Validation of proton stopping power ratio estimation based on dual energy CT using fresh tissue samples. (14th December 2017)

• Record Type: Journal Article
• Authors: Taasti, Vicki T; Michalak, Gregory J; Hansen, David C; Deisher, Amanda J; Kruse, Jon J; Krauss, Bernhard; Muren, Ludvig P; Petersen, Jørgen B B; McCollough, Cynthia H
• Is Part Of: Physics in medicine & biology. Volume 63:Number 1(2018:Jan.)
• Publication Date: 2017-12-14
• Subjects: proton therapy -- treatment planning -- stopping power ratio -- dual energy CT -- organic tissue measurements -- proton pencil beam measurements; Biophysics -- Periodicals; Medical physics -- Periodicals; 610.153
• DOI: 10.1088/1361-6560/aa952f
• Languages: English
• ISSNs: 0031-9155

Abstract

Abstract: Dual energy CT (DECT) has been shown, in theoretical and phantom studies, to improve the stopping power ratio (SPR) determination used for proton treatment planning compared to the use of single energy CT (SECT). However, it has not been shown that this also extends to organic tissues. The purpose of this study was therefore to investigate the accuracy of SPR estimation for fresh pork and beef tissue samples used as surrogates of human tissues. The reference SPRs for fourteen tissue samples, which included fat, muscle and femur bone, were measured using proton pencil beams. The tissue samples were subsequently CT scanned using four different scanners with different dual energy acquisition modes, giving in total six DECT-based SPR estimations for each sample. The SPR was estimated using a proprietary algorithm ( syngo .via DE Rho/Z Maps, Siemens Healthcare, Forchheim, Germany) for extracting the electron density and the effective atomic number. SECT images were also acquired and SECT-based SPR estimations were performed using a clinical Hounsfield look-up table. The mean and standard deviation of the SPR over large volume-of-interests were calculated. For the six different DECT acquisition methods, the root-mean-square errors (RMSEs) for the SPR estimates over all tissue samples were between 0.9% and 1.5%. For the SECT-based SPR estimation the RMSE was 2.8%. For one DECT acquisition method, a positive bias was seen in the SPR estimates, having a mean error of 1.3%. The largest errors were found in the very dense cortical bone from a beef femur. This study confirms the advantages of DECT-based SPR estimation although good results were also obtained using SECT for most tissues.