Computerized assessment of placental calcification post‐ultrasound: a novel software tool
Open accessAbstract
Objectives: Placental calcification is associated with an increased risk of perinatal morbidity and mortality. The subjectivity of current ultrasound methods of assessment of placental calcification indicates that a more objective method is required. The aim of this study was to correlate the percentage of calcification defined by the clinician using a new software tool for calculating the extent of placental calcification with traditional ultrasound methods and with pregnancy outcome. Methods: Ninety placental images were individually assessed. An upper threshold was defined, based on high intensity, to quantify calcification within the placenta. Output metrics were then produced including the overall percentage of calcification with respect to the total number of pixels within the region of interest. The results were correlated with traditional ultrasound methods of assessment of placental calcification and with pregnancy outcome. Results: The results demonstrate a significant correlation between placental calcification, as defined using the software, and traditional methods of Grannum grading of placental calcification. Whilst correlation with perinatal outcome and cord pH was not significant as a result of small numbers, patients with placental calcification assessed using the computerized software at the upper quartile had higher rates of poor perinatal outcome when compared with those at the lower quartile (8/22 (36%) vs 3/23 (13%); P = 0.069). Conclusion: These results suggest that this computerized software tool has the potential to become an alternative method of assessing placental calcification. Copyright © 2012 ISUOG. Published by John Wiley & Sons, Ltd.
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Single feature often cannot detect all fine details of a US image, and fusion of features outperforms single feature by providing more latent and intrinsic information.
“Single feature often cannot detect all the fine details of the US image, and fusion of features outperforms single feature by providing more latent and intrinsic information12346.”
From Discriminative Learning for Automatic Staging of Placental Maturity via Multi-layer Fisher Vector (2015) · cites this paper as [2]
The Methods describe selecting a placental region of interest and using an intensity threshold to quantify calcification; the Discussion considers the tool’s potential as an alternative assessment method. Neither section addresses whether a single feature misses fine image details or whether feature fusion outperforms it. Searches for the claim’s feature-fusion language and a paraphrase found no supporting passage; page numbers were not available in our copy. (LLM, conf=0.76)
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Cites
The ultrasonic changes in the maturing placenta and their relation to fetal pulmonic maturity
Grannum, P. A. T., Berkowitz, R. L., & Hobbins, J. C. (1979) · American Journal of Obstetrics and Gynecology · doi:10.1016/0002-9378(79)90312-0 · Cited by 408 · see citing works
Routine ultrasound in late pregnancy (after 24 weeks' gestation)
Bricker, L., Medley, N., & Pratt, J. J. (2015) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd001451.pub4 · Cited by 337 · see citing works
Routine ultrasound in late pregnancy (after 24 weeks' gestation)
Bricker, L., Neilson, J. P., & Dowswell, T. (2008) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd001451.pub3 · Cited by 122 · see citing works
Chen, K. H., Chen, L. R., & Lee, Y. H. (2010) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.7733 · Cited by 103 · see citing works
Ultrasonic evidence of placental calcification at 36 weeks' gestation: maternal and fetal outcomes
McKenna, D., Tharmaratnam, S., Mahsud, S., & Dornan, J. C. (2004) · Acta Obstetricia Et Gynecologica Scandinavica · doi:10.1111/j.0001-6349.2005.00563.x · Cited by 96 · see citing works
Higgins, M., McAuliffe, F. M., & Mooney, E. E. (2011) · Pediatric and Developmental Pathology · doi:10.2350/10-07-0872-oa.1 · Cited by 95 · see citing works
Self-citationUltrasound of the Placenta: A Systematic Approach. Part I: Imaging
Abramowicz, J. S., & Sheiner, E. (2008) · Placenta · doi:10.1016/j.placenta.2007.12.006 · Cited by 91 · see citing works
Stereology of the placenta in type 1 and type 2 diabetes
Higgins, M., Felle, P., Mooney, E. E., Bannigan, J., & McAuliffe, F. M. (2011) · Placenta · doi:10.1016/j.placenta.2011.04.015 · Cited by 89 · see citing works
Self-citationFox, H. (1964) · BJOG An International Journal of Obstetrics & Gynaecology · doi:10.1111/j.1471-0528.1964.tb04353.x · Cited by 33 · see citing works
Imaging and assessment of placental function
Moran, M., & McAuliffe, F. M. (2011) · Journal of Clinical Ultrasound · doi:10.1002/jcu.20846 · Cited by 31 · see citing works
Self-citationDistribution of placental grade in high-risk gravidas
Hills, D., Irwin, G., Tuck, S. M., & Baim, R. S. (1984) · American Journal of Roentgenology · doi:10.2214/ajr.143.5.1011 · Cited by 30 · see citing works
Intraobserver and interobserver variation in the sonographic grading of placental maturity
Sau, A., Seed, P. T., & Langford, K. (2004) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.1004 · Cited by 30 · see citing works
Poor agreement between operators on grading of the placenta
Moran, M., Ryan, J. T., Higgins, M., Brennan, P., & McAuliffe, F. M. (2011) · Journal of Obstetrics and Gynaecology · doi:10.3109/01443615.2010.522266 · Cited by 28 · see citing works
Self-citationPlacental grading in the complicated or high-risk pregnancy.
Clair, M. R., Rosenberg, E. R., Tempkin, D., et al. (1983) · Journal of Ultrasound in Medicine · doi:10.7863/jum.1983.2.7.297 · Cited by 22 · see citing works
Amniotic band syndrome: Antepartum ultrasonic diagnosis of discordant anencephaly
Worthen, N. J., Lawrence, D., & Bustillo, M. (1980) · Journal of Clinical Ultrasound · doi:10.1002/jcu.1870080513 · Cited by 19 · see citing works
Ultrasound assessment of the postmature pregnancy.
Moya, F., Grannum, P. A. T., Pinto, K., et al. (1985) · PubMed · Cited by 18 · see citing works
Ultrasonic features of preeclampsia
Carroll, B. A. (1980) · Journal of Clinical Ultrasound · doi:10.1002/jcu.1870080607 · Cited by 11 · see citing works
Ryan, J. T., McAuliffe, F. M., Higgins, M., et al. (2008) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.769464 · Cited by 7 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 3
- Carroll B. Ultrasonic features of pre-eclampsia. J Clin Ultrasound 1980; 8: 453.
- Veena A, Sapna J. Placental grade and its correlation with foetal outcome. J Obstet Gynecol Ind 2000; 50: 59-62.
- Copyright 2012 ISUOG. Published by John Wiley & Sons Ltd. Ultrasound Obstet Gynecol 2013; 41: 545-549. 14690705, 2013, 5, Downloaded from https://obgyn.onlinelibrary.wiley.com/doi/10.1002/uog.12278, Wiley Online Library on [05/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
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Segmentation and classification in MRI and US fetal imaging: Recent trends and future prospects
Torrents-Barrena, J., Piella, G., Masoller, N., Gratacós, E., Eixarch, E., Ceresa, M., & Ballester, M. Á. G. (2019) · Medical Image Analysis · doi:10.1016/j.media.2018.10.003 · Cited by 97 · see citing works
Discriminative Learning for Automatic Staging of Placental Maturity via Multi-layer Fisher Vector
Lei, B., Yao, Y., Chen, S., Li, S., Li, W., Ni, D., & Wang, T. (2015) · Scientific Reports · doi:10.1038/srep12818 · Cited by 28 · see citing works
“…and prognosis decision not only based on the doctor’s subjective diagnosis experience, but also decision scores from the developed learned models via training, which can obtain a more accurate US image interpretation for the placental function evaluation than the traditional methods 2,15–18 .”
Background
- Authors
- Moran, M., Higgins, M., Zombori, G., Ryan, J., & McAuliffe, F. M.
- Affiliations
- University College Dublin (IE)
- Corresponding author
- McAuliffe, F. M.
- Venue
- Ultrasound in Obstetrics & Gynecology
- Publisher
- Wiley
- Published
- 2013-04
- Volume
- 41
- Issue
- 5
- Pages
- 545-549
- ISSN
- 0960-7692 (ISSN-L)
- 1469-0705
- OpenAlex
- W1832575962
- Cited by
- 16
- References
- 18
- Citations by year
- 2026: 1 · 2025: 1 · 2023: 1 · 2022: 1 · 2020: 2 · 2019: 1 · 2018: 3 · 2016: 2 · 2015: 4
- FWCI
- 1.54
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Ultrasound in Obstetrics and Gynecology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- University College Dublin
- Topics
- Health Sciences › Medicine › Obstetrics and Gynecology › Pregnancy and preeclampsia studies
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Maternal and fetal healthcare
- Health Sciences › Medicine › Obstetrics and Gynecology › Maternal and Perinatal Health Interventions
- Keywords
- placental calcification, computerized image analysis, perinatal outcomes, perinatal morbidity and mortality, placental ultrasound
- MeSH terms
- Adult, Analysis of Variance, Calcinosis, Diagnosis, Computer-Assisted, Female, Humans, Placenta Diseases, Pregnancy, Pregnancy Outcome, Prospective Studies, Software, Ultrasonography, Prenatal, Young Adult
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