Three-dimensional US Fractional Moving Blood Volume: Validation of Renal Perfusion Quantification
Open accessAbstract
Background Three-dimensional (3D) fractional moving blood volume (FMBV) derived from 3D power Doppler US has been proposed for noninvasive approximation of perfusion. However, 3D FMBV has never been applied in animals against a ground truth. Purpose To determine the correlation between 3D FMBV and the reference standard of fluorescent microspheres (FMS) for measurement of renal perfusion in a porcine model. Materials and Methods From February 2017 to September 2017, adult pigs were administered FMS before and after measurement of renal 3D FMBV at baseline (100%) and approximately 75%, 50%, and 25% flow levels by using US machines from two different vendors. The 3D power Doppler US volumes were converted and segmented, and correlations between FMS and 3D FMBV were made with simple linear regression (r2). Similarity and reproducibility of manual segmentation were determined with the Dice similarity coefficient and 3D FMBV reproducibility (intraclass correlation coefficient [ICC]). Results Thirteen pigs were studied with 33 flow measurements. Kidney volume (mean Dice similarity coefficient ± standard deviation, 0.89 ± 0.01) and renal segmentation (coefficient of variation = 12.6%; ICC = 0.86) were consistent. The 3D FMBV calculations had high reproducibility (ICC = 0.97; 95% confidence interval: 0.96, 0.98). The 3D FMBV per-pig correlation showed excellent correlation for US machines from both vendors (mean r2 = 0.96 [range, 0.92–1.0] and 0.93 [range, 0.78–1.0], respectively). The correlation between 3D FMBV and perfusion measured with microspheres was high for both US machines (r2 = 0.80 [P < .001] and 0.70 [P < .001], respectively). Conclusion The strong correlation between three-dimensional (3D) fractional moving blood volume (FMBV) and fluorescent microspheres indicates that 3D FMBV shows excellent correlation to perfusion and good reproducibility. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Morrell et al in this issue.
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When combined with power Doppler ultrasound, the model will allow automated measurement of perfusion of the utero-placental interface.
“When combined with power Doppler ultrasound this will allow for automated measurement of perfusion of the utero-placental interface [10], [44].”
From Fully Automated 3-D Ultrasound Segmentation of the Placenta, Amniotic Fluid, and Fetus for Early Pregnancy Assessment (2021) · cites this paper as [10]
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Cites
Matplotlib: a 2D graphics environment
Hunter, J. D. (2007) · Computing in Science & Engineering · doi:10.1109/mcse.2007.55 · Cited by 39,249 · see citing works
Measures of the Amount of Ecologic Association Between Species
Dice, L. R. (1945) · Ecology · doi:10.2307/1932409 · Cited by 12,153 · see citing works
Power Doppler US: a potentially useful alternative to mean frequency-based color Doppler US.
Rubin, J. M., Bude, R. O., Carson, P. L., Bree, R. L., & Adler, R. S. (1994) · Radiology · doi:10.1148/radiology.190.3.8115639 · Cited by 864 · see citing works
Self-citationirr: Various Coefficients of Interrater Reliability and Agreement
Gamer, M., Lemon, J., Fellows, I., & Singh, P. (2005) · doi:10.32614/cran.package.irr · Cited by 543 · see citing works
Levy, B. I., Schiffrin, E. L., Mourad, J., Agostini, D., Vicaut, É., Safar, M. E., & Struijker-Boudier, H. A. J. (2008) · Circulation · doi:10.1161/circulationaha.107.763730 · Cited by 472 · see citing works
Fractional moving blood volume: estimation with power Doppler US.
Rubin, J. M., Adler, R. S., Fowlkes, J. B., Spratt, S., Pallister, J. E., Chen, J. F., & Carson, P. L. (1995) · Radiology · doi:10.1148/radiology.197.1.7568820 · Cited by 298 · see citing works
Self-citationBlood flow distributions by microsphere deposition methods
Prinzen, F. W. (2000) · Cardiovascular Research · doi:10.1016/s0008-6363(99)00252-7 · Cited by 183 · see citing works
User-Guided Segmentation of Multi-modality Medical Imaging Datasets with ITK-SNAP
Yushkevich, P. A., Pashchinskiy, A., Oguz, I., Mohan, S., Schmitt, J. E., Stein, J. M., Zukić, D., Vicory, J., McCormick, M., Yushkevich, N., et al. (2019) · Neuroinformatics · doi:10.1007/s12021-018-9385-x · Cited by 175 · see citing works
Lundell, A., Bergqvist, D., Mattsson, E. J. R., & Nilsson, B. (1993) · Clinical Physiology · doi:10.1111/j.1475-097x.1993.tb00470.x · Cited by 131 · see citing works
Rubin, J. M., Bude, R. O., Fowlkes, J. B., Spratt, R. S., Carson, P. L., & Adler, R. S. (1997) · Radiology · doi:10.1148/radiology.205.3.9393532 · Cited by 107 · see citing works
Self-citationMorel, O., Pachy, F., Chavatte‐Palmer, P., et al. (2010) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.7741 · Cited by 72 · see citing works
Artz, N. S., Wentland, A. L., Sadowski, E. A., et al. (2010) · Investigative Radiology · doi:10.1097/rli.0b013e3181f5e101 · Cited by 60 · see citing works
Acharya, G., Sitras, V., Erkinaro, T. M., Mäkikallio, K., Kavasmaa, T., Päkkilä, M., Huhta, J. C., & Rasanen, J. P. (2007) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.3977 · Cited by 59 · see citing works
Hernandez‐Andrade, E., Jansson, T., Ley, D., Bellander, M., Persson, M., Lingman, G., & Maršál, K. (2004) · Ultrasound in Obstetrics & Gynecology · doi:10.1002/uog.1002 · Cited by 58 · see citing works
Collins, S. L., Stevenson, G. N., Noble, J. A., Impey, L., & Welsh, A. W. (2012) · Ultrasound in Obstetrics & Gynecology · doi:10.1002/uog.10122 · Cited by 52 · see citing works
Self-citationIn Vivo Perfusion Estimation Using Subharmonic Contrast Microbubble Signals
Forsberg, F., Liu, J., Shi, W. T., et al. (2006) · Journal of Ultrasound in Medicine · doi:10.7863/jum.2006.25.1.15 · Cited by 49 · see citing works
Measurement of Volumetric Flow
Kripfgans, O. D., Rubin, J. M., Hall, A. L., et al. (2006) · Journal of Ultrasound in Medicine · doi:10.7863/jum.2006.25.10.1305 · Cited by 46 · see citing works
Self-citationQuantification of power Doppler and the index 'fractional moving blood volume' (FMBV)
Welsh, A. (2004) · Ultrasound in Obstetrics & Gynecology · doi:10.1002/uog.1037 · Cited by 44 · see citing works
Self-citationAn Automated Approach for Kidney Segmentation in Three-Dimensional Ultrasound Images
Marsousi, M., Plataniotis, K. N., & Stergiopoulos, S. (2016) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2016.2580040 · Cited by 39 · see citing works
Stevenson, G. N., Collins, S. L., Welsh, A. W., Impey, L. W., & Noble, J. A. (2015) · Radiology · doi:10.1148/radiol.14132363 · Cited by 38 · see citing works
Self-citationProceedings of the 10th Python in Science Conference
(2011) · Proceedings of the Python in Science Conferences · doi:10.25080/majora-ebaa42b7-014 · Cited by 37 · see citing works
Perfusion Estimation Using Contrast-Enhanced 3-dimensional Subharmonic Ultrasound Imaging
Sridharan, A. N., Eisenbrey, J. R., Liu, J., et al. (2013) · Investigative Radiology · doi:10.1097/rli.0b013e3182925160 · Cited by 34 · see citing works
Warmuth, C., Nagel, S., Hegemann, O., et al. (2007) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.21011 · Cited by 29 · see citing works
Lemoine, S., Papillard, M., Belloi, A., Rognant, N., Fouque, D. P., Laville, M., Rouvière, O., & Juillard, L. (2011) · Radiology · doi:10.1148/radiol.11101317 · Cited by 29 · see citing works
Gain setting in power Doppler US.
Martinoli, C., & Derchi, L. E. (1997) · Radiology · doi:10.1148/radiology.202.1.8988227 · Cited by 25 · see citing works
Collins, S. L., Welsh, A. W., Impey, L., Noble, J. A., & Stevenson, G. N. (2017) · PLOS ONE · doi:10.1371/journal.pone.0178675 · Cited by 25 · see citing works
Self-citationSelection of the Sub-noise Gain Level for Acquisition of VOCAL Data Sets: A Reliability Study
Sanderson, J., Wu, L., Mahajan, A., Meriki, N., Henry, A., & Welsh, A. W. (2013) · Ultrasound in Medicine & Biology · doi:10.1016/j.ultrasmedbio.2013.09.004 · Cited by 9 · see citing works
Self-citationGu, B., Stevenson, G. N., Ferreira, A. G. D. M. T., Pathirana, S., Sanderson, J., Henry, A., Alphonse, J., & Welsh, A. W. (2018) · Australasian Journal of Ultrasound in Medicine · doi:10.1002/ajum.12094 · Cited by 1 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 4
- [11]Cox RW, Ashburner J, Breman H, Fissell K, Haselgrove C, Holmes CJ, Lancaster JL, Rex DE, Smith SM, Woodward JB. A (Sort of) new image data format standard: NIfTI-1: WE 150. Neuroimage 2004; 22: e1440.
- [14]Stevenson GN, Collins SL, Welsh AW, Impey LW, Noble JA. A Technique for the Estimation of Fractional Moving Blood Volume by Using Three-dimensional Power Doppler US. Radiology 2015; 274: 230– 237. doi: 10.1148/radiol.14132363 25117590 · DOI · Paper page
- [17]McKinney W. Data structures for statistical computing in python. Proceedings of the 9th Python in Science Conference: Austin, TX, 2010; p. 51– 56.
- [25]Drost CJ. Vessel diameter-independent volume flow measurements using ultrasound. Proc San Diego Biomed 1978; 17: 299– 302.
Cited by
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Looney, P., Yin, Y., Collins, S. L., Nicolaides, K. H., Plasencia, W., Molloholli, M., Natsis, S., & Stevenson, G. N. (2021) · IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control · doi:10.1109/tuffc.2021.3052143 · Cited by 40 · see citing works
Self-citationWeerasinghe, N. H., Lovell, N. H., Welsh, A. W., & Stevenson, G. N. (2021) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.3027318 · Cited by 27 · see citing works
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- Authors
- Welsh, A. W., Fowlkes, J. B., Pinter, S. Z., Ives, K. A., Owens, G. E., Rubin, J. M., Kripfgans, O. D., Looney, P., Collins, S. L., & Stevenson, G. N.
- Affiliations
- University of Michigan (US)
- Corresponding author
- Stevenson, Gordon N.
- ORCID
- Venue
- Radiology
- Published
- 2019-11
- Volume
- 293
- Issue
- 2
- Pages
- 460-468
- ISSN
- 0033-8419 (ISSN-L)
- 1527-1315
- PMC
- PMC6800606
- OpenAlex
- W2979227121
- Cited by
- 31
- References
- 28
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 5 · 2023: 5 · 2022: 2 · 2021: 8 · 2020: 3 · 2019: 1
- FWCI
- 2.57
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Radiology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- UNSWorks (UNSW Sydney) (submittedVersion, cc-by-nc-nd)
- Funders
- University of New South Wales
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Renal and Vascular Pathologies
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Ultrasound Imaging and Elastography
- Keywords
- fractional moving blood volume, 3D power Doppler ultrasound, renal perfusion, fluorescent microspheres, porcine model, perfusion quantification, reproducibility, kidney segmentation, ground truth validation
- MeSH terms
- Animals, Blood Flow Velocity, Blood Volume, Fluorescence, Kidney, Microspheres, Swine, Reproducibility of Results, Ultrasonography, Doppler, Imaging, Three-Dimensional, Models, Animal
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