ArticleMolecular imaging and biology2021
Cross-Modality Imaging of Murine Tumor Vasculature-a Feasibility Study.
Article in Molecular imaging and biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers.
What it found
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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.
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Who cites it
12 citing papers in PubMed, 17 citations in OpenAlex.
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- In situ isotropic 3D imaging of vasculature perfusion specimens using x-ray microscopic dual-energy CT.Journal of microscopy · 2025Article
- Confocal microscopic oxygen imaging of xenograft tumors using Ir(III) complexes as in vivo intravascular and intracellular probes.Scientific reports · 2024Article
- Correlative geochemical imaging of Desmophyllum dianthus reveals biomineralisation strategy as a key coral vital effect.Scientific reports · 2024Article
- Lossy Image Compression in a Preclinical Multimodal Imaging Study.Journal of digital imaging · 2023Article
- Quantitative Image Processing for Three-Dimensional Episcopic Images of Biological Structures: Current State and Future Directions.Biomedicines · 2023Review
- Visualizing vasculature and its response to therapy in the tumor microenvironment.Theranostics · 2023Review
- Contribution of Intravital Neuroimaging to Study Animal Models of Multiple Sclerosis.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2023Review
- U-Net based vessel segmentation for murine brains with small micro-magnetic resonance imaging reference datasets.PloS one · 2023Article
- Development of Stereo NIR-II Fluorescence Imaging System for 3D Tumor Vasculature in Small Animals.Biosensors · 2022Article
- Review
Corrections and comments
- Erratum issued
Authors and funding
18 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumor vasculature and angiogenesis play a crucial role in tumor progression. Their visualization is therefore of utmost importance to the community. In this proof-of-principle study, we have established a novel cross-modality imaging (CMI) pipeline to characterize exactly the same murine tumors across scales and penetration depths, using orthotopic models of melanoma cancer. This allowed the acquisition of a comprehensive set of vascular parameters for a single tumor. The workflow visualizes capillaries at different length scales, puts them into the context of the overall tumor vessel network and allows quantification and comparison of vessel densities and morphologies by different modalities. The workflow adds information about hypoxia and blood flow rates. The CMI approach includes well-established technologies such as magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), and ultrasound (US), and modalities that are recent entrants into preclinical discovery such as optical coherence tomography (OCT) and high-resolution episcopic microscopy (HREM). This novel CMI platform establishes the feasibility of combining these technologies using an extensive image processing pipeline. Despite the challenges pertaining to the integration of microscopic and macroscopic data across spatial resolutions, we also established an open-source pipeline for the semi-automated co-registration of the diverse multiscale datasets, which enables truly correlative vascular imaging. Although focused on tumor vasculature, our CMI platform can be used to tackle a multitude of research questions in cancer biology.
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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 OpenQuestion graph.