Evidence map›Paper›PMID 42588686›Full record

ReviewCancers2026

Bridging In Vitro and Murine Breast Cancer Models: Advanced Imaging Across Multiscale Experimental Platforms.

Cristina Terlizzi, Ylenia Ferrara, Annachiara Sarnella

Abstract readReview
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Cristina TerlizziInstitute of Biostructure and Bioimaging, National Research Council, 80145 Napoli, Italy.ORCID 0000-0001-5422-4737
Ylenia FerraraInstitute of Biostructure and Bioimaging, National Research Council, 80145 Napoli, Italy.
Annachiara SarnellaInstitute of Biostructure and Bioimaging, National Research Council, 80145 Napoli, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

breast cancermultimodal imagingorganoidspatient-derived xenograftpreclinical models

Identifiers

PMID42588686
PMCPMC13465759

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.