Estimation of tissue-water linear stopping power ratio of the proton beam from proton density-weighted MRI.

BACKGROUND: In MRI-integrated radiotherapy, image registration between magnetic resonance imaging (MRI) and computed tomography (CT) can introduce systematic errors of up to 5 mm. To avoid such errors in proton therapy, one of the prerequisites is the determination of the tissue-water linear stopping power ratio S tissue , water ${S}_{\textit{tissue},\ \mathrm{water}}$ from MRI for treatment planning. PURPOSE: S tissue , water ${S}_{\textit{tissue},\ \mathrm{water}}$ depends on the elemental composition of the medium. Proton density-weighted MRI measures the concentration of hydrogen ( 1 1 H ${}_1^1{\mathrm{H}}$ ), which is independent of the magnetic field strength. This study evaluated the potential of proton density-weighted MRI to estimate S tissue , water ${S}_{\textit{tissue},\ \mathrm{water}}$ in MRI-integrated proton therapy. METHODS: Based on ICRU 46, we analyzed and modeled the relationship between tissue-water hydrogen concentration ratio H t i s s u e , water ${{H}_{tissue,\ {\mathrm{water}}}}$ and S t i s s u e , water ${{S}_{tissue,\ {\mathrm{water}}}}$ at 100 MeV proton energy using linear regression. The model was evaluated for the accuracy of the regression fit and tissue composition variability at proton energies from 70-230 MeV. To assess the accuracy of proton density-weighted MRI, we developed a deuterium oxide (D2O)-water (H2O) phantom that replicates the hydrogen concentration range in human tissues. Fast spin-echo (FSE) and gradient-echo (GRE)-based sequences were compared. Positional and voxel-level signal variability were investigated. RESULTS AND DISCUSSION: For soft and bone tissues, there was a linear correlation (R2 = 0.99) between H t i s s u e , water ${{H}_{tissue,\ {\mathrm{water}}}}$ and S t i s s u e , water ${{S}_{tissue,\ {\mathrm{water}}}}$ . The inflated lung deviated from this correlation because it includes air volume, which reduces H t i s s u e , water ${{H}_{tissue,\ {\mathrm{water}}}}$ and S t i s s u e , water ${{S}_{tissue,\ {\mathrm{water}}}}$ significantly. By incorporating air and compressed lung from ICRP 110, a linear correlation (R2 = 1.00) was found for lung-related tissues. The D2O-H2O phantom covered the hydrogen concentration range ( H s o l u t i o n , water ${{H}_{solution,{\mathrm{\ water}}}}$  = 0.30-1.00) relevant to human tissue. A partial molar volume effect in the phantom emphasized the need for mass density measurement. The FSE sequence provided higher image quality and demonstrated a strong linear correlation (R2 = 1.00) between H s o l u t i o n , water ${{H}_{solution,{\mathrm{\ water}}}}$ and signal-noise ratio (SNR). By contrast, the GRE showed distortion artifacts. Based on the evaluation criteria, composite uncertainties were 6.89%, 3.00%, and 1.92% for soft, bone, and lung tissues, respectively. Adipose tissue contributed significantly to soft tissue uncertainties. CONCLUSIONS: The relationship between H t i s s u e , water ${{H}_{tissue,\ {\mathrm{water}}}}$ and S t i s s u e , water ${{S}_{tissue,\ {\mathrm{water}}}}$ remained consistent despite variability in tissue composition and treatment energies. The D2O-H2O phantom, which is simple and reproducible, proved effective for accurately calibrating proton density-weighted MRI against H t i s s u e , water ${{H}_{tissue,\ {\mathrm{water}}}}$ . These findings demonstrate the potential of proton density-weighted MRI to directly estimate S t i s s u e , water ${{S}_{tissue,\ {\mathrm{water}}}}$ . A separate method to identify adipose through lipid concentration measurement may further improve accuracy in soft tissues.