Radiographic Detection of Intrathoracic Lymphadenomegaly in Dogs: How Useful Is It?

作者
Gordon Lye,Rachel E. Pollard,Angela Hartman,Sarah Pemberton,Michael S. Kent,Allison L. Zwingenberger
出处
期刊:Veterinary Radiology & Ultrasound [Wiley]
卷期号:67 (1): e70113-e70113
标识
DOI:10.1111/vru.70113
摘要

ABSTRACT The intrathoracic lymph nodes (LN) of clinical interest in dogs are the sternal (STLN), cranial mediastinal (CrMLN), and tracheobronchial (TBLN) groups. Although computed tomography (CT) depicts and measures these nodes well, thoracic screening commonly relies on three‐view radiographs. We hypothesized that enlargement of these nodes would not be consistently identified radiographically, even by experienced observers. In this retrospective, multicenter study (2012–2023), three board‐certified radiologists independently graded three‐view thoracic radiographs from 74 dogs. Each LN group was scored on a 5‐point scale (1, cannot assess; 2, normal; 3, mild; 4, moderate; 5, marked). Corresponding per‐group CT volumes (STLN, CrMLN, and combined TBLN) were calculated using the ellipsoid formula, and analyses were performed at the LN‐group level. Inter‐rater agreement was estimated with Gwet's AC1, and associations between radiographic grades and CT volumes were evaluated with Spearman's rank correlation. Observer agreement on radiographs was almost perfect (AC1: STLN 0.88, CrMLN 0.93, and TBLN 0.95). Correlations between radiographic grades and CT volumes were weak or nonsignificant; only one observer for TBLN showed a weak positive correlation ( ρ = 0.27, p = 0.02). No CT‐derived volume threshold yielded a unanimous radiographic classification of enlargement (grade ≥ 3) across observers. Radiographs frequently failed to detect enlarged nodes and occasionally overcalled normal‐sized nodes. These findings indicate poor alignment between radiographic grading and CT‐measured volume for intrathoracic lymphadenomegaly, despite high interobserver agreement. When accurate intrathoracic LN assessment is expected to influence clinical decision‐making, CT should be considered.
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
虫二发布了新的文献求助10
3秒前
哥没有跑调完成签到 ,获得积分10
3秒前
标致映秋完成签到,获得积分10
4秒前
吴晨曦完成签到,获得积分0
4秒前
勤劳太阳完成签到,获得积分10
4秒前
relx完成签到 ,获得积分10
4秒前
洪旺旺完成签到 ,获得积分10
4秒前
cyl黄金杖完成签到,获得积分10
7秒前
Serena完成签到 ,获得积分10
8秒前
阿尔治完成签到,获得积分10
9秒前
闪闪的小小完成签到,获得积分10
10秒前
HebFind完成签到,获得积分10
10秒前
zzz123完成签到 ,获得积分10
11秒前
芋泥小天才完成签到 ,获得积分10
11秒前
骑着蚂蚁追大象完成签到,获得积分10
11秒前
芹菜完成签到,获得积分10
12秒前
冷cool完成签到,获得积分10
12秒前
Judy完成签到 ,获得积分10
12秒前
偶尔喜欢完成签到,获得积分10
12秒前
wangjian1573完成签到 ,获得积分10
12秒前
Aquila发布了新的文献求助10
13秒前
ll完成签到,获得积分10
14秒前
高大无声完成签到,获得积分10
14秒前
平常的雁凡完成签到,获得积分10
14秒前
gala完成签到,获得积分10
15秒前
15秒前
淡淡手机完成签到,获得积分10
16秒前
shengwang完成签到 ,获得积分10
17秒前
LILLIAN完成签到 ,获得积分10
17秒前
顺心的夜南完成签到,获得积分10
17秒前
木木完成签到,获得积分10
17秒前
wenrui完成签到 ,获得积分10
18秒前
hadern完成签到,获得积分10
20秒前
20秒前
小马甲应助科研通管家采纳,获得10
20秒前
英俊的铭应助科研通管家采纳,获得10
20秒前
小章鱼完成签到 ,获得积分10
20秒前
香蕉曼寒完成签到 ,获得积分10
21秒前
眯眯眼的冰蓝完成签到 ,获得积分10
21秒前
巧依发布了新的文献求助10
22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
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
DIPPR Project 801 - Full Version 380
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7765974
求助须知:如何正确求助?哪些是违规求助? 9309963
关于积分的说明 20313419
捐赠科研通 7350773
什么是DOI,文献DOI怎么找? 3315010
关于科研通互助平台的介绍 2464543
邀请新用户注册赠送积分活动 2329592