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

Ernst S Kooreman, Petra J van Houdt, Marlies E Nowee, Vivian W J van Pelt, Rob H N Tijssen, Eric S Paulson, Oliver J Gurney-Champion, Jihong Wang, Folkert Koetsveld, Laurens D van Buuren, Leon C Ter Beek, Uulke A van der Heide

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77 Citations (Scopus)

Abstract

PURPOSE: Systems for magnetic resonance (MR-) guided radiotherapy enable daily MR imaging of cancer patients during treatment, which is of interest for treatment response monitoring and biomarker discovery using quantitative MRI (qMRI). Here, the performance of a 1.5 T MR-linac regarding qMRI was assessed on phantoms. Additionally, we show the feasibility of qMRI in a prostate cancer patient on this system for the first time.

MATERIALS AND METHODS: Four 1.5 T MR-linac systems from four institutes were included in this study. T1 and T2 relaxation times, and apparent diffusion coefficient (ADC) maps, as well as dynamic contrast enhanced (DCE) images were acquired. Bland-Altman statistics were used, and accuracy, repeatability, and reproducibility were determined.

RESULTS: Median accuracy for T1 ranged over the four systems from 2.7 to 14.3%, for T2 from 10.4 to 14.1%, and for ADC from 1.9 to 2.7%. For DCE images, the accuracy ranged from 12.8 to 35.8% for a gadolinium concentration of 0.5 mM and deteriorated for higher concentrations. Median short-term repeatability for T1 ranged from 0.6 to 5.1%, for T2 from 0.4 to 1.2%, and for ADC from 1.3 to 2.2%. DCE acquisitions showed a coefficient of variation of 0.1-0.6% in the signal intensity. Long-term repeatability was 1.8% for T1, 1.4% for T2, 1.7% for ADC, and 17.9% for DCE. Reproducibility was 11.2% for T1, 2.9% for T2, 2.2% for ADC, and 18.4% for DCE.

CONCLUSION: These results indicate that qMRI on the Unity MR-linac is feasible, accurate, and repeatable which is promising for treatment response monitoring and treatment plan adaptation based on daily qMRI.

Original languageEnglish
Pages (from-to)156-162
Number of pages7
JournalRadiotherapy and oncology
Volume133
DOIs
Publication statusPublished - Apr 2019

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