Performance of an enhanced afterloader with electromagnetic tracking capabilities for channel reconstruction and error detection

A comprehensive quality assurance protocol for electromagnetic tracking in brachytherapy

BACKGROUND

Electromagnetic tracking (EMT) systems have proven to be a valuable source of information regarding the location and geometry of applicators in patients undergoing brachytherapy (BT). As an important element of an enhanced and individualized pre-treatment verification, EMT can play a pivotal role in detecting treatment errors and uncertainties to increase patient safety.

PURPOSE

The purpose of this study is two-fold: to design, develop and test a dedicated measurement protocol for the use of EMT-enabled afterloaders in BT and to collect and compare the data acquired from three different radiation oncology centers in different clinical environments.

METHODS

A novel quality assurance (QA) phantom composed of a scaffold with supports to fix the field generator, different BT applicators, and reference sensors (sensor verification tools) was used to assess the precision (jitter error) and accuracy (relative distance errors and target registration error) of the EMT sensor integrated into an afterloader prototype. Measurements were repeated in different environments where EMT measurements are likely to be performed, namely an electromagnetically clean laboratory, a BT suite, an operating room, and, if available, a CT suite and an MRI suite dedicated to BT.

RESULTS

The mean positional jitter was consistently under 0.1 mm across all measurement points, with a slight trend of increased jitter at greater distances from the field generator. The mean variability of sensor positioning in the tested tandem and ring gynecological applicator was also below 0.1 mm. The tracking accuracy close to the center of the measurement volume was higher than at its edges. The relative distance error at the center was 0.2-0.3 mm with maximum values reaching 1.2-1.8 mm, but up to 5.5 mm for measurement points close to the edges. In general, similar accuracy results were obtained in the clinical environments and in all investigated institutions (median distance error 0.1-0.4 mm, maximum error 1.0-2.0 mm), however, errors were found to be larger in the CT suite (median distance error up to 1.0 mm, maximum error up to 3.6 mm).

CONCLUSION

The presented quality assessment protocol for EMT systems in BT has demonstrated that EMT offers a high-accuracy determination of the applicator/implant geometry even in clinical environments. In addition to that, it has provided valuable insights into the performance of EMT-enabled afterloaders across different radiation oncology centers.

Accuracy of an electromagnetic tracking enabled afterloader based on the automated registration with CT phantom images

BACKGROUND

Electromagnetic tracking (EMT) has been researched for brachytherapy applications, showing a great potential for automating implant reconstruction, and overcoming image-based limitations such as contrast and spatial resolution. One of the challenges of this technology is that it does not intrinsically share the same reference frame as the patient's medical imaging.

PURPOSE

To present a novel phantom that can be used for a comprehensive quality assurance (QA) program of brachytherapy EMT systems and use this phantom to validate a novel applicator-based registration method of EMT and image reference frames for gynecological (GYN) interstitial brachytherapy.

MATERIALS AND METHODS

Eleven 6F-catheters (20 cm long), one 6F round tip catheter (29.4 cm long) and a tandem and ring gynecological applicator (Elekta, CT/MR 60°, 40 mm long tandem, 30 mm diameter ring) were placed in a rigid custom-made phantom (Elekta Brachytherapy, Veenendaal, The Netherlands) to reconstruct their geometry using a five-degree of freedom EMT sensor attached to an afterloader's check cable. All EMT reconstructions were done in three different environments: disturbance free (no metal nearby), computed tomography (CT)-on-rails brachytherapy suite and magnetic resonance imaging (MRI) brachytherapy suite. Implants were placed parallel to a magnetic field generatorand were reconstructed using two different acquisition methods: step-and-record and continuous motion. In all cases, the acquisition is performed at a rate of approximately 40 Hz. A CT scan of the phantom inside a water cube was obtained. In the treatment planning system (TPS), all catheters in the CT images were manually reconstructed and the applicator reconstruction was achieved by manually placing its solid 3D model, found in the applicator library of the TPS. The Iterative Closest Point and the Coherent Point Drift algorithms were used, initialized with four known points, to register both EMT and CT scan reference frames using corresponding points from the EMT and CT based reconstructions of the phantom, following three approaches: one gynecological applicator, four interstitial catheters inside four calibration plates having an S-shaped path, and four 5 mm diameter ceramic marbles found in each of the four calibration plates. Once registered, the registration error (perpendicular distance) was computed.

RESULTS

The absolute median deviation from the expected value for EMT measurements in the disturbance free environment, CT-on-rails brachytherapy suite, and MRI-brachytherapy suite are 0.41, 0.23, and 0.31 mm, respectively, while for the CT scan it is 0.18 mm. These values significantly lie below the sensor's expected accuracy of 0.70 mm (p < 0.001), suggesting that the environment did not have a significant impact on the measurements, given that care is taken in the immediate surroundings. In all three environments, the two acquisitions and three registration approaches have mean and median registration errors that lie at or below 1 mm, which is lower than the clinical acceptable threshold of 2 mm.

CONCLUSIONS

The novel phantom allowed to successfully evaluate the accuracy of EMT-based reconstructions of catheters and a GYN tandem and ring applicator in different clinical environments. A registration method based only on the applicator geometry, reconstructed withan EMT sensor and the TPS solid applicator library, was validated and shows clinically acceptable accuracy, comparable to CT-based reconstruction but within a few minutes. Since the applicator is also visible in MRI, this method could potentially be used in clinics in an EMT-MR interstitial GYN brachytherapy workflow.

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.

Brachytherapy evolution as seen today

While brachytherapy is the oldest form of radiation therapy, it is also a very exciting field from both physics and clinical perspectives. From the physics standpoint, brachytherapy dosimetry is largely being governed by the inverse-square law, leading to an unparalleled dose deposition kernel (dose emitted by a seed or single dwell position), even compared to proton or heavy-ion beamlets. There is slightly more dose beyond the central deposition point, but comparatively very little prior to it, that is, little or no entrance dose! It is easy to sum multiple dwell positions that cover a tumor, and the intensity can be modulated quite effectively using dwell times. From a clinical perspective, what sets brachytherapy apart from other intraoperative modalities (e.g., laser, radiofrequency, cryogenic) is our ability to precisely calculate the energy deposited across the relevant patient geometry, anticipate the effect from known dose-outcome relationships, and deliver that energy with exquisite control and selectively to the target volume while sparing organs at risks. This targeting ability has improved substantially over the last two decades. It is built upon key foundational elements, many of which stem from the research and development within our medical physics community. This article provides an overview of these elements that combine to make brachytherapy a successful and developing radiotherapy modality.

Influence and compensation of patient motion in electromagnetic tracking based quality assurance in interstitial brachytherapy of the breast

PURPOSE

Electromagnetic tracking (EMT) is a versatile and viable technique for various quality assurance (QA) tasks in interstitial brachytherapy (iBT). As the duration of EMT measurements in iBT is on the order of minutes, they can be strongly affected by patient motion, especially breathing, which gives rise to motion artefacts. Since the centrepiece of EMT related QA in iBT is to assess the geometry of the iBT implant or applicator, the absence of adequate motion compensation techniques could impede the use of EMT for QA purposes. A common way to compensate for this is to reference the data to either external or internal reference sensors (ERS, IRS) which are fixated on the patient's body or inside the applicator and therefore move with the patient. The purpose of the presented study is to provide a quantitative and in-depth analysis on the use of reference sensors for motion compensation.

METHODS

First, the need for adequate motion compensation is identified both qualitatively and quantitatively using a phantom subjected to simulated breathing motion. An evaluation routine is developed to assess the influence of motion compensation using reference sensors on the acquired EMT data. The evaluation metric is based on the observed displacement of the EMT sensor from its mean position while dwelling at a dwell position (DP) for a dwell time of 1 s. After that the routine is applied to a cohort of 54 breast cancer patients treated with iBT and the quality of an ERS based compensation approach is assessed. In a subgroup of four patients, an IRS is inserted into the iBT implant and IRS based compensation is compared to the ERS based approach. Moreover, a correlation analysis of the ERS and IRS approach is performed, also including respiratory signals derived from the trajectories of the different reference sensors.

RESULTS

It was found that motion compensation with ERS effectively reduced the mean sensor displacement per DP to median values as low as 0.11 mm in both phantom and patient measurements, which is below the precision of the EMT system (0.48 mm). Compensation using the IRS yielded comparable results and was as good as compensation with ERS. The results obtained from both approaches showed a strong correlation. Also the respiratory signals calculated from the different reference sensors were well correlated in most cases.

CONCLUSION

These results indicate that motion compensation with ERS can effectively remove motion artefacts in EMT data. While compensation with an IRS leads to comparable results, the IRS occupies one catheter whose geometry hence cannot be assessed. The use of ERS has proven to be both effective and practical in clinical routine. This article is protected by copyright. All rights reserved.

The Challenges Facing Deep Learning based Catheter Localization for Ultrasound Guided High-Dose-Rate Prostate Brachytherapy

BACKGROUND

Automated catheter localization for ultrasound guided high-dose-rate prostate brachytherapy faces challenges relating to imaging noise and artifacts. To date, catheter reconstruction during the clinical procedure is performed manually. Deep learning has been successfully applied to a wide variety of complex tasks and has the potential to tackle the unique challenges associated with multiple catheter localization on ultrasound. Such a task is well suited for automation, with the potential to improve productivity and reliability.

PURPOSE

We developed a deep learning model for automated catheter reconstruction and investigated potential factors influencing model performance. The model was designed to integrate into a clinical workflow, with a proposed reconstruction confidence metric to aid in planner verification.

METHODS

Datasets from 242 patients treated from 2016 to 2020 were collected retrospectively. The anonymized dataset comprises of 31,000 transverse images reconstructed from 3D sagittal ultrasound acquisitions and 3,500 implanted catheters manually localized by the planner. Each catheter was retrospectively ranked based on the severity of imaging artifacts affecting reconstruction difficulty. The U-NET deep learning architecture was trained to localize implanted catheters on transverse images. A five-fold cross-validation method was used, allowing for evaluation over the entire dataset. The post-processing software combined the predictions with patient-specific implant information to reconstructed catheters in 3D space, uniquely matched to the implanted grid positions. A reconstruction confidence metric was calculated based on the number and probability of localized predictions per catheter. For each patient, deep learning prediction and post-processing reconstruction was completed in under two minutes on a non-performance PC.

RESULTS

Overall, 80% of catheter reconstructions were accurate, within 2 mm along 90% of the length. The catheter tip was often not detected and required extrapolation during reconstruction. The reconstruction accuracy was 89% for the easiest catheter ranking and decreased to 13% for the highest difficulty ranking, when the aid of live ultrasound would have been recommended. Even when limited to the easiest ranked catheters, the reconstruction accuracy decreased at distal grid positions, down to 50%. Individual implantation style was found to influence the frequency of severe artifacts, slightly impacting the model accuracy. A reconstruction confidence metric identified the difficult catheters, removed the observed individual variation, and increased the overall accuracy to 91% while excluding 27% of the reconstructions.

CONCLUSIONS

The deep learning model localized implanted catheters over a large clinical dataset, with overall promising results. The model faced challenges due to ultrasound artifacts and image degradation distal to the probe, underlining the continued importance of maintaining image quality and minimizing artifacts. A potential workflow for integration into the clinical procedure was demonstrated, including the use of a confidence metric to predict low accuracy reconstructions. Comparison between models evaluated on different datasets should also consider underlying differences, such as the frequency and severity of imaging artifacts. This article is protected by copyright. All rights reserved.