Feasibility study of ultrasound imaging for stereotactic body radiation therapy with active breathing coordinator in pancreatic cancer

Enhancing Image-Guided Radiation Therapy for Pancreatic Cancer: Utilizing Aligned Peak Response Beamforming in Flexible Array Transducers

To develop ultrasound-guided radiotherapy, we proposed an assistant structure with embedded markers along with a novel alternative method, the Aligned Peak Response (APR) method, to alter the conventional delay-and-sum (DAS) beamformer for reconstructing ultrasound images obtained from a flexible array. We simulated imaging targets in Field-II using point target phantoms with point targets at different locations. In the experimental phantom ultrasound images, image RF data were acquired with a flexible transducer with in-house assistant structures embedded with needle targets for testing the accuracy of the APR method. The lateral full width at half maximum (FWHM) values of the objective point target (OPT) in ground truth ultrasound images, APR-delayed ultrasound images with a flat shape, and images acquired with curved transducer radii of 500 mm and 700 mm were 3.96 mm, 4.95 mm, 4.96 mm, and 4.95 mm. The corresponding axial FWHM values were 1.52 mm, 4.08 mm, 5.84 mm, and 5.92 mm, respectively. These results demonstrate that the proposed assistant structure and the APR method have the potential to construct accurate delay curves without external shape sensing, thereby enabling a flexible ultrasound array for tracking pancreatic tumor targets in real time for radiotherapy.

DAART: a deep learning platform for deeply accelerated adaptive radiation therapy for lung cancer

Purpose

The study aimed to implement a novel, deeply accelerated adaptive radiation therapy (DAART) approach for lung cancer radiotherapy (RT). Lung cancer is the most common cause of cancer-related death, and RT is the preferred medically inoperable treatment for early stage non-small cell lung cancer (NSCLC). In the current lengthy workflow, it takes a median of four weeks from diagnosis to RT treatment, which can result in complete restaging and loss of local control with delay. We implemented the DAART approach, featuring a novel deepPERFECT system, to address unwanted delays between diagnosis and treatment initiation.

Materials and methods

We developed a deepPERFECT to adapt the initial diagnostic imaging to the treatment setup to allow initial RT planning and verification. We used data from 15 patients with NSCLC treated with RT to train the model and test its performance. We conducted a virtual clinical trial to evaluate the treatment quality of the proposed DAART for lung cancer radiotherapy.

Results

We found that deepPERFECT predicts planning CT with a mean high-intensity fidelity of 83 and 14 HU for the body and lungs, respectively. The shape of the body and lungs on the synthesized CT was highly conformal, with a dice similarity coefficient (DSC) of 0.91, 0.97, and Hausdorff distance (HD) of 7.9 mm, and 4.9 mm, respectively, compared with the planning CT scan. The tumor showed less conformality, which warrants acquisition of treatment Day1 CT and online adaptive RT. An initial plan was designed on synthesized CT and then adapted to treatment Day1 CT using the adapt to position (ATP) and adapt to shape (ATS) method. Non-inferior plan quality was achieved by the ATP scenario, while all ATS-adapted plans showed good plan quality.

Conclusion

DAART reduces the common online ART (ART) treatment course by at least two weeks, resulting in a 50% shorter time to treatment to lower the chance of restaging and loss of local control.

Ultrasound Imaging with Flexible Array Transducer for Pancreatic Cancer Radiation Therapy

Pancreatic cancer with less than 10% 3-year survival rate is one of deadliest cancer types and greatly benefits from enhanced radiotherapy. Organ motion monitoring helps spare the normal tissue from high radiation and, in turn, enables the dose escalation to the target that has been shown to improve the effectiveness of RT by doubling and tripling post-RT survival rate. The flexible array transducer is a novel and promising solution to address the limitation of conventional US probes. We proposed a novel shape estimation for flexible array transducer using two sequential algorithms: (i) an optical tracking-based system that uses the optical markers coordinates attached to the probe at specific positions to estimate the array shape in real-time and (ii) a fully automatic shape optimization algorithm that automatically searches for the optimal array shape that results in the highest quality reconstructed image. We conducted phantom and in vivo experiments to evaluate the estimated array shapes and the accuracy of reconstructed US images. The proposed method reconstructed US images with low full-width-at-half-maximum (FWHM) of the point scatters, correct aspect ratio of the cyst, and high-matching score with the ground truth. Our results demonstrated that the proposed methods reconstruct high-quality ultrasound images with significantly less defocusing and distortion compared with those without any correction. Specifically, the automatic optimization method reduced the array shape estimation error to less than half-wavelength of transmitted wave, resulting in a high-quality reconstructed image.

deepPERFECT: Novel Deep Learning CT Synthesis Method for Expeditious Pancreatic Cancer Radiotherapy

Major sources of delay in the standard of care RT workflow are the need for multiple appointments and separate image acquisition. In this work, we addressed the question of how we can expedite the workflow by synthesizing planning CT from diagnostic CT. This idea is based on the theory that diagnostic CT can be used for RT planning, but in practice, due to the differences in patient setup and acquisition techniques, separate planning CT is required. We developed a generative deep learning model, deepPERFECT, that is trained to capture these differences and generate deformation vector fields to transform diagnostic CT into preliminary planning CT. We performed detailed analysis both from an image quality and a dosimetric point of view, and showed that deepPERFECT enabled the preliminary RT planning to be used for preliminary and early plan dosimetric assessment and evaluation.

deepPERFECT: Novel Deep Learning CT Synthesis Method for Expeditious Pancreatic Cancer Radiotherapy

Pancreatic cancer with more than 60,000 new cases each year has less than 10 percent 5-year overall survival. Radiation therapy (RT) is an effective treatment for Locally advanced pancreatic cancer (LAPC). The current clinical RT workflow is lengthy and involves separate image acquisition for diagnostic CT (dCT) and planning CT (pCT). Studies have shown a reduction in mortality rate from expeditious radiotherapy treatment. dCT and pCT are acquired separately because of the differences in the image acquisition setup and patient body. We are presenting deepPERFECT: deep learning-based model to adapt the shape of the patient body on dCT to the treatment delivery setup. Our method expedites the treatment course by allowing the design of the initial RT planning before the pCT acquisition. Thus, the physicians can evaluate the potential RT prognosis ahead of time, verify the plan on the treatment day-one CT and apply any online adaptation if needed. We used the data from 25 pancreatic cancer patients. The model was trained on 15 cases and tested on the remaining ten cases. We evaluated the performance of four different deep-learning architectures for this task. The synthesized CT (sCT) and regions of interest (ROIs) were compared with ground truth (pCT) using Dice similarity coefficient (DSC) and Hausdorff distance (HD). We found that the three-dimensional Generative Adversarial Network (GAN) model trained on large patches has the best performance. The average DSC and HD for body contours were 0.93, and 4.6 mm. We found no statistically significant difference between the synthesized CT plans and the ground truth. We showed that employing deepPERFECT shortens the current lengthy clinical workflow by at least one week and improves the effectiveness of treatment and the quality of life of pancreatic cancer patients.

Systematic study of the iodinated rectal hydrogel spacer material discrepancy on accuracy of proton dosimetry

PURPOSE

Iodination of rectal hydrogel spacer increases the computed tomography (CT) visibility. The effect of iodinated hydrogel spacer material on the accuracy of proton dosimetry has not been fully studied yet. We presented a systematic study to determine the effect of iodination on proton dosimetry accuracy during proton therapy (PT).

METHODS

PT plans were designed for 20 prostate cancer patients with rectal hydrogel spacer. Three variations of hydrogel density were considered. First, as the ground truth, the true elemental composition of hydrogel true material (TM), verified by our measurement of spacer stopping power ratio, was used for plan optimization and Monte Carlo dose calculation. The dose distribution was recalculated with (1) no material (NM) override based on the CT intensity of the iodinated spacer, and (2) the water material (WM) override, where spacer material was replaced by water. The plans were compared with the ground truth using the metrics of gamma index (GI) and dosimetric indices.

RESULTS

The iodination of hydrogel spacer affected the proton dose distribution with the NM scenario showing the most deviation from the ground truth. The iodination of spacer resulted in a notable increase in CT intensity and led to the treatment planning systems mistreating the iodinated spacer as a high-density material. Among the structures adjacent to the target, neurovascular bundles showed the largest dose difference, up to 350 cGy or about 5% of the prescribed dose with NM. Compared to the WM scenario, dose distribution similarity and GI passing ratios were lower in the NM scenario.

CONCLUSION

The inaccurate CT intensity-based material for iodinated spacer resulted in errors in PT dose calculation. We found that the error was negligible if the iodinated spacer was replaced with water. Water density can be used as a clinically accessible and convenient alternative material override to true spacer material.

A phantom-based analysis for tracking intra-fraction pancreatic tumor motion by ultrasound imaging during radiation therapy

Purpose

In this study, we aim to further evaluate the accuracy of ultrasound tracking for intra-fraction pancreatic tumor motion during radiotherapy by a phantom-based study.

Methods

Twelve patients with pancreatic cancer who were treated with stereotactic body radiation therapy were enrolled in this study. The displacement points of the respiratory cycle were acquired from 4DCT and transferred to a motion platform to mimic realistic breathing movements in our phantom study. An ultrasound abdominal phantom was placed and fixed in the motion platform. The ground truth of phantom movement was recorded by tracking an optical tracker attached to this phantom. One tumor inside the phantom was the tracking target. In the evaluation of the results, the monitoring results from the ultrasound system were compared with the phantom motion results from the infrared camera. Differences between infrared monitoring motion and ultrasound tracking motion were analyzed by calculating the root-mean-square error.

Results

The 82.2% ultrasound tracking motion was within a 0.5 mm difference value between ultrasound tracking displacement and infrared monitoring motion. 0.7% ultrasound tracking failed to track accurately (a difference value > 2.5 mm). These differences between ultrasound tracking motion and infrared monitored motion do not correlate with respiratory displacements, respiratory velocity, or respiratory acceleration by linear regression analysis.

Conclusions

The highly accurate monitoring results of this phantom study prove that the ultrasound tracking system may be a potential method for real-time monitoring targets, allowing more accurate delivery of radiation doses.

An integrated ultrasound imaging and abdominal compression device for respiratory motion management in radiation therapy

BACKGROUND

Radiotherapy to tumors in the abdomen is challenging because of the significant organ movement and tissue deformation caused by respiration.

PURPOSE

A motion management strategy that integrated ultrasound (US) imaging with abdominal compression was developed and evaluated, where US was used to real-time monitor organ motion after abdominal compression.

METHODS

A device that combined a US imaging system and an abdominal compression plate (ACP) was developed. Twenty-one healthy volunteers were involved to evaluate the motion management efficacy. Each volunteer was immobilized on a flat bench by the device. Abdominal US data were successively collected with and without ACP compression and experiments were repeated three times to verify the imaging reproducibility. A template matching algorithm based on normalized cross correlation (NCC) was implemented to track the targets (vessels in the liver, pancreas and stomach) automatically. The matching algorithm was validated by comparing with the manual references. Automatic tracking was judged as failed if the center of mass difference from manual tracking was beyond a failure threshold. Based on the locations obtained through the template matching algorithm, the motion correlation between liver and pancreas/stomach was investigated using Pearson correlation test. Paired Student's t-test was used to analyze the difference between the results without and with ACP compression.

RESULTS

The liver motion amplitude over all 21 volunteers was significantly (p<0.001) reduced from 14.9 ± 5.5/3.4 ± 1.8 mm in superior-inferior (SI)/anterior-posterior (AP) direction before ACP compression to 7.3 ± 1.5/1.6 ± 0.7 mm after ACP compression. The mean liver motion standard deviation before compression was on average 2.8/1.4 mm in SI/AP direction, and was significantly (p<0.001) reduced to 0.9/0.4 mm after compression. The failure rates of automatic tracking for liver, pancreas and stomach were reduced for failure thresholds of 1-5 mm after applying ACP. The Pearson correlation coefficients between liver and pancreas/stomach were 0.98/0.97 without ACP and 0.96/0.94 with ACP in SI direction, and were 0.68/0.68 and 0.43/0.42 in AP direction. The motion prediction errors for pancreas/stomach with ACP have significantly (p<0.001) reduced to 0.45 ± 0.36/0.52 ± 0.43 mm from 0.69 ± 0.56/0.71 ± 0.66 mm without ACP in SI direction, and to 0.38 ± 0.33/0.39 ± 0.27 mm from 0.44 ± 0.35/0.61 ± 0.59 mm in AP direction.

CONCLUSIONS

The proposed strategy that combines real-time US imaging and abdominal compression has the potential to reduce the abdominal organ motion while improving both target tracking reliability and motion reproducibility. Furthermore, the observed correlation between liver and pancreas/stomach motion indicates the possibility of indirect pancreas/stomach tracking using liver markers as tracking surrogates. The strategy is expected to provide an alternative for respiratory motion management in the radiation treatment of abdominal tumors. This article is protected by copyright. All rights reserved.

Radiotherapy respiratory motion management in hepatobiliary and pancreatic malignancies: a systematic review of patient factors influencing effectiveness of motion reduction with abdominal compression

BACKGROUND

The effectiveness of abdominal compression for motion management in hepatobiliary-pancreatic (HPB) radiotherapy has not been systematically evaluated.

METHODS & MATERIALS

A systematic review was carried out using PubMed/Medline, Cochrane Library, Web of Science, and CINAHL databases up to 1 July 2021. No date restrictions were applied. Additional searches were carried out using the University of Manchester digital library, Google Scholar and of retrieved papers' reference lists. Studies conducted evaluating respiratory motion utilising imaging with and without abdominal compression in the same patients available in English were included. Studies conducted in healthy volunteers or majority non-HPB sites, not providing descriptive motion statistics or patient characteristics before and after compression in the same patients or published without peer-review were excluded. A narrative synthesis was employed by tabulating retrieved studies and organising chronologically by abdominal compression device type to help identify patterns in the evidence.

RESULTS

The inclusion criteria were met by 6 studies with a total of 152 patients. Designs were a mix of retrospective and prospective quantitative designs with chronological, non-randomised recruitment. Abdominal compression reduced craniocaudal respiratory motion in the majority of patients, although in four studies there were increases seen in at least one direction. The influence of patient comorbidities on effectiveness of compression, and/or comfort with compression was not evaluated in any study.

CONCLUSION

Abdominal compression may not be appropriate for all patients, and benefit should be weighed with potential increase in motion or discomfort in patients with small initial motion (<5 mm). Patient factors including male sex, and high body mass index (BMI) were found to impact the effectiveness of compression, however with limited evidence. High-quality studies are warranted to fully assess the clinical impact of abdominal compression on treatment outcomes and toxicity prospective in comparison to other motion management strategies.

Demonstrating the benefits of corrective intraoperative feedback in improving the quality of duodenal hydrogel spacer placement

Purpose

Pancreatic cancer is the fourth leading cause of cancer‐related death with a 10% 5‐year overall survival rate (OS). Radiation therapy (RT) in addition to dose escalation improves the outcome by significantly increasing the OS at 2 and 3 years but is hindered by the toxicity of the duodenum. Our group showed that the insertion of hydrogel spacer reduces duodenal toxicity, but the complex anatomy and the demanding procedure make the benefits highly uncertain. Here, we investigated the feasibility of augmenting the workflow with intraoperative feedback to reduce the adverse effects of the uncertainties.

Materials and Methods

We simulated three scenarios of the virtual spacer for four cadavers with two types of gross tumor volume (GTV) (small and large); first, the ideal injection; second, the nonideal injection that incorporates common spacer placement uncertainties; and third, the corrective injection that uses the simulation result from nonideal injection and is designed to compensate for the effect of uncertainties. We considered two common uncertainties: (1) “Narrowing” is defined as the injection of smaller spacer volume than planned. (2) “Missing part” is defined as failure to inject spacer in the ascending section of the duodenum. A total of 32 stereotactic body radiation therapy (SBRT) plans (33 Gy in 5 fractions) were designed, for four cadavers, two GTV sizes, and two types of uncertainties. The preinjection scenario for each case was compared with three scenarios of virtual spacer placement from the dosimetric and geometric points of view.

Results

We found that the overlapping PTV space with the duodenum is an informative quantity for determining the effective location of the spacer. The ideal spacer distribution reduced the duodenal V33Gy for small and large GTV to less than 0.3 and 0.1cc, from an average of 3.3cc, and 1.2cc for the preinjection scenario. However, spacer placement uncertainties reduced the efficacy of the spacer in sparing the duodenum (duodenal V33Gy: 1.3 and 0.4cc). The separation between duodenum and GTV decreased by an average of 5.3 and 4.6 mm. The corrective feedback can effectively bring back the expected benefits from the ideal location of the spacer (averaged V33Gy of 0.4 and 0.1cc).

Conclusions

An informative feedback metric was introduced and used to mitigate the effect of spacer placement uncertainties and maximize the benefits of the EUS‐guided procedure.

Finite Element-Based Personalized Simulation of Duodenal Hydrogel Spacer: Spacer Location Dependent Duodenal Sparing and a Decision Support System for Spacer-Enabled Pancreatic Cancer Radiation Therapy

Purpose

Pancreatic cancer is the fourth leading cause of cancer-related death, with a very low 5-year overall survival rate (OS). Radiation therapy (RT) together with dose escalation significantly increases the OS at 2 and 3 years. However, dose escalation is very limited due to the proximity of the duodenum. Hydrogel spacers are an effective way to reduce duodenal toxicity, but the complexity of the anatomy and the procedure makes the success and effectiveness of the spacer procedure highly uncertain. To provide a preoperative simulation of hydrogel spacers, we presented a patient-specific spacer simulator algorithm and used it to create a decision support system (DSS) to provide a preoperative optimal spacer location to maximize the spacer benefits.

Materials and Methods

Our study was divided into three phases. In the validation phase, we evaluated the patient-specific spacer simulator algorithm (FEMOSSA) for the duodenal spacer using the dice similarity coefficient (DSC), overlap volume histogram (OVH), and radial nearest neighbor distance (RNND). For the simulation phase, we simulated four virtual spacer scenarios based on the location of the spacer in para-duodenal space. Next, stereotactic body radiation therapy (SBRT) plans were designed and dosimetrically analyzed. Finally, in the prediction phase, using the result of the simulation phase, we created a Bayesian DSS to predict the optimal spacer location and biological effective dose (BED).

Results

A realistic simulation of the spacer was achieved, reflected in a statistically significant increase in average target and duodenal DSC for the simulated spacer. Moreover, the small difference in average mean and 5th-percentile RNNDs (0.5 and 2.1 mm) and OVH thresholds (average of less than 0.75 mm) showed that the simulation attained similar separation as the real spacer. We found a spacer-location-independent decrease in duodenal V20Gy, a highly spacer-location-dependent change in V33Gy, and a strong correlation between L1cc and V33Gy. Finally, the Bayesian DSS predicted the change in BED with a root mean squared error of 3.6 Gys.

Conclusions

A duodenal spacer simulator platform was developed and used to systematically study the dosimetric effect of spacer location. Further, L1cc is an informative anatomical feedback to guide the DSS to indicate the spacer efficacy, optimum location, and expected improvement.

The Feasibility of Haar Feature-Based Endoscopic Ultrasound Probe Tracking for Implanting Hydrogel Spacer in Radiation Therapy for Pancreatic Cancer

Purpose

We proposed a Haar feature-based method for tracking endoscopic ultrasound (EUS) probe in diagnostic computed tomography (CT) and Magnetic Resonance Imaging (MRI) scans for guiding hydrogel injection without external tracking hardware. This study aimed to assess the feasibility of implementing our method with phantom and patient images.

Materials and Methods

Our methods included the pre-simulation section and Haar features extraction steps. Firstly, the simulated EUS set was generated based on anatomic information of interpolated CT/MRI images. Secondly, the efficient Haar features were extracted from simulated EUS images to create a Haar feature dictionary. The relative EUS probe position was estimated by searching the best matched Haar feature vector of the dictionary with Haar feature vector of target EUS images. The utilization of this method was validated using EUS phantom and patient CT/MRI images.

Results

In the phantom experiment, we showed that our Haar feature-based EUS probe tracking method can find the best matched simulated EUS image from a simulated EUS dictionary which includes 123 simulated images. The errors of all four target points between the real EUS image and the best matched EUS images were within 1 mm. In the patient CT/MRI scans, the best matched simulated EUS image was selected by our method accurately, thereby confirming the probe location. However, when applying our method in MRI images, our method is not always robust due to the low image resolution.

Conclusions

Our Haar feature-based method is capable to find the best matched simulated EUS image from the dictionary. We demonstrated the feasibility of our method for tracking EUS probe without external tracking hardware, thereby guiding the hydrogel injection between the head of the pancreas and duodenum.

Deep Learning for Ultrasound Beamforming in Flexible Array Transducer

Ultrasound imaging has been developed for image-guided radiotherapy for tumor tracking, and the flexible array transducer is a promising tool for this task. It can reduce the user dependence and anatomical changes caused by the traditional ultrasound transducer. However, due to its flexible geometry, the conventional delay-and-sum (DAS) beamformer may apply incorrect time delay to the radio-frequency (RF) data and produce B-mode images with considerable defocusing and distortion. To address this problem, we propose a novel end-to-end deep learning approach that may alternate the conventional DAS beamformer when the transducer geometry is unknown. Different deep neural networks (DNNs) were designed to learn the proper time delays for each channel, and they were expected to reconstruct the undistorted high-quality B-mode images directly from RF channel data. We compared the DNN results to the standard DAS beamformed results using simulation and flexible array transducer scan data. With the proposed DNN approach, the averaged full-width-at-half-maximum (FWHM) of point scatters is 1.80 mm and 1.31 mm lower in simulation and scan results, respectively; the contrast-to-noise ratio (CNR) of the anechoic cyst in simulation and phantom scan is improved by 0.79 dB and 1.69 dB, respectively; and the aspect ratios of all the cysts are closer to 1. The evaluation results show that the proposed approach can effectively reduce the distortion and improve the lateral resolution and contrast of the reconstructed B-mode images.

A prospective trial demonstrating the benefit of personalized selection of breath-hold technique for upper-abdominal radiotherapy using the Active Breathing Co-ordinator (ABC)

BACKGROUND

For upper abdominal (UA) tumors, our institutional-standard motion reduction method is Expiration Breath Hold (EBH), using Active Breathing Coordinator (ABC)^TM. However, an individual patient's breath-hold (BH) reproducibility (R_BH) may be improved in Deep Inspiration or Inspiration Breath-Hold (DIBH or IBH). This trial compared the tumor position R_BH, stability (S_BH), and breath-hold time (T_BH) of three BH methods, using ABC, to personalize the selection of technique, by employing a pre-planning screening assessment.

METHODS

Patients planned for UA radiotherapy (kidney, pancreas, liver, or adrenal gland), were invited to participate in this prospective trial. Active Breathing Coordinator (ABC)^TM education was conducted, then participants attempted EBH, DIBH and IBH, in randomized order. During five consecutive BH's for each method, kV fluoroscopy images of the diaphragm were acquired. The BH technique selection was personalized according to a decision matrix. The EBH and the personalized technique cohort mean R_BH and S_BH of were analyzed.

RESULTS

Between May 2019 and March 2020, 19 participants were recruited. Median age of participants was 68 years (range 32-81). Tumor sites included kidney (n=1), adrenal gland (n=5) and liver (n=14). One participant was excluded due to poor BH compliance, leaving 270 images from 18 participants for analysis. Mean T_BH was 22.1, 23.9 & 24.2 seconds for EBH, DIBH and IBH respectively. Screening selected EBH for 44% (n=8), IBH for 39% (n=7) and DIBH for 17% (n=3) of participants. The mean R_BH was superior at 0.92mm (0.79mm SD) for the personalized technique, compared to EBH of 1.79mm (1.49mm SD) (p=0.016). Pre-planned subset analysis of participants whose personalized technique was not EBH showed improved mean R_BH of 0.63mm (0.29mm SD) compared to their EBH R_BH of 2.2mm (1.7mm SD) (p=0.011).

CONCLUSIONS

In 56% of participants, DIBH or IBH demonstrated superior R_BH compared to EBH Personalized BH screening can inform selection of an ABC BH method which provides optimal R_BH with improved T_BH for an individual's planning and treatment course.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ANZCTR): XXX (withheld - blinded manuscript).

EUS-guided hydrogel microparticle injection in a cadaveric model

BACKGROUND AND AIMS

A potential method to reduce gastrointestinal toxicity during radiation therapy in pancreatic head cancer is to create a physical space between the head of the pancreas (HOP) and the duodenum. To date, there have been early reports on the feasibility of endoscopic ultrasound (EUS)-guided hydrogel injection into the interface between the HOP and the duodenum to increase the peri-pancreatic space for radiotherapy. We aimed to evaluate the technical feasibility of EUS-guided hydrogel injection for the creation of space at the peri-pancreatic interface in a cadaveric model.

METHODS

Baseline abdominal computerized tomography (CT) was performed on three unfixed cadaveric specimens. The hydrogel was injected transduodenally into the interface between the HOP and duodenum using linear-array EUS and a 19G needle for fine needle aspiration (FNA). This procedure was repeated along the length of the HOP. CT imaging and gross dissection were performed after the procedure to confirm the localization of the hydrogel and to measure the distance between the HOP and the duodenum.

RESULTS

All cadavers underwent successful EUS-guided injection of the hydrogel. Cadavers 1, 2, and 3 were injected with 9.5, 27, and 10 cc of hydrogel, respectively; along the HOP, the formation of the peri-pancreatic space was a maximum size of 11.77, 13.20, and 12.89 mm, respectively. The hydrogel injections were clearly visualized as hyperechoic bullae during EUS and on post-procedure CT images without any artifacts in all cases.

CONCLUSIONS

We demonstrated that EUS-guided delivery of hydrogel is feasible, and that it increases the peri-pancreatic space in a cadaveric model. The polyethylene glycol (PEG) hydrogel was clearly visible on EUS and CT, without significant artifacts. This may lead to new treatment approaches for pancreatic carcinomas.

Protocol of a study investigating breath-hold techniques for upper-abdominal radiation therapy (BURDIE): addressing the challenge of a moving target

BACKGROUND

Radiation therapy to upper abdominal sites is technically challenging due to motion of tumors and surrounding organs resulting from normal respiration. Breath-hold, using an Active Breathing Coordinator is one strategy used to reduce motion in these tumor sites. Though widely used, no studies have prospectively compared the different breath-hold techniques (inspiration, deep-inspiration and expiration) using ABC in the same patient cohort.

METHODS

Patients planned for radiation therapy to upper abdominal tumors are invited to participate in this prospective study. Participants attempt three breath hold techniques: inspiration, deep-inspiration and expiration breath-hold, in random order. kV fluoroscopy images of the dome of diaphragm are taken of five consecutive breath-holds in each technique. Reproducibility and stability of tumour position are measured, and used to select the technique with which to proceed to planning and treatment. Reproducibility at planning and each treatment fraction is measured, along with breath hold time, treatment efficiency and patient experience.

DISCUSSION

The screening method was validated after the first three participants. This screening process may be able to select the best breath-hold technique for an individual, which may lead to improved reproducibility. The screening process is being piloted as a prospective clinical trial.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ANZCTR): 12618001691235. Registered 12th October 2018. https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=376109&isReview=true .

Setup Management for Stereotactic Body Radiation Therapy of Patients With Pancreatic Cancer Treated via the Breath-Hold Technique

PURPOSE

Active Breathing Coordinator (Elekta AB, Crawley, UK) is a motion management strategy for radiation treatment. During setup, aligning the patient to the bony spine alone does not necessarily lead to an accurate alignment to soft tissue targets, and further adjustment is necessary. Determining a safe range of values for such adjustments is an important quality assurance measure and was the purpose of this study, with focus on stereotactic body radiation therapy in patients with pancreatic cancer.

METHODS AND MATERIALS

The retrospective study included 19 previously treated patients. For each fraction, a free-breathing cone beam computed tomography scan was registered to a reference breath-hold computed tomography for alignment to the spine. Two perpendicular breath-hold kV projection images were then acquired and compared with corresponding reference digitally reconstructed radiographs for additional alignment with a surrogate fiducial marker. By comparing the breath-hold kV projection images from subsequent treatment fractions with those from the first fraction, we derived the 3-dimensional variability of the fiducial position with respect to the reference image.

RESULTS

We observed intrafraction setup error to be within 2.0 mm. For interfraction, we observed average reproducibility of 1.7 ± 0.8 mm, 2.0 ± 1.4 mm, and 3.2 ± 2.5 mm in the left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions, respectively. The average excursion values from free breathing spine to breath-hold fiducial alignment were 1.5 ± 1.4 mm, 2.0 ± 1.9 mm, and 3.0 ± 2.0 mm in the LR, AP and SI directions, respectively. The observed ranges of average excursions among all patients were 0.2 to 5.1 mm, 0.1 to 5. 9 mm, and 0.6 to 7.8 mm in the LR, AP, and SI directions, respectively.

CONCLUSIONS

This study demonstrates that intrafraction targeting errors can be within 2 mm, and interfraction shifts from free-breathing spine to Active Breathing Coordinator breath-hold target can be as high as 8 mm. Values that deviate significantly would need further investigation to rule out factors such as local progression, bowel gas, or fiducial shift before treatment.

2D ultrasound imaging based intra-fraction respiratory motion tracking for abdominal radiation therapy using machine learning

We have previously developed a robotic ultrasound imaging system for motion monitoring in abdominal radiation therapy. Owing to the slow speed of ultrasound image processing, our previous system could only track abdominal motions under breath-hold. To overcome this limitation, a novel 2D-based image processing method for tracking intra-fraction respiratory motion is proposed. Fifty-seven different anatomical features acquired from 27 sets of 2D ultrasound sequences were used in this study. Three 2D ultrasound sequences were acquired with the robotic ultrasound system from three healthy volunteers. The remaining datasets were provided by the 2015 MICCAI Challenge on Liver Ultrasound Tracking. All datasets were preprocessed to extract the feature point, and a patient-specific motion pattern was extracted by principal component analysis and slow feature analysis (SFA). The tracking finds the most similar frame (or indexed frame) by a k-dimensional-tree-based nearest neighbor search for estimating the tracked object location. A template image was updated dynamically through the indexed frame to perform a fast template matching (TM) within a learned smaller search region on the incoming frame. The mean tracking error between manually annotated landmarks and the location extracted from the indexed training frame is 1.80  ±  1.42 mm. Adding a fast TM procedure within a small search region reduces the mean tracking error to 1.14  ±  1.16 mm. The tracking time per frame is 15 ms, which is well below the frame acquisition time. Furthermore, the anatomical reproducibility was measured by analyzing the location's anatomical landmark relative to the probe; the position-controlled probe has better reproducibility and yields a smaller mean error across all three volunteer cases, compared to the force-controlled probe (2.69 versus 11.20 mm in the superior-inferior direction and 1.19 versus 8.21 mm in the anterior-posterior direction). Our method reduces the processing time for tracking respiratory motion significantly, which can reduce the delivery uncertainty.

Real-time intrafraction motion monitoring in external beam radiotherapy

Radiotherapy (RT) aims to deliver a spatially conformal dose of radiation to tumours while maximizing the dose sparing to healthy tissues. However, the internal patient anatomy is constantly moving due to respiratory, cardiac, gastrointestinal and urinary activity. The long term goal of the RT community to 'see what we treat, as we treat' and to act on this information instantaneously has resulted in rapid technological innovation. Specialized treatment machines, such as robotic or gimbal-steered linear accelerators (linac) with in-room imaging suites, have been developed specifically for real-time treatment adaptation. Additional equipment, such as stereoscopic kilovoltage (kV) imaging, ultrasound transducers and electromagnetic transponders, has been developed for intrafraction motion monitoring on conventional linacs. Magnetic resonance imaging (MRI) has been integrated with cobalt treatment units and more recently with linacs. In addition to hardware innovation, software development has played a substantial role in the development of motion monitoring methods based on respiratory motion surrogates and planar kV or Megavoltage (MV) imaging that is available on standard equipped linacs. In this paper, we review and compare the different intrafraction motion monitoring methods proposed in the literature and demonstrated in real-time on clinical data as well as their possible future developments. We then discuss general considerations on validation and quality assurance for clinical implementation. Besides photon RT, particle therapy is increasingly used to treat moving targets. However, transferring motion monitoring technologies from linacs to particle beam lines presents substantial challenges. Lessons learned from the implementation of real-time intrafraction monitoring for photon RT will be used as a basis to discuss the implementation of these methods for particle RT.

Evaluation of 2D and 3D ultrasound tracking algorithms and impact on ultrasound-guided liver radiotherapy margins

PURPOSE

Compensation for respiratory motion is important during abdominal cancer treatments. In this work we report the results of the 2015 MICCAI Challenge on Liver Ultrasound Tracking and extend the 2D results to relate them to clinical relevance in form of reducing treatment margins and hence sparing healthy tissues, while maintaining full duty cycle.

METHODS

We describe methodologies for estimating and temporally predicting respiratory liver motion from continuous ultrasound imaging, used during ultrasound-guided radiation therapy. Furthermore, we investigated the trade-off between tracking accuracy and runtime in combination with temporal prediction strategies and their impact on treatment margins.

RESULTS

Based on 2D ultrasound sequences from 39 volunteers, a mean tracking accuracy of 0.9 mm was achieved when combining the results from the 4 challenge submissions (1.2 to 3.3 mm). The two submissions for the 3D sequences from 14 volunteers provided mean accuracies of 1.7 and 1.8 mm. In combination with temporal prediction, using the faster (41 vs 228 ms) but less accurate (1.4 vs 0.9 mm) tracking method resulted in substantially reduced treatment margins (70% vs 39%) in contrast to mid-ventilation margins, as it avoided non-linear temporal prediction by keeping the treatment system latency low (150 vs 400 ms). Acceleration of the best tracking method would improve the margin reduction to 75%.

CONCLUSIONS

Liver motion estimation and prediction during free-breathing from 2D ultrasound images can substantially reduce the in-plane motion uncertainty and hence treatment margins. Employing an accurate tracking method while avoiding non-linear temporal prediction would be favorable. This approach has the potential to shorten treatment time compared to breath-hold and gated approaches, and increase treatment efficiency and safety.

A visual probe positioning tool for 4D ultrasound-guided radiotherapy

Ultrasound (US) guidance is a rapidly growing area in image-guided radiotherapy. For motion compensation, the therapy target needs to be visualized with the US probe to continuously determine its position and adapt for shifts. While US has obvious benefits such as real-time capability and proven safety, one of the main drawbacks to date is its user dependency - high quality results require long years of clinical experience. To provide positioning assistance for the setup of US equipment by non-experts, we developed a visual guidance tool combining real-time US volume and CT visualization in a geometrically calibrated setup. By using a 4D US station with real-time data access and an optical tracking system, we achieved a calibration accuracy of 1.2 mm and a mean 2D contour distance of 1.7 mm between organ boundaries identified in US and CT. With this low calibration error as well as the good visual alignment of the structures, the developed probe positioning tool could be a valuable aid for ultrasound-guided radiotherapy and other interventions by guiding the user to a suitable acoustic window while potentially improving setup reproducibility.