Patient-specific IMRT verification using independent fluence-based dose calculation software: experimental benchmarking and initial clinical experience

Impact of log file source and data frequency on accuracy of log file-based patient specific quality assurance

Performing phantom measurements for patient-specific quality assurance (PSQA) adds a significant amount of time to the adaptive radiotherapy procedure. Log file based PSQA can be used to increase the efficiency of this process. This study compared the dosimetric accuracy of high-frequency linear accelerator (Linac) log files and low-frequency log data stored in the oncology information system (OIS). Thirty patients were included, that were recently treated in the head and neck (HN), brain, and prostate region with volumetric modulated arc therapy (VMAT) and an additional ten patients treated using stereotactic body radiation therapy (SBRT) with 3D-conformal radiotherapy (3D-CRT) technique. Log data containing a single fraction were used to calculate the dose distributions. The dosimetric differences between Linac log files and OIS logs were evaluated with a gamma analysis with 2%/2 mm criterion and dose threshold of 30%. The original treatment plan was used as a reference. Moreover, DVH parameters of D_98%, D_50%, and D_2% of the planning-target volume (PTV) and dose to several organs at risk (OARs) were reported. Significant differences in dose distributions between the two log types and the original dose were observed for PTV D_98% and D_2% (r < 0.001) for HN cases, PTV D_98% (r = 0.005) for brain cases, and PTV D_50% (r = 0.015) for prostate cases. No significant differences were found between the two log types with respect to D_50%. The root mean square (RMS) error of the leaf positions of the OIS log was approximately twice the RMS error of the Linac log file for VMAT plans, but identical for 3D-CRT plans. The relationship between the gamma pass rate and the RMS error showed a moderate correlation for the Linac log files (r = -0.58, p < 0.001) and strong correlation for OIS logs (r = -0.71, p < 0.001). Furthermore, all doses calculated using Linac log files and OIS log data had a GPR >90% for an RMS error < 3.3 mm. Based on these findings, a tolerance limit of RMS error of 3.3 mm for considering OIS log based PSQA was established. Nevertheless, the OIS log data quality should be improved to achieve adequate PSQA.

Efficient dose-volume histogram-based pretreatment patient-specific quality assurance methodology with combined deep learning and machine learning models for volumetric modulated arc radiotherapy

BACKGROUND

Weak correlation between gamma passing rates and dose differences in target volumes and organs at risk (OARs) has been reported in several studies. Evaluation on the differences between planned dose-volume histogram (DVH) and reconstructed DVH from measurement was adopted and incorporated into patient-specific quality assurance (PSQA). However, it is difficult to develop a methodology allowing the evaluation of errors on DVHs accurately and quickly.

PURPOSE

To develop a DVH-based pretreatment PSQA for volumetric modulated arc therapy (VMAT) with combined deep learning (DL) and machine learning models to overcome the limitation of conventional gamma index (GI) and improve the efficiency of DVH-based PSQA.

METHODS

A DL model with a three-dimensional squeeze-and-excitation residual blocks incorporated into a modified U-net was developed to predict the measured PSQA DVHs of 208 head-and-neck (H&N) cancer patients underwent VMAT between 2018 and 2021 from two hospitals, in which 162 cases was randomly selected for training, 18 for validation, and 28 for testing. After evaluating the differences between treatment planning system (TPS) and PSQA DVHs predicted by DL model with multiple metrics, a pass or fail (PoF) classification model was developed using XGBoost algorithm. Evaluation of domain experts on dose errors between TPS and reconstructed PSQA DVHs was taken as ground truth for PoF classification model training.

RESULTS

The prediction model was able to achieve a good agreement between predicted, measured, and TPS doses. Quantitative evaluation demonstrated no significant difference between predicted PSQA dose and measured dose for target and OARs, except for D_mean of PTV6900 (p = 0.001), D₅₀ of PTV6000 (p = 0.014), D₂ of PTV5400 (p = 0.009), D₅₀ of left parotid (p = 0.015), and D_max of left inner ear (p = 0.007). The XGBoost model achieved an area under curves, accuracy, sensitivity, and specificity of 0.89 versus 0.88, 0.89 versus 0.86, 0. 71 versus 0.71, and 0.95 versus 0.91 with measured and predicted PSQA doses, respectively. The agreement between domain experts and the classification model was 86% for 28 test cases.

CONCLUSIONS

The successful prediction of PSQA doses and classification of PoF for H&N VMAT PSQA indicating that this DVH-based PSQA method is promising to overcome the limitations of GI and to improve the efficiency and accuracy of VMAT delivery.

Report of AAPM Task Group 219 on independent calculation-based dose/MU verification for IMRT

Independent verification of the dose per monitor unit (MU) to deliver the prescribed dose to a patient has been a mainstay of radiation oncology quality assurance (QA). We discuss the role of secondary dose/MU calculation programs as part of a comprehensive QA program. This report provides guidelines on calculation-based dose/MU verification for intensity modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT) provided by various modalities. We provide a review of various algorithms for "independent/second check" of monitor unit calculations for IMRT/VMAT. The report makes recommendations on the clinical implementation of secondary dose/MU calculation programs; on commissioning and acceptance of various commercially available secondary dose/MU calculation programs; on benchmark QA and periodic QA; and on clinically reasonable action levels for agreement of secondary dose/MU calculation programs.

Cross verification of independent dose recalculation, log files based, and phantom measurement-based pretreatment quality assurance for volumetric modulated arc therapy

Independent treatment planning system (TPS) check with Mobius3D software, log files based quality assurance (QA) with MobiusFX, and phantom measurement‐based QA with ArcCHECK were performed and cross verified for head‐and‐neck (17 patients), chest (16 patients), and abdominal (19 patients) cancer patients who underwent volumetric modulated arc therapy (VMAT). Dosimetric differences and percentage gamma passing rates (%GPs) were evaluated and compared for this cross verification. For the dosimetric differences in planning target volume (PTV) coverage, there was no significant difference among TPS vs. Mobius3D, TPS vs. MobiusFX, and TPS vs. ArcCHECK. For the dosimetric differences in organs at risks (OARs), the number of metrics with an average dosimetric differences higher than ±3% for TPS vs Mobius3D, TPS vs MobiusFX, and TPS vs ArcCHECK were 1, 1, 7; 2, 1, 4; 1, 1, 5 for the patients with head‐and‐neck, abdomen, and chest cancer, respectively. The %GPs of global gamma indices for Mobius3D and MobiousFX were above 97%, while it ranged from 92% to 96% for ArcCHECK. The %GPs of individual volume‐based gamma indices were around 98% for Mobius3D and MobiousFX, except for γPTV for chest and abdominal cancer (88.9% to 92%); while it ranged from 86% to 99% for ArcCHECK. In conclusion, some differences in dosimetric metrics and gamma passing rates were observed with ArcCHECK measurement‐based QA in comparison with independent dosecheck and log files based QA. Care must be taken when considering replacing phantom measurement‐based IMRT/VMAT QA.

Validation of a GPU-Based 3D dose calculator for modulated beams

A superposition/convolution GPU-accelerated dose computation algorithm (the Calculator) has been recently incorporated into commercial software. The algorithm requires validation prior to clinical use. Three photon energies were examined: conventional 6 MV and 15 MV, and 10 MV flattening filter free (10 MVFFF). For a set of IMRT and VMAT plans based on four of the five AAPM Practice Guideline 5a downloadable datasets, ion chamber (IC) measurements were performed on the water-equivalent phantoms. The average difference between the Calculator and IC was -0.3 ± 0.8% (1SD). The same plans were projected on a phantom containing a biplanar diode array. We used the forthcoming criteria for routine gamma analysis, 3% dose-error (global (G) normalization, 2 mm distance to agreement, and 10% low dose cutoff). The γ (3%G/2 mm) average passing rate was 98.9 ± 2.1%. Measurement-guided three-dimensional dose reconstruction on the patient CT dataset (excluding the Lung) resulted in a similar average agreement rate with the Calculator: 98.2 ± 2.0%. The mean γ (3%G/2 mm) passing rate comparing the Calculator to the TPS (again excluding the Lung) was 99.0 ± 1.0%. Because of the significant inhomogeneity, the Lung case was investigated separately. The calculator has an alternate heterogeneity correction mode that can change the results in the thorax for higher-energy beams (15 MV). As this correction is nonphysical and was optimized for simple slab geometries, its application leads to mixed results when compared to the TPS and independent Monte Carlo calculations, depending on the CT dataset and the plan. The Calculator vs. TPS 15 MV Guideline 5a IMRT and VMAT plans demonstrate 96.3% and 93.4% γ (3%G/2 mm) passing rates respectively. For the lower energies, which should be predominantly used in the thoracic region, the passing rates for the same plans and criteria range from 98.6 to 100%. Overall, the Calculator accuracy is sufficient for the intended use.

A method to reconstruct and apply 3D primary fluence for treatment delivery verification

Motivation

In this study, a method is reported to perform IMRT and VMAT treatment delivery verification using 3D volumetric primary beam fluences reconstructed directly from planned beam parameters and treatment delivery records. The goals of this paper are to demonstrate that 1) 3D beam fluences can be reconstructed efficiently, 2) quality assurance (QA) based on the reconstructed 3D fluences is capable of detecting additional treatment delivery errors, particularly for VMAT plans, beyond those identifiable by other existing treatment delivery verification methods, and 3) QA results based on 3D fluence calculation (3DFC) are correlated with QA results based on physical phantom measurements and radiation dose recalculations.

Methods

Using beam parameters extracted from DICOM plan files and treatment delivery log files, 3D volumetric primary fluences are reconstructed by forward‐projecting the beam apertures, defined by the MLC leaf positions and modulated by beam MU values, at all gantry angles using first‐order ray tracing. Treatment delivery verifications are performed by comparing 3D fluences reconstructed using beam parameters in delivery log files against those reconstructed from treatment plans. Passing rates are then determined using both voxel intensity differences and a 3D gamma analysis. QA sensitivity to various sources of errors is defined as the observed differences in passing rates. Correlations between passing rates obtained from QA derived from both 3D fluence calculations and physical measurements are investigated prospectively using 20 clinical treatment plans with artificially introduced machine delivery errors.

Results

Studies with artificially introduced errors show that common treatment delivery problems including gantry angle errors, MU errors, jaw position errors, collimator rotation errors, and MLC leaf position errors were detectable at less than normal machine tolerances. The reported 3DFC QA method has greater sensitivity than measurement‐based QA methods. Statistical analysis‐based Spearman's correlations shows that the 3DFC QA passing rates are significantly correlated with passing rates of physical phantom measurement‐based QA methods.

Conclusion

Among measurement‐less treatment delivery verification methods, the reported 3DFC method is less demanding than those based on full dose re‐calculations, and more comprehensive than those that solely checks beam parameters in treatment log files. With QA passing rates correlating to measurement‐based passing rates, the 3DFC QA results could be useful for complementing the physical phantom measurements, or verifying treatment deliveries when physical measurements are not available. For the past 4+ years, the reported method has been implemented at authors’ institution 1) as a complementary metric to physical phantom measurements for pretreatment, patient‐specific QA of IMRT and VMAT plans, and 2) as an important part of the log file‐based automated verification of daily patient treatment deliveries. It has been demonstrated to be useful in catching both treatment plan data transfer errors and treatment delivery problems.

Towards effective and efficient patient-specific quality assurance for spot scanning proton therapy

An intensity-modulated proton therapy (IMPT) patient-specific quality assurance (PSQA) program based on measurement alone can be very time consuming due to the highly modulated dose distributions of IMPT fields. Incorporating independent dose calculation and treatment log file analysis could reduce the time required for measurements. In this article, we summarize our effort to develop an efficient and effective PSQA program that consists of three components: measurements, independent dose calculation, and analysis of patient-specific treatment delivery log files. Measurements included two-dimensional (2D) measurements using an ionization chamber array detector for each field delivered at the planned gantry angles with the electronic medical record (EMR) system in the QA mode and the accelerator control system (ACS) in the treatment mode, and additional measurements at depths for each field with the ACS in physics mode and without the EMR system. Dose distributions for each field in a water phantom were calculated independently using a recently developed in-house pencil beam algorithm and compared with those obtained using the treatment planning system (TPS). The treatment log file for each field was analyzed in terms of deviations in delivered spot positions from their planned positions using various statistical methods. Using this improved PSQA program, we were able to verify the integrity of the data transfer from the TPS to the EMR to the ACS, the dose calculation of the TPS, and the treatment delivery, including the dose delivered and spot positions. On the basis of this experience, we estimate that the in-room measurement time required for each complex IMPT case (e.g., a patient receiving bilateral IMPT for head and neck cancer) is less than 1 h using the improved PSQA program. Our experience demonstrates that it is possible to develop an efficient and effective PSQA program for IMPT with the equipment and resources available in the clinic.

Adaptive beamlet-based finite-size pencil beam dose calculation for independent verification of IMRT and VMAT

PURPOSE

The use of sophisticated dose calculation procedure in modern radiation therapy treatment planning is inevitable in order to account for complex treatment fields created by multileaf collimators (MLCs). As a consequence, independent volumetric dose verification is time consuming, which affects the efficiency of clinical workflow. In this study, the authors present an efficient adaptive beamlet-based finite-size pencil beam (AB-FSPB) dose calculation algorithm that minimizes the computational procedure while preserving the accuracy.

METHODS

The computational time of finite-size pencil beam (FSPB) algorithm is proportional to the number of infinitesimal and identical beamlets that constitute an arbitrary field shape. In AB-FSPB, dose distribution from each beamlet is mathematically modeled such that the sizes of beamlets to represent an arbitrary field shape no longer need to be infinitesimal nor identical. As a result, it is possible to represent an arbitrary field shape with combinations of different sized and minimal number of beamlets. In addition, the authors included the model parameters to consider MLC for its rounded edge and transmission.

RESULTS

Root mean square error (RMSE) between treatment planning system and conventional FSPB on a 10 × 10 cm(2) square field using 10 × 10, 2.5 × 2.5, and 0.5 × 0.5 cm(2) beamlet sizes were 4.90%, 3.19%, and 2.87%, respectively, compared with RMSE of 1.10%, 1.11%, and 1.14% for AB-FSPB. This finding holds true for a larger square field size of 25 × 25 cm(2), where RMSE for 25 × 25, 2.5 × 2.5, and 0.5 × 0.5 cm(2) beamlet sizes were 5.41%, 4.76%, and 3.54% in FSPB, respectively, compared with RMSE of 0.86%, 0.83%, and 0.88% for AB-FSPB. It was found that AB-FSPB could successfully account for the MLC transmissions without major discrepancy. The algorithm was also graphical processing unit (GPU) compatible to maximize its computational speed. For an intensity modulated radiation therapy (∼12 segments) and a volumetric modulated arc therapy fields (∼90 control points) with a 3D grid size of 2.0 × 2.0 × 2.0 mm(3), dose was computed within 3-5 and 10-15 s timeframe, respectively.

CONCLUSIONS

The authors have developed an efficient adaptive beamlet-based pencil beam dose calculation algorithm. The fast computation nature along with GPU compatibility has shown better performance than conventional FSPB. This enables the implementation of AB-FSPB in the clinical environment for independent volumetric dose verification.

Modulation factors calculated with an EPID-derived MLC fluence model to streamline IMRT/VMAT second checks

This work outlines the development of a robust method of calculating modulation factors used for the independent verification of MUs for IMRT and VMAT treatments, to replace onerous ion chamber measurements. Two‐dimensional fluence maps were calculated for dynamic MLC fields that include MLC interleaf leakage, transmission, and tongue‐and‐groove effects, as characterized from EPID‐acquired images. Monte Carlo‐generated dose kernels were then used to calculate doses for a modulated field and that field with the modulation removed at a depth specific to the calculation point in the patient using in‐house written software, Mod_Calc. The ratio of these two doses was taken to calculate modulation factors. Comparison between Mod_Calc calculation and ion chamber measurement of modulation factors for 121 IMRT fields yielded excellent agreement, where the mean difference between the two was −0.3%±1.2%. This validated use of Mod_Calc clinically. Analysis of 5,271 dynamic fields from clinical use of Mod_Calc gave a mean difference of 0.3%±1.0% between Mod_Calc and Eclipse‐generated factors. In addition, 99.3% and 96.5% fields pass 5% and 2% criteria, respectively, for agreement between these two predictions. The development and use of Mod_Calc at our clinic has considerably streamlined our QA process for IMRT and RapidArc fields, compared to our previous method based on ion chamber measurements. As a result, it has made it feasible to maintain our established and trusted current in‐house method of MU verification, without resorting to commercial software alternatives.

PACS numbers: 87.55.km, 87.55.Qr, 87.55.kd, 87.57.uq

Application of an independent dose calculation software for estimating the impact of inter-fractional setup shifts in Helical Tomotherapy treatments

The purpose of this study is to validate the capability of in-house independent point dose calculation software to be used as a second check for Helical Tomotherapy treatment plans. The software performed its calculations in homogenous conditions (using the Cheese phantom, which is a cylindrical phantom with radius 15 cm and length 18 cm) using a factor-based algorithm. Fifty patients, who were treated for pelvic (10), prostate (14), lung (10), head & neck (12) and brain (4) cancers, were used. Based on the individual patient kVCT images and the pretreatment MVCT images for each treatment fraction, the corresponding daily patient setup shifts in the IEC-X, IEC-Y, and IEC-Z directions were registered. For each patient, the registered fractional setup shifts were grouped into systematic and random shifts. The average systematic dosimetric variations showed small dose deviation for the different cancer types (1.0%-3.0%) compared to the planned dose. Of the fifty patients, only three had percent differences larger than 5%. The average random dosimetric variations showed relatively small dose deviations (0.2%-1.1%) compared to the planned dose. None of the patients had percent differences larger than 5%. By examining the individual fractions of each patient, it is observed that only in 31 out of 1358 fractions the percent differences exceeded the border of 5%. These results indicate that the overall dosimetric impact from systematic and random variations is small and that the software is a capable platform for independent point dose validation for the Helical Tomotherapy modality.

Establishing an optimized patient-specific verification program for volumetric modulated arc therapy

Quality assurance (QA) of volumetric modulated arc therapy (VMAT) increases the workload significantly. We compared the results from 4 verification methods to establish an efficient VMAT QA. Planning for VMAT treatments was carried out for 40 consecutive patients. Pretreatment verifications were carried out with ion chamber array Physikalish-Technische Werkstätten (PTW729), electronic portal dosimetry (EPID), ion chamber measurements, and independent dose calculation with Diamond program. 2D analyses were made using the gamma analysis (3mm distance to agreement and 3% dose difference relative to maximum, 10% dose threshold). Average point dose difference calculated by Eclipse relative to ion chamber measurements and Diamond were 0.1%±0.9% and 0.6%±2.2%, respectively. Average pass rate for PTW729 was 99.2%±1.9% and 98.3%±1.3% for EPID. The total required time (linac occupancy time given in parentheses) for each QA method was: PTW729 43.5 minutes (26.5 minutes), EPID 14.5 minutes (2.5 minutes), ion chamber 34.5 minutes (26.5 minutes), and Diamond 12.0 minutes (0 minute). The results were consistent and allowed us to establish an optimized protocol, considering safety and accuracy as well as workload, consisting of 2 verification methods: EPID 2D analysis and independent dose calculation.

Evaluation of the efficiency and effectiveness of independent dose calculation followed by machine log file analysis against conventional measurement based IMRT QA

Experimental methods are commonly used for patient-specific IMRT delivery verification. There are a variety of IMRT QA techniques which have been proposed and clinically used with a common understanding that not one single method can detect all possible errors. The aim of this work was to compare the efficiency and effectiveness of independent dose calculation followed by machine log file analysis to conventional measurement-based methods in detecting errors in IMRT delivery. Sixteen IMRT treatment plans (5 head-and-neck, 3 rectum, 3 breast, and 5 prostate plans) created with a commercial treatment planning system (TPS) were recalculated on a QA phantom. All treatment plans underwent ion chamber (IC) and 2D diode array measurements. The same set of plans was also recomputed with another commercial treatment planning system and the two sets of calculations were compared. The deviations between dosimetric measurements and independent dose calculation were evaluated. The comparisons included evaluations of DVHs and point doses calculated by the two TPS systems. Machine log files were captured during pretreatment composite point dose measurements and analyzed to verify data transfer and performance of the delivery machine. Average deviation between IC measurements and point dose calculations with the two TPSs for head-and-neck plans were 1.2 ± 1.3% and 1.4 ± 1.6%, respectively. For 2D diode array measurements, the mean gamma value with 3% dose difference and 3 mm distance-to-agreement was within 1.5% for 13 of 16 plans. The mean 3D dose differences calculated from two TPSs were within 3% for head-and-neck cases and within 2% for other plans. The machine log file analysis showed that the gantry angle, jaw position, collimator angle, and MUs were consistent as planned, and maximal MLC position error was less than 0.5 mm. The independent dose calculation followed by the machine log analysis takes an average 47 ± 6 minutes, while the experimental approach (using IC and 2D diode array measurements) takes an average about 2 hours in our clinic. Independent dose calculation followed by machine log file analysis can be a reliable tool to verify IMRT treatments. Additionally, independent dose calculations have the potential to identify several problems (heterogeneity calculations, data corruptions, system failures) with the primary TPS, which generally are not identifiable with a measurement-based approach. Additionally, machine log file analysis can identify many problems (gantry, collimator, jaw setting) which also may not be detected with a measurement-based approach. Machine log file analysis could also detect performance problems for individual MLC leaves which could be masked in the analysis of a measured fluence.

Monte Carlo simulations to replace film dosimetry in IMRT verification

Patient-specific verification of intensity-modulated radiation therapy (IMRT) plans can be done by dosimetric measurements or by independent dose or monitor unit calculations. The aim of this study was the clinical evaluation of IMRT verification based on a fast Monte Carlo (MC) program with regard to possible benefits compared to commonly used film dosimetry. 25 head-and-neck IMRT plans were recalculated by a pencil beam based treatment planning system (TPS) using an appropriate quality assurance (QA) phantom. All plans were verified both by film and diode dosimetry and compared to MC simulations. The irradiated films, the results of diode measurements and the computed dose distributions were evaluated, and the data were compared on the basis of gamma maps and dose-difference histograms. Average deviations in the high-dose region between diode measurements and point dose calculations performed with the TPS and MC program were 0.7 ± 2.7% and 1.2 ± 3.1%, respectively. For film measurements, the mean gamma values with 3% dose difference and 3mm distance-to-agreement were 0.74 ± 0.28 (TPS as reference) with dose deviations up to 10%. Corresponding values were significantly reduced to 0.34 ± 0.09 for MC dose calculation. The total time needed for both verification procedures is comparable, however, by far less labor intensive in the case of MC simulations. The presented study showed that independent dose calculation verification of IMRT plans with a fast MC program has the potential to eclipse film dosimetry more and more in the near future. Thus, the linac-specific QA part will necessarily become more important. In combination with MC simulations and due to the simple set-up, point-dose measurements for dosimetric plausibility checks are recommended at least in the IMRT introduction phase.

Effect of photon-beam energy on VMAT and IMRT treatment plan quality and dosimetric accuracy for advanced prostate cancer

PURPOSE

The goal of the research was to evaluate treatment plan quality and dosimetric accuracy of volumetric modulated arc therapy (VMAT) and intensity-modulated radiotherapy (IMRT) plans using 6, 10, and 15 MV photon beams for prostate cancer including lymph nodes.

METHODS

In this retrospective study, VMAT and IMRT plans were generated with the Pinnacle© treatment planning system (TPS) (V9.0) for 10 prostate cancer cases. Each plan consisted of two target volumes: PTV(B) included the prostate bed, PTV(PC+LN) contained PTV(B) and lymph nodes. For plan evaluation statistics, the homogeneity index, conformity index, mean doses, and near-max doses to organs at risk (OAR) were analyzed. Treatment time and number of monitor units were assessed to compare delivery efficiency. Dosimetric plan verification was performed with a 2D ionization chamber array placed in a full scatter phantom.

RESULTS

No differences were found for target and OAR parameters in low and high energy photon beam plans for both VMAT and IMRT. A slightly higher low dose volume was detected for 6 MV VMAT plans (normal tissue: D(mean) = 16.47 Gy) compared to 10 and 15 MV VMAT plans (D(mean) = 15.90 Gy and 15.74 Gy, respectively), similar to the findings in IMRT. In VMAT, > 96% of detector points passed the 3%/ 3 mm γ criterion; marginally better accuracy was found in IMRT (> 97%).

CONCLUSION

For static and rotational IMRT, 15 MV photons did not show advantages over 6 and 10 MV high energy photon beams in large volume pelvic plans. For the investigated TPS and linac combination, 10 MV photon beams can be used as the general purpose energy for intensity modulation.

eIMRT: a web platform for the verification and optimization of radiation treatment plans

The eIMRT platform is a remote distributed computing tool that provides users with Internet access to three different services: Monte Carlo optimization of treatment plans, CRT & IMRT treatment optimization, and a database of relevant radiation treatments/clinical cases. These services are accessible through a user-friendly and platform independent web page. Its flexible and scalable design focuses on providing the final users with services rather than a collection of software pieces. All input and output data (CT, contours, treatment plans and dose distributions) are handled using the DICOM format. The design, implementation, and support of the verification and optimization algorithms are hidden to the user. This allows a unified, robust handling of the software and hardware that enables these computation-intensive services. The eIMRT platform is currently hosted by the Galician Supercomputing Center (CESGA) and may be accessible upon request (there is a demo version at http://eimrt.cesga.es:8080/eIMRT2/demo; request access in http://eimrt.cesga.es/signup.html). This paper describes all aspects of the eIMRT algorithms in depth, its user interface, and its services. Due to the flexible design of the platform, it has numerous applications including the intercenter comparison of treatment planning, the quality assurance of radiation treatments, the design and implementation of new approaches to certain types of treatments, and the sharing of information on radiation treatment techniques. In addition, the web platform and software tools developed for treatment verification and optimization have a modular design that allows the user to extend them with new algorithms. This software is not a commercial product. It is the result of the collaborative effort of different public research institutions and is planned to be distributed as an open source project. In this way, it will be available to any user; new releases will be generated with the new implemented codes or upgrades.