title: Evaluation of an automated fetal myocardial performance index.
abstract: OBJECTIVE
  To compare automated measurements of the fetal left myocardial performance index (MPI) with manual measurements for absolute value, repeatability and waveform acceptability.
  
  
  METHODS
  This was a multicenter international online study using images from uncomplicated, morphologically normal singleton pregnancies (16-38 weeks' gestation). Single Doppler ultrasound cardiac cycle images of 25 cases were selected, triplicated and randomized (n = 75). Six senior observers, unaware of the repetition of images, manually calculated MPI for each waveform and the results were compared with automation. Intraobserver repeatability and interobserver reproducibility were assessed using intraclass correlation coefficients (ICCs) and 95% CI. The agreement between each observer's manual MPI measurements and corresponding automated measurements was evaluated using Bland-Altman plots and ICCs with 95% CI. The degree of variation between experts in the classification of fetal MPI waveform quality was assessed using individual cardiac cycle left MPI images previously classified by two authors as 'optimal', 'suboptimal' or 'unacceptable', with 30 images selected for each quality group. Ten images in each category were duplicated and the resulting 120 images were randomized and then classified online by five observers. The kappa statistic (κ) was used to demonstrate interobserver and intraobserver agreement and agreement of classifications by the five observers.
  
  
  RESULTS
  The automated measurement software returned the same value for any given image, resulting in an ICC of 1.00. Manual measurements had intraobserver repeatability ICC values ranging from 0.69 to 0.97, and the interobserver reproducibility ICC was 0.78. Comparison of automated vs manual MPI absolute measurements for each observer gave ICCs ranging from 0.77 to 0.96. Interobserver image quality classification agreement gave k = 0.69 (P < 0.001), and the intraobserver agreement was variable (κ ranging from 0.40 to 0.81).
  
  
  CONCLUSIONS
  Automated fetal MPI provides superior repeatability and reproducibility to manual methodology. Additionally, experts vary significantly when classifying suitability of fetal MPI waveforms. Automated MPI may facilitate clinical translation by removing human subjectivity. Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd.
authors.affiliation: Department of Maternal-Fetal Medicine, Royal Hospital for Women, Randwick, Sydney, New South Wales, Australia. alec.welsh@unsw.edu.au.|School of Women's & Children's Health, University of New South Wales, Sydney, New South Wales, Australia. alec.welsh@unsw.edu.au.
authors.forename: A W
authors.initials: AW
authors.lastname: Welsh
authors.affiliation: Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia.
authors.forename: P
authors.initials: P
authors.lastname: Maheshwari
authors.affiliation: Graduate School of Biomedical Engineering, University of New South Wales, Sydney, New South Wales, Australia.
authors.forename: J
authors.initials: J
authors.lastname: Wang
authors.affiliation: Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia.
authors.forename: A
authors.initials: A
authors.lastname: Henry
authors.affiliation: Graduate School of Biomedical Engineering, University of New South Wales, Sydney, New South Wales, Australia.
authors.forename: D
authors.initials: D
authors.lastname: Chang
authors.affiliation: Maternal-Fetal Medicine, Hospital Clinica Barcelona, Barcelona, Spain.
authors.forename: F
authors.initials: F
authors.lastname: Crispi
authors.affiliation: The Fetal Center, UT Health, Houston, TX, USA.
authors.forename: H M
authors.initials: HM
authors.lastname: Gardiner
authors.affiliation: Department of Obstetrics and Gynecology, Fetal Medicine Unit, Wayne State University School of Medicine Detroit, Detroit, MI, USA.
authors.forename: E
authors.initials: E
authors.lastname: Hernandez-Andrade
authors.affiliation: School of Medicine, King Saud University, Riyadh, Saudi Arabia.
authors.forename: N
authors.initials: N
authors.lastname: Meriki
authors.affiliation: Graduate School of Biomedical Engineering, University of New South Wales, Sydney, New South Wales, Australia.
authors.forename: S
authors.initials: S
authors.lastname: Redmond
authors.affiliation: Obstetrics and Gynaecology, Hadassah University Hospital, Mt Scopus, Jerusalem, Israel.
authors.forename: S
authors.initials: S
authors.lastname: Yagel
mesh_terms: D015150:Echocardiography, Doppler / Q000379:methods*; D005260:Female; D005318:Fetal Heart / Q000000981:diagnostic imaging*; D005865:Gestational Age; D006801:Humans; D015588:Observer Variation; D011247:Pregnancy; D011446:Prospective Studies; D015203:Reproducibility of Results; D012984:Software; D016216:Ultrasonography, Prenatal / Q000379:methods*
keywords: Doppler; automation; cardiac MPI; fetus