Labour and delivery: a clinician's perspective on a biomechanics problem

Feltovich, Helen

doi:10.1098/rsfs.2019.0032

Cited by 11 publications

(9 citation statements)

References 39 publications

(52 reference statements)

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“…contract, deform, or rupture, to facilitate safe delivery of the fetus. Failure and mistiming of these essentially mechanical events contribute to major obstetrical complications such as PTB [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Longitudinal ultrasonic dimensions and parametric solid models of the gravid uterus and cervix

et al. 2021

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Tissue mechanics is central to pregnancy, during which maternal anatomic structures undergo continuous remodeling to serve a dual function to first protect the fetus in utero while it develops and then facilitate its passage out. In this study of normal pregnancy using biomechanical solid modeling, we used standard clinical ultrasound images to obtain measurements of structural dimensions of the gravid uterus and cervix throughout gestation. 2-dimensional ultrasound images were acquired from the uterus and cervix in 30 pregnant subjects in supine and standing positions at four time points during pregnancy (8-14, 14-16, 22-24, and 32-34 weeks). Offline, three observers independently measured from the images of multiple anatomic regions. Statistical analysis was performed to evaluate inter-observer variance, as well as effect of gestational age, gravity, and parity on maternal geometry. A parametric solid model developed in the Solidworks computer aided design (CAD) software was used to convert ultrasonic measurements to a 3-dimensional solid computer model, from which estimates of uterine and cervical volumes were made. This parametric model was compared against previous 3-dimensional solid models derived from magnetic resonance frequency images in pregnancy. In brief, we found several anatomic measurements easily derived from standard clinical imaging are reproducible and reliable, and provide sufficient information to allow biomechanical solid modeling. This structural dataset is the first, to our knowledge, to provide key variables to enable future computational calculations of tissue stress and stretch in pregnancy, making it possible to characterize the biomechanical milieu of normal pregnancy. This vital dataset will be the foundation to understand how the uterus and cervix malfunction in pregnancy leading to adverse perinatal outcomes.

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Section: Introductionmentioning

confidence: 99%

Longitudinal ultrasonic dimensions and parametric solid models of the gravid uterus and cervix

et al. 2021

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“…Todo esto puede ocurrir sin sintomatología y detectarse por evaluación ecográfica transvaginal (20,21). La activación decidual-miometrial y la remodelación cervical prematura están fuertemente asociadas, lo que refuerza la necesidad de evaluar el cuello uterino con pruebas que evalúen estos mecanismos (22). En una estructura como el cuello uterino con una variedad de patrones predecibles y ordenados, las regiones de interés seleccionados pueden diferir aleatoriamente y, por lo tanto, reflejan una mayor heterogeneidad.…”

Section: Discussionunclassified

Índice de heterogeneidad cervical o longitud cervical en la predicción de parto pretérmino inminente en pacientes sintomáticas

Mejia-Montilla¹,

Reyna-Villasmil²,

Torres-Cepeda³

et al. 2021

RSOGV

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Objetivo: Comparar el índice de heterogeneidad cervical con la longitud cervical en la predicción de parto pretérmino inminente en pacientes sintomáticas. Métodos. Estudio prospectivo realizado en mujeres con embarazos simples entre 24 y 35 semanas, con diagnóstico clínico de amenaza de parto pretérmino que asistieron al Hospital Central “Dr. Urquinaona”, Maracaibo, Venezuela. Al momento del diagnóstico las pacientes fueron evaluadas utilizando ecografía transvaginal para establecer los valores del índice de heterogeneidad cervical y longitud cervical. La resultante principal fue parto inminente (en los 7 días siguientes a la evaluación). Resultados. Fueron incluidas 326 pacientes, 152 mujeres presentaron parto pretérmino inminente (grupo A) y 251 pacientes fueron consideradas como controles (grupo B). No se encontraron diferencias entre los grupos con relación edad materna, nuliparidad, antecedente de parto pretérmino, antecedente de hábito tabáquico e índice de masa corporal (p = ns). Las pacientes del grupo A presentaron valores significativamente más bajos del índice de heterogeneidad cervical y longitud cervical comparado con las pacientes del grupo B (p < 0,0001). El índice de heterogeneidad cervical mostró un valor de área bajo la curva de 0,858 mientras que el valor del área bajo la curva de la longitud cervical fue de 0,985. La diferencia de la capacidad de discriminación entre las áreas bajo la curva de cada prueba fue significativa (p < 0,0001). Conclusión: El índice de heterogeneidad cervical no es superior a la longitud cervical en la predicción de parto pretérmino inminente en pacientes sintomáticas. Palabras clave: Índice de heterogeneidad cervical, Longitud cervical, Parto pretérmino, Predicción.

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“…The cervix is the lower part of the uterus that acts as the gateway to delivery, and remodels dramatically throughout pregnancy from firm, long and closed as the fetus develops in utero to short, soft, and dilated to allow delivery [35]. In obstetrics, predicting the risk of spontaneous preterm birth or the success of induction of labor are challenging problems that currently rely on many factors including a clinician's subjective assessment of cervical softening [36]. Ultrasound SWE has the potential to address this clinical need by providing objective and quantitative measurements of cervix stiffness [36]- [40].…”

Section: Cervix Elastography In Pregnancymentioning

confidence: 99%

SweiNet: Deep Learning Based Uncertainty Quantification for Ultrasound Shear Wave Elasticity Imaging

Jin¹,

Carlson²,

Feltovich³

et al. 2022

Preprint

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In ultrasound shear wave elasticity (SWE) imaging, a number of algorithms exist for estimating the shear wave speed (SWS) from spatiotemporal displacement data. However, no method provides a well-calibrated and practical uncertainty metric, hindering SWE's clinical adoption and utility in downstream decision-making. Here, we designed a deep learning SWS estimator that simultaneously outputs a quantitative and well-calibrated uncertainty value for each estimate. Our deep neural network (DNN) takes as input a single 2D spatiotemporal plane of tracked displacement data and outputs the two parameters m and σ of a log-normal probability distribution. For training and testing, we used in vivo 2D-SWE data of the cervix collected from 30 pregnant subjects, totaling 551 acquisitions and >2 million space-time plots. Points were grouped by uncertainty into bins to assess uncertainty calibration: the predicted uncertainty closely matched the root-meansquare estimation error, with an average absolute percent deviation of 3.84%. We created a leave-one-out ensemble model that estimated uncertainty with better calibration (1.45%) than any individual ensemble member on a heldout patient's data. Lastly, we applied the DNN to an external dataset to evaluate its generalizability. We have made the trained model, SweiNet, openly available to provide the research community with a fast SWS estimator that also outputs a well-calibrated estimate of the predictive uncertainty.

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Labour and delivery: a clinician's perspective on a biomechanics problem

Cited by 11 publications

References 39 publications

Longitudinal ultrasonic dimensions and parametric solid models of the gravid uterus and cervix

Longitudinal ultrasonic dimensions and parametric solid models of the gravid uterus and cervix

Índice de heterogeneidad cervical o longitud cervical en la predicción de parto pretérmino inminente en pacientes sintomáticas

SweiNet: Deep Learning Based Uncertainty Quantification for Ultrasound Shear Wave Elasticity Imaging

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