity to replan for the anatomy of the day. Extreme hypofractionation schedules become a possibility using the potentially automated steps of autosegmentation, MRI-only workflow, and real-time adaptive planning. The present report reviews the steps involved in hypofractionated adaptive MRI-guided prostate radiation therapy and addresses the challenges for implementation.

ACR Appropriateness Criteria for external beam radiation therapy treatment planning for clinically localized prostate cancer, part II of II

PURPOSE

To present the most updated American College of Radiology (ACR) Appropriateness Criteria formed by an expert panel on the appropriate delivery of external beam radiation to manage stage T1 and T2 prostate cancer (in the definitive setting and post-prostatectomy) and to provide clinical variants with expert recommendations based on accompanying Appropriateness Criteria for target volumes and treatment planning.

METHODS AND MATERIALS

The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a panel of multidisciplinary experts. The guideline development and revision process includes an extensive analysis of current medical literature from peer-reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In instances in which evidence is lacking or equivocal, expert opinion may supplement available evidence to recommend imaging or treatment.

RESULTS

The panel summarizes the most recent and relevant literature on the topic, including organ motion and localization methods, image guidance, and delivery techniques (eg, 3-dimensional conformal intensity modulation). The panel presents 7 clinical variants, including (1) a standard case and cases with (2) a distended rectum, (3) a large-volume prostate, (4) bilateral hip implants, (5) inflammatory bowel disease, (6) prior prostatectomy, and (7) a pannus extending into the radiation field. Each case outlines the appropriate techniques for simulation, treatment planning, image guidance, dose, and fractionation. Numerical rating and commentary is given for each treatment approach in each variant.

CONCLUSIONS

External beam radiation is a key component of the curative management of T1 and T2 prostate cancer. By combining the most recent medical literature, these Appropriateness Criteria can aid clinicians in determining the appropriate treatment delivery and personalized approaches for individual patients.

4D VMAT planning and verification technique for dynamic tracking using a direct aperture deformation (DAD) method

We developed a four‐dimensional volumetric modulated arc therapy (4D VMAT) planning technique for moving targets using a direct aperture deformation (DAD) method and investigated its feasibility for clinical use. A 3D VMAT plan was generated on a reference phase of a 4D CT dataset. The plan was composed of a set of control points including the beam angle, MLC apertures and weights. To generate the 4D VMAT plan, these control points were assigned to the closest respiratory phases using the temporal information of the gantry angle and respiratory curve. Then, a DAD algorithm was used to deform the beam apertures at each control point to the corresponding phase to compensate for the tumor motion and shape changes. Plans for a phantom and five lung cases were included in this study to evaluate the proposed technique. Dosimetric comparisons were performed between 4D and 3D VMAT plans. Plan verification was implemented by delivering the 4D VMAT plans on a moving QUASAR™ phantom driven with patient‐specific respiratory curves. The phantom study showed that the 4D VMAT plan generated with the DAD method was comparable to the ideal 3D VMAT plan. DVH comparisons indicated that the planning target volume (PTV) coverages and minimum doses were nearly invariant, and no significant difference in lung dosimetry was observed. Patient studies revealed that the GTV coverage was nearly the same; although the PTV coverage dropped from 98.8% to 94.7%, and the mean dose decreased from 64.3 to 63.8 Gy on average. For the verification measurements, the average gamma index pass rate was 98.6% and 96.5% for phantom 3D and 4D VMAT plans with 3%/3 mm criteria. For patient plans, the average gamma pass rate was 96.5% (range 94.5–98.5%) and 95.2% (range 94.1–96.1%) for 3D and 4D VMAT plans. The proposed 4D VMAT planning technique using the DAD method is feasible to incorporate the intra‐fraction organ motion and shape change into a 4D VMAT planning. It has great potential to provide high plan quality and delivery efficiency for moving targets.

Adaptive radiotherapy strategies for pelvic tumors - a systematic review of clinical implementations

Introdution: Variation in shape, position and treatment response of both tumor and organs at risk are major challenges for accurate dose delivery in radiotherapy. Adaptive radiotherapy (ART) has been proposed to customize the treatment to these motion/response patterns of the individual patients, but increases workload and thereby challenges clinical implementation. This paper reviews strategies and workflows for clinical and in silico implemented ART for prostate, bladder, gynecological (gyne) and ano-rectal cancers.

MATERIAL AND METHODS

Initial identification of papers was based on searches in PubMed. For each tumor site, the identified papers were screened independently by two researches for selection of studies describing all processes of an ART workflow: treatment monitoring and evaluation, decision and execution of adaptations. Both brachytherapy and external beam studies were eligible for review.

RESULTS

The review consisted of 43 clinical studies and 51 in silico studies. For prostate, 1219 patients were treated with offline re-planning, mainly to adapt prostate motion relative to bony anatomy. For gyne 1155 patients were treated with online brachytherapy re-planning while 25 ano-rectal cancer patients were treated with offline re-planning, all to account for tumor regression detected by magnetic resonance imaging (MRI)/computed tomography (CT). For bladder and gyne, 161 and 64 patients, respectively, were treated with library-based online plan selection to account for target volume and shape variations. The studies reported sparing of rectum (prostate and bladder cancer), bladder (ano-rectal cancer) and bowel cavity (gyne and bladder cancer) as compared to non-ART.

CONCLUSION

Implementations of ART were dominated by offline re-planning and online brachytherapy re-planning strategies, although recently online plan selection workflows have increased with the availability of cone-beam CT. Advantageous dosimetric and outcome patterns using ART was documented by the studies of this review. Despite this, clinical implementations were scarce due to challenges in target/organ re-contouring and suboptimal patient selection in the ART workflows.

A deformable head and neck phantom with in-vivo dosimetry for adaptive radiotherapy quality assurance

PURPOSE

Patients' interfractional anatomic changes can compromise the initial treatment plan quality. To overcome this issue, adaptive radiotherapy (ART) has been introduced. Deformable image registration (DIR) is an important tool for ART and several deformable phantoms have been built to evaluate the algorithms' accuracy. However, there is a lack of deformable phantoms that can also provide dosimetric information to verify the accuracy of the whole ART process. The goal of this work is to design and construct a deformable head and neck (HN) ART quality assurance (QA) phantom with in vivo dosimetry.

METHODS

An axial slice of a HN patient is taken as a model for the phantom construction. Six anatomic materials are considered, with HU numbers similar to a real patient. A filled balloon inside the phantom tissue is inserted to simulate tumor. Deflation of the balloon simulates tumor shrinkage. Nonradiopaque surface markers, which do not influence DIR algorithms, provide the deformation ground truth. Fixed and movable holders are built in the phantom to hold a diode for dosimetric measurements.

RESULTS

The measured deformations at the surface marker positions can be compared with deformations calculated by a DIR algorithm to evaluate its accuracy. In this study, the authors selected a Demons algorithm as a DIR algorithm example for demonstration purposes. The average error magnitude is 2.1 mm. The point dose measurements from the in vivo diode dosimeters show a good agreement with the calculated doses from the treatment planning system with a maximum difference of 3.1% of prescription dose, when the treatment plans are delivered to the phantom with original or deformed geometry.

CONCLUSIONS

In this study, the authors have presented the functionality of this deformable HN phantom for testing the accuracy of DIR algorithms and verifying the ART dosimetric accuracy. The authors' experiments demonstrate the feasibility of this phantom serving as an end-to-end ART QA phantom.

Common-mask guided image reconstruction (c-MGIR) for enhanced 4D cone-beam computed tomography

Compared to 3D cone beam computed tomography (3D CBCT), the image quality of commercially available four-dimensional (4D) CBCT is severely impaired due to the insufficient amount of projection data available for each phase. Since the traditional Feldkamp-Davis-Kress (FDK)-based algorithm is infeasible for reconstructing high quality 4D CBCT images with limited projections, investigators had developed several compress-sensing (CS) based algorithms to improve image quality. The aim of this study is to develop a novel algorithm which can provide better image quality than the FDK and other CS based algorithms with limited projections. We named this algorithm 'the common mask guided image reconstruction' (c-MGIR).In c-MGIR, the unknown CBCT volume is mathematically modeled as a combination of phase-specific motion vectors and phase-independent static vectors. The common-mask matrix, which is the key concept behind the c-MGIR algorithm, separates the common static part across all phase images from the possible moving part in each phase image. The moving part and the static part of the volumes were then alternatively updated by solving two sub-minimization problems iteratively. As the novel mathematical transformation allows the static volume and moving volumes to be updated (during each iteration) with global projections and 'well' solved static volume respectively, the algorithm was able to reduce the noise and under-sampling artifact (an issue faced by other algorithms) to the maximum extent. To evaluate the performance of our proposed c-MGIR, we utilized imaging data from both numerical phantoms and a lung cancer patient. The qualities of the images reconstructed with c-MGIR were compared with (1) standard FDK algorithm, (2) conventional total variation (CTV) based algorithm, (3) prior image constrained compressed sensing (PICCS) algorithm, and (4) motion-map constrained image reconstruction (MCIR) algorithm, respectively. To improve the efficiency of the algorithm, the code was implemented with a graphic processing unit for parallel processing purposes.Root mean square error (RMSE) between the ground truth and reconstructed volumes of the numerical phantom were in the descending order of FDK, CTV, PICCS, MCIR, and c-MGIR for all phases. Specifically, the means and the standard deviations of the RMSE of FDK, CTV, PICCS, MCIR and c-MGIR for all phases were 42.64  ±  6.5%, 3.63  ±  0.83%, 1.31%  ±  0.09%, 0.86%  ±  0.11% and 0.52 %  ±  0.02%, respectively. The image quality of the patient case also indicated the superiority of c-MGIR compared to other algorithms.The results indicated that clinically viable 4D CBCT images can be reconstructed while requiring no more projection data than a typical clinical 3D CBCT scan. This makes c-MGIR a potential online reconstruction algorithm for 4D CBCT, which can provide much better image quality than other available algorithms, while requiring less dose and potentially less scanning time.

Accelerated gradient-based free form deformable registration for online adaptive radiotherapy

The registration of planning fan-beam computed tomography (FBCT) and daily cone-beam CT (CBCT) is a crucial step in adaptive radiation therapy. The current intensity-based registration algorithms, such as Demons, may fail when they are used to register FBCT and CBCT, because the CT numbers in CBCT cannot exactly correspond to the electron densities. In this paper, we investigated the effects of CBCT intensity inaccuracy on the registration accuracy and developed an accurate gradient-based free form deformation algorithm (GFFD). GFFD distinguishes itself from other free form deformable registration algorithms by (a) measuring the similarity using the 3D gradient vector fields to avoid the effect of inconsistent intensities between the two modalities; (b) accommodating image sampling anisotropy using the local polynomial approximation-intersection of confidence intervals (LPA-ICI) algorithm to ensure a smooth and continuous displacement field; and (c) introducing a 'bi-directional' force along with an adaptive force strength adjustment to accelerate the convergence process. It is expected that such a strategy can decrease the effect of the inconsistent intensities between the two modalities, thus improving the registration accuracy and robustness. Moreover, for clinical application, the algorithm was implemented by graphics processing units (GPU) through OpenCL framework. The registration time of the GFFD algorithm for each set of CT data ranges from 8 to 13 s. The applications of on-line adaptive image-guided radiation therapy, including auto-propagation of contours, aperture-optimization and dose volume histogram (DVH) in the course of radiation therapy were also studied by in-house-developed software.

Adaptive replanning to account for lumpectomy cavity change in sequential boost after whole-breast irradiation

PURPOSE

To evaluate the efficiency of standard image-guided radiation therapy (IGRT) to account for lumpectomy cavity (LC) variation during whole-breast irradiation (WBI) and propose an adaptive strategy to improve dosimetry if IGRT fails to address the interfraction LC variations.

METHODS AND MATERIALS

Daily diagnostic-quality CT data acquired during IGRT in the boost stage using an in-room CT for 19 breast cancer patients treated with sequential boost after WBI in the prone position were retrospectively analyzed. Contours of the LC, treated breast, ipsilateral lung, and heart were generated by populating contours from planning CTs to boost fraction CTs using an auto-segmentation tool with manual editing. Three plans were generated on each fraction CT: (1) a repositioning plan by applying the original boost plan with the shift determined by IGRT; (2) an adaptive plan by modifying the original plan according to a fraction CT; and (3) a reoptimization plan by a full-scale optimization.

RESULTS

Significant variations were observed in LC. The change in LC volume at the first boost fraction ranged from a 70% decrease to a 50% increase of that on the planning CT. The adaptive and reoptimization plans were comparable. Compared with the repositioning plans, the adaptive plans led to an improvement in target coverage for an increased LC case (1 of 19, 7.5% increase in planning target volume evaluation volume V95%), and breast tissue sparing for an LC decrease larger than 35% (3 of 19, 7.5% decrease in breast evaluation volume V50%; P=.008).

CONCLUSION

Significant changes in LC shape and volume at the time of boost that deviate from the original plan for WBI with sequential boost can be addressed by adaptive replanning at the first boost fraction.

Towards automated on-line adaptation of 2-Step IMRT plans: QUASIMODO phantom and prostate cancer cases

Background

The standard clinical protocol of image-guided IMRT for prostate carcinoma introduces isocenter relocation to restore the conformity of the multi-leaf collimator (MLC) segments to the target as seen in the cone-beam CT on the day of treatment. The large interfractional deformations of the clinical target volume (CTV) still require introduction of safety margins which leads to undesirably high rectum toxicity. Here we present further results from the 2-Step IMRT method which generates adaptable prostate IMRT plans using Beam Eye View (BEV) and 3D information.

Methods

Intermediate/high-risk prostate carcinoma cases are treated using Simultaneous Integrated Boost at the Universitätsklinkum Würzburg (UKW). Based on the planning CT a CTV is defined as the prostate and the base of seminal vesicles. The CTV is expanded by 10 mm resulting in the PTV; the posterior margin is limited to 7 mm. The Boost is obtained by expanding the CTV by 5 mm, overlap with rectum is not allowed. Prescription doses to PTV and Boost are 60.1 and 74 Gy respectively given in 33 fractions.

We analyse the geometry of the structures of interest (SOIs): PTV, Boost, and rectum, and generate 2-Step IMRT plans to deliver three fluence steps: conformal to the target SOIs (S0), sparing the rectum (S1), and narrow segments compensating the underdosage in the target SOIs due to the rectum sparing (S2). The width of S2 segments is calculated for every MLC leaf pair based on the target and rectum geometry in the corresponding CT layer to have best target coverage. The resulting segments are then fed into the DMPO optimizer of the Pinnacle treatment planning system for weight optimization and fine-tuning of the form, prior to final dose calculation using the collapsed cone algorithm.

We adapt 2-Step IMRT plans to changed geometry whilst simultaneously preserving the number of initially planned Monitor Units (MU). The adaptation adds three further steps to the previous isocenter relocation: 1) 2-Step generation for the geometry of the day using the relocated isocenter, MU transfer from the planning geometry; 2) Adaptation of the widths of S2 segments to the geometry of the day; 3) Imitation of DMPO fine-tuning for the geometry of the day.

Results and conclusion

We have performed automated 2-Step IMRT adaptation for ten prostate adaptation cases. The adapted plans show statistically significant improvement of the target coverage and of the rectum sparing compared to those plans in which only the isocenter is relocated. The 2-Step IMRT method may become a core of the automated adaptive radiation therapy system at our department.

ACR Appropriateness Criteria® external-beam radiation therapy treatment planning for clinically localized prostate cancer

Image-based radiation treatment planning and localization have contributed to better targeting of the prostate and sparing of normal tissues. Guidelines are needed to address radiation dose delivery, including patient setup and immobilization, target volume definition, treatment planning, treatment delivery methods, and target localization. Guidelines for external-beam radiation treatment planning have been updated and are presented here. The use of appropriate doses, simulation techniques, and verification of field setup are essential for the accurate delivery of radiation therapy. The ACR Appropriateness Criteria(®) are evidence-based guidelines for specific clinical conditions that are reviewed every 2 years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer-reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances in which evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.

Automatic segmentation and online virtualCT in head-and-neck adaptive radiation therapy

PURPOSE

The purpose of this work was to develop and validate an efficient and automatic strategy to generate online virtual computed tomography (CT) scans for adaptive radiation therapy (ART) in head-and-neck (HN) cancer treatment.

METHOD

We retrospectively analyzed 20 patients, treated with intensity modulated radiation therapy (IMRT), for an HN malignancy. Different anatomical structures were considered: mandible, parotid glands, and nodal gross tumor volume (nGTV). We generated 28 virtualCT scans by means of nonrigid registration of simulation computed tomography (CTsim) and cone beam CT images (CBCTs), acquired for patient setup. We validated our approach by considering the real replanning CT (CTrepl) as ground truth. We computed the Dice coefficient (DSC), center of mass (COM) distance, and root mean square error (RMSE) between correspondent points located on the automatically segmented structures on CBCT and virtualCT.

RESULTS

Residual deformation between CTrepl and CBCT was below one voxel. Median DSC was around 0.8 for mandible and parotid glands, but only 0.55 for nGTV, because of the fairly homogeneous surrounding soft tissues and of its small volume. Median COM distance and RMSE were comparable with image resolution. No significant correlation between RMSE and initial or final deformation was found.

CONCLUSION

The analysis provides evidence that deformable image registration may contribute significantly in reducing the need of full CT-based replanning in HN radiation therapy by supporting swift and objective decision-making in clinical practice. Further work is needed to strengthen algorithm potential in nGTV localization.

Methods for monitor-unit-preserving adaptation of intensity modulated arc therapy techniques to the daily target-A simple comparison

PURPOSE

For fast adaptation of step and shoot intensity modulated radiotherapy (IMRT) plans, monitor units (MU)-preserving methods which modify only the segment shapes have been proposed in the literature. In this work, two such adaptation methods are applied to intensity modulated arc therapy (IMAT) and their results are compared to that of a newly optimized IMAT plan.

METHODS

In a simplified cylindrically symmetric model, the organ at risk (OAR) is surrounded by the planning target volume (PTV). For the initial plan, a steep dose gradient is produced by variants of double arc (IMAT) plans. To simulate situations which require adaptation, the OAR radius and the inner PTV radius have been varied. One adaptation method (Warp) is based on a mesh spanned over structures identified within the beam's eye view (BEV). Changes to the structure projections warp the mesh. For the adaptation, the segment shapes are fixed to the mesh. The other method (2-Step) uses geometrical 3D information from the computed tomography (CT). For comparison, the objective function representing the dose to the PTV as well as the mean and the maximum dose to the OAR is used.

RESULTS

For the narrow segments that compensate the underdosage in the PTV areas proximate to the OAR, the Warp method suggests contrary adaptation rules compared to the 2-Step method. In contrast to Warp, the 2-Step method approximates the behavior of a newly optimized plan and leads to better dose homogeneity in the clinical target volume (CTV) and the PTV, whilst simultaneously sparing the OAR.

CONCLUSIONS

For minor changes associated with less steep dose gradients, both Warp and 2-Step methods are suitable. However, the 2-Step method should be preferred for more challenging cases, where steep dose gradients between the OAR and the concave PTV are needed. For considerable interfractional reductions of the gap between the OAR and the PTV, where especially steep dose gradients have to be generated, MU-preserving adaptation techniques are not adequate. In this case, narrower segments in the initial plan can be used to facilitate the adaptation. Otherwise, non-MU-preserving adaptation methods have to be applied. Further work is needed to include clinical cases with more complex geometries and expand the methods to IMRT techniques.

Patient-specific three-dimensional concomitant dose from cone beam computed tomography exposure in image-guided radiotherapy

PURPOSE

The purpose of the present study was to quantify the concomitant dose received by patients undergoing cone beam computed tomography (CBCT) scanning in different clinical scenarios as a part of image-guided radiotherapy (IGRT) procedures.

METHODS AND MATERIALS

We calculated the three-dimensional concomitant dose received as a result of CBCT scans in 6 patients representing different clinical scenarios: two pelvis, two head and neck, and two chest. We assessed the effect that a daily on-line IGRT strategy would have on the patient dose distribution, assuming 40 CBCT scans throughout the treatment course. The additional dose to the planning target volume margin region was also estimated.

RESULTS

In the pelvis, a single CBCT scan delivered a mean dose to the femoral heads of 2-6 cGy and the rectum of 1-2 cGy. An additional dose to the planning target volume was within 1-3 cGy. In the chest, the mean dose to the planning target volume varied from 2.5 to 5 cGy. The lung and spinal cord planning organ at risk volume received ≤4 cGy and ≤5 cGy, respectively. In the head and neck, a single CBCT scan delivered a mean dose of 0.3 cGy, with bony structures receiving 0.5-0.8 cGy. The femoral heads received an additional dose of 1.5-2.5 Gy. A reduction of 20-30% in the mean dose to the organs at risk was achieved using bowtie filtration. In the head and neck, the dose to the eyes and brainstem was eliminated by decreasing the craniocaudal field size.

CONCLUSIONS

The additional dose from on-line IGRT procedures can be clinically relevant. The organ dose can be significantly reduced with the use of appropriate patient-specific settings. The concomitant dose from CBCT should be accounted for and the acquisition settings optimized for optimal IGRT strategies on a patient basis.

Ultra-Fast Digital Tomosynthesis Reconstruction Using General-Purpose GPU Programming for Image-Guided Radiation Therapy

The purpose of this work is to demonstrate an ultra-fast reconstruction technique for digital tomosynthesis (DTS) imaging based on the algorithm proposed by Feldkamp, Davis, and Kress (FDK) using standard general-purpose graphics processing unit (GPGPU) programming interface. To this end, the FDK-based DTS algorithm was programmed “in-house” with C language with utilization of 1) GPU and 2) central processing unit (CPU) cards. The GPU card consisted of 480 processing cores (2 × 240 dual chip) with 1,242 MHz processing clock speed and 1,792 MB memory space. In terms of CPU hardware, we used 2.68 GHz clock speed, 12.0 GB DDR3 RAM, on a 64-bit OS. The performance of proposed algorithm was tested on twenty-five patient cases (5 lung, 5 liver, 10 prostate, and 5 head-and-neck) scanned either with a full-fan or half-fan mode on our cone-beam computed tomography (CBCT) system. For the full-fan scans, the projections from 157.5°–202.5° (45°-scan) were used to reconstruct coronal DTS slices, whereas for the half-fan scans, the projections from both 157.5°–202.5° and 337.5°–22.5° (2 × 45°-scan) were used to reconstruct larger FOV coronal DTS slices. For this study, we chose 45°-scan angle that contained ~80 projections for the full-fan and ~160 projections with 2 × 45°-scan angle for the half-fan mode, each with 1024 × 768 pixels with 32-bit precision. Absolute pixel value differences, profiles, and contrast-to-noise ratio (CNR) calculations were performed to compare and evaluate the images reconstructed using GPU- and CPU-based implementations. The time dependence on the reconstruction volume was also tested with (512 × 512) × 16, 32, 64, 128, and 256 slices. In the end, the GPU-based implementation achieved, at most, 1.3 and 2.5 seconds to complete full reconstruction of 512 × 512 × 256 volume, for the full-fan and half-fan modes, respectively. In turn, this meant that our implementation can process > 13 projections-per-second (pps) and > 18 pps for the full-fan and half-fan modes, respectively. Since commercial CBCT system nominally acquires 11 pps (with 1 gantry-revolution-per-minute), our GPU-based implementation is sufficient to handle the incoming projections data as they are acquired and reconstruct the entire volume immediately after completing the scan. In addition, on increasing the number of slices (hence volume) to be reconstructed from 16 to 256, only minimal increases in reconstruction time were observed for the GPU-based implementation where from 0.73 to 1.27 seconds and 1.42 to 2.47 seconds increase were observed for the full-fan and half-fan modes, respectively. This resulted in speed improvement of up to 87 times compared with the CPU-based implementation (for 256 slices case), with visually identical images and small pixel-value discrepancies (< 6.3%), and CNR differences (< 2.3%). With this achievement, we have shown that time allocation for DTS image reconstruction is virtually eliminated and that clinical implementation of this approach has become quite appealing. In addition, with the speed achievement, further image processing and real-time applications that was prohibited prior due to time restrictions can now be tempered with.

A GPU-based finite-size pencil beam algorithm with 3D-density correction for radiotherapy dose calculation

Targeting at the development of an accurate and efficient dose calculation engine for online adaptive radiotherapy, we have implemented a finite-size pencil beam (FSPB) algorithm with a 3D-density correction method on graphics processing unit (GPU). This new GPU-based dose engine is built on our previously published ultrafast FSPB computational framework (Gu et al 2009 Phys. Med. Biol. 54 6287-97). Dosimetric evaluations against Monte Carlo dose calculations are conducted on ten IMRT treatment plans (five head-and-neck cases and five lung cases). For all cases, there is improvement with the 3D-density correction over the conventional FSPB algorithm and for most cases the improvement is significant. Regarding the efficiency, because of the appropriate arrangement of memory access and the usage of GPU intrinsic functions, the dose calculation for an IMRT plan can be accomplished well within 1 s (except for one case) with this new GPU-based FSPB algorithm. Compared to the previous GPU-based FSPB algorithm without 3D-density correction, this new algorithm, though slightly sacrificing the computational efficiency (∼5-15% lower), has significantly improved the dose calculation accuracy, making it more suitable for online IMRT replanning.

On-line adaptive radiation therapy: feasibility and clinical study

The purpose of this paper is to evaluate the feasibility and clinical dosimetric benefit of an on-line, that is, with the patient in the treatment position, Adaptive Radiation Therapy (ART) system for prostate cancer treatment based on daily cone-beam CT imaging and fast volumetric reoptimization of treatment plans. A fast intensity-modulated radiotherapy (IMRT) plan reoptimization algorithm is implemented and evaluated with clinical cases. The quality of these adapted plans is compared to the corresponding new plans generated by an experienced planner using a commercial treatment planning system and also evaluated by an in-house developed tool estimating achievable dose-volume histograms (DVHs) based on a database of existing treatment plans. In addition, a clinical implementation scheme for ART is designed and evaluated using clinical cases for its dosimetric qualities and efficiency.

Evaluation of the 'dose of the day' for IMRT prostate cancer patients derived from portal dose measurements and cone-beam CT

PURPOSE

High geometrical and dosimetrical accuracies are required for radiotherapy treatments where IMRT is applied in combination with narrow treatment margins in order to minimize dose delivery to normal tissues. As an overall check, we implemented a method for reconstruction of the actually delivered 3D dose distribution to the patient during a treatment fraction, i.e., the 'dose of the day'. In this article results on the clinical evaluation of this concept for a group of IMRT prostate cancer patients are presented.

MATERIALS AND METHODS

The actual IMRT fluence maps delivered to a patient were derived from measured EPID-images acquired during treatment using a previously described iterative method. In addition, the patient geometry was obtained from in-room acquired cone-beam CT images. For dose calculation, a mapping of the Hounsfield Units from the planning CT was applied. With the fluence maps and the modified cone-beam CT the 'dose of the day' was calculated. The method was validated using phantom measurements and evaluated clinically for 10 prostate cancer patients in 4 or 5 fractions.

RESULTS

The phantom measurements showed that the delivered dose could be reconstructed within 3%/3mm accuracy. For prostate cancer patients, the isocenter dose agreed within -0.4+/-1.0% (1 SD) with the planned value, while for on average 98.1% of the pixels within the 50% isodose surface the actually delivered dose agreed within 3% or 3mm with the planned dose. For most fractions, the dose coverage of the prostate volume was slightly deteriorated which was caused by small prostate rotations and small inaccuracies in fluence delivery. The dose that was delivered to the rectum remained within the constraints used during planning. However, for two patients a large degrading of the dose delivery was observed in two fractions. For one patient this was related to changes in rectum filling with respect to the planning CT and for the other to large intra-fraction motion during treatment delivery, resulting in mean underdosages of 16% in the prostate volume.

CONCLUSIONS

A method to accurately assess the 'dose of the day' was evaluated for prostate cancer patients treated with IMRT. To correct for observed dose deviations off-line dose-adaptive strategies will be developed.

Implementation and evaluation of various demons deformable image registration algorithms on a GPU

Online adaptive radiation therapy (ART) promises the ability to deliver an optimal treatment in response to daily patient anatomic variation. A major technical barrier for the clinical implementation of online ART is the requirement of rapid image segmentation. Deformable image registration (DIR) has been used as an automated segmentation method to transfer tumor/organ contours from the planning image to daily images. However, the current computational time of DIR is insufficient for online ART. In this work, this issue is addressed by using computer graphics processing units (GPUs). A gray-scale-based DIR algorithm called demons and five of its variants were implemented on GPUs using the compute unified device architecture (CUDA) programming environment. The spatial accuracy of these algorithms was evaluated over five sets of pulmonary 4D CT images with an average size of 256 x 256 x 100 and more than 1100 expert-determined landmark point pairs each. For all the testing scenarios presented in this paper, the GPU-based DIR computation required around 7 to 11 s to yield an average 3D error ranging from 1.5 to 1.8 mm. It is interesting to find out that the original passive force demons algorithms outperform subsequently proposed variants based on the combination of accuracy, efficiency and ease of implementation.

GPU-based ultra-fast dose calculation using a finite size pencil beam model

Online adaptive radiation therapy (ART) is an attractive concept that promises the ability to deliver an optimal treatment in response to the inter-fraction variability in patient anatomy. However, it has yet to be realized due to technical limitations. Fast dose deposit coefficient calculation is a critical component of the online planning process that is required for plan optimization of intensity-modulated radiation therapy (IMRT). Computer graphics processing units (GPUs) are well suited to provide the requisite fast performance for the data-parallel nature of dose calculation. In this work, we develop a dose calculation engine based on a finite-size pencil beam (FSPB) algorithm and a GPU parallel computing framework. The developed framework can accommodate any FSPB model. We test our implementation in the case of a water phantom and the case of a prostate cancer patient with varying beamlet and voxel sizes. All testing scenarios achieved speedup ranging from 200 to 400 times when using a NVIDIA Tesla C1060 card in comparison with a 2.27 GHz Intel Xeon CPU. The computational time for calculating dose deposition coefficients for a nine-field prostate IMRT plan with this new framework is less than 1 s. This indicates that the GPU-based FSPB algorithm is well suited for online re-planning for adaptive radiotherapy.