First-in-human technique translation of oxygen-enhanced MRI to an MR Linac system in patients with head and neck cancer.

Background and Purpose: Tumour hypoxia is prognostic in head and neck cancer (HNC), associated with poor loco-regional control, poor survival and treatment resistance. The advent of hybrid MRI - radiotherapy linear accelerator or 'MR Linac' systems - could permit imaging for treatment adaptation based on hypoxic status. We sought to develop oxygen-enhanced MRI (OE-MRI) in HNC and translate the technique onto an MR Linac system.
Materials and Methods: MRI sequences were developed in phantoms and 15 healthy participants. Next, 14 HNC patients (with 21 primary or local nodal tumours) were evaluated. Baseline tissue longitudinal relaxation time (T ₁ ) was measured alongside the change in 1/T ₁ (termed ΔR ₁ ) between air and oxygen gas breathing phases. We compared results from 1.5 T diagnostic MR and MR Linac systems.
Results: Baseline T ₁ had excellent repeatability in phantoms, healthy participants and patients on both systems. Cohort nasal concha oxygen-induced ΔR ₁ significantly increased (p < 0.0001) in healthy participants demonstrating OE-MRI feasibility. ΔR ₁ repeatability coefficients (RC) were 0.023-0.040 s ^-1 across both MR systems. The tumour ΔR ₁ RC was 0.013 s ^-1 and the within-subject coefficient of variation (wCV) was 25% on the diagnostic MR. Tumour ΔR ₁ RC was 0.020 s ^-1 and wCV was 33% on the MR Linac. ΔR ₁ magnitude and time-course trends were similar on both systems.
Conclusion: We demonstrate first-in-human translation of volumetric, dynamic OE-MRI onto an MR Linac system, yielding repeatable hypoxia biomarkers. Data were equivalent on the diagnostic MR and MR Linac systems. OE-MRI has potential to guide future clinical trials of biology guided adaptive radiotherapy.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)