Technical note: Minimizing CIED artifacts on a 0.35 T MRI-Linac using deep learning

BACKGROUND

Artifacts from implantable cardioverter defibrillators (ICDs) are a challenge to magnetic resonance imaging (MRI)-guided radiotherapy (MRgRT).

PURPOSE

This study tested an unsupervised generative adversarial network to mitigate ICD artifacts in balanced steady-state free precession (bSSFP) cine MRIs and improve image quality and tracking performance for MRgRT.

METHODS

Fourteen healthy volunteers (Group A) were scanned on a 0.35 T MRI-Linac with and without an MR conditional ICD taped to their left pectoral to simulate an implanted ICD. bSSFP MRI data from 12 of the volunteers were used to train a CycleGAN model to reduce ICD artifacts. The data from the remaining two volunteers were used for testing. In addition, the dataset was reorganized three times using a Leave-One-Out scheme. Tracking metrics [Dice similarity coefficient (DSC), target registration error (TRE), and 95 percentile Hausdorff distance (95% HD)] were evaluated for whole-heart contours. Image quality metrics [normalized root mean square error (nRMSE), peak signal-to-noise ratio (PSNR), and multiscale structural similarity (MS-SSIM) scores] were evaluated. The technique was also tested qualitatively on three additional ICD datasets (Group B) including a patient with an implanted ICD.

RESULTS

For the whole-heart contour with CycleGAN reconstruction: 1) Mean DSC rose from 0.910 to 0.935; 2) Mean TRE dropped from 4.488 to 2.877 mm; and 3) Mean 95% HD dropped from 10.236 to 7.700 mm. For the whole-body slice with CycleGAN reconstruction: 1) Mean nRMSE dropped from 0.644 to 0.420; 2) Mean MS-SSIM rose from 0.779 to 0.819; and 3) Mean PSNR rose from 18.744 to 22.368. The three Group B datasets evaluated qualitatively displayed a reduction in ICD artifacts in the heart.

CONCLUSION

CycleGAN-generated reconstructions significantly improved both tracking and image quality metrics when used to mitigate artifacts from ICDs.

Real-time motion management in MRI-guided radiotherapy: Current status and AI-enabled prospects

MRI-guided radiotherapy (MRIgRT) is a highly complex treatment modality, allowing adaptation to anatomical changes occurring from one treatment day to the other (inter-fractional), but also to motion occurring during a treatment fraction (intra-fractional). In this vision paper, we describe the different steps of intra-fractional motion management during MRIgRT, from imaging to beam adaptation, and the solutions currently available both clinically and at a research level. Furthermore, considering the latest developments in the literature, a workflow is foreseen in which motion-induced over- and/or under-dosage is compensated in 3D, with minimal impact to the radiotherapy treatment time. Considering the time constraints of real-time adaptation, a particular focus is put on artificial intelligence (AI) solutions as a fast and accurate alternative to conventional algorithms.

Impact of abdominal compression on intra-fractional motion and delivered dose in magnetic resonance image-guided adaptive radiation ablation of adrenal gland metastases

PURPOSE

The current study investigated the impact of abdominal compression on motion and the delivered dose during non-gated, magnetic resonance image (MRI)-guided radiation ablation of adrenal gland metastases.

METHODS

Thirty-one patients with adrenal gland metastases treated to 45-60 Gy in 3-8 fractions on a 1.5 T MRI-linac were included in the study. The patients were breathing freely (n = 14) or with motion restricted by using an abdominal compression belt (n = 17). The time-resolved position of the target in online 2D cine MR images acquired during treatment was assessed and used to estimate the dose delivered to the GTV and abutting luminal organs at risk (OAR).

RESULTS

The median (range) 3D root-mean-square target position error was significantly higher in patients treated without a compression belt [2.9 (1.9-5.6) mm] compared to patients using the belt [2.1 (1.2-3.5) mm] (P < 0.01). The median (range) GTV V95% was significantly reduced from planned 98.6 (65.9-100) % to delivered 96.5 (64.5-99.9) % due to motion (P < 0.01). Most prominent dose reductions were found in patients showing either large target drift or respiration motion and were mainly treated without abdominal compression. Motion did not lead to an increased number of constraint violations for luminal OAR.

CONCLUSIONS

Acceptable target coverage and dose to OAR was observed in the vast majority of patients despite intra-fractional motion during adaptive MRI-guided radiation ablation. The use of abdominal compression significantly reduced the target position error and prevented the most prominent target coverage degradations and is, therefore, recommended as motion management at MRI-linacs.

Accuracy of deformable image registration-based intra-fraction motion management in Magnetic Resonance-guided radiotherapy

Background and Purpose

Intra-fraction motion management is key in Stereotactic Ablative Radiotherapy (SABR) gated delivery. This study assessed the accuracy of automatic tumor segmentation in the delivery of MR-guided radiotherapy (MRgRT) by comparing it to manual delineations performed by experienced observers.

Materials and Methods

Twenty patients previously treated with MR-guided SABR for thoracic and abdominal tumors were included. Five observers with at least two years of experience in MRgRT manually delineated the gross tumor volume (GTV) for 20 patients on 240 frames of a cine MRI on a sagittal plane. Deformable Image Registration (DIR) based GTV contours were propagated using four different algorithms from a reference frame to subsequent frames.Geometrical analysis based on the Dice Similarity Coefficient (DSC), centroid distance and Hausdorff Distance (HDD) were performed to assess the inter-observer variability and the accuracy of automatic segmentation. A Confidence Value (CV) metric for the reliability of the tumor auto-contouring was also calculated.

Results

Inter-observer delineation variability resulted in mean DSC of 0.89, HDD of 5.8 mm and centroid distance of 1.7 mm. Tumor auto-contouring by the four DIR algorithms resulted in an excellent agreement with the manual delineations by the experienced observers. Mean DSC for each algorithm across all patients was greater than 0.90, whereas the HDD and centroid distances were below 4.0 mm and 1.5 mm, respectively. The CV showed a strong correlation with the DSC.

Conclusions

DIR-based auto-contouring in MRgRT exhibited a high level of agreement with the manual contouring performed by experts, allowing accurate gated delivery.

Fast Deformable Image Registration for Real-Time Target Tracking During Radiation Therapy Using Cine MRI and Deep Learning

PURPOSE

We developed a deep learning (DL) model for fast deformable image registration using 2-dimensional sagittal cine magnetic resonance imaging (MRI) acquired during radiation therapy and evaluated its potential for real-time target tracking compared with conventional image registration methods.

METHODS AND MATERIALS

Our DL model uses a pair of cine MRI images as input and provides a motion vector field (MVF) as output. The MVF is then applied to align the input images. A retrospective study was conducted to train and evaluate our model using cine MRI data from patients undergoing treatment for abdominal and thoracic tumors. For each treatment fraction, MR-linear accelerator delivery log files, tracking videos, and cine image files were analyzed. Individual MRI frames were temporally sampled to construct a large set of image registration pairs used to evaluate multiple methods. The DL model was optimized using 5-fold cross validation, and model outputs (transformed images and MVFs) using test set images were saved for comparison with 3 conventional registration methods (affine, b-spline, and demons). Evaluation metrics were 3-fold: (1) registration error, (2) MVF stability (both spatial and temporal), and (3) average computation time.

RESULTS

We analyzed >21 hours of cine MRI (>629,000 frames) acquired during 86 treatment fractions from 21 patients. In a test set of 10,320 image registration pairs, DL registration outperformed conventional methods in both registration error (affine, b-spline, demons, DL; root mean square error: 0.067, 0.040, 0.036, 0.032; paired t test demons vs DL: t[20] = 4.2, P < .001) and computation time per frame (51, 1150, 4583, 8 ms). Among deformable methods, spatial stability of resulting MVFs was comparable; however, the DL model had significantly improved temporal consistency.

CONCLUSIONS

DL-based image registration can leverage large-scale MR cine data sets to outperform conventional registration methods and is a promising solution for real-time deformable motion estimation in radiation therapy.

Same-day consultation, simulation and lung Stereotactic Ablative Radiotherapy delivery on a Magnetic Resonance-linac

•

A same-day consultation and lung SABR workflow was introduced, and experience in 10 patients reported.

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A detailed simulation procedure and the use of real-time cine magnetic resonance imaging enabled accurate treatment delivery.

•

All patients reported satisfaction with the procedure, which improved patient convenience.

•

On average, at least 94.4% (5th percentile) of the GTV was always located inside the PTV during beam-on.

•

System-latency for triggering a beam-off event comprised 5.3% of the delivery time.

Background and Purpose

Magnetic resonance-guided radiotherapy (MRgRT) with real-time intra-fraction tumor motion monitoring allows for high precision Stereotactic Ablative Radiotherapy (SABR). This study aimed to investigate the clinical feasibility, patient satisfaction and delivery accuracy of single-fraction MR-guided SABR in a single day (one-stop-shop, OSS).

Methods and Materials

Ten patients with small lung tumors eligible for single fraction treatments were included. The OSS procedure consisted of consultation, treatment simulation, treatment planning and delivery. Following SABR delivery, patients completed a reported experience measure (PREM) questionnaire. Prescribed doses ranged 28–34 Gy. Median GTV was 2.2 cm³ (range 1.3–22.9 cm³). A gating boundary of 3 mm, and PTV margin of 5 mm around the GTV, were used with auto-beam delivery control. Accuracy of SABR delivery was studied by analyzing delivered MR-cines reconstructed from machine log files.

Results

All 10 patients completed the OSS procedure in a single day, and all reported satisfaction with the process. Median time for the treatment planning step and the whole procedure were 2.8 h and 6.6 h, respectively. With optimization of the procedure, treatment could be completed in half a day. During beam-on, the 3 mm tracking boundary encompassed between 78.0 and 100 % of the GTV across all patients, with corresponding PTV values being 94.4–100 % (5th-95th percentiles). On average, system-latency for triggering a beam-off event comprised 5.3 % of the delivery time. Latency reduced GTV coverage by an average of −0.3 %. Duty-cycles during treatment delivery ranged from 26.1 to 64.7 %.

Conclusions

An OSS procedure with MR-guided SABR for lung cancer led to good patient satisfaction. Gated treatment delivery was highly accurate with little impact of system-latency.

Stability of conventional and machine learning-based tumor auto-segmentation techniques using undersampled dynamic radial bSSFP acquisitions on a 0.35 T hybrid MR-linac system

PURPOSE

Hybrid MRI-linear accelerator systems (MR-linacs) allow for the incorporation of MR images with high soft-tissue contrast into the radiation therapy procedure prior to, during, or post irradiation. This allows not only for the optimization of the treatment planning, but also for real-time monitoring of the tumor position using cine MRI, from which intrafractional motion can be compensated. Fast imaging and accurate tumor tracking are crucial for effective compensation. This study investigates the application of cine MRI with a radial acquisition scheme on a low-field MR-linac to accelerate the acquisition rate and evaluates the effect on tracking accuracy.

METHODS

An MR sequence using tiny golden-angle radial k-space sampling was developed and applied to cine imaging on patients with liver tumors on a 0.35 T MR-linac. Tumor tracking was assessed for accuracy and stability from the cine images with increasing k-space undersampling factors. Tracking was achieved using two different auto-segmentation algorithms: a deformable image registration B-spline similar to that implemented on the MR-linac and a convolutional neural network approach known as U-Net.

RESULTS

Radial imaging allows for increased temporal resolution with reliable tumor tracking, although tracking robustness decreases as temporal resolution increases. Additional acquisition-based artifacts can be avoided by reducing the angle increment using tiny golden-angles. The U-net algorithm was found to have superior auto-segmentation metrics compared to B-spline. U-net was able to track two well-defined tumors, imaged with just 30 spokes per image (10.6 frames per second), with an average Dice coefficient ≥ 83%, Hausdorff distance ≤ 1.4 pixel, and mean contour distance ≤ 0.5 pixel.

CONCLUSIONS

Radial acquisitions are commonplace in dynamic imaging; however, in MR-guided radiotherapy, robust tumor tracking is also required. This study demonstrates the in vivo feasibility of tumor tracking from radially acquired images on a low-field MR-linac. Radial imaging allows for decreased image acquisition times while maintaining robust tracking. The U-net algorithm can track a tumor with higher accuracy in images with undersampling artifacts than a conventional deformable B-spline algorithm and is a promising tool for tracking in MR-guided radiation therapy.

Optimized CyberKnife Lung Treatment: Effect of Fractionated Tracking Volume Change on Tracking Results

Objectives

To explore the impact of volume change in the fractionated tracking of stereotactic radiotherapy on the results of synchronous, respiratory tracking algorithm using CyberKnife.

Methods

A total of 38 lung tumor patients receiving stereotactic radiotherapy at our center from March 2018 to October 2019 were counted. Photoshop CS4 image processing software was used to obtain the pixels and the average value of brightness of the tracking volume in the image and calculate the grayscale within the contour of the tracking volume on the real-time X-ray image. At the same time, parameters of the synchronous respiratory tracking algorithm of the fractional CyberKnife were extracted for comparison between the volume of image-guided image tracking and the number of fractions during stereotactic radiotherapy. We also analyzed the relationship between fraction tumor location and characteristics and the calculated results of synchronous respiratory tracking by CyberKnife.

Results

There were no significant differences between the first four fractions (p > 0.05) for left lung lesions and no significant differences between the first five fractions for right lung lesions (p ≥ 0.05). For peripheral lung cancer, longer fractional treatment led to greater variation in grayscale (G-A: >4 fractions p < 0.05), while for central lung cancer, longer fractional treatment led to greater variation in parameters of the synchronous respiratory tracking algorithm (Uncertainty A and Uncertainty B: >4 fractions p < 0.05). There was a significant correlation between radiotherapy-graded tumor density and relevant parameters, and the correlation was strong (>0.7, p < 0.05).

Conclusion

With the increase of treatment fractions, the gray value in the patient tracking volume decreased. Patients of >4 fractions were advised to reevaluate with simulated CT and replan. For tumors with small diameter and low density, the imaging changes of volume should be closely followed during treatment. For left lung and central lung cancer, carefully select the synchronous tracking treatment with 2-view.

Dose uncertainty and resolution of polymer gel dosimetry using an MRI guided radiation therapy system's onboard 0.35 T scanner

Magnetic Resonance Imaging (MRI) scanners are widely used for 3D gel dosimeters readout. However, limited access to MRI scanners is a challenge in MRI-based gel dosimetry. Recent clinical implementation of MRI-guided radiation therapy machines provides potential opportunities for onboard gel dosimetry using its MRI subsystem. The objective of this study was to investigate the feasibility of gel dosimetry using ViewRay's onboard 0.35 T MRI scanner. A BANG® polymer gel dosimeter was irradiated by three beams of 3 × 3 cm2 field size. The T2 relaxation rate (R2) of the irradiated gel was measured using a Philips 1.5 T Ingenia MRI and a ViewRay 0.35 T onboard MRI and spin-echo pulse sequences. The number of signal averages (NSA) was set to 16 for the ViewRay acquisitions and one for the Philips 1.5 T MRI to achieve similar signal-to-noise ratios. The in-plane spatial resolution was 1.5 × 1.5 mm2 and the slice thickness was 5 mm. The relative dose uncertainty was obtained using R2 versus dose curves to compare the performance of dosimetry using the two different MRIs and field strengths. The dose uncertainty decreased from 12% at 2 Gy to 3.5% at 7.5 Gy at 1.5 T. The dose uncertainty decreased from 13% at 2 Gy to 4% at 7.5 Gy with NSA = 16 and 3 × 3 mm2 pixel size, and from 10.5% at 2 Gy to 3.2% at 7.5 Gy with NSA = 16 and denoised R2 maps (1.5 × 1.5 mm2 pixel size) at 0.35 T. The mean of dose resolution was 0.4 Gy at 1.5 T while the mean of dose resolution was 0.8 Gy and 0.64 Gy at 0.35 T by downsampling and denoising the R2 map, respectively. Therefore, comparable dose uncertainty was achievable using the ViewRay's onboard 0.35 T and Philips 1.5 T MRI scanners. 3D gel dosimetry using onboard low-field MRI scanner provides ViewRay users a 3D high resolution dosimetry option besides film and ionization chamber.

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.

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.

Deformable image registration for radiation therapy: principle, methods, applications and evaluation

Background: Deformable image registration (DIR) is increasingly used in the field of radiation therapy (RT) to account for anatomical deformations. The aims of this paper are to describe the main applications of DIR in RT and discuss current DIR evaluation methods. Methods: Articles on DIR published from January 2000 to October 2018 were extracted from PubMed and Science Direct. Our search was restricted to articles that report data obtained from humans, were written in English, and address DIR methods for RT. A total of 207 articles were selected from among 2506 identified in the search process. Results: At planning, DIR is used for organ delineation using atlas-based segmentation, deformation-based planning target volume definition, functional planning and magnetic resonance imaging-based dose calculation. In image-guided RT, DIR is used for contour propagation and dose calculation on per-treatment imaging. DIR is also used to determine the accumulated dose from fraction to fraction in external beam RT and brachytherapy, both for dose reporting and adaptive RT. In the case of re-irradiation, DIR can be used to estimate the cumulated dose of the two irradiations. Finally, DIR can be used to predict toxicity in voxel-wise population analysis. However, the evaluation of DIR remains an open issue, especially when dealing with complex cases such as the disappearance of matter. To quantify DIR uncertainties, most evaluation methods are limited to geometry-based metrics. Software companies have now integrated DIR tools into treatment planning systems for clinical use, such as contour propagation and fraction dose accumulation. Conclusions: DIR is increasingly important in RT applications, from planning to toxicity prediction. DIR is routinely used to reduce the workload of contour propagation. However, its use for complex dosimetric applications must be carefully evaluated by combining quantitative and qualitative analyses.

A ROI-based global motion model established on 4DCT and 2D cine-MRI data for MRI-guidance in radiation therapy

In-room magnetic resonance imaging (MRI) allows the acquisition of fast 2D cine-MRI centered in the tumor for advanced motion management in radiotherapy. To achieve 3D information during treatment, patient-specific motion models can be considered the most viable solution. However, conventional global motion models are built using a single motion surrogate, independently from the anatomical location. In this work, we present a novel motion model based on regions of interest (ROIs) established on 4D computed tomography (4DCT) and 2D cine-MRI, aiming at accurately compensating for changes during treatment. In the planning phase, a motion model is built on a 4DCT dataset, through 3D deformable image registration (DIR). ROIs are then defined and correlated with motion fields derived by 2D DIR between CT slices centered in the tumor. In the treatment phase, the model is applied to in-room cine-MRI data to compensate for organ motion in a multi-modal framework, aiming at estimating a time-resolved 3DCT. The method is validated on a digital phantom and tested on two lung patients. Analysis is performed by considering different anatomical planes (coronal, sagittal and a combination of the two) and evaluating the performance of the method on tumor and diaphragm. For the phantom study, the ROI-based model results in a uniform median error on both diaphragm and tumor below 1.5 mm. For what concerns patients, median errors on both diaphragm and tumor are around 2 mm (maximum patient resolution), confirming the capability of the method to regionally compensate for motion. A novel ROI-based motion model is proposed as an integral part of an envisioned clinical MRI-guided workflow aiming at enhanced image guidance compared to conventional strategies.

Delineation of a Cardiac Planning Organ-At-Risk Volume Using Real-Time Magnetic Resonance Imaging for Cardiac Protection in Thoracic and Breast Radiation Therapy

PURPOSE

Cardiac radiation is associated with cardiotoxicity in patients with thoracic and breast malignancies. We conducted a prospective study using cine magnetic resonance imaging (MRI) scans to evaluate heart motion. We hypothesized that cine MRI could be used to define population-based cardiac planning organ-at-risk volumes (PRV).

METHODS AND MATERIALS

A total of 16 real-time acquisitions were obtained per subject on a 1.5 Tesla MRI (Philips Ingenia). Planar cine MRI was performed in 4 sequential sagittal and coronal planes at free-breathing (FB) and deep-inspiratory breath hold (DIBH). In-plane cardiac motion was assessed using a scale-invariant feature transformation-based algorithm. Subject-specific pixel motion ranges were defined in anteroposterior (AP), left-right (LR), and superoinferior (SI) planes. Averages of the 98% and 67% of the maximum ranges of pixel displacement were defined by subject, then averaged across the cohort to calculate PRV expansions at FB and DIBH.

RESULTS

Data from 20 subjects with a total of 3120 image frames collected per subject in coronal and sagittal planes at DIBH and FB, and 62,400 total frames were analyzed. Cohort averages of 98% of the maximum cardiac motion ranges comprised margin expansions of 12.5 ± 1.1 mm SI, 5.8 ± 1.2 mm AP, and 6.6 ± 1.0 mm LR at FB and 6.7 ± 1.5 mm SI, 4.7 ± 1.3 mm AP, and 5.3 ± 1.3 mm LR at DIBH. Margins for 67% of the maximum range comprised 7.7 ± 0.7 mm SI, 3.2 ± 0.6 mm AP, and 3.7 ± 0.6 mm LR at FB and 4.1 ± 0.9 mm SI, 2.7 ± 0.8 mm AP, and 3.2 ± 0.8 mm LR at DIBH. Subsequently, these margins were simplified to form PRVs for treatment planning.

CONCLUSIONS

We implemented scale-invariant feature transformation-based motion tracking for analysis of the cardiac cine MRI scans to quantify motion and create cohort-based cardiac PRVs to improve cardioprotection in breast and thoracic radiation.

The impact of 2D cine MR imaging parameters on automated tumor and organ localization for MR-guided real-time adaptive radiotherapy

2D cine MR imaging may be utilized to monitor rapidly moving tumors and organs-at-risk for real-time adaptive radiotherapy. This study systematically investigates the impact of geometric imaging parameters on the ability of 2D cine MR imaging to guide template-matching-driven autocontouring of lung tumors and abdominal organs. Abdominal 4D MR images were acquired of six healthy volunteers and thoracic 4D MR images were obtained of eight lung cancer patients. At each breathing phase of the images, the left kidney and gallbladder or lung tumor, respectively, were outlined as volumes of interest. These images and contours were used to create artificial 2D cine MR images, while simultaneously serving as 3D ground truth. We explored the impact of five different imaging parameters (pixel size, slice thickness, imaging plane orientation, number and relative alignment of images as well as strategies to create training images). For each possible combination of imaging parameters, we generated artificial 2D cine MR images as training and test images. A template-matching algorithm used the training images to determine the tumor or organ position in the test images. Subsequently, a 3D base contour was shifted to the determined position and compared to the ground truth via centroid distance and Dice similarity coefficient. The median centroid distance between adapted and ground truth contours was 1.56 mm for the kidney, 3.81 mm for the gallbladder and 1.03 mm for the lung tumor (median Dice similarity coefficient: 0.95, 0.72 and 0.93). We observed that a decrease in image resolution led to a modest decrease in localization accuracy, especially for the small gallbladder. However, for all volumes of interest localization accuracy varied substantially more between subjects than due to the different imaging parameters. Automated tumor and organ localization using 2D cine MR imaging and template-matching-based autocontouring is robust against variation of geometric imaging parameters. Future work and optimization efforts of 2D cine MR imaging for real-time adaptive radiotherapy is needed to characterize the influence of sequence- and anatomical site-specific imaging contrast.

MRI-guidance for motion management in external beam radiotherapy: current status and future challenges

High precision conformal radiotherapy requires sophisticated imaging techniques to aid in target localisation for planning and treatment, particularly when organ motion due to respiration is involved. X-ray based imaging is a well-established standard for radiotherapy treatments. Over the last few years, the ability of magnetic resonance imaging (MRI) to provide radiation-free images with high-resolution and superb soft tissue contrast has highlighted the potential of this imaging modality for radiotherapy treatment planning and motion management. In addition, these advantageous properties motivated several recent developments towards combined MRI radiation therapy treatment units, enabling in-room MRI-guidance and treatment adaptation. The aim of this review is to provide an overview of the state-of-the-art in MRI-based image guidance for organ motion management in external beam radiotherapy. Methodological aspects of MRI for organ motion management are reviewed and their application in treatment planning, in-room guidance and adaptive radiotherapy described. Finally, a roadmap for an optimal use of MRI-guidance is highlighted and future challenges are discussed.

Stereotactic ablative radiotherapy (SABR) for early-stage central lung tumors: New insights and approaches

The use of stereotactic ablative radiotherapy (SABR) for central lung tumors is increasing. Centrally located lung tumors can be subdivided into two categories, namely the 'moderately central' tumors where the planning target volume is located within 2 cm of the proximal bronchial tree, and the 'ultracentral' tumors where a planning target volume (PTV) overlaps the trachea or main stem bronchi. The toxicity of SABR appears acceptable when 'moderately central' tumors are treated using techniques that comply with organs at risk tolerance doses used for prospective trials and in recent publications. A high toxicity is seen when ultracentral tumors are treated using SABR, and conventional radiotherapy appears more appropriate in such tumors as the true normal organ tolerance doses remain unknown. When ultracentral tumors are treated with non-SABR hypofractionated radiotherapy, a homogenous dose distribution in the planning target volume and limitation of both normal organ maximum point doses and volumes receiving high doses seems to be needed.

Role of Daily Plan Adaptation in MR-Guided Stereotactic Ablative Radiation Therapy for Adrenal Metastases

PURPOSE

To study interfractional organ changes during magnetic resonance (MR)-guided stereotactic ablative radiation therapy for adrenal metastases and to evaluate the dosimetric advantages of online plan adaptation.

METHODS AND MATERIALS

Seventeen patients underwent a total of 84 fractions of video-assisted, respiration-gated, MR-guided adaptive radiation therapy to deliver either 50 Gy (5 fractions), 60 Gy (8 fractions), or 24 Gy (3 fractions). An MR scan was repeated before each fraction, followed by rigid coregistration to the gross tumor volume (GTV) on the pretreatment MR scan. Contour deformation, planning target volume (PTV) (GTV + 3 mm) expansion, and online plan reoptimization were then performed. Reoptimized plans were compared with baseline treatment plans recalculated on the anatomy-of-the-day ("predicted plans"). Interfractional changes in organs at risk (OARs) were quantified according to OAR volume changes within a 3 cm distance from the PTV surface, center of mass displacements, and the Dice similarity coefficient. Plan quality evaluation was based on target coverage (GTV and PTV) and high dose sparing of all OARs (V_36Gy, V_33Gy, and V_25Gy).

RESULTS

Substantial center of mass displacements were observed for stomach, bowel, and duodenum, 17, 27 and 36 mm, respectively. Maximum volume changes for the stomach, bowel, and duodenum within 3 cm of PTV were 23.8, 20.5, and 20.9 cm³, respectively. Dice similarity coefficient values for OARs ranged from 0.0 to 0.9 for all fractions. Baseline plans recalculated on anatomy-of-the-day revealed underdosage of target volumes and variable OAR sparing, leading to a failure to meet institutional constraints in a third of fractions. Online reoptimization improved target coverage in 63% of fractions and reduced the number of fractions not meeting the V_95% objective for GTV and PTV. Reoptimized plans exhibited significantly better sparing of OARs.

CONCLUSIONS

Significant interfractional changes in OAR positions were observed despite breath-hold stereotactic ablative radiation therapy delivery under MR-guidance. Online reoptimization of treatment plans led to significant improvements in target coverage and OAR sparing.

MR-guided Gated Stereotactic Radiation Therapy Delivery for Lung, Adrenal, and Pancreatic Tumors: A Geometric Analysis

PURPOSE

We implemented magnetic resonance-guided breath-hold stereotactic body radiation therapy in combination with visual feedback using the MRIdian system. Both accuracy of gated delivery and reproducibility of tumor positions were studied.

METHODS AND MATERIALS

Tumor tracking is realized through repeated magnetic resonance imaging in a single sagittal plane at 4 frames per second with deformable image registration. An in-room monitor allowed visualization of the tracked gross tumor volume (GTV) contour and the planning target volume (PTV) (GTV + 3 mm), which was the gating boundary. For each delivery, a predefined threshold-region of interest percentage (ROI%) allows a percentage of GTV area to be outside the gating boundary before a beam-hold is triggered. Accuracy of gated delivery and tumor position reproducibility during breath-holds was analyzed for 15 patients (87 fractions) with lung, adrenal, and pancreas tumors. For each fraction, we analyzed (1) reproducibility of system-tracked GTV centroid position within the PTV; (2) geometric coverage of GTV area within the PTV; (3) treatment duty cycle efficiency; (4) effects of threshold ROI% settings on treatment duty cycle efficiency and GTV area coverage; and (5) beam-off latency effect on mean GTV coverage.

RESULTS

For lung, adrenal, and pancreatic tumors, grouped 5th to 95th percentile distributions of GTV centroid positions in the dorsoventral direction, relative to PTV-center of mass (COM), were, respectively, -3.3 mm to 2.8 mm, -2.5 mm to 3.7 mm, and -4.4 mm to 2.9 mm. Corresponding distributions in the craniocaudal direction were -2.6 mm to 4.6 mm, -4.1 mm to 4.4 mm, and -4.4 mm to 4.5 mm, respectively. Mean GTV areas encompassed during beam-on for all fractions were 94.6%, 94.3%, and 95.3% for lung, adrenal, and pancreas tumors, respectively. Mean treatment duty cycle efficiency ranged from 67% to 87% for these tumors. Use of higher threshold-ROI% resulted in increased duty cycle efficiency, at the cost of a small decrease in GTV area coverage. The beam-off latency had a marginal impact on the GTV coverage.

CONCLUSIONS

Gated stereotactic body radiation therapy delivery during breath-hold, real-time magnetic resonance guidance resulted in at least 95% geometric GTV coverage in lung, adrenal, and pancreatic tumors.

Initial clinical observations of intra- and interfractional motion variation in MR-guided lung SBRT

OBJECTIVE

To evaluate variations in intra- and interfractional tumour motion, and the effect on internal target volume (ITV) contour accuracy, using deformable image registration of real-time two-dimensional-sagittal cine-mode MRI acquired during lung stereotactic body radiation therapy (SBRT) treatments.

METHODS

Five lung tumour patients underwent free-breathing SBRT treatments on the ViewRay system, with dose prescribed to a planning target volume (defined as a 3-6 mm expansion of the 4DCT-ITV). Sagittal slice cine-MR images (3.5 × 3.5 mm² pixels) were acquired through the centre of the tumour at 4 frames per second throughout the treatments (3-4 fractions of 21-32 min). Tumour gross tumour volumes (GTVs) were contoured on the first frame of the MR cine and tracked for the first 20 min of each treatment using offline optical-flow based deformable registration implemented on a GPU cluster. A ground truth ITV (MR-ITV_20 min) was formed by taking the union of tracked GTV contours. Pseudo-ITVs were generated from unions of the GTV contours tracked over 10 s segments of image data (MR-ITV_10 s).

RESULTS

Differences were observed in the magnitude of median tumour displacement between days of treatments. MR-ITV_10 s areas were as small as 46% of the MR-ITV_20 min.

CONCLUSION

An ITV offers a "snapshot" of breathing motion for the brief period of time the tumour is imaged on a specific day. Real-time MRI over prolonged periods of time and over multiple treatment fractions shows that ITV size varies. Further work is required to investigate the dosimetric effect of these results. Advances in knowledge: Five lung tumour patients underwent free-breathing MRI-guided SBRT treatments, and their tumours tracked using deformable registration of cine-mode MRI. The results indicate that variability of both intra- and interfractional breathing amplitude should be taken into account during planning of lung radiotherapy.

MRI-guided lung SBRT: Present and future developments

Stereotactic body radiotherapy (SBRT) is rapidly becoming an alternative to surgery for the treatment of early-stage non-small cell lung cancer patients. Lung SBRT is administered in a hypo-fractionated, conformal manner, delivering high doses to the target. To avoid normal-tissue toxicity, it is crucial to limit the exposure of nearby healthy organs-at-risk (OAR). Current image-guided radiotherapy strategies for lung SBRT are mostly based on X-ray imaging modalities. Although still in its infancy, magnetic resonance imaging (MRI) guidance for lung SBRT is not exposure-limited and MRI promises to improve crucial soft-tissue contrast. Looking beyond anatomical imaging, functional MRI is expected to inform treatment decisions and adaptations in the future. This review summarises and discusses how MRI could be advantageous to the different links of the radiotherapy treatment chain for lung SBRT: diagnosis and staging, tumour and OAR delineation, treatment planning, and inter- or intrafractional motion management. Special emphasis is placed on a new generation of hybrid MRI treatment devices and their potential for real-time adaptive radiotherapy.

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.

A method to detect landmark pairs accurately between intra-patient volumetric medical images

PURPOSES

An image processing procedure was developed in this study to detect large quantity of landmark pairs accurately in pairs of volumetric medical images. The detected landmark pairs can be used to evaluate of deformable image registration (DIR) methods quantitatively.

METHODS

Landmark detection and pair matching were implemented in a Gaussian pyramid multi-resolution scheme. A 3D scale-invariant feature transform (SIFT) feature detection method and a 3D Harris-Laplacian corner detection method were employed to detect feature points, i.e., landmarks. A novel feature matching algorithm, Multi-Resolution Inverse-Consistent Guided Matching or MRICGM, was developed to allow accurate feature pairs matching. MRICGM performs feature matching using guidance by the feature pairs detected at the lower resolution stage and the higher confidence feature pairs already detected at the same resolution stage, while enforces inverse consistency.

RESULTS

The proposed feature detection and feature pair matching algorithms were optimized to process 3D CT and MRI images. They were successfully applied between the inter-phase abdomen 4DCT images of three patients, between the original and the re-scanned radiation therapy simulation CT images of two head-neck patients, and between inter-fractional treatment MRIs of two patients. The proposed procedure was able to successfully detect and match over 6300 feature pairs on average. The automatically detected landmark pairs were manually verified and the mismatched pairs were rejected. The automatic feature matching accuracy before manual error rejection was 99.4%. Performance of MRICGM was also evaluated using seven digital phantom datasets with known ground truth of tissue deformation. On average, 11855 feature pairs were detected per digital phantom dataset with TRE = 0.77 ± 0.72 mm.

CONCLUSION

A procedure was developed in this study to detect large number of landmark pairs accurately between two volumetric medical images. It allows a semi-automatic way to generate the ground truth landmark datasets that allow quantitatively evaluation of DIR algorithms for radiation therapy applications.

Magnetic Resonance Image Guided Radiation Therapy for External Beam Accelerated Partial-Breast Irradiation: Evaluation of Delivered Dose and Intrafractional Cavity Motion

PURPOSE

To use magnetic resonance image guided radiation therapy (MR-IGRT) for accelerated partial-breast irradiation (APBI) to (1) determine intrafractional motion of the breast surgical cavity; and (2) assess delivered dose versus planned dose.

METHODS AND MATERIALS

Thirty women with breast cancer (stages 0-I) who underwent breast-conserving surgery were enrolled in a prospective registry evaluating APBI using a 0.35-T MR-IGRT system. Clinical target volume was defined as the surgical cavity plus a 1-cm margin (excluding chest wall, pectoral muscles, and 5 mm from skin). No additional margin was added for the planning target volume (PTV). A volumetric MR image was acquired before each fraction, and patients were set up to the surgical cavity as visualized on MR imaging. To determine the delivered dose for each fraction, the electron density map and contours from the computed tomography simulation were transferred to the pretreatment MR image via rigid registration. Intrafractional motion of the surgical cavity was determined by applying a tracking algorithm to the cavity contour as visualized on cine MR.

RESULTS

Median PTV volume was reduced by 52% when using no PTV margin compared with a 1-cm PTV margin used conventionally. The mean (± standard deviation) difference between planned and delivered dose to the PTV (V95) was 0.6% ± 0.1%. The mean cavity displacement in the anterior-posterior and superior-inferior directions was 0.6 ± 0.4 mm and 0.6 ± 0.3 mm, respectively. The mean margin required for at least 90% of the cavity to be contained by the margin for 90% of the time was 0.7 mm (5th-95th percentile: 0-2.7 mm).

CONCLUSION

Minimal intrafractional motion was observed, and the mean difference between planned and delivered dose was less than 1%. Assessment of efficacy and cosmesis of this MR-guided APBI approach is under way.