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Computational and Mathematical Methods in Medicine
Volume 2013 (2013), Article ID 278978, 8 pages
Research Article

Automatic Evaluation of Progression Angle and Fetal Head Station through Intrapartum Echographic Monitoring

1National Research Council, Institute of Clinical Physiology, University Campus Ecotekne, Via Monteroni, 73100 Lecce, Italy
2Department of Obstetrics and Gynecology, University of Perugia, Santa Maria della Misericordia University Hospital, San Sisto, 06132 Perugia, Italy
3Obstetrics and Gynecology Department, “Vito Fazzi” Hospital, Piazza Filippo Muratore, 73100 Lecce, Italy

Received 31 May 2013; Accepted 2 August 2013

Academic Editor: Massimo Mischi

Copyright © 2013 Sergio Casciaro et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Labor progression is routinely assessed through transvaginal digital inspections, meaning that the clinical decisions taken during the most delicate phase of pregnancy are subjective and scarcely supported by technological devices. In response to such inadequacies, we combined intrapartum echographic acquisitions with advanced tracking algorithms in a new method for noninvasive, quantitative, and automatic monitoring of labor. Aim of this work is the preliminary clinical validation and accuracy evaluation of our automatic algorithm in assessing progression angle (PA) and fetal head station (FHS). A cohort of 10 parturients underwent conventional labor management, with additional translabial echographic examinations after each uterine contraction. PA and FHS were evaluated by our automatic algorithm on the acquired images. Additionally, an experienced clinical sonographer, blinded regarding the algorithm results, quantified on the same acquisitions of the two parameters through manual contouring, which were considered as the standard reference in the evaluation of automatic algorithm and routine method accuracies. The automatic algorithm (mean error ± 2SD) provided a global accuracy of  mm for FHS and 4° ± 9° for PA, which is far above the diagnostic ability shown by the routine method, and therefore it resulted in a reliable method for earlier identification of abnormal labor patterns in support of clinical decisions.