Hypofractionation and SABR: 25 years of evolution in medical physics and a glimpse of the future

As we were invited to write an article for celebrating the 50^th Anniversary of Medical Physics journal, on something historically significant, commemorative, and exciting happening in the past decades, the first idea came to our mind is the fascinating radiotherapy paradigm shift from conventional fractionation to hypofractionation and stereotactic ablative radiotherapy (SABR). It is historically and clinically significant since as we all know this RT treatment revolution not only reduces treatment duration for patients, but also improves tumor control and cancer treatment outcomes. It is also commemorative and exciting for us medical physicists since the technology development in medical physics has been the main driver for the success of this treatment regimen which requires high precision and accuracy throughout the entire treatment planning and delivery. This article provides an overview of the technological development and clinical trials evolvement in the past 25 years for hypofractionation and SABR, with an outlook to the future improvement.

The markerless lung target tracking AAPM Grand Challenge (MATCH) results

PURPOSE

Lung stereotactic ablative body radiotherapy (SABR) is a radiation therapy success story with level 1 evidence demonstrating its efficacy. To provide real-time respiratory motion management for lung SABR, several commercial and preclinical markerless lung target tracking (MLTT) approaches have been developed. However, these approaches have yet to be benchmarked using a common measurement methodology. This knowledge gap motivated the MArkerless lung target Tracking CHallenge (MATCH). The aim was to localize lung targets accurately and precisely in a retrospective in silico study and a prospective experimental study.

METHODS

MATCH was an American Association of Physicists in Medicine sponsored Grand Challenge. Common materials for the in silico and experimental studies were the experiment setup including an anthropomorphic thorax phantom with two targets within the lungs, and a lung SABR planning protocol. The phantom was moved rigidly with patient-measured lung target motion traces, which also acted as ground truth motion. In the retrospective in silico study a volumetric modulated arc therapy treatment was simulated and a dataset consisting of treatment planning data and intra-treatment kilovoltage (kV) and megavoltage (MV) images for four blinded lung motion traces was provided to the participants. The participants used their MLTT approach to localize the moving target based on the dataset. In the experimental study, the participants received the phantom experiment setup and five patient-measured lung motion traces. The participants used their MLTT approach to localize the moving target during an experimental SABR phantom treatment. The challenge was open to any participant, and participants could complete either one or both parts of the challenge. For both the in silico and experimental studies the MLTT results were analyzed and ranked using the prospectively defined metric of the percentage of the tracked target position being within 2 mm of the ground truth.

RESULTS

A total of 30 institutions registered and 15 result submissions were received, four for the in silico study and 11 for the experimental study. The participating MLTT approaches were: Accuray CyberKnife (2), Accuray Radixact (2), BrainLab Vero, C-RAD, and preclinical MLTT (5) on a conventional linear accelerator (Varian TrueBeam). For the in silico study the percentage of the 3D tracking error within 2 mm ranged from 50% to 92%. For the experimental study, the percentage of the 3D tracking error within 2 mm ranged from 39% to 96%.

CONCLUSIONS

A common methodology for measuring the accuracy of MLTT approaches has been developed and used to benchmark preclinical and commercial approaches retrospectively and prospectively. Several MLTT approaches were able to track the target with sub-millimeter accuracy and precision. The study outcome paves the way for broader clinical implementation of MLTT. MATCH is live, with datasets and analysis software being available online at https://www.aapm.org/GrandChallenge/MATCH/ to support future research.

Advances in anthropomorphic thorax phantoms for radiotherapy: a review

A phantom is a highly specialized device, which mimic human body, or a part of it. There are three categories of phantoms: physical phantoms, physiological phantoms, and computational phantoms. The phantoms have been utilized in medical imaging and radiotherapy for numerous applications. In radiotherapy, the phantoms may be used for various applications such as quality assurance (QA), dosimetry, end-to-end testing, etc. In thoracic radiotherapy, unique QA problems including tumor motion, thorax deformation, and heterogeneities in the beam path have complicated the delivery of dose to both tumor and organ at risks (OARs). Also, respiratory motion is a major challenge in radiotherapy of thoracic malignancies, which can be resulted in the discrepancies between the planned and delivered doses to cancerous tissue. Hence, the overall treatment procedure needs to be verified. Anthropomorphic thorax phantoms, which are made of human tissue-mimicking materials, can be utilized to obtain the ground truth to validate these processes. Accordingly, research into new anthropomorphic thorax phantoms has accelerated. Therefore, the review is intended to summarize the current status of the commercially available and in-house-built anthropomorphic physical/physiological thorax phantoms in radiotherapy. The main focus is on anthropomorphic, deformable thorax motion phantoms. This review also discusses the applications of three-dimensional (3D) printing technology for the fabrication of thorax phantoms.

Dosimetric effect of intrafraction motion and different localization strategies in prostate SBRT

The aim of this study was to evaluate the dosimetric effect of continuous motion monitoring based localization (Calypso, Varian Medical Systems), gating and intrafraction motion correction in prostate SBRT. Delivered doses were modelled by reconstructing motion inclusive dose distributions for different localization strategies. Actually delivered dose (strategy A) utilized initial Calypso localization, CBCT and additional pre-treatment motion correction by kV-imaging and Calypso, and gating during the irradiation. The effect of gating was investigated by simulating non-gated treatments (strategy B). Additionally, non-gated and single image-guided (CBCT) localization was simulated (strategy C). A total of 308 fractions from 22 patients were reconstructed. The dosimetric effect was evaluated by comparing motion inclusive target and risk organ dose-volume parameters to planned values. Motion induced dose deficits were seen mainly in PTV and CTV to PTV margin regions, whereas CTV dose deficits were small in all strategies: mean ± SD difference in CTVD99% was -0.3 ± 0.4%, -0.4 ± 0.6% and -0.7 ± 1.2% in strategies A, B and C, respectively. Largest dose deficits were seen in individual fractions for strategy C (maximum dose reductions were -29.0% and -7.1% for PTVD95% and CTVD99%, respectively). The benefit of gating was minor, if additional motion correction was applied immediately prior to irradiation. Continuous motion monitoring based localization and motion correction ensured the target coverage and minimized the OAR exposure for every fraction and is recommended to use in prostate SBRT. The study is part of clinical trial NCT02319239.

Real-time intrafraction motion monitoring in external beam radiotherapy

Radiotherapy (RT) aims to deliver a spatially conformal dose of radiation to tumours while maximizing the dose sparing to healthy tissues. However, the internal patient anatomy is constantly moving due to respiratory, cardiac, gastrointestinal and urinary activity. The long term goal of the RT community to 'see what we treat, as we treat' and to act on this information instantaneously has resulted in rapid technological innovation. Specialized treatment machines, such as robotic or gimbal-steered linear accelerators (linac) with in-room imaging suites, have been developed specifically for real-time treatment adaptation. Additional equipment, such as stereoscopic kilovoltage (kV) imaging, ultrasound transducers and electromagnetic transponders, has been developed for intrafraction motion monitoring on conventional linacs. Magnetic resonance imaging (MRI) has been integrated with cobalt treatment units and more recently with linacs. In addition to hardware innovation, software development has played a substantial role in the development of motion monitoring methods based on respiratory motion surrogates and planar kV or Megavoltage (MV) imaging that is available on standard equipped linacs. In this paper, we review and compare the different intrafraction motion monitoring methods proposed in the literature and demonstrated in real-time on clinical data as well as their possible future developments. We then discuss general considerations on validation and quality assurance for clinical implementation. Besides photon RT, particle therapy is increasingly used to treat moving targets. However, transferring motion monitoring technologies from linacs to particle beam lines presents substantial challenges. Lessons learned from the implementation of real-time intrafraction monitoring for photon RT will be used as a basis to discuss the implementation of these methods for particle RT.

Investigating the effectiveness of monitoring relevant variations during IMRT and VMAT treatments by EPID-based 3D in vivo verification performed using planning CTs

Purpose

The goal of this study was to investigate the effectiveness of monitoring relevant variations during treatments for electronic portal imaging device (EPID)-based 3D in vivo verification performed using planning CTs.

Methods

Experiments on two simple phantoms (uniform and nonuniform phantoms) and a thoracic phantom were analyzed in this study, and six relevant variations including the machine output, planning target volume (PTV) deformation, multileaf collimator (MLC) and Phantom shift (set-up errors), and gantry and couch angle shifts were evaluated. 3D gamma and dose-volume histogram (DVH) methods were used to evaluate the detection sensitivity of the EPID-based 3D in vivo dosimetry and the dose accuracy of the EPID reconstruction, respectively, as affected by the variations, and the results were validated by determining the consistency with TPS simulated results.

Results

The results of the simple phantoms showed that the gamma failure rates and DVH trend of EPID reconstructions were consistent with the results of TPS simulations for machine output and MLC shifts and inconsistent for phantom shift, gantry/couch angle shift and PTV deformation variations. The results of the thoracic phantom showed that CBCT-guided EPID reconstruction sensitively detected 3-mm Phantom shift in thoracic phantom and its gamma failure rates and DVH trend were consistent with the results of TPS simulations.

Conclusion

The variations, such as machine output and MLC shift, that are phantom unrelated and cause changes in the beam of the linear accelerator can be sensitively detected by EPID-based 3D in vivo dosimetry and do not affect the accuracy of the EPID reconstruction dose. Planning CT will limit the detection sensitivity and the accuracy of the reconstruction dose of the EPID-based 3D in vivo dosimetry for phantom-related variations (such as Phantom shift and gantry/couch angle shift). EPID reconstruction combined with IGRT technology is a more effective method to monitor phantom shift variations.

Review of Real-Time 3-Dimensional Image Guided Radiation Therapy on Standard-Equipped Cancer Radiation Therapy Systems: Are We at the Tipping Point for the Era of Real-Time Radiation Therapy?

PURPOSE

To review real-time 3-dimensional (3D) image guided radiation therapy (IGRT) on standard-equipped cancer radiation therapy systems, focusing on clinically implemented solutions.

METHODS AND MATERIALS

Three groups in 3 continents have clinically implemented novel real-time 3D IGRT solutions on standard-equipped linear accelerators. These technologies encompass kilovoltage, combined megavoltage-kilovoltage, and combined kilovoltage-optical imaging. The cancer sites treated span pelvic and abdominal tumors for which respiratory motion is present. For each method the 3D-measured motion during treatment is reported. After treatment, dose reconstruction was used to assess the treatment quality in the presence of motion with and without real-time 3D IGRT. The geometric accuracy was quantified through phantom experiments. A literature search was conducted to identify additional real-time 3D IGRT methods that could be clinically implemented in the near future.

RESULTS

The real-time 3D IGRT methods were successfully clinically implemented and have been used to treat more than 200 patients. Systematic target position shifts were observed using all 3 methods. Dose reconstruction demonstrated that the delivered dose is closer to the planned dose with real-time 3D IGRT than without real-time 3D IGRT. In addition, compromised target dose coverage and variable normal tissue doses were found without real-time 3D IGRT. The geometric accuracy results with real-time 3D IGRT had a mean error of <0.5 mm and a standard deviation of <1.1 mm. Numerous additional articles exist that describe real-time 3D IGRT methods using standard-equipped radiation therapy systems that could also be clinically implemented.

CONCLUSIONS

Multiple clinical implementations of real-time 3D IGRT on standard-equipped cancer radiation therapy systems have been demonstrated. Many more approaches that could be implemented were identified. These solutions provide a pathway for the broader adoption of methods to make radiation therapy more accurate, impacting tumor and normal tissue dose, margins, and ultimately patient outcomes.

Establishing action threshold for change in patient anatomy using EPID gamma analysis and PTV coverage for head and neck radiotherapy treatment

PURPOSE

To present a new adaptive radiotherapy (ART) method based on relative gamma analysis and patient classification for the identification of anatomical changes that induce a sufficient dosimetric impact to affect the treatment delivery and require complete replanning.

METHODS

This retrospective study includes 55 patients treated for a head and neck cancer with IMRT, VMAT, or 3D conformal RT. Electronic Portal Imaging Device images for all treatment fields were acquired daily at every fraction. CBCTs were collected at least once a week. Gamma analysis was performed using the first fraction of the treatment as a reference once validated that it was delivered without error. Gamma analysis parameters (<γ>, standard deviation and the Top 1% γ) were used to define categories using statistic from a k-means clustering analysis. From these categories an action threshold was defined and correlated with dosimetric changes. For 23 of 55 patients, the V100% for PTV was computed for both, the planning CT and original contours deformed onto CBCT acquired at the last fraction. These values were then compared with 2D image relative γ-analysis of EPID images. Sensitivity and specificity of the method for the detection of dosimetric changes were computed.

RESULTS

Three categories indicating an increasing level of change with the planned treatment were identified. A threshold was established for which patients were at risk of deviation at <γ> = 0.42. From 23 recomputing plans, it has been confirmed that patients with a strong dosimetric impact were above this threshold, with a specificity of 0.80 and a sensitivity of 0.84.

CONCLUSIONS

The specificity and the sensitivity value confirmed the performance of the method to detect anatomical changes. The γ-analysis threshold correlated well with morphological changes that have a relevant dosimetric impact. Analysis of daily EPID images provides a method to identify patients at risk of deviation from their planned treatment and can support an early replanning decision.

Classification of changes occurring in lung patient during radiotherapy using relative γ analysis and hidden Markov models

PURPOSE

To present a new automated patient classification method based on relative gamma analysis and hidden Markov models (HMM) to identify patients undergoing important anatomical changes during radiation therapy.

METHODS

Daily EPID images of every treatment field were acquired for 52 patients treated for lung cancer. In addition, CBCT were acquired on a regular basis. Gamma analysis was performed relative to the first fraction given that no significant anatomical change was observed on the CBCT of the first fraction compared to the planning CT. Several parameters were extracted from the gamma analysis (e.g., average gamma value, standard deviation, percent above 1). These parameters formed patient-specific time series. Data from the first 24 patients were used as a training set for the HMM. The trained HMM was then applied to the remaining 28 patients and compared to manual clinical evaluation and fixed thresholds.

RESULTS

A three-category system was used for patient classification ranging from minor deviations (category 1) to severe deviations (category 3) from the treatment plan. Patient classified using the HMM lead to the same result as the classification made by a human expert 83% of the time. The HMM overestimate the category 10% of the time and underestimate 7% of the time. Both methods never disagree by more than one category. In addition, the information provided by the HMM is richer than the simple threshold-based approach. HMM provides information on the likelihood that a patient will improve or deteriorate as well as the expected time the patient will remain in that state.

CONCLUSION

We showed a method to classify patients during the course of radiotherapy based on relative changes in EPID images and a hidden Markov model. Information obtained through this automated classification can complement the clinical information collected during treatment and help identify patients in need of a plan adaptation.

Technical Note: Combination of multiple EPID imager layers improves image quality and tracking performance of low contrast-to-noise objects

PURPOSE

We hypothesized that combining multiple amorphous silicon flat panel layers increases photon detection efficiency in an electronic portal imaging device (EPID), improving image quality and tracking accuracy of low-contrast targets during radiotherapy.

METHODS

The prototype imager evaluated in this study contained four individually programmable layers each with a copper converter layer, Gd₂ O₂ S scintillator, and active-matrix flat panel imager (AMFPI). The imager was placed on a Varian TrueBeam linac and a Las Vegas phantom programmed with sinusoidal motion (peak-to-peak amplitude = 20 mm, period = 3.5 s) was imaged at a frame rate of 10 Hz with one to four layers activated. Number of visible circles and CNR of least visible circle (depth = 0.5 mm, diameter = 7 mm) was computed to assess the image quality of single and multiple layers. A previously validated tracking algorithm was employed for auto-tracking. Tracking error was defined as the difference between the programmed and tracked positions of the circle. Pearson correlation coefficient (R) of CNR and tracking errors was computed.

RESULTS

Motion-induced blurring significantly reduced circle visibility. During four cycles of phantom motion, the number of visible circles varied from 11-23, 13-24, 15-25, and 16-26 for one-, two-, three-, and four-layer imagers, respectively. Compared with using only a single layer, combining two, three, and four layers increased the median CNR by factors of 1.19, 1.42, and 1.71, respectively and reduced the average tracking error from 3.32 mm to 1.67 mm to 1.47 mm, and 0.74 mm, respectively. Significant correlations (P~10^-9 ) were found between the tracking error and CNR.

CONCLUSION

Combination of four conventional EPID layers significantly improves the EPID image quality and tracking accuracy for a poorly visible object which is moving with a frequency and amplitude similar to respiratory motion.

Beam's-eye-view imaging during non-coplanar lung SBRT

PURPOSE

Beam's-eye-view (BEV) imaging with an electronic portal imaging device (EPID) can be performed during lung stereotactic body radiation therapy (SBRT) to monitor the tumor location in real-time. Image quality for each patient and treatment field depends on several factors including the patient anatomy and the gantry and couch angles. The authors investigated the angular dependence of automatic tumor localization during non-coplanar lung SBRT delivery.

METHODS

All images were acquired at a frame rate of 12 Hz with an amorphous silicon EPID. A previously validated markerless lung tumor localization algorithm was employed with manual localization as the reference. From ten SBRT patients, 12 987 image frames of 123 image sequences acquired at 48 different gantry-couch rotations were analyzed. δ was defined by the position difference of the automatic and manual localization.

RESULTS

Regardless of the couch angle, the best tracking performance was found in image sequences with a gantry angle within 20° of 250° (δ = 1.40 mm). Image sequences acquired with gantry angles of 150°, 210°, and 350° also led to good tracking performances with δ = 1.77-2.00 mm. Overall, the couch angle was not correlated with the tracking results. Among all the gantry-couch combinations, image sequences acquired at (θ = 30°, ϕ = 330°), (θ = 210°, ϕ = 10°), and (θ = 250°, ϕ = 30°) led to the best tracking results with δ = 1.19-1.82 mm. The worst performing combinations were (θ = 90° and 230°, ϕ = 10°) and (θ = 270°, ϕ = 30°) with δ > 3.5 mm. However, 35% (17/48) of the gantry-couch rotations demonstrated substantial variability in tracking performances between patients. For example, the field angle (θ = 70°, ϕ = 10°) was acquired for five patients. While the tracking errors were ≤1.98 mm for three patients, poor performance was found for the other two patients with δ ≥ 2.18 mm, leading to average tracking error of 2.70 mm. Only one image sequence was acquired for all other gantry-couch rotations (δ = 1.18-10.29 mm).

CONCLUSIONS

Non-coplanar beams with gantry-couch rotation of (θ = 30°, ϕ = 330°), (θ = 210°, ϕ = 10°), and (θ = 250°, ϕ = 30°) have the highest accuracy for BEV lung tumor localization. Additionally, gantry angles of 150°, 210°, 250°, and 350° also offer good tracking performance. The beam geometries (θ = 90° and 230°, ϕ = 10°) and (θ = 270°, ϕ = 30°) are associated with substantial automatic localization errors. Overall, lung tumor visibility and tracking performance were patient dependent for a substantial number of the gantry-couch angle combinations studied.

3D delivered dose assessment using a 4DCT-based motion model

PURPOSE

The purpose of this work is to develop a clinically feasible method of calculating actual delivered dose distributions for patients who have significant respiratory motion during the course of stereotactic body radiation therapy (SBRT).

METHODS

A novel approach was proposed to calculate the actual delivered dose distribution for SBRT lung treatment. This approach can be specified in three steps. (1) At the treatment planning stage, a patient-specific motion model is created from planning 4DCT data. This model assumes that the displacement vector field (DVF) of any respiratory motion deformation can be described as a linear combination of some basis DVFs. (2) During the treatment procedure, 2D time-varying projection images (either kV or MV projections) are acquired, from which time-varying "fluoroscopic" 3D images of the patient are reconstructed using the motion model. The DVF of each timepoint in the time-varying reconstruction is an optimized linear combination of basis DVFs such that the 2D projection of the 3D volume at this timepoint matches the projection image. (3) 3D dose distribution is computed for each timepoint in the set of 3D reconstructed fluoroscopic images, from which the total effective 3D delivered dose is calculated by accumulating deformed dose distributions. This approach was first validated using two modified digital extended cardio-torso (XCAT) phantoms with lung tumors and different respiratory motions. The estimated doses were compared to the dose that would be calculated for routine 4DCT-based planning and to the actual delivered dose that was calculated using "ground truth" XCAT phantoms at all timepoints. The approach was also tested using one set of patient data, which demonstrated the application of our method in a clinical scenario.

RESULTS

For the first XCAT phantom that has a mostly regular breathing pattern, the errors in 95% volume dose (D95) are 0.11% and 0.83%, respectively for 3D fluoroscopic images reconstructed from kV and MV projections compared to the ground truth, which is clinically comparable to 4DCT (0.093%). For the second XCAT phantom that has an irregular breathing pattern, the errors are 0.81% and 1.75% for kV and MV reconstructions, both of which are better than that of 4DCT (4.01%). In the case of real patient, although it is impossible to obtain the actual delivered dose, the dose estimation is clinically reasonable and demonstrates differences between 4DCT and MV reconstruction-based dose estimates.

CONCLUSIONS

With the availability of kV or MV projection images, the proposed approach is able to assess delivered doses for all respiratory phases during treatment. Compared to the planning dose based on 4DCT, the dose estimation using reconstructed 3D fluoroscopic images was as good as 4DCT for regular respiratory pattern and was a better dose estimation for the irregular respiratory pattern.

Registration of clinical volumes to beams-eye-view images for real-time tracking

PURPOSE

The authors combine the registration of 2D beam's eye view (BEV) images and 3D planning computed tomography (CT) images, with relative, markerless tumor tracking to provide automatic absolute tracking of physician defined volumes such as the gross tumor volume (GTV).

METHODS

During treatment of lung SBRT cases, BEV images were continuously acquired with an electronic portal imaging device (EPID) operating in cine mode. For absolute registration of physician-defined volumes, an intensity based 2D/3D registration to the planning CT was performed using the end-of-exhale (EoE) phase of the four dimensional computed tomography (4DCT). The volume was converted from Hounsfield units into electron density by a calibration curve and digitally reconstructed radiographs (DRRs) were generated for each beam geometry. Using normalized cross correlation between the DRR and an EoE BEV image, the best in-plane rigid transformation was found. The transformation was applied to physician-defined contours in the planning CT, mapping them into the EPID image domain. A robust multiregion method of relative markerless lung tumor tracking quantified deviations from the EoE position.

RESULTS

The success of 2D/3D registration was demonstrated at the EoE breathing phase. By registering at this phase and then employing a separate technique for relative tracking, the authors are able to successfully track target volumes in the BEV images throughout the entire treatment delivery.

CONCLUSIONS

Through the combination of EPID/4DCT registration and relative tracking, a necessary step toward the clinical implementation of BEV tracking has been completed. The knowledge of tumor volumes relative to the treatment field is important for future applications like real-time motion management, adaptive radiotherapy, and delivered dose calculations.

Time-resolved dose reconstruction by motion encoding of volumetric modulated arc therapy fields delivered with and without dynamic multi-leaf collimator tracking

BACKGROUND

Organ motion during treatment delivery in radiotherapy (RT) may lead to deterioration of the planned dose, but can be mitigated by dynamic multi-leaf collimator (DMLC) tracking. The purpose of this study was to implement and experimentally validate a method for time-resolved motion including dose reconstruction for volumetric modulated arc therapy (VMAT) treatments delivered with and without DMLC tracking.

MATERIAL AND METHODS

Tracking experiments were carried out on a linear accelerator (Trilogy, Varian) with a prototype DMLC tracking system. A motion stage carrying a biplanar dosimeter phantom (Delta4PT, Scandidos) reproduced eight representative clinical tumor trajectories (four lung, four prostate). For each trajectory, two single-arc 6 MV VMAT treatments with low and high modulation were delivered to the moving phantom with and without DMLC tracking. An existing in-house developed program that adds target motion to treatment plans was extended with the ability to split an arc plan into any number of sub-arcs, allowing the calculated dose for different parts of the treatment to be examined individually. For each VMAT sub-arc, reconstructed and measured doses were compared using dose differences and 3%/3 mm γ-tests.

RESULTS

For VMAT sub-arcs the reconstructed dose distributions had a mean root-mean-square (rms) dose difference of 2.1% and mean γ failure rate of 2.0% when compared with the measured doses. For final accumulated doses the mean rms dose difference was 1.6% and the γ failure rate was 0.7%.

CONCLUSION

The time-resolved motion including dose reconstruction was experimentally validated for complex tracking and non-tracking treatments with patient-measured tumor motion trajectories. The reconstructed dose will be of high value for evaluation of treatment plan robustness facing organ motion and adaptive RT.

A method of dose reconstruction for moving targets compatible with dynamic treatments

PURPOSE

To develop a method that allows a commercial treatment planning system (TPS) to perform accurate dose reconstruction for rigidly moving targets and to validate the method in phantom measurements for a range of treatments including intensity modulated radiation therapy (IMRT), volumetric arc therapy (VMAT), and dynamic multileaf collimator (DMLC) tracking.

METHODS

An in-house computer program was developed to manipulate Dicom treatment plans exported from a TPS (Eclipse, Varian Medical Systems) such that target motion during treatment delivery was incorporated into the plans. For each treatment, a motion including plan was generated by dividing the intratreatment target motion into 1 mm position bins and construct sub-beams that represented the parts of the treatment that were delivered, while the target was located within each position bin. For each sub-beam, the target shift was modeled by a corresponding isocenter shift. The motion incorporating Dicom plans were reimported into the TPS, where dose calculation resulted in motion including target dose distributions. For experimental validation of the dose reconstruction a thorax phantom with a moveable lung equivalent rod with a tumor insert of solid water was first CT scanned. The tumor insert was delineated as a gross tumor volume (GTV), and a planning target volume (PTV) was formed by adding margins. A conformal plan, two IMRT plans (step-and-shoot and sliding windows), and a VMAT plan were generated giving minimum target doses of 95% (GTV) and 67% (PTV) of the prescription dose (3 Gy). Two conformal fields with MLC leaves perpendicular and parallel to the tumor motion, respectively, were generated for DMLC tracking. All treatment plans were delivered to the thorax phantom without tumor motion and with a sinusoidal tumor motion. The two conformal fields were delivered with and without portal image guided DMLC tracking based on an embedded gold marker. The target dose distribution was measured with a radiochromic film in the moving rod and compared with the reconstructed doses using gamma tests.

RESULTS

Considerable interplay effects between machine motion and target motion were observed for the treatments without tracking. For nontracking experiments, the mean 2 mm∕2% gamma pass rate over all investigated scenarios was 99.6% between calculated and measured doses. For tracking experiments, the mean gamma pass rate was 99.4%.

CONCLUSIONS

A method for accurate dose reconstruction for moving targets with dynamic treatments was developed and experimentally validated in a variety of delivery scenarios. The method is suitable for integration into TPSs, e.g., for reconstruction of the dose delivered to moving tumors or calculation of target doses delivered with DMLC tracking.