Dimensionless squared jerk: An objective differential to assess experienced and novice probe movement in obstetric ultrasound

Dromey, Brian; Ahmed, Shahanaz; Vasconcelos, Francisco; Mazomenos, Evangelos B.; Kunpalin, Yada; Ourselin, Sébastien; Deprest, Jan; David, Anna L.; Stoyanov, Danail; Peebles, Donald

doi:10.1002/pd.5855

Cited by 16 publications

(20 citation statements)

References 25 publications

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“…A comparison between experienced sonographers and novice operator was made by Dromey et al but in an experimental setting. 17 They analyzed the difference in deliberate hand movements using a mid-trimester phantom and showed that experienced sonographers reached the desirable plane easier than non-experienced sonographers and in a shorter time. A prospective cohort study investigated the performance of trainees compared to specialists in third-trimester ultrasound.…”

Section: Discussionmentioning

confidence: 99%

Training in Obstetric Ultrasound Biometry

Donadono

Grandjean

Stegen

et al. 2022

J of Ultrasound Medicine

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Objectives To assess the intra‐ and interobserver reproducibility of fetal biometry measurements obtained by trainee (junior) and experienced sonographers (senior) in the contest of two training programs in obstetric ultrasound. Methods This was a prospective study on 192 women recruited ensuring an even distribution throughout gestation (18–41 weeks), at University College London Hospital (UCLH), England (87 cases), and at Maternité Regionale Universitaire de Nancy (MRUN), France (105 cases). The training took place in two training centers with experience in ultrasound training and subspecialist training in fetal medicine. Measurements for head circumference (HC), abdominal circumference (AC), and femur length (FL) were obtained twice by junior and senior sonographers, blind to their own and each other's measurements. Differences between and within sonographers were expressed in millimeters and as a percentage of fetal dimensions. Reproducibility was assessed using Bland–Altman plots. Results Reproducibility was overall high with 95% confidence intervals (CI) within <6% for intraobserver and <8% for interobserver reproducibility. Intraobserver reproducibility was lower within junior than within senior sonographers' measurements for HC (95% CI: <4% versus <3%) and FL (95% CI: <6% and < 5%). Intraobserver reproducibility was similar between the two centers/training programs (AC 95% CI: <6%). Cumulative interobserver reproducibility in both centers was similar to the reproducibility within a single site (95% CI: <5%, <8%, and <7% for HC, AC, and FL, respectively). Conclusions Reproducibility of fetal biometry measurement was high in centers with structured training programs regardless of sonographers' experience. Reproducibility was higher in sonographers who completed the training.

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Section: Discussionmentioning

confidence: 99%

Training in Obstetric Ultrasound Biometry

Donadono

Grandjean

Stegen

et al. 2022

J of Ultrasound Medicine

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“…Common SPs include the trans-ventricular plane to measure the fetal head circumference, the trans-abdominal plane to measure the fetal abdominal circumference, and femoral plane to measure the femur length. Obtaining manual measurements can be time-consuming and operator-dependent, especially for trainees [9], and results in high inter-and intra-operator variability [13]. In fetal biometry, interoperator measurements variability range between ±4.9% and ±11.1% and an intra-operator variability between ±3% and ±6.6% [19].…”

Section: Introductionmentioning

confidence: 99%

BiometryNet: Landmark-based Fetal Biometry Estimation from Standard Ultrasound Planes

Avisdris,

Joskowicz,

Dromey

et al. 2022

Preprint

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Fetal growth assessment from ultrasound is based on a few biometric measurements that are performed manually and assessed relative to the expected gestational age. Reliable biometry estimation depends on the precise detection of landmarks in standard ultrasound planes. Manual annotation can be time-consuming and operator dependent task, and may results in high measurements variability. Existing methods for automatic fetal biometry rely on initial automatic fetal structure segmentation followed by geometric landmark detection. However, segmentation annotations are time-consuming and may be inaccurate, and landmark detection requires developing measurement-specific geometric methods. This paper describes BiometryNet, an end-to-end landmark regression framework for fetal biometry estimation that overcomes these limitations. It includes a novel Dynamic Orientation Determination (DOD) method for enforcing measurement-specific orientation consistency during network training. DOD reduces variabilities in network training, increases landmark localization accuracy, thus yields accurate and robust biometric measurements. To validate our method, we assembled a dataset of 3,398 ultrasound images from 1,829 subjects acquired in three clinical sites with seven different ultrasound devices. Comparison and cross-validation of three different biometric measurements on two independent datasets shows that BiometryNet is robust and yields accurate measurements whose errors are lower than the clinically permissible errors, outperforming other existing automated biometry estimation methods. Code is available at https://github.com/netanellavisdris/fetalbiometry.

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“…There is little global consensus on how to train, assess and evaluate skills in prenatal second trimester ultrasound (US) screening. Recommended assessment and quality control metrics vary across countries and institutions [5]. Despite this, standardized US planes and metrics to assess fetal size are well established [20].…”

Section: Introductionmentioning

confidence: 99%

“…The acquisition of these standard planes is subject to intraoperator and interoperator variabilities [22] which introduces some degree of uncertainty in the clinically obtained weight measurements and consequently requires a degree of caution when clinicians are interpreting fetal growth reports. Sonography expertise has a significant impact on minimizing variability of image quality and fetal biometry [5]. Consequently, training and competence assessment are of great importance to ensure effective, reproducible and safe clinical practice.…”

Section: Introductionmentioning

confidence: 99%

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AutoFB: Automating Fetal Biometry Estimation from Standard Ultrasound Planes

Bano¹,

Dromey²,

Júnior³

et al. 2021

Preprint

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During pregnancy, ultrasound examination in the second trimester can assess fetal size according to standardized charts. To achieve a reproducible and accurate measurement, a sonographer needs to identify three standard 2D planes of the fetal anatomy (head, abdomen, femur) and manually mark the key anatomical landmarks on the image for accurate biometry and fetal weight estimation. This can be a timeconsuming operator-dependent task, especially for a trainee sonographer. Computer-assisted techniques can help in automating the fetal biometry computation process. In this paper, we present a unified automated framework for estimating all measurements needed for the fetal weight assessment. The proposed framework semantically segments the key fetal anatomies using state-of-the-art segmentation models, followed by region fitting and scale recovery for the biometry estimation. We present an ablation study of segmentation algorithms to show their robustness through 4-fold cross-validation on a dataset of 349 ultrasound standard plane images from 42 pregnancies. Moreover, we show that the network with the best segmentation performance tends to be more accurate for biometry estimation. Furthermore, we demonstrate that the error between clinically measured and predicted fetal biometry is lower than the permissible error during routine clinical measurements.

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Dimensionless squared jerk: An objective differential to assess experienced and novice probe movement in obstetric ultrasound

Cited by 16 publications

References 25 publications

Training in Obstetric Ultrasound Biometry

Training in Obstetric Ultrasound Biometry

BiometryNet: Landmark-based Fetal Biometry Estimation from Standard Ultrasound Planes

AutoFB: Automating Fetal Biometry Estimation from Standard Ultrasound Planes

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