Lucas Persoon

Benefits of a clinical data warehouse with data mining tools to collect data for a radiotherapy trial.

INTRODUCTION Collecting trial data in a medical environment is at present mostly performed manually and therefore time-consuming, prone to errors and often incomplete with the complex data considered. Faster and more accurate methods are needed to improve the data quality and to shorten data collection times where information is often scattered over multiple data sources. The purpose of this study is to investigate the possible benefit of modern data warehouse technology in the radiation oncology field. MATERIAL AND METHODS In this study, a Computer Aided Theragnostics (CAT) data warehouse combined with automated tools for feature extraction was benchmarked against the regular manual data-collection processes. Two sets of clinical parameters were compiled for non-small cell lung cancer (NSCLC) and rectal cancer, using 27 patients per disease. Data collection times and inconsistencies were compared between the manual and the automated extraction method. RESULTS The average time per case to collect the NSCLC data manually was 10.4 ± 2.1 min and 4.3 ± 1.1 min when using the automated method (p<0.001). For rectal cancer, these times were 13.5 ± 4.1 and 6.8 ± 2.4 min, respectively (p<0.001). In 3.2% of the data collected for NSCLC and 5.3% for rectal cancer, there was a discrepancy between the manual and automated method. CONCLUSIONS Aggregating multiple data sources in a data warehouse combined with tools for extraction of relevant parameters is beneficial for data collection times and offers the ability to improve data quality. The initial investments in digitizing the data are expected to be compensated due to the flexibility of the data analysis. Furthermore, successive investigations can easily select trial candidates and extract new parameters from the existing databases.

First clinical results of adaptive radiotherapy based on 3D portal dosimetry for lung cancer patients with atelectasis treated with volumetric-modulated arc therapy (VMAT)

Abstract Atelectasis in lung cancer patients can change rapidly during a treatment course, which may displace the tumor/healthy tissues, or change tissue densities locally. This may result in differences between the planned and the actually delivered dose. With complex delivery techniques treatment verification is essential and inter-fractional adaptation may be necessary. We present the first clinical results of treatment adaptation based on an in-house developed three-dimensional (3D) portal dose measurement (PDM) system. Material and methods. A method was developed for 3D PDM combined with cone beam computed tomography (kV-CBCT) imaging. Lung cancer patients are monitored routinely with this imaging technique. During treatment, the first three fractions are analyzed with 3D PDM and weekly thereafter. The reconstructed measured dose is compared to the planned dose using dose-volume histograms and a γ evaluation. Patients having |γ|> 1 in more than 5% of the (primary tumor or organ at risk) volume were subjected to further analysis. In this study we show the PDM dose changes for five patients. Results. We detected relevant dose changes induced by changes in atelectasis in the presented cases. Two patients received two treatment adaptations after being detected with PDM confirmed by visual inspection of the kV-CBCTs, and in two other patients the radiation treatment plan was adapted once. In one case no dose delivery change was detected with PDM. Conclusion. The first clinical patients show that 3D PDM combined with kV-CBCT is a valuable quality assurance tool for detecting anatomical alterations and their dosimetric consequences during the course of radiotherapy. In our clinic, 3D PDM is fully automated for ease and speed of the procedure, and for minimization of human error. The technique is able to flag patients with suspected dose discrepancies for potential adaptation of the treatment plan.

Design of and technical challenges involved in a framework for multicentric radiotherapy treatment planning studies

This report introduces a framework for comparing radiotherapy treatment planning in multicentric in silico clinical trials. Quality assurance, data incompatibility, transfer and storage issues, and uniform analysis of results are discussed. The solutions that are given provide a useful guide for the set-up of future multicentric planning studies or public repositories of high quality data.

A fast three-dimensional gamma evaluation using a GPU utilizing texture memory for on-the-fly interpolations

PURPOSE A widely accepted method to quantify differences in dose distributions is the gamma (γ) evaluation. Currently, almost all γ implementations utilize the central processing unit (CPU). Recently, the graphics processing unit (GPU) has become a powerful platform for specific computing tasks. In this study, we describe the implementation of a 3D γ evaluation using a GPU to improve calculation time. METHODS The γ evaluation algorithm was implemented on an NVIDIA Tesla C2050 GPU using the compute unified device architecture (cuda). First, several cubic virtual phantoms were simulated. These phantoms were tested with varying dose cube sizes and set-ups, introducing artificial dose differences. Second, to show applicability in clinical practice, five patient cases have been evaluated using the 3D dose distribution from a treatment planning system as the reference and the delivered dose determined during treatment as the comparison. A calculation time comparison between the CPU and GPU was made with varying thread-block sizes including the option of using texture or global memory. RESULTS A GPU over CPU speed-up of 66 ± 12 was achieved for the virtual phantoms. For the patient cases, a speed-up of 57 ± 15 using the GPU was obtained. A thread-block size of 16 × 16 performed best in all cases. The use of texture memory improved the total calculation time, especially when interpolation was applied. Differences between the CPU and GPU γs were negligible. CONCLUSIONS The GPU and its features, such as texture memory, decreased the calculation time for γ evaluations considerably without loss of accuracy.

Interfractional trend analysis of dose differences based on 2D transit portal dosimetry

Dose delivery of a radiotherapy treatment can be influenced by a number of factors. It has been demonstrated that the electronic portal imaging device (EPID) is valuable for transit portal dosimetry verification. Patient related dose differences can emerge at any time during treatment and can be categorized in two types: (1) systematic-appearing repeatedly, (2) random-appearing sporadically during treatment. The aim of this study is to investigate how systematic and random information appears in 2D transit dose distributions measured in the EPID plane over the entire course of a treatment and how this information can be used to examine interfractional trends, building toward a methodology to support adaptive radiotherapy. To create a trend overview of the interfractional changes in transit dose, the predicted portal dose for the different beams is compared to a measured portal dose using a γ evaluation. For each beam of the delivered fraction, information is extracted from the γ images to differentiate systematic from random dose delivery errors. From the systematic differences of a fraction for a projected anatomical structures, several metrics are extracted like percentage pixels with |γ| > 1. We demonstrate for four example cases the trends and dose difference causes which can be detected with this method. Two sample prostate cases show the occurrence of a random and systematic difference and identify the organ that causes the difference. In a lung cancer case a trend is shown of a rapidly diminishing atelectasis (lung fluid) during the course of treatment, which was detected with this trend analysis method. The final example is a breast cancer case where we show the influence of set-up differences on the 2D transit dose. A method is presented based on 2D portal transit dosimetry to record dose changes throughout the course of treatment, and to allow trend analysis of dose discrepancies. We show in example cases that this method can identify the causes of dose delivery differences and that treatment adaptation can be triggered as a result. It provides an important element toward informed decision-making for adaptive radiotherapy.

Prediction of DVH parameter changes due to setup errors for breast cancer treatment based on 2D portal dosimetry.

Electronic portal imaging devices (EPIDs) are increasingly used for portal dosimetry applications. In our department, EPIDs are clinically used for two-dimensional (2D) transit dosimetry. Predicted and measured portal dose images are compared to detect dose delivery errors caused for instance by setup errors or organ motion. The aim of this work is to develop a model to predict dose-volume histogram (DVH) changes due to setup errors during breast cancer treatment using 2D transit dosimetry. First, correlations between DVH parameter changes and 2D gamma parameters are investigated for different simulated setup errors, which are described by a binomial logistic regression model. The model calculates the probability that a DVH parameter changes more than a specific tolerance level and uses several gamma evaluation parameters for the planning target volume (PTV) projection in the EPID plane as input. Second, the predictive model is applied to clinically measured portal images. Predicted DVH parameter changes are compared to calculated DVH parameter changes using the measured setup error resulting from a dosimetric registration procedure. Statistical accuracy is investigated by using receiver operating characteristic (ROC) curves and values for the area under the curve (AUC), sensitivity, specificity, positive and negative predictive values. Changes in the mean PTV dose larger than 5%, and changes in V90 and V95 larger than 10% are accurately predicted based on a set of 2D gamma parameters. Most pronounced changes in the three DVH parameters are found for setup errors in the lateral-medial direction. AUC, sensitivity, specificity, and negative predictive values were between 85% and 100% while the positive predictive values were lower but still higher than 54%. Clinical predictive value is decreased due to the occurrence of patient rotations or breast deformations during treatment, but the overall reliability of the predictive model remains high. Based on our predictive model, 2D transit dosimetry measurements can now directly be translated in clinically more relevant DVH parameter changes for the PTV during conventional breast treatment. In this way, the possibility to design decision protocols based on extracted DVH changes is created instead of undertaking elaborate actions such as repeated treatment planning or 3D dose reconstruction for a large group of patients.

Is integrated transit planar portal dosimetry able to detect geometric changes in lung cancer patients treated with volumetric modulated arc therapy

ABSTRACT Background. Geometric changes are frequent during the course of treatment of lung cancer patients. This may potentially result in deviations between the planned and actual delivered dose. Electronic portal imaging device (EPID)-based integrated transit planar portal dosimetry (ITPD) is a fast method for absolute in-treatment dose verification. The aim of this study was to investigate if ITPD could detect geometric changes in lung cancer patients. Materials and methods. A total of 460 patients treated with volumetric modulated arc therapy (VMAT) following daily cone beam computed tomography (CT)-based setup were visually inspected for geometrical changes on a daily basis. Forty-six patients were subject to changes and had a re-CT and an adaptive treatment plan. The reasons for adaptation were: change in atelectasis (n = 18), tumor regression (n = 9), change in pleural effusion (n = 8) or other causes (n = 11). The ITPDs were calculated on both the initial planning CT and the re-CT and compared with a global gamma (γ) evaluation (criteria: 3%\3mm). A treatment fraction failed when the percentage of pixels failing in the radiation fields exceeded 10%. Dose-volume histograms (DVHs) were compared between the initial plan versus the plan re-calculated on the re-CT. Results. The ITPD threshold method detected 76% of the changes in atelectasis, while only 50% of the tumor regression cases and 42% of the pleural effusion cases were detected. Only 10% of the cases adapted for other reasons were detected with ITPD. The method has a 17% false-positive rate. No significant correlations were found between changes in DVH metrics and γ fail-rates. Conclusions. This study showed that most cases with geometric changes caused by atelectasis could be captured by ITPD, however for other causes ITPD is not sensitive enough to detect the clinically relevant changes and no predictive power of ITPD was found.

Weekly kilovoltage cone-beam computed tomography for detection of dose discrepancies during (chemo)radiotherapy for head and neck cancer.

ABSTRACT Background. Use of highly conformal radiotherapy in patients with head and neck carcinoma may lead to under-/overdosage of gross target volume (GTV) and organs at risk (OAR) due to changes in patients’ anatomy. A method to achieve more effective radiation treatment combined with less toxicity is dose-guided radiotherapy (DGRT). The aim of this study was to evaluate discrepancies between planned and actually delivered radiation dose in head and neck patients and to identify predictive factors. Methods. In this retrospective analysis, 20 patients with cT2-4 N0-3 M0 carcinoma originating from oropharynx, oral cavity, larynx and hypopharynx (Cohort 1), and seven patients with cT1-4 N0-3 M0 nasopharyngeal carcinoma (Cohort 2) treated with primary (chemo)radiotherapy and undergoing weekly kV-CBCT scans were included. Radiation dose was recalculated on 184 kV-CBCT images, which was quantified by D95% (GTV), Dmean (parotid and submandibular glands) and D2% (spinal cord). Predictive factors investigated for changes in these dose metrics were: gender, age, cT/N-stage, tumor grade, HPV-status, systemic therapy, body mass index at start of treatment, weight loss and volume change over the duration of the radiotherapy. Results. There was no significant difference between the planned and delivered dose for GTV and OARs of Week 1 to subsequent weeks for Cohort 1. In Cohort 2, actually delivered Dmean to parotid glands was significant higher than planned dose (1.1 Gy, p = 0.002). No clinically relevant correlations between dose changes and predictive factors were found. Conclusion. Weekly dose calculations do not seem to improve dose delivery for patients with tumors of the oral cavity, oropharynx, larynx and hypopharynx. In patients with nasopharyngeal carcinoma, however, mid-treatment imaging may facilitate DGRT.

Time-Resolved Versus Integrated Transit Planar Dosimetry for Volumetric Modulated Arc Therapy: Patient-Specific Dose Differences During Treatment, a Proof of Principle

Purpose: It is desirable that dosimetric deviations during radiation treatments are detected. Integrated transit planar dosimetry is commonly used to evaluate external beam treatments such as volumetric-modulated arc therapy. This work focuses on patient geometry changes which result in differences between the planned and the delivered radiation dose. Integrated transit planar dosimetry will average out some deviations. Novel time-resolved transit planar dosimetry compares the delivered dose of volumetric-modulated arc therapy to the planned dose at various time points. Four patient cases are shown where time-resolved transit planar dosimetry detects patient geometry changes during treatment. Methods: A control point to control point comparison between the planned dose and the treatment dose of volumetric-modulated arc therapy beams is calculated using the planning computed tomography and the kV cone-beam computed tomography of the day and evaluated with a time-resolved γ function. Results were computed for 4 patients treated with volumetric-modulated arc therapy, each showing an anatomical change: pleural effusion, rectal gas pockets, and tumor regression. Results: In all cases, the geometrical change was detected by time-resolved transit planar dosimetry, whereas integrated transit planar dosimetry showed minor or no indication of the dose discrepancy. Both tumor regression cases were detected earlier in the treatment with time-resolved planar dosimetry in comparison to integrated transit planar dosimetry. The pleural effusion and the gas pocket were detected exclusively with time-resolved transit planar dosimetry. Conclusions: Clinical cases were presented in this proof-of-principle study in which integrated transit planar dosimetry did not detect dosimetrically relevant deviations to the same extent time-resolved transit planar dosimetry was able to. Time-resolved transit planar dosimetry also provides results that can be presented as a function of arc delivery angle allowing easier interpretation compared to integrated transit planar dosimetry.

Time-resolved versus time-integrated portal dosimetry: the role of an object's position with respect to the isocenter in volumetric modulated arc therapy.

The aim of this work is to compare time-resolved (TR) and time-integrated (TI) portal dosimetry, focussing on the role of an objects position with respect to the isocenter in volumetric modulated arc therapy (VMAT). Portal dose images (PDIs) are simulated and measured for different cases: a sphere (1), a bovine bone (2) and a patient geometry (3). For the simulated case (1) and the experimental case (2), several transformations are applied at different off-axis positions. In the patient case (3), three simple plans with different isocenters are created and pleural effusion is simulated in the patient. The PDIs before and after the sphere transformations, as well as the PDIs with and without simulated pleural effusion, are compared using a TI and TR gamma analysis. In addition, the performance of the TI and TR gamma analyses for the detection of real geometric changes in patients treated with clinical plans is investigated and a correlation analysis is performed between gamma fail rates and differences in dose volume histogram (DVH) metrics. The TI gamma analysis can show large differences in gamma fail rates for the same transformation at different off-axis positions (or for different plan isocenters). The TR gamma analysis, however, shows consistent gamma fail rates. For the detection of real geometric changes in patients treated with clinical plans, the TR gamma analysis has a higher sensitivity than the TI gamma analysis. However, the specificity for the TR gamma analysis is lower than for the TI gamma analysis. Both the TI and TR gamma fail rates show no correlation with changes in DVH metrics. This work shows that TR portal dosimetry is fundamentally superior to TI portal dosimetry, because it removes the strong dependence of the gamma fail rate on the off-axis position/plan isocenter. However, for 2D TR portal dosimetry, it is still difficult to interpret gamma fail rates in terms of changes in DVH metrics for patients treated with VMAT.