MLC tracking for lung SABR reduces planning target volumes and dose to organs at risk

Benchmarking machine learning-based real-time respiratory signal predictors in 4D SBRT

BACKGROUND

Stereotactic body radiotherapy of thoracic and abdominal tumors has to account for respiratory intrafractional tumor motion. Commonly, an external breathing signal is continuously acquired that serves as a surrogate of the tumor motion and forms the basis of strategies like breathing-guided imaging and gated dose delivery. However, due to inherent system latencies, there exists a temporal lag between the acquired respiratory signal and the system response. Respiratory signal prediction models aim to compensate for the time delays and to improve imaging and dose delivery.

PURPOSE

The present study explores and compares six state-of-the-art machine and deep learning-based prediction models, focusing on real-time and real-world applicability. All models and data are provided as open source and data to ensure reproducibility of the results and foster reuse.

METHODS

The study was based on 2502 breathing signals (t t o t a l ≈ 90 $t_{total} \approx 90$  h) acquired during clinical routine, split into independent training (50%), validation (20%), and test sets (30%). Input signal values were sampled from noisy signals, and the target signal values were selected from corresponding denoised signals. A standard linear prediction model (Linear), two state-of-the-art models in general univariate signal prediction (Dlinear, Xgboost), and three deep learning models (Lstm, Trans-Enc, Trans-TSF) were chosen. The prediction performance was evaluated for three different prediction horizons (480, 680, and 920 ms). Moreover, the robustness of the different models when applied to atypical, that is, out-of-distribution (OOD) signals, was analyzed.

RESULTS

The Lstm model achieved the lowest normalized root mean square error for all prediction horizons. The prediction errors only slightly increased for longer horizons. However, a substantial spread of the error values across the test signals was observed. Compared to typical, that is, in-distribution test signals, the prediction accuracy of all models decreased when applied to OOD signals. The more complex deep learning models Lstm and Trans-Enc showed the least performance loss, while the performance of simpler models like Linear dropped the most. Except for Trans-Enc, inference times for the different models allowed for real-time application.

CONCLUSION

The application of the Lstm model achieved the lowest prediction errors. Simpler prediction filters suffer from limited signal history access, resulting in a drop in performance for OOD signals.

BIOGUIDE-X: A First-in-Human Study of the Performance of Positron Emission Tomography-Guided Radiation Therapy

PURPOSE

Positron emission tomography (PET)-guided radiation therapy is a novel tracked dose delivery modality that uses real-time PET to guide radiation therapy beamlets. The BIOGUIDE-X study was performed with sequential cohorts of participants to (1) identify the fluorodeoxyglucose (FDG) dose for PET-guided therapy and (2) confirm that the emulated dose distribution was consistent with a physician-approved radiation therapy plan.

METHODS AND MATERIALS

This prospective study included participants with at least 1 FDG-avid targetable primary or metastatic tumor (2-5 cm) in the lung or bone. For cohort I, a modified 3 + 3 design was used to determine the FDG dose that would result in adequate signal for PET-guided therapy. For cohort II, PET imaging data were collected on the X1 system before the first and last fractions among patients undergoing conventional stereotactic body radiation therapy. PET-guided therapy dose distributions were modeled on the patient's computed tomography anatomy using the collected PET data at each fraction as input to an "emulated delivery" and compared with the physician-approved plan.

RESULTS

Cohort I demonstrated adequate FDG activity in 6 of 6 evaluable participants (100.0%) with the first injected dose level of 15 mCi FDG. In cohort II, 4 patients with lung tumors and 5 with bone tumors were enrolled, and evaluable emulated delivery data points were collected for 17 treatment fractions. Sixteen of the 17 emulated deliveries resulted in dose distributions that were accurate with respect to the approved PET-guided therapy plan. The 17th data point was just below the 95% threshold for accuracy (dose-volume histogram score = 94.6%). All emulated fluences were physically deliverable. No toxicities were attributed to multiple FDG administrations.

CONCLUSIONS

PET-guided therapy is a novel radiation therapy modality in which a radiolabeled tumor can act as its own fiducial for radiation therapy targeting. Emulated therapy dose distributions calculated from continuously acquired real-time PET data were accurate and machine-deliverable in tumors that were 2 to 5 cm in size with adequate FDG signal characteristics.

Real-time 4D MRI using MR signature matching (MRSIGMA) on a 1.5T MR-Linac system

Objective. To develop real-time 4D MRI using MR signature matching (MRSIGMA) for volumetric motion imaging in patients with pancreatic cancer on a 1.5T MR-Linac system.Approach. Two consecutive MRI scans with 3D golden-angle radial stack-of-stars acquisitions were performed on ten patients with inoperable pancreatic cancer. The complete first scan (905 angles) was used to compute a 4D motion dictionary including ten pairs of 3D motion images and signatures. The second scan was used for real-time imaging, where each angle (275 ms) was processed separately to match it to one of the dictionary entries. The complete second scan was also used to compute a 4D reference to assess motion tracking performance.Dicecoefficients of the gross tumor volume (GTV) and two organs-at-risk (duodenum-stomach and small bowel) were calculated between signature matching and reference. In addition, volume changes, displacements, center of mass shifts, andDicescores over time were calculated to characterize motion.Main results. Total imaging latency of MRSIGMA (acquisition + matching) was less than 300 ms. TheDicecoefficients were 0.87 ± 0.06 (GTV), 0.86 ± 0.05 (duodenum-stomach), and 0.85 ± 0.05 (small bowel), which indicate high accuracy (high mean value) and low uncertainty (low standard deviation) of MRSIGMA for real-time motion tracking. The center of mass shift was 3.1 ± 2.0 mm (GTV), 5.3 ± 3.0 mm (duodenum-stomach), and 3.4 ± 1.5 mm (small bowel). TheDicescores over time (0.97 ± [0.01-0.03]) were similarly high for MRSIGMA and reference scans in all the three contours.Significance. This work demonstrates the feasibility of real-time 4D MRI using MRSIGMA for volumetric motion tracking on a 1.5T MR-Linac system. The high accuracy and low uncertainty of real-time MRSIGMA is an essential step towards continuous treatment adaptation of tumors affected by real-time respiratory motion and could ultimately improve treatment safety by optimizing ablative dose delivery near gastrointestinal organs.

Film measurement and analytical approach for assessing treatment accuracy and latency in a magnetic resonance-guided radiotherapy system

PURPOSE

We measure the dose distribution of gated delivery for different target motions and estimate the gating latency in a magnetic resonance-guided radiotherapy (MRgRT) system.

METHOD

The dose distribution accuracy of the gated MRgRT system (MRIdian, Viewray) was investigated using an in-house-developed phantom that was compatible with the magnetic field and gating method. This phantom contains a simulated tumor and a radiochromic film (EBT3, Ashland, Inc.). To investigate the effect of the number of beam switching and target velocity on the dose distribution, two types of target motions were applied. One is that the target was periodically moved at a constant velocity of 5 mm/s with different pause times (0, 1, 3, 10, and 20 s) between the motions. During different pause times, different numbers of beams were switched on/off. The other one is that the target was moved at velocities of 3, 5, 8, and 10 mm/s without any pause (i.e., continuous motion). The gated method was applied to these motions at MRIdian, and the dose distributions in each condition were measured using films. To investigate the relation between target motion and dose distribution in the gating method, we compared the results of the gamma analysis of the calculated and measured dose distributions. Moreover, we analytically estimated the gating latencies from the dose distributions measured using films and the gamma analysis results.

RESULTS

The gamma pass rate linearly decreased with increasing beam switching and target velocity. The overall gating latencies of beam-hold and beam-on were 0.51 ± 0.17 and 0.35 ± 0.05 s, respectively.

CONCLUSIONS

Film measurements highlighted the factors affecting the treatment accuracy of the gated MRgRT system. Our analytical approach, employing gamma analysis on films, can be used to estimate the overall latency of the gated MRgRT system.

Integrated MRI-guided radiotherapy - opportunities and challenges

MRI can help to categorize tissues as malignant or non-malignant both anatomically and functionally, with a high level of spatial and temporal resolution. This non-invasive imaging modality has been integrated with radiotherapy in devices that can differentially target the most aggressive and resistant regions of tumours. The past decade has seen the clinical deployment of treatment devices that combine imaging with targeted irradiation, making the aspiration of integrated MRI-guided radiotherapy (MRIgRT) a reality. The two main clinical drivers for the adoption of MRIgRT are the ability to image anatomical changes that occur before and during treatment in order to adapt the treatment approach, and to image and target the biological features of each tumour. Using motion management and biological targeting, the radiation dose delivered to the tumour can be adjusted during treatment to improve the probability of tumour control, while simultaneously reducing the radiation delivered to non-malignant tissues, thereby reducing the risk of treatment-related toxicities. The benefits of this approach are expected to increase survival and quality of life. In this Review, we describe the current state of MRIgRT, and the opportunities and challenges of this new radiotherapy approach.

MArkerless image Guidance using Intrafraction Kilovoltage x-ray imaging (MAGIK): study protocol for a phase I interventional study for lung cancer radiotherapy

INTRODUCTION

In radiotherapy, tumour tracking leads the radiation beam to accurately target the tumour while it moves in a complex and unpredictable way due to respiration. Several tumour tracking techniques require the implantation of fiducial markers around the tumour, a procedure that involves unnecessary risks and costs. Markerless tumour tracking (MTT) negates the need for implanted markers, potentially enabling accurate and optimal radiotherapy in a non-invasive way.

METHODS AND ANALYSIS

We will perform a phase I interventional trial called MArkerless image Guidance using Intrafraction Kilovoltage x-ray imaging (MAGIK) to investigate the technical feasibility of the MTT technology developed at the University of Sydney (sponsor). 30 participants will undergo the current standard of care lung stereotactic ablative radiation therapy, with the exception that kilovoltage X-ray images will be acquired continuously during treatment delivery to enable MTT. If MTT indicates that the mean lung tumour position has shifted >3 mm, a warning message will be displayed to indicate the need for a treatment intervention. The radiation therapist will then pause the treatment, shift the treatment couch to account for the shift in tumour position and resume the treatment. Participants will be implanted with fiducial markers, which act as the ground truth for evaluating the accuracy of MTT. MTT is considered feasible if the tracking accuracy is <3 mm in each dimension for >80% of the treatment time.

ETHICS AND DISSEMINATION

The MAGIK trial has received ethical approval from The Alfred Human Research Ethics Committee and has been registered with ClinicalTrials.gov with the Identifier: NCT04086082. Estimated time of first recruitment is early 2022. The study recruitment and data analysis phases will be performed concurrently. Treatment for all 30 participants is expected to be completed within 2 years and participant follow-up within a total duration of 7 years. Findings will be disseminated through peer-reviewed publications and conference presentations.

TRIAL REGISTRATION NUMBER

NCT04086082; Pre-result.

A review of artificial intelligence applications for motion tracking in radiotherapy

During radiotherapy, the organs and tumour move as a result of the dynamic nature of the body; this is known as intrafraction motion. Intrafraction motion can result in tumour underdose and healthy tissue overdose, thereby reducing the effectiveness of the treatment while increasing toxicity to the patients. There is a growing appreciation of intrafraction target motion management by the radiation oncology community. Real-time image-guided radiation therapy (IGRT) can track the target and account for the motion, improving the radiation dose to the tumour and reducing the dose to healthy tissue. Recently, artificial intelligence (AI)-based approaches have been applied to motion management and have shown great potential. In this review, four main categories of motion management using AI are summarised: marker-based tracking, markerless tracking, full anatomy monitoring and motion prediction. Marker-based and markerless tracking approaches focus on tracking the individual target throughout the treatment. Full anatomy algorithms monitor for intrafraction changes in the full anatomy within the field of view. Motion prediction algorithms can be used to account for the latencies due to the time for the system to localise, process and act.

Stereotactic radiotherapy for early stage non-small cell lung cancer: current standards and ongoing research

Stereotactic body radiation therapy (SBRT) allows for the non-invasive and precise delivery of ablative radiation dose. The use and availability of SBRT has increased rapidly over the past decades. SBRT has been proven to be a safe, effective and efficient treatment for early stage non-small cell lung cancer (NSCLC) and is presently considered the standard of care in the treatment of medically or functionally inoperable patients. Evidence from prospective randomized trials on the optimal treatment of patients deemed medically operable remains owing, as three trials comparing SBRT to surgery in this cohort were terminated prematurely due to poor accrual. Yet, SBRT in early stage NSCLC is associated with favorable toxicity profiles and excellent rates of local control, prompting discussion in regard of the treatment of medically operable patients, where the standard of care currently remains surgical resection. Although local control in early stage NSCLC after SBRT is high, distant failure remains an issue, prompting research interest to the combination of SBRT and systemic treatment. Evolving advances in SBRT technology further facilitate the safe treatment of patients with medically or anatomically challenging situations. In this review article, we discuss international guidelines and the current standard of care, ongoing clinical challenges and future directions from the clinical and technical point of view.

AAPM Task Group 264: The safe clinical implementation of MLC tracking in radiotherapy

The era of real-time radiotherapy is upon us. Robotic and gimbaled linac tracking are clinically established technologies with the clinical realization of couch tracking in development. Multileaf collimators (MLCs) are a standard equipment for most cancer radiotherapy systems, and therefore MLC tracking is a potentially widely available technology. MLC tracking has been the subject of theoretical and experimental research for decades and was first implemented for patient treatments in 2013. The AAPM Task Group 264 Safe Clinical Implementation of MLC Tracking in Radiotherapy Report was charged to proactively provide the broader radiation oncology community with (a) clinical implementation guidelines including hardware, software, and clinical indications for use, (b) commissioning and quality assurance recommendations based on early user experience, as well as guidelines on Failure Mode and Effects Analysis, and (c) a discussion of potential future developments. The deliverables from this report include: an explanation of MLC tracking and its historical development; terms and definitions relevant to MLC tracking; the clinical benefit of, clinical experience with and clinical implementation guidelines for MLC tracking; quality assurance guidelines, including example quality assurance worksheets; a clinical decision pathway, future outlook and overall recommendations.

Dose-based optimisation for multi-leaf collimator tracking during radiation therapy

Motion in the patient anatomy causes a reduction in dose delivered to the target, while increasing dose to healthy tissue. Multi-leaf collimator (MLC) tracking has been clinically implemented to adapt dose delivery to account for intrafraction motion. Current methods shift the planned MLC aperture in the direction of motion, then optimise the new aperture based on the difference in fluence. The drawback of these methods is that 3D dose, a function of patient anatomy and MLC aperture sequence, is not properly accounted for. To overcome the drawback of current fluence-based methods, we have developed and investigated real-time adaptive MLC tracking based on dose optimisation. A novel MLC tracking algorithm, dose optimisation, has been developed which accounts for the moving patient anatomy by optimising the MLC based on the dose delivered during treatment, simulated using a simplified dose calculation algorithm. The MLC tracking with dose optimisation method was applied in silico to a prostate cancer VMAT treatment dataset with observed intrafraction motion. Its performance was compared to MLC tracking with fluence optimisation and, as a baseline, without MLC tracking. To quantitatively assess performance, we computed the dose error and 3D γ failure rate (2 mm/2%) for each fraction and method. Dose optimisation achieved a γ failure rate of (4.7 ± 1.2)% (mean and standard deviation) over all fractions, which was significantly lower than fluence optimisation (7.5 ± 2.9)% (Wilcoxon sign-rank test p < 0.01). Without MLC tracking, a γ failure rate of (15.3 ± 12.9)% was achieved. By considering the accumulation of dose in the moving anatomy during treatment, dose optimisation is able to optimise the aperture to actively target regions of underdose while avoiding overdose.

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

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

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.

Software simulation of tumour motion dose effects during flattened and unflattened ITV-based VMAT lung SBRT

Purpose

Restricted studies comparing different dose rate parameters are available while ITV-based VMAT lung SBRT planning leads to perform the analysis of the most suitable parameters of the external beams used. The special emphasis was placed on the impact of dose rate on dose distribution variations in target volumes due to interplay effects.

Methods

Four VMAT plans were calculated for 15 lung tumours using 6 MV photon beam quality (flattening filter FF vs. flattening filter free FFF beams) and maximum dose rate of 600 MU/min, 1000 MU/min and 1400 MU/min. Three kinds of motion simulations were performed finally giving 180 plans with perturbed dose distributions.

Results

6FFF-1400 MUs/min plans were characterized by the shortest beam on time (1.8 ± 0.2 min). Analysing the performed motion simulation results, the mean dose (Dmean) is not a sensitive parameter to related interplay effects. Looking for local maximum and local minimum doses, some discrepancies were found, but their significance was presented for individual patients, not for the whole cohort. The same was observed for other verified dose metrics.

Conclusions

Generally, the evaluation of VMAT robustness between FF and FFF concepts against interplay effect showed a negligible effect of simulated motion influence on tumour coverage among different photon beam quality parameters. Due to the lack of FFF beams, smaller radiotherapy centres are able to perform ITV-based VMAT lung SBRT treatment in a safe way. Radiotherapy department having FFF beams could perform safe, fast and efficient ITV-based VMAT lung SBRT without a concern about significance of interplay effects.

Anthropomorphic phantom for deformable lung and liver CT and MR imaging for radiotherapy

In this study, a functioning and ventilated anthropomorphic phantom was further enhanced for the purpose of CT and MR imaging of the lung and liver. A deformable lung, including respiratory tract was 3D printed. Within the lung's inner structures is a solid region shaped from a patient's lung tumour and six nitro-glycerine capsules as reference landmarks. The full internal mesh was coated, and the tumour filled, with polyorganosiloxane based gel. A moulded liver was created with an external casing of silicon filled with polyorganosiloxane gel and flexible plastic internal structures. The liver, fitted to the inferior portion of the right lung, moves along with the lung's ventilation. In the contralateral side, a cavity is designed to host a dosimeter, whose motion is correlated to the lung pressure. A 4DCT of the phantom was performed along with static and 4D T1 weighted MR images. The CT Hounsfield units (HU) for the flexible 3D printed material were -600-100 HU (lung and liver structures), for the polyorganosiloxane gel 30-120 HU (lung coating and liver filling) and for the silicon 650-800 HU (liver casing). The MR image intensity units were 0-40, 210-280 and 80-130, respectively. The maximum range of motion in the 4D imaging for the superior lung was 1-3.5 mm and 3.5-8 mm in the inferior portion. The liver motion was 5.5-8.0 mm at the tip and 5.7-10.0 mm at the dome. No measurable drift in motion was observed over a 2 h session and motion was reproducible over three different sessions for sin²(t), sin⁴(t) and a patient-like breathing curve with the interquartile range of amplitudes for all breathing cycles within 0.5 mm. The addition of features within the lung and of a deformable liver will allow the phantom to be used for imaging studies such as validation of 4DMRI and pseudo CT methods.

[Stereotactic body radiotherapy. How to better protect normal tissues?]

The use of stereotactic body radiotherapy (SBRT) has increased rapidly over the past decade. Optimal preservation of normal tissues is a major issue because of their high sensitivity to high doses per session. Extreme hypofractionation can convert random errors into systematic errors. Optimal preservation of organs at risk requires first of all a rigorous implementation of this technique according to published guidelines. The robustness of the imaging modalities used for planning, and training medical and paramedical staff are an integral part of these guidelines too. The choice of SBRT indications, dose fractionation, dose heterogeneity, ballistics, are also means of optimizing the protection of normal tissues. Non-coplanarity and tracking of moving targets allow dosimetric improvement in some clinical settings. Automatic planning could also improve normal tissue protection. Adaptive SBRT, with new image guided radiotherapy modalities such as MRI, could further reduce the risk of toxicity.

See, Think, and Act: Real-Time Adaptive Radiotherapy

The world is embracing the information age, with real-time data at hand to assist with many decisions. Similarly, in cancer radiotherapy we are inexorably moving toward using information in a smarter and faster fashion, to usher in the age of real-time adaptive radiotherapy. The three critical steps of real-time adaptive radiotherapy, aligned with driverless vehicle technology are a continuous see, think, and act loop. See: use imaging systems to probe the patient anatomy or physiology as it evolves with time. Think: use current and prior information to optimize the treatment using the available adaptive degrees of freedom. Act: deliver the real-time adapted treatment. This paper expands upon these three critical steps for real-time adaptive radiotherapy, provides a historical context, reviews the clinical rationale, and gives a future outlook for real-time adaptive radiotherapy.

Comparison of the automatic segmentation of multiple organs at risk in CT images of lung cancer between deep convolutional neural network-based and atlas-based techniques

BACKGROUND

In this study, a deep convolutional neural network (CNN)-based automatic segmentation technique was applied to multiple organs at risk (OARs) depicted in computed tomography (CT) images of lung cancer patients, and the results were compared with those generated through atlas-based automatic segmentation.

MATERIALS AND METHODS

An encoder-decoder U-Net neural network was produced. The trained deep CNN performed the automatic segmentation of CT images for 36 cases of lung cancer. The Dice similarity coefficient (DSC), the mean surface distance (MSD) and the 95% Hausdorff distance (95% HD) were calculated, with manual segmentation results used as the standard, and were compared with the results obtained through atlas-based segmentation.

RESULTS

For the heart, lungs and liver, both the deep CNN-based and atlas-based techniques performed satisfactorily (average values: 0.87 < DSC < 0.95, 1.8 mm < MSD < 3.8 mm, 7.9 mm < 95% HD <11 mm). For the spinal cord and the oesophagus, the two methods had statistically significant differences. For the atlas-based technique, the average values were 0.54 < DSC < 0.71, 2.6 mm < MSD < 3.1 mm and 9.4 mm < 95% HD <12 mm. For the deep CNN-based technique, the average values were 0.71 < DSC < 0.79, 1.2 mm < MSD <2.2 mm and 4.0 mm < 95% HD < 7.9 mm.

CONCLUSION

Our results showed that automatic segmentation based on a deep convolutional neural network enabled us to complete automatic segmentation tasks rapidly. Deep convolutional neural networks can be satisfactorily adapted to segment OARs during radiation treatment planning for lung cancer patients.

Intrafractional motion management in external beam radiotherapy

The recent advancements in radiotherapy technologies have made delivery of the highly conformal dose to the target volume possible. With the increasing popularity of delivering high dose per fraction in modern radiotherapy schemes such as in stereotactic body radiotherapy and stereotactic body ablative therapy, high degree of treatment precision is essential. In order to achieve this, we have to overcome the potential difficulties caused by patient instability due to immobilization problems; patient anxiety and random motion due to prolonged treatment time; tumor deformation and baseline shift during a treatment course. This is even challenging for patients receiving radiotherapy in the chest and abdominal regions because it is affected by the patient's respiration which inevitably leads to tumor motion. Therefore, monitoring of intrafractional motion has become increasingly important in modern radiotherapy. Major intrafractional motion management strategies including integration of respiratory motion in treatment planning; breath-hold technique; forced shallow breathing with abdominal compression; respiratory gating and dynamic real-time tumor tracking have been developed. Successful intrafractional motion management is able to reduce the planning target margin and ensures planned dose delivery to the target and organs at risk. Meanwhile, the emergency of MRI-linear accelerator has facilitated radiation-free real-time monitoring of soft tissue during treatment and could be the future modality in motion management. This review article summarizes the various approaches that deal with intrafractional target, organs or patient motion with discussion of their advantages and limitations. In addition, the potential future advancements including MRI-based tumor tracking are also discussed.

Single fraction computed tomography-guided high-dose-rate brachytherapy or stereotactic body radiotherapy for primary and metastatic lung tumors?

PURPOSE

To provide a pilot dosimetric study of computed tomography (CT)-guided high-dose-rate (HDR) brachytherapy (BRT) and stereotactic body radiotherapy (SBRT) for primary and metastatic lung lesions.

MATERIAL AND METHODS

For nine lung primary and metastasis patients, 3D image-based BRT plan using a single virtual catheter was planned for 34 Gy in single fraction to the gross tumor volume (GTV) + 3 mm margin to account for tumor deformation. These plans were compared to margin-based (MB-) and robustness optimized (RO-) SBRT, assuming the same tumor deformation under real-time tumor tracking. Consistent dose calculation was ensured for both BRT and SBRT plans using the same class of collapsed cone convolution superposition algorithm. Plan quality metrics were compared by Friedman tests and Wilcoxon t-tests.

RESULTS AND CONCLUSIONS

Brachytherapy plans showed significant higher GTV mean dose compared to MB- and RO-SBRT (122.2 Gy vs. 50.4 and 44.7 Gy, p < 0.05), and better dose gradient index (R50) = 2.9 vs. 4.3 and 8.4 for MB- and RO-SBRT, respectively. Dose constraints per the RTOG 0915 protocol were achieved for all critical organs except chest wall in BRT. All other dose-volume histograms (DVH) metrics are comparable between BRT and SBRT. Treatment delivery time of BRT and SBRT plans significantly increased and decreased with increasing GTV size, respectively. SBRT using advanced MLC tracking technique and non-coplanar VMAT can achieve comparable dosimetric quality to HDR BRT. Whether or not, the significantly higher GTV dose can increase killing of radioresistant tumor cells and offset the effect of tumor reoxygenation in single fraction BRT, requires further clinical investigation.

Non-coplanar VMAT combined with non-uniform dose prescription markedly reduces lung dose in breath-hold lung SBRT

BACKGROUND AND PURPOSE

In this retrospective treatment planning study, the effect of a uniform and non-uniform planning target volume (PTV) dose coverage as well as a coplanar and non-coplanar volumetric modulated arc therapy (VMAT) delivery approach for lung stereotactic body radiation therapy (SBRT) in deep inspiration breath-hold (DIBH) were compared.

MATERIALS AND METHODS

For 46 patients with lesions in the peripheral lungs, three different treatment plans were generated: First, a coplanar 220° VMAT sequence with a uniform PTV dose prescription (UC). Second, a coplanar 220° VMAT treatment plan with a non-uniform dose distribution in the PTV (nUC). Third, a non-coplanar VMAT dose delivery with four couch angles (0°, ±35°, 90°) and a non-uniform prescription (nUnC) was used. All treatment plans were optimized for pareto-optimality with respect to PTV coverage and ipsilateral lung dose. Treatment sequences were delivered on a flattening-filter-free linear accelerator and beam-on times were recorded. Dosimetric comparison between the three techniques was performed.

RESULTS

For the three scenarios (UC, nUC, nUnC), median gross tumor volume (GTV) doses were 63.4 ± 2.5, 74.4 ± 3.6, and 77.9 ± 3.8 Gy, and ipsilateral V10Gy lung volumes were 15.7 ± 6.1, 13.9 ± 4.7, and 12.0 ± 5.1%, respectively. Normal tissue complication probability of the ipsilateral lung was 3.9, 3.1, and 2.8%, respectively. The number of monitor units were 5141 ± 1174, 4104 ± 786, and 3657 ± 710 MU and the corresponding beam-on times were 177 ± 54, 143 ± 29, and 148 ± 26 s.

CONCLUSION

For SBRT treatments in DIBH, a non-uniform dose prescription in the PTV, combined with a non-coplanar VMAT arc arrangement, significantly spares the ipsilateral lung while increasing dose to the GTV without major treatment time increase.

Optimization of training periods for the estimation model of three-dimensional target positions using an external respiratory surrogate

Background

During therapeutic beam irradiation, an unvisualized three-dimensional (3D) target position should be estimated using an external surrogate with an estimation model. Training periods for the developed model with no additional imaging during beam irradiation were optimized using clinical data.

Methods

Dual-source 4D-CBCT projection data for 20 lung cancer patients were used for validation. Each patient underwent one to three scans. The actual target positions of each scan were equally divided into two equal parts: one for the modeling and the other for the validating session. A quadratic target position estimation equation was constructed during the modeling session. Various training periods for the session—i.e., modeling periods (T_M)—were employed: T_M ∈ {5,10,15,25,35} [s]. First, the equation was used to estimate target positions in the validating session of the same scan (intra-scan estimations). Second, the equation was then used to estimate target positions in the validating session of another temporally different scan (inter-scan estimations). The baseline drift of the surrogate and target between scans was corrected. Various training periods for the baseline drift correction—i.e., correction periods (T_Cs)—were employed: T_C ∈ {5,10,15; T_C ≤ T_M} [s]. Evaluations were conducted with and without the correction. The difference between the actual and estimated target positions was evaluated by the root-mean-square error (RMSE).

Results

The range of mean respiratory period and 3D motion amplitude of the target was 2.4–13.0 s and 2.8–34.2 mm, respectively. On intra-scan estimation, the median 3D RMSE was within 1.5–2.1 mm, supported by previous studies. On inter-scan estimation, median elapsed time between scans was 10.1 min. All T_Ms exhibited 75th percentile 3D RMSEs of 5.0–6.4 mm due to baseline drift of the surrogate and the target. After the correction, those for each T_Ms fell by 1.4–2.3 mm. The median 3D RMSE for both the 10-s T_M and the T_C period was 2.4 mm, which plateaued when the two training periods exceeded 10 s.

Conclusions

A widely-applicable estimation model for the 3D target positions during beam irradiation was developed. The optimal T_M and T_C for the model were both 10 s, to allow for more than one respiratory cycle.

Trial registration

UMIN000014825. Registered: 11 August 2014.

Electronic supplementary material

The online version of this article (10.1186/s13014-018-1019-9) contains supplementary material, which is available to authorized users.

Tumour auto-contouring on 2d cine MRI for locally advanced lung cancer: A comparative study

BACKGROUND AND PURPOSE

Radiotherapy guidance based on magnetic resonance imaging (MRI) is currently becoming a clinical reality. Fast 2d cine MRI sequences are expected to increase the precision of radiation delivery by facilitating tumour delineation during treatment. This study compares four auto-contouring algorithms for the task of delineating the primary tumour in six locally advanced (LA) lung cancer patients.

MATERIAL AND METHODS

Twenty-two cine MRI sequences were acquired using either a balanced steady-state free precession or a spoiled gradient echo imaging technique. Contours derived by the auto-contouring algorithms were compared against manual reference contours. A selection of eight image data sets was also used to assess the inter-observer delineation uncertainty.

RESULTS

Algorithmically derived contours agreed well with the manual reference contours (median Dice similarity index: ⩾0.91). Multi-template matching and deformable image registration performed significantly better than feature-driven registration and the pulse-coupled neural network (PCNN). Neither MRI sequence nor image orientation was a conclusive predictor for algorithmic performance. Motion significantly degraded the performance of the PCNN. The inter-observer variability was of the same order of magnitude as the algorithmic performance.

CONCLUSION

Auto-contouring of tumours on cine MRI is feasible in LA lung cancer patients. Despite large variations in implementation complexity, the different algorithms all have relatively similar performance.