Software for quantitative analysis of radiotherapy: overview, requirement analysis and design solutions

Radiotherapy-specific quality indicators at national level: How to make it happen

PURPOSE /OBJECTIVE

To promote best practice and quality of care, the Belgian College of Physicians for Radiotherapy Centers established a set of radiotherapy specific quality indicators for benchmarking on a national level. This paper describes the development, the collected QIs, the observed trends and the departments' evaluation of this initiative.

MATERIAL AND METHODS

The Donabedian approach was used, focussing on structural, process and outcome QIs. The criteria for QI selection were availability, required for low-threshold regular collection, and applicability to guidelines and good practice. The QIs were collected yearly and individualized reports were sent out to all RT departments. In 2021, a national survey was held to evaluate the ease of data collection and submission, and the perceived importance and validity of the collected QIs.

RESULTS

18 structural QI and 37 process and outcome parameters (n = 25 patients/pathology/department) were collected. The participation rate amounted to 95 % overall. The analysis gave a national overview of RT activity, resources, clinical practice and reported acute toxicities. The individualized reports allowed departments to benchmark their performance. The 2021 survey indicated that the QIs were overall easy to collect, relevant and reliable. The collection of acute recorded toxicities was deemed a weak point due to inter-observer variabilities and lack of follow-up time.

CONCLUSION

QI collection on a national level is a valuable process in steering quality improvement initiatives. The feasibility and relevance was demonstrated with a high level of participation. The national initiative will continue to evolve as a quality monitoring and improvement tool.

Statistical breathing curve sampling to quantify interplay effects of moving lung tumors in a 4D Monte Carlo dose calculation framework

PURPOSE

The interplay between respiratory tumor motion and dose application by intensity modulated radiotherapy (IMRT) techniques can potentially lead to undesirable and non-intuitive deviations from the planned dose distribution. We developed a 4D Monte Carlo (MC) dose recalculation framework featuring statistical breathing curve sampling, to precisely simulate the dose distribution for moving target volumes aiming at a comprehensive assessment of interplay effects.

METHODS

We implemented a dose accumulation tool that enables dose recalculations of arbitrary breathing curves including the actual breathing curve of the patient. This MC dose recalculation framework is based on linac log-files, facilitating a high temporal resolution up to 0.1 s. By statistical analysis of 128 different breathing curves, interplay susceptibility of different treatment parameters was evaluated for an exemplary patient case. To facilitate prospective clinical application in the treatment planning stage, in which patient breathing curves or linac log-files are not available, we derived a log-file free version with breathing curves generated by a random walk approach. Interplay was quantified by standard deviations σ in D_5%, D_50% and D_95%.

RESULTS

Interplay induced dose deviations for single fractions were observed and evaluated for IMRT and volumetric arc therapy (σ_D95% up to 1.3 %) showing a decrease with higher fraction doses and an increase with higher MU rates. Interplay effects for conformal treatment techniques were negligible (σ<0.1%). The log-file free version and the random walk generated breathing curves yielded similar results (deviations in σ< 0.1 %) and can be used as substitutes for interplay assessment.

CONCLUSION

It is feasible to combine statistically sampled breathing curves with MC dose calculations. The universality of the presented framework allows comprehensive assessment of interplay effects in retrospective and prospective clinically relevant scenarios.

PAGAT gel dosimetry for everyone: gel production, measurement and evaluation

Polymer gel (PG) dosimetry is a valuable tool to measure complex dose distributions in 3D with a high spatial resolution. However, due to complex protocols that need to be followed for in-house produced PGs and the high costs of commercially available gels, PG gels are only rarely applied in quality assurance procedures worldwide. In this work, we provide an introduction to perform highly standardized dosimetric PG experiments using PAGAT (PolyAcrylamide Gelatine gel fabricated at ATmospheric conditions) dosimetry gel. PAGAT gel can be produced at atmospheric conditions, at low costs and is evaluated using magnetic resonance imaging (MRI). The conduction of PG experiments is described in great detail including the gel production, treatment planning, irradiation, MRI evaluation and post-processing procedure. Furthermore, a plugin in an open source image processing tool for post-processing is provided free of charge that allows a standardized and reproducible analysis of PG experiments.

Biologically consistent dose accumulation using daily patient imaging

BACKGROUND

This work addresses a basic inconsistency in the way dose is accumulated in radiotherapy when predicting the biological effect based on the linear quadratic model (LQM). To overcome this inconsistency, we introduce and evaluate the concept of the total biological dose, bEQD_d.

METHODS

Daily computed tomography imaging of nine patients treated for prostate carcinoma with intensity-modulated radiotherapy was used to compute the delivered deformed dose on the basis of deformable image registration (DIR). We compared conventional dose accumulation (DA) with the newly introduced bEQD_d, a new method of accumulating biological dose that considers each fraction dose and tissue radiobiology. We investigated the impact of the applied fractionation scheme (conventional/hypofractionated), uncertainties induced by the DIR and by the assigned α/β-value.

RESULTS

bEQD_d was systematically higher than the conventionally accumulated dose with difference hot spots of 3.3-4.9 Gy detected in six out of nine patients in regions of high dose gradient in the bladder and rectum. For hypofractionation, differences are up to 8.4 Gy. The difference amplitude was found to be in a similar range to worst-case uncertainties induced by DIR and was higher than that induced by α/β.

CONCLUSION

Using bEQD_d for dose accumulation overcomes a potential systematic inaccuracy in biological effect prediction based on accumulated dose. Highest impact is found for serial-type late responding organs at risk in dose gradient regions and for hypofractionation. Although hot spot differences are in the order of several Gray, in dose-volume parameters there is little difference compared with using conventional or biological DA. However, when local dose information is used, e.g. dose surface maps, difference hot spots can potentially change outcomes of dose-response modelling and adaptive treatment strategies.

EView: An electric field visualization web platform for electroporation-based therapies

BACKGROUND AND OBJECTIVES

Electroporation is the phenomenon by which cell membrane permeability to ions and macromolecules is increased when the cell is briefly exposed to high electric fields. In electroporation-based treatments, such exposure is typically performed by delivering high voltage pulses across needle electrodes in tissue. For a given tissue and pulsing protocol, an electric field magnitude threshold exists that must be overreached for treatment efficacy. However, it is hard to preoperatively infer the treatment volume because the electric field distribution intricately depends on the electrodes' positioning and length, the applied voltage, and the electric conductivity of the treated tissues. For illustrating such dependencies, we have created EView (https://eview.upf.edu), a web platform that estimates the electric field distribution for arbitrary needle electrode locations and orientations and overlays it on 3D medical images.

METHODS

A client-server approach has been implemented to let the user set the electrode configuration easily on the web browser, whereas the simulation is computed on a dedicated server. By means of the finite element method, the electric field is solved in a 3D volume. For the sake of simplicity, only a homogeneous tissue is modeled, assuming the same properties for healthy and pathologic tissues. The non-linear dependence of tissue conductivity on the electric field due to the electroporation effect is modeled. The implemented model has been validated against a state of the art finite element solver, and the server has undergone a heavy load test to ensure reliability and to report execution times.

RESULTS

The electric field is rapidly computed for any electrode and tissue configuration, and alternative setups can be easily compared. The platform provides the same results as the state of the art finite element solver (Dice = 98.3 ± 0.4%). During the high load test, the server remained responsive. Simulations are computed in less than 2 min for simple cases consisting of two electrodes and take up to 40 min for complex scenarios consisting of 6 electrodes.

CONCLUSIONS

With this free platform we provide expert and non-expert electroporation users a way to rapidly model the electric field distribution for arbitrary electrode configurations.

Comparison of planned dose on different CT image sets to four-dimensional Monte Carlo dose recalculation using the patient's actual breathing trace for lung stereotactic body radiation therapy

PURPOSE

The need for four-dimensional (4D) treatment planning becomes indispensable when it comes to radiation therapy for moving tumors in the thoracic and abdominal regions. The primary purpose of this study is to combine the actual breathing trace during each individual treatment fraction with the Linac's log file information and Monte Carlo 4D dose calculations. We investigated this workflow on multiple computed tomography (CT) datasets in a clinical environment for stereotactic body radiation therapy (SBRT) treatment planning.

METHODS

We have developed a workflow, which allows us to recalculate absorbed dose to a 4DCT dataset using Monte Carlo calculation methods and accumulate all 4D doses in order to compare them to the planned dose using the Linac's log file, a 4DCT dataset, and the patient's actual breathing curve for each individual fraction. For five lung patients, three-dimensional-conformal radiation therapy (3D-CRT) and volumetric modulated arc treatment (VMAT) treatment plans were generated on four different CT image datasets: a native free-breathing 3DCT, an average intensity projection (AIP) and a maximum intensity projection (MIP) CT both obtained from a 4DCT, and a 3DCT with density overrides based on the 3DCT (DO). The Monte Carlo 4D dose has been calculated on each 4DCT phase using the Linac's log file and the patient's breathing trace as a surrogate for tumor motion and dose was accumulated to the gross tumor volume (GTV) at the 50% breathing phase (end of exhale) using deformable image registration.

RESULTS

Δ D 98 % and Δ D 2 % between 4D dose and planned dose differed largely for 3DCT-based planning and also for DO in three patients. Least dose differences between planned and recalculated dose have been found for AIP and MIP treatment planning which both tend to be superior to DO, but the results indicate a dependency on the breathing variability, tumor motion, and size. An interplay effect has not been observed in the small patient cohort.

CONCLUSIONS

We have developed a workflow which, to our best knowledge, is the first incorporation of the patient breathing trace over the course of all individual treatment fractions with the Linac's log file information and 4D Monte Carlo recalculations of the actual treated dose. Due to the small patient cohort, no clear recommendation on which CT can be used for SBRT treatment planning can be given, but the developed workflow, after adaption for clinical use, could be used to enhance a priori 4D Monte Carlo treatment planning in the future and help with the decision on which CT dataset treatment planning should be carried out.

A complete workflow for utilizing Monte Carlo toolkits in clinical cases for a double-scattering proton therapy system

The methods described in this paper allow end users to utilize Monte Carlo (MC) toolkits for patient‐specific dose simulation and perform analysis and plan comparisons for double‐scattering proton therapy systems. The authors aim to fill two aspects of this process previously not explicitly published. The first one addresses the modeling of field‐specific components in simulation space. Patient‐specific compensator and aperture models are exported from treatment planning system and converted to STL format using a combination of software tools including Matlab and Autodesk's Netfabb. They are then loaded into the MC geometry for simulation purpose. The second details a method for easily visualizing and comparing simulated doses with the dose calculated from the treatment planning system. This system is established by utilizing the open source software 3D Slicer. The methodology was demonstrated with a two‐field proton treatment plan on the IROC lung phantom. Profiles and two‐dimensional (2D) dose planes through the target isocenter were analyzed using our in‐house software tools. This present workflow and set of codes can be easily adapted by other groups for their clinical practice.

Moddicom: a complete and easily accessible library for prognostic evaluations relying on image features

Decision Support Systems (DSSs) are increasingly exploited in the area of prognostic evaluations. For predicting the effect of therapies on patients, the trend is now to use image features, i.e. information that can be automatically computed by considering images resulting by analysis. The DSSs application as predictive tools is particularly suitable for cancer treatment, given the peculiarities of the disease -which is highly localised and lead to significant social costs- and the large number of images that are available for each patient. At the state of the art, there exists tools that allow to handle image features for prognostic evaluations, but they are not designed for medical experts. They require either a strong engineering or computer science background since they do not integrate all the required functions, such as image retrieval and storage. In this paper we fill this gap by proposing Moddicom, a user-friendly complete library specifically designed to be exploited by physicians. A preliminary experimental analysis, performed by a medical expert that used the tool, demonstrates the efficiency and the effectiveness of Moddicom.

Data collection of patient outcomes: one institution's experience

Patient- and provider-reported outcomes are recognized as important in evaluating quality of care, guiding health care policy, comparative effectiveness research, and decision-making in radiation oncology. Combining patient and provider outcome data with a detailed description of disease and therapy is the basis for these analyses. We report on the combination of technical solutions and clinical process changes at our institution that were used in the collection and dissemination of this data. This initiative has resulted in the collection of treatment data for 23 541 patients, 20 465 patients with provider-based adverse event records, and patient-reported outcome surveys submitted by 5622 patients. All of the data is made accessible using a self-service web-based tool.

Changes in Gross Tumor Volume and Organ Motion Analysis During Neoadjuvant Radiochemotherapy in Patients With Locally Advanced Pancreatic Cancer Using an In-House Analysis System

BACKGROUND AND PURPOSE

During radiation treatment, movement of the target and organs at risks as well as tumor response can significantly influence dose distribution. This is highly relevant in patients with pancreatic cancer, where organs at risk lie in close proximity to the target.

MATERIAL AND METHODS

Data sets of 10 patients with locally advanced pancreatic cancer were evaluated. Gross tumor volume deformation was analyzed. Dose changes to organs at risk were determined with focus on kidneys both without adaptive radiotherapy compensation and with replanning based on weekly acquired computed tomography scans.

RESULTS

During irradiation, gross tumor volume changes between 0% and 26% and moves within a radius of 5 to 16 mm. Required maximal dose to organs at risk for kidneys can be met with the current practice of matching computed tomography scans during treatment and adjusting patient position accordingly. Comparison of the mean doses and V15, V20 volumes demonstrated that weekly replanning could bring a significant dose sparing of the left kidney.

CONCLUSION

Manual matching with focus on bony structures can lead to overall acceptable positioning of patients during treatment. Thus, tolerance doses of organs at risk, such as the kidneys, can be met. With adequate margins, normal tissue constraints to organs at risk can be kept as well. Adaptive radiotherapy approaches (in this case with weekly rescanning) reduced dose to organs at risk, which may be especially important for hypofractionated approaches.

γ+ index: A new evaluation parameter for quantitative quality assurance

PURPOSE

The accuracy of dose delivery and the evaluation of differences between calculated and delivered dose distributions, has been studied by several groups. The aim of this investigation is to extend the gamma index by including radiobiological information and to propose a new index that we will here forth refer to as the gamma plus (γ+). Furthermore, to validate the robustness of this new index in performing a quality control analysis of an IMRT treatment plan using pure radiobiological measures such as the biologically effective uniform dose (D) and complication-free tumor control probability (P+).

MATERIAL AND METHODS

A new quality assurance index, the (γ+), is proposed based on the theoretical concept of gamma index presented by Low et al. (1998). In this study, the dose difference, including the radiobiological dose information (biological effective dose, BED) is used instead of just the physical dose difference when performing the γ+ calculation. An in-house software was developed to compare different dose distributions based on the γ+ concept. A test pattern for a two-dimensional dose comparison was built using the in-house software platform. The γ+ index was tested using planar dose distributions (exported from the treatment planning system) and delivered (film) dose distributions acquired in a solid water phantom using a test pattern and a theoretical clinical case. Furthermore, a lung cancer case for a patient treated with IMRT was also selected for the analysis. The respective planar dose distributions from the treatment plan and the film were compared based on the γ+ index and were evaluated using the radiobiological measures of P+ and D.

RESULTS

The results for the test pattern analysis indicate that the γ+ index distributions differ from those of the gamma index since the former considers radiobiological parameters that may affect treatment outcome. For the theoretical clinical case, it is observed that the γ+ index varies for different treatment parameters (e.g. dose per fraction). The dose area histogram (DAH) from the plan and film dose distributions are associated with P+ values of 50.8% and 49.0%, for a D to the target of 54.0 Gy and 53.3 Gy, respectively.

CONCLUSION

The γ+ index shows advantageous properties in the quantitative evaluation of dose delivery and quality control of IMRT treatments because it includes information about the expected responses and radiobiological doses of the individual tissues.

A simple versatile solution for collecting multidimensional clinical data based on the CakePHP web application framework

Clinical trials aiming for regulatory approval of a therapeutic agent must be conducted according to Good Clinical Practice (GCP). Clinical Data Management Systems (CDMS) are specialized software solutions geared toward GCP-trials. They are however less suited for data management in small non-GCP research projects. For use in researcher-initiated non-GCP studies, we developed a client-server database application based on the public domain CakePHP framework. The underlying MySQL database uses a simple data model based on only five data tables. The graphical user interface can be run in any web browser inside the hospital network. Data are validated upon entry. Data contained in external database systems can be imported interactively. Data are automatically anonymized on import, and the key lists identifying the subjects being logged to a restricted part of the database. Data analysis is performed by separate statistics and analysis software connecting to the database via a generic Open Database Connectivity (ODBC) interface. Since its first pilot implementation in 2011, the solution has been applied to seven different clinical research projects covering different clinical problems in different organ systems such as cancer of the thyroid and the prostate glands. This paper shows how the adoption of a generic web application framework is a feasible, flexible, low-cost, and user-friendly way of managing multidimensional research data in researcher-initiated non-GCP clinical projects.

Development and validation of automatic tools for interactive recurrence analysis in radiation therapy: optimization of treatment algorithms for locally advanced pancreatic cancer

BACKGROUND

In radiation oncology recurrence analysis is an important part in the evaluation process and clinical quality assurance of treatment concepts. With the example of 9 patients with locally advanced pancreatic cancer we developed and validated interactive analysis tools to support the evaluation workflow.

METHODS

After an automatic registration of the radiation planning CTs with the follow-up images, the recurrence volumes are segmented manually. Based on these volumes the DVH (dose volume histogram) statistic is calculated, followed by the determination of the dose applied to the region of recurrence and the distance between the boost and recurrence volume. We calculated the percentage of the recurrence volume within the 80%-isodose volume and compared it to the location of the recurrence within the boost volume, boost + 1 cm, boost + 1.5 cm and boost + 2 cm volumes.

RESULTS

Recurrence analysis of 9 patients demonstrated that all recurrences except one occurred within the defined GTV/boost volume; one recurrence developed beyond the field border/outfield. With the defined distance volumes in relation to the recurrences, we could show that 7 recurrent lesions were within the 2 cm radius of the primary tumor. Two large recurrences extended beyond the 2 cm, however, this might be due to very rapid growth and/or late detection of the tumor progression.

CONCLUSION

The main goal of using automatic analysis tools is to reduce time and effort conducting clinical analyses. We showed a first approach and use of a semi-automated workflow for recurrence analysis, which will be continuously optimized. In conclusion, despite the limitations of the automatic calculations we contributed to in-house optimization of subsequent study concepts based on an improved and validated target volume definition.