Segmentation of Whole-Body Images into Two Compartments in Model for Bone Marrow Dosimetry Increases the Correlation with Hematological Response in 177 Lu-DOTATATE Treatments

作者
Linn Hagmarker,Johanna Svensson,Tobias Rydèn,Peter Gjertsson,Peter Bernhardt
出处
期刊:Cancer Biotherapy and Radiopharmaceuticals [Mary Ann Liebert, Inc.]
卷期号:32 (9): 335-343 被引量:8
标识
DOI:10.1089/cbr.2017.2317
摘要

Background: In 177 Lu-DOTATATE treatments, bone marrow (BM) is one of the most important organs at risk. The authors previously developed an image-based two-compartment method for BM dosimetry, showing a significant correlation between absorbed dose to BM and hematological toxicity in 177 Lu-DOTATATE treatments. In the present study, they aimed to further evaluate this BM dosimetry method by finding optimal settings for dividing the whole body into two compartments; in terms of minimizing the coefficient of variation (CV) for the individual absorbed doses and studying its correlation to the BM response. The authors have also added specific absorbed fractions for male and female. Finally, they compare this two-compartment method with whole-body dosimetry. Methods: This study included 46 patients with advanced neuroendocrine tumors treated with 177 Lu-DOTATATE on two to five occasions at Sahlgrenska University Hospital. Planar gamma camera images were collected at four time points postinjection, and a segmentation tool using a normalized number of uptake foci (nNUF) to divide the whole body into high- and low-uptake compartments was used. The authors characterized the two-compartment model and compared it with whole-body dosimetry. Results and Conclusion: The dosimetry method was robust, with an optimal nNUF value of 0.1–0.2. Using an nNUF value of 0.15, the absorbed BM dose was estimated as 0.20 Gy/7.4 GBq, and the CV as 8.4%. Compared to whole-body dosimetry, stronger correlation was found between absorbed dose to BM and hematological response using the two-compartment method. The two-compartment method has potential as a valuable image-based alternative to blood-based BM dosimetry.

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
悦耳冰萍完成签到,获得积分10
1秒前
mjr1227发布了新的文献求助30
3秒前
啦啦完成签到 ,获得积分10
3秒前
小张要当好医生完成签到,获得积分10
3秒前
7秒前
7秒前
8秒前
8秒前
fengwanru完成签到,获得积分10
8秒前
yjh123应助王永涛采纳,获得20
8秒前
Jasper应助爱笑修洁采纳,获得10
9秒前
无限小土豆应助123采纳,获得10
10秒前
11秒前
11秒前
11秒前
dde发布了新的文献求助10
12秒前
在水一方应助大胆采纳,获得10
12秒前
h123发布了新的文献求助10
13秒前
13秒前
乐乐应助坚强的寒梦采纳,获得10
15秒前
15秒前
15秒前
wanci应助郑鹏飞采纳,获得10
16秒前
16秒前
科研通AI6.3应助朱广能采纳,获得30
17秒前
沙萝发布了新的文献求助10
19秒前
lumu发布了新的文献求助10
19秒前
柯柯完成签到 ,获得积分10
19秒前
19秒前
轻松的百川完成签到,获得积分20
19秒前
19秒前
高贵烧鹅完成签到,获得积分10
21秒前
li发布了新的文献求助30
22秒前
郑鹏飞完成签到,获得积分10
22秒前
科目三应助123654采纳,获得10
24秒前
24秒前
老乔发布了新的文献求助10
25秒前
25秒前
杨茜然完成签到 ,获得积分10
26秒前
美好沛萍完成签到 ,获得积分10
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
APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior 1000
全员动态考核,锚定高质量发展:读懂同济大学教师人事改革新政的深层价值 900
Health Psychology 800
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
Römisch-Germanische Forschungen 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 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7595223
求助须知:如何正确求助?哪些是违规求助? 9171969
关于积分的说明 19633872
捐赠科研通 7172557
什么是DOI,文献DOI怎么找? 3267802
关于科研通互助平台的介绍 2432624
邀请新用户注册赠送积分活动 2260845