清晨好,您是今天最早来到科研通的研友!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您科研之路漫漫前行!

Radiomics Based Differentiation of Glioblastoma and Metastatic Disease: Impact of Different T1-Contrast Enhanced Sequences on Radiomic Features and Model Performance

医学 无线电技术 随机森林 特征(语言学) 核医学 胶质母细胞瘤 特征选择 支持向量机 人工智能 接收机工作特性 模式识别(心理学) 放射科 计算机科学 内科学 癌症研究 语言学 哲学
作者
Girish Bathla,Camila Gadens Zamboni,Nicholas B. Larson,Yanan Liu,Honghai Zhang,Nam H Lee,Amit Agarwal,Neetu Soni,Milan Sonka
出处
期刊:American Journal of Neuroradiology [American Society of Neuroradiology]
卷期号:: ajnr.A8470-ajnr.A8470
标识
DOI:10.3174/ajnr.a8470
摘要

ABSTRACT

BACKGROUND AND PURPOSE:

To evaluate the radiomics-based model performance for differentiation between glioblastoma (GB) and brain metastases (BM) using magnetization prepared rapid gradient echo (MPRAGE) and volumetric interpolated breath-hold examination (VIBE) T1-contrast enhanced sequences.

MATERIALS AND METHODS:

T1-CE MPRAGE and VIBE sequences acquired in 108 patients (31 GBs and 77 BM) during the same MRI session were retrospectively evaluated. Post standardized image pre-processing and segmentation, radiomics features were extracted from necrotic and enhancing tumor components. Pearson correlation analysis of radiomics features from tumor subcomponents was also performed. A total of 90 machine learning (ML) pipelines were evaluated using a five-fold cross validation. Performance was measured by mean AUC-ROC, Log-loss and Brier scores.

RESULTS:

A feature-wise comparison showed that the radiomic features between sequences were strongly correlated, with the highest correlation for shape-based features. The mean AUC across the top-ten pipelines ranged between 0.851-0.890 with T1-CE MPRAGE and between 0.869-0.907 with T1-CE VIBE sequence. Top performing models for the MPRAGE sequence commonly used support vector machines, while those for VIBE sequence used either support vector machines or random forest. Common feature reduction methods for top-performing models included linear combination filter and least absolute shrinkage and selection operator (LASSO) for both sequences. For the same ML-feature reduction pipeline, model performances were comparable (AUC-ROC difference range: [-0.078, 0.046]).

CONCLUSIONS:

Radiomic features derived from T1-CE MPRAGE and VIBE sequences are strongly correlated and may have similar overall classification performance for differentiating GB from BM. ABBREVIATIONS: BM: Brain metastases, GB: glioblastoma, T1-CE: T1 contrast enhanced sequence, MPRAGE: magnetization prepared rapid gradient echo, ML: machine learning, RF: random forest, VIBE: volumetric interpolated breath-hold examination.
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
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
科研通AI2S应助ANEWKID采纳,获得10
3秒前
殷勤的紫槐完成签到,获得积分10
8秒前
allrubbish完成签到,获得积分10
10秒前
11秒前
12秒前
15秒前
量子星尘发布了新的文献求助10
16秒前
ANEWKID发布了新的文献求助10
20秒前
田様应助ANEWKID采纳,获得10
23秒前
26秒前
ybwei2008_163完成签到,获得积分20
40秒前
41秒前
Air完成签到 ,获得积分10
43秒前
量子星尘发布了新的文献求助10
46秒前
1分钟前
1分钟前
ANEWKID发布了新的文献求助10
1分钟前
量子星尘发布了新的文献求助10
1分钟前
1分钟前
纪鹏飞完成签到,获得积分10
1分钟前
量子星尘发布了新的文献求助10
1分钟前
slycmd完成签到,获得积分10
1分钟前
研友Bn发布了新的文献求助10
1分钟前
彭于晏应助ANEWKID采纳,获得10
1分钟前
2分钟前
量子星尘发布了新的文献求助10
2分钟前
2分钟前
火星上惜天完成签到 ,获得积分10
2分钟前
皮皮完成签到 ,获得积分10
2分钟前
善学以致用应助尺素寸心采纳,获得10
2分钟前
2分钟前
量子星尘发布了新的文献求助10
2分钟前
ANEWKID发布了新的文献求助10
2分钟前
ANEWKID完成签到,获得积分10
2分钟前
单薄松鼠完成签到 ,获得积分10
2分钟前
2分钟前
烟花应助ANEWKID采纳,获得10
2分钟前
沈惠映完成签到 ,获得积分10
2分钟前
2分钟前
joker完成签到 ,获得积分10
2分钟前
高分求助中
【提示信息,请勿应助】请使用合适的网盘上传文件 10000
The Oxford Encyclopedia of the History of Modern Psychology 1500
Green Star Japan: Esperanto and the International Language Question, 1880–1945 800
Sentimental Republic: Chinese Intellectuals and the Maoist Past 800
The Martian climate revisited: atmosphere and environment of a desert planet 800
The Psychology of Advertising (5th edition) 500
Electron microscopy study of magnesium hydride (MgH2) for Hydrogen Storage 500
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 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3865751
求助须知:如何正确求助?哪些是违规求助? 3408343
关于积分的说明 10657160
捐赠科研通 3132316
什么是DOI,文献DOI怎么找? 1727549
邀请新用户注册赠送积分活动 832351
科研通“疑难数据库(出版商)”最低求助积分说明 780242