ReviewJournal of biomedical science2020
Photoacoustic imaging of cells in a three-dimensional microenvironment.
Review in Journal of biomedical science, 2020. 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.
- 4D nanoimaging-guided smart therapeutics: spatiotemporal control of disease microenvironments.RSC advances · 2026Review
- 3-D Visualization of Atlantic salmon skin through Ultrasound and Photoacoustic Microscopy.PLoS computational biology · 2024Article
- TowardsFundamental research · 2024Review
- Visualizing Singularity Phenomenon.Biophysics and physicobiology · 2024Article
- Metal Sulfide Nanoparticles for Imaging and Phototherapeutic Applications.Molecules (Basel, Switzerland) · 2023Review
- Early diagnosis of bladder cancer by photoacoustic imaging of tumor-targeted gold nanorods.Photoacoustics · 2022Article
- Evaluation of differentScientific reports · 2022Article
- Nondestructive testing of native and tissue-engineered medical products: adding numbers to pictures.Trends in biotechnology · 2022Review
- Exogenous Contrast Agents in Photoacoustic Imaging: An In Vivo Review for Tumor Imaging.Nanomaterials (Basel, Switzerland) · 2022Review
- Functional photoacoustic calcium imaging using chlorophosphonazo III in a 3D tumor cell culture.Biomedical optics express · 2021Article
- Integrated Neurophotonics: Toward Dense Volumetric Interrogation of Brain Circuit Activity-at Depth and in Real Time.Neuron · 2020Review
- Photoacoustic endoscopy and EUS: Shaking the future of multimodal endoscopy.Endoscopic ultrasoundArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Imaging live cells in a three-dimensional (3D) culture system yields more accurate information and spatial visualization of the interplay of cells and the surrounding matrix components compared to using a two-dimensional (2D) cell culture system. However, the thickness of 3D cultures results in a high degree of scattering that makes it difficult for the light to penetrate deeply to allow clear optical imaging. Photoacoustic (PA) imaging is a powerful imaging modality that relies on a PA effect generated when light is absorbed by exogenous contrast agents or endogenous molecules in a medium. It combines a high optical contrast with a high acoustic spatiotemporal resolution, allowing the noninvasive visualization of 3D cellular scaffolds at considerable depths with a high resolution and no image distortion. Moreover, advances in targeted contrast agents have also made PA imaging capable of molecular and cellular characterization for use in preclinical personalized diagnostics or PA imaging-guided therapeutics. Here we review the applications and challenges of PA imaging in a 3D cellular microenvironment. Potential future developments of PA imaging in preclinical applications are also discussed.
Indexed as
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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.