Habitat-based radiomics analysis for evaluating immediate response in colorectal cancer lung metastases treated by radiofrequency ablation

医学 无线电技术 结直肠癌 射频消融术 接收机工作特性 烧蚀 肺癌 肿瘤科 癌症 放射科 内科学
作者
Haozhe Huang,Hong Chen,Dezhong Zheng,Chao Chen,Ying Wang,Lichao Xu,Yaohui Wang,Xinhong He,Yuanyuan Yang,Wentao Li
出处
期刊:Cancer Imaging [BioMed Central]
卷期号:24 (1) 被引量:28
标识
DOI:10.1186/s40644-024-00692-w
摘要

Abstract Purpose To create radiomics signatures based on habitat to assess the instant response in lung metastases of colorectal cancer (CRC) after radiofrequency ablation (RFA). Methods Between August 2016 and June 2019, we retrospectively included 515 lung metastases in 233 CRC patients who received RFA (412 in the training group and 103 in the test group). Multivariable analysis was performed to identify independent risk factors for developing the clinical model. Tumor and ablation regions of interest (ROI) were split into three spatial habitats through K-means clustering and dilated with 5 mm and 10 mm thicknesses. Radiomics signatures of intratumor, peritumor, and habitat were developed using the features extracted from intraoperative CT data. The performance of these signatures was primarily evaluated using the area under the receiver operating characteristics curve (AUC) via the DeLong test, calibration curves through the Hosmer-Lemeshow test, and decision curve analysis. Results A total of 412 out of 515 metastases (80%) achieved complete response. Four clinical variables (cancer antigen 19–9, simultaneous systemic treatment, site of lung metastases, and electrode type) were utilized to construct the clinical model. The Habitat signature was combined with the Peri-5 signature, which achieved a higher AUC than the Peri-10 signature in the test set (0.825 vs. 0.816). The Habitat+Peri-5 signature notably surpassed the clinical and intratumor radiomics signatures (AUC: 0.870 in the test set; both, p < 0.05), displaying improved calibration and clinical practicality. Conclusions The habitat-based radiomics signature can offer precise predictions and valuable assistance to physicians in developing personalized treatment strategies.
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
今后应助CCF采纳,获得10
刚刚
1秒前
AE86发布了新的文献求助10
1秒前
2秒前
无限的初雪完成签到,获得积分10
5秒前
YuZhang完成签到 ,获得积分10
5秒前
汤汤发布了新的文献求助10
5秒前
小田完成签到,获得积分20
6秒前
Zhangky发布了新的文献求助10
6秒前
6秒前
爱吃的肥虾完成签到,获得积分10
9秒前
AE86完成签到,获得积分20
9秒前
控飘发布了新的文献求助10
11秒前
文艺安青完成签到 ,获得积分10
13秒前
Mxy发布了新的文献求助10
13秒前
14秒前
zy3637完成签到 ,获得积分10
14秒前
14秒前
16秒前
小太阳完成签到,获得积分10
17秒前
共享精神应助假装有昵称采纳,获得10
18秒前
小二郎应助小太阳采纳,获得10
23秒前
研友_VZG7GZ应助Singularity采纳,获得10
25秒前
CipherSage应助wg采纳,获得10
26秒前
木易发布了新的文献求助10
28秒前
31秒前
31秒前
直率冷之完成签到,获得积分20
33秒前
小二郎应助Astraeus采纳,获得10
34秒前
可爱的函函应助崔伟采纳,获得10
34秒前
星辰大海应助文献求助采纳,获得10
35秒前
勤奋冬灵完成签到 ,获得积分10
35秒前
35秒前
lllllxy发布了新的文献求助10
36秒前
直率冷之发布了新的文献求助30
36秒前
彭于晏应助假装有昵称采纳,获得10
37秒前
小二郎应助微笑爆米花采纳,获得10
38秒前
善良易文完成签到,获得积分10
38秒前
Luckydan完成签到,获得积分10
41秒前
陈成了发布了新的文献求助10
41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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Mass participant sport event brand associations: an analysis of two event categories 500
Photodetectors: From Ultraviolet to Infrared 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 6354971
求助须知:如何正确求助?哪些是违规求助? 8170168
关于积分的说明 17199106
捐赠科研通 5411068
什么是DOI,文献DOI怎么找? 2864148
邀请新用户注册赠送积分活动 1841739
关于科研通互助平台的介绍 1690150