ReviewCancers2026
Bridging In Vitro and Murine Breast Cancer Models: Advanced Imaging Across Multiscale Experimental Platforms.
Review in Cancers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.