Jiahao Chen, Yunwen Huang, Ning Zhao, Yi Ru, Yidong Yang
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For BLT reconstruction, the surface bioluminescence signal is first decomposed using a Gaussian mathematical model into multiple independent signal distributions, before separate reconstruction of individual targets. The final tumor distribution is the summation of the individual reconstruction results. BLT/CT imaging was performed on two types of metastatic tumor models, PC3 prostate tumors and HCT116 colorectal tumors, with 2 mice in each model. A double-blind histopathological analysis was conducted to verify the imaging results.Results and ConclusionBy incorporating the proposed strategy, the iSMAART system accurately differentiated and localized multiple tightly clustered tumors of varying sizes and optical intensities in all mice, and four tumors in a single mouse were simultaneously diagnosed. The tumor sizes measured by BLT closely matched the histopathological results (mean value 2.76 vs 2.41 mm). In this study, we proposed a \"2D decomposition + 3D reconstruction\" strategy, which enables the iSMAART system to accurately localize and quantify multiple tumors in live animals despite significant signal overlap and intensity variations, providing a powerful tool to fulfill and even open up more high-demand research fields.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251382977"},"PeriodicalIF":2.8000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12480804/pdf/","citationCount":"0","resultStr":"{\"title\":\"Differentiation and Localization of Adjacent Murine Tumors Using X-ray and Bioluminescence Tomography.\",\"authors\":\"Jiahao Chen, Yunwen Huang, Ning Zhao, Yi Ru, Yidong Yang\",\"doi\":\"10.1177/15330338251382977\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>IntroductionPreviously, a multimodal imaging system including x-ray computed tomography (CT) and bioluminescence tomography (BLT) has been developed on iSMAART and is capable of accurately localizing small tumors on the millimeter scale in three dimensions (3D). Here, a \\\"2D decomposition + 3D reconstruction\\\" strategy is proposed to recover multiple tumors that are closely spaced and may have drastically different bioluminescence intensities.MethodsIn the iSMAART system, CT provides the animal anatomy and surface contours required for BLT reconstruction. The BLT and CT are physically registered, rendering superimposed images. For BLT reconstruction, the surface bioluminescence signal is first decomposed using a Gaussian mathematical model into multiple independent signal distributions, before separate reconstruction of individual targets. The final tumor distribution is the summation of the individual reconstruction results. BLT/CT imaging was performed on two types of metastatic tumor models, PC3 prostate tumors and HCT116 colorectal tumors, with 2 mice in each model. A double-blind histopathological analysis was conducted to verify the imaging results.Results and ConclusionBy incorporating the proposed strategy, the iSMAART system accurately differentiated and localized multiple tightly clustered tumors of varying sizes and optical intensities in all mice, and four tumors in a single mouse were simultaneously diagnosed. The tumor sizes measured by BLT closely matched the histopathological results (mean value 2.76 vs 2.41 mm). 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引用次数: 0
摘要
此前,在iSMAART上已经开发了包括x射线计算机断层扫描(CT)和生物发光断层扫描(BLT)在内的多模态成像系统,能够在三维(3D)上精确定位毫米尺度的小肿瘤。本文提出了一种“2D分解+ 3D重建”的策略,用于恢复间隔较近且生物发光强度差异较大的多发肿瘤。方法在iSMAART系统中,CT提供BLT重建所需的动物解剖和表面轮廓。BLT和CT是物理配准的,呈现叠加图像。对于BLT重建,首先使用高斯数学模型将表面生物发光信号分解成多个独立的信号分布,然后对单个目标进行单独重建。最终的肿瘤分布是个体重建结果的总和。对两种转移性肿瘤模型PC3前列腺肿瘤和HCT116结肠肿瘤进行BLT/CT成像,每种模型2只小鼠。采用双盲组织病理学分析验证影像学结果。结果与结论采用该策略,iSMAART系统能够准确地区分和定位所有小鼠中大小、光强不同的多个紧密聚集的肿瘤,并可同时诊断出单个小鼠中的4个肿瘤。BLT测量的肿瘤大小与组织病理学结果非常吻合(平均值2.76 vs 2.41 mm)。在本研究中,我们提出了一种“2D分解+ 3D重建”的策略,使iSMAART系统能够在存在显著的信号重叠和强度变化的情况下,准确地定位和量化活体动物的多个肿瘤,为实现甚至开辟更多高需求的研究领域提供了有力的工具。
Differentiation and Localization of Adjacent Murine Tumors Using X-ray and Bioluminescence Tomography.
IntroductionPreviously, a multimodal imaging system including x-ray computed tomography (CT) and bioluminescence tomography (BLT) has been developed on iSMAART and is capable of accurately localizing small tumors on the millimeter scale in three dimensions (3D). Here, a "2D decomposition + 3D reconstruction" strategy is proposed to recover multiple tumors that are closely spaced and may have drastically different bioluminescence intensities.MethodsIn the iSMAART system, CT provides the animal anatomy and surface contours required for BLT reconstruction. The BLT and CT are physically registered, rendering superimposed images. For BLT reconstruction, the surface bioluminescence signal is first decomposed using a Gaussian mathematical model into multiple independent signal distributions, before separate reconstruction of individual targets. The final tumor distribution is the summation of the individual reconstruction results. BLT/CT imaging was performed on two types of metastatic tumor models, PC3 prostate tumors and HCT116 colorectal tumors, with 2 mice in each model. A double-blind histopathological analysis was conducted to verify the imaging results.Results and ConclusionBy incorporating the proposed strategy, the iSMAART system accurately differentiated and localized multiple tightly clustered tumors of varying sizes and optical intensities in all mice, and four tumors in a single mouse were simultaneously diagnosed. The tumor sizes measured by BLT closely matched the histopathological results (mean value 2.76 vs 2.41 mm). In this study, we proposed a "2D decomposition + 3D reconstruction" strategy, which enables the iSMAART system to accurately localize and quantify multiple tumors in live animals despite significant signal overlap and intensity variations, providing a powerful tool to fulfill and even open up more high-demand research fields.
期刊介绍:
Technology in Cancer Research & Treatment (TCRT) is a JCR-ranked, broad-spectrum, open access, peer-reviewed publication whose aim is to provide researchers and clinicians with a platform to share and discuss developments in the prevention, diagnosis, treatment, and monitoring of cancer.