Wilson Katheryne E, Bachawal Sunitha V, Tian Lu, Willmann Jürgen K
1. Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, School of Medicine, Stanford, California, USA;
2. Department of Health Research and Policy, Stanford University, School of Medicine, Stanford, California, USA.
Theranostics. 2014 Aug 15;4(11):1062-71. doi: 10.7150/thno.9922. eCollection 2014.
To evaluate the potential of multiparametric spectroscopic photoacoustic imaging using oxygen saturation, total hemoglobin, and lipid content to differentiate among four different breast histologies (normal, hyperplasia, ductal carcinoma in situ (DCIS), and invasive breast carcinoma) in a transgenic mouse model of breast cancer development.
Animal studies were approved by the Institutional Administrative Panel on Laboratory Animal Care. Mammary glands (n=251) of a transgenic mouse model of breast cancer development (FVB/N-Tg(MMTV-PyMT)634Mul) were imaged using B-mode ultrasound and spectroscopic photoacoustic imaging, analyzed for oxygen saturation, total hemoglobin, and lipid content, and processed for histological analysis. Statistical analysis was performed using one-way ANOVA, two-sample t-tests, logistic regression, and ROC analysis.
Eighty-two normal, 12 hyperplastic, 96 DCIS, and 61 invasive breast carcinoma mammary glands were analyzed. Based on spectroscopic photoacoustic imaging, the oxygen saturation of hyperplasia (50.6%), DCIS (43.0%), and invasive carcinoma (46.2%) significantly increased compared to normal glands (35.5%, P <0.0001), while both total hemoglobin (P<0.01), and lipid content (P<0.0008) significantly decreased with advancing histology. In differentiating normal and hyperplasia from DCIS and invasive breast carcinoma, multiparametric imaging of oxygen saturation, lipid content, and raw photoacoustic signal at 750 nm provided an AUC value of 0.770.
Multiparametric spectroscopic photoacoustic imaging is feasible and allows detection of differences in concentration of tissue chromophores among different histologies in a transgenic mouse model of breast cancer development.
在乳腺癌发生的转基因小鼠模型中，评估利用氧饱和度、总血红蛋白和脂质含量的多参数光谱光声成像区分四种不同乳腺组织学类型（正常、增生、导管原位癌（DCIS）和浸润性乳腺癌）的潜力。
动物研究经机构实验动物护理管理委员会批准。使用B型超声和光谱光声成像对乳腺癌发生转基因小鼠模型（FVB/N-Tg(MMTV-PyMT)634Mul）的乳腺（n = 251）进行成像，分析其氧饱和度、总血红蛋白和脂质含量，并进行组织学分析处理。采用单因素方差分析、两样本t检验、逻辑回归和ROC分析进行统计分析。
分析了82个正常乳腺、12个增生乳腺、96个DCIS乳腺和61个浸润性乳腺癌乳腺。基于光谱光声成像，增生（50.6%）、DCIS（43.0%）和浸润性癌（46.2%）的氧饱和度与正常腺体（35.5%，P < 0.0001）相比显著升高，而总血红蛋白（P < 0.01）和脂质含量（P < 0.0008）均随组织学进展显著降低。在区分正常和增生与DCIS及浸润性乳腺癌时，氧饱和度、脂质含量和75O nm处原始光声信号的多参数成像的AUC值为0.770。
多参数光谱光声成像可行，能够检测乳腺癌发生转基因小鼠模型中不同组织学类型之间组织发色团浓度的差异。
