生境成像用于肝细胞癌的研究进展
Advances in Habitat Imaging for Hepatocellular Carcinoma
摘要: 肝细胞癌(HCC)具有高度异质性,传统影像评估难以揭示其生物学行为。生境成像(HI)通过整合多模态影像参数及聚类算法,将肿瘤分割为功能与分子特征各异的亚区,无创表征瘤内异质性与肿瘤微环境。HI在术前预测微血管侵犯、术后复发风险及治疗反应中展现重要价值。本文将系统回顾并分析基于生境技术在HCC诊疗评估中的临床应用现状及未来研究方向。
Abstract: Hepatocellular carcinoma (HCC) is highly heterogeneous, making it difficult to reveal its biological behavior with conventional imaging assessment. Habitat imaging (HI) is a non-invasive method to characterize intratumor heterogeneity and tumor microenvironment by integrating multimodal imaging parameters and clustering algorithms to segment tumors into subregions with different functional and molecular characteristics, and it has shown great value in predicting microvascular invasion before surgery, recurrence risk after surgery, and treatment response. In this paper, we will systematically review the current status and future research direction of the clinical application of Habitat-based technology in the diagnostic and therapeutic evaluation of HCC.
文章引用:肖沿, 郭大静. 生境成像用于肝细胞癌的研究进展[J]. 临床医学进展, 2025, 15(5): 2505-2510. https://doi.org/10.12677/acm.2025.1551644

参考文献

[1] Bray, F., Laversanne, M., Sung, H., et al. (2024) Global Cancer Statistics 2022: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians, 74, 229-263. [Google Scholar] [CrossRef] [PubMed]
[2] Zeng, H., Chen, W., Zheng, R., Zhang, S., Ji, J.S., Zou, X., et al. (2018) Changing Cancer Survival in China during 2003-15: A Pooled Analysis of 17 Population-Based Cancer Registries. The Lancet Global Health, 6, e555-e567. [Google Scholar] [CrossRef] [PubMed]
[3] Llovet, J.M., Kelley, R.K., Villanueva, A., Singal, A.G., Pikarsky, E., Roayaie, S., et al. (2021) Hepatocellular Carcinoma. Nature Reviews Disease Primers, 7, Article No. 6. [Google Scholar] [CrossRef] [PubMed]
[4] Shi, Z., Huang, X., Cheng, Z., Xu, Z., Lin, H., Liu, C., et al. (2023) Erratum For: MRI-Based Quantification of Intratumoral Heterogeneity for Predicting Treatment Response to Neoadjuvant Chemotherapy in Breast Cancer. Radiology, 308, e222830. [Google Scholar] [CrossRef] [PubMed]
[5] Fu, Y., Liang, S., Luo, M. and Wang, X. (2025) Intratumoral Heterogeneity and Drug Resistance in Cancer. Cancer Cell International, 25, Article No. 103. [Google Scholar] [CrossRef] [PubMed]
[6] Dagogo-Jack, I. and Shaw, A.T. (2017) Tumour Heterogeneity and Resistance to Cancer Therapies. Nature Reviews Clinical Oncology, 15, 81-94. [Google Scholar] [CrossRef] [PubMed]
[7] 陈春玉, 黄映聪, 王强, 等. 基于信息熵的CT图像目标自动提取实验研究——以恐龙蛋壳化石切片CT图像为例[J]. 液晶与显示, 2022, 37(7): 891-899.
[8] 杨采薇, 蒋涵羽, 刘曦娇, 等. 影像组学在胰腺肿瘤病变影像学评估中的研究进展[J]. 放射学实践, 2019, 34(9): 963-968.
[9] 周健文, 冯峰. 食管CT影像组学研究进展[J]. CT理论与应用研究, 2022, 31(5): 687-696.
[10] 谢佳培, 张卫东, 朱婧怡, 等. 磁共振T1、T2值在脑胶质瘤分级及细胞增殖活性预测中的临床价值[J]. 磁共振成像, 2021, 12(1): 15-20.
[11] Cho, H., Kim, H., Nam, S.Y., Lee, J.E., Han, B., Ko, E.Y., et al. (2022) Measurement of Perfusion Heterogeneity within Tumor Habitats on Magnetic Resonance Imaging and Its Association with Prognosis in Breast Cancer Patients. Cancers, 14, Article 1858. [Google Scholar] [CrossRef] [PubMed]
[12] Erstad, D.J. and Tanabe, K.K. (2019) Prognostic and Therapeutic Implications of Microvascular Invasion in Hepatocellular Carcinoma. Annals of Surgical Oncology, 26, 1474-1493. [Google Scholar] [CrossRef] [PubMed]
[13] Zhang, Y., Chen, J., Yang, C., Dai, Y. and Zeng, M. (2024) Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma Using Diffusion-Weighted Imaging-Based Habitat Imaging. European Radiology, 34, 3215-3225. [Google Scholar] [CrossRef] [PubMed]
[14] Huang, Z., Huang, W., Jiang, L., Zheng, Y., Pan, Y., Yan, C., et al. (2025) Decision Fusion Model for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Multi-MR Habitat Imaging and Machine-Learning Classifiers. Academic Radiology, 32, 1971-1980. [Google Scholar] [CrossRef] [PubMed]
[15] Wang, C., Wu, F., Wang, F., Chong, H., Sun, H., Huang, P., et al. (2024) The Association between Tumor Radiomic Analysis and Peritumor Habitat‐Derived Radiomic Analysis on Gadoxetate Disodium‐Enhanced MRI with Microvascular Invasion in Hepatocellular Carcinoma. Journal of Magnetic Resonance Imaging, 61, 1428-1439. [Google Scholar] [CrossRef] [PubMed]
[16] Shah, S.A., Greig, P.D., Gallinger, S., Cattral, M.S., Dixon, E., Kim, R.D., et al. (2006) Factors Associated with Early Recurrence after Resection for Hepatocellular Carcinoma and Outcomes. Journal of the American College of Surgeons, 202, 275-283. [Google Scholar] [CrossRef] [PubMed]
[17] Zhang, Y., Ma, H., Lei, P., Li, Z., Yan, Z. and Wang, X. (2025) Prediction of Early Postoperative Recurrence of Hepatocellular Carcinoma by Habitat Analysis Based on Different Sequence of Contrast-Enhanced CT. Frontiers in Oncology, 14, Article 1522501. [Google Scholar] [CrossRef] [PubMed]
[18] Huang, Z., Pan, Y., Huang, W., Pan, F., Wang, H., Yan, C., et al. (2025) Predicting Microvascular Invasion and Early Recurrence in Hepatocellular Carcinoma Using Deeplab V3+ Segmentation of Multiregional MR Habitat Images. Academic Radiology. Articles in Press. [Google Scholar] [CrossRef] [PubMed]
[19] Villanueva, A. (2019) Hepatocellular Carcinoma. New England Journal of Medicine, 380, 1450-1462. [Google Scholar] [CrossRef] [PubMed]
[20] Zhang, Y., Yang, C., Qian, X., Dai, Y. and Zeng, M. (2023) Evaluate the Microvascular Invasion of Hepatocellular Carcinoma (≤5 Cm) and Recurrence Free Survival with Gadoxetate Disodium‐Enhanced MRI‐Based Habitat Imaging. Journal of Magnetic Resonance Imaging, 60, 1664-1675. [Google Scholar] [CrossRef] [PubMed]
[21] Zhang, Y., Yang, C., Sheng, R., Dai, Y. and Zeng, M. (2023) Predicting the Recurrence of Hepatocellular Carcinoma (≤ 5 Cm) after Resection Surgery with Promising Risk Factors: Habitat Fraction of Tumor and Its Peritumoral Micro-Environment. La Radiologia Medica, 128, 1181-1191. [Google Scholar] [CrossRef] [PubMed]
[22] Chen, K., Sui, C., Wang, Z., Liu, Z., Qi, L. and Li, X. (2025) Habitat Radiomics Based on CT Images to Predict Survival and Immune Status in Hepatocellular Carcinoma, a Multi-Cohort Validation Study. Translational Oncology, 52, Article 102260. [Google Scholar] [CrossRef] [PubMed]
[23] Zhou, C., Lu, X., Wang, Y., et al. (2022) Histopathological Components Correlated with MRI Features and Prognosis in Combined Hepatocellular Carcinoma-Cholangiocarcinoma. European Radiology, 32, 6702-6711. [Google Scholar] [CrossRef] [PubMed]
[24] Xiao, Y., Huang, P., Zhang, Y., Lu, X., Zhou, C., Wu, F., et al. (2024) Component Prediction in Combined Hepatocellular Carcinoma-Cholangiocarcinoma: Habitat Imaging and Its Biologic Underpinnings. Abdominal Radiology, 49, 1063-1073. [Google Scholar] [CrossRef] [PubMed]
[25] Yan, W., Liu, X., Ma, H., Zhang, H., Song, X., Gao, L., et al. (2015) Tim-3 Fosters HCC Development by Enhancing TGF-β-Mediated Alternative Activation of Macrophages. Gut, 64, 1593-1604. [Google Scholar] [CrossRef] [PubMed]
[26] Tang, Z., Wang, W., Gao, B., Liu, X., Liu, X., Zhuo, Y., et al. (2024) Unveiling Tim-3 Immune Checkpoint Expression in Hepatocellular Carcinoma through Abdominal Contrast-Enhanced CT Habitat Radiomics. Frontiers in Oncology, 14, Article 1456748. [Google Scholar] [CrossRef] [PubMed]
[27] Zhu, Y., Liu, T., Chen, J., Wen, L., Zhang, J. and Zheng, D. (2025) Prediction of Therapeutic Response to Transarterial Chemoembolization Plus Systemic Therapy Regimen in Hepatocellular Carcinoma Using Pretreatment Contrast-Enhanced MRI Based Habitat Analysis and Crossformer Model. Abdominal Radiology, 50, 2464-2475. [Google Scholar] [CrossRef] [PubMed]