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Bridging In Vitro and Murine Breast Cancer Models: Advanced Imaging Across Multiscale Experimental Platforms
Institute of Biostructure and Bioimaging, National Research Council, 80145 Napoli, Italy
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Author to whom correspondence should be addressed.
Cancers 2026, 18(15), 2469; https://doi.org/10.3390/cancers18152469
Submission received: 22 June 2026
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Revised: 23 July 2026
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Accepted: 29 July 2026
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Published: 31 July 2026
(This article belongs to the Special Issue Advancements in Preclinical Models for Solid Cancers)
Simple Summary
Breast cancer is a complex disease with significant differences among patients in terms of tumor features, disease progression, and response to treatment. Although several experimental models are available to study breast cancer, no single model can fully recapitulate the complexity of human tumors. This review highlights how the integration of complementary models, including patient-derived three-dimensional systems and animal models, with advanced imaging technologies, can provide a more comprehensive overview of tumor biology. Multimodal imaging enables the non-invasive and longitudinal monitoring of tumor growth, microenvironment changes, metastatic progression, and response to therapy, while supporting the identification of clinically relevant biomarkers. These integrated approaches can improve the predictive value of preclinical studies and contribute to the development of more personalized strategies for breast cancer diagnosis and treatment.
Abstract
Breast cancer is a highly heterogeneous disease characterized by distinct molecular subtypes, dynamic tumor–microenvironment interactions, and variable therapeutic responses. Despite the availability of multiple preclinical platforms, a major challenge remains the lack of a coherent multiscale framework capable of integrating biological complexity across experimental systems. This limitation reduces the predictive power of individual models and highlights the need for complementary strategies that reproduce disease progression across multiple biological scales. In this context, advanced imaging technologies have emerged as essential tools for linking preclinical platforms and enhancing their translational relevance. This review examines how multimodal imaging supports the integration of in vitro, ex vivo, and in vivo breast cancer models. We discuss how optical imaging, high-frequency ultrasound, magnetic resonance imaging, positron emission tomography/computed tomography, and intravital microscopy provide complementary molecular, functional, anatomical, and cellular information for the longitudinal assessment of tumor growth, metastatic dissemination, microenvironment remodeling, and therapeutic response. Particular attention is given to emerging translational workflows that combine patient-derived models with advanced imaging to investigate drug sensitivity, treatment resistance, and tumor progression within a precision oncology perspective. We also highlight the role of multimodal imaging in biomarker validation across platforms and in the development of clinically relevant preclinical pipelines. Overall, advanced imaging represents a critical translational bridge across breast cancer model systems, improving the predictive value of preclinical studies and supporting imaging-guided precision oncology from bench to bedside.
