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![Overview of the online dose computation triggered for each received MLC aperture. [Color figure can be viewed at wileyonlinelibrary.com]](publication/319212514/figure/fig1/AS:570919832821760@1513129303598/Overview-of-the-online-dose-computation-triggered-for-each-received-MLC-aperture-Color.png)
Overview of the online dose computation triggered for each received MLC aperture. [Color figure can be viewed at wileyonlinelibrary.com]
Source publication
Purpose:
Firstly, this study provides a real-time implementation of online dose reconstruction for tracked volumetric arc therapy (VMAT). Secondly, this study describes a novel offline quality assurance tool, based on commercial dose calculation algorithms.
Methods:
Online dose reconstruction for VMAT is a computationally challenging task in ter...
Citations
... This includes offline studies where the dose reconstruction was performed after treatment delivery 4,5,14,15,22 and online studies where the dose reconstruction was performed during actual treatment delivery. [23][24][25][26][27] The online dose reconstruction studies include treatments of "air" in lieu of a patient using sim-ulated motion monitoring, [23][24][25] treatments of a moving dosimeter using optical motion monitoring, 26 and treatments of patients using combined optical and imagebased motion monitoring. 27 Rotation-including dose reconstruction studies have so far only been performed offline after treatment delivery. ...
... This includes offline studies where the dose reconstruction was performed after treatment delivery 4,5,14,15,22 and online studies where the dose reconstruction was performed during actual treatment delivery. [23][24][25][26][27] The online dose reconstruction studies include treatments of "air" in lieu of a patient using sim-ulated motion monitoring, [23][24][25] treatments of a moving dosimeter using optical motion monitoring, 26 and treatments of patients using combined optical and imagebased motion monitoring. 27 Rotation-including dose reconstruction studies have so far only been performed offline after treatment delivery. ...
Background
Hypofractionation in prostate radiotherapy is of increasing interest. Steep dose gradients and a large weight on each individual fraction emphasize the need for motion management. Real‐time motion management techniques such as multileaf collimator (MLC) tracking or couch tracking typically adjust for translational motion while rotations remain uncompensated with unknown dosimetric impact.
Purpose
The purpose of this study is to demonstrate and validate dynamic real‐time rotation‐including dose reconstruction during radiotherapy experiments with and without MLC and couch tracking.
Methods
Real‐time dose reconstruction was performed using the in‐house developed software DoseTracker. DoseTracker receives streamed target positions and accelerator parameters during treatment delivery and uses a pencil beam algorithm with water density assumption to reconstruct the dose in a moving target. DoseTracker's ability to reconstruct motion‐induced dose errors in a dynamically rotating and translating target was investigated during three different scenarios: (1) no motion compensation and translational motion correction with (2) MLC tracking and (3) couch tracking.
In each scenario, dose reconstruction was performed online and in real time during delivery of two dual‐arc volumetric‐modulated arc therapy prostate plans with a prescribed fraction dose of 7 Gy to the prostate and simultaneous intraprostatic lesion boosts with doses of at least 8 Gy, but up to 10 Gy as long as the organs at risk dose constraints were fulfilled. The plans were delivered to a pelvis phantom that replicated three patient‐measured motion traces using a rotational insert with 21 layers of EBT3 film spaced 2.5 mm apart. DoseTracker repeatedly calculated the actual motion‐including dose increment and the planned static dose increment since the last calculation in 84 500 points in the film stack. The experiments were performed with a TrueBeam accelerator with MLC and couch tracking based on electromagnetic transponders embedded in the film stack.
The motion‐induced dose error was quantified as the difference between the final cumulative dose with motion and without motion using the 2D 2%/2 mm γ‐failure rate and the difference in dose to 95% of the clinical target volume (CTV ΔD95%) and the gross target volume (GTV ΔD95%) as well as the difference in dose to 0.1 cm³ of the urethra, bladder, and rectum (ΔD0.1CC). The motion‐induced errors were compared between dose reconstructions and film measurements.
Results
The dose was reconstructed in all calculation points at a mean frequency of 4.7 Hz. The root‐mean‐square difference between real‐time reconstructed and film‐measured motion‐induced errors was 3.1%‐points (γ‐failure rate), 0.13 Gy (CTV ΔD95%), 0.23 Gy (GTV ΔD95%), 0.19 Gy (urethra ΔD0.1CC), 0.09 Gy (bladder ΔD0.1CC), and 0.07 Gy (rectum ΔD0.1CC).
Conclusions
In a series of phantom experiments, online real‐time rotation‐including dose reconstruction was performed for the first time. The calculated motion‐induced errors agreed well with film measurements. The dose reconstruction provides a valuable tool for monitoring dose delivery and investigating the efficacy of advanced motion‐compensation techniques in the presence of translational and rotational motion.
... Though DoseTracker's use of a simplified dose calculation creates uncertainty in the absolute dose, it can accurately calculate the difference between planned and accumulated dose (dose error) as compared to a treatment planning system (Ravkilde et al 2014), providing real-time dose reconstructions for liver stereotactic body radiation therapy (SBRT) with phantom experiments (Ravkilde et al 2018) and in silico with previous clinical treatments (Skouboe et al 2019). Similarly, provided real-time dose reconstruction using pre-calculated dose influence data generated by a Monte Carlo dose calculation engine on prostate step-and-shoot intensity modulated radiation therapy (IMRT) treatments, which was further extended to lung SBRT and prostate VMAT (Kamerling et al 2017). A new online motion management workflow for MRI-Linac has been proposed in which IMRT treatments are adapted on the fly to account for inter-and intrafraction motion (Kontaxis et al 2015a(Kontaxis et al , 2015b. ...
Motion in the patient anatomy causes a reduction in dose delivered to the target, while increasing dose to healthy tissue. Multi-Leaf Collimator (MLC) tracking has been clinically implemented to adapt dose delivery to account for intrafraction motion. Current methods shift the planned MLC aperture in the direction of motion, then optimise the new aperture based on the difference in fluence. The drawback of these methods is that 3D dose, a function of patient anatomy and MLC aperture sequence, is not properly accounted for. To overcome the drawback of current fluence-based methods, we have developed and investigated real-time adaptive MLC tracking based on dose optimisation. A novel MLC tracking algorithm, dose optimisation, has been developed which accounts for the moving patient anatomy by optimising the MLC based on the dose delivered dose during treatment. The MLC tracking with dose optimisation method was applied in silico to a prostate cancer VMAT treatment dataset with observed intrafraction motion. Its performance was compared to MLC tracking with fluence optimisation and, as a baseline, without MLC tracking. To quantitatively assess performance, we computed the dose error and 3D γ failure rate (2 mm/2%) for each fraction and method. Dose optimisation achieved a γ failure rate of (4.7±1.2)% (mean and standard deviation) over all fractions, which was significantly lower than fluence optimisation (7.5±2.9)% (Wilcoxon sign-rank test p<0.01). Without MLC tracking, a γ failure rate of (15.3±12.9)% was achieved. By considering the accumulation of dose in the moving anatomy during treatment, dose optimisation was shown to reduce the dose error to levels below that of the currently clinically implemented fluence optimisation. These results show that adapting the MLC to account for dose accumulation provides better conformity to the planned dose.
... In radiotherapy, there is a clear increase of the use of stereotactic body radiotherapy (SBRT), 1 which may be planned with inhomogeneous target doses for focal lesion ablation and organ at risk sparing. 2 This makes accurate treatment delivery at each fraction of paramount importance, which is unfortunately challenged by intrafractional motion and anatomical changes. [3][4][5][6][7] The motion can deteriorate the delivered dose distribution, especially in the tumor, as concluded in various studies performing dynamic (time-resolved) dose reconstruction for indications such as liver, [8][9][10][11][12] lung, 13,14 prostate, [15][16][17][18] and stomach 19 with various motion mitigation strategies. The studies show a large dosimetric impact of target motion and the dosimetric benefit of applying motion mitigation strategies. ...
Purpose
Intrafractional motion during radiotherapy delivery can deteriorate the delivered dose. Dynamic rotational motion of up to 38 degrees has been reported during prostate cancer radiotherapy, but methods to determine the dosimetric consequences of such rotations are lacking. Here, we create and experimentally validate a dose reconstruction method that accounts for dynamic rotations and translations in a commercial treatment planning system (TPS). Interplay effects are quantified by comparing dose reconstructions with dynamic and constant rotations.
Methods
The dose reconstruction accumulates the dose in points of interest while the points are moved in six degrees of freedom (6DoF) in a precalculated time‐resolved four‐dimensional (4D) dose matrix to emulate dynamic motion in a patient. The required 4D dose matrix was generated by splitting the original treatment plan into multiple sub‐beams, each representing 0.4 s dose delivery, and recalculating the dose of the split plan in the TPS (Eclipse). The dose accumulation was performed via TPS scripting by querying the dose of each sub‐beam in dynamically moving points, allowing dose reconstruction with any dynamic motion.
The dose reconstruction was validated with film dosimetry for two prostate dual arc VMAT plans with intra‐prostatic lesion boosts. The plans were delivered to a pelvis phantom with internal dynamic rotational motion of a film stack (21 films with 2.5 mm separation). Each plan was delivered without motion and with three prostate motion traces. Motion‐including dose reconstruction was performed for each motion experiment using the actual dynamic rotation as well as a constant rotation equal to the mean rotation during the experiment. For each experiment, the 3%/2 mm γ failure rate of the TPS dose reconstruction was calculated with the film measurement being the reference. For each motion experiment, the motion‐induced 3%/2 mm γ failure rate was calculated using the static delivery as the reference and compared between film measurements and TPS dose reconstruction. DVH metrics for RT structures fully contained in the film volume were also compared between film and TPS.
Results
The mean γ failure rate of the TPS dose reconstructions when compared to film doses was 0.8% (two static experiments) and 1.7% (six dynamic experiments). The mean (range) of the motion‐induced γ failure rate in film measurements was 35.4% (21.3–59.2%). The TPS dose reconstruction agreed with these experimental γ failure rates with root‐mean‐square errors of 2.1% (dynamic rotation dose reconstruction) and 17.1% (dose reconstruction assuming constant rotation).
By DVH metrics, the mean (range) difference between dose reconstructions with dynamic and constant rotation was 4.3% (−0.3–10.6%) (urethra D2%), −0.6% (−5.6%–2.5%) (urethra D99%), 1.1% (−7.1–7.7%) (GTV D2%), −1.4% (−17.4–7.1%) (GTV D95%), −1.2% (−17.1–5.7%) (GTV D99%), and −0.1% (−3.2–7.6%) (GTV mean dose). Dose reconstructions with dynamic motion revealed large interplay effects (cold and hot spots).
Conclusions
A method to perform dose reconstructions for dynamic 6DoF motion in a TPS was developed and experimentally validated. It revealed large differences in dose distribution between dynamic and constant rotations not identifiable through dose reconstructions with constant rotation.
... The proposed phantom with corresponding forward and backwards DVFs can be used as a ground truth to validate the geometric (Paganelli et al., 2019;Eiben et al., 2019) and dosimetric (Bertholet et al., 2019a) accuracy of different types of motion models such as rigid shifts (Poulsen et al., 2012;Kamerling et al., 2017), 4D imaging (Kamerling et al., 2016;Paganelli et al., 2018a) or deformable motion models (McClelland et al., 2013;Paganelli et al., 2019). Other applications include the validation of DIR-based image processing for motion mitigation strategies (van de Lindt et al., 2019) and 4DCT-based planning methods comparison (Wolthaus et al., 2008). ...
Breathing motion is challenging for radiotherapy planning and delivery. This requires advanced four-dimensional (4D) imaging and motion mitigation strategies and associated validation tools with known deformations. Numerical phantoms such as the XCAT provide reproducible and realistic data for simulation-based validation. However, the XCAT generates partially inconsistent and non-invertible deformations where tumours remain rigid and structures can move through each other. We address these limitations by post-processing the XCAT deformation vector fields (DVF) to generate a breathing phantom with realistic motion and quantifiable deformation.
An open-source post-processing framework was developed that corrects and inverts the XCAT-DVFs while preserving sliding motion between organs. Those post-processed DVFs are used to warp the first XCAT-generated image to consecutive time points providing a 4D phantom with a tumour that moves consistently with the anatomy, the ability to scale lung density as well as consistent and invertible DVFs. For a regularly breathing case, the inverse consistency of the DVFs was verified and the tumour motion was compared to the original XCAT. The generated phantom and DVFs were used to validate a motion-including dose reconstruction (MIDR) method using isocenter shifts to emulate rigid motion. Differences between the reconstructed doses with and without lung density scaling were evaluated.
The post-processing framework produced DVFs with a maximum 95 t h -percentile inverse-consistency error of 0.02 mm. The generated phantom preserved the dominant sliding motion between the chest wall and inner organs. The tumour of the original XCAT phantom preserved its trajectory while deforming consistently with the underlying tissue. The MIDR was compared to the ground truth dose reconstruction illustrating its limitations. MIDR with and without lung density scaling resulted in small dose differences up to 1 Gy (prescription 54 Gy).
The proposed open-source post-processing framework overcomes important limitations of the original XCAT phantom and makes it applicable to a wider range of validation applications within radiotherapy.
... Tumor and patient positions were tracked by MRI for abdominal and liver SBRT in the simulation studies conducted by Glitzner et al. [109] and Fast et al. [110] respectively. Signals from the electromagnetic transponder-based positioning system (Calypso) were used for reconstructing prostate position [111] and liver trajectories [112,113]. The lung tumor motion trajectories were reconstructed using data acquired with 4D Computed tomography in the study by Kamerling et al. [114]. ...
... The impact of MLC tracking for margin reduction was evaluated in simulation studies for prostate [111,115] and lung [114]. Two kidney cases were simulated using 4D-MRI imaging of volunteers by Glitzneret et al. [109]. ...
Stereotactic body radiation therapy (SBRT) has been recognized as a standard treatment option for many anatomical sites. Sophisticated radiation therapy techniques have been developed for carrying out these treatments and new quality assurance (QA) programs are therefore required to guarantee high geometrical and dosimetric accuracy. This paper focuses on recent advances on in-vivo measurements methods (IVM) for SBRT treatment. More specifically, all of the online QA methods for estimating the effective dose delivered to patients were compared. Determining the optimal IVM for performing SBRT treatments would reduce the risk of errors that could jeopardize treatment outcome. A total of 89 papers were included. The papers were subdivided into the following topics: point dosimeters (PD), transmission detectors (TD), log file analysis (LFA), electronic portal imaging device dosimetry (EPID), dose accumulation methods (DAM). The detectability capability of the main IVM detectors/devices were evaluated. All of the systems have some limitations: PD has no spatial data, EPID has limited sensitivity towards set-up errors and intra-fraction motion in some anatomical sites, TD is insensitive towards patient related errors, LFA is not an independent measure, DAMs are not always based on measures. In order to minimize errors in SBRT dose delivery, we recommend using synergic combinations of two or more of the systems described in our review: on-line tumor position and patient information should be combined with MLC position and linac output detection accuracy. In this way the effects of SBRT dose delivery errors will be reduced.
... The deployed dose reconstruction workflow evolved from a set of tools that were originally developed to validate real-time dose accumulation methods [26]. It aims at calculating the delivered dose by combining continuous information about the treatment machine status with a dynamic model of the patient anatomy (see Fig. 1). ...
Background and purpose:
Anatomical changes during external beam radiotherapy prevent the accurate delivery of the intended dose distribution. Resolving the delivered dose, which is currently unknown, is crucial to link radiotherapy doses to clinical outcomes and ultimately improve the standard of care.
Material and methods:
In this study, we present a dose reconstruction workflow based on data routinely acquired during MR-guided radiotherapy. It employs 3D MR images, 2D cine MR images and treatment machine log files to calculate the delivered dose taking intrafractional motion into account. The developed pipeline was used to measure anatomical changes and assess their dosimetric impact in 89 prostate radiotherapy fractions delivered with a 1.5 T MR-linac at our institute.
Results:
Over the course of radiation delivery, the CTV shifted 0.6 mm ± 2.1 mm posteriorly and 1.3 mm ± 1.5 mm inferiorly. When extrapolating the dose changes in each case to 20 fractions, the mean clinical target volume D98% and clinical target volume D50% dose-volume metrics decreased by 1.1 Gy ± 1.6 Gy and 0.1 Gy ± 0.2 Gy, respectively. Bladder D3% did not change (0.0 Gy ± 1.2 Gy), while rectum D3% decreased by 1.0 Gy ± 2.0 Gy. Although anatomical changes and their dosimetric impact were small in the majority of cases, large intrafractional motion caused the delivered dose to substantially deviate from the intended plan in some fractions.
Conclusions:
The presented end-to-end workflow is able to reliably, non-invasively and automatically reconstruct the delivered prostate radiotherapy dose by processing MR-linac treatment log files and online MR images. In the future, we envision this workflow to be adapted to other cancer sites and ultimately to enter widespread clinical use.
... En plus d'un suivi du volume cible pendant l'irradiation (tracking), une reconstruction de dose en temps réel peut être envisagée afin de corriger la dose délivrée en temps réel. Plusieurs études se sont intéressées à cette problématique [91][92][93][94], certaines proposent des algorithmes de calcul de dose simplifiés afin de réaliser des calculs rapides [91]. ...
Standard external beam radiotherapy is based on a planning computed tomography(CT) scan. This CT provideselectron densities required for dose calculation. 3D imaging such as cone beam CT (CBCT), MV-CT or magnetic resonance imaging (MRI), areacquired just before irradiationfor target volume registration. These images could be used to quantify dosimetric impact of anatomical variations occurring during the treatment course. The objective of the thesis was to develop, evaluate and compare CBCT-based and MRI-based dose calculation methods, in a dose-guided adaptive radiotherapy perspective. For head-and-neck CBCT-based dose calculation, adeep learning method was compared to three other methods from literature. For prostate MRI-based dose calculation, nine methodsincluding an atlas-based, a patch-based and deep learning methods with different architectures were compared. Moreover, dosimetric benefits of adaptive radiotherapy strategies (offline for head-and-neck and plan treatment library for cervix) wereevaluated. To generate pseudo-CT from CBCT or MRI, deep learningmethods arepromising, since they are fast and accurate. These methods can be used for a dose monitoring during treatment course in an adaptive radiotherapy process.
... Real-time motion-including dose reconstruction has been demonstrated in simulated treatments [13][14][15] and in phantom experiments. 16 We previously created an in-house developed software program, DoseTracker, 16 with the intent of determining motion-induced dosimetric errors in real time. ...
... Real-time motion-including dose reconstruction has been demonstrated elsewhere by mapping precalculated doses from a plan CT onto a moving target. [13][14][15]26 Relying on precalculated doses may however limit the applicability in certain scenarios. ...
Purpose
In radiotherapy, tumor motion may deteriorate the planned dose distribution. However, the dosimetric consequences of the motion are normally unknown for individual treatments. We here present a method for real‐time motion‐including tumor dose reconstruction and demonstrate its use for simulated stereotactic body radiotherapy (SBRT) of patients with liver cancer previously treated with Calypso‐guided gating.
Methods
Real‐time motion‐including dose reconstruction was performed using in‐house developed software, DoseTracker, on offline replays of previous clinical treatments. The patient cohort consisted of fifteen patients previously treated in our clinic with three‐fraction SBRT to the liver using conformal or IMRT plans. The tumor motion at treatment was monitored with implanted electromagnetic transponders. The dose reconstruction was performed for both the actual gated treatments and simulated nongated treatments using a 21 Hz data stream containing accelerator parameters and the recorded motion. The dose was reconstructed in the same calculation points within the planning target volume (PTV) as used by the treatment planning system (TPS). The reconstructed doses were compared with calculations performed in the TPS, in which the motion was modeled as a series of isocenter shifts. The comparison included point doses as a function of treatment time and the dose volume histogram (DVH) for the clinical target volume (CTV). The motion‐induced reduction in the dose to 95% of the CTV, ΔD95%, and in the mean CTV dose, ΔDMean, was compared between DoseTracker and the TPS for each simulated fraction. DoseTracker currently assumes water density within the patient contour, so for comparison, the TPS calculations were performed with both CT density and water density. The calculation times were additionally analyzed.
Results
Dose reconstruction was carried out for ninety SBRT sessions with calculation volumes ranging from 9.9 to 366.4 cm³ and median calculation times of 55–155 ms (equivalent to 18.2–6.5 Hz). Time‐resolved trends of doses to a single calculation point in the patient were well replicated and dose differences between actual and planned calculations matched well. ΔDMean had a range of −0.1%–30.7%‐points and was estimated by DoseTracker with a root‐mean‐square deviation (RMSD) to the TPS calculations of 0.43%–points (water density) and 0.79%‐points (CT density). Similarly, ΔD95% had a range of 0.0%–35.2%‐points and was estimated by DoseTracker with an RMSD of 0.80%‐points (water density) and 1.33%‐points (CT density). DoseTracker predicted losses in tumor dose coverage above 5%‐points with high sensitivity (91.7%) and specificity (97.6%).
Conclusions
Real‐time dose reconstruction to moving tumors was demonstrated on offline replays of previous clinical treatments. DVHs of actually delivered dose are made available immediately after the end of treatment fractions. It shows promising results for liver SBRT with accurate estimation of CTV dose deteriorations caused by motion during treatment.
... The actually delivered dose, taking motion into account, may be estimated from time-resolved motion monitoring data (Poulsen et al 2012b, Kamerling et al 2017, Ravkilde et al 2018 and would arguably allow to establish more accurate dose-response models than the planned dose (Siochi et al 2015, Meijers et al 2019. ...
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.
... In modern radiotherapy, the focus has shifted toward adaptive radiotherapy, and an increasing demand for online dose verification of dose delivery has been observed [13]. Dose-distribution prediction by analyzing the machine delivery log file has been introduced for online dose verification [14]. Reconstructed three-dimensional (3D) dose verification models have also been developed for the same purpose [15][16][17]. ...
Background:
The demand for dose verification during treatment has risen with the increasing use of intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) in modern radiation therapy. This study aims to validate the transmission factors of a new transmission detector, the Dolphin online monitoring system (IBA Dosimetry, Schwarzenbruck, Germany), for clinical use.
Methods:
The transmission factors of the Dolphin detector were evaluated using 6 MV, 6 flattening filter free (FFF), 10 MV, and 10 FFF clinical beams from a TrueBeam STx linear accelerator system. Two-dimensional (2D) dose distributions were measured through portal dosimetry with and without Dolphin to derive the transmission factors. The measurements were performed using 10 IMRT and 10 VMAT treatment plans. The transmission factors were calculated using a non-negative least squares problem solver for the 2D dose matrix. Normalized plans were generated using the derived transmission factors. Patient-specific quality assurance with normalized plans was performed using portal dosimetry and an ArcCheck detector to verify the transmission factors. The gamma passing rates were calculated for the 2%/2 mm and 1%/1 mm criteria.
Results:
The transmission factors for the 6 MV, 6 FFF, 10 MV, and 10 FFF beams, were 0.878, 0.824, 0.913, and 0.883, respectively. The average dose difference between the original plan without Dolphin and the normalized plan with Dolphin was less than 1.8% for all measurements. The mean passing rates of the gamma evaluation were 98.1 ± 2.1 and 82.9 ± 12.6 for the 2%/2 mm and 1%/1 mm criteria, respectively, for portal dosimetry of the original plan. In the case of the portal dosimetry of the normalized plan, the mean passing rates of the gamma evaluation were 97.2 ± 2.8 and 79.1 ± 14.8 for the 2%/2 mm and 1%/1 mm criteria, respectively.
Conclusions:
The Dolphin detector can be used for online dosimetry when valid transmission factors are applied to the clinical plan.
