ReviewThe American journal of pathology2013
Preclinical magnetic resonance imaging and systems biology in cancer research: current applications and challenges.
Review in The American journal of pathology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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
12 citing papers in PubMed.
- Targeted Nanotheransotics: Integration of Preclinical MRI and CT in the Molecular Imaging and Therapy of Advanced Diseases.Nanotheranostics · 2024Review
- Cerebral Creatine Deficiency Affects the Timing of Oligodendrocyte Myelination.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- EMT-independent detection of circulating tumor cells in human blood samples and pre-clinical mouse models of metastasis.Clinical & experimental metastasis · 2021Article
- Magnetic Resonance Imaging and Bioluminescence Imaging for Evaluating Tumor Burden in Orthotopic Colon Cancer.Scientific reports · 2019Article
- Bombesin-functionalized superparamagnetic iron oxide nanoparticles for dual-modality MR/NIRFI in mouse models of breast cancer.International journal of nanomedicine · 2019Article
- Circulating Tumor Cell Analysis in Preclinical Mouse Models of Metastasis.Diagnostics (Basel, Switzerland) · 2018Review
- Multifunctional SPIO/DOX-loaded A54 Homing Peptide Functionalized Dextran-g-PLGA Micelles for Tumor Therapy and MR Imaging.Scientific reports · 2016Article
- Precision medicine and molecular imaging: new targeted approaches toward cancer therapeutic and diagnosis.American journal of nuclear medicine and molecular imaging · 2016Article
- Review
- Real-time assessment of tissue hypoxia in vivo with combined photoacoustics and high-frequency ultrasound.Theranostics · 2014Article
- An expanded role for Caveolin-1 in brain tumors.Cell cycle (Georgetown, Tex.) · 2013Article
- Integration of Network Biology and Imaging to Study Cancer Phenotypes and Responses.IEEE/ACM transactions on computational biology and bioinformaticsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Biologically accurate mouse models of human cancer have become important tools for the study of human disease. The anatomical location of various target organs, such as brain, pancreas, and prostate, makes determination of disease status difficult. Imaging modalities, such as magnetic resonance imaging, can greatly enhance diagnosis, and longitudinal imaging of tumor progression is an important source of experimental data. Even in models where the tumors arise in areas that permit visual determination of tumorigenesis, longitudinal anatomical and functional imaging can enhance the scope of studies by facilitating the assessment of biological alterations, (such as changes in angiogenesis, metabolism, cellular invasion) as well as tissue perfusion and diffusion. One of the challenges in preclinical imaging is the development of infrastructural platforms required for integrating in vivo imaging and therapeutic response data with ex vivo pathological and molecular data using a more systems-based multiscale modeling approach. Further challenges exist in integrating these data for computational modeling to better understand the pathobiology of cancer and to better affect its cure. We review the current applications of preclinical imaging and discuss the implications of applying functional imaging to visualize cancer progression and treatment. Finally, we provide new data from an ongoing preclinical drug study demonstrating how multiscale modeling can lead to a more comprehensive understanding of cancer biology and therapy.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.