已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Evaluating patient-specific neoadjuvant regimens for breast cancer via a mathematical model constrained by quantitative magnetic resonance imaging data

乳腺癌 磁共振成像 养生 医学 临床试验 新辅助治疗 加药 肿瘤科 癌症 医学物理学 内科学 放射科
作者
Angela M. Jarrett,David A. Hormuth,Chengyue Wu,Anum S. Kazerouni,David A. Ekrut,John Virostko,Anna G. Sorace,Julie C. DiCarlo,Jeanne Kowalski,Debra A. Patt,Boone Goodgame,Sarah Avery,Thomas E. Yankeelov
出处
期刊:Neoplasia [Elsevier BV]
卷期号:22 (12): 820-830 被引量:46
标识
DOI:10.1016/j.neo.2020.10.011
摘要

The ability to accurately predict response and then rigorously optimize a therapeutic regimen on a patient-specific basis, would transform oncology. Toward this end, we have developed an experimental-mathematical framework that integrates quantitative magnetic resonance imaging (MRI) data into a biophysical model to predict patient-specific treatment response of locally advanced breast cancer to neoadjuvant therapy. Diffusion-weighted and dynamic contrast-enhanced MRI data is collected prior to therapy, after 1 cycle of therapy, and at the completion of the first therapeutic regimen. The model is initialized and calibrated with the first 2 patient-specific MRI data sets to predict response at the third, which is then compared to patient outcomes (N = 18). The model's predictions for total cellularity, total volume, and the longest axis at the completion of the regimen are significant within expected measurement precision (P< 0.05) and strongly correlated with measured response (P < 0.01). Further, we use the model to investigate, in silico, a range of (practical) alternative treatment plans to achieve the greatest possible tumor control for each individual in a subgroup of patients (N = 13). The model identifies alternative dosing strategies predicted to achieve greater tumor control compared to the standard of care for 12 of 13 patients (P < 0.01). In summary, a predictive, mechanism-based mathematical model has demonstrated the ability to identify alternative treatment regimens that are forecasted to outperform the therapeutic regimens the patients clinically. This has important implications for clinical trial design with the opportunity to alter oncology care in the future.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
Jing关注了科研通微信公众号
2秒前
乐糖完成签到 ,获得积分10
4秒前
斐嘿嘿发布了新的文献求助10
4秒前
小桐完成签到,获得积分10
5秒前
陌上花开完成签到,获得积分0
6秒前
yuan完成签到,获得积分10
9秒前
Arui发布了新的文献求助10
10秒前
wanci应助谨慎哈密瓜采纳,获得10
13秒前
13秒前
SciGPT应助平淡的乐曲采纳,获得30
14秒前
mw完成签到,获得积分10
15秒前
hyhyhyhy发布了新的文献求助10
18秒前
乐乐应助hhllhh采纳,获得10
18秒前
yumiao发布了新的文献求助10
19秒前
小橙子完成签到,获得积分10
20秒前
Mtx3098520564完成签到 ,获得积分10
20秒前
FF完成签到 ,获得积分10
21秒前
29秒前
陈军应助雪山飞鹰采纳,获得10
30秒前
sky发布了新的文献求助10
30秒前
谨慎哈密瓜完成签到,获得积分10
32秒前
34秒前
35秒前
Yuson_L发布了新的文献求助10
36秒前
hhllhh发布了新的文献求助10
37秒前
儒雅南风发布了新的文献求助10
37秒前
38秒前
38秒前
负责怀莲发布了新的文献求助10
41秒前
42秒前
看不了一点文献应助lzm采纳,获得20
44秒前
852应助mpenny77采纳,获得30
45秒前
眨眼发布了新的文献求助10
48秒前
48秒前
SUE关闭了SUE文献求助
52秒前
53秒前
斯文败类应助Jing采纳,获得10
54秒前
54秒前
NexusExplorer应助迷人的高烽采纳,获得10
54秒前
无情的宛儿完成签到,获得积分10
55秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
‘Unruly’ Children: Historical Fieldnotes and Learning Morality in a Taiwan Village (New Departures in Anthropology) 400
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3989857
求助须知:如何正确求助?哪些是违规求助? 3531994
关于积分的说明 11255679
捐赠科研通 3270758
什么是DOI,文献DOI怎么找? 1805053
邀请新用户注册赠送积分活动 882195
科研通“疑难数据库(出版商)”最低求助积分说明 809208