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Review of consensus test methods in medical imaging and current practices in photoacoustic image quality assessment.

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Title: Review of consensus test methods in medical imaging and current practices in photoacoustic image quality assessment.
Authors: Palma-Chavez, Jorge1 (AUTHOR) jpalmachavez@eng.ucsd.edu, Pfefer, T. Joshua2 (AUTHOR) joshua.pfefer@fda.hhs.gov, Agrawal, Anant2 (AUTHOR) anant.agrawal@fda.hhs.gov, Jokerst, Jesse V.1,3,4 (AUTHOR) jjokerst@ucsd.edu, Vogt, William C.2 (AUTHOR) william.vogt@fda.hhs.gov
Source: Journal of Biomedical Optics. Sep2021, Vol. 26 Issue 9, p90901-90901. 1p.
Subjects: Acoustic imaging, Magnetic resonance imaging, Diagnostic imaging, Test methods, Magnetic resonance mammography, Ultrasonic imaging, Photoacoustic effect
Abstract: Significance: Photoacoustic imaging (PAI) is a powerful emerging technology with broad clinical applications, but consensus test methods are needed to standardize performance evaluation and accelerate translation. Aim: To review consensus image quality test methods for mature imaging modalities [ultrasound, magnetic resonance imaging (MRI), x-ray CT, and x-ray mammography], identify best practices in phantom design and testing procedures, and compare against current practices in PAI phantom testing. Approach: We reviewed scientific papers, international standards, clinical accreditation guidelines, and professional society recommendations describing medical image quality test methods. Observations are organized by image quality characteristics (IQCs), including spatial resolution, geometric accuracy, imaging depth, uniformity, sensitivity, low-contrast detectability, and artifacts. Results: Consensus documents typically prescribed phantom geometry and material property requirements, as well as specific data acquisition and analysis protocols to optimize test consistency and reproducibility. While these documents considered a wide array of IQCs, reported PAI phantom testing focused heavily on in-plane resolution, depth of visualization, and sensitivity. Understudied IQCs that merit further consideration include out-of-plane resolution, geometric accuracy, uniformity, low-contrast detectability, and co-registration accuracy. Conclusions: Available medical image quality standards provide a blueprint for establishing consensus best practices for photoacoustic image quality assessment and thus hastening PAI technology advancement, translation, and clinical adoption. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Biomedical Optics is the property of SPIE - International Society of Optical Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 152790440
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
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  Label: Title
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  Data: Review of consensus test methods in medical imaging and current practices in photoacoustic image quality assessment.
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  Data: <searchLink fieldCode="AR" term="%22Palma-Chavez%2C+Jorge%22">Palma-Chavez, Jorge</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jpalmachavez@eng.ucsd.edu</i><br /><searchLink fieldCode="AR" term="%22Pfefer%2C+T%2E+Joshua%22">Pfefer, T. Joshua</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> joshua.pfefer@fda.hhs.gov</i><br /><searchLink fieldCode="AR" term="%22Agrawal%2C+Anant%22">Agrawal, Anant</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> anant.agrawal@fda.hhs.gov</i><br /><searchLink fieldCode="AR" term="%22Jokerst%2C+Jesse+V%2E%22">Jokerst, Jesse V.</searchLink><relatesTo>1,3,4</relatesTo> (AUTHOR)<i> jjokerst@ucsd.edu</i><br /><searchLink fieldCode="AR" term="%22Vogt%2C+William+C%2E%22">Vogt, William C.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> william.vogt@fda.hhs.gov</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Biomedical+Optics%22">Journal of Biomedical Optics</searchLink>. Sep2021, Vol. 26 Issue 9, p90901-90901. 1p.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Acoustic+imaging%22">Acoustic imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetic+resonance+imaging%22">Magnetic resonance imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Diagnostic+imaging%22">Diagnostic imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Test+methods%22">Test methods</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetic+resonance+mammography%22">Magnetic resonance mammography</searchLink><br /><searchLink fieldCode="DE" term="%22Ultrasonic+imaging%22">Ultrasonic imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Photoacoustic+effect%22">Photoacoustic effect</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Significance: Photoacoustic imaging (PAI) is a powerful emerging technology with broad clinical applications, but consensus test methods are needed to standardize performance evaluation and accelerate translation. Aim: To review consensus image quality test methods for mature imaging modalities [ultrasound, magnetic resonance imaging (MRI), x-ray CT, and x-ray mammography], identify best practices in phantom design and testing procedures, and compare against current practices in PAI phantom testing. Approach: We reviewed scientific papers, international standards, clinical accreditation guidelines, and professional society recommendations describing medical image quality test methods. Observations are organized by image quality characteristics (IQCs), including spatial resolution, geometric accuracy, imaging depth, uniformity, sensitivity, low-contrast detectability, and artifacts. Results: Consensus documents typically prescribed phantom geometry and material property requirements, as well as specific data acquisition and analysis protocols to optimize test consistency and reproducibility. While these documents considered a wide array of IQCs, reported PAI phantom testing focused heavily on in-plane resolution, depth of visualization, and sensitivity. Understudied IQCs that merit further consideration include out-of-plane resolution, geometric accuracy, uniformity, low-contrast detectability, and co-registration accuracy. Conclusions: Available medical image quality standards provide a blueprint for establishing consensus best practices for photoacoustic image quality assessment and thus hastening PAI technology advancement, translation, and clinical adoption. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Biomedical Optics is the property of SPIE - International Society of Optical Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=152790440
RecordInfo BibRecord:
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        Value: 10.1117/1.JBO.26.9.090901
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        Text: English
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        Type: general
      – SubjectFull: Magnetic resonance imaging
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      – SubjectFull: Diagnostic imaging
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      – SubjectFull: Test methods
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      – SubjectFull: Magnetic resonance mammography
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      – SubjectFull: Ultrasonic imaging
        Type: general
      – SubjectFull: Photoacoustic effect
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      – TitleFull: Review of consensus test methods in medical imaging and current practices in photoacoustic image quality assessment.
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            NameFull: Palma-Chavez, Jorge
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              M: 09
              Text: Sep2021
              Type: published
              Y: 2021
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