Markerless positional verification using template matching and triangulation of kV images acquired during irradiation for lung tumors treated in breath-hold

Deep learning-based target decomposition for markerless lung tumor tracking in radiotherapy

BACKGROUND

In radiotherapy, real-time tumor tracking can verify tumor position during beam delivery, guide the radiation beam to target the tumor, and reduce the chance of a geometric miss. Markerless kV x-ray image-based tumor tracking is challenging due to the low tumor visibility caused by tumor-obscuring structures. Developing a new method to enhance tumor visibility for real-time tumor tracking is essential.

PURPOSE

To introduce a novel method for markerless kV image-based tracking of lung tumors via deep learning-based target decomposition.

METHODS

We utilized a conditional Generative Adversarial Network (cGAN), known as Pix2Pix, to build a patient-specific model and generate the synthetic decomposed target image (sDTI) to enhance tumor visibility on the real-time kV projection images acquired by the onboard kV imager equipped on modern linear accelerators. We used 4DCT simulation images to generate the digitally reconstructed radiograph (DRR) and DTI image pairs for model training. We augmented the training dataset by randomly shifting the 4DCT in the superior-inferior, anterior-posterior, and left-right directions during the DRR and DTI generation process. We performed real-time 2D tumor tracking via template matching between the DTI generated from the CT simulation and the sDTI generated from the real-time kV projection images. We validated the proposed method using nine patients' datasets with implanted beacons near the tumor.

RESULTS

The sDTI can effectively improve the image contrast around the lung tumors on the kV projection images for the nine patients. With the beacon motion as ground truth, the tracking errors were on average 0.8 ± 0.7 mm in the superior-inferior (SI) direction and 0.9 ± 0.8 mm in the in-plane left-right (IPLR) direction. The percentage of successful tracking, defined as a tracking error less than 2 mm in the SI direction, is 92.2% on the 4312 tested images. The patient-specific model took approximately 12 h to train. During testing, it took approximately 35 ms to generate one sDTI, and 13 ms to perform the tumor tracking using template matching.

CONCLUSIONS

Our method offers the potential solution for nearly real-time markerless lung tumor tracking. It achieved a high level of accuracy and an impressive tracking rate. Further development of 3D lung tumor tracking is warranted.

Toward quantitative intrafractional monitoring in paraspinal SBRT using a proprietary software application: clinical implementation and patient results

Objective.We report on paraspinal motion and the clinical implementation of our proprietary software that leverages Varian's intrafraction motion review (IMR) capability for quantitative tracking of the spine during paraspinal SBRT. The work is based on our prior development and analysis on phantoms.Approach.To address complexities in patient anatomy, digitally reconstructed radiographs (DRR's) that highlight only the spine or hardware were constructed as tracking reference. Moreover, a high-pass filter and first-pass coarse search were implemented to enhance registration accuracy and stability. For evaluation, 84 paraspinal SBRT patients with sites spanning across the entire vertebral column were enrolled with prescriptions ranging from 24 to 40 Gy in one to five fractions. Treatments were planned and delivered with 9 IMRT beams roughly equally distributed posteriorly. IMR was triggered every 200 or 500 MU for each beam. During treatment, the software grabbed the IMR image, registered it with the corresponding DRR, and displayed the motion result in near real-time on auto-pilot mode. Four independent experts completed offline manual registrations as ground truth for tracking accuracy evaluation.Main results.Our software detected ≥1.5 mm and ≥2 mm motions among 17.1% and 6.6% of 1371 patient images, respectively, in either lateral or longitudinal direction. In the validation set of 637 patient images, 91.9% of the tracking errors compared to manual registration fell within ±0.5 mm in either direction. Given a motion threshold of 2 mm, the software accomplished a 98.7% specificity and a 93.9% sensitivity in deciding whether to interrupt treatment for patient re-setup.Significance.Significant intrafractional motion exists in certain paraspinal SBRT patients, supporting the need for quantitative motion monitoring during treatment. Our improved software achieves high motion tracking accuracy clinically and provides reliable guidance for treatment intervention. It offers a practical solution to ensure accurate delivery of paraspinal SBRT on a conventional Linac platform.

Deep learning-based markerless lung tumor tracking in stereotactic radiotherapy using Siamese networks

BACKGROUND

Radiotherapy (RT) is involved in about 50% of all cancer patients, making it a very important treatment modality. The most common type of RT is external beam RT, which consists of delivering the radiation to the tumor from outside the body. One novel treatment delivery method is volumetric modulated arc therapy (VMAT), where the gantry continuously rotates around the patient during the radiation delivery.

PURPOSE

Accurate tumor position monitoring during stereotactic body radiotherapy (SBRT) for lung tumors can help to ensure that the tumor is only irradiated when it is inside the planning target volume. This can maximize tumor control and reduce uncertainty margins, lowering organ-at-risk dose. Conventional tracking methods are prone to errors, or have a low tracking rate, especially for small tumors that are in close vicinity to bony structures.

METHODS

We investigated patient-specific deep Siamese networks for real-time tumor tracking, during VMAT. Due to lack of ground truth tumor locations in the kilovoltage (kV) images, each patient-specific model was trained on synthetic data (DRRs), generated from the 4D planning CT scans, and evaluated on clinical data (x-rays). Since there are no annotated datasets with kV images, we evaluated the model on a 3D printed anthropomorphic phantom but also on six patients by computing the correlation coefficient with the breathing-related vertical displacement of the surface-mounted marker (RPM). For each patient/phantom, we used 80% of DRRs for training and 20% for validation.

RESULTS

The proposed Siamese model outperformed the conventional benchmark template matching-based method (RTR): (1) when evaluating both methods on the 3D phantom, the Siamese model obtained a 0.57-0.79-mm mean absolute distance to the ground truth tumor locations, compared to 1.04-1.56 mm obtained by RTR; (2) on patient data, the Siamese-determined longitudinal tumor position had a correlation coefficient of 0.71-0.98 with the RPM, compared to 0.07-0.85 for RTR; (3) the Siamese model had a 100% tracking rate, compared to 62%-82% for RTR.

CONCLUSIONS

Based on these results, we argue that Siamese-based real-time 2D markerless tumor tracking during radiation delivery is possible. Further investigation and development of 3D tracking is warranted.

A markerless beam's eye view tumor tracking algorithm based on unsupervised deformable registration learning framework of VoxelMorph in medical image with partial data

PURPOSE

To propose an unsupervised deformable registration learning framework-based markerless beam's eye view (BEV) tumor tracking algorithm for the inferior quality megavolt (MV) images with occlusion and deformation.

METHODS

Quality assurance (QA) plans for thorax phantom were delivered to the linear accelerator with artificially treatment offsets. Electronic portal imaging device (EPID) images (682 in total) and corresponding digitally reconstructed radiograph (DRR) were gathered as the moving and fixed image pairs, which were randomly divided into training and testing set in a ratio of 0.7:0.3 to train a non-rigid registration model with Voxelmorph. Simultaneously, 533 pairs of patient images from 21 lung tumor plans were acquired for tumor tracking investigation to offer quantifiable tumor motion data. Tracking error and image similarity measures were employed to evaluate the algorithm's accuracy.

RESULTS

The tracking algorithm can handle image registration with non-rigid deformation and losses ranging from 10 % to 80 %. The tracking errors in the phantom study were below 3 mm in about 86.8 % of cases, and below 2 mm in about 80 % of cases. The normalized mutual information (NMI) changes from 1.182 ± 0.024 to 1.198 ± 0.024 (p < 0.005). The patient target had an average translation of 3.784 mm and a maximum comprehensive displacement value of 7.455 mm. NMI of patient images changes from 1.209 ± 0.027 to 1.217 ± 0.026 (p < 0.005), indicating the presence of non-negligible non-rigid deformation.

CONCLUSIONS

The study provides a robust markerless tumor tracking algorithm for multi-modal, partial data and inferior quality image processing.

Effect of different noise reduction techniques and template matching parameters on markerless tumor tracking using dual-energy imaging

PURPOSE

To evaluate the impact of various noise reduction algorithms and template matching parameters on the accuracy of markerless tumor tracking (MTT) using dual-energy (DE) imaging.

METHODS

A Varian TrueBeam linear accelerator was used to acquire a series of alternating 60 and 120 kVp images (over a 180° arc) using fast kV switching, on five early-stage lung cancer patients. Subsequently, DE logarithmic weighted subtraction was performed offline on sequential images to remove bone. Various noise reduction techniques-simple smoothing, anticorrelated noise reduction (ACNR), noise clipping (NC), and NC-ACNR-were applied to the resultant DE images. Separately, tumor templates were generated from the individual planning CT scans, and band-pass parameter settings for template matching were varied. Template tracking was performed for each combination of noise reduction techniques and templates (based on band-pass filter settings). The tracking success rate (TSR), root mean square error (RMSE), and missing frames (percent unable to track) were evaluated against the estimated ground truth, which was obtained using Bayesian inference.

RESULTS

DE-ACNR, combined with template band-pass filter settings of σ_low  = 0.4 mm and σ_high  = 1.6 mm resulted in the highest TSR (87.5%), RMSE (1.40 mm), and a reasonable amount of missing frames (3.1%). In comparison to unprocessed DE images, with optimized band-pass filter settings of σ_low  = 0.6 mm and σ_high  = 1.2 mm, the TSR, RMSE, and missing frames were 85.3%, 1.62 mm, and 2.7%, respectively. Optimized band-pass filter settings resulted in improved TSR values and a lower missing frame rate for both unprocessed DE and DE-ACNR as compared to the use previously published band-pass parameters based on single energy kV images.

CONCLUSION

Noise reduction strategies combined with the optimal selection of band-pass filter parameters can improve the accuracy and TSR of MTT for lung tumors when using DE imaging.

Single-fraction 34Gy lung SBRT using proton transmission beams: FLASH-dose calculations and the influence of different dose-rate methods and dose/dose-rate thresholds

Purpose

Research suggests that in addition to the dose-rate, a dose threshold is also important for the reduction in normal tissue toxicity with similar tumor control after ultrahigh dose-rate radiation therapy (UHDR-RT). In this analysis we aimed to identify factors that might limit the ability to achieve this “FLASH”-effect in a scenario attractive for UHDR-RT (high fractional beam dose, small target, few organs-at-risk): single-fraction 34 Gy lung stereotactic body radiation therapy.

Methods and Materials

Clinical volumetric-modulated arc therapy (VMAT) plans, intensity modulated proton therapy (IMPT) plans and transmission beam (TB) plans were compared for 6 small and 1 large lung lesion. The TB-plan dose-rate was calculated using 4 methods and the FLASH-percentage (percentage of dose delivered at dose-rates ≥40/100 Gy/s and ≥4/8 Gy) was determined for various variables: a minimum spot time (minST) of 0.5/2 ms, maximum nozzle current (maxN) of 200/40 0nA, and 2 gantry current (GC) techniques (energy-layer based, spot-based [SB]).

Results

Based on absolute doses 5-beam TB and VMAT-plans are similar, but TB-plans have higher rib, skin, and ipsilateral lung dose than IMPT. Dose-rate calculation methods not considering scanning achieve FLASH-percentages between ∼30% to 80%, while methods considering scanning often achieve <30%. FLASH-percentages increase for lower minST/higher maxN and when using SB GC instead of energy-layer based GC, often approaching the percentage of dose exceeding the dose-threshold. For the small lesions average beam irradiation times (including scanning) varied between 0.06 to 0.31 seconds and total irradiation times between 0.28 to 1.57 seconds, for the large lesion beam times were between 0.16 to 1.47 seconds with total irradiation times of 1.09 to 5.89 seconds.

Conclusions

In a theoretically advantageous scenario for FLASH we found that TB-plan dosimetry was similar to that of VMAT, but inferior to that of IMPT, and that decreasing minST or using SB GC increase the estimated amount of FLASH. For the appropriate machine/delivery parameters high enough dose-rates can be achieved regardless of calculation method, meaning that a possible FLASH dose-threshold will likely be the primary limiting factor.

The markerless lung target tracking AAPM Grand Challenge (MATCH) results

PURPOSE

Lung stereotactic ablative body radiotherapy (SABR) is a radiation therapy success story with level 1 evidence demonstrating its efficacy. To provide real-time respiratory motion management for lung SABR, several commercial and preclinical markerless lung target tracking (MLTT) approaches have been developed. However, these approaches have yet to be benchmarked using a common measurement methodology. This knowledge gap motivated the MArkerless lung target Tracking CHallenge (MATCH). The aim was to localize lung targets accurately and precisely in a retrospective in silico study and a prospective experimental study.

METHODS

MATCH was an American Association of Physicists in Medicine sponsored Grand Challenge. Common materials for the in silico and experimental studies were the experiment setup including an anthropomorphic thorax phantom with two targets within the lungs, and a lung SABR planning protocol. The phantom was moved rigidly with patient-measured lung target motion traces, which also acted as ground truth motion. In the retrospective in silico study a volumetric modulated arc therapy treatment was simulated and a dataset consisting of treatment planning data and intra-treatment kilovoltage (kV) and megavoltage (MV) images for four blinded lung motion traces was provided to the participants. The participants used their MLTT approach to localize the moving target based on the dataset. In the experimental study, the participants received the phantom experiment setup and five patient-measured lung motion traces. The participants used their MLTT approach to localize the moving target during an experimental SABR phantom treatment. The challenge was open to any participant, and participants could complete either one or both parts of the challenge. For both the in silico and experimental studies the MLTT results were analyzed and ranked using the prospectively defined metric of the percentage of the tracked target position being within 2 mm of the ground truth.

RESULTS

A total of 30 institutions registered and 15 result submissions were received, four for the in silico study and 11 for the experimental study. The participating MLTT approaches were: Accuray CyberKnife (2), Accuray Radixact (2), BrainLab Vero, C-RAD, and preclinical MLTT (5) on a conventional linear accelerator (Varian TrueBeam). For the in silico study the percentage of the 3D tracking error within 2 mm ranged from 50% to 92%. For the experimental study, the percentage of the 3D tracking error within 2 mm ranged from 39% to 96%.

CONCLUSIONS

A common methodology for measuring the accuracy of MLTT approaches has been developed and used to benchmark preclinical and commercial approaches retrospectively and prospectively. Several MLTT approaches were able to track the target with sub-millimeter accuracy and precision. The study outcome paves the way for broader clinical implementation of MLTT. MATCH is live, with datasets and analysis software being available online at https://www.aapm.org/GrandChallenge/MATCH/ to support future research.

A novel complementation method of an acoustic shadow region utilizing a convolutional neural network for ultrasound-guided therapy

PURPOSE

Noise-free ultrasound images are essential for organ monitoring during regional ultrasound-guided therapy. When the affected area is located under the ribs, however, acoustic shadow is caused by the reflection of sound from hard tissues such as bone, and the image is output with missing information in this region. Therefore, in the present study, we attempt to complement the image in the missing area.

METHODS

The overall flow of the complementation method to generate a shadow-free composite image is as follows. First, we constructed a binary classification method for the presence or absence of acoustic shadow on a phantom kidney based on a convolutional neural network. Second, we created a composite shadow-free image by searching for a suitable image from a time-series database and superimposing the corresponding area without shadow onto the missing area of the target image. In addition, we constructed and verified an automatic kidney mask generation method utilizing U-Net.

RESULTS

The complementation accuracy for kidney tracking could be enhanced by template matching. Zero-mean normalized cross-correlation (ZNCC) values after complementation were higher than that of before complementation under four different data generation conditions: (i) changing the position of the bed of the robotic ultrasound diagnostic system in the translational direction, (ii) changing the probe angle in the translational direction, (iii) with the addition of rotational motion of the probe to condition (ii). Although there was large variation in the shape of the kidney contour in condition (iii), the proposed method improved the ZNCC value from 0.5437 to 0.5807.

CONCLUSIONS

The effectiveness of the proposed method was demonstrated in phantom experiments. Verification of its effectiveness in real organs is necessary in future study.

Markerless 3D tumor tracking during single-fraction free-breathing 10MV flattening-filter-free stereotactic lung radiotherapy

BACKGROUND AND PURPOSE

Positional verification during single fraction lung SBRT could increase confidence and reduce the chance of geographic miss. As planar 2DkV imaging during VMAT irradiation is already available on current linear accelerators, markerless tracking based on these images could offer widely available and low-cost verification. We evaluated treatment delivery data and template matching and triangulation for 3D-positional verification during free-breathing, single fraction (34 Gy), 10 MV flattening-filter-free VMAT lung SBRT.

METHODS AND MATERIALS

Tumor tracking based on kV imaging at 7 frames/second was performed during irradiation in 6 consecutive patients (7 lesions). Tumor characteristics, tracking ability, comparison of tracking displacements with CBCT-based shifts, tumor position relative to the PTV margin, and treatment times are reported.

RESULTS

For all 7 lesions combined, 3D tumor position could be determined for, on average, 71% (51-84%) of the total irradiation time. Visually estimated tracked and automated match +/- manually-corrected CBCT-derived displacements generally agreed within 1 mm. During the tracked period, the longitudinal, lateral and vertical position of the tumor was within a 5 mm/3 mm PTV margin 95.5/85.3% of the time. The PTV was derived from the ITV including all tumor motion. The total time from first set-up imaging to end of the last arc was 18.3-31.4 min (mean = 23.4, SD = 4.1).

CONCLUSION

3D positional verification during irradiation of small lung targets with limited motion, was feasible. However, tumor position could not be determined for on average 29% of the time. Improvements are needed. Margin reduction may be feasible. Imaging and delivery of a single 34 Gy fraction was fast.

Markerless Real-Time 3-Dimensional kV Tracking of Lung Tumors During Free Breathing Stereotactic Radiation Therapy

Purpose

Accurate verification of tumor position during irradiation could reduce the probability of target miss. We investigated whether a commercial gantry-mounted 2-dimensional (2D) kilo-voltage (kV) imaging system could be used for real-time 3D tumor tracking during volumetric modulated arc therapy (VMAT) lung stereotactic body radiation therapy (SBRT). Markerless tumor tracking on kV fluoroscopic images was validated using a life-like moving thorax phantom and subsequently performed on kV images continuously acquired before and during free-breathing VMAT lung SBRT.

Methods and Materials

The 3D-printed/molded phantom containing 3 lung tumors was moved in 3D in TrueBeam developer mode, using simulated regular/irregular breathing patterns. Planar kV images were acquired at 7 frames/s during 11 Gy/fraction 10 MV flattening filter free VMAT. 2D reference templates were created for each gantry angle using the planning 4D computed tomography inspiration phase. kV images and templates were matched using normalized cross correlation to determine 2D tumor position, and triangulation of 2D matched projections determined the third dimension. 3D target tracking performed on cone beam computed tomography projection data from 18 patients (20 tumors) and real-time online tracking data from 2 of the 18 patients who underwent free-breathing VMAT lung SBRT are presented.

Results

For target 1 and 2 of the phantom (upper lung and middle/medial lung, mean density –130 Hounsfield units), 3D results within 2 mm of the known position were present in 92% and 96% of the kV projections, respectively. For target 3 (inferior lung, mean density –478 Hounsfield units) this dropped to 80%. Benchmarking against the respiratory signal, 13/20 (65%) tumors (10.5 ± 11.1 cm³) were considered successfully tracked on the cone beam computed tomography data. Tracking was less successful (≤50% of the time) in 7/20 (1.2 ± 1.5 cm³). Successful online tracking during lung SBRT was demonstrated.

Conclusions

3D markerless tumor tracking on a standard linear accelerator using template matching and triangulation of free-breathing kV fluoroscopic images was possible in 65% of small lung tumors. The smallest tumors were most challenging.

Visually guided inspiration breath-hold facilitated with nasal high flow therapy in locally advanced lung cancer

BACKGROUND AND PURPOSE

Reducing breathing motion in radiotherapy (RT) is an attractive strategy to reduce margins and better spare normal tissues. The objective of this prospective study (NCT03729661) was to investigate the feasibility of irradiation of non-small cell lung cancer (NSCLC) with visually guided moderate deep inspiration breath-hold (IBH) using nasal high-flow therapy (NHFT).

MATERIAL AND METHODS

Locally advanced NSCLC patients undergoing photon RT were given NHFT with heated humidified air (flow: 40 L/min with 80% oxygen) through a nasal cannula. IBH was monitored by optical surface tracking (OST) with visual feedback. At a training session, patients had to hold their breath as long as possible, without and with NHFT. For the daily cone beam CT (CBCT) and RT treatment in IBH, patients were instructed to keep their BH as long as it felt comfortable. OST was used to analyze stability and reproducibility of the BH, and CBCT to analyze daily tumor position. Subjective tolerance was measured with a questionnaire at 3 time points.

RESULTS

Of 10 included patients, 9 were treated with RT. Seven (78%) completed the treatment with NHFT as planned. At the training session, the mean BH length without NHFT was 39 s (range 15-86 s), and with NHFT 78 s (range 29-223 s) (p = .005). NHFT prolonged the BH duration by a mean factor of 2.1 (range 1.1-3.9s). The mean overall stability and reproducibility were within 1 mm. Subjective tolerance was very good with the majority of patients having no or minor discomfort caused by the devices. The mean inter-fraction tumor position variability was 1.8 mm (-1.1-8.1 mm;SD 2.4 mm).

CONCLUSION

NHFT for RT treatment of NSCLC in BH is feasible, well tolerated and significantly increases the breath-hold duration. Visually guided BH with OST is stable and reproducible. We therefore consider this an attractive patient-friendly approach to treat lung cancer patients with RT in BH.

Clinical Implications of Geometric and Dosimetric Uncertainties of Inter- and Intra-Fractional Movement during Volumetric Modulated Arc Therapy for Breast Cancer Patients

Simple Summary

Radiotherapy is an essential treatment modality for breast cancer. Compared to conventional radiotherapy techniques, modern radiotherapy with fewer fractions and smaller target volumes requires higher accuracy. Image-guidance using cone-beam computed tomography (CBCT) is one of the most common methods used for positional verification before treatment. This study reports geometric and dosimetric outcomes evaluated by analyzing CBCT images acquired before and during treatments. The positional change and internal movement of the patient were less than 1 cm in most cases without significant deviation in the dosimetric parameters of interest. However, there were cases involving extreme variation, which resulted in insufficient radiation delivered to the target areas and increased radiation exposure to adjacent normal organs. The results of the current study suggest that unexpected intra-fractional motion may occur, prompting for marginal adaptation in selected patients who are deemed to suffer from this kind of event.

Abstract

With the introduction of modern sophisticated radiotherapy (RT) techniques, the significance of accuracy has increased considerably. This study evaluated the necessity of pre-treatment and intra-fractional cone-beam computed tomography (CBCT) by analyzing inter- and intra-fractional CBCT images of breast cancer patients receiving RT. From 57 patients, 1206 pre-treatment CBCT and 1067 intra-fractional CBCT images were collected. Geometric movements of patients were measured quantitively in both inter- and intra-fractional CBCT, and changes in dosimetric parameters were evaluated in selected patients with extreme intra-fractional movement. For right-sided breast cancer patients, left-sided breast cancer patients treated using deep-inspiration breath hold (DIBH), and left-sided breast cancer patients treated using continuous positive airway pressure (CPAP), median inter-fractional deviations were 0.53 (range 0.06–2.98) cm, 0.66 (range 0.08–4.41) cm, and 0.69 (range 0.04–3.80) cm, and median intra-fractional deviations were 0.14 (range 0.00–0.62) cm, 0.23 (range 0.02–0.96) cm, and 0.24 (0.00–1.15) cm, respectively. Modified plans reflecting large changes in intra-fractional position in 10 selected cases revealed insufficient target coverage in seven cases and more than 20-fold increase in the volume of heart receiving at least 25 Gy in two cases. Intra-fractional verification, as well as pre-treatment verification, might be considered in patients using DIBH or CPAP.

Pre-treatment and real-time image guidance for a fixed-beam radiotherapy system

PURPOSE

A radiotherapy system with a fixed treatment beam and a rotating patient positioning system could be smaller, more robust and more cost effective compared to conventional rotating gantry systems. However, patient rotation could cause anatomical deformation and compromise treatment delivery. In this work, we demonstrate an image-guided treatment workflow with a fixed beam prototype system that accounts for deformation during rotation to maintain dosimetric accuracy.

METHODS

The prototype system consists of an Elekta Synergy linac with the therapy beam orientated downward and a custom-built patient rotation system (PRS). A phantom that deforms with rotation was constructed and rotated within the PRS to quantify the performance of two image guidance techniques: motion compensated cone-beam CT (CBCT) for pre-treatment volumetric imaging and kilovoltage infraction monitoring (KIM) for real-time image guidance. The phantom was irradiated with a 3D conformal beam to evaluate the dosimetric accuracy of the workflow.

RESULTS

The motion compensated CBCT was used to verify pre-treatment position and the average calculated position was within -0.3 ± 1.1 mm of the phantom's ground truth position at 0°. KIM tracked the position of the target in real-time as the phantom was rotated and the average calculated position was within -0.2 ± 0.8 mm of the phantom's ground truth position. A 3D conformal treatment delivered on the prototype system with image guidance had a 3%/2 mm gamma pass rate of 96.3% compared to 98.6% delivered using a conventional rotating gantry linac.

CONCLUSIONS

In this work, we have shown that image guidance can be used with fixed-beam treatment systems to measure and account for changes in target position in order to maintain dosimetric coverage during horizontal rotation. This treatment modality could provide a viable treatment option when there insufficient space for a conventional linear accelerator or where the cost is prohibitive.

Scatter imaging during lung stereotactic body radiation therapy characterized with phantom studies

By collecting photons scattered out of the therapy beam, scatter imaging creates images of the treated volume. Two phantoms were used to assess the possible application of scatter imaging for markerless tracking of lung tumors during stereotactic body radiation therapy (SBRT) treatment. A scatter-imaging camera was assembled with a CsI flat-panel detector and a 5 mm diameter pinhole collimator. Scatter images were collected during the irradiation of phantoms with megavoltage photons. To assess scatter image quality, spherical phantom lung tumors of 2.1-2.8 cm diameters were placed inside a static, anthropomorphic phantom. To show the efficacy of the technique with a moving target (3 cm diameter), the position of a simulated tumor was tracked in scatter images during sinusoidal motion (15 mm amplitude, 0.25 Hz frequency) in a dynamic lung phantom in open-field, dynamic conformal arc (DCA), and volumetric modulated arc therapy (VMAT) deliveries. Anatomical features are identifiable on static phantom scatter images collected with 10 MU of delivered dose (2.1 cm diameter lung tumor contrast-to-noise ratio of 4.4). The contrast-to-noise ratio increases with tumor size and delivered dose. During dynamic motion, the position of the 3.0 cm diameter lung tumor was identified with a root-mean-square error of 0.8, 1.2, and 2.9 mm for open field (0.3 s frame integration), DCA (0.5 s), and VMAT (0.5 s), respectively. Based on phantom studies, scatter imaging is a potential technique for markerless lung tumor tracking during SBRT without additional imaging dose. Quality scatter images may be collected at low, clinically relevant doses (10 MU). Scatter images are capable of sub-millimeter tracking precision, but modulation decreases accuracy.

Automated MV markerless tumor tracking for VMAT

Tumor tracking during radiotherapy treatment can improve dose accuracy, conformity and sparing of healthy tissue. Many methods have been introduced to tackle this challenge utilizing multiple imaging modalities, including a template matching based approach using the megavoltage (MV) on-board portal imager demonstrated on 3D conformal treatments. However, the complexity of treatments is evolving with the introduction of VMAT and IMRT, and successful motion management is becoming more important due to a trend towards hypofractionation. We have developed a markerless lung tumor tracking algorithm, utilizing the electronic portal imager (EPID) of the treatment machine. The algorithm has been specifically adapted to track during complex treatment deliveries with gantry and MLC motion. The core of the algorithm is an adaptive template matching method that relies on template stability metrics and local relative orientations to perform multiple feature tracking simultaneously. Only a single image is required to initialize the algorithm and features are automatically added, modified or removed in response to the input images. This algorithm was evaluated against images collected during VMAT arcs of a dynamic thorax phantom. Dynamic phantom images were collected during radiation delivery for multiple lung SBRT breathing traces and an example patient data set. The tracking error was 1.34 mm for the phantom data and 0.68 mm for the patient data. A multi-region, markerless tracking algorithm has been developed, capable of tracking multiple features simultaneously without requiring any other a priori information. This novel approach delivers robust target localization during complex treatment delivery. The reported tracking error is similar to previous reports for 3D conformal treatments.

Delivery of magnetic resonance-guided single-fraction stereotactic lung radiotherapy

BACKGROUND AND PURPOSE

Single-fraction stereotactic ablative radiotherapy (SABR) is an effective treatment for early-stage lung cancer, but concerns remain about the accurate delivery of SABR in a single session. We evaluated the delivery of single-fraction lung SABR using magnetic resonance (MR)-guidance.

MATERIALS AND METHODS

An MR-simulation was performed in 17 patients, seven of whom were found to be unsuitable, largely due to unreliable tracking of small tumors. Ten patients underwent single-fraction SABR to 34 Gy on a 0.35 T MR-linac system, with online plan adaptation. Gated breath-hold SABR was delivered using a planning target volume (PTV) margin of 5 mm, and a 3 mm gating window. Continuous MR-tracking of the gross tumor volume (GTVt) was performed in sagittal plane, with visual patient feedback provided using an in-room monitor. The real-time MR images were analyzed to determine precision and efficiency of gated delivery.

RESULTS

All but one patient completed treatment in a single session. The median total in-room procedure was 120 min, with a median SABR delivery session of 39 min. Review of 7.4 h of cine-MR imaging revealed a mean GTVt coverage by the PTV during beam-on of 99.6%. Breath-hold patterns were variable, resulting in a mean duty cycle efficiency of 51%, but GTVt coverage was not influenced due to real-time MR-guidance. On-table adaptation improved PTV coverage, but had limited impact on GTV doses.

CONCLUSIONS

Single-fraction gated SABR of lung tumors can be performed with high precision using MR-guidance. However, improvements are needed to ensure MR-tracking of small tumors, and to reduce treatment times.

The first prospective implementation of markerless lung target tracking in an experimental quality assurance procedure on a standard linear accelerator

The ability to track tumour motion without implanted markers on a standard linear accelerator (linac) could enable wide access to real-time adaptive radiotherapy for cancer patients. We previously have retrospectively validated a method for 3D markerless target tracking using intra-fractional kilovoltage (kV) projections acquired on a standard linac. This paper presents the first prospective implementation of markerless lung target tracking on a standard linac and its quality assurance (QA) procedure. The workflow and the algorithm developed to track the 3D target position during volumetric modulated arc therapy treatment delivery were optimised. The linac was operated in clinical QA mode, while kV projections were streamed to a dedicated computer using a frame-grabber software. The markerless target tracking accuracy and precision were measured in a lung phantom experiment under the following conditions: static localisation of seven distinct positions, dynamic localisation of five patient-measured motion traces, and dynamic localisation with treatment interruption. The QA guidelines were developed following the AAPM Task Group 147 report with the requirement that the tracking margin components, the margins required to account for tracking errors, did not exceed 5 mm in any direction. The mean tracking error ranged from 0.0 to 0.9 mm (left-right), -0.6 to  -0.1 mm (superior-inferior) and  -0.7 to 0.1 mm (anterior-posterior) over the three tests. Larger errors were found in cases with large left-right or anterior-posterior and small superior-inferior motion. The tracking margin components did not exceed 5 mm in any direction and ranged from 0.4 to 3.2 mm (left-right), 0.7 to 1.6 mm (superior-inferior) and 0.8 to 1.5 mm (anterior-posterior). This study presents the first prospective implementation of markerless lung target tracking on a standard linac and provides a QA procedure for its safe clinical implementation, potentially enabling real-time adaptive radiotherapy for a large population of lung cancer patients.

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.

Feasibility of markerless 3D position monitoring of the central airways using kilovoltage projection images: Managing the risks of central lung stereotactic radiotherapy

BACKGROUND AND PURPOSE

Central lung stereotactic body radiotherapy (SBRT) can cause proximal bronchial tree (PBT) toxicity. Information on PBT position relative to the high-dose could aid risk management. We investigated template matching + triangulation for high-frequency markerless 3D PBT position monitoring.

MATERIALS AND METHODS

Kilovoltage projections of a moving phantom (full-fan cone-beam CT [CBCT, 15 frames/second] without MV irradiation: 889 images/dataset + CBCT and 7 frames/second fluoroscopy with MV irradiation) and ten patients undergoing free-breathing stereotactic/hypofractionated lung irradiation (full-fan CBCT without MV irradiation, 470-500 images/dataset) were retrospectively analyzed. 2D PBT reference templates (1 filtered digitally reconstructed radiograph/°) were created from planning CT data. Using normalized cross-correlation, templates were matched to projection images for 2D position. Multiple registrations were triangulated for 3D position.

RESULTS

For the phantom, 2D right/left PBT position could be determined in 86.6/75.1% of the CBCT dataset without MV irradiation, and 3D position (excluding first 20° due to the minimum triangulation angle) in 84.7/72.7%. With MV irradiation, this was up to 2% less. For right/left PBT, root-mean-square errors of measured versus "known" position were 0.5/0.8, 0.4-0.5/0.7, and 0.4/0.5-0.6 mm for left-right, superior-inferior, and anterior-posterior directions, respectively. 2D PBT position was determined in, on average, 89.8% of each patient dataset (range: 79.4-99.2%), and 3D position (excluding first 20°) in 85.1% (range: 67.9-99.6%). Motion was mainly superior-inferior (range: 4.5-13.6 mm, average: 8.5 mm).

CONCLUSIONS

High-frequency 3D PBT position verification during free-breathing is technically feasible using markerless template matching + triangulation of kilovoltage projection images acquired during gantry rotation. Applications include organ-at-risk position monitoring during central lung SBRT.