4.7 Article

ADC measurements on the Unity MR-linac - A recommendation on behalf of the Elekta Unity MR-linac consortium

Journal

RADIOTHERAPY AND ONCOLOGY
Volume 153, Issue -, Pages 106-113

Publisher

ELSEVIER IRELAND LTD
DOI: 10.1016/j.radonc.2020.09.046

Keywords

MR-linac; Diffusion weighted imaging; DWI; ADC; Recommendation

Funding

  1. German Research Council (DFG) [ZI 736/2-1, TH 1528/6-1]
  2. Elekta Instruments AB
  3. Elekta AB
  4. Philips Healthcare
  5. ITEA project 'Starlit'

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Background and purpose: Diffusion-weighted imaging (DWI) for treatment response monitoring is feasible on hybrid magnetic resonance linear accelerator (MR-linac) systems. The MRI scanner of the Elekta Unity system has an adjusted design compared to diagnostic scanners. We investigated its impact on measuring the DWI-derived apparent diffusion coefficient (ADC) regarding three aspects: the choice of b-values, the spatial variation of the ADC, and scanning during radiation treatment. The aim of this study is to give recommendations for accurate ADC measurements on Unity systems. Materials and methods: Signal-to-noise ratio (SNR) measurements with increasing b-values were done to determine the highest bvalue that can be measured reliably. The spatial variation of the ADC was assessed on six Unity systems with a cylindrical phantom of 40 cm diameter. The influence of gantry rotation and irradiation was investigated by acquiring DWI images before and during treatment of 11 prostate cancer patients. Results: On the Unity system, a maximum b-value of 500 s/mm(2) should be used for ADC quantification, as a trade-off between SNR and diffusion weighting. Accurate ADC values were obtained within 7 cm from the iso-center, while outside this region ADC values deviated more than 5%. The ADC was not influenced by the rotating linac or irradiation during treatment. Conclusion: We provide Unity system specific recommendations for measuring the ADC. This will increase the consistency of ADC values acquired in different centers on the Unity system, enabling large cohort studies for biomarker discovery and treatment response monitoring. (C) 2020 Elsevier B.V. All rights reserved.

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