Technical Note: Relative proton stopping power estimation from virtual monoenergetic images reconstructed from dual‐layer computed tomography

Abstract

Purpose: The objective of this technical note was to investigate the accuracy of proton stopping power relative to water (RSP) estimation using a novel dual-layer, dual-energy computed tomography (DL-DECT) scanner for potential use in proton therapy planning. DL-DECT allows dual-energy reconstruction from scans acquired at a single x-ray tube voltage V by using two-layered detectors. Methods: Sets of calibration and evaluation inserts were scanned at a DL-DECT scanner in a custom phantom with variable diameter D (0 to 150 mm) at V of 120 and 140 kV. Inserts were additionally scanned at a synchrotron computed tomography facility to obtain comparative linear attenuation coefficients for energies from 50 to 100 keV, and reference RSP was obtained using a carbon ion beam and variable water column. DL-DECT monoenergetic (mono-E) reconstructions were employed to obtain RSP by adapting the Yang-Saito-Landry (YSL) method. The method was compared to reference RSP via the root mean square error (RMSE) over insert mean values obtained from volumetric regions of interest. The accuracy of intermediate quantities such as the relative electron density (RED), effective atomic number (EAN), and the mono-E was additionally evaluated. Results: The lung inserts showed higher errors for all quantities and we report RMSE excluding them. RMSE for l from DL-DECT mono-E was below 1.9%. For the evaluation inserts at D = 150 mm and V = 140 kV, RED RMSE was 1.0%, while for EAN it was 2.9%. RSP RMSE was below 0.8% for all D and V, which did not strongly affect the results. Conclusions: In this investigation of RSP accuracy from DL-DECT, we have shown that RMSE below 1% can be achieved. It was possible to adapt the YSL method for DL-DECT and intermediate quantities RED and EAN had comparable accuracy to previous publications.

Proton stopping power prediction based on dual‐energy CT‐generated virtual monoenergetic images

“…We have demonstrated that the proposed method can predict SPRs with an accuracy that, for soft tissue and bone, matches or improves on the SPRs predicted with the conventional stoichiometric method. While no direct comparison could be made to other DECT‐based methods for SPR prediction, as we found no such method that could be implemented on a fast kV‐switching system, the SPR RMSEs for soft tissue and bone in Table 4 are comparable with RMSEs reported in the literature 21‐23 …”

“…Landry et al adapted the work of Hudobivnik et al for a dual-layer DECT reporting a SPR RMSE <0.8%, and Faller et al evaluated the built-in applications for extracting EAN and RED on the same type of DECT make and model, reporting a SPR RMSE <0.6%. [21][22][23] We have not found any consensus in the literature, or in clinical codes of practice, regarding which method would constitute the best approach.…”

“…Landry et al . substituted the native low and high kV images with a pair of VM images (50 and 200 keV, based on a 140 kV x‐ray beam) in their adaptation of the method proposed by Hudobivnik et al 21,23 . The method proposed in this work does not require calibration and is applicable with any DECT scanner capable of generating VM images, that is, all currently commercially available systems.…”

“…6,8,9 Multiple approaches have been proposed to improve SPR prediction by utilizing the extra information acquired with a dual-energy CT (DECT) scanner to extract the relative electron density (RED) and effective atomic number (EAN), or the RED and the mean ionization value (I-value). [10][11][12][13][14][15][16][17][18][19][20][21][22][23] Most of the methods use native low and high kilovoltage (kV) images, and have been evaluated on DECT systems where such images are accessible, with reported SPR root mean square errors (RMSE) ranging between 0.5% and 1.5 %. 12,13,14,15,16,17,18,19,20,21,24 However, these methods are not directly applicable on the commercially available systems that uses a dual-layer detector or rapid kVswitching, as the necessary native images are not available.…”

“…6,26,27,28 Bazalova et al applied the formalism of Jackson and Hawkes on the polychromatic native low and high kV images on a dual-source system, in an approach that requires knowledge of the tissue-filtered x-ray spectra. 12 Landry et al substituted the native low and high kV images with a pair of VM images (50 and 200 keV, based on a 140 kV x-ray beam) in their adaptation of the method proposed by Hudobivnik et al 21,23 The method proposed in this work does not require calibration and is applicable with any DECT scanner capable of generating VM images, that is, all currently commercially available systems. Furthermore, compared to native kV images, VM images have been shown to stabilize the mean CT number by demonstrating the ability to compensate for beam hardening due to patient size and composition of the imaged volume.…”