Experimental verification of stopping-power prediction from single- and dual-energy computed tomography in biological tissues

TL;DR

This study experimentally compares single- and dual-energy CT methods for predicting tissue stopping power, demonstrating that DECT provides more accurate predictions with lower errors, which could improve proton therapy range accuracy.

Contribution

The paper introduces an experimental setup for precise measurement of tissue stopping-power ratios and validates that DECT significantly improves prediction accuracy over SECT.

Findings

DECT achieves mean absolute error of 0.10% in SPR prediction.

SECT has a mean absolute error of 1.27%.

DECT reduces range uncertainty in biological tissues.

Abstract

An experimental setup for consecutive measurement of ion and x-ray absorption in tissue or other materials is introduced. With this setup using a 3D-printed sample container, the reference stopping-power ratio (SPR) of materials can be measured with an uncertainty of below 0.1%. A total of 65 porcine and bovine tissue samples were prepared for measurement, comprising five samples each of 13 tissue types representing about 80% of the total body mass (three different muscle and fatty tissues, liver, kidney, brain, heart, blood, lung and bone). Using a standard stoichiometric calibration for single-energy CT (SECT) as well as a state-of-the-art dual-energy CT (DECT) approach, SPR was predicted for all tissues and then compared to the measured reference. With the SECT approach, the SPRs of all tissues were predicted with a mean error of (-0.84 $\pm$ 0.12)% and a mean absolute error of (1.27 $\pm$ 0.12)%. In contrast, the DECT-based SPR predictions were overall consistent with the measured reference with a mean error of (-0.02 $\pm$ 0.15)% and a mean absolute error of (0.10 $\pm$ 0.15)%. Thus, in this study, the potential of DECT to decrease range uncertainty could be confirmed in biological tissue.