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Challenges and developments of magnetic resonance image-guided radiation therapy for brain tumors

1 Department of Radiation Oncology, Yashoda Hospitals, Yashoda Cancer Institute, Hyderabad, Telangana; School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, India
2 School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, India

Date of Submission04-Aug-2020
Date of Decision28-Dec-2020
Date of Acceptance12-Jan-2021
Date of Web Publication13-Apr-2021

Correspondence Address:
Anu Radha Chandrasekaran,
School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jcrt.JCRT_1023_20

 > Abstract 

Treatment of brain lesions with magnetic resonance imaging (MRI) is indispensable. Although computed tomography (CT) is the gold standard for radiotherapy (RT) planning, recent developments in image-guided RT have compelling reasons to remove CT from the regular RT workflow. Thus, magnetic resonance (MR) only RT is gaining interest rapidly. In this review, we look at how MRI has gained the importance in radiation planning at various stages and why we try to refrain CT imaging. We have elaborated the MR simulation techniques for the brain from different expertise to get a clear insight about the imaging protocols and quality assurance steps tweaked for RT requirements. We have described the basic and complex algorithms utilized to promulgate a CT-like data set from appropriate MR sequences for crucial treatment planning process. In a small section, we have narrated the significance of dose escalation using the functional MR images. In the final section, we describe a pivotal (yet least researched) area of digital radiograph generation using MR dataset for day-to-day pretreatment image verification on couch.

Keywords: Brain tumors, dose escalation, magnetic resonance only radiotherapy, magnetic resonance simulation, synthetic computed tomography

How to cite this URL:
Ilamurugu A, Chandrasekaran AR. Challenges and developments of magnetic resonance image-guided radiation therapy for brain tumors. J Can Res Ther [Epub ahead of print] [cited 2022 Dec 4]. Available from: https://www.cancerjournal.net/preprintarticle.asp?id=313663

 > Introduction Top

Poor soft-tissue contrast and radiation dose are the primary concerns to exclude the computed tomography (CT) scans from the radiotherapy (RT) process. Former is the most compelling reason that made RT community to consider magnetic resonance imaging (MRI) as the most viable imaging solution. As such MRI is not new to the RT planning and has been used in conjunction with CT images.[1],[2] CT images are gold standard in RT planning since the advent of computerized planning.[3] A rigid registered CT-magnetic resonance (MR) data set helps in obtaining MR-based volumes for target delineation and CT-based electron densities for dose calculations. Furthermore, there are problems associated with the MR-CT registration process which can be avoided if MRI is directly used for RT planning and delivery.

For the effective use of MR image for target delineation, it is routinely coregistered with the CT image which is exclusively done for the treatment planning purpose. Vendors associated with radiation treatment planning (RTP) have come out with best registration algorithms to register the CT and MR; often using the mutual information from the datasets. There are very few studies to quantify the rigid registrations between two different image sequences. Contour-based analysis postregistration is one of the methods to verify the registration algorithms. Registration between images is inevitable process in the treatment planning process as there are differences in the patient anatomy during MR and CT examination. Accuracy of contours done on planning CT with the MR images in background depends on the credibility of image fusion process. The uncertainty of registration error is hardly quantified in RT.

The world is moving toward MR only planning, and there is cost benefit and reduced workload if CT imaging is ruled out from radiation planning. In this review, we see the development of MR-based simulation, treatment planning with credible dose escalation, and delivery methods up-to-date in brain tumors. An electronic search in performed and peer-reviewed English publications was sorted for this overview. The search terms include “CT versus MRI in oncology,” “advantages of MRI over CT in brain tumors,” “MR imaging in radiation therapy planning,” “MR simulation,” “synthetic CT generation methods,” “DRR verification for MR only radiotherapy,” “dose escalation in radiotherapy,” and “dose escalation using functional MRI.” The references in the popular review and original articles were also chosen. Primarily, they were sorted based on the abstract information, and later full papers were collected.

 > Rationale Top

The use of MR imaging in RT planning was evaluated way back in 1985 by Shuman et al.,[4] where three-dimensional (3D) planning was not prevalent. They found a measurable difference in the plan when MR was made available in addition to CT. It was a work in progress at that time and they predicted that MR will become a necessary procedure in planning for many cases, as they increased confidence in the original plan. Vaghi et al.,[5] in 1986, found that MR imaging has the upper hand in depicting the extension of tumor and its anatomic relationship for cerebral gliomas. They showed that the differentiation between tumor and edema was difficult using CT images, whereas the tumor and the necrotic areas are clearly evident using MR images.

Shuman et al. in 1987, have investigated the benefit of MR imaging in Oligodendro-Glioma[6] of nine patients. In six out of nine cases, MR found tumor volumes which were not evident in CT. The abnormality interface was well correlated using MR, especially in the tumor adjacent edema regions. They believed that MR is superior to CT in providing adequate information for radiation planning purposes. Furthermore, in December 1987, Fraass et al.[7] have widely discussed the technical considerations to integrate the MR images into planning. MRI has shown significant change in portals of ten out of 17 cases in comparison to CT as reported by Just et al.[8] CT and MR image correlation leads to improved target volume delineation in contrast to CT-alone information for RTP. This study was done by Phillips et al.[9] and Schad et al.[10] on arteriovenous malformations and basal meningiomas, respectively. [Figure 1] shows for true disease extent from MR data in comparison to CT data.
Figure 1: Visual discrimination of computed tomography versus magnetic resonance data for cranial malignancies. (a) Sagittal views of T1W contrast-enhanced magnetic resonance (TE/TR = 4.2 ms/20.7 ms) and contrast computed tomography of Grade III glioma. (b) Axial views of a patient showing clear target visualization of left-sided acoustic neuroma on three-dimensional fast spoiled gradient echo (gadolinium enhanced) magnetic resonance image (TE/TR = 1.75 ms/4.2 ms) in comparison to computed tomography with contrast. (c) Coronal and axial view comparisons of glioblastoma between T1W contrast magnetic resonance (TE/TR = 10.3 ms/17.08 ms) and Contrast-enhanced computed tomography

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The quantitative assessment and clinical utility of addition of MRI to 3D-CT-based planning were assessed by Ten Haken et al.[11] and Thornton et al.,[12] respectively, for brain neoplasms. They found that the MR data integration with CT data is essential and practical. Heesters et al., in 1993,[13] have found a large difference in field size and positions for low-grade gliomas (non-CT contrast-enhancing lesions) but not in high-grade (HG) gliomas (CT contrast-enhancing tumors). Pardo et al.[14] and Hamilton et al.[15] have explored the use of functional MRI data in RTP for brain tumors, although it yielded a less probable significance in planning. As seen from the above references, MRI is a highly preferable modality to access the cranial lesions. It provides the excellent visualization of tumor and organs-at-risk compared to CT. It also reduces the inter-observer and intra-observer variations in brain tumors. The inter-observer variation was reduced significantly by CT-MR registration for acoustic neuromas, astrocytomas, and the lesion of brainstem and cerebellum.[16],[17] Similar results were inferred by Cattaneo et al.[18] for postoperative irradiation of HG gliomas, thereby reducing the target volume margins.

 > Challenges and Developments for Magnetic Resonance-Only Radiotherapy in the Brain Top


In late 90s, registration of CT and MR images is commonly performed to define the targets for RTP. MR image suffer from geometric distortion (both patient and machine induced), whereas CT are usually regarded as geometrically stable. Spatial MR distortions vary with field strengths and acquisition protocols. It was reported as early in 2001 by Fransson et al.[19] that phantom-based correction techniques are sufficient at low magnetic fields, and patient-related distortion corrections are also needed at higher field strength. Phantom studies for distortions were further done using low-field MR.[20],[21] Indefinite geometric fidelity is an important reason that RT community is apprehensive to use MRI for RTP. MR-only RTP for the brain is promising for the same reason that the distortion will be minimal as the intracranial movements are less or negligible. In addition, the external motion for the skull can be effectively immobilized. [Table 1] summarizes that how MR simulation (for RTP) is distinct from diagnostic MR scans.
Table 1: Differentiation of magnetic resonance simulation for radiation planning from regular diagnostic magnetic resonance

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A comprehensive MR simulation protocols were introduced by Paulson et al.[22] with a 70 cm, three tesla (3T) dedicated scanner for RT procedures. The author has given practical strategies for clinical MR scans for different sites including the brain and has standardized the MR images to be used for RTP after distortion correction (postprocessing). They were successful in lodging the patient setup and immobilization devices to get uniform high contrast-to-noise ratio MR images. They also implemented quality assurance (QA) program tweaked for RT-specific MR simulation to maintain reproducibility and accuracy. Similar works to integrate MR simulation into RT workflow is done by Glide-Hurst et al.[23] They have given site-specific coils, immobilization devices, and appropriate image sequences for MR-simulation procedures. More recently, Taghizadeh et al.[24] attempted to generate nondistorted MR sequences with respect to stereotactic radiosurgery (SRS) planning [Table 2]. They have evaluated the geometric constancy and artefacts by scanning commercial phantoms with SRS frames and localizers.
Table 2: Tumor-specific magnetic resonance sequences for stereotactic radiosurgery/stereotactic radiotherapy simulation techniques

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Liney and Moerland[25] believed that present MR scanners could provide satisfactory results if relevant pulse sequence techniques [Table 3] are adopted for RTP. Their recommendations are primitive and form a good basis to implement MR-only RT planning. They have given following recommendation for dedicated/existing MR scanners to acquire scans for RT planning based on a detailed analysis in MR simulation.
Table 3: Pulse sequence techniques relevant to radiation treatment planning

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  • Field strength 1.5 >T< 3.0
  • Wide bore magnet with closed configuration
  • A flat table top to mimic RT treatment position
  • Multichannel radiofrequency (RF) coils with intensity correction
  • Verification of geometric distortion in all three planes with proper slice coverage
  • Fast or turbo spin echo should be preferred for lesser acquisition time
  • MR slice thickness should be matched with CT slice thickness for apt registration
  • Acquisition must be strictly site specific and appropriate
  • QA of image protocol must be carried our periodically.


Electron density information from CT images is vital for RT dose calculations which use megavoltage (MV) beams. As Compton interaction dominates in MV range, and it is linearly proportional to the electron density (electrons/gm), correction for tissue in-homogeneity is a gold-standard in RTP. MRI lacks this information, and this is the second most limiting factor apart from image distortions. Many authors attempted to solve this problem in the following ways:

  • Assigning bulk densities to three or more structures and performing a dosimetric comparison
  • Performing dose calculation without in-homogeneity correction and comparing with clinical CT plans
  • Developing a synthetic CT (sCT) form MR images form atlas-based/hybrid methods with or without dose comparison.

sCT generation is a promising concept and does not come without challenges. With the existing methods air, bone, soft tissue, and fat are easily segmented using a MRI image, whereas bone segmentation is crucial and difficult. It has been understood clinically that ultra-short time (UTE) MR image sequence is good for bones and connective tissue visibility better than other sequences.[26] It was recognized that tissues such as cortical bone which have short T2, the MR signal with short echo times (TE) is not detectable as these decay very rapidly and thus they appear dark. Pulse sequence with shorter TE in the range of 8–200 microseconds (μs) can be produced (thus the name UTE). These pulse sequences have TE 10–200 times shorter than the routine TE used in MR systems. Thus, the cortical bone with mean T2 of the order of 0.4 to 0.5 ms can be easily visualized.

Hsu et al.[27] have been successful in discriminating air and bone using postprocessed UTE images. Johansson et al.[28] used a Gaussian mixture regression model to link the voxel value of CT and MR sequences. They have utilized one T2-W 3D spin echo and dual UTE MRI (with different TE and flip angles) to train and generate substitute CT or sCT. There was no large difference in accuracy and considered robust as it is voxel based. They also did a pilot study to investigate the dose calculation accuracy on MRI. The dose calculation is done on CT, sCT, sCT without heterogeneity correction and on bulk-density assigned MR images. As per their results, dose calculation accuracy on sCT is improved with only 2% difference compared to the dose calculation done on sCT without heterogeneity correction.[29] This team has also investigated the accuracy of inverse planning for volumetric modulated arc therapy and a geometric comparison of digitally reconstructed radiographs (DRR) derived from sCT and actual CT for brain lesions.[30] A typical flowchart of sCT preparation is show in [Figure 2].
Figure 2: A typical flowchart for the generation of synthetic computed tomography using Atlas-based method

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Further studies were carried out to verify the dosimetric accuracy of MR generated sCT by various methods and models, and the results were fruitful for brain tumors.[31],[32],[33] The dose volume histogram spread of all plans and the least difference of isodose comparison between clinical CT and sCT for brain gives us more confidence. Investigation of dose calculation variation of bulk-density assigned fast-spoiled gradient echo MR image is done to figure out if there is a little deviation between the plans with and without progressive resolution optimization.[34] This study was deliberately done in the cerebellopontine region to rule out any significance of re-optimization (without changing the constraints) in highly heterogeneous area. Koivula et al. have done a feasibility study of MR-only planning for proton therapy treatment plans (intensity modulated proton therapy). The author has observed maximum absolute dose difference of 8.9% and 1.4% for homogeneous and heterogeneous sCT, respectively, for brain tumor clinical target volumes.[35] Rank et al.[36] have also noted very small deviation for ion and photon-based treatment plans in the brain regions. More recently, dosimetric evaluation of MR-based sCT was done for large cohort of 52 patients in the cranial regions and found accurate.[37]

Dose escalation

New technologies in RT have made a progressive contribution in the past two decades for dose escalation (for example, advent of multi-leaf collimators). Functional MRI is one such modality which has the potential to discriminate the aggressive nature of tumors and help us to escalate the dose[38] suitably [Figure 3]. This will have a meaningful influence on treatment outcomes. Highly packed tumor cells reduce extracellular diffusion compared to the intracellular diffusion. Detection of this hypercellularity in tumors is the basis for diffusion-weighted imaging (DWI). Zhu et al. (from Mreading in RT, 3rd Edition ESTRO 2017, 26–31) showed that high b-value (3000 s/mm2) DWI improves the accuracy of target delineation by detecting hyper-cellular components in glioblastoma (GBM) with high specificity. They evaluated that gross tumor volume definition is possibly improved with increase in the sensitivity of DWI.
Figure 3: A pictorial representation of dose escalation schema (b) in comparison to routine treatment volumes (a); GTV - Gross tumor volume; CTV - Clinical target volume; PTV - Planning target volume; BTV - Biological target volume.

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Rogers et al. (Mreading in RT, 2nd Edition ESTRO 2016, 29–31) have explored diffusion tensor imaging along with fractional angiography to adequately include the regions of microscopic filtration and exclude the normal brain for HG gliomas. They derived biological contours instead of regular clinical contours from T1W contrast MRI. This helps prevents the risk of neurotoxicity by irradiating large volumes in the brain. Spectroscopic MRI (sMRI) of GBM is studied for prominent dose escalation by Saumya et al. They believed that not escalating the dose beyond 60 Gy and inability to identify the high-risk tumor lead to disease progression and recurrence. As image processing and expertise in sMRI complicate the implementation, they have developed a brain imaging collaboration suite to integrate sMRI to evaluate metabolic activity (Mreading in RT, 4th Edition ESTRO 2018, 40–43). This has enabled physicians to delineate tumor on voxel basis to selectively give higher dose (up to 75Gy) in RT planning.

Although surgical resections for GBM are still routinely performed, the ability of MR-IGRT has the potential to obviate the need for surgery in future. With the ablative doses, and with and without the utilization of biologic agents during MR imaging, a novel noninvasive stereotactic radiation could be performed before the regular conformal RT dose of 60Gy to improve the prognosis.[39] Integrated MR systems would be used to both radiation and chemoresponses. With adaptive planning tools available, nonresponsive areas could be dose escalated designed on the daily basis and could be delivered online. Early response assessment post-RT MR imaging could be done in a treatment room itself to determine residual areas with disease.[40]

Treatment delivery

Beam delivery is incomplete without verification image. Image verification is next big challenge for MR-only RT where DRR cannot be directly generated from MRI sequence unlike CT. Radiation units, worldwide employ either MV or Kilovoltage (kV)-based portal images for verification and target localization. In routine CT-based treatments, patient setup is verified using kV or MR image pairs primarily against DRR produced from CT datasets. Poor bone visualization of regular MR sequence poses problem in the generation of DRR too. As MR-simulation is clinically feasible as discussed earlier, it is compelling that MR-simulation images need to be transformed into a “CT-like” DRR image to validate the patient setup on daily basis. Ramsey and Oliver in 1998 have attempted MR-derived DRR[41] images from T1-weighted scan sequence of anthromorphic RANDO head phantom and found equivalent to a CT based DRR. Yin et al. have also concluded that MR-DRR could be used as a reference for portal verification.[42] In 1999, Ramsey et al.[43] have demonstrated the clinical utility of MR-DRR for setup verification which has come about 3–10 mm of misalignments. Contrast-enhanced T1-W MR scans with a slice thickness of 5 mm were acquired using 1.5 T scanner (using standard head coil) for this study.

Yang et al.[44] have been able to capture cranial, facial, and vertebral landmarks using UTE images which uses ultrashort T2 signals. They have accessed the accuracy of UTE-based DRRs for cranial tumors. A single UTE-MRI protocol with flip angle of 18° is acquired in 50% less time in contrast to the twin protocol proposed by Johansson et al.[28] Manual reference points were used to find the registration discrepancies in the range of sub-millimeters between CT-DRR and UTE-DRR, which is quite remarkable. Price et al.[45] have found a close agreement between the accuracy of sCT generated DRR to regular CT-DRR. They have evaluated volumetric and planar images using phantom as well as brain patients. This work strongly backs the implementation of MR-only treatment in the brain. It has been shown that MR-based DRRs could very well replace CT-based DRRs for MR only treatment.

 > Magnetic Resonance-Guided Radiotherapy Systems Top

VewRay developed its first commercial MR-guided RT system[46],[47] which combines both MR imaging and intensity-modulated radiation therapy. This system has been in use since 2014, comprises 0.35 T MRI and houses 3 Cobalt-60 sources for beam delivery with simultaneous tumor tracking facility (gating). The RF signal interference from Linac and the impact of magnetic field on the path of electrons in an MR-Linac are avoided. This system fits in any existing Linac vaults which avoids delay in installation. The MR-linac version from VewRay Inc. (Oakward, USA) integrates a 0.35 T MRI with a 6MV flattening-filter-free linear accelerator.[48] This system offers pretreatment and posttreatment MR imaging of a patient. It offers real-time organ position and automated beam gating (SmartTARGET) for accurate dose delivery, whereby the clinicians could escalate dose wherever possible. It also offers integrated adaptive treatment which allows re-optimization of treatment plan with current treatment position (SmartADAPT).

The Elekta Unity system has been developed and started its clinical used in 2017.[49] This hybrid 1.5 T MR-linac is built in UMC Utrecht with Electa AB (Stokholm, Sweden) and Philips (Best, The Netherlands).[50] The goal of the integration is to enable the visualization of soft tissue and other anatomical changes directly from the couch top during the course of treatment.[51] Daily MRI is used for position verification, replanning, dose accumulation, or real-time replanning.

Particle therapy (PT) along with MR imaging could be used instead of photons. MR-integrated proton therapy (MRiPT) hybrid systems offer unprecedented soft-tissue contrast of MRI with most conformal, best dose steering capability provided by modern PT.[52] MRiPT is in its infancy stages and several research groups have started addressing the technical difficulties to bring into clinical reality.[53] The challenges associated with the systems are magnetic interactions between the MRI and PT system,[54] prediction and measurements of dose in the presence of magnetic fields,[55] dose calculation from MR information and hardware and software improvements.[56]

 > Conclusion Top

The future of MR RT will not only help us to “see what we treat” but also to “look what we have done.” Thus, we see a huge opportunity for tumor visualization from accurate MRI sequences to use directly for treatment planning. Furthermore, the treatment delivery and monitoring the tumor response almost on a day-to-day basis for plan adaptation and/or dose escalation are very much feasible with MR-only RT.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

 > References Top

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  [Figure 1], [Figure 2], [Figure 3]

  [Table 1], [Table 2], [Table 3]


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