Chen Li, Choyke Peter L, Wang Niya, Clarke Robert, Bhujwalla Zaver M, Hillman Elizabeth M C, Wang Ge, Wang Yue
Genetics Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, United States of America; Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, United States of America.
Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, United States of America.
PLoS One. 2014 Nov 7;9(11):e112143. doi: 10.1371/journal.pone.0112143. eCollection 2014.
With the existence of biologically distinctive malignant cells originated within the same tumor, intratumor functional heterogeneity is present in many cancers and is often manifested by the intermingled vascular compartments with distinct pharmacokinetics. However, intratumor vascular heterogeneity cannot be resolved directly by most in vivo dynamic imaging. We developed multi-tissue compartment modeling (MTCM), a completely unsupervised method of deconvoluting dynamic imaging series from heterogeneous tumors that can improve vascular characterization in many biological contexts. Applying MTCM to dynamic contrast-enhanced magnetic resonance imaging of breast cancers revealed characteristic intratumor vascular heterogeneity and therapeutic responses that were otherwise undetectable. MTCM is readily applicable to other dynamic imaging modalities for studying intratumor functional and phenotypic heterogeneity, together with a variety of foreseeable applications in the clinic.
由于同一肿瘤内存在生物学特性不同的恶性细胞,肿瘤内功能异质性在许多癌症中都存在,并且通常表现为具有不同药代动力学的混合血管腔室。然而,大多数体内动态成像无法直接解析肿瘤内血管异质性。我们开发了多组织腔室建模(MTCM),这是一种完全无监督的方法,用于对来自异质性肿瘤的动态成像序列进行去卷积,可在许多生物学背景下改善血管特征描述。将MTCM应用于乳腺癌的动态对比增强磁共振成像,揭示了肿瘤内特征性的血管异质性和治疗反应,而这些在其他情况下是无法检测到的。MTCM很容易应用于其他动态成像模式,以研究肿瘤内功能和表型异质性,以及临床上各种可预见的应用。