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Maximal Reduction of STIC Acquisition Time for Volumetric Assessment of the Fetal Heart-Benefits and Limitations of Semiautomatic Fetal Intelligent Navigation Echocardiography (FINE) Static Mode.

ABSTRACT: (1) Objective: To scrutinize the reliability and the clinical value of routinely used fetal intelligent navigation echocardiography (FINE) static mode (5DHeartStatic™) for accelerated semiautomatic volumetric assessment of the normal fetal heart. (2) Methods: In this study, a total of 296 second and third trimester fetuses were examined by targeted ultrasound. Spatiotemporal image correlation (STIC) volumes of the fetal heart were acquired for further volumetric assessment. In addition, all fetal hearts were scanned by a fast acquisition time volume (1 s). The volumes were analyzed using the FINE software. The data were investigated regarding the number of properly reconstructed planes and cardiac axis. (3) Results: A total of 257 volumes were included for final analysis. The mean gestational age (GA) was 23.9 weeks (14.3 to 37.7 weeks). In 96.9 (standard acquisition time, FINE standard mode) and 94.2% (fast acquisition time, FINE static mode) at least seven planes were reconstructed properly (p = 0.0961, not significant). Regarding the overall depiction rate, the standard mode was able to reconstruct 96.9% of the planes properly, whereas the static mode showed 95.2% of the planes (p = 0.0098). Moreover, there was no significant difference between the automatic measurement of the cardiac axis (37.95 + 9.14 vs. 38.00 + 8.92 degrees, p = 0.8827, not significant). (4) Conclusions: Based on our results, the FINE static mode technique is a reliable method. It provides similar information of the cardiac anatomy compared to conventional STIC volumes assessed by the FINE method. The FINE static mode has the potential to minimize the influence of motion artifacts during volume acquisition and might therefore be helpful concerning volumetric cardiac assessment in daily routine.

SUBMITTER: Gembicki M

PROVIDER: S-EPMC9320472 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:OBJECTIVE:To evaluate prospectively the performance of Fetal Intelligent Navigation Echocardiography (FINE) applied to spatiotemporal image correlation (STIC) volume datasets of the normal fetal heart. METHODS:In all women between 19 and 30 weeks' gestation with a normal fetal heart, an attempt was made to acquire STIC volume datasets of the apical four-chamber view if the following criteria were met: (1) fetal spine located between 5- and 7-o'clock positions; (2) minimal or absent shadowing (including a clearly visible transverse aortic arch); (3) absence of fetal breathing, hiccups, or movement; and (4) adequate image quality. Each STIC volume successfully acquired was evaluated by STICLoop™ to determine its appropriateness before applying the FINE method. Visualization rates of fetal echocardiography views using diagnostic planes and/or Virtual Intelligent Sonographer Assistance (VIS-Assistance®) were calculated. RESULTS:One or more STIC volumes (365 in total) were obtained successfully in 72.5% (150/207) of women undergoing ultrasound examination. Of the 365 volumes evaluated by STICLoop, 351 (96.2%) were considered to be appropriate. From the 351 STIC volumes, only one STIC volume per patient (n = 150) was analyzed using the FINE method, and consequently nine fetal echocardiography views were generated in 76-100% of cases using diagnostic planes only, in 98-100% of cases using VIS-Assistance only, and in 98-100% of cases when using a combination of diagnostic planes and/or VIS-Assistance. CONCLUSIONS:In women between 19 and 30 weeks' gestation with a normal fetal heart undergoing prospective sonographic examination, STIC volumes can be obtained successfully in 72.5% of cases. The FINE method can be applied to generate nine standard fetal echocardiography views in 98-100% of these cases using a combination of diagnostic planes and/or VIS-Assistance. This suggests that FINE could be implemented in fetal cardiac screening programs. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Project description:ObjectiveTo evaluate the performance of color and bidirectional power Doppler ultrasound combined with Fetal Intelligent Navigation Echocardiography (FINE) in examining the fetal heart.MethodsA prospective cohort study was conducted of fetuses in the second and third trimesters with a normal heart or with congenital heart disease (CHD). One or more spatiotemporal image correlation (STIC) volume datasets, combined with color or bidirectional power Doppler (S-flow) imaging, were acquired in the apical four-chamber view. Each successfully obtained STIC volume was evaluated by STICLoop™ to determine its appropriateness before applying the FINE method. Visualization rates for standard fetal echocardiography views using diagnostic planes and/or Virtual Intelligent Sonographer Assistance (VIS-Assistance®) were calculated for grayscale (removal of Doppler signal), color Doppler and S-flow Doppler. In four cases with CHD (one case each of tetralogy of Fallot, hypoplastic left heart and coarctation of the aorta, interrupted inferior vena cava with azygos vein continuation and asplenia, and coarctation of the aorta with tricuspid regurgitation and hydrops), the diagnostic potential of this new technology was presented.ResultsA total of 169 STIC volume datasets of the normal fetal heart (color Doppler, n = 78; S-flow Doppler, n = 91) were obtained from 37 patients. Only a single STIC volume of color Doppler and/or a single volume of S-flow Doppler per patient were analyzed using FINE. Therefore, 60 STIC volumes (color Doppler, n = 27; S-flow Doppler, n = 33) comprised the final study group. Median gestational age at sonographic examination was 23 (interquartile range, 21-27.5) weeks. Color Doppler FINE generated nine fetal echocardiography views (grayscale) using (1) diagnostic planes in 73-100% of cases, (2) VIS-Assistance in 100% of cases, and (3) a combination of diagnostic planes and/or VIS-Assistance in 100% of cases. The rate of generating successfully eight fetal echocardiography views with appropriate color and S-flow Doppler information was 89-100% and 91-100% of cases, respectively, using a combination of diagnostic planes and/or VIS-Assistance. However, the success rate for the ninth echocardiography view (i.e. superior and inferior venae cavae) was 33% and 30% for color and S-flow Doppler, respectively. In all four cases of CHD, color Doppler FINE demonstrated evidence of abnormal fetal cardiac anatomy and/or hemodynamic flow.ConclusionsThe FINE method applied to STIC volumes of normal fetal hearts acquired with color or bidirectional power Doppler information can generate successfully eight to nine standard fetal echocardiography views (via grayscale, color Doppler or power Doppler) in the second and third trimesters. In cases of CHD, color Doppler FINE demonstrates successfully abnormal anatomy and/or Doppler flow characteristics. Published 2017. This article is a U.S. Government work and is in the public domain in the USA. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

Project description:Due to advances in the acquisition and analysis of medical imaging, it is currently possible to quantify the tumor phenotype. The emerging field of Radiomics addresses this issue by converting medical images into minable data by extracting a large number of quantitative imaging features. One of the main challenges of Radiomics is tumor segmentation. Where manual delineation is time consuming and prone to inter-observer variability, it has been shown that semi-automated approaches are fast and reduce inter-observer variability. In this study, a semiautomatic region growing volumetric segmentation algorithm, implemented in the free and publicly available 3D-Slicer platform, was investigated in terms of its robustness for quantitative imaging feature extraction. Fifty-six 3D-radiomic features, quantifying phenotypic differences based on tumor intensity, shape and texture, were extracted from the computed tomography images of twenty lung cancer patients. These radiomic features were derived from the 3D-tumor volumes defined by three independent observers twice using 3D-Slicer, and compared to manual slice-by-slice delineations of five independent physicians in terms of intra-class correlation coefficient (ICC) and feature range. Radiomic features extracted from 3D-Slicer segmentations had significantly higher reproducibility (ICC?=?0.85±0.15, p?=?0.0009) compared to the features extracted from the manual segmentations (ICC?=?0.77±0.17). Furthermore, we found that features extracted from 3D-Slicer segmentations were more robust, as the range was significantly smaller across observers (p?=?3.819e-07), and overlapping with the feature ranges extracted from manual contouring (boundary lower: p?=?0.007, higher: p?=?5.863e-06). Our results show that 3D-Slicer segmented tumor volumes provide a better alternative to the manual delineation for feature quantification, as they yield more reproducible imaging descriptors. Therefore, 3D-Slicer can be employed for quantitative image feature extraction and image data mining research in large patient cohorts.

Project description:BackgroundCongenital Heart Disease represents the most frequent fetal malformation. The lack of prenatal identification of congenital heart defects can have adverse consequences for the neonate, while a correct prenatal diagnosis of specific cardiac anomalies improves neonatal care neurologic and surgery outcomes. Sonographers perform prenatal diagnosis manually during the first or second-trimester scan, but the reported detection rates are low. This project's primary objective is to develop an Intelligent Decision Support System that uses two-dimensional video files of cardiac sweeps obtained during the standard first-trimester fetal echocardiography (FE) to signal the presence/absence of previously learned key features.MethodsThe cross-sectional study will be divided into a training part of the machine learning approaches and the testing phase on previously unseen frames and eventually on actual video scans. Pregnant women in their 12-13 + 6 weeks of gestation admitted for routine first-trimester anomaly scan will be consecutively included in a two-year study, depending on the availability of the experienced sonographers in early fetal cardiac imaging involved in this research. The Data Science / IT department (DSIT) will process the key planes identified by the sonographers in the two- dimensional heart cine loop sweeps: four-chamber view, left and right ventricular outflow tracts, three vessels, and trachea view. The frames will be grouped into the classes representing the plane views, and then different state-of-the- art deep-learning (DL) pre-trained algorithms will be tested on the data set. The sonographers will validate all the intermediary findings at the frame level and the meaningfulness of the video labeling.DiscussionFE is feasible and efficient during the first trimester. Still, the continuous training process is impaired by the lack of specialists or their limited availability. Therefore, in our study design, the sonographer benefits from a second opinion provided by the developed software, which may be very helpful, especially if a more experienced colleague is unavailable. In addition, the software may be implemented on the ultrasound device so that the process could take place during the live examination.Trial registrationThe study is registered under the name "Learning deep architectures for the Interpretation of Fetal Echocardiography (LIFE)", project number 408PED/2020, project code PN-III-P2-2.1-PED-2019.Trial registrationClinicalTrials.gov , unique identifying number NCT05090306, date of registration 30.10.2020.

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Maximal Reduction of STIC Acquisition Time for Volumetric Assessment of the Fetal Heart-Benefits and Limitations of Semiautomatic Fetal Intelligent Navigation Echocardiography (FINE) Static Mode.

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