Abstract

Curative-intent radiotherapy plays an integral role in the treatment of lung cancer and therefore improving its therapeutic index is vital. MR guided radiotherapy (MRgRT) systems are the latest technological advance which may help with achieving this aim. The majority of MRgRT treatments delivered to date have been stereotactic body radiation therapy (SBRT) based and include the treatment of (ultra-) central tumors. However, there is a move to also implement MRgRT as curative-intent treatment for patients with inoperable locally advanced NSCLC. This paper presents the initial clinical experience of using the two commercially available systems to date: the ViewRay MRIdian and Elekta Unity. The challenges and potential solutions associated with MRgRT in lung cancer will also be highlighted.

Highlights

  • Lung Cancer in Contextstereotactic body radiation therapy (SBRT) plays an important role in the curative-intent treatment of medically inoperable patients with early-stage NSCLC [1, 2]

  • The initial clinical experience of thoracic MR guided radiotherapy (MRgRT) has mainly included the use of SBRT for the treatment of early-stage lung cancer [30,31,32,33,34,35,36,37,38]

  • Adaptive MRgRT for lung SBRT was found to improve organs at risk (OARs) sparing in 88% of treatments and improve PTV coverage compared to a nonadaptive plan in a small cohort [34]

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Summary

INTRODUCTION

SBRT plays an important role in the curative-intent treatment of medically inoperable patients with early-stage NSCLC [1, 2]. MRgRT may improve the therapeutic index of radiotherapy treatment for lung cancer Another advantage of MRgRT is the ability to acquire functional imaging to assess response and to potentially permit adaptive workflows based on biological information [13]. MRgRT may prove advantageous to patients with locally advanced disease, especially in more challenging cases where other imaging modalities, e.g., CT (Computed Tomography) and 18Fluorodeoxyglucose-Positron Emission Tomography (FDGPET) may fail to provide enough planning information. Examples of this include the ability to better assess tumor invasion into surrounding tissue (e.g., mediastinum, chest-wall) or where the tumor is abutting collapsed lung. As of March 2020, 236 peer-reviewed publications on the development and implementation of the system have been produced [28, 29]

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DATA AVAILABILITY STATEMENT
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