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!

The accurate staging of ovarian cancer using 3T magnetic resonance imaging – a realistic option

医学 磁共振成像 卵巢癌 放射科 恶性肿瘤 阶段(地层学) 外科病理学 癌症 病理 内科学 古生物学 生物
作者
S. J. Booth,LW Turnbull,Poole,I Richmond
出处
期刊:Bjog: An International Journal Of Obstetrics And Gynaecology [Wiley]
卷期号:115 (7): 894-901 被引量:28
标识
DOI:10.1111/j.1471-0528.2008.01716.x
摘要

Objectives The aim of the study was to determine whether staging primary ovarian cancer using 3.0 Tesla (3T) magnetic resonance imaging (MRI) is comparable to surgical staging of the disease. Design A retrospective study consisting of a search of the pathology database to identify women with ovarian pathology from May 2004 to January 2007. Setting All women treated for suspected ovarian cancer in our cancer centre region. Sample All women suspected of ovarian pathology who underwent 3T MRI prior to primary surgical intervention between May 2004 and January 2007. Methods All women found to have ovarian pathology, both benign and malignant, were then cross checked with the magnetic resonance (MR) database to identify those who had undergone 3T MRI prior to surgery. The resulting group of women underwent comparison of the MR, surgical and histopathological findings for each individual including diagnosis of benign or malignant disease and International Federation of Gynecology and Obstetrics (FIGO) staging where appropriate. Main outcome measures Comparisons were made between the staging accuracy of 3T MRI and surgical staging compared with histopathological findings and FIGO stage using weighted kappa. Sensitivity, specificity and accuracy were calculated for diagnosing malignant ovarian disease with 3T MRI. Results A total of 191 women identified as having ovarian pathology underwent imaging with 3T MR and primary surgical intervention. In 19 of these women, the ovarian disease was an incidental finding. The group for which staging methods were compared consisted of 77 women of primary ovarian malignancy (20 of whom had borderline tumours). 3T MRI was able to detect ovarian malignancy with a sensitivity of 92% and a specificity of 76%. The overall accuracy in detecting malignancy with 3T MRI was 84%, with a positive predictive value of 80% and negative predictive value of 90%. Statistical analysis of the two methods of staging using weighted kappa, gave a K value of 0.926 (SE ±0.121) for surgical staging and 0.866 (SE ±0.119) for MR staging. A further analysis of the staging data for ovarian cancers alone, excluding borderline tumours resulted in a K value of 0.931 (SE ±0.136) for histopathological staging versus MR staging and 0.958 (±0.140) for histopathological stage versus surgical staging. Conclusion Our study has shown that MRI can achieve staging of ovarian cancer comparable with the accuracy seen with surgical staging. No previous studies comparing different modalities have used the higher field strength 3T MRI. In addition, all other studies comparing radiological assessment of ovarian cancer have grouped the stages into I, II, III and IV rather than the more clinically appropriate a, b and c subgroups.

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
nn应助科研通管家采纳,获得10
刚刚
zzz1310发布了新的文献求助10
1秒前
1秒前
1秒前
小二郎应助科研通管家采纳,获得10
1秒前
学术小白完成签到,获得积分10
1秒前
1秒前
小蘑菇应助科研通管家采纳,获得10
1秒前
光亮的唇膏完成签到 ,获得积分10
2秒前
A0564发布了新的文献求助10
2秒前
3秒前
Akim应助老实的水蜜桃采纳,获得10
3秒前
沙莎完成签到 ,获得积分10
4秒前
momo完成签到 ,获得积分10
5秒前
Dlan完成签到,获得积分10
6秒前
qqa完成签到,获得积分10
6秒前
斯文败类应助OK采纳,获得10
7秒前
7秒前
qqa发布了新的文献求助10
10秒前
ww完成签到,获得积分10
11秒前
11秒前
小白加油完成签到 ,获得积分10
12秒前
西瓜发布了新的文献求助10
12秒前
soilbeginner发布了新的文献求助10
13秒前
Xixi完成签到 ,获得积分10
13秒前
会撒娇的面包完成签到,获得积分10
14秒前
Young完成签到 ,获得积分10
14秒前
kaka完成签到,获得积分0
14秒前
16秒前
16秒前
小休完成签到 ,获得积分10
18秒前
科研通AI6.4应助小卢同学采纳,获得10
20秒前
20秒前
大狒狒发布了新的文献求助10
21秒前
婷er发布了新的文献求助10
21秒前
斯文败类应助zzz1310采纳,获得10
22秒前
淡然大米完成签到 ,获得积分10
24秒前
严钰佳发布了新的文献求助10
25秒前
25秒前
巫衣絮完成签到,获得积分10
25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
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
Management and the Arts 310
Teaching Social and Emotional Learning in Physical Education 300
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 7633078
求助须知:如何正确求助?哪些是违规求助? 9207462
关于积分的说明 19747264
捐赠科研通 7202069
什么是DOI,文献DOI怎么找? 3274916
关于科研通互助平台的介绍 2436819
邀请新用户注册赠送积分活动 2271731