SU-E-I-97: Characterizing the Modulation Transfer Function (MTF) of Proton Radiography

J Seco; M Oumano; N Depauw; M Dias; R Teixeira

doi:10.1118/1.4734814

SU-E-I-97: Characterizing the Modulation Transfer Function (MTF) of Proton Radiography

Med Phys. 2012 Jun;39(6Part5):3647. doi: 10.1118/1.4734814.

Authors

J Seco^{1

2

3

4}, M Oumano^{1

2

3

4}, N Depauw^{1

2

3

4}, M Dias^{1

2

3

4}, R Teixeira^{1

2

3

4}

Affiliations

¹ Mass General Hospital; Harvard Medical, Boston, MA.
² University of Massachusetts at Boston, Boston, MA.
³ Massachusetts General Hospital, Boston, MA.
⁴ University of Lisbon, Lisbon, Portugal.

PMID: 28517648
DOI: 10.1118/1.4734814

Abstract

Purpose: To characterize the modulation transfer function (MTF) of proton radiography using GEANT4 Monte Carlo simulations.

Methods: A phantom was specifically modeled using five main materials: bone (1.92 g/cm³ ), muscle (1.2 g/cm³ ), water (1.0 g/cm³ ), adipose tissue (0.9 g/cm³ ), and lung (0.3 g/cm³ ). The basic geometry of the phantom consists of cube-shaped inserts of biological materials placed in water. The thickness of the water, the size of the cube, the depth of the cube in the water, and the proton beam energy have all been varied and studied. The contrast-to-noise ratio (CNR) between the two materials was evaluated at multiple points along a line-of-interest (LOI) in order to ultimately characterize the spatial resolution by the 10% point of the modulation-transfer-function (MTF10% or MTF 10).

Results: The MTF was generated for interfaces of water-lung, water-bone, water-muscle, water-adipose. This study indicates that proton radiography can distinguish one material from another with a resolution better than 1 mm for water-adipose and water-muscle or sub-millimeter in cases of water-bone and water-lung interfaces.

Conclusions: The sub-millimeter resolution of proton radiography offers clinicians a potentially tool in specific tumor diagnostics (such as in lung cancer), patient-setup for daily proton therapy, and the reduction of absorbed dose delivered when compared to photon imaging.

Keywords: Cancer; Lungs; Medical diagnosis; Modulation transfer functions; Monte Carlo methods; Muscles; Protons; Radiography; Spatial resolution; Tissues.