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!

Diagnostic approach for mediastinal masses with radiopathological correlation

医学 恶性肿瘤 纵隔肿块 放射科 纵隔 鉴别诊断 淋巴瘤 病理
作者
Masashi Taka,Satoshi Kobayashi,Kaori Mizutomi,Dai Inoue,Shigeyuki Takamatsu,Toshifumi Gabata,Isao Matsumoto,Hiroko Ikeda,Takeshi Kobayashi,Hiroshi Minato,Hitoshi Abo
出处
期刊:European Journal of Radiology [Elsevier BV]
卷期号:162: 110767-110767 被引量:15
标识
DOI:10.1016/j.ejrad.2023.110767
摘要

Purpose Mediastinal masses have various histopathological and radiological findings. Although lymphoma is the most common type of tumor, thymic epithelial and neurogenic tumors are common in adults and children, respectively, but several other types are difficult to distinguish. No previous review has simply and clearly shown how to differentiate mediastinal masses. Method We conducted a review of the latest mediastinal classifications and mass differentiation methods, with a focus on neoplastic lesions. Both older and recent studies were searched, and imaging and histopathological findings of mediastinal masses were reviewed. Original simple-to-use differentiation flowcharts are presented. Results Assessing localizations and internal characteristics is very important for mediastinal mass differentiation. The mass location and affected organ/tissue should be accurately assessed first, followed by more qualitative diagnosis, and optimization of the treatment strategy. In 2014, the International Thymic Malignancy Interest Group presented a new mediastinal clinical classification. In this classification, mediastinal masses are categorized into three groups according to location: prevascular (anterior)-, visceral (middle)-, and paravertebral (posterior)-compartment masses. Then, the internal characteristics and functional images are evaluated. Conclusions Differentiation of mediastinal masses is very difficult. However, if typical imaging findings and clinical characteristics are combined, reasonable differentiation is possible. In each patient, proper differential diagnosis may contribute to better treatment selection.
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
宋锦博完成签到,获得积分10
2秒前
W-博艺完成签到,获得积分10
3秒前
犹豫静白完成签到,获得积分10
4秒前
m(_._)m完成签到 ,获得积分0
6秒前
9秒前
张元东完成签到 ,获得积分10
11秒前
13秒前
阿格完成签到 ,获得积分10
13秒前
sadsa发布了新的文献求助10
14秒前
sun发布了新的文献求助10
15秒前
吴yx完成签到,获得积分10
15秒前
脑洞疼应助轻松的水壶采纳,获得30
16秒前
沉默白猫完成签到 ,获得积分10
16秒前
Lucas应助polaris采纳,获得10
17秒前
罐罐发布了新的文献求助10
18秒前
21秒前
23秒前
Wolfram完成签到 ,获得积分10
24秒前
25秒前
27秒前
研友_VZG7GZ应助轻松的水壶采纳,获得10
28秒前
ekko完成签到,获得积分10
28秒前
三水完成签到 ,获得积分10
29秒前
醉翁发布了新的文献求助10
30秒前
土豆芝士发布了新的文献求助10
31秒前
佟韩发布了新的文献求助10
32秒前
TigerOvO应助泠漓采纳,获得10
34秒前
xixilizi完成签到,获得积分10
35秒前
tx应助王小果采纳,获得10
35秒前
清风霁月完成签到 ,获得积分10
36秒前
SolderOH完成签到,获得积分10
37秒前
obsession完成签到 ,获得积分10
40秒前
L8完成签到,获得积分10
41秒前
悟123完成签到 ,获得积分10
42秒前
粥粥完成签到 ,获得积分10
42秒前
CodeCraft应助Omni采纳,获得10
44秒前
淡淡溪灵完成签到 ,获得积分10
46秒前
王小果完成签到,获得积分10
47秒前
xiao完成签到 ,获得积分10
51秒前
51秒前
高分求助中
Markov Chain Monte Carlo 10000
(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
Bend stiffness of submarine cables – an experimental and numerical investigation 5000
Advanced Weaponeering Fourth Edition, Volume 2 1000
Weaponeering: An Introduction Fourth Edition, Volume 1 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
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 7542789
求助须知:如何正确求助?哪些是违规求助? 9126701
关于积分的说明 19498924
捐赠科研通 7138734
什么是DOI,文献DOI怎么找? 3258475
关于科研通互助平台的介绍 2425826
邀请新用户注册赠送积分活动 2246617