Spatial correlation between in vivo imaging and immunohistochemical biomarkers: A methodological study

IF 5 2区 医学 Q2 Medicine Translational Oncology Pub Date : 2024-07-16 DOI:10.1016/j.tranon.2024.102051
{"title":"Spatial correlation between in vivo imaging and immunohistochemical biomarkers: A methodological study","authors":"","doi":"10.1016/j.tranon.2024.102051","DOIUrl":null,"url":null,"abstract":"<div><p>In this study, we present a method that enables voxel-by-voxel comparison of in vivo imaging to immunohistochemistry (IHC) biomarkers. As a proof of concept, we investigated the spatial correlation between dynamic contrast enhanced (DCE-)CT parameters and IHC biomarkers Ki-67 (proliferation), HIF-1α (hypoxia), and CD45 (immune cells). 54 whole-mount tumor slices of 15 laryngeal and hypopharyngeal carcinomas were immunohistochemically stained and digitized. Heatmaps of biomarker positivity were created and registered to DCE-CT parameter maps. The adiabatic approximation to the tissue homogeneity model was used to fit the following DCE parameters: <span><math><msup><mrow><mi>K</mi></mrow><mrow><mi>t</mi><mi>r</mi><mi>a</mi><mi>n</mi><mi>s</mi></mrow></msup></math></span> (transfer constant), <span><math><msub><mi>V</mi><mi>e</mi></msub></math></span> (extravascular and extracellular space), and <span><math><msub><mi>V</mi><mi>i</mi></msub></math></span> (intravascular space). Both IHC and DCE maps were downsampled to 4 × 4 × 3 mm[<span><span>3</span></span>] voxels. The mean values per tumor were used to calculate the between-subject correlations between parameters. For the within-subject (spatial) correlation, values of all voxels within a tumor were compared using the repeated measures correlation (<span><math><msub><mi>r</mi><mrow><mi>r</mi><mi>m</mi></mrow></msub></math></span>). No between-subject correlations were found between IHC biomarkers and DCE parameters, whereas we found multiple significant within-subject correlations: <span><math><msub><mi>V</mi><mi>e</mi></msub></math></span> and Ki-67 (<span><math><msub><mi>r</mi><mrow><mi>r</mi><mi>m</mi></mrow></msub></math></span> = -0.17, <em>P</em> &lt; .001), <span><math><msub><mi>V</mi><mi>e</mi></msub></math></span> and HIF-1α (<span><math><msub><mi>r</mi><mrow><mi>r</mi><mi>m</mi></mrow></msub></math></span> = -0.12, <em>P</em> &lt; .001), <span><math><msup><mrow><mi>K</mi></mrow><mrow><mi>t</mi><mi>r</mi><mi>a</mi><mi>n</mi><mi>s</mi></mrow></msup></math></span> and CD45 (<span><math><msub><mi>r</mi><mrow><mi>r</mi><mi>m</mi></mrow></msub></math></span> = 0.13, <em>P</em> &lt; .001), <span><math><msub><mi>V</mi><mi>i</mi></msub></math></span> and CD45 (<span><math><msub><mi>r</mi><mrow><mi>r</mi><mi>m</mi></mrow></msub></math></span> = 0.16, <em>P</em> &lt; .001), and <span><math><msub><mi>V</mi><mi>i</mi></msub></math></span> and Ki-67 (<span><math><msub><mi>r</mi><mrow><mi>r</mi><mi>m</mi></mrow></msub></math></span> = 0.08, <em>P</em> = .003). The strongest correlation was found between IHC biomarkers Ki-67 and HIF-1α (<span><math><msub><mi>r</mi><mrow><mi>r</mi><mi>m</mi></mrow></msub></math></span> = 0.35, <em>P</em> &lt; .001). This study shows the technical feasibility of determining the 3 dimensional spatial correlation between histopathological biomarker heatmaps and in vivo imaging. It also shows that between-subject correlations do not reflect within-subject correlations of parameters.</p></div>","PeriodicalId":48975,"journal":{"name":"Translational Oncology","volume":null,"pages":null},"PeriodicalIF":5.0000,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1936523324001785/pdfft?md5=a7b818637215ccd4114924d88a571465&pid=1-s2.0-S1936523324001785-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational Oncology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1936523324001785","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

Abstract

In this study, we present a method that enables voxel-by-voxel comparison of in vivo imaging to immunohistochemistry (IHC) biomarkers. As a proof of concept, we investigated the spatial correlation between dynamic contrast enhanced (DCE-)CT parameters and IHC biomarkers Ki-67 (proliferation), HIF-1α (hypoxia), and CD45 (immune cells). 54 whole-mount tumor slices of 15 laryngeal and hypopharyngeal carcinomas were immunohistochemically stained and digitized. Heatmaps of biomarker positivity were created and registered to DCE-CT parameter maps. The adiabatic approximation to the tissue homogeneity model was used to fit the following DCE parameters: Ktrans (transfer constant), Ve (extravascular and extracellular space), and Vi (intravascular space). Both IHC and DCE maps were downsampled to 4 × 4 × 3 mm[3] voxels. The mean values per tumor were used to calculate the between-subject correlations between parameters. For the within-subject (spatial) correlation, values of all voxels within a tumor were compared using the repeated measures correlation (rrm). No between-subject correlations were found between IHC biomarkers and DCE parameters, whereas we found multiple significant within-subject correlations: Ve and Ki-67 (rrm = -0.17, P < .001), Ve and HIF-1α (rrm = -0.12, P < .001), Ktrans and CD45 (rrm = 0.13, P < .001), Vi and CD45 (rrm = 0.16, P < .001), and Vi and Ki-67 (rrm = 0.08, P = .003). The strongest correlation was found between IHC biomarkers Ki-67 and HIF-1α (rrm = 0.35, P < .001). This study shows the technical feasibility of determining the 3 dimensional spatial correlation between histopathological biomarker heatmaps and in vivo imaging. It also shows that between-subject correlations do not reflect within-subject correlations of parameters.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
活体成像与免疫组化生物标记物之间的空间相关性:方法学研究
在本研究中,我们提出了一种方法,可逐个体素比较体内成像和免疫组化(IHC)生物标记物。作为概念验证,我们研究了动态对比增强(DCE-)CT 参数与 IHC 生物标记物 Ki-67(增殖)、HIF-1α(缺氧)和 CD45(免疫细胞)之间的空间相关性。对 15 例喉癌和下咽癌的 54 张全切肿瘤切片进行免疫组化染色和数字化处理。绘制了生物标记物阳性热图,并与 DCE-CT 参数图进行了登记。组织均匀性模型的绝热近似用于拟合以下 DCE 参数:Ktrans(转移常数)、Ve(血管外和细胞外空间)和 Vi(血管内空间)。IHC 和 DCE 图谱均下采样为 4 × 4 × 3 mm[3] 体素。每个肿瘤的平均值用于计算参数之间的受试者间相关性。对于受试者内(空间)相关性,使用重复测量相关性(rrm)比较肿瘤内所有体素的值。没有发现 IHC 生物标记物与 DCE 参数之间存在受试者间相关性,但我们发现了多个显著的受试者内相关性:Ve 与 Ki-67(rrm = -0.17,P < .001)、Ve 与 HIF-1α(rrm = -0.12,P < .001)、Ktrans 与 CD45(rrm = 0.13,P < .001)、Vi 与 CD45(rrm = 0.16,P < .001)、Vi 与 Ki-67(rrm = 0.08,P = .003)。IHC 生物标志物 Ki-67 与 HIF-1α 之间的相关性最强(rrm = 0.35,P < .001)。这项研究表明,确定组织病理学生物标记热图与活体成像之间的三维空间相关性在技术上是可行的。它还表明,受试者之间的相关性并不能反映受试者内部参数的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
8.40
自引率
2.00%
发文量
314
审稿时长
54 days
期刊介绍: Translational Oncology publishes the results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of oncology patients. Translational Oncology will publish laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer. Peer reviewed manuscript types include Original Reports, Reviews and Editorials.
期刊最新文献
Excavating regulated cell death signatures to predict prognosis, tumor microenvironment and therapeutic response in HR+/HER2- breast cancer CCL22 as an independent prognostic factor in endometrial cancer patients HADH suppresses clear cell renal cell carcinoma progression through reduced NRF2-dependent glutathione synthesis Effect of tumor-derived extracellular vesicle-shuttled lncRNA MALAT1 on proliferation, invasion and metastasis of triple-negative breast cancer by regulating macrophage M2 polarization via the POSTN/Hippo/YAP axis Metavert synergises with standard cytotoxics in human PDAC organoids and is associated with transcriptomic signatures of therapeutic response
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1