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Measurement and image-based estimation of dielectric properties of biological tissues -past, present, and future

PAPER manual 2022 Review Effect: unclear Evidence: Insufficient

Abstract

Measurement and image-based estimation of dielectric properties of biological tissues -past, present, and future Sasaki K, Porter E, Rashed EA, Farrugia L, Schmid G. Measurement and image-based estimation of dielectric properties of biological tissues -past, present, and future. Phys Med Biol. 2022;67(14):10.1088/1361- 6560/ac7b64. Published 2022 Jul 8. doi:10.1088/1361-6560/ac7b64. Abstract The dielectric properties of biological tissues are fundamental pararmeters that are essential for electromagnetic modeling of the human body. The primary database of dielectric properties compiled in 1996 on the basis of dielectric measurements at frequencies from 10 Hz to 20 GHz has attracted considerable attention in the research field of human protection from non-ionizing radiation. This review summarizes findings on the dielectric properties of biological tissues at frequencies up to 1 THz since the database was developed. Although the 1996 database covered general (normal) tissues, this review also covers malignant tissues that are of interest in the research field of medical applications. An intercomparison of dielectric properties based on reported data is presented for several tissue types. Dielectric properties derived from image-based estimation techniques developed as a result of recent advances in dielectric measurement are also included. Finally, research essential for future advances in human body modeling is discussed. Open access paper: iopscience.iop.org

AI evidence extraction

At a glance
Study type
Review
Effect direction
unclear
Population
Sample size
Exposure
Evidence strength
Insufficient
Confidence: 74% · Peer-reviewed: yes

Main findings

This review summarizes reported findings on dielectric properties of biological tissues at frequencies up to 1 THz since the 1996 dielectric property database (10 Hz to 20 GHz) was developed. It includes intercomparisons across tissue types, covers malignant tissues, and includes dielectric properties derived from image-based estimation techniques.

Outcomes measured

  • Dielectric properties of biological tissues
  • Dielectric properties measurement data (reported since 1996 database)
  • Image-based estimation of dielectric properties
  • Intercomparison of dielectric properties across tissue types
  • Dielectric properties of malignant tissues (as covered in review)
View raw extracted JSON
{
    "study_type": "review",
    "exposure": {
        "band": null,
        "source": null,
        "frequency_mhz": null,
        "sar_wkg": null,
        "duration": null
    },
    "population": null,
    "sample_size": null,
    "outcomes": [
        "Dielectric properties of biological tissues",
        "Dielectric properties measurement data (reported since 1996 database)",
        "Image-based estimation of dielectric properties",
        "Intercomparison of dielectric properties across tissue types",
        "Dielectric properties of malignant tissues (as covered in review)"
    ],
    "main_findings": "This review summarizes reported findings on dielectric properties of biological tissues at frequencies up to 1 THz since the 1996 dielectric property database (10 Hz to 20 GHz) was developed. It includes intercomparisons across tissue types, covers malignant tissues, and includes dielectric properties derived from image-based estimation techniques.",
    "effect_direction": "unclear",
    "limitations": [],
    "evidence_strength": "insufficient",
    "confidence": 0.7399999999999999911182158029987476766109466552734375,
    "peer_reviewed_likely": "yes",
    "keywords": [
        "dielectric properties",
        "biological tissues",
        "electromagnetic modeling",
        "non-ionizing radiation",
        "human body modeling",
        "image-based estimation",
        "malignant tissues",
        "10 Hz to 1 THz",
        "20 GHz",
        "THz"
    ],
    "suggested_hubs": []
}

AI can be wrong. Always verify against the paper.

AI-extracted fields are generated from the abstract/metadata and may be incomplete or incorrect. This content is for informational purposes only and is not medical advice.

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