Towards mid-position based Stereotactic Body Radiation Therapy on the MR-linac for central lung tumours

Background and purpose: Central lung tumours can be treated by magnetic resonance (MR)-guided radiotherapy. Complications might be reduced by decreasing the Planning Target Volume (PTV) using mid-position (midP)-based planning instead of Internal Target Volume (ITV)-based planning. In this study, we aimed to verify a method to automatically derive patient-specific PTV margins for midP-based planning, and show dosimetric robustness of midP-based planning for a 1.5T MR-linac.

Materials and methods: Central(n = 12) and peripheral(n = 4) central lung tumour cases who received 8x7.5 Gy were included. A midP-image was reconstructed from ten phases of the 4D-Computed Tomography using deformable image registration. The Gross Tumor Volume (GTV) was delineated on the midP-image and the PTV margin was automatically calculated based on van Herk’s margin recipe, treating the standard deviation of all Deformation Vector Fields, within the GTV, as random error component. Dosimetric robustness of midP-based planning for MR-linac using automatically derived margins was verified by 4D dose-accumulation. MidP-based plans were compared to ITV-based plans. Automatically derived margins were verified with manually derived margins.

Results: The mean D95% target coverage in GTV + 2 mm was 59.9 Gy and 62.0 Gy for midP- and ITV-based central lung plans, respectively. The mean lung dose was significantly lower for midP-based treatment plans (difference:-0.3 Gy; p<0.042). Automatically derived margins agreed within one millimeter with manually derived margins.

Conclusions: This retrospective study indicates that mid-position-based treatment plans for central lung Stereotactic Body Radiation Therapy yield lower OAR doses compared to ITV-based treatment plans on the MR-linac. Patient-specific GTV-to-PTV margins can be derived automatically and result in clinically acceptable target coverage.

Synthetic CT for single-fraction neoadjuvant partial breast irradiation on an MRI-linac

A synthetic computed tomography (sCT) is required for daily plan optimization on an MRI-linac. Yet, only limited information is available on the accuracy of dose calculations on sCT for breast radiotherapy. This work aimed to (1) evaluate dosimetric accuracy of treatment plans for single-fraction neoadjuvant partial breast irradiation (PBI) on a 1.5 T MRI-linac calculated on a) bulk-density sCT mimicking the current MRI-linac workflow and b) deep learning-generated sCT, and (2) investigate the number of bulk-density levels required. For ten breast cancer patients we created three bulk-density sCTs of increasing complexity from the planning-CT, using bulk-density for: (1) body, lungs, and GTV (sCT_BD1); (2) volumes for sCT_BD1plus chest wall and ipsilateral breast (sCT_BD2); (3) volumes for sCT_BD2plus ribs (sCT_BD3); and a deep learning-generated sCT (sCT_DL) from a 1.5 T MRI in supine position. Single-fraction neoadjuvant PBI treatment plans for a 1.5 T MRI-linac were optimized on each sCT and recalculated on the planning-CT. Image evaluation was performed by assessing mean absolute error (MAE) and mean error (ME) in Hounsfield Units (HU) between the sCTs and the planning-CT. Dosimetric evaluation was performed by assessing dose differences, gamma pass rates, and dose-volume histogram (DVH) differences. The following results were obtained (median across patients for sCT_BD1/sCT_BD2/sCT_BD3/sCT_DLrespectively): MAE inside the body contour was 106/104/104/75 HU and ME was 8/9/6/28 HU, mean dose difference in the PTV_GTVwas 0.15/0.00/0.00/-0.07 Gy, median gamma pass rate (2%/2 mm, 10% dose threshold) was 98.9/98.9/98.7/99.4%, and differences in DVH parameters were well below 2% for all structures except for the skin in the sCT_DL. Accurate dose calculations for single-fraction neoadjuvant PBI on an MRI-linac could be performed on both bulk-density and deep learning sCT, facilitating further implementation of MRI-guided radiotherapy for breast cancer. Balancing simplicity and accuracy, sCT_BD2showed the optimal number of bulk-density levels for a bulk-density approach.

DeepDose: a robust deep learning-based dose engine for abdominal tumours in a 1.5 T MRI radiotherapy system

We present a robust deep learning-based framework for dose calculations of abdominal tumours in a 1.5 T MRI radiotherapy system. For a set of patient plans, a convolutional neural network is trained on the dose of individual multi-leaf-collimator segments following the DeepDose framework. It can then be used to predict the dose distribution per segment for a set of patient anatomies. The network was trained using data from three anatomical sites of the abdomen: prostate, rectal and oligometastatic tumours. A total of 216 patient fractions were used, previously treated in our clinic with fixed-beam IMRT using the Elekta MR-linac. For the purpose of training, 176 fractions were used with random gantry angles assigned to each segment, while 20 fractions were used for the validation of the network. The ground truth data were calculated with a Monte Carlo dose engine at 1% statistical uncertainty per segment. For a total of 20 independent abdominal test fractions with the clinical angles, the network was able to accurately predict the dose distributions, achieving 99.4% ± 0.6% for the whole plan prediction at the 3%/3 mm gamma test. The average dose difference and standard deviation per segment was 0.3% ± 0.7%. Additional dose prediction on one cervical and one pancreatic case yielded high dose agreement of 99.9% and 99.8% respectively for the 3%/3 mm criterion. Overall, we show that our deep learning-based dose engine calculates highly accurate dose distributions for a variety of abdominal tumour sites treated on the MR-linac, in terms of performance and generality.

Proof-of-concept delivery of intensity modulated arc therapy on the Elekta Unity 1.5 T MR-linac

In this work we present the first delivery of intensity modulated arc therapy on the Elekta Unity 1.5 T MR-linac. The machine's current intensity modulated radiation therapy based control system was modified suitably to enable dynamic delivery of radiation, for the purpose of exploring MRI-guided radiation therapy adaptation modes in a research setting. The proof-of-concept feasibility was demonstrated by planning and delivering two types of plans, each investigating the performance of different parts of a dynamic treatment. A series of fixed-speed arc plans was used to show the high-speed capabilities of the gantry during radiation, while several fully modulated prostate plans-optimised following the volumetric modulated arc therapy approach-were delivered in order to establish the performance of its multi-leaf collimator and diaphragms. These plans were delivered to Delta⁴ Phantom+ MR and film phantoms passing the clinical quality assurance criteria used in our clinic. In addition, we also performed some initial MR imaging experiments during dynamic therapy, demonstrating that the impact of radiation and moving gantry/collimator components on the image quality is negligible. These results show that arc therapy is feasible on the Elekta Unity system. The machine's high performance components enable dynamic delivery during fast gantry rotation and can be controlled in a stable fashion to deliver fully modulated plans.

Delivered dose quantification in prostate radiotherapy using online 3D cine imaging and treatment log files on a combined 1.5T magnetic resonance imaging and linear accelerator system

BACKGROUND AND PURPOSE

Monitoring the intrafraction motion and its impact on the planned dose distribution is of crucial importance in radiotherapy. In this work we quantify the delivered dose for the first prostate patients treated on a combined 1.5T Magnetic Resonance Imaging (MRI) and linear accelerator system in our clinic based on online 3D cine-MR and treatment log files.

MATERIALS AND METHODS

A prostate intrafraction motion trace was obtained with a soft-tissue based rigid registration method with six degrees of freedom from 3D cine-MR dynamics with a temporal resolution of 8.5-16.9 s. For each fraction, all dynamics were also registered to the daily MR image used during the online treatment planning, enabling the mapping to this reference point. Moreover, each fraction's treatment log file was used to extract the timestamped machine parameters during delivery and assign it to the appropriate dynamic volume. These partial plans to dynamic volume combinations were calculated and summed to yield the delivered fraction dose. The planned and delivered dose distributions were compared among all patients for a total of 100 fractions.

RESULTS

The clinical target volume underwent on average a decrease of 2.2% ± 2.9% in terms of D99% coverage while bladder V62Gy was increased by 1.6% ± 2.3% and rectum V62Gy decreased by 0.2% ± 2.2%.

CONCLUSIONS

The first MR-linac dose reconstruction results based on prostate tracking from intrafraction 3D cine-MR and treatment log files are presented. Such a pipeline is essential for online adaptation especially as we progress to MRI-guided extremely hypofractionated treatments.

Dosimetric impact of soft-tissue based intrafraction motion from 3D cine-MR in prostate SBRT

To investigate the dosimetric impact of intrafraction translation and rotation motion of the prostate, as extracted from daily acquired post-treatment 3D cine-MR based on soft-tissue contrast, in extremely hypofractionated (SBRT) prostate patients. Accurate dose reconstruction is performed by using a prostate intrafraction motion trace which is obtained with a soft-tissue based rigid registration method on 3D cine-MR dynamics with a temporal resolution of 11 s. The recorded motion of each time-point was applied to the planning CT, resulting in the respective dynamic volume used for dose calculation. For each treatment fraction, the treatment delivery record was generated by proportionally splitting the plan into 11 s intervals based on the delivered monitor units. For each fraction the doses of all partial plan/dynamic volume combinations were calculated and were summed to lead to the motion-affected fraction dose. Finally, for each patient the five fraction doses were summed, yielding the total treatment dose. Both daily and total doses were compared to the original reference dose of the respective patient to assess the impact of the intrafraction motion. Depending on the underlying motion of the prostate, different types of motion-affected dose distributions were observed. The planning target volumes (PTVs) ensured CTV_30 (seminal vesicles) D99% coverage for all patients, CTV_35 (prostate corpus) coverage for 97% of the patients and GTV_50 (local boost) for 83% of the patients when compared against the strict planning target D99% value. The dosimetric impact due to prostate intrafraction motion in extremely hypofractionated treatments was determined. The presented study is an essential step towards establishing the actual delivered dose to the patient during radiotherapy fractions.

Feasibility of stereotactic radiotherapy using a 1.5 T MR-linac: Multi-fraction treatment of pelvic lymph node oligometastases

Online adaptive radiotherapy using the 1.5 Tesla MR-linac is feasible for SBRT (5 × 7 Gy) of pelvic lymph node oligometastases. The workflow allows full online planning based on daily anatomy. Session duration is less than 60 min. Quality assurance tests, including independent 3D dose calculations and film measurements were passed.

Towards fast online intrafraction replanning for free-breathing stereotactic body radiation therapy with the MR-linac

The hybrid MRI-radiotherapy machines, like the MR-linac (Elekta AB, Stockholm, Sweden) installed at the UMC Utrecht (Utrecht, The Netherlands), will be able to provide real-time patient imaging during treatment. In order to take advantage of the system's capabilities and enable online adaptive treatments, a new generation of software should be developed, ranging from motion estimation to treatment plan adaptation. In this work we present a proof of principle adaptive pipeline designed for high precision stereotactic body radiation therapy (SBRT) suitable for sites affected by respiratory motion, like renal cell carcinoma (RCC). We utilized our research MRL treatment planning system (MRLTP) to simulate a single fraction 25 Gy free-breathing SBRT treatment for RCC by performing inter-beam replanning for two patients and one volunteer. The simulated pipeline included a combination of (pre-beam) 4D-MRI and (online) 2D cine-MR acquisitions. The 4DMRI was used to generate the mid-position reference volume, while the cine-MRI, via an in-house motion model, provided three-dimensional (3D) deformable vector fields (DVFs) describing the anatomical changes during treatment. During the treatment fraction, at an inter-beam interval, the mid-position volume of the patient was updated and the delivered dose was accurately reconstructed on the underlying motion calculated by the model. Fast online replanning, targeting the latest anatomy and incorporating the previously delivered dose was then simulated with MRLTP. The adaptive treatment was compared to a conventional mid-position SBRT plan with a 3 mm planning target volume margin reconstructed on the same motion trace. We demonstrate that our system produced tighter dose distributions and thus spared the healthy tissue, while delivering more dose to the target. The pipeline was able to account for baseline variations/drifts that occurred during treatment ensuring target coverage at the end of the treatment fraction.

A new methodology for inter- and intrafraction plan adaptation for the MR-linac

The new era of hybrid MRI and linear accelerator machines, including the MR-linac currently being installed in the University Medical Center Utrecht (Utrecht, The Netherlands), will be able to provide the actual anatomy and real-time anatomy changes of the patient's target(s) and organ(s) at risk (OARs) during radiation delivery. In order to be able to take advantage of this input, a new generation of treatment planning systems is needed, that will allow plan adaptation to the latest anatomy state in an online regime. In this paper, we present a treatment planning algorithm for intensity-modulated radiotherapy (IMRT), which is able to compensate for patient anatomy changes. The system consists of an iterative sequencing loop open to anatomy updates and an inter- and intrafraction adaptation scheme that enables convergence to the ideal dose distribution without the need of a final segment weight optimization (SWO). The ability of the system to take into account organ motion and adapt the plan to the latest anatomy state is illustrated using artificial baseline shifts created for three different kidney cases. Firstly, for two kidney cases of different target volumes, we show that the system can account for intrafraction motion, delivering the intended dose to the target with minimal dose deposition to the surroundings compared to conventional plans. Secondly, for a third kidney case we show that our algorithm combined with the interfraction scheme can be used to deliver the prescribed dose while adapting to the changing anatomy during multi-fraction treatments without performing a final SWO.