Search

Intra-fraction motion of lesions in the thorax and abdomen due to respiration is an important source of uncertainty in SBRT. MR-Linacs provide the ability to continuously track the target and gate the radiation beam accordingly. Gating allows for smaller margins and can facilitate hypo-fractionation, but also lengthens the treatment due to the typically reduced delivery efficiency. Offering biofeedback (BF) and providing breathing instructions to the patient potentially helps counteracting the delivery efficiency penalty introduced by gating. In this work we present the first results of a patient study on a 1.5 T MR-Linac, using a prototype visual BF system, compatible with the vendor-provided motion management software. Experiments were conducted on a 1.5 T MR-Linac, equipped with clinical motion monitoring and gating functionality. 12 healthy volunteers (age: 24-79y, female/male: 6/6) were included in the study in phase 1, followed by 6 cancer patients (age: 30-74y, female/male: 2/4), in phase 2. Target motion was estimated in real-time based on 6 Hz sagittal/coronal interleaved 2D cine-MRI data. The resulting target position was streamed to in-house developed BF software and displayed to the study participants on an MRI-compatible monitor positioned at the rear of the MR-Linac bore, visible via an in-bore mirror. End-exhale and end-inhale breath hold (BH) workflows with 6 mm gating windows (GW) were simulated. Each study participant received BF for two consecutive 5-minute sessions. In phase 1, participants were used to select the preferred graphical user interface (GUI) from two GUI concepts (no data shown). In phase 2, patients received instructions and BF using a graph-style GUI to maintain a subject-determined BH (SDBH) as long as comfortable. The duration of each BH was not specified. SDBHs were conducted by three patients in end-exhale and by three patients in end-inhale. For the SDBH workflow, the average estimated delivery efficiency, defined as the ratio between the time spend within the GW and the total session time (5 min), was 49% (62%, 41%, 40%) for end-exhale SDBHs and 69% for end-inhale SDBHs (50%, 74%, 84%) and. Three patients showed a strong learning effect (+8, +6, +18 percentage points) between the subsequent sessions. Questionnaires revealed that all patients fully agreed that it was clear when to perform a BH and when to breathe normally. Two patients, performing an end-exhale SDBH, indicated that they might have found an end-inhale SDBH easier and more intuitive. Visual BF is expected to dramatically improve the delivery efficiency during gating treatments on the MR-Linac. Patient selection for BF systems is important, especially with regards to visual or cognitive impairments. Performance improvements over time in individual patients point towards the value of dedicated training sessions. [ABSTRACT FROM AUTHOR]

To report an interim clinical evaluation of combined external beam irradiation (EBRT) and interstitial or regional hyperthermia in the treatment of locally advanced prostate cancer. From 1997 to 2001, 26 patients with T3-4/NX/0M0 prostate carcinoma were treated with a combination of conformal EBRT and hyperthermia. Fourteen patients received five weekly regional hyperthermia treatments within an optimization (phase II) study, using the coaxial transverse electrical magnetic system. Twelve patients received one interstitial hyperthermia treatment within a feasibility study (phase I), using the multi-electrode current source system. Irradiation was delivered using a conformal three-field technique, administering 70 Gy in 2-Gy fractions in 7 weeks. The mean initial prostate-specific antigen level was 26 ng/mL. Three patients had a T4 and 23 a T3 tumour; the tumours were classified as well (four), moderately (16) and poorly (six) differentiated. The mean follow-up was 36 months. In the combined treatments there was no toxicity of more than grade 2. In regional hyperthermia the mean index temperature (T90 and T50, i.e. exceeded by 90% and 50% of the measurements) was 40.2 °C and 40.8 °C, and for interstitial hyperthermia 39.4 °C and 41.8 °C, respectively. All patients survived; seven patients had a biochemical relapse (27%), three in the regional and four in the interstitial group. The actuarial probability of freedom from biochemical relapse was 70% at 36 months for all patients together, 79% for regional and 57% for interstitial. No factors were found that could be used to predict relapse. The clinical outcome in these patients with advanced localized prostate cancer seems to compare favourably with most series using irradiation alone, and the treatment caused no severe complications. [ABSTRACT FROM AUTHOR]

• First study of seminal vesicle intrafraction motion during MR-Linac RT sessions. • High quality 3D cine-MRI and seminal vesicle tracking is feasible during RT beam-on. • Seminal vesicles show larger intrafraction rotational spread than prostate. • 5 mm isometric expansion provides seminal vesicle coverage probability of 99%. To evaluate seminal vesicle (SV) intrafraction motion using cinematic magnetic resonance imaging (cine-MR) during the delivery of online adaptive MR-Linac radiotherapy fractions, in preparation of MR-guided extremely hypofractionated radiotherapy for intermediate to high-risk prostate cancer patients. Fifty prostate cancer patients were treated with 5 × 7.25 Gy on a 1.5 Tesla MR-Linac. 3D Cine-MR imaging was started simultaneously and acquired over the full beam-on period. Intrafraction motion in this cine-MR was determined for each SV separately with a previously validated soft-tissue contrast-based tracking algorithm. Motion statistics and coverage probability for the SVs and prostate were determined based on the obtained results. SV motion was automatically determined during the beam-on period (approx. 10 min) for 247 fractions. SV intrafraction motion shows larger spread than prostate intrafraction motion and increases over time. This difference is especially evident in the anterior and cranial translation directions. Significant difference in rotation about the left–right axis was found, with larger rotation for the SVs than the prostate. Intra-fraction coverage probability of 99% can be achieved when using 5 mm isometric expansion for the left and right SV and 3 mm for the prostate. This is the first study to investigate SV intrafraction motion during MR-guided RT sessions on an MR-Linac. We have shown that high quality 3D cine-MR imaging and SV tracking during RT is feasible with beam-on. The tracking method as described may be used as input for a fast replanning algorithm, which allows for intrafraction plan adaptation. [ABSTRACT FROM AUTHOR]

• Deep-learning networks for prediction of PBS and VMAT doses were established. • Relative errors between planned and predicted doses were minimal in the target. • Strong correlation (r > 0.9) was found between planned and predicted DVH metrics. • The networks classified the PBS dosimetric benefit over VMAT with 98% precision. • Proposed networks can accurately predict the treatment modality selection outcome. Dose prediction using deep learning networks prior to radiotherapy might lead tomore efficient modality selections. The study goal was to predict proton and photon dose distributions based on the patient-specific anatomy and to assess their clinical usage for paediatric abdominal tumours. Data from 80 patients with neuroblastoma or Wilms' tumour was included. Pencil beam scanning (PBS) (5 mm/ 3%) and volumetric-modulated arc therapy (VMAT) plans (5 mm) were robustly optimized on the internal target volume (ITV). Separate 3-dimensional patch-based U-net networks were trained to predict PBS and VMAT dose distributions. Doses, planning-computed tomography images and relevant optimization masks (ITV, vertebra and organs-at-risk) of 60 patients were used for training with a 5-fold cross validation. The networks' performance was evaluated by computing the relative error between planned and predicted dose-volume histogram (DVH) parameters for 20 inference patients. In addition, the organs-at-risk mean dose difference between modalities was calculated using planned and predicted dose distributions (ΔD mean = D VMAT -D PBS). Two radiation oncologists performed a blind PBS/VMAT modality selection based on either planned or predicted ΔD mean. Average DVH differences between planned and predicted dose distributions were ≤ |6%| for both modalities. The networks classified the organs-at-risk D mean difference as a gain (ΔD mean > 0) with 98% precision. An identical modality selection based on planned compared to predicted ΔD mean was made for 18/20 patients. Deep learning networks for accurate prediction of proton and photon dose distributions for abdominal paediatric tumours were established. These networks allowing fast dose visualisation might aid in identifying the optimal radiotherapy technique when experience and/or resources are unavailable. [ABSTRACT FROM AUTHOR]

To evaluate prostate intrafraction motion using MRI during the full course of online adaptive MR-Linac radiotherapy (RT) fractions, in preparation of MR-guided extremely hypofractionated RT. Five low and intermediate risk prostate cancer patients were treated with 20 × 3.1 Gy fractions on a 1.5T MR-Linac. Each fraction, initial MRI (Pre) scans were obtained at the start of every treatment session. Pre-treatment planning MRI contours were propagated and adapted to this Pre scan after which plan re-optimization was started in the treatment planning system followed by dose delivery. 3D Cine-MR imaging was started simultaneously with beam-on and acquired over the full beam-on period. Prostate intrafraction motion in this cine-MR was determined with a previously validated soft-tissue contrast based tracking algorithm. In addition, absolute accuracy of the method was determined using a 4D phantom. Prostate motion was completely automatically determined over the full on-couch period (approx. 45 min) with no identified mis-registrations. The translation 95% confidence intervals are within clinically applied margins of 5 mm, and plan adaption for intrafraction motion was required in only 4 out of 100 fractions. This is the first study to investigate prostate intrafraction motions during entire MR-guided RT sessions on an MR-Linac. We have shown that high quality 3D cine-MR imaging and prostate tracking during RT is feasible with beam-on. The clinically applied margins of 5 mm have proven to be sufficient for these treatments and may potentially be further reduced using intrafraction plan adaptation guided by cine-MR imaging. [ABSTRACT FROM AUTHOR]

Purpose: To quickly and automatically propagate organ contours from pretreatment to fraction images in magnetic resonance (MR)‐guided prostate external‐beam radiotherapy. Methods: Five prostate cancer patients underwent 20 fractions of image‐guided external‐beam radiotherapy on a 1.5 T MR‐Linac system. For each patient, a pretreatment T2‐weighted three‐dimensional (3D) MR imaging (MRI) scan was used to delineate the clinical target volume (CTV) contours. The same scan was repeated during each fraction, with the CTV contour being manually adapted if necessary. A convolutional neural network (CNN) was trained for combined image registration and contour propagation. The network estimated the propagated contour and a deformation field between the two input images. The training set consisted of a synthetically generated ground truth of randomly deformed images and prostate segmentations. We performed a leave‐one‐out cross‐validation on the five patients and propagated the prostate segmentations from the pretreatment to the fraction scans. Three variants of the CNN, aimed at investigating supervision based on optimizing segmentation overlap, optimizing the registration, and a combination of the two were compared to results of the open‐source deformable registration software package Elastix. Results: The neural networks trained on segmentation overlap or the combined objective achieved significantly better Hausdorff distances between predicted and ground truth contours than Elastix, at the much faster registration speed of 0.5 s. The CNN variant trained to optimize both the prostate overlap and deformation field, and the variant trained to only maximize the prostate overlap, produced the best propagation results. Conclusions: A CNN trained on maximizing prostate overlap and minimizing registration errors provides a fast and accurate method for deformable contour propagation for prostate MR‐guided radiotherapy. [ABSTRACT FROM AUTHOR]

Radiation therapy (RT) is an essential component of effective cancer care and is used across nearly all cancer types. The delivery of RT is becoming more precise through rapid advances in both computing and imaging. The direct integration of magnetic resonance imaging (MRI) with linear accelerators represents an exciting development with the potential to dramatically impact cancer research and treatment. These impacts extend beyond improved imaging and dose deposition. Real-time MRI-guided RT is actively transforming the work flows and capabilities of virtually every aspect of RT. It has the opportunity to change entirely the delivery methods and response assessments of numerous malignancies. This review intends to approach the topic of MRI-based RT guidance from a vendor neutral and international perspective. It also aims to provide an introduction to this topic targeted towards oncologists without a speciality focus in RT. Speciality implications, areas for physician education and research opportunities are identified as they are associated with MRI-guided RT. The uniquely disruptive implications of MRI-guided RT are discussed and placed in context. We further aim to describe and outline important future changes to the speciality of radiation oncology that will occur with MRI-guided RT. The impacts on RT caused by MRI guidance include target identification, RT planning, quality assurance, treatment delivery, training, clinical workflow, tumour response assessment and treatment scheduling. In addition, entirely novel research areas that may be enabled by MRI guidance are identified for future investigation. • We present a review on the current state of MR-guided RT (RT). • Speciality implications, areas for physician education and research opportunities are identified. • Some impacts include target identification, quality assurance and tumour response assessment. [ABSTRACT FROM AUTHOR]

Poster: RTT track: Treatment planning and dose calculation / QC and QA PO-1868: In silico hypofractionation feasibility study for lymph node oligometastases SBRT on the MRI-linac D. Winkel, W.S.C. Eppinga, M.P.W. Intven, A.M. Werensteijn-Honingh, J. Hes, L.M.W. Snoeren, G.H. Bol, B.W. Raaymakers, I.M. Jürgenliemk-Schulz, P.S. Kroon. [Extracted from the article]

Teaching Lecture: Dosimetry and QA for MR-Linacs SP-0727: Dosimetry and QA for MR-Linacs B. Van Asselen, S.L. Hackett, S.J. Woodings, B.W. Raaymakers, J.W.H. Wolthaus. [Extracted from the article]

Poster discussion: RTT 2 PD-0672: Effect of a vacuum mattress on bone & target intra-fraction motion during MR-guided lymph node SBRT A.M. Werensteijn-honingh, P.S. Kroon, D. Winkel, C.G. Gadellaa-Van Hooijdonk, G.G. Sikkes, N.G.P.M. Vissers, W.S.C. Eppinga, M. Intven, B.W. Raaymakers, I.M. Jürgenliemk-Schulz. [Extracted from the article]

Poster discussion: PH: Adaptive radiotherapy and interfraction motion management 2 PD-0557: Biomechanical quality assurance criteria for deformable registration in image guided radiotherapy C. Zachiu, B. Denis de Senneville, M. Ries, B.W. Raaymakers. [Extracted from the article]

Proffered Papers: Proffered papers 18: Intra-fractional motion management OC-0341: Seminal vesicle motion tracking in 3D cine-MR during MR-Linac prostate treatments D. De Muinck Keizer, T. Willigenburg, M.D. Den Hartogh, J.R.N. Van der Voort van Zyp, B.W. Raaymakers, J.J.W. Lagendijk, H.C.J. De Boer. [Extracted from the article]

Poster Highlights: Poster highlights 17 CL: Palliation PH-0529: Prostate intrafraction motion during the full course of MR-guided radiotherapy sessions D. De Muinck Keizer, L.G.W. Kerkmeijer, T. Willigenburg, M.D. Den Hartogh, J.R.N. Van der Voort van Zyp, E.N. De Groot-van Breugel, B.W. Raaymakers, J.J.W. Lagendijk, H.C.J. De Boer. [Extracted from the article]