Impact of Ultrasound Training and Experience on Accuracy regarding Fetal Weight Estimation at Term Creative Education

Lanowski, Jan-Simon; Lanowski, Gabriele; Ehr, J. von; Jentschke, M.; Hillemanns, Peter; Kuehnle, Elna; Staboulidou, I.

doi:10.4236/ce.2017.811120

Cited by 3 publications

(3 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The slightest movement in the probe results in a drastic change in the appearance of an organ's image, while the noise produced in the video feed also hinders locating the organ [4]. Consequently, the resultant error in fetal biometry and time required are inconsistent, which may vary over the period as the sonographer gains experience [5] - [7].…”

Section: Introductionmentioning

confidence: 99%

Automated Fetal Head Classification and Segmentation Using Ultrasound Video

et al. 2021

View full text Add to dashboard Cite

During pregnancy, fetal ultrasound provides essential insight into a baby's growth and development. In this ultrasound, accurate assessment of fetal head biometry is critical to the clinical management of pregnancy. Current methodologies used for fetal head biometry heavily rely upon sonographer skills and experience to locate a baby's head. In this paper a novel approach is proposed to automate the fetal head biometry using live ultrasound feed; which is also capable of tackling low abdominal contrast against surroundings. Proposed model is trained on ALEXNET and UNET for classification and segmentation of headframes respectively from ultrasound video. To compute biparietal diameter (BPD) and head circumference (HC); which are essential requirements to compute gestational age, an ellipse is drawn on the contour of the annotated segmented fetal head. It should be noted that to validate gestational age estimate, ellipse are drawn on multiple best classified headframes obtained using ALEXNET. The proposed system is able to estimate gestational age within clinically acceptable ± one week of observed gestational age with an accuracy of 96%. Moreover, it uses robust machine vision features to reduce the sonographer's interaction with the system, thus reducing the overall procedure time and making it independent of sonographer's skill.

show abstract

Section: Introductionmentioning

confidence: 99%

Automated Fetal Head Classification and Segmentation Using Ultrasound Video

et al. 2021

View full text Add to dashboard Cite

show abstract

“…[ 6 7 ] Other factors, such as the time gap between ultrasound scan and delivery, measurement error, and examiner's skill and experience, have been also investigated to find out their potential impact on the accuracy of fetal weight estimation. [ 8 9 10 11 ] However, the exact impact of these factors is still not fully understood. Conflicting results from the different studies have made it even more complicated.…”

Section: Introductionmentioning

confidence: 99%

Analysis of factors influencing accuracy of ultrasound-based fetal weight estimation

Hiwale

Firtion

2020

Indian Journal of Radiology and Imaging

View full text Add to dashboard Cite

Context: The primary objective of this study was to examine the impact of maternal age, parity, gestational age, fetal gender, gestational diabetes mellitus, and pregnancy-induced hypertension on the accuracy of ultrasonography-based fetal weight estimation. The secondary objective was to find the impact of a formula selection on the accuracy of fetal weight estimation. Subjects and Methods: The inclusion criteria were a live-birth singleton pregnancy and the last ultrasound scan to delivery interval ≤7 days. Fetal weight was estimated using the Hadlock-4 formula. To study the concurrent impact of all the factors on the accuracy, cases were divided into two subcategories based on percentage error, with ±10% as a threshold. The accuracy of Hadlock-4 formula was compared with the two Indian population-based formulas, Hiwale-1 and Hiwale-2. Results: In total, 184 cases were included in the study. It was observed that the systematic error in weight estimation was significantly less in the male fetuses (8.45 ± 9.34%) in comparison to the female fetuses (11.71 ± 10.34%). The combined impact of all the factors on the accuracy was found to be nonsignificant by the multivariate analysis. The Hiwale-1 (-0.59 ± 8.75%) and Hiwale-2 (-0.65 ± 8.7%) formulas had statistically significant less errors compared to the Hadlock-4 formula (11.67 ± 7.95%). Conclusion: All the studied clinical factors were found to have a limited impact on the overall accuracy of fetal weight estimation. However, the formula selection was found to have a significant impact on the accuracy, with the native population-based formulas being significantly more accurate.

show abstract

“…Teleradiology is currently the most common use of telehealth in veterinary medicine (Poteet 2008). Ultrasonography has traditionally been the less frequent imaging modality used in teleradiology due to the importance of real-time assessment and this modality being largely operator dependent (Lanowski et al 2017). Technological advances that allow duplicating screens and the use of cameras or smart glasses that allow transmission of point of view video and twoway verbal communication are rapidly solving these problems.…”

Section: Introductionmentioning

confidence: 99%

Real‐time telehealth using ultrasonography is feasible in equine practice

Solís¹,

Bevevino²,

Doering³

et al. 2019

Equine Veterinary Education

View full text Add to dashboard Cite

Summary Telehealth allows health care professionals to evaluate patients in remote locations using telecommunications technology. This manuscript presents a pilot experience with the goal of testing the feasibility and exploring the benefits for patients and veterinarians, technological challenges and perceived value of telehealth in ultrasound. In phase 1, experienced equine private practitioners and a sonographer performed diagnostic ultrasound examinations in collaboration using telecommunications technology. In phase 2, horses underwent two consecutive ultrasound examinations. One examination was performed by an inexperienced sonographer assisted by a remote expert, and all horses were then scanned by an expert sonographer on‐site. Information about each interaction was collected, and a questionnaire was used at the end of the project to summarise practitioners’ and trainees’ experiences and perceptions. Thirty‐six cases were evaluated using telecommunications technology. There were technological problems that were minor in 11 occasions, and in one case, the remote assistance had to be cancelled. Sonograms were longer when performed by an inexperienced sonographer aided remotely (40 ± 19, [9–73] min) than when performed by a sonographer (24 ± 12, [4–43 min], P = 0.02). Telehealth for ultrasound was feasible, and technological challenges could be solved. Telehealth for ultrasound was well received by private practitioners, house officers and sonography experts. The perceived benefits were the addition of clinically useful information, reassurance to practitioners and horse owners and education for practitioners. The results of this study support generating the hypothesis that telehealth could in the future increase the quality of equine medicine, and prospective studies are needed to confirm this. Rigorous care will be needed to ensure that implementation of telehealth technology prioritises equine health and the veterinary profession.

show abstract

Impact of Ultrasound Training and Experience on Accuracy regarding Fetal Weight Estimation at Term Creative Education

Cited by 3 publications

References 34 publications

Automated Fetal Head Classification and Segmentation Using Ultrasound Video

Automated Fetal Head Classification and Segmentation Using Ultrasound Video

Analysis of factors influencing accuracy of ultrasound-based fetal weight estimation

Real‐time telehealth using ultrasonography is feasible in equine practice

Contact Info

Product

Resources

About