Prediction of MYCN Gene Amplification in Pediatric Neuroblastomas: Development of a Deep Learning–Based Tool for Automatic Tumor Segmentation and Comparative Analysis of Computed Tomography–Based Radiomics Features Harmonization

人工智能 特征选择 分割 计算机科学 接收机工作特性 随机森林 无线电技术 医学 机器学习 模式识别(心理学)
作者
Ling Yun Yeow,Yu Xuan Teh,Xinyu Lu,Arvind Channarayapatna Srinivasa,Eelin Tan,Timothy Shao Ern Tan,Phua Hwee Tang,Bhanu Prakash
出处
期刊:Journal of Computer Assisted Tomography [Lippincott Williams & Wilkins]
卷期号:47 (5): 786-795 被引量:4
标识
DOI:10.1097/rct.0000000000001480
摘要

MYCN oncogene amplification is closely linked to high-grade neuroblastoma with poor prognosis. Accurate quantification is essential for risk assessment, which guides clinical decision making and disease management. This study proposes an end-to-end deep-learning framework for automatic tumor segmentation of pediatric neuroblastomas and radiomics features-based classification of MYCN gene amplification.Data from pretreatment contrast-enhanced computed tomography scans and MYCN status from 47 cases of pediatric neuroblastomas treated at a tertiary children's hospital from 2009 to 2020 were reviewed. Automated tumor segmentation and grading pipeline includes (1) a modified U-Net for tumor segmentation; (2) extraction of radiomic textural features; (3) feature-based ComBat harmonization for removal of variabilities across scanners; (4) feature selection using 2 approaches, namely, ( a ) an ensemble approach and ( b ) stepwise forward-and-backward selection method using logistic regression classifier; and (5) radiomics features-based classification of MYCN gene amplification using machine learning classifiers.Median train/test Dice score for modified U-Net was 0.728/0.680. The top 3 features from the ensemble approach were neighborhood gray-tone difference matrix (NGTDM) busyness, NGTDM strength, and gray-level run-length matrix (GLRLM) low gray-level run emphasis, whereas those from the stepwise approach were GLRLM low gray-level run emphasis, GLRLM high gray-level run emphasis, and NGTDM coarseness. The top-performing tumor classification algorithm achieved a weighted F1 score of 97%, an area under the receiver operating characteristic curve of 96.9%, an accuracy of 96.97%, and a negative predictive value of 100%. Harmonization-based tumor classification improved the accuracy by 2% to 3% for all classifiers.The proposed end-to-end framework achieved high accuracy for MYCN gene amplification status classification.
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
4秒前
buerzi完成签到,获得积分10
4秒前
魁梧的盼望完成签到 ,获得积分10
6秒前
量子星尘发布了新的文献求助30
7秒前
10秒前
wzk完成签到,获得积分10
11秒前
称心翠容完成签到,获得积分10
13秒前
LaixS完成签到,获得积分10
14秒前
尊敬代亦发布了新的文献求助10
15秒前
要笑cc完成签到,获得积分10
16秒前
青珊发布了新的文献求助10
18秒前
宣宣宣0733完成签到,获得积分10
18秒前
俊逸吐司完成签到 ,获得积分10
19秒前
ttxxcdx完成签到 ,获得积分10
20秒前
胡质斌完成签到,获得积分10
20秒前
充电宝应助科研通管家采纳,获得10
23秒前
24秒前
姚怜南完成签到,获得积分10
26秒前
青珊完成签到,获得积分10
28秒前
自觉石头完成签到 ,获得积分10
29秒前
VVTTWW完成签到 ,获得积分10
31秒前
感性的寄真完成签到 ,获得积分10
33秒前
zhang完成签到,获得积分10
36秒前
39秒前
比比谁的速度快应助zhang采纳,获得50
43秒前
绿袖子完成签到,获得积分10
45秒前
52秒前
刘刘完成签到 ,获得积分10
53秒前
执着夏岚完成签到 ,获得积分10
53秒前
Xzx1995完成签到 ,获得积分10
57秒前
Hululu完成签到 ,获得积分10
59秒前
淡然的芷荷完成签到 ,获得积分10
1分钟前
GT完成签到,获得积分10
1分钟前
qiancib202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
等待的幼晴完成签到,获得积分10
1分钟前
负责灵萱完成签到 ,获得积分10
1分钟前
幽默的忆霜完成签到 ,获得积分10
1分钟前
1分钟前
1分钟前
高分求助中
【提示信息,请勿应助】关于scihub 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 3000
徐淮辽南地区新元古代叠层石及生物地层 3000
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
Handbook of Industrial Diamonds.Vol2 1100
Global Eyelash Assessment scale (GEA) 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 550
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 4038029
求助须知:如何正确求助?哪些是违规求助? 3575740
关于积分的说明 11373751
捐赠科研通 3305559
什么是DOI,文献DOI怎么找? 1819224
邀请新用户注册赠送积分活动 892652
科研通“疑难数据库(出版商)”最低求助积分说明 815022