Potential of a Second-Generation Dual-Layer Spectral CT for Dose Calculation in Particle Therapy Treatment Planning

质子疗法 粒子疗法 阻止力 放射治疗计划 有效原子序数 粒子(生态学) 质子 计算物理学 材料科学 核医学 离子 物理 原子序数 光学 医学 梁(结构) 原子物理学 放射科 核物理学 放射治疗 海洋学 量子力学 地质学
作者
Friderike K. Longarino,Antonia Kowalewski,Thomas Tessonnier,Stewart Mein,Benjamin Ackermann,Jürgen Debus,Andrea Mairani,Wolfram Stiller
出处
期刊:Frontiers in Oncology [Frontiers Media]
卷期号:12 被引量:5
标识
DOI:10.3389/fonc.2022.853495
摘要

In particle therapy treatment planning, dose calculation is conducted using patient-specific maps of tissue ion stopping power ratio (SPR) to predict beam ranges. Improving patient-specific SPR prediction is therefore essential for accurate dose calculation. In this study, we investigated the use of the Spectral CT 7500, a second-generation dual-layer spectral computed tomography (DLCT) system, as an alternative to conventional single-energy CT (SECT) for patient-specific SPR prediction. This dual-energy CT (DECT)-based method allows for the direct prediction of SPR from quantitative measurements of relative electron density and effective atomic number using the Bethe equation, whereas the conventional SECT-based method consists of indirect image data-based prediction through the conversion of calibrated CT numbers to SPR. The performance of the Spectral CT 7500 in particle therapy treatment planning was characterized by conducting a thorough analysis of its SPR prediction accuracy for both tissue-equivalent materials and common non-tissue implant materials. In both instances, DLCT was found to reduce uncertainty in SPR predictions compared to SECT. Mean deviations of 0.7% and 1.6% from measured SPR values were found for DLCT- and SECT-based predictions, respectively, in tissue-equivalent materials. Furthermore, end-to-end analyses of DLCT-based treatment planning were performed for proton, helium, and carbon ion therapies with anthropomorphic head and pelvic phantoms. 3D gamma analysis was performed with ionization chamber array measurements as the reference. DLCT-predicted dose distributions revealed higher passing rates compared to SECT-predicted dose distributions. In the DLCT-based treatment plans, measured distal-edge evaluation layers were within 1 mm of their predicted positions, demonstrating the accuracy of DLCT-based particle range prediction. This study demonstrated that the use of the Spectral CT 7500 in particle therapy treatment planning may lead to better agreement between planned and delivered dose compared to current clinical SECT systems.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
诚心宛筠发布了新的文献求助10
1秒前
晶jing完成签到,获得积分10
1秒前
执着大象完成签到,获得积分10
1秒前
2秒前
2秒前
4秒前
4秒前
4秒前
小雷同学发布了新的文献求助10
4秒前
LANER发布了新的文献求助10
5秒前
迷人的映雁完成签到,获得积分10
6秒前
搞对完成签到,获得积分10
6秒前
Licy发布了新的文献求助10
7秒前
8秒前
9秒前
晶jing发布了新的文献求助10
10秒前
Salvator完成签到,获得积分10
10秒前
丁点发布了新的文献求助10
11秒前
乐观尔容发布了新的文献求助10
11秒前
XY完成签到 ,获得积分10
12秒前
12秒前
在水一方应助北漓笙采纳,获得10
13秒前
鸡鸡bong发布了新的文献求助10
13秒前
13秒前
和璨完成签到,获得积分10
15秒前
Wellbeing发布了新的文献求助10
16秒前
wz1666发布了新的文献求助30
16秒前
wen发布了新的文献求助10
17秒前
唠叨的莺完成签到,获得积分10
17秒前
20秒前
21秒前
李健的小迷弟应助Dawn采纳,获得10
21秒前
PPPPPP完成签到,获得积分10
22秒前
哈哈哈哈xhy完成签到,获得积分10
22秒前
华仔应助执着大象采纳,获得10
22秒前
asipilin完成签到,获得积分10
22秒前
任性访风完成签到,获得积分10
22秒前
鸡鸡bong完成签到,获得积分10
24秒前
披着羊皮的狼应助Rain采纳,获得10
25秒前
26秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The Organometallic Chemistry of the Transition Metals 800
Chemistry and Physics of Carbon Volume 18 800
The Organometallic Chemistry of the Transition Metals 800
The formation of Australian attitudes towards China, 1918-1941 640
Signals, Systems, and Signal Processing 610
全相对论原子结构与含时波包动力学的理论研究--清华大学 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6441901
求助须知:如何正确求助?哪些是违规求助? 8255853
关于积分的说明 17579255
捐赠科研通 5500618
什么是DOI,文献DOI怎么找? 2900336
邀请新用户注册赠送积分活动 1877230
关于科研通互助平台的介绍 1717101