Evaluations of an adaptive planning technique incorporating dose feedback in image-guided radiotherapy of prostate cancer

Evaluation of knowledge-based planning models for male pelvic CBCT-based online adaptive radiotherapy on conventional linear accelerators

PURPOSE

To assess the practicality of employing a commercial knowledge-based planning tool (RapidPlan) to generate adapted intact prostate and prostate bed volumetric modulated arc therapy (VMAT) plans on iterative cone-beam computed tomography (iCBCT) datasets.

METHODS AND MATERIALS

Intact prostate and prostate bed RapidPlan models were trained utilizing planning data from 50 and 44 clinical cases, respectively. To ensure that refined models were capable of producing adequate clinical plans with a single optimization, models were tested with 50 clinical planning CT datasets by comparing dose-volume histogram (DVH) and plan quality metric (PQM) values between clinical and RapidPlan-generated plans. The RapidPlan tool was then used to retrospectively generate adapted VMAT plans on daily iCBCT images for 20 intact prostate and 15 prostate bed cases. As before, DVH and PQM metrics were utilized to dosimetrically compare scheduled (iCBCT Verify) and adapted (iCBCT RapidPlan) plans. Timing data was collected to further evaluate the feasibility of integrating this approach within an online adaptive radiotherapy workflow.

RESULTS

Model testing results confirmed the models were capable of producing VMAT plans within a single optimization that were overall improved upon or dosimetrically comparable to original clinical plans. Direct application of RapidPlan on iCBCT datasets produced satisfactory intact prostate and prostate bed plans with generally improved target volume coverage/conformality and rectal sparing relative to iCBCT Verify plans as indicated by DVH values, though bladder metrics were marginally increased on average. Average PQM values for iCBCT RapidPlans were significantly improved compared to iCBCT Verify plans. The average time required [in mm:ss] to generate adapted plans was 06:09 ± 02:06 (intact) and 07:12 ± 01:04 (bed).

CONCLUSION

This study demonstrated the feasibility of leveraging RapidPlan to expeditiously generate adapted VMAT intact prostate and prostate bed plans on iCBCT datasets. In general, adapted plans were dosimetrically improved relative to scheduled plans, emphasizing the practicality of the proposed approach.

Real-time, volumetric imaging of radiation dose delivery deep into the liver during cancer treatment

Ionizing radiation acoustic imaging (iRAI) allows online monitoring of radiation's interactions with tissues during radiation therapy, providing real-time, adaptive feedback for cancer treatments. We describe an iRAI volumetric imaging system that enables mapping of the three-dimensional (3D) radiation dose distribution in a complex clinical radiotherapy treatment. The method relies on a two-dimensional matrix array transducer and a matching multi-channel preamplifier board. The feasibility of imaging temporal 3D dose accumulation was first validated in a tissue-mimicking phantom. Next, semiquantitative iRAI relative dose measurements were verified in vivo in a rabbit model. Finally, real-time visualization of the 3D radiation dose delivered to a patient with liver metastases was accomplished with a clinical linear accelerator. These studies demonstrate the potential of iRAI to monitor and quantify the 3D radiation dose deposition during treatment, potentially improving radiotherapy treatment efficacy using real-time adaptive treatment.

Dose accumulation for MR-guided adaptive radiotherapy: From practical considerations to state-of-the-art clinical implementation

MRI-linear accelerator (MR-linac) devices have been introduced into clinical practice in recent years and have enabled MR-guided adaptive radiation therapy (MRgART). However, by accounting for anatomical changes throughout radiation therapy (RT) and delivering different treatment plans at each fraction, adaptive radiation therapy (ART) highlights several challenges in terms of calculating the total delivered dose. Dose accumulation strategies-which typically involve deformable image registration between planning images, deformable dose mapping, and voxel-wise dose summation-can be employed for ART to estimate the delivered dose. In MRgART, plan adaptation on MRI instead of CT necessitates additional considerations in the dose accumulation process because MRI pixel values do not contain the quantitative information used for dose calculation. In this review, we discuss considerations for dose accumulation specific to MRgART and in relation to current MR-linac clinical workflows. We present a general dose accumulation framework for MRgART and discuss relevant quality assurance criteria. Finally, we highlight the clinical importance of dose accumulation in the ART era as well as the possible ways in which dose accumulation can transform clinical practice and improve our ability to deliver personalized RT.

Varian ethos online adaptive radiotherapy for prostate cancer: Early results of contouring accuracy, treatment plan quality, and treatment time

The Varian Ethos system allows for online adaptive treatments through the utilization of artificial intelligence (AI) and deformable image registration which automates large parts of the anatomical contouring and plan optimization process. In this study, treatments of intact prostate and prostate bed, with and without nodes, were simulated for 182 online adaptive fractions, and then a further 184 clinical fractions were delivered on the Ethos system. Frequency and magnitude of contour edits were recorded, as well as a range of plan quality metrics. From the fractions analyzed, 11% of AI generated contours, known as influencer contours, required no change, and 81% required minor edits in any given fraction. The frequency of target and noninfluencer organs at risk (OAR) contour editing varied substantially between different targets and noninfluencer OARs, although across all targets 72% of cases required no edits. The adaptive plan was the preference in 95% of fractions. The adaptive plan met more goals than the scheduled plan in 78% of fractions, while in 15% of fractions the number of goals met was the same. The online adaptive recontouring and replanning process was carried out in 19 min on average. Significant improvements in dosimetry are possible with the Ethos online adaptive system in prostate radiotherapy.

A new method to reconstruct intra-fractional prostate motion in volumetric modulated arc therapy

Intra-fractional motion is a concern during prostate radiation therapy, as it may cause deviations between planned and delivered radiation doses. Because accurate motion information during treatment delivery is critical to address dose deviation, we developed the projection marker matching method (PM³), a novel method for prostate motion reconstruction in volumetric modulated arc therapy. The purpose of this method is to reconstruct in-treatment prostate motion trajectory using projected positions of implanted fiducial markers measured in kV x-ray projection images acquired during treatment delivery. We formulated this task as a quadratic optimization problem. The objective function penalized the distance from the reconstructed 3D position of each fiducial marker to the corresponding straight line, defined by the x-ray projection of the marker. Rigid translational motion of the prostate and motion smoothness along the temporal dimension were assumed and incorporated into the optimization model. We tested the motion reconstruction method in both simulation and phantom experimental studies. We quantified the accuracy using 3D normalized root-mean-square (RMS) error defined as the norm of a vector containing ratios between the absolute RMS errors and corresponding motion ranges in three dimensions. In the simulation study with realistic prostate motion trajectories, the 3D normalized RMS error was on average [Formula: see text] (range from [Formula: see text] to [Formula: see text]). In an experimental study, a prostate phantom was driven to move along a realistic prostate motion trajectory. The 3D normalized RMS error was [Formula: see text]. We also examined the impact of the model parameters on reconstruction accuracy, and found that a single set of parameters can be used for all the tested cases to accurately reconstruct the motion trajectories. The motion trajectory derived by PM³ may be incorporated into novel strategies, including 4D dose reconstruction and adaptive treatment replanning to address motion-induced dose deviation.

Dose tracking assessment for image-guided radiotherapy of the prostate bed and the impact on clinical workflow

Background

The cumulative dose was compared with the planned dose among fourteen patients undergoing image-guided, intensity-modulated radiotherapy of the prostate bed. Moreover, we investigated the feasibility of adding dose tracking to the routine workflow for radiotherapy.

Methods

Daily cone beam computed tomography was conducted for image-guided radiotherapy, and weekly cumulative delivered doses were calculated for dose tracking. Deformable image registration was applied to map weekly dose distributions to the original treatment plan and to create a cumulative dose distribution. The dose–volume histogram (DVH) cut-off points for the rectum and bladder and the planning target volume (PTV), were used to compare the planned and cumulative delivered doses. The additional time required by the departmental staff to complete these duties was recorded.

Results

The PTV coverage of the delivered treatment did not satisfy the expected goal for three patients (V98% >98%). In another three patients, the DVH cut-off point for the bladder was higher than the limits, while for the rectum, treatment was as expected in all cases (two patients failed both their bladder constraints and the PTV coverage). Overall, four patients did not satisfy one or more criteria at the end of their treatment.

Conclusions

A well-defined strategy for dose tracking assessment is feasible, would have minimal impact on the workload of a radiotherapy department, and may offer objective information to support radiation oncologists in making decisions about adaptive procedures.

Application programming in C# environment with recorded user software interactions and its application in autopilot of VMAT/IMRT treatment planning

An autopilot scheme of volumetric‐modulated arc therapy (VMAT)/intensity‐modulated radiation therapy (IMRT) planning with the guidance of prior knowledge is established with recorded interactions between a planner and a commercial treatment planning system (TPS). Microsoft (MS) Visual Studio Coded UI is applied to record some common planner‐TPS interactions as subroutines. The TPS used in this study is a Windows‐based Eclipse system. The interactions of our application program with Eclipse TPS are realized through a series of subroutines obtained by prerecording the mouse clicks or keyboard strokes of a planner in operating the TPS. A strategy to autopilot Eclipse VMAT/IMRT plan selection process is developed as a specific example of the proposed “scripting” method. The autopiloted planning is navigated by a decision function constructed with a reference plan that has the same prescription and similar anatomy with the case at hand. The calculation proceeds by alternating between the Eclipse optimization and the outer‐loop optimization independent of the Eclipse. In the C# program, the dosimetric characteristics of a reference treatment plan are used to assess and modify the Eclipse planning parameters and to guide the search for a clinically sensible treatment plan. The approach is applied to plan a head and neck (HN) VMAT case and a prostate IMRT case. Our study demonstrated the feasibility of application programming method in C# environment with recorded interactions of planner‐TPS. The process mimics a planner's planning process and automatically provides clinically sensible treatment plans that would otherwise require a large amount of manual trial and error of a planner. The proposed technique enables us to harness a commercial TPS by application programming via the use of recorded human computer interactions and provides an effective tool to greatly facilitate the treatment planning process.

PACS number(s): 87.55.D‐, 87.55.kd, 87.55.de

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.

Target margins in radiotherapy of prostate cancer

We reviewed the literature on the use of margins in radiotherapy of patients with prostate cancer, focusing on different options for image guidance (IG) and technical issues. The search in PubMed database was limited to include studies that involved external beam radiotherapy of the intact prostate. Post-prostatectomy studies, brachytherapy and particle therapy were excluded. Each article was characterized according to the IG strategy used: positioning on external marks using room lasers, bone anatomy and soft tissue match, usage of fiducial markers, electromagnetic tracking and adapted delivery. A lack of uniformity in margin selection among institutions was evident from the review. In general, introduction of pre- and in-treatment IG was associated with smaller planning target volume (PTV) margins, but there was a lack of definitive experimental/clinical studies providing robust information on selection of exact PTV values. In addition, there is a lack of comparative research regarding the cost-benefit ratio of the different strategies: insertion of fiducial markers or electromagnetic transponders facilitates prostate gland localization but at a price of invasive procedure; frequent pre-treatment imaging increases patient in-room time, dose and labour; online plan adaptation should improve radiation delivery accuracy but requires fast and precise computation. Finally, optimal protocols for quality assurance procedures need to be established.

Validation of a dose warping algorithm using clinically realistic scenarios

Objective:

Dose warping following deformable image registration (DIR) has been proposed for interfractional dose accumulation. Robust evaluation workflows are vital to clinically implement such procedures. This study demonstrates such a workflow and quantifies the accuracy of a commercial DIR algorithm for this purpose under clinically realistic scenarios.

Methods:

12 head and neck (H&N) patient data sets were used for this retrospective study. For each case, four clinically relevant anatomical changes have been manually generated. Dose distributions were then calculated on each artificially deformed image and warped back to the original anatomy following DIR by a commercial algorithm. Spatial registration was evaluated by quantitative comparison of the original and warped structure sets, using conformity index and mean distance to conformity (MDC) metrics. Dosimetric evaluation was performed by quantitative comparison of the dose–volume histograms generated for the calculated and warped dose distributions, which should be identical for the ideal “perfect” registration of mass-conserving deformations.

Results:

Spatial registration of the artificially deformed image back to the planning CT was accurate (MDC range of 1–2 voxels or 1.2–2.4 mm). Dosimetric discrepancies introduced by the DIR were low (0.02 ± 0.03 Gy per fraction in clinically relevant dose metrics) with no statistically significant difference found (Wilcoxon test, 0.6 ≥ p ≥ 0.2).

Conclusion:

The reliability of CT-to-CT DIR-based dose warping and image registration was demonstrated for a commercial algorithm with H&N patient data.

Advances in knowledge:

This study demonstrates a workflow for validation of dose warping following DIR that could assist physicists and physicians in quantifying the uncertainties associated with dose accumulation in clinical scenarios.

A framework for deformable image registration validation in radiotherapy clinical applications

Quantitative validation of deformable image registration (DIR) algorithms is extremely difficult because of the complexity involved in constructing a deformable phantom that can duplicate various clinical scenarios. The purpose of this study is to describe a framework to test the accuracy of DIR based on computational modeling and evaluating using inverse consistency and other methods. Three clinically relevant organ deformations were created in prostate (distended rectum and rectal gas), head and neck (large neck flexion), and lung (inhale and exhale lung volumes with variable contrast enhancement) study sets. DIR was performed using both B-spline and diffeomorphic demons algorithms in the forward and inverse direction. A compositive accumulation of forward and inverse deformation vector fields was done to quantify the inverse consistency error (ICE). The anatomical correspondence of tumor and organs at risk was quantified by comparing the original RT structures with those obtained after DIR. Further, the physical characteristics of the deformation field, namely the Jacobian and harmonic energy, were computed to quantify the preservation of image topology and regularity of spatial transformation obtained in DIR. The ICE was comparable in prostate case but the B-spline algorithm had significantly better anatomical correspondence for rectum and prostate than diffeomorphic demons algorithm. The ICE was 6.5 mm for demons algorithm for head and neck case when compared to 0.7 mm for B-spline. Since the induced neck flexion was large, the average Dice similarity coefficient between both algorithms was only 0.87, 0.52, 0.81, and 0.67 for tumor, cord, parotids, and mandible, respectively. The B-spline algorithm accurately estimated deformations between images with variable contrast in our lung study, while diffeomorphic demons algorithm led to gross errors on structures affected by contrast variation. The proposed framework offers the application of known deformations on any image datasets, to evaluate the overall accuracy and limitations of a DIR algorithm used in radiation oncology. The evaluation based on anatomical correspondence, physical characteristics of deformation field, and image characteristics can facilitate DIR verification with the ultimate goal of implementing adaptive radiotherapy. The suitability of application of a particular evaluation metric in validating DIR is dependent on the clinical deformation observed.