Treatment verification in high dose rate brachytherapy using a realistic 3D printed head phantom and an imaging panel

PURPOSE

Even though High Dose Rate (HDR) brachytherapy has good treatment outcomes in different treatment sites, treatment verification is far from widely implemented because of a lack of easily available solutions. Previously it has been shown that an imaging panel (IP) near the patient can be used to determine treatment parameters such as the dwell time and source positions in a single material pelvic phantom. In this study we will use a heterogeneous head phantom to test this IP approach, and simulate common treatment errors to assess the sensitivity and specificity of the error-detecting capabilities of the IP.

METHODS AND MATERIALS

A heterogeneous head-phantom consisting of soft tissue and bone equivalent materials was 3D-printed to simulate a base of tongue treatment. An High Dose Rate treatment plan with 3 different catheters was used to simulate a treatment delivery, using dwell times ranging from 0.3 s to 4 s and inter-dwell distances of 2 mm. The IP was used to measure dwell times, positions and detect simulated errors. Measured dwell times and positions were used to calculate the delivered dose.

RESULTS

Dwell times could be determined within 0.1 s. Source positions were measured with submillimeter accuracy in the plane of the IP, and average distance accuracy of 1.7 mm in three dimensions. All simulated treatment errors (catheter swap, catheter shift, afterloader errors) were detected. Dose calculations show slightly different distributions with the measured dwell positions and dwell times (gamma pass rate for 1 mm/1% of 96.5%).

CONCLUSIONS

Using an IP, it was possible to verify the treatment in a realistic heterogeneous phantom and detect certain treatment errors.

MaxiCalc: A tool for online dosimetric evaluation of source-tracking based treatment verification in HDR brachytherapy

PURPOSE

Source tracking is becoming a more widely used approach in HDR brachytherapy treatment verification. While it provides a sensitive method to detect deviations from the treatment plan during delivery, it does not show the clinical significance of any detected changes. By incorporating a tool that calculates volumetric doses and DVH indices from measurements, source tracking systems can be expanded to assess dosimetric significance of any deviations from the plan.

METHODS

The source tracking dose calculation tool, MaxiCalc, was developed in MATLAB. Validation was performed by comparing doses and DVH indices calculated in MaxiCalc to those calculated by the clinical TPS, for several test plans and 10 clinical plans. Clinical implementation was demonstrated by calculating volumetric doses from a clinical source tracking event.

RESULTS

MaxiCalc showed excellent agreement with the clinical TPS for point and volumetric doses (mean difference < 0.01% and 0.1% respectively). MaxiCalc calculates dosimetrically equivalent plans to the TPS with agreement < 0.3% for all DVH indices except PTV V200%. Small differences seen for the clinical source tracking event were consistent with the known tracking uncertainties enabling them to be quantified for clinical decision making. Calculations are fast, enabling real-time use.

CONCLUSIONS

MaxiCalc is an independent tool that calculates doses and DVH indices from dwells measured with any clinical HDR brachytherapy source tracking system. This extends the capabilities of source tracking systems from determining discrepancies in positions or times during delivery to assessing the dosimetric impact of any detected deviations, allowing for more comprehensive treatment verification and evaluation.

Simple template-based optimization for pediatric total lymphoid irradiation (TLI) radiotherapy treatments

Total lymphoid irradiation (TLI) is used in the management of pediatric allogeneic hematopoietic stem cell transplantation (HSCT. This work aims to simplify the treatment planning process for TLI via a proposed template using the volumetric modulated arc therapy (VMAT) technique. Fifteen pediatric patients were planned, prescribed to 8 Gy in 4 fractions. Cost functions included in the template were the ones for the planning target volume (PTV), and conformality cost function (CCF) for the rest of the patient's volume. Conformity index (CI), homogeneity index (HI), conformation number (CN), gradient index (GI), integral dose, and doses to the organs at risk achieved with the template were reported. Cost function influence over various indexes was studied by Wilcoxon signed ranks test. Same 15 patients were planned with 3-dimensional conventional radiotherapy (3D-CRT) technique for comparison. Mean CI and HI were 1.33 and 0.13, respectively, which indicates good dose conformation and homogeneity. Mean CN and GI values were 0.69 and 4.51, respectively. Mean PTV coverage was reached (V_100% > 95%). No correlation between the CCF and indexes values was found (p > 0.05). Doses to organs at risk (OARs) were as low as possible without losing PTV coverage. VMAT plan showed higher levels of conformation and similar homogeneity as 3D-CRT plans. Doses to OARs were inferior with VMAT except for the right kidney. The proposed template simplifies the planning of TLI treatments, and it is able to create acceptable plans with little modification in order to reduce doses to certain organs like the kidneys or the heart. VMAT technique showed higher conformation and lower doses to OAR compared to 3D-CRT.

Identification of treatment error types for lung cancer patients using convolutional neural networks and EPID dosimetry

BACKGROUND/PURPOSE

Electronic portal imaging device (EPID) dosimetry aims to detect treatment errors, potentially leading to treatment adaptation. Clinically used threshold classification methods for detecting errors lead to loss of information (from multi-dimensional EPID data to a few numbers) and cannot be used for identifying causes of errors. Advanced classification methods, such as deep learning, can use all available information. In this study, convolutional neural networks (CNNs) were trained to detect and identify error type and magnitude of simulated treatment errors in lung cancer patients. The purpose of this simulation study is to provide a proof-of-concept of CNNs for error identification using EPID dosimetry in an in vivo scenario.

MATERIALS AND METHODS

Clinically realistic ranges of anatomical changes, positioning errors and mechanical errors were simulated for lung cancer patients. Predicted portal dose images (PDIs) containing errors were compared to error-free PDIs using the widely used gamma analysis. CNNs were trained to classify errors using 2D gamma maps. Three classification levels were assessed: Level 1 (main error type, e.g., anatomical change), Level 2 (error subtype, e.g., tumor regression) and Level 3 (error magnitude, e.g., >50% tumor regression).

RESULTS

CNNs showed good performance for all classification levels (training/test accuracy 99.5%/96.1%, 92.5%/86.8%, 82.0%/72.9%). For Level 3, overfitting became more apparent.

CONCLUSION

This simulation study indicates that deep learning is a promising powerful tool for identifying types and magnitude of treatment errors with EPID dosimetry, providing additional information not currently available from EPID dosimetry. This is a first step towards rapid, automated models for identification of treatment errors using EPID dosimetry.

In vivo dosimetry in brachytherapy: Requirements and future directions for research, development, and clinical practice

Brachytherapy can deliver high doses to the target while sparing healthy tissues due to its steep dose gradient leading to excellent clinical outcome. Treatment accuracy depends on several manual steps making brachytherapy susceptible to operational mistakes. Currently, treatment delivery verification is not routinely available and has led, in some cases, to systematic errors going unnoticed for years. The brachytherapy community promoted developments in in vivo dosimetry (IVD) through research groups and small companies. Although very few of the systems have been used clinically, it was demonstrated that the likelihood of detecting deviations from the treatment plan increases significantly with time-resolved methods. Time–resolved methods could interrupt a treatment avoiding gross errors which is not possible with time-integrated dosimetry. In addition, lower experimental uncertainties can be achieved by using source-tracking instead of direct dose measurements. However, the detector position in relation to the patient anatomy remains a main source of uncertainty. The next steps towards clinical implementation will require clinical trials and systematic reporting of errors and near-misses. It is of utmost importance for each IVD system that its sensitivity to different types of errors is well understood, so that end-users can select the most suitable method for their needs. This report aims to formulate requirements for the stakeholders (clinics, vendors, and researchers) to facilitate increased clinical use of IVD in brachytherapy. The report focuses on high dose-rate IVD in brachytherapy providing an overview and outlining the need for further development and research.

4D in vivo dose verification for real-time tumor tracking treatments using EPID dosimetry

The use of sophisticated techniques such as gating and tracking treatments requires additional quality assurance to mitigate increased patient risks. To address this need, we have developed and validated an in vivo method of dose delivery verification for real-time aperture tracking techniques, using an electronic portal imaging device (EPID)-based, on-treatment patient dose reconstruction and a dynamic anthropomorphic phantom. Using 4DCT scan of the phantom, ten individual treatment plans were created, 1 for each of the 10 separate phases of the respiratory cycle. The 10 MLC apertures were combined into a single dynamic intensity-modulated radiation therapy (IMRT) plan that tracked the tumor motion. The tumor motion and linac delivery were synchronized using an RPM system (Varian Medical Systems) in gating mode with a custom breathing trace. On-treatment EPID frames were captured using a data-acquisition computer with a dedicated frame-grabber. Our in-house EPID-based in vivo dose reconstruction model was modified to reconstruct the 4D accumulated dose distribution for a dynamic MLC (DMLC) tracking plan using the 10-phase 4DCT dataset. Dose estimation accuracy was assessed for the DMLC tracking plan and a single-phase (50% phase) static tumor plan, represented a static field test to verify baseline accuracy. The 3%/3 mm chi-comparison between the EPID-based dose reconstruction for the static tumor delivery and the TPS dose calculation for the static plan resulted in 100% pass rate for planning target volume (PTV) voxels while the mean percentage dose difference was 0.6%. Comparing the EPID-based dose reconstruction for the DMLC tracking to the TPS calculation for the static plan gave a 3%/3 mm chi pass rate of 99.3% for PTV voxels and a mean percentage dose difference of 1.1%. While further work is required to assess the accuracy of this approach in more clinically relevant situations, we have established clinical feasibility and baseline accuracy of using the transmission EPID-based, in vivo patient dose verification for MLC-tracking treatments.

Limitations in learning: How treatment verifications fail and what to do about it?

PURPOSE

The purposes of this study were: to provide dialog on why classic incident learning systems have been insufficient for patient safety improvements, discuss failures in treatment verification, and to provide context to the reasons and lessons that can be learned from these failures.

METHODS AND MATERIALS

Historically, incident learning in brachytherapy is performed via database mining which might include reading of event reports and incidents followed by incorporating verification procedures to prevent similar incidents. A description of both classic event reporting databases and current incident learning and reporting systems is given. Real examples of treatment failures based on firsthand knowledge are presented to evaluate the effectiveness of verification. These failures will be described and analyzed by outlining potential pitfalls and problems based on firsthand knowledge.

RESULTS

Databases and incident learning systems can be limited in value and fail to provide enough detail for physicists seeking process improvement. Four examples of treatment verification failures experienced firsthand by experienced brachytherapy physicists are described. These include both underverification and oververification of various treatment processes.

CONCLUSIONS

Database mining is an insufficient method to affect substantial improvements in the practice of brachytherapy. New incident learning systems are still immature and being tested. Instead, a new method of shared learning and implementation of changes must be created.

Dosimetric impact of intrafraction changes in MR-guided high-dose-rate (HDR) brachytherapy for prostate cancer

PURPOSE

To assess changes in implant and treatment volumes through the course of a prostate high-dose-rate brachytherapy procedure and their impact on plan quality metrics.

METHODS AND MATERIALS

Sixteen MRI-guided high-dose-rate procedures included a post-treatment MR (ptMR) immediately after treatment delivery (135 min between MR scans). Target and organs at risk (OARs) were contoured, and catheters were reconstructed. The delivered treatment plan was applied to the ptMR image set. Volumes and dosimetric parameters in the ptMR were evaluated and compared with the delivered plan using a paired two-tailed t-test with p < 0.05 considered statistically significant.

RESULTS

An average increase of 8.9% in prostate volume was observed for whole-gland treatments, resulting in reduction in coverage for both prostate and planning target volume, reflected in decreased V₁₀₀ (mean 3.3% and 4.6%, respectively, p < 0.05), and D₉₀ (mean 7.1% and 7.6%, respectively, of prescription dose, p < 0.05). There was no significant change in doses to OARs. For partial-gland treatments, there was an increase in planning target volume (9.1%), resulting in reduced coverage and D₉₀ (mean 3.6% and 12.4%, respectively, p < 0.05). A decrease in D_0.5cc for bladder (3%, p < 0.05) was observed, with no significant changes in dose to other OARs.

CONCLUSIONS

Volumetric changes were observed during the time between planning MR and ptMR. Nonetheless, treatment plans for both whole- and partial-gland therapies remained clinically acceptable. These results apply to clinical settings in which patients remain in the same position and under anesthesia during the entire treatment process.

Implementation and evaluation of a transit dosimetry system for treatment verification

PURPOSE

To evaluate a formalism for transit dosimetry using a phantom study and prospectively evaluate the protocol on a patient population undergoing 3D conformal radiotherapy.

METHODS

Amorphous silicon EPIDs were calibrated for dose and used to acquire images of delivered fields. The measured EPID dose map was back-projected using the planning CT images to calculate dose at pre-specified points within the patient using commercially available software, EPIgray (DOSIsoft, France). This software compared computed back-projected dose with treatment planning system dose. A series of tests were performed on solid water phantoms (linearity, field size effects, off-axis effects). 37 patients were enrolled in the prospective study.

RESULTS

The EPID dose response was stable and linear with dose. For all tested field sizes the agreement was good between EPID-derived and treatment planning system dose in the central axis, with performance stability up to a measured depth of 18cm (agreement within -0.5% at 10cm depth on the central axis and within -1.4% at 2cm off-axis). 126 transit images were analysed of 37 3D-conformal patients. Patient results demonstrated the potential of EPIgray with 91% of all delivered fields achieved the initial set tolerance level of ΔD of 0±5-cGy or %ΔD of 0±5%.

CONCLUSIONS

The in vivo dose verification method was simple to implement, with very few commissioning measurements needed. The system required no extra dose to the patient, and importantly was able to detect patient position errors that impacted on dose delivery in two of cases.

A comparison between radiation therapists and medical specialists in the use of kilovoltage cone-beam computed tomography scans for potential lung cancer radiotherapy target verification and adaptation

Target volume matching using cone-beam computed tomography (CBCT) is the preferred treatment verification method for lung cancer in many centers. However, radiation therapists (RTs) are trained in bony matching and not soft tissue matching. The purpose of this study was to determine whether RTs were equivalent to radiation oncologists (ROs) and radiologists (RDs) in alignment of the treatment CBCT with the gross tumor volume (GTV) defined at planning and in delineating the GTV on the treatment CBCT, as may be necessary for adaptive radiotherapy. In this study, 10 RTs, 1 RO, and 1 RD performed a manual tumor alignment and correction of the planning GTV to a treatment CBCT to generate an isocenter correction distance for 15 patient data sets. Participants also contoured the GTV on the same data sets. The isocenter correction distance and the contoured GTVs from the RTs were compared with the RD and RO. The mean difference in isocenter correction distances was 0.40cm between the RO and RD, 0.51cm between the RTs, and RO and 0.42cm between the RTs and RD. The 95% CIs were smaller than the equivalence limit of 0.5cm, indicating that the RTs were equivalent to the RO and RD. For GTV delineation comparisons, the RTs were not found to be equivalent to the RD or RO. The alignment of the planning defined GTV and treatment CBCT using soft tissue matching by the RTs has been shown to be equivalent to those by the RO and RD. However, tumor delineation by the RTs on the treatment CBCT was not equivalent to that of the RO and RD. Thus, it may be appropriate for RTs to undertake soft tissue alignment based on CBCT; however, further investigation may be necessary before RTs undertake delineation for adaptive radiotherapy purposes.