Respiratory motion compensation for simultaneous PET/MR based on highly undersampled MR data

PET/MR enterography in inflammatory bowel disease: A review of applications and technical considerations

Positron emission tomography (PET) magnetic resonance (MR) enterography is a novel hybrid imaging technique that is gaining popularity in the study of complex inflammatory disorders of the gastrointestinal system, such as inflammatory bowel disease (IBD). This imaging technique combines the metabolic information of PET imaging with the spatial resolution and soft tissue contrast of MR imaging. Several studies have suggested potential roles for PET/MR imaging in determining the activity status of IBD, evaluating treatment response, stratifying risk, and predicting long-term clinical outcomes. However, there are challenges in generalizing findings due to limited studies, technical aspects of hybrid MR/PET imaging, and clinical indications of this imaging modality. This review aims to further elucidate the possible role of PET/MR in IBD, highlight important technical aspects of imaging, and address potential pitfalls and prospects of this modality in IBDs.

On the correction of respiratory motion-induced image reconstruction errors in positron-emission tomography-guided radiation therapy

Background and purpose

Free breathing (FB) positron emission tomography (PET) images are routinely used in radiotherapy for lung cancer patients. Respiration-induced artifacts in these images compromise treatment response assessment and obstruct clinical implementation of dose painting and PET-guided radiotherapy. The purpose of this study is to develop a blurry image decomposition (BID) method to correct motion-induced image-reconstruction errors in FB-PETs.

Materials and methods

Assuming a blurry PET is represented as an average of multi-phase PETs. A four-dimensional computed-tomography image is deformably registered from the end-inhalation (EI) phase to other phases. With the registration-derived deformation maps, PETs at other phases can be deformed from a PET at the EI phase. To reconstruct the EI-PET, the difference between the blurry PET and the average of the deformed EI-PETs is minimized using a maximum-likelihood expectation-maximization algorithm. The developed method was evaluated with computational and physical phantoms as well as PET/CT images acquired from three patients.

Results

The BID method increased the signal-to-noise ratio from 1.88 ± 1.05 to 10.5 ± 3.3 and universal-quality index from 0.72 ± 0.11 to 1.0 for the computational phantoms, and reduced the motion-induced error from 69.9% to 10.9% in the maximum of activity concentration and from 317.5% to 8.7% in the full width at half maximum of the physical PET-phantom. The BID-based corrections increased the maximum standardized-uptake values by 17.7 ± 15.4% and reduced tumor volumes by 12.5 ± 10.4% on average for the three patients.

Conclusions

The proposed image-decomposition method reduces respiration-induced errors in PET images and holds potential to improve the quality of radiotherapy for thoracic and abdominal cancer patients.

MR-assisted PET respiratory motion correction using deep-learning based short-scan motion fields

PURPOSE

We evaluated the impact of PET respiratory motion correction (MoCo) in a phantom and patients. Moreover, we proposed and examined a PET MoCo approach using motion vector fields (MVFs) from a deep-learning reconstructed short MRI scan.

METHODS

The evaluation of PET MoCo was performed in a respiratory motion phantom study with varying lesion sizes and tumor to background ratios (TBRs) using a static scan as the ground truth. MRI-based MVFs were derived from either 2000 spokes (MoCo2000 , 5-6 min acquisition time) using a Fourier transform reconstruction or 200 spokes (MoCoP2P200 , 30-40 s acquisition time) using a deep-learning Phase2Phase (P2P) reconstruction and then incorporated into PET MoCo reconstruction. For six patients with hepatic lesions, the performance of PET MoCo was evaluated using quantitative metrics (SUVmax , SUVpeak , SUVmean , lesion volume) and a blinded radiological review on lesion conspicuity.

RESULTS

MRI-assisted PET MoCo methods provided similar results to static scans across most lesions with varying TBRs in the phantom. Both MoCo2000 and MoCoP2P200 PET images had significantly higher SUVmax , SUVpeak , SUVmean and significantly lower lesion volume than non-motion-corrected (non-MoCo) PET images. There was no statistical difference between MoCo2000 and MoCoP2P200 PET images for SUVmax , SUVpeak , SUVmean or lesion volume. Both radiological reviewers found that MoCo2000 and MoCoP2P200 PET significantly improved lesion conspicuity.

CONCLUSION

An MRI-assisted PET MoCo method was evaluated using the ground truth in a phantom study. In patients with hepatic lesions, PET MoCo images improved quantitative and qualitative metrics based on only 30-40 s of MRI motion modeling data.

Adapting Imaging Protocols for PET-CT and PET-MRI for Immunotherapy Monitoring

Hybrid imaging with positron emission tomography (PET) in combination with computer tomography (CT) is a well-established diagnostic tool in oncological staging and restaging. The combination of PET with magnetic resonance imaging (MRI) as a clinical scanner was introduced approximately 10 years ago. Although MRI provides superb soft tissue contrast and functional information without the radiation exposure of CT, PET-MRI is not as widely introduced in oncologic imaging as PET-CT. One reason for this hesitancy lies in the relatively long acquisition times for a PET-MRI scan, if the full diagnostic potential of MRI is exploited. In this review, we discuss the possible advantages of combined imaging protocols of PET-CT and PET-MRI, within the context of staging and restaging of patients under immunotherapy, in order to achieve "multi-hybrid imaging" in one single patient visit.

Synergistic motion compensation strategies for positron emission tomography when acquired simultaneously with magnetic resonance imaging

Subject motion in positron emission tomography (PET) is a key factor that degrades image resolution and quality, limiting its potential capabilities. Correcting for it is complicated due to the lack of sufficient measured PET data from each position. This poses a significant barrier in calculating the amount of motion occurring during a scan. Motion correction can be implemented at different stages of data processing either during or after image reconstruction, and once applied accurately can substantially improve image quality and information accuracy. With the development of integrated PET-MRI (magnetic resonance imaging) scanners, internal organ motion can be measured concurrently with both PET and MRI. In this review paper, we explore the synergistic use of PET and MRI data to correct for any motion that affects the PET images. Different types of motion that can occur during PET-MRI acquisitions are presented and the associated motion detection, estimation and correction methods are reviewed. Finally, some highlights from recent literature in selected human and animal imaging applications are presented and the importance of motion correction for accurate kinetic modelling in dynamic PET-MRI is emphasized. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Imaging coronary plaques using 3D motion-compensated [18F]NaF PET/MR

Background

Cardiac PET has recently found novel applications in coronary atherosclerosis imaging using [¹⁸F]NaF as a radiotracer, highlighting vulnerable plaques. However, the resulting uptakes are relatively small, and cardiac motion and respiration-induced movement of the heart can impair the reconstructed images due to motion blurring and attenuation correction mismatches. This study aimed to apply an MR-based motion compensation framework to [¹⁸F]NaF data yielding high-resolution motion-compensated PET and MR images.

Methods

Free-breathing 3-dimensional Dixon MR data were acquired, retrospectively binned into multiple respiratory and cardiac motion states, and split into fat and water fraction using a model-based reconstruction framework. From the dynamic MR reconstructions, both a non-rigid cardiorespiratory motion model and a motion-resolved attenuation map were generated and applied to the PET data to improve image quality. The approach was tested in 10 patients and focal tracer hotspots were evaluated concerning their target-to-background ratio, contrast-to-background ratio, and their diameter.

Results

MR-based motion models were successfully applied to compensate for physiological motion in both PET and MR. Target-to-background ratios of identified plaques improved by 7 ± 7%, contrast-to-background ratios by 26 ± 38%, and the plaque diameter decreased by −22 ± 18%. MR-based dynamic attenuation correction strongly reduced attenuation correction artefacts and was not affected by stent-related signal voids in the underlying MR reconstructions.

Conclusions

The MR-based motion correction framework presented here can improve the target-to-background, contrast-to-background, and width of focal tracer hotspots in the coronary system. The dynamic attenuation correction could effectively mitigate the risk of attenuation correction artefacts in the coronaries at the lung-soft tissue boundary. In combination, this could enable a more reproducible and reliable plaque localisation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-020-05180-4.

Motion correction for PET data using subspace-based real-time MR imaging in simultaneous PET/MR

Image quality of positron emission tomography (PET) reconstructions is degraded by subject motion occurring during the acquisition. Magnetic resonance (MR)-based motion correction approaches have been studied for PET/MR scanners and have been successful at capturing regular motion patterns, when used in conjunction with surrogate signals (e.g. navigators) to detect motion. However, handling irregular respiratory motion and bulk motion remains challenging. In this work, we propose an MR-based motion correction method relying on subspace-based real-time MR imaging to estimate motion fields used to correct PET reconstructions. We take advantage of the low-rank characteristics of dynamic MR images to reconstruct high-resolution MR images at high frame rates from highly undersampled k-space data. Reconstructed dynamic MR images are used to determine motion phases for PET reconstruction and estimate phase-to-phase nonrigid motion fields able to capture complex motion patterns such as irregular respiratory and bulk motion. MR-derived binning and motion fields are used for PET reconstruction to generate motion-corrected PET images. The proposed method was evaluated on in vivo data with irregular motion patterns. MR reconstructions accurately captured motion, outperforming state-of-the-art dynamic MR reconstruction techniques. Evaluation of PET reconstructions demonstrated the benefits of the proposed method in terms of motion artifacts reduction, improving the contrast-to-noise ratio by up to a factor 3 and achieveing a target-to-background ratio up to 90% superior compared to standard/uncorrected methods. The proposed method can improve the image quality of motion-corrected PET reconstructions in clinical applications.

From Mouse to Man and Back: Closing the Correlation Gap between Imaging and Histopathology for Lung Diseases

Lung diseases such as fibrosis, asthma, cystic fibrosis, infection and cancer are life-threatening conditions that slowly deteriorate quality of life and for which our diagnostic power is high, but our knowledge on etiology and/or effective treatment options still contains important gaps. In the context of day-to-day practice, clinical and preclinical studies, clinicians and basic researchers team up and continuously strive to increase insights into lung disease progression, diagnostic and treatment options. To unravel disease processes and to test novel therapeutic approaches, investigators typically rely on end-stage procedures such as serum analysis, cyto-/chemokine profiles and selective tissue histology from animal models. These techniques are useful but provide only a snapshot of disease processes that are essentially dynamic in time and space. Technology allowing evaluation of live animals repeatedly is indispensable to gain a better insight into the dynamics of lung disease progression and treatment effects. Computed tomography (CT) is a clinical diagnostic imaging technique that can have enormous benefits in a research context too. Yet, the implementation of imaging techniques in laboratories lags behind. In this review we want to showcase the integrated approaches and novel developments in imaging, lung functional testing and pathological techniques that are used to assess, diagnose, quantify and treat lung disease and that may be employed in research on patients and animals. Imaging approaches result in often novel anatomical and functional biomarkers, resulting in many advantages, such as better insight in disease progression and a reduction in the numbers of animals necessary. We here showcase integrated assessment of lung disease with imaging and histopathological technologies, applied to the example of lung fibrosis. Better integration of clinical and preclinical imaging technologies with pathology will ultimately result in improved clinical translation of (therapy) study results.

A modern review of the uncertainties in volumetric imaging of respiratory-induced target motion in lung radiotherapy

Radiotherapy has become a critical component for the treatment of all stages and types of lung cancer, often times being the primary gateway to a cure. However, given that radiation can cause harmful side effects depending on how much surrounding healthy tissue is exposed, treatment of the lung can be particularly challenging due to the presence of moving targets. Careful implementation of every step in the radiotherapy process is absolutely integral for attaining optimal clinical outcomes. With the advent and now widespread use of stereotactic body radiation therapy (SBRT), where extremely large doses are delivered, accurate, and precise dose targeting is especially vital to achieve an optimal risk to benefit ratio. This has largely become possible due to the rapid development of image-guided technology. Although imaging is critical to the success of radiotherapy, it can often be plagued with uncertainties due to respiratory-induced target motion. There has and continues to be an immense research effort aimed at acknowledging and addressing these uncertainties to further our abilities to more precisely target radiation treatment. Thus, the goal of this article is to provide a detailed review of the prevailing uncertainties that remain to be investigated across the different imaging modalities, as well as to highlight the more modern solutions to imaging motion and their role in addressing the current challenges.

Flexible numerical simulation framework for dynamic PET-MR data

This paper presents a simulation framework for dynamic PET-MR. The main focus of this framework is to provide motion-resolved MR and PET data and ground truth motion information. This can be used in the optimisation and quantitative evaluation of image registration and in assessing the error propagation due to inaccuracies in motion estimation in complex motion-compensated reconstruction algorithms. Contrast and tracer kinetics can also be simulated and are available as ground truth information. To closely emulate medical examination, input and output of the simulation are files in standardised open-source raw data formats. This enables the use of existing raw data as a template input and ensures seamless integration of the output into existing reconstruction pipelines. The proposed framework was validated in PET-MR and image registration applications. It was used to simulate a FDG-PET-MR scan with cardiac and respiratory motion. Ground truth motion information could be utilised to optimise parameters for PET and synergistic PET-MR image registration. In addition, a free-breathing dynamic contrast enhancement (DCE) abdominal scan of a patient with hepatic lesions was simulated. In order to correct for breathing motion, a motion-corrected image reconstruction scheme was used and a Toft's model was fit to the DCE data to obtain quantitative DCE-MRI parameters. Utilising the ground truth motion information, the dependency of quantitative DCE-MR images on the accuracy of the motion estimation was evaluated. We demonstrated that respiratory motion had to be available with an average accuracy of at least the spatial resolution of the DCE-MR images in order to ensure an improvement in lesions visualisation and quantification compared to no motion correction. The proposed framework provides a valuable tool with a wide range of scientific PET and MR applications and will be available as part of the open-source project Synergistic Image Reconstruction Framework (SIRF).

What scans we will read: imaging instrumentation trends in clinical oncology

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non-invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/CT), advanced MRI, optical or ultrasound imaging.This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and, then point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now.Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by advances in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as "data", and - through the wider adoption of advanced analysis, including machine learning approaches and a "big data" concept - move to the next stage of non-invasive tumour phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi-dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging.

Impact of respiratory motion correction on lesion visibility and quantification in thoracic PET/MR imaging

The impact of a method for MR-based respiratory motion correction of PET data on lesion visibility and quantification in patients with oncologic findings in the lung was evaluated. Twenty patients with one or more lesions in the lung were included. Hybrid imaging was performed on an integrated PET/MR system using 18F-FDG as radiotracer. The standard thoracic imaging protocol was extended by a free-breathing self-gated acquisition of MR data for motion modelling. PET data was acquired simultaneously in list-mode for 5-10 mins. One experienced radiologist and one experienced nuclear medicine specialist evaluated and compared the post-processed data in consensus regarding lesion visibility (scores 1-4, 4 being best), image noise levels (scores 1-3, 3 being lowest noise), SUVmean and SUVmax. Motion-corrected (MoCo) images were additionally compared with gated images. Non-motion-corrected free-breathing data served as standard of reference in this study. Motion correction generally improved lesion visibility (3.19 ± 0.63) and noise ratings (2.95 ± 0.22) compared to uncorrected (2.81 ± 0.66 and 2.95 ± 0.22, respectively) or gated PET data (2.47 ± 0.93 and 1.30 ± 0.47, respectively). Furthermore, SUVs (mean and max) were compared for all methods to estimate their respective impact on the quantification. Deviations of SUVmax were smallest between the uncorrected and the MoCo lesion data (average increase of 9.1% of MoCo SUVs), while SUVmean agreed best for gated and MoCo reconstructions (MoCo SUVs increased by 1.2%). The studied method for MR-based respiratory motion correction of PET data combines increased lesion sharpness and improved lesion activity quantification with high signal-to-noise ratio in a clinical setting. In particular, the detection of small lesions in moving organs such as the lung and liver may thus be facilitated. These advantages justify the extension of the PET/MR imaging protocol by 5-10 minutes for motion correction.

MR-based cardiac and respiratory motion correction of PET: application to static and dynamic cardiac 18F-FDG imaging

Motion of the myocardium deteriorates the quality and quantitative accuracy of cardiac PET images. We present a method for MR-based cardiac and respiratory motion correction of cardiac PET data and evaluate its impact on estimation of activity and kinetic parameters in human subjects. Three healthy subjects underwent simultaneous dynamic 18F-FDG PET and MRI on a hybrid PET/MR scanner. A cardiorespiratory motion field was determined for each subject using navigator, tagging and golden-angle radial MR acquisitions. Acquired coincidence events were binned into cardiac and respiratory phases using electrocardiogram and list mode-driven signals, respectively. Dynamic PET images were reconstructed with MR-based motion correction (MC) and without motion correction (NMC). Parametric images of 18F-FDG consumption rates (Ki) were estimated using Patlak's method for both MC and NMC images. MC alleviated motion artifacts in PET images, resulting in improved spatial resolution, improved recovery of activity in the myocardium wall and reduced spillover from the myocardium to the left ventricle cavity. Significantly higher myocardium contrast-to-noise ratio and lower apparent wall thickness were obtained in MC versus NMC images. Likewise, parametric images of Ki calculated with MC data had improved spatial resolution as compared to those obtained with NMC. Consistent with an increase in reconstructed activity concentration in the frames used during kinetic analyses, MC led to the estimation of higher Ki values almost everywhere in the myocardium, with up to 18% increase (mean across subjects) in the septum as compared to NMC. This study shows that MR-based motion correction of cardiac PET results in improved image quality that can benefit both static and dynamic studies.

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.

Comparison of the clinical performance of upper abdominal PET/DCE-MRI with and without concurrent respiratory motion correction (MoCo)

PURPOSE

To compare the clinical performance of upper abdominal PET/DCE-MRI with and without concurrent respiratory motion correction (MoCo).

METHODS

MoCo PET/DCE-MRI of the upper abdomen was acquired in 44 consecutive oncologic patients and compared with non-MoCo PET/MRI. SUVmax and MTV of FDG-avid upper abdominal malignant lesions were assessed on MoCo and non-MoCo PET images. Image quality was compared between MoCo DCE-MRI and non-MoCo CE-MRI, and between fused MoCo PET/MRI and fused non-MoCo PET/MRI images.

RESULTS

MoCo PET resulted in higher SUVmax (10.8 ± 5.45) than non-MoCo PET (9.62 ± 5.42) and lower MTV (35.55 ± 141.95 cm³) than non-MoCo PET (38.11 ± 198.14 cm³; p < 0.005 for both). The quality of MoCo DCE-MRI images (4.73 ± 0.5) was higher than that of non-MoCo CE-MRI images (4.53±0.71; p = 0.037). The quality of fused MoCo-PET/MRI images (4.96 ± 0.16) was higher than that of fused non-MoCo PET/MRI images (4.39 ± 0.66; p < 0.005).

CONCLUSION

MoCo PET/MRI provided qualitatively better images than non-MoCo PET/MRI, and upper abdominal malignant lesions demonstrated higher SUVmax and lower MTV on MoCo PET/MRI.

Synthesis of Realistic Simultaneous Positron Emission Tomography and Magnetic Resonance Imaging Data

The investigation of the performance of different positron emission tomography (PET) reconstruction and motion compensation methods requires accurate and realistic representation of the anatomy and motion trajectories as observed in real subjects during acquisitions. The generation of well-controlled clinical datasets is difficult due to the many different clinical protocols, scanner specifications, patient sizes, and physiological variations. Alternatively, computational phantoms can be used to generate large data sets for different disease states, providing a ground truth. Several studies use registration of dynamic images to derive voxel deformations to create moving computational phantoms. These phantoms together with simulation software generate raw data. This paper proposes a method for the synthesis of dynamic PET data using a fast analytic method. This is achieved by incorporating realistic models of respiratory motion into a numerical phantom to generate datasets with continuous and variable motion with magnetic resonance imaging (MRI)-derived motion modeling and high resolution MRI images. In this paper, data sets for two different clinical traces are presented, ¹⁸F-FDG and ⁶⁸Ga-PSMA. This approach incorporates realistic models of respiratory motion to generate temporally and spatially correlated MRI and PET data sets, as those expected to be obtained from simultaneous PET-MRI acquisitions.

Motion vector field phase-to-amplitude resampling for 4D motion-compensated cone-beam CT

We propose a phase-to-amplitude resampling (PTAR) method to reduce motion blurring in motion-compensated (MoCo) 4D cone-beam CT (CBCT) image reconstruction, without increasing the computational complexity of the motion vector field (MVF) estimation approach. PTAR is able to improve the image quality in reconstructed 4D volumes, including both regular and irregular respiration patterns. The PTAR approach starts with a robust phase-gating procedure for the initial MVF estimation and then switches to a phase-adapted amplitude gating method. The switch implies an MVF-resampling, which makes them amplitude-specific. PTAR ensures that the MVFs, which have been estimated on phase-gated reconstructions, are still valid for all amplitude-gated reconstructions. To validate the method, we use an artificially deformed clinical CT scan with a realistic breathing pattern and several patient data sets acquired with a TrueBeam^TM integrated imaging system (Varian Medical Systems, Palo Alto, CA, USA). Motion blurring, which still occurs around the area of the diaphragm or at small vessels above the diaphragm in artifact-specific cyclic motion compensation (acMoCo) images based on phase-gating, is significantly reduced by PTAR. Also, small lung structures appear sharper in the images. This is demonstrated both for simulated and real patient data. A quantification of the sharpness of the diaphragm confirms these findings. PTAR improves the image quality of 4D MoCo reconstructions compared to conventional phase-gated MoCo images, in particular for irregular breathing patterns. Thus, PTAR increases the robustness of MoCo reconstructions for CBCT. Because PTAR does not require any additional steps for the MVF estimation, it is computationally efficient. Our method is not restricted to CBCT but could rather be applied to other image modalities.

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.