ReviewAnnals of biomedical engineering2016
Non-invasive and Non-destructive Characterization of Tissue Engineered Constructs Using Ultrasound Imaging Technologies: A Review.
Review in Annals of biomedical engineering, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Data-driven multiscale design of composite biomaterials: Integrating experiments, imaging, and computational modeling for biomedical engineering.Materials today. Bio · 2026Review
- Article
- High-Frequency Wearable Ultrasound Array Belt for Small Animal Echocardiography.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2024Article
- Multimodal fluorescence lifetime imaging and optical coherence tomography for longitudinal monitoring of tissue-engineered cartilage maturation in a preclinical implantation model.Journal of biomedical optics · 2023Article
- Tissue Engineering Techniques for Induced Pluripotent Stem Cell Derived Three-Dimensional Cardiac Constructs.Tissue engineering. Part B, Reviews · 2022Review
- Principles for the design of multicellular engineered living systems.APL bioengineering · 2022Article
- FRDD-Net: Automated Carotid Plaque Ultrasound Images Segmentation Using Feature Remapping and Dense Decoding.Sensors (Basel, Switzerland) · 2022Article
- Automated Multi-View Multi-Modal Assessment of COVID-19 Patients Using Reciprocal Attention and Biomedical Transform.Frontiers in public health · 2022Article
- Article
- Medical imaging of tissue engineering and regenerative medicine constructs.Biomaterials science · 2021Review
- In Vivo Tracking of Tissue Engineered Constructs.Micromachines · 2019Review
- An Ultrasensitive Calcium Reporter System via CRISPR-Cas9-Mediated Genome Editing in Human Pluripotent Stem Cells.iScience · 2018Article
- Predicting in vivo behavior of injectable, in situ-forming drug-delivery systems.Therapeutic delivery · 2017Article
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
With the rapid expansion of biomaterial development and coupled efforts to translate such advances toward the clinic, non-invasive and non-destructive imaging tools to evaluate implants in situ in a timely manner are critically needed. The required multi-level information is comprehensive, including structural, mechanical, and biological changes such as scaffold degradation, mechanical strength, cell infiltration, extracellular matrix formation and vascularization to name a few. With its inherent advantages of non-invasiveness and non-destructiveness, ultrasound imaging can be an ideal tool for both preclinical and clinical uses. In this review, currently available ultrasound imaging technologies that have been applied in vitro and in vivo for tissue engineering and regenerative medicine are discussed and some new emerging ultrasound technologies and multi-modality approaches utilizing ultrasound are introduced.
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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.