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      Automatic Segmentation of the Fetus in 3D Magnetic Resonance Images Using Deep Learning: Accurate and Fast Fetal Volume Quantification for Clinical Use

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          Abstract

          Magnetic resonance imaging (MRI) provides images for estimating fetal volume and weight, but manual delineations are time consuming. The aims were to (1) validate an algorithm to automatically quantify fetal volume by MRI; (2) compare fetal weight by Hadlock’s formulas to that of MRI; and (3) quantify fetal blood flow and index flow to fetal weight by MRI. Forty-two fetuses at 36 (29–39) weeks gestation underwent MRI. A neural network was trained to segment the fetus, with 20 datasets for training and validation, and 22 for testing. Hadlock’s formulas 1–4 with biometric parameters from MRI were compared with weight by MRI. Blood flow was measured using phase-contrast MRI and indexed to fetal weight. Bland–Altman analysis assessed the agreement between automatic and manual fetal segmentation and the agreement between Hadlock’s formulas and fetal segmentation for fetal weight. Bias and 95% limits of agreement were for automatic versus manual measurements 4.5 ± 351 ml (0.01% ± 11%), and for Hadlock 1–4 vs MRI 108 ± 435 g (3% ± 14%), 211 ± 468 g (7% ± 15%), 106 ± 425 g (4% ± 14%), and 179 ± 472 g (6% ± 15%), respectively. Umbilical venous flow was 406 (range 151–650) ml/min (indexed 162 (range 52–220) ml/min/kg), and descending aortic flow was 763 (range 481–1160) ml/min (indexed 276 (range 189–386) ml/min/kg). The automatic method showed good agreement with manual measurements and saves considerable analysis time. Hadlock 1–4 generally agree with MRI. This study also illustrates the confounding effects of fetal weight on absolute blood flow, and emphasizes the benefit of indexed measurements for physiological assessment.

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          Most cited references23

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          Estimation of fetal weight with the use of head, body, and femur measurements--a prospective study.

          In utero estimates of fetal weight were evaluated prospectively in 109 fetuses with the use of sonographic models developed in a previous study. This report confirms that the best in utero weight estimates result from the use of models based on measurements of head size, abdominal size, and femur length. Since the accuracy of these models (1 SD = 7.5%) is significantly better than those based on measurements of head and body (e.g., biparietal diameter, abdominal circumference), we recommend routine use of such models in obstetric sonography.
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            Design and validation of Segment - freely available software for cardiovascular image analysis

            Background Commercially available software for cardiovascular image analysis often has limited functionality and frequently lacks the careful validation that is required for clinical studies. We have already implemented a cardiovascular image analysis software package and released it as freeware for the research community. However, it was distributed as a stand-alone application and other researchers could not extend it by writing their own custom image analysis algorithms. We believe that the work required to make a clinically applicable prototype can be reduced by making the software extensible, so that researchers can develop their own modules or improvements. Such an initiative might then serve as a bridge between image analysis research and cardiovascular research. The aim of this article is therefore to present the design and validation of a cardiovascular image analysis software package (Segment) and to announce its release in a source code format. Results Segment can be used for image analysis in magnetic resonance imaging (MRI), computed tomography (CT), single photon emission computed tomography (SPECT) and positron emission tomography (PET). Some of its main features include loading of DICOM images from all major scanner vendors, simultaneous display of multiple image stacks and plane intersections, automated segmentation of the left ventricle, quantification of MRI flow, tools for manual and general object segmentation, quantitative regional wall motion analysis, myocardial viability analysis and image fusion tools. Here we present an overview of the validation results and validation procedures for the functionality of the software. We describe a technique to ensure continued accuracy and validity of the software by implementing and using a test script that tests the functionality of the software and validates the output. The software has been made freely available for research purposes in a source code format on the project home page http://segment.heiberg.se. Conclusions Segment is a well-validated comprehensive software package for cardiovascular image analysis. It is freely available for research purposes provided that relevant original research publications related to the software are cited.
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              Sonographic estimation of fetal weight. The value of femur length in addition to head and abdomen measurements.

              Sonographic estimation of fetal weight in utero was performed in 167 live-born fetuses examined within one week of delivery. Regression models were based on measurements of abdominal circumference, head circumference, biparietal diameter, and femur length, both alone and in combination. The best results (1 S.D. = 7.5% of actual weight) were obtained by combining measurements of the fetal head, abdomen, and femur, most likely due to the strong linear relationship between femur length and crown-heel length.
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                Author and article information

                Contributors
                Erik.Hedstrom@med.lu.se
                Journal
                Pediatr Cardiol
                Pediatr Cardiol
                Pediatric Cardiology
                Springer US (New York )
                0172-0643
                1432-1971
                5 November 2022
                5 November 2022
                2023
                : 44
                : 6
                : 1311-1318
                Affiliations
                [1 ]GRID grid.4514.4, ISNI 0000 0001 0930 2361, Clinical Physiology, Department of Clinical Sciences Lund, , Lund University, Skane University Hospital, ; Lund, Sweden
                [2 ]GRID grid.4514.4, ISNI 0000 0001 0930 2361, Wallenberg Centre for Molecular Medicine, , Lund University, ; Lund, Sweden
                [3 ]GRID grid.4514.4, ISNI 0000 0001 0930 2361, Diagnostic Radiology, Department of Clinical Sciences Lund, , Lund University, Skane University Hospital, ; Lund, Sweden
                Article
                3038
                10.1007/s00246-022-03038-0
                10293340
                36334112
                9a897336-bc13-4294-82bd-0d7ea4031e90
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 8 April 2022
                : 21 October 2022
                Funding
                Funded by: Lund University
                Categories
                Research
                Custom metadata
                © Springer Science+Business Media, LLC, part of Springer Nature 2023

                Cardiovascular Medicine
                fetal cardiovascular magnetic resonance imaging,fetal weight,prenatal diagnosis

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