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Dosimetric feasibility of magnetic resonance (MR)-based dose calculation of prostate radiotherapy using multilevel threshold algorithm

Published online by Cambridge University Press:  20 June 2017

Turki Almatani*
Affiliation:
College of Medicine, Swansea University, Swansea, UK
Richard P. Hugtenburg
Affiliation:
College of Medicine, Swansea University, Swansea, UK Department of Medical Physics and Clinical Engineering, Singleton Hospital, ABM University Health Board, Swansea, UK
Ryan D. Lewis
Affiliation:
Department of Medical Physics and Clinical Engineering, Singleton Hospital, ABM University Health Board, Swansea, UK
Susan E. Barley
Affiliation:
Oncology Systems Limited, Shrewsbury, UK
Mark A. Edwards
Affiliation:
Department of Medical Physics and Clinical Engineering, Singleton Hospital, ABM University Health Board, Swansea, UK
*
Correspondence to: Turki Almatani, College of Medicine, Swansea University, Singleton Park, Swansea SA2 8PP, Tel: 0044 1792 602720. UK. E-mail: [email protected]

Abstract

Objective

The development of magnetic resonance (MR) imaging systems has been extended for the entire radiotherapy process. However, MR images provide voxel values that are not directly related to electron densities, thus MR images cannot be used directly for dose calculation. The aim of this study is to investigate the feasibility of dose calculations to be performed on MR images and evaluate the necessity of re-planning.

Methods

A prostate cancer patient was imaged using both MR and computed tomography (CT). The multilevel threshold (MLT) algorithm was used to categorise voxel values in the MR images into three segments (air, water and bone) with homogeneous Hounsfield units (HU). An intensity-modulated radiation therapy plan was generated from CT images of the patient. The plan was then copied to the segmented MR datasets and the doses were recalculated using pencil beam (PB) and collapsed cone (CC) algorithms and Monte Carlo (MC) modelling.

Results

γ Evaluation showed that the percentage of points in regions of interest with γ<1 (3%/3 mm) were more than 94% in the segmented MR. Compared with the planning CT plan, the segmented MR plan resulted in a dose difference of –0·3, 0·8 and –1·3% when using PB, CC and MC algorithms, respectively.

Conclusion

The segmentation and conversion of MR images into HU data using the MLT algorithm, used in this feasibility study, can be used for dose calculation. This method can be used as a dosimetric assessment tool and can be easily implemented in the clinic.

Type
Original Articles
Copyright
© Cambridge University Press 2017 

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