Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy

Abstract

Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft-tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision-making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.

Keywords: RT; multiparametric MRI; response assessment.

FIGURE 1

(a) clinical workflow of radiation therapy (RT) in three stages: treatment simulation, treatment planning, and image-guided treatment; (b) proposed clinical flow of RT with an additional treatment assessment stage

FIGURE 2

An illustration of magnetic resonance imaging (MRI) evolution in brain arteriovenous malformation (AVM) stereotactic radiosurgery (SRS). In this application, anatomical MRI scans are acquired for general cranial anatomy evaluation. Two physiologic scans are adopted: two-dimensional/three-dimensional based MR angiography is acquired to identify target region(s), and diffusion tensor imaging (DTI) is acquired for tractography to identify nerve tracts avoidance candidates. On-board x-ray based imaging and potential MR imaging techniques can be used for accurate target positioning purpose during SRS administration

FIGURE 3

An example of multiparametric magnetic resonance imaging (mpMRI) containing T1 post-contrast (T1+C), apparent diffusion coefficient (ADC), T1, and R2* maps estimated from data acquired pre (a) and one-month post-RT (b) from a 58-year-old woman with partially resected glioblastoma of the left temporal lobe. The DWI images used to estimate the ADC maps and the T1+C were acquired on a 3T Skyra (Siemens, Erlangen, Germany) clinical scanner and the data used to estimate T1 and R2* maps were obtained on a 0.35 T MRIdian (ViewRay, Cleveland, OH) combination MRI and RT system. The multiparametric analysis was performed for voxels within two different regions of interest (ROI). The yellow ellipse highlights the peritumoral ROI (c). The resection cavity and tumor original contrast-enhanced volume are highlighted by the inner and outer magenta circles within the peritumoral ROI, respectively. A contralateral control ROI (green ellipse) was also analyzed by the multiparametric approach (d) in order to provide a measurement of each parameter’s stability across different time points

FIGURE 4

Four case examples of breast cancer patients receiving neoadjuvant chemotherapy. The images are maximum intensity projection at baseline and follow-up examinations after 4 weeks and after completing the entire course. The top patient has an immediately operable tumor, but elects to receive NAC to facilitate surgery and achieve a better outcome. The second patient has inoperable cancer and shows a great response to NAC, which not only facilitates surgery but also further allows breast conservation. The third patient has an invasive lobular cancer, which appears to respond well; however, in the post-NAC specimen examination, the scattered cells are seen in the entire original tumor bed. For lobular cancer and non-mass lesions, minimum residual disease may present as scattered cells or cell clusters, and underestimated by magnetic resonance imaging. The last patient shows a complete response in primary cancer, but the partial response in the lymph node, suggesting the need for axillary dissection and axillary radiation

FIGURE 5

A comparison of post-enhancement dynamic contrast enhanced (DCE)-magnetic resonance imaging (MRI) (top) and diffusion weighted imaging (DWI) (b = 500 mm2/s) (bottom) images before and after single-fraction delivery of stereotactic body radiation therapy. Red CTV contour is resampled in DCE-MRI and DWI coordinates, respectively

FIGURE 6

An example HNC IMRT: (a) three-dimensional view of PTV in red; (b) PTV and dose distribution outlined on axial CT slice; (c) diffusion weighted imaging (DWI) image and (d) the corresponding ADC map assisted CTV delineation (purple segments) in (b)

FIGURE 7

multiparametric magnetic resonance imaging (mpMRI) acquired from a patient with locally advanced rectal cancer receiving neoadjuvant chemo-RT. After treatment, the signal intensity is decreased on diffusion weighted imaging (b = 800 mm2/s), suggesting the increase of apparent diffusion coefficient. The enhanced tumor area becomes smaller, also suggesting a good response