Feasibility and accuracy of quantitative imaging on a 1.5 T MR-linear accelerator

Kooreman, Ernst S.; Houdt, Petra J. van; Nowee, Marlies E.; Pelt, V.W.J. Van; Tijssen, Rob H N; Paulson, E.S.; Gurney‐Champion, Oliver J.; Wang, Jihong; Koetsveld, F.; Buuren, L. D. van; Beek, Leon C. ter; Heide, Uulke A. van der

doi:10.1016/j.radonc.2019.01.011

Cited by 90 publications

(111 citation statements)

References 39 publications

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“…In a recent multisite study, qMRI images (T1, T2, ADC maps and Dynamic Contrast Enhanced (DCE) images) were acquired on a 1.5 T MR-linac and demonstrated in a prostate cancer patient. 10 Similar to our work on a 0.35 T MR-linac, repeated measurements on the 1.5 T MR-linac also showed low intersession CV for the T1, T2, and ADC values that were measured in phantom inserts.…”

Section: Discussionsupporting

confidence: 82%

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Rapid multicontrast brain imaging on a 0.35T MR‐linac

et al. 2020

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Purpose: Magnetic resonance-guided radiation therapy (MRgRT) has shown great promise for localization and real-time tumor monitoring. However, to date, quantitative imaging has been limited for low field MRgRT. This work benchmarks quantitative T1, R2*, and Proton Density (PD)mapping in a phantom on a 0.35 T MR-linac and implements a novel acquisition method, STrategically Acquired Gradient Echo (STAGE). To further validate STAGE in a clinical setting, a pilot study was undertaken in a cohort of brain tumor patients to elucidate opportunities for longitudinal functional imaging with an MR-linac in the brain. Methods: STAGE (two triple-echo gradient echo (GRE) acquisitions) was optimized for a 0.35T low-field MR-linac. Simulations were performed to choose two flip angles to optimize signal-tonoise ratio (SNR) and T1-mapping precision. Tradeoffs between SNR, scan time, and spatial resolution for whole-brain coverage were evaluated in healthy volunteers. Data were inputted into a STAGE processing pipeline to yield four qualitative images (T1-weighted, enhanced T1-weighted, protondensity (PD) weighted, and simulated FLuid-Attenuated Inversion Recovery (sFLAIR)), and three quantitative datasets (T1, PD, and R2*). A benchmarking ISMRM/NIST phantom consisting of vials with variable NiCl 2 and MnCl 2 concentrations was scanned using variable flip angles (VFA) (2-60 degrees) and inversion recovery (IR) methods at 0.35 T. STAGE and VFA T1 values of vials were compared to IR T1 values. As measures of agreement with reference values and repeatability, relative error (RE) and coefficient of variability (CV) were calculated, respectively, for quantitative MR values within the phantom vials (spheres). To demonstrate feasibility, longitudinal STAGE data (pretreatment, weekly, and~2 months post-treatment) were acquired in an IRB-approved pilot study of brain tumor cases via the generation of temporal and differential quantitative MRI maps. Results: In the phantom, RE of measured VFA T1 and STAGE relative to IR reference values were 7.0 AE 2.5% and 9.5 AE 2.2% respectively. RE for the PD vials was 8.1 AE 6.8% and CV for phantom R2* measurements was 10.1 AE 9.9%. Simulations and volunteer experiments yielded final STAGE parameters of FA = 50°/10°, 1 9 1 9 3 mm 3 resolution, TR = 40 ms, TE = 5/20/34 ms in 10 min (64 slices). In the pilot study of brain tumor patients, differential maps for R2* and T1 maps were sensitive to local tumor changes and appeared similar to 3 T follow-up MRI datasets. Conclusion: Quantitative T1, R2*, and PD mapping are promising at 0.35 T agreeing well with reference data. STAGE phantom data offer quantitative representations comparable to traditional methods in a fraction of the acquisition time. Initial feasibility of implementing STAGE at 0.35 T in a patient brain tumor cohort suggests that detectable changes can be observed over time. With confirmation in a larger cohort, results may be implemented to identify areas of recurrence and facilitate adaptive radiation therapy.

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Section: Discussionsupporting

confidence: 82%

“…Furthermore, a recent multi-institutional study reported the feasibility and accuracy of performing qMRI on a 1.5 T MRgRT system using a benchmarking phantom. 10 In this study, T1, T2, ADC maps, and dynamic contrast-enhanced (DCE) images were demonstrated in a patient with prostate cancer.…”

Section: Introductionmentioning

confidence: 99%

Rapid multicontrast brain imaging on a 0.35T MR‐linac

et al. 2020

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“…To ensure the translatability of results between sites, it is desired that the sequence performance (bias and variance) on a standard phantom are reported in publications. For example, Kooreman et al used several commercial phantoms to characterize the performance of several MR-Linac scanners for quantitative imaging [110]. The phantoms used for this purpose should either be commercial or well documented, such that other sites can easily test whether their scanners have similar performance in this welldefined environment before building upon the published results.…”

Section: Reportingmentioning

confidence: 99%

Quantitative imaging for radiotherapy purposes

Gurney‐Champion

Mahmood

Schie

et al. 2020

Radiotherapy and Oncology

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Quantitative imaging biomarkers show great potential for use in radiotherapy. Quantitative images based on microscopic tissue properties and tissue function can be used to improve contouring of the radiotherapy targets. Furthermore, quantitative imaging biomarkers might be used to predict treatment response for several treatment regimens and hence be used as a tool for treatment stratification, either to determine which treatment modality is most promising or to determine patient-specific radiation dose. Finally, patient-specific radiation doses can be further tailored to a tissue/voxel specific radiation dose when quantitative imaging is used for dose painting. In this review, published standards, guidelines and recommendations on quantitative imaging assessment using CT, PET and MRI are discussed. Furthermore, critical issues regarding the use of quantitative imaging for radiation oncology purposes and resultant pending research topics are identified.

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“…Here, quantitative imaging methods are required to ensure multi-centre comparability of data and guarantee a robust basis for future interventions based on those biomarkers, such as dose painting [20][21][22].…”

Section: Imagingmentioning

confidence: 99%