Literature DB >> 25117590

A technique for the estimation of fractional moving blood volume by using three-dimensional power Doppler US.

Gordon N Stevenson1, Sally L Collins, Alec W Welsh, Lawrence W Impey, J Alison Noble.   

Abstract

PURPOSE: To (a) demonstrate an image-processing method that can automatically measure the power Doppler signal in a three-dimensional ( 3D three-dimensional ) ultrasonographic (US) volume by using the location of organs within the image and (b) compare 3D three-dimensional fractional moving blood volume ( FMBV fractional moving blood volume ) results with commonly used, unstandardized measures of 3D three-dimensional power Doppler by using the human placenta as the organ of interest.
MATERIALS AND METHODS: This is a retrospective study of scans obtained as part of a prospective study of imaging placental biomarkers with US, performed with ethical approval and written informed consent. One hundred forty-three consecutive female patients were examined by using an image-processing technique. Three-dimensional FMBV fractional moving blood volume was measured on the vasculature from the uteroplacental interface to a depth 5 mm into the placenta by using a normalization volume 10 mm outside the uteroplacental interface and compared against the Virtual Organ Computer-aided AnaLysis ( VOCAL Virtual Organ Computer-aided AnaLysis ; GE Healthcare, Milwaukee, Wis) vascularization flow index ( VFI vascularization flow index ). Intra- and interobserver variability was assessed in a subset of 18 volumes. Wilcoxon signed rank test and intraclass correlation coefficients were used to assess measurement repeatability.
RESULTS: The mean 3D three-dimensional FMBV fractional moving blood volume value ± standard deviation was 11.78% ± 9.30 (range, 0.012%-44.16%). Mean VFI vascularization flow index was 2.26 ± 0.96 (range, 0.15-6.06). Linear regression of VFI vascularization flow index versus FMBV fractional moving blood volume produced an R(2) value of 0.211 and was significantly different in distribution (P < .001). Intraclass correlation coefficient analysis showed higher FMBV fractional moving blood volume values than VFI vascularization flow index for intra- and interobserver variability; intraobserver values were 0.95 for FMBV fractional moving blood volume (95% confidence interval [ CI confidence interval ]: 0.90, 0.98) versus 0.899 for VFI vascularization flow index (95% CI confidence interval : 0.78, 0.96), and interobserver values were 0.93 for FMBV fractional moving blood volume (95% CI confidence interval : 0.82, 0.97) versus 0.67 for VFI vascularization flow index (95% CI confidence interval : 0.32, 0.86).
CONCLUSION: The extension of an existing two-dimensional standardized power Doppler measurement into 3D three-dimensional by using an image-processing technique was shown in an in utero placental study. Three-dimensional FMBV fractional moving blood volume and VFI vascularization flow index produced significantly different results. FMBV fractional moving blood volume performed better than VFI vascularization flow index in repeatability studies. Further studies are needed to assess accuracy against a reference standard.

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Mesh:

Year:  2014        PMID: 25117590     DOI: 10.1148/radiol.14132363

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  13 in total

1.  Three-dimensional US Fractional Moving Blood Volume: Validation of Renal Perfusion Quantification.

Authors:  Alec W Welsh; J Brian Fowlkes; Stephen Z Pinter; Kimberly A Ives; Gabe E Owens; Jonathan M Rubin; Oliver D Kripfgans; Pádraig Looney; Sally L Collins; Gordon N Stevenson
Journal:  Radiology       Date:  2019-10-01       Impact factor: 11.105

2.  Standardization of blood flow measurements by automated vascular analysis from power Doppler ultrasound scan.

Authors:  Yi Yin; Pádraig Looney; Sally L Collins
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2020-03-16

3.  Applying spatial-temporal image correlation to the fetal kidney: Repeatability of 3D segmentation and volumetric impedance indices.

Authors:  Bonita Gu; Gordon N Stevenson; Ana Ferreira; Sudeshni Pathirana; Jennifer Sanderson; Amanda Henry; Jennifer Alphonse; Alec W Welsh
Journal:  Australas J Ultrasound Med       Date:  2018-05-11

4.  Novel spatial-temporal image correlation derived indices of tissue vascular impedance: A variability study.

Authors:  Linda Wu; Ana Ferreira; Gordon N Stevenson; Jennifer Sanderson; Aditi Mahajan; Neama Meriki; Alec W Welsh
Journal:  Australas J Ultrasound Med       Date:  2017-07-11

Review 5.  Targeted drug delivery for maternal and perinatal health: Challenges and opportunities.

Authors:  Anjali Sharma; Nirnath Sah; Sujatha Kannan; Rangaramanujam M Kannan
Journal:  Adv Drug Deliv Rev       Date:  2021-08-26       Impact factor: 17.873

6.  Ultrasonographic tissue perfusion analysis at implant and palatal donor sites following soft tissue augmentation: A clinical pilot study.

Authors:  Lorenzo Tavelli; Shayan Barootchi; Jad Majzoub; Hsun-Liang Chan; William V Giannobile; Hom-Lay Wang; Oliver D Kripfgans
Journal:  J Clin Periodontol       Date:  2021-02-03       Impact factor: 8.728

7.  Fully Automated 3-D Ultrasound Segmentation of the Placenta, Amniotic Fluid, and Fetus for Early Pregnancy Assessment.

Authors:  Padraig Looney; Yi Yin; Sally L Collins; Kypros H Nicolaides; Walter Plasencia; Malid Molloholli; Stavros Natsis; Gordon N Stevenson
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2021-05-25       Impact factor: 3.267

8.  Placental vascularization alterations in hypertensive disorders complicating pregnancy (HDCP) and small for gestational age with HDCP using three-dimensional power doppler in a prospective case control study.

Authors:  Ting Yuan; Ting Zhang; Zhen Han
Journal:  BMC Pregnancy Childbirth       Date:  2015-10-05       Impact factor: 3.007

9.  3D fractional moving blood volume (3D-FMBV) demonstrates decreased first trimester placental vascularity in pre-eclampsia but not the term, small for gestation age baby.

Authors:  Sally L Collins; Alec W Welsh; Lawrence Impey; J Alison Noble; Gordon N Stevenson
Journal:  PLoS One       Date:  2017-06-01       Impact factor: 3.240

10.  Deep Learning strategies for Ultrasound in Pregnancy.

Authors:  Pedro H B Diniz; Yi Yin; Sally Collins
Journal:  Eur Med J Reprod Health       Date:  2020-08-25
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