Next Article in Journal
Fertigation Strategies to Improve Water and Nitrogen Use Efficiency in Surface Irrigation System in the North China Plain
Previous Article in Journal
Geraniol: A Potential Defense-Related Volatile in “Baiye No. 1” Induced by Colletotrichum camelliae
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agriculture
Volume 13
Issue 1
10.3390/agriculture13010016
agriculture-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Ultrasonographic Monitoring of Fetal Growth and Fetal Weight Calculation in Sows during Gestation

by
Andreas Vernunft
1,*,
Anja Eggert
1 and
Klaus-Peter Brüssow
2
1
Research Institute for Farm Animal Biology (FBN), 18196 Dummerstorf, Germany
2
Faculty of Biological and Veterinary Science, Institute of Veterinary Medicine, Nicolaus Copernicus University, 87-100 Torun, Poland
*
Author to whom correspondence should be addressed.
Agriculture 2023, 13(1), 16; https://doi.org/10.3390/agriculture13010016
Submission received: 17 November 2022 / Revised: 13 December 2022 / Accepted: 19 December 2022 / Published: 21 December 2022
(This article belongs to the Section Farm Animal Production)
Browse Figures
Versions Notes

Abstract

:
Ultrasound examinations offer the possibility to monitor fetal growth and estimate fetal weight, but reference data for such techniques in pigs are rare. The aim of this study was therefore to identify suitable anatomical fetal structures for monitoring physiological growth dynamics by ultrasound examinations and to estimate fetal weight using appropriate mathematical models. For this purpose, 198 fetuses of 15 primiparous Landrace sows were examined by ultrasound on days 36, 50, 64, 79 and 92 of gestation in live sows and in utero after slaughter. Biparietal distance (BPD), rostro-occipital distance (ROD), corpus vitreum diameter, heart length, abdominal circumference (AC) and transverse and sagittal abdominal diameter were determined by ultrasound in utero, and the fetuses were subsequently ex uteri determined and weighed. Reference curves for the continuous increase in fetal parameters over the pregnancy were established. Weight estimation could be performed with linear models at a known stage of pregnancy using one or a combination of parameters. Cubic equations were developed to describe the relationships between body measurements and weight over the course of gestation. BPD, ROD and AC have been shown to be the most suitable parameters for fetal weight estimation, but in live sows, only the fetal head parameters could be easily and reliably determined. These techniques could initially be of interest for research into fetal growth, but future application in veterinary practice is also conceivable.

1. Introduction

Ultrasound-assisted visualisation of fetal structures and measurement of their dimensions (fetal biometry, fetometry, fetomorphometry) as well as calculation of fetal weight by sonographic fetometry is a widely used tool in gynaecology and obstetrics for monitoring pregnancy and birth. In human medicine, a main application of fetal biometry is the early detection of fetal abnormalities, fetal growth disorders or the determination of gestational age [1]. In most commercially bred livestock, the time of conception is known due to reproductive management. Therefore, the dating of pregnancy is only of interest in wild species and some uncontrolled farmed species such as sheep, or pet animals [2,3,4,5,6].
Ultrasound technology has been used in reproductive medicine in farm animals for thirty years and is mainly used for the early and safe detection of pregnancy, the detection of twin pregnancies in horses and the determination of fetal sex in horses and cattle [6,7,8]. In pigs, pregnancy is usually detected by nonimaging Doppler ultrasound techniques, and reports of the use of B-mode imaging during pregnancy in pigs are rare [8]. However, sonographically assisted fetometry offers the possibility of continuous and minimally invasive monitoring of fetal development throughout pregnancy [9,10].
In pigs, reproductive performance has been significantly increased in recent decades through larger litter sizes, while at the same time, problems with inhomogeneous litters and higher proportions of small piglets with high mortality until weaning have occurred [11]. Therefore, investigating the underlying mechanisms of intrauterine growth retardation (IUGR) in pigs is important [12]. To perform this, research must identify specific critical stages during pregnancy in the development of the fetus to focus research and intervention approaches [10]. Measuring the fetal growth rate through repeated examinations can also help to identify influencing factors for fetal maldevelopments such as IUGR and to develop therapeutic strategies [10,13]. To calculate the weight of a fetus and monitor its physiological growth, there are several formulas and reference values in human medicine available [1,14]. They are mainly based on the measurement of various skull structures (such as biparietal distance or head circumference), body dimensions (such as crown-rump length), skeletal structures (such as femur and humerus length) and various abdominal measurements, sometimes in combination with the week of gestation. This knowledge is lacking in veterinary reproductive medicine, especially in pigs.
The aim of this study was therefore to identify suitable anatomical fetal structures in order to present reference curves for physiological growth dynamics using ultrasound examinations, and to estimate fetal weight over the entire gestation period in pigs using mathematical models.

2. Materials and Methods

2.1. Animals

A total of 15 pregnant primiparous sows from the purebred German Landrace herd of the Research Institute for Farm Animal Biology (FBN, Dummerstorf, Germany) were provided for measurements in this study. The animals were housed and bred at the Experimental Station for Pigs and were regularly slaughtered at the institute’s abattoir. The animals were kept in a group and fed with a diet for pregnant sows according to their needs, as previously described in detail as standard diet [15]. The animals used were also comparable in age, weight and origin to those previously mentioned. The sows were artificially inseminated in a time-fixed manner with semen from purebred Landrace boars as part of the herd’s regular breeding programme, as previously described [16]. Pregnancy was detected with a Doppler ultrasound scanner on the fourth week of pregnancy. Based on our previous research [15,17], we have selected an experimental design that can adequately represent fetal growth at two-week intervals from early to late gestation. Therefore, for these studies, animals were selected for slaughter successively on the 36th, 50th, 64th, 79th and 92nd day of gestation. One day before slaughter, pregnancy was reconfirmed by B-mode ultrasound examination. The transducer was placed in the ventocaudal area of the right or left flank, dorsal to the udder. A frequency between 6–8 MHz was used; the penetration depth was set at 12 cm and the grain was set to 75%. Isopropyl alcohol was used as the coupling medium. At least one fetus was visualised and, as far as possible, the fetal parameters described below were determined in order to prove the practicability of the applied parameters on the living sow. Data collection for these analyses was carried out in 2012. No invasive examinations were carried out on the animals; the basis for the investigations of the fetuses was slaughterhouse material. All examinations of the animals as well as their regular slaughter and the only use of slaughterhouse material for this study were carried out in accordance with national and institutional regulations, relevant guidelines and the provisions of ethical regulations.

2.2. Ultrasound Measurements

All ultrasound measurements were performed with a portable ultrasound scanner (MyLabOne, Esaote, Cologne, Germany) equipped with a linear ultrasound probe (SV 3513). Three sows were slaughtered on the 36th, 50th, 64th, 79th and 92nd day of gestation and their excised gravid uterus was provided for ultrasound measurements on the fetuses. The settings of the ultrasound machine were adjusted to a 7–10 cm penetration depth, a frequency of 8 MHz and a gain of 65%. The ultrasound probe was placed directly on the isolated uterus and all fetuses (13 ± 2.4 fetuses/sow) were measured from one uterine tip to the other. A total of 198 fetuses were examined (36th day: n = 44; 50th day: n = 43; 64th day: n = 33; 79th day: n = 37; 92nd day of gestation: n = 41). The fetal morphometric parameters measured were biparietal distance (BPD), rostro-occipital distance (ROD), corpus vitreum diameter (CVD), heart length (HL), abdominal circumference (AC) and abdominal transverse and sagittal diameters (ATD, ASD), as shown in Figure 1. According to reference points from human medicine [1,14], the biparietal distance was measured by scanning the skull in a transverse or horizontal section (plana dorsalia). At the widest transverse size of the skull, callipers were placed on the lateral surfaces of the ossa cranii near the junction region of the os parietale and os temporale in a rostrocaudal plane with the sella turcica. As an equivalent for the fronto-occipital distance in human medicine, the widest rostro-occipital distance between the outer surfaces of the planum rostrale and the os occipitale was measured in a median-sagittal section of the fetal head. The largest diameter of the eyeball (corpus vitreum) was measured in the rostrocaudal direction. The longitudinal heart diameter (heart length) was determined in the four-chamber view plane, and the distance between the apex and the highest point of the atrial septum was determined. For the calculation of abdominal parameters, a cross-section was sought at the level of the liver, where the umbilical vein joins the caudal vena cava and the caudal vena cava has a circular cross-section. The abdominal circumference was measured with the ellipse measuring tool, and the widest transverse and sagittal diameters were determined with the distance measuring tool of the ultrasonic device. For all parameters, the mean of at least two measurements of the same morphology in each fetus was taken as the measured value. The relative differences between the first and second measurements within a determination were less than 1% at all time points and parameters investigated (ROD 0.2%; BPD 0.6%; CVD 0.7%; AC 0.4%; AST 0.8%; ATD 0.8%; HL 0.8%). After completion of the ultrasound examinations, all fetuses were removed from the uterus and the parameters (except heart length) were estimated again ex uteri manually with callipers and tape measures, and the weights of the fetuses were determined. Statistical comparisons revealed no significant differences between the ultrasonographic and manual fetal measurements (p > 0.05), except for ROD on the 36th day of pregnancy (p = 0.02, slightly higher values by manual measurements; data not presented).

2.3. Statistical Data Analysis

Statistical data analyses were conducted using R statistical software v. 4.2.0 [18] and specifically for data processing and visualization with the “tidyverse” package [19]. Temporal developments of all morphometric parameters over the course of pregnancy are shown as smooth curves of the medians, the lower 5% and the upper 95% percentiles. Smooth curves were fitted using Loess, a non-parametric local Regression approach. To inspect the linear relationship between fetus weight and all measured morphometric parameters (BPD, CVD, ROD, AC, ASD, ATD, HL), separate linear regression models were fitted for each parameter at each of the five investigated times points of pregnancy. R-square (R2) is used as the indicator of the goodness of fit of the models. As a next step, effects of all measured morphometric parameters, including day of pregnancy, on fetus weight were estimated fitting a linear mixed model using the lmer function of the package “lme4” [20]. The nested structure in the data, i.e., 10–17 fetus per sow, was properly defined and all variables were treated as fixed, continuous predictors. We log-transformed fetus weight to approximate normal distributions. Likelihood ratio tests were performed to test for the fixed effects. Based on these results, the three most important morphometric parameters were identified (AC, BPD, ROD) and multiple linear regressions were fitted to predict fetus weight, again separately at each of the five investigated time points of pregnancy. Adjusted R-square (R2), i.e., adjusted for the number of predictors and the associated changes in degrees of freedom, was used as the indicator of the goodness of fit of the multiple regression models. Finally, nonlinear, least squares regression models were fitted separately for the three most important morphometric parameters (AC, BPD, ROD) to predict fetal weight. A cubic function was chosen ( y = a · x 3 ). As goodness of the fit of a nonlinear regression model cannot be assessed using R-square. We therefore present the residual standard error (RSE). The smaller the values, the better the model fits the dataset. In addition, prediction bands of the fitted lines were calculated and visualized.
The datasets presented in this study can be found in the ZENODO online repository: DOI: 10.5281/zenodo.7431994, Publication date: 13 December 2022.

3. Results

3.1. Fetal Growth

The development of fetal weight and fetal morphometric parameters during the observation period from day 36 to day 92 of gestation were shown in Figure 2 as medians, with the lower 5% and the upper 95% percentiles. Fetal weight increases slightly exponentially as gestation progresses, with a parallel increasing weight range. The cranial parameters BPD and ROD as well as the dimensions of the abdomen (AC, ASD, ATD) increased continuously linearly with parallel, slightly increasing ranges. In contrast, the diameter of the corpus vitreum and heart length increased continuously only up to day 64 of gestation and then showed no clear further progression up to day 92.

3.1.1. Fetal Weight Calculation by Linear Regression Models

Linear regression models were fitted for each single morphometric parameter and separately for each day of gestation (Figure 3; Table 1). These results showed that it is possible, to some extent, to estimate fetal weight by single morphometric parameters, if taking into account the day of gestation. Figure 3 shows linear regressions between fetal parameters and fetal weight separately for each of the five investigated time points of pregnancy. In addition, all measured values of the fetal parameters are shown as a scatter plot together with the prediction intervals in these graphs. This representation shows that the measured values of the different fetal parameters partly show a large scatter, so that measured values of the fetal structures or weight from different time points can be at a comparable level. In particular, the measured values of the corpus vitreum diameter and heart length overlap between the examined time points in the second half of pregnancy. It can be clearly seen here that the prediction intervals for the fetal weight of the linear regressions can differ significantly between the different measurement time points and partly overlap. The same applies to the linear relationship between the fetal parameter and weight (slope of the regression lines). Most accurate estimates, i.e., highest R2 values were found when using AC (R2: 0.46–0.85) and ASD (R2: 0.29–0.80) (Table 1). In contrast, linear regressions between corpus vitreum diameter or heart length and fetal weights had very low R-squares of <0.2 in many cases (Table 1). The linear regressions between BPD and fetal weight also only reached R-squares of 0.13–0.30. However, it is noticeable that the R-squares of the linear regressions as well as their slopes greatly differ between the examined time points of pregnancy within one parameter (Table 1).

3.1.2. Fetal Weight Calculation by Multiple Linear Regression Models

The results of a linear mixed model, estimating effects of all measured morphometric parameters, showed that in addition to gestation day, BPD, ROD and AC had the largest effects on fetal weight (Table 2). In order to generate better models for weight estimation on the different days of pregnancy studied, the three most relevant parameters (ROD, BPD, AC) were tested in multiple linear regressions to predict fetal weight, again, separately for each pregnancy day (Table 3). Table 3 presents the best fitting three- and two-way combinations for the different time points investigated. At each stage of pregnancy studied, the best prediction of fetal weight was achieved with a three-way combination of BPD, ROD and AC, resulting in R-squared of up to 0.89. Using a two-way combination, the best prediction of fetal weight was achieved with a combination of BPD and AC at each time point investigated (Table 3). These combinations achieved R-squares that ranged between 0.55 on the 36th and 0.86 on the 79th day of pregnancy. The exclusive combination of head parameters only led to relatively low prediction values for fetal weight (R-squares of approximately 0.4–0.5, data not shown).

3.1.3. Fetal Weight Calculation by Nonlinear Regression Models

As the linear regressions between fetal parameters and weight did not describe the relationships adequately and continuously, a weight estimation model for the entire pregnancy period was developed by fitting a cubic nonlinear regression model ( y = a · x 3 ) for the three most relevant morphometric parameters (ROD, BPD, AC) (Figure 4). A continuous measurement series resulted from the fact that overlapping piglet weights occurred between measurement times. For AC, the fetal weight factor “a” and its standard error was estimated to be 0.077 ± 0.001 and the residual standard error (RSE) was 33.23. For BPD and ROD, the model yielded factor “a” of 12.228 ± 0.178 and 1.199 ± 0.011, respectively. The RSE of the two parameters were slightly larger than for AC, with values of 71.03 and 45.66. With increasing gestation length, prediction intervals become significantly smaller.

3.2. Transabdominal Ultrasound Scan

Ultrasound studies on live sows showed that the fetal head parameters (BPD, ROD, CVD) were most reliable to measure in a transabdominal scan (Table 4). The correct sectional plane to determine the abdominal parameters (AC, ASD, ATD), on the other hand, became difficult with increasing gestation length with our used technique.

4. Discussion

Ultrasonographic monitoring of fetal growth and weight calculation are well studied in humans and are used in human obstetrics. Initial adaptations of this knowledge in animals showed that not all commonly used fetal parameters can be used directly in animals. In most veterinary studies, fetometry is only used to calculate gestational age or time to birth [3,4,5,21]. This is one of the few studies in animals and the first study in pigs to demonstrate the possibility of pregnancy monitoring and fetal weight estimation using ultrasonographic fetometry.
Analogous to the use of fetometry in human medicine, mainly the parameters of the head and trunk were chosen for this study. Due to the anatomical conditions in pigs, some common parameters of human medicine could not be used in pigs or had to be adapted. For example, head circumference is well established in humans but can hardly be standardised in pigs. The fronto-occipital distance, which is common in humans, had to be adapted as the rostro-occipital distance in pigs, as is common in animals [5,22]. Some important and commonly used limb parameters, such as femur and humerus length, were not included in this study because they cannot be used in early pregnancy due to the lack of ossification of bones [23] or are difficult to visualise in the required plane in pigs. The well-established determination of crown-rump length was not considered in this study because it cannot be determined in late gestation in large animals due to their size [2,24]. In addition, it should be mentioned that the position of the fetus in the sow cannot be massively manipulated to fit the structure of interest into the scanned sector at a standardised angle. Furthermore, in a transcutaneous ultrasound examination in pigs, the direction of the ultrasound probe cannot be adjusted to the position of the fetus to the same extent as would be possible in examinations in women or a transrectal examination in cattle. Therefore, this study focused on the cranial and abdominal parameters presented.

4.1. Fetal Growth

The exponential development of fetal weight during the studied pregnancy period (Figure 2) conforms to the expected pattern and values for fetal growth in pigs, as reviewed by Kim and shown by others [25,26,27], and also seen in our own previous work [15,17]. It can therefore be assumed that the growth curves presented can be used as references for different pig breeds, as long as body proportions, birth weight and gestation length are comparable to the German Landrace (such as Yorkshire [28]). For deviating breeds (and wild boars), own reference values must certainly be worked out. In human obstetrics, it is common to use ethnic-specific values [1].
The continuous linear progress of the biparietal distance and rostro-occipital distance during pregnancy are in accordance with findings in humans (fronto-occipital), ruminants and pigs [1,10,28,29]. The diameter of the corpus vitreum (eyeball) showed no clear progress in the second half of pregnancy. Other studies in bovines, buffaloes, camels and horses (eyeball width) have also shown a linear development in early pregnancy, but a flattening of the eyeball growth curve in late pregnancy [23,24,29,30]. The eyeball, as a phylogenetic part of the brain, has growing parts in early gravity and differentiating parts later. The maturation of the fetal eye of the pig is described as relatively early compared to other species [31]. Studies that showed stronger correlations between the fetal eye and fetal development used the distance between the eyes or the size of the orbita, and therefore, tended to reflect more the growth of the fetal skull as a whole [14,32,33]. Heart length also showed no continuous increase during pregnancy in this study, especially in the second trimester. Other studies showed a linear growth of heart length in pigs [32] and in humans [34], or described the growth of various heart dimensions (heart length, circumference and volume) as a sigmoidal function with variable slopes during pregnancy with linear components in the second trimester [35]. For an accurate estimate of the fetal heart, it is necessary to take the measurements during a desired period of the cardiac cycle. For the inner and outer diameters of the heart, it is recommended to take the measurements at the end of diastole [36]. In the context of this study, measurements on the fetuses were carried out postmortem on slaughterhouse materials. Therefore, the fetuses had developed different degrees of rigor mortis during the current measurements of a litter, so that a standardised estimation at the stage of maximum relaxed heart muscle was almost impossible. The validity of the measured heart length in this study is therefore limited due to the experimental design. The abdominal measurements (abdominal circumference, transversal and sagittal diameter) showed a clear linear progression over the entire gravity. As expected from a mathematical point of view, when a body grows exponentially, its dimensions and circumference increase almost linearly. For humans and animals, linear growth development for abdominal dimensions over pregnancy has been well described [4,14,21,23,29].
Conversely, the different growth curves of Figure 1 can also be used to estimate the stage of pregnancy when the mating date is unknown. In pigs, the gestation age is usually known due to targeted mating. However, estimating the stage of pregnancy could be of importance for free-range farms with a boar, or hobby farms. In human medicine, however, the determination of gestational age by the use of fetometry is an important part of gynaecological examination [1,14], and also has some significance for other animals [3,4,5,21].

4.2. Fetal Weight Calculation

The basis for weight calculation through biometry is a strong relationship between the fetal morphology considered and weight. The variety of different formulas that have been developed (in human medicine), as well as the constant revision of weight estimates, clearly show that there is no formula that satisfies the desire for an absolutely reliable weight estimate in all cases [37,38,39]. This is also confirmed by comparative studies [40,41].
For weight development of fetuses, the duration of gestation is an inevitably significant influencing factor. Some authors in human medical studies therefore consider the week of gestation in their equations for a more accurate estimation of fetal weight [38,40]. In pigs, since the time of insemination, and, therefore, the stage of gestation is known, an estimate of weight can be made as a function of the week of gestation. Our results showed that an estimation of the weight can be realised by the use of linear regressions at certain times of gestation. The measured parameters of the skull and abdomen proved to be particularly accurate, but with highly variable results. There was a tendency for a more accurate estimate to be possible as the gestation period progressed. Measurements of eyeball and heart length did not give satisfactory results. As explained above, this might be due to inconsistent growth [29] and changing shape [24] of the eyeball during pregnancy, and heart contraction (rigor mortis) during measurement.
However, the use of only one parameter or the use of linear models are unusual. Other authors have also attempted to describe relationships between body measurements and fetal weight in a limited period of time (period close to birth) using nonexponential equations, but have used combinations of different parameters to accomplish this [42,43,44,45,46]. As with these other authors, the accuracy of weight estimation can be increased by combining different parameters. In this study, combinations of head parameters and abdominal circumference have proven to be useful (BPD/ROD/AC or BPD/AC). It is also common in human medicine to use equations that combine head parameters and abdominal circumference for weight estimation [44,47], especially with a combination of BPD/AC often being suggested [41,42,43,44,46,47]. In addition, the measurement of femur length is often recommended for the improvement of weight estimation [45,46,47,48]. However, this can be difficult in practice with pigs, as the fetuses must be at a suitable angle to the transducer. Fetuses were measured at the 36th, 50th, 64th, 79th and 92nd day of gestation. Due to the experimental scheme, piglet weights partially overlapped between measurement times, resulting in a continuous data set on weight/fetus development over the gestation period. This was used to test formulas that allow weight estimation over the entire pregnancy. Our study showed that the parameters AC, ROD and BPD are suitable for this purpose. For weight estimation over the entire pregnancy, the following cubic equations were found: estimated fetal weight (EFW) = 0.077 (AC)3; or EFW = 1.199 (ROD)3; or EFW = 12.228 (BPD)3. In human medicine, simplified equations for weight estimation over pregnancy using only one parameter are found almost exclusively for AC [41,44,47,48,49,50]. These equations are all exponential (quadratic, cubic). In particular, the simplified formulas of Higginbottom et al. [50] (EFW = 0.0816 (AC)3) and Merz et al. [41] (EFW = 0.1 (AC)3) are very close to our results. The slightly lower factor of 0.077 could be because in the human fetus, the head is proportionally larger to the body than in the pig, and, therefore, the values for pigs have to be corrected downwards. The formulas we found for weight estimation over the entire pregnancy by the use of only ROD or BPD do not find equivalent examples in the literature. At best, the sole use of femur length in a polynomial model is described in humans [48]. Otherwise, polynomial formulas combining different parameters were also developed [1,14,40]. However, the estimation accuracy can be, but is not necessarily significantly increased by multivariable polynomial equations [40,41]. Therefore, simplified formulas might rather be used in veterinary practice. When using generally valid equations, it must be pointed out that some factors could potentially influence the precision of sonographic weight estimation [37], especially the weight of fetuses [38,41] and the sex [39] can have an impact on the accuracy of an equation. The extent to which the equations found can also be applied to other races is unclear and would have to be investigated in further studies. A requirement for the application of the equations presented is a similarity of body proportions to the German Landrace. In human obstetrics, it is not common to use ethnic-specific equations for fetal weight estimation, but weight estimation is considered inaccurate in malformed fetuses [1].
The transabdominal ultrasound examinations on live sows showed that the parameters of the abdomen could not be reliably determined. This is because the angle between the transducer and the fetus can only be changed and adjusted to a limited extent in pigs, and thus, the reference plane could not be displayed. The ROD and BPD, on the other hand, could be determined easily and reliably in living animals. These parameters could therefore find a simpler application, even if the formulas involving the AC achieved a higher estimation accuracy. The diameter of the eyeball, which could also be determined very reliably in living animals, cannot be recommended for weight determination according to our results, but models that look at the orbita or the interocular distance might be developed [24,32,33]. Heart length could also be reliably determined on the living animal, but in future studies, it will be necessary to perform the measurements during a desired period of the cardiac cycle [36] to develop appropriate formulas based on linear heart growth [32,34,35]. Through further development of ultrasound technology such as 3D scanning with downstream fetus measurement, the formulas presented that include parameters of the abdomen (AC, ASD, ATD) might also be applied in the future. This should make more precise estimates achievable.
In summary, our study shows that ultrasound-based morphological measurements of porcine fetuses are possible and thus can be used to monitor fetal growth through gestation or to estimate fetal weight. The biparietal distance, rostro-occipital distance and abdominal circumference have proven to be suitable parameters. Weight estimation can be performed with linear models at a known stage of gestation using one or a combination of several parameters. Cubic equations can describe the relationships between body measurements and weight across gestation. For monitoring fetal growth in live sows, it may be difficult to transfer the results directly because of the difficulty of identification of individual fetuses in longitudinal observations, and some variance in fetal weights within a litter. However, average values could be determined and used by measuring several fetuses in a sow or a group of sows. These techniques may initially be of interest for research into factors influencing fetal growth, but future use in veterinary practice is also conceivable. Further studies may also be needed for other races.

Author Contributions

Conceptualization, A.V. and K.-P.B.; formal analysis, A.V. and A.E.; investigation, A.V. and K.-P.B.; writing—original draft, A.V. and A.E.; writing—review & editing, A.E. and K.-P.B.; visualization, A.V. and A.E.; supervision, K.-P.B.; project administration, K.-P.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The datasets presented in this study can be found in the ZENODO online repository: DOI: 10.5281/zenodo.7431994, Publication date: 13 December 2022.

Acknowledgments

We would like to thank S. Baltzer for her support, who worked on the project as part of her Master’s thesis.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Benson, C.B.; Doubilet, P.M. Fetal biometry and growth. In Callen’s Ultrasonography in Obstetrics and Gynecology; Norton, M.E., Scoutt, L.M., Feldstein, V.A., Eds.; Elsevier: Philadelphia, PA, USA, 2017; Volume 6, pp. 118–131, Appendix A and B. [Google Scholar]
  2. Amer, H.A. Ultrasonographic assessment of early pregnancy diagnosis, fetometry and sex determination in goats. Anim. Reprod. Sci. 2010, 117, 226–231. [Google Scholar] [CrossRef] [PubMed]
  3. Beccaglia, M.; Alonge, S.; Trovo’, C.; Luvoni, G.C. Determination of gestational time and prediction of parturition in dogs and cats: An update. Reprod. Domest. Anim. 2016, 51, 12–17. [Google Scholar] [CrossRef] [PubMed]
  4. Gosselin, V.B.; Volkmann, D.H.; Dufour, S.; Middleton, J.R. Use of ultrasonographic fetometry for the estimation of days to kidding in dairy does. Theriogenology 2018, 118, 22–26. [Google Scholar] [CrossRef] [PubMed]
  5. Santiago-Moreno, J.; Gonzalez-Bulnes, A.; Gomez-Brunet, A.; Toledano-Diaz, A.; Lopez-Sebastian, A. Prediction of gestational age by transrectal ultrasonographic measurements in the mouflon (Ovis gmelini musimon). J. Zoo Wildl. Med. 2005, 36, 457–462. [Google Scholar] [CrossRef]
  6. Jones, A.K.; Reed, S.A. Benefits of ultrasound scanning during gestation in the small ruminant. Small Rumin. Res. 2017, 149, 163–171. [Google Scholar] [CrossRef]
  7. Kahn, W. Ultrasonography as a diagnostic-tool in female animal reproduction. Anim. Reprod. Sci. 1992, 28, 1–10. [Google Scholar] [CrossRef]
  8. Kauffold, J.; Peltoniemi, O.; Wehrend, A.; Althouse, G.C. Principles and Clinical Uses of Real-Time Ultrasonography in Female Swine Reproduction. Animals 2019, 9, 950. [Google Scholar] [CrossRef] [Green Version]
  9. Stenhouse, C.; Tennant, P.; Duncan, W.C.; Ashworth, C.J. Doppler ultrasound can be used to monitor umbilical arterial blood flow in lightly sedated pigs at multiple gestational ages. Reprod. Fertil. Dev. 2018, 30, 1402–1411. [Google Scholar] [CrossRef]
  10. Gonzalez-Bulnes, A.; Astiz, S.; Ovilo, C.; Lopez-Bote, C.J.; Sanchez-Sanchez, R.; Perez-Solana, M.L.; Torres-Rovira, L.; Ayuso, M.; Gonzalez, J. Early-postnatal changes in adiposity and lipids profile by transgenerational developmental programming in swine with obesity/leptin resistance. J. Endocrinol. 2014, 223, M17–M29. [Google Scholar] [CrossRef] [Green Version]
  11. Schild, S.L.A.; Foldager, L.; Rangstrup-Christensen, L.; Pedersen, L.J. Characteristics of Piglets Born by Two Highly Prolific Sow Hybrids. Front. Vet. Sci. 2020, 7, 355. [Google Scholar] [CrossRef]
  12. Gonzalez-Bulnes, A.; Parraguez, V.H.; Berlinguer, F.; Barbero, A.; Garcia-Contreras, C.; Lopez-Tello, J.; Pesantez-Pacheco, J.L.; Martinez-Ros, P. The impact of prenatal environment on postnatal life and performance: Future perspectives for prevention and treatment. Theriogenology 2020, 150, 15–19. [Google Scholar] [CrossRef] [PubMed]
  13. Vielwerth, S.E.; Jensen, R.B.; Larsen, T.; Holst, K.K.; Molgaard, C.; Greisen, G.; Vaag, A. The effect of birthweight upon insulin resistance and associated cardiovascular risk factors in adolescence is not explained by fetal growth velocity in the third trimester as measured by repeated ultrasound fetometry. Diabetologia 2008, 51, 1483–1492. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Merz, E. Biometrie des Fetus. In Sonografische Diagnostik in Gynaekologie und Geburtshilfe: Lehrbuch und Atlas; Merz, E., Ed.; Thieme: Stutgard, Germany; New York, NY, USA, 2002; Volume 2, pp. 139–167. [Google Scholar]
  15. Metzler-Zebeli, B.U.; Lang, I.S.; Görs, S.; Brüssow, K.-P.; Hennig, U.; Nürnberg, G.; Rehfeldt, C.; Otten, W.; Metges, C.C. High-protein–low-carbohydrate diet during pregnancy alters maternal plasma amino acid concentration and placental amino acid extraction but not fetal plasma amino acids in pigs. Br. J. Nutr. 2012, 108, 2176–2189. [Google Scholar] [CrossRef] [Green Version]
  16. Vernunft, A.; Maass, M.; Brussow, K.P. Placental Characteristics of German Landrace Sows and Their Relationships to Different Fertility Parameters. Czech J. Anim. Sci. 2018, 63, 339–346. [Google Scholar]
  17. Vernunft, A.; Ivell, R.; Heng, K.; Anand-Ivell, R. The Male Fetal Biomarker INSL3 Reveals Substantial Hormone Exchange between Fetuses in Early Pig Gestation. PLoS ONE 2016, 11, e0152689. [Google Scholar]
  18. R-Core-Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria; Available online: https://www.R-project.org/ (accessed on 16 November 2022).
  19. Wickham, H.; Averick, M.; Bryan, J.; Chang, W.; McGowan, L.D.; François, R.; Grolemund, G.; Hayes, A.; Henry, L.; Hester, J.; et al. Welcome to the Tidyverse. J. Open Source Softw. 2019, 43, 1689. [Google Scholar] [CrossRef] [Green Version]
  20. Bates, D.; Machler, M.; Bolker, B.M.; Walker, S.C. Fitting Linear Mixed-Effects Models Using lme4. J. Stat. Softw. 2015, 67, 1–48. [Google Scholar] [CrossRef]
  21. Cecchetto, M.; Milani, C.; Vencato, J.; Sontas, H.; Mollo, A.; Contiero, B.; Romagnoli, S. Clinical use of fetal measurements to determine the whelping day in German shepherd breed bitches. Anim. Reprod. Sci. 2017, 184, 110–119. [Google Scholar] [CrossRef]
  22. Riding, G.A.; Lehnert, S.A.; French, A.J.; Hill, J.R. Conceptus-related measurements during the first trimester of bovine pregnancy. Vet. J. 2008, 175, 266–272. [Google Scholar] [CrossRef]
  23. Ali, A.; Fahmy, S. Ultrasonographic fetometry and determination of fetal sex in buffaloes (Bubalus bubalis). Anim. Reprod. Sci. 2008, 106, 90–99. [Google Scholar] [CrossRef]
  24. Murase, H.; Endo, Y.; Tsuchiya, T.; Kotoyori, Y.; Shikichi, M.; Ito, K.; Sato, F.; Nambo, Y. Ultrasonographic Evaluation of Equine Fetal Growth Throughout Gestation in Normal Mares Using a Convex Transducer. J. Vet. Med. Sci. 2014, 76, 947–953. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Kim, S.W. Recent advances in sow nutrition. Rev. Bras. Zootec. 2010, 39, 303–310. [Google Scholar] [CrossRef]
  26. McPherson, R.L.; Ji, F.; Wu, G.; Blanton, J.R.; Kim, S.W. Growth and compositional changes of fetal tissues in pigs. J. Anim. Sci. 2004, 82, 2534–2540. [Google Scholar] [CrossRef] [PubMed]
  27. Pontelo, T.P.; Miranda, J.R.; Felix, M.A.R.; Pereira, B.A.; da Silva, W.E.; Avelar, G.F.; Mariano, F.C.M.Q.; Guimarães, G.C.; Zangeronimo, M.G. Histological characteristics of the gonads of pig fetuses and their relationship with fetal anatomical measurements. Res. Vet. Sci. 2018, 117, 28–36. [Google Scholar] [CrossRef] [PubMed]
  28. Harris, E.K.; Berg, E.P.; Berg, E.L.; Vonnahme, K.A. Effect of maternal activity during gestation on maternal behavior, fetal growth, umbilical blood flow, and farrowing characteristics in pigs. J. Anim. Sci. 2013, 91, 734–744. [Google Scholar] [CrossRef] [PubMed]
  29. Kahn, W. Sonographic Fetometry in the Bovine. Theriogenology 1989, 31, 1105–1121. [Google Scholar] [CrossRef]
  30. Ali, A.; Al-Sobayil, F.; Derar, R.; El-Tookhy, O. Ultrasonographic fetometry and prenatal fetal sex assessment in camels (Camelus dromedarius). Theriogenology 2013, 80, 609–618. [Google Scholar] [CrossRef]
  31. Evans, H.E.; Sack, W.O. Prenatal Development of Domestic and Laboratory Mammals: Growth Curves, External Features and Selected References. Anat. Histol. Embryol. 1973, 2, 11–45. [Google Scholar] [CrossRef]
  32. Frauenholz, J.; Kähn, W.L.W. Sonogrophy for Pregnancy diagnosis in Swine—Comparison between transrectal and transcutaneous procedures. Mh. Vet.-Med. 1989, 44, 425–430. [Google Scholar]
  33. Merz, E.; Wellek, S.; Püttmann, S.; Bahlmann, F.; Weber, G. Orbital Diameter, Interorbital and Biocular Diameters—A Growth Model for Fetal Orbital Parameters. Ultraschall Med. 1995, 16, 12–17. [Google Scholar] [CrossRef]
  34. Chaoui, R.; Heling, K.S.; Bollmann, R. Sonographical Fetal Cardiac Measurements Performed in the 4-Chamber-View Plane. Geburtshilfe Frauenheilkd. 1994, 54, 92–97. [Google Scholar] [CrossRef] [PubMed]
  35. Lampl, M.; Kuzawa, C.W.; Jeanty, P. Growth patterns of the heart and kidney suggest inter-organ collaboration in facultative fetal growth. Am. J. Hum. Biol. 2005, 17, 178–194. [Google Scholar] [CrossRef] [PubMed]
  36. Smrcek, J.M.; Berg, C.; Geipel, A.; Fimmers, R.; Diedrich, K.; Gembruch, U. Early fetal echocardiography—Heart biometry and visualization of cardiac structures between 10 and 15 weeks’ gestation. J. Ultrasound Med. 2006, 25, 173–182. [Google Scholar] [CrossRef] [PubMed]
  37. Heer, I.M.; Kümper, C.; Vögtle, N.; Müller-Egloff, S.; Dugas, M.; Strauss, A. Analysis of Factors Influencing the Ultrasonic Fetal Weight Estimation. Fetal Diagn. Ther. 2008, 23, 204–210. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Sabbagha, R.E.; Minogue, J.; Tamura, R.K.; Hungerford, S.A. Estimation of birth weight by use of ultrasonographic formulas targeted to large-, appropriate-, and small-for-gestational-age fetuses. Am. J. Obstet. Gynecol. 1989, 160, 854–862. [Google Scholar] [CrossRef]
  39. Siemer, J.; Hilbert, A.; Wolf, T.; Hart, N.; Muller, A.; Schild, R.L. Gender-specific weight estimation of fetuses between 2,501 and 3,999 g—New regression formulae. Fetal Diagn. Ther. 2008, 24, 304–309. [Google Scholar] [CrossRef] [PubMed]
  40. Barel, O.; Vaknin, Z.; Tovbin, J.; Herman, A.; Maymon, R. Assessment of the Accuracy of Multiple Sonographic Fetal Weight Estimation Formulas. J. Ultrasound Med. 2013, 32, 815–823. [Google Scholar] [CrossRef]
  41. Merz, E.; Lieser, H.; Schicketanz, K.H.; Harle, J. Predicting fetal weight by ultrasound. Ultraschall Med. 1988, 9, 15–24. [Google Scholar] [CrossRef]
  42. Shepard, M.J.; Richards, V.A.; Berkowitz, R.L.; Warsof, S.L.; Hobbins, J.C. An evaluation of 2 equations for predicting fetal weight by ultrasound. Am. J. Obstet. Gynecol. 1982, 142, 47–54. [Google Scholar] [CrossRef]
  43. Vintzileos, A.M.; Campbell, W.A.; Rodis, J.F.; Borskoefoed, R.; Nochimson, D.J. Fetal weight estimation formulas with head, abdominal, femur, and thigh circumference measurements. Am. J. Obstet. Gynecol. 1987, 157, 410–414. [Google Scholar] [CrossRef]
  44. Jordaan, H.V.F. Estimation of fetal weight by ultrasound. J. Clin. Ultrasound 1983, 11, 59–66. [Google Scholar] [CrossRef] [PubMed]
  45. Hadlock, F.P.; Harrist, R.B.; Sharman, R.S.; Deter, R.L.; Park, S.K. Estimation of fetal weight with the use of head, body, and femur measurements—A prospective-study. Am. J. Obstet. Gynecol. 1985, 151, 333–337. [Google Scholar] [CrossRef] [PubMed]
  46. Woo, J.S.K.; Wan, C.W.; Cho, K.M. Computer-Assisted Evaluation of Ultrasonic Fetal Weight Prediction Using Multiple-Regression Equations with and without the Fetal Femur Length. J. Ultrasound Med. 1985, 4, 65–67. [Google Scholar] [CrossRef] [PubMed]
  47. Hadlock, F.P.; Harrist, R.B.; Carpenter, R.J.; Deter, R.L.; Park, S.K. Sonographic estimation of fetal weight—The value of femur length in addition to head and abdomen measurements. Radiology 1984, 150, 535–540. [Google Scholar] [CrossRef] [PubMed]
  48. Warsof, S.L.; Wolf, P.; Coulehan, J.; Queenan, J.T. Comparison of fetal weight estimation formulas with and without head measurements. Obstet. Gynecol. 1986, 67, 569–573. [Google Scholar]
  49. Campbell, S.; Wilkin, D. Ultrasonic measurement of fetal abdomen circumference in estimation of fetal weight. Br. J. Obstet. Gynaecol. 1975, 82, 689–697. [Google Scholar] [CrossRef]
  50. Higginbottom, J.; Slater, J.; Porter, G.; Whitfield, C.R. Estimation of fetal weight from ultrasonic measurement of trunk circumference. Br. J. Obstet. Gynaecol. 1975, 82, 698–701. [Google Scholar] [CrossRef]
Agriculture 13 00016 g001 550
Figure 1. Demonstration of the investigated morphometric fetal parameters in ultrasound (yellow dotted lines, distance (D) between calipers (+)) and corresponding real cross-sectional images (yellow dotted lines). From top to bottom: rostro-occipital distance (ROD), biparietal distance (BPD), corpus vitreum diameter (CVD), abdominal circumference (AC) with abdominal transversal and sagittal diameter (ATD, ASD), heart length (HL).
Figure 1. Demonstration of the investigated morphometric fetal parameters in ultrasound (yellow dotted lines, distance (D) between calipers (+)) and corresponding real cross-sectional images (yellow dotted lines). From top to bottom: rostro-occipital distance (ROD), biparietal distance (BPD), corpus vitreum diameter (CVD), abdominal circumference (AC) with abdominal transversal and sagittal diameter (ATD, ASD), heart length (HL).
Agriculture 13 00016 g001
Agriculture 13 00016 g002 550
Figure 2. Development of fetal weight and monitored anatomical structures during pregnancy. Shown are smooth Loess curves of temporal development of the median (solid line) and the 5% and 95% percentiles (dashed lines) of the investigated parameters from the 36th to the 92nd day of pregnancy.
Figure 2. Development of fetal weight and monitored anatomical structures during pregnancy. Shown are smooth Loess curves of temporal development of the median (solid line) and the 5% and 95% percentiles (dashed lines) of the investigated parameters from the 36th to the 92nd day of pregnancy.
Agriculture 13 00016 g002
Agriculture 13 00016 g003 550
Figure 3. Relationships between examined morphological parameters and fetal weight. Shown are the individual measurements (dots) and the different colours indicate the five investigated time points of pregnancy (36, 50, 64, 79 and 92 days of pregnancy). Separate linear regression models were fitted at each day of pregnancy. Fitted linear regression lines (solid lines) and 95% prediction bands (dashed lines) are shown. Estimated parameters of the linear regression model are given in Table 1.
Figure 3. Relationships between examined morphological parameters and fetal weight. Shown are the individual measurements (dots) and the different colours indicate the five investigated time points of pregnancy (36, 50, 64, 79 and 92 days of pregnancy). Separate linear regression models were fitted at each day of pregnancy. Fitted linear regression lines (solid lines) and 95% prediction bands (dashed lines) are shown. Estimated parameters of the linear regression model are given in Table 1.
Agriculture 13 00016 g003
Agriculture 13 00016 g004 550
Figure 4. Estimated fetal weight (EFW) over the entire gestation using a cubic function ( y = a · x 3 ). Nonlinear, least squares regression models were fitted for the morphometric parameters abdominal circumference, biparietal distance and rostro-occipital distance. Shown are the individual measurements and the different colours indicate the five investigated time points of pregnancy (36, 50, 64, 79 and 92 days of pregnancy). Fitted nonlinear regression lines (solid lines) and the 95% prediction intervals (grey shadow) are shown. For each parameter, estimated parameters and residual standard errors (RSE) are given.
Figure 4. Estimated fetal weight (EFW) over the entire gestation using a cubic function ( y = a · x 3 ). Nonlinear, least squares regression models were fitted for the morphometric parameters abdominal circumference, biparietal distance and rostro-occipital distance. Shown are the individual measurements and the different colours indicate the five investigated time points of pregnancy (36, 50, 64, 79 and 92 days of pregnancy). Fitted nonlinear regression lines (solid lines) and the 95% prediction intervals (grey shadow) are shown. For each parameter, estimated parameters and residual standard errors (RSE) are given.
Agriculture 13 00016 g004
Table
Table 1. Estimation of fetal weight (EFW, in grams) using linear regression models individually for all examined morphological parameters and days of pregnancy (PD) (supplementary to Figure 3).
Table 1. Estimation of fetal weight (EFW, in grams) using linear regression models individually for all examined morphological parameters and days of pregnancy (PD) (supplementary to Figure 3).
Morphometric ParametersPregnancy DayR2p ValueFetal Weight Calculation
rostro-occipital distance360.37<0.001EFWPD36 = −0.28 + 2.79·RODcm
(ROD)500.200.002EFWPD50 = −7.15 + 14.69·RODcm
640.160.023EFWPD64 = −74.30 + 48.28·RODcm
790.71<0.001EFWPD79 = −1408.91 + 260.54·RODcm
920.47<0.001EFWPD92 = −1725.21 + 291.47·RODcm
biparietal distance360.30<0.001EFWPD36 = −0.34 + 5.52·BPDcm
(BPD)500.29<0.001EFWPD50 = −31.10 + 41.90·BPDcm
640.240.004EFWPD64 = −187.98 + 136.08·BPDcm
790.130.027EFWPD79 = −343.57 + 231.10·BPDcm
920.210.003EFWPD92 = −206.23 + 232.26·BPDcm
corpus vitreum diameter36<0.010.918EFWPD36 = 4.24 + 0.28·CVDcm
(CVD)50<0.010.968EFWPD50 = 41.94 − 0.55·CVDcm
64<0.010.967EFWPD64 = 172.53 + 2.22·CVDcm
790.080.086EFWPD79 = 136.37 + 218.43·CVDcm
920.110.034EFWPD92 = 229.45 + 326.58·CVDcm
abdominal circumference360.46<0.001EFWPD36 = −1.47 + 1.17·ACcm
(AC)500.73<0.001EFWPD50 = −30.90 + 8.36·ACcm
640.63<0.001EFWPD64 = −220.28 + 30.19·ACcm
790.85<0.001EFWPD79 = −571.91 + 57.18·ACcm
920.74<0.001EFWPD92 = −898.74 + 76.35·ACcm
abdominal sagittal diameter360.29<0.001EFWPD36 = 0.38 + 2.41·ASDcm
(ASD)500.62<0.001EFWPD50 = −34.07 + 25.38·ASDcm
640.46<0.001EFWPD64 = −75.94 + 55.82·ASDcm
790.80<0.001EFWPD79 = −514.31 + 163.48·ASDcm
920.57<0.001EFWPD92 = −497.12 + 173.33·ASDcm
abdominal transversal diameter360.34<0.001EFWPD36 = −0.12 + 3.02·ATDcm
(ATD)500.42<0.001EFWPD50 = 3.49 + 15.80·ATDcm
640.030.351EFWPD64 = 121.46 + 14.71·ATDcm
790.61<0.001EFWPD79 = −382.70 + 158.47·ATDcm
920.37<0.001EFWPD92 = −55.26 + 123.00·ATDcm
heart length36<0.010.714EFWPD36 = 4.03 + 0.38·HLcm
(HL)500.030.314EFWPD50 = 32.02 + 8.31·HLcm
640.38<0.001EFWPD64 = 41.87 + 64.16·HLcm
790.51<0.001EFWPD79 = −401.49 + 367.64·HLcm
920.190.005EFWPD92 = −70.90 + 270.60·HLcm
Table
Table 2. Type II ANOVA table of fixed effects of a linear mixed model testing for effects of all measured morphometric parameters, including day of pregnancy on fetal weight (Num DF = number of degrees of freedom; Den DF = denominator degrees of freedom).
Table 2. Type II ANOVA table of fixed effects of a linear mixed model testing for effects of all measured morphometric parameters, including day of pregnancy on fetal weight (Num DF = number of degrees of freedom; Den DF = denominator degrees of freedom).
Fixed EffectsSum of SquaresNum DFDen DFF Valuep Value
abdominal circumference (AC)0.1641174.227.76<0.0001
biparietal distance (BPD)0.1251174.621.17<0.0001
rostro-occipital distance (ROD)0.0821174.313.910.0003
abdominal sagittal diameter (ASD)0.0331174.15.540.0197
heart length (HL)0.0271175.34.510.0352
corpus vitreum diameter (CVD)0.0021175.50.410.5249
abdominal transversal diameter (ATD)0.0021175.30.390.5339
pregnancy day (PD)0.090125.315.240.0006
Table
Table 3. Best estimates of fetal weight (EFW, in grams) using multiple linear regression models with either three or two independent morphometric parameters (rostro-occipital distance (ROD), biparietal distance (BPD), abdominal circumference (AC)) on different pregnancy days (PD).
Table 3. Best estimates of fetal weight (EFW, in grams) using multiple linear regression models with either three or two independent morphometric parameters (rostro-occipital distance (ROD), biparietal distance (BPD), abdominal circumference (AC)) on different pregnancy days (PD).
Pregnancy DayMorphometric Parameters R a d j . 2 Estimated Fetal Weight
36BPD | ROD | AC0.58EFWPD36 = −3.71 + 2.58·BPDcm + 1.19·RODcm + 0.80·ACcm
BPD | AC0.55EFWPD36 = −3.37 + 3.56·BPDcm + 0.95·ACcm
50BPD | ROD | AC0.75EFWPD50 = −56.90 + 10.00·BPDcm+ 6.00·RODcm + 7.06·ACcm
BPD | AC0.73EFWPD50 = −41.51 + 9.22·BPDcm + 7.74·ACcm
64BPD | ROD | AC0.76EFWPD64 = −538.14 + 88.19·BPDcm + 28.58·RODcm + 25.23·ACcm
BPD | AC0.71EFWPD64 = −414.79 + 87.51·BPDcm + 27.22·ACcm
79BPD | ROD | AC0.89EFWPD79 = −1161.31 + 71.36·BPDcm + 91.29·RODcm + 41.20·ACcm
BPD | AC0.86EFWPD79 = −814.98 + 87.88·BPDcm + 54.97·ACcm
92BPD | ROD | AC0.83EFWPD92 = −1837.48 + 115.79·BPDcm + 107.89·RODcm + 58.32·ACcm
BPD | AC0.79EFWPD92 = −1262.13 + 130.23·BPDcm + 70.66·ACcm
Table
Table 4. Results of the feasibility test for transabdominal measurement of the investigated morphometric fetal parameters on live sows in the barn. The fetuses were visualised during ultrasonographic examination one day before the slaughter time points. Each cross represents the successful measurement of a fetal parameter in one of the three sows on a specific gestation day.
Table 4. Results of the feasibility test for transabdominal measurement of the investigated morphometric fetal parameters on live sows in the barn. The fetuses were visualised during ultrasonographic examination one day before the slaughter time points. Each cross represents the successful measurement of a fetal parameter in one of the three sows on a specific gestation day.
ParameterPregnancy Day
3549637891
RODxxxxxxxxxxxxxx
BPD xxxxxxxxxxxx
CVDxxxxxxxxxxxxxx
ACxxxx xxx
ASDxx xxx
ATDxx xxx
HLxxxxxxxxxxx
(Measurement on at least one fetus possible in 1/3 sows (x); 2/3 sows (xx) or 3/3 sows (xxx)); (ROD: rostro-occipital distance, BPD: biparietal distance, CVD: corpus vitreum diameter, AC: abdominal circumference, ASD: abdominal sagittal diameter, ATD: abdominal transversal diameter, HL: heart length).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Vernunft, A.; Eggert, A.; Brüssow, K.-P. Ultrasonographic Monitoring of Fetal Growth and Fetal Weight Calculation in Sows during Gestation. Agriculture 2023, 13, 16. https://doi.org/10.3390/agriculture13010016

AMA Style

Vernunft A, Eggert A, Brüssow K-P. Ultrasonographic Monitoring of Fetal Growth and Fetal Weight Calculation in Sows during Gestation. Agriculture. 2023; 13(1):16. https://doi.org/10.3390/agriculture13010016

Chicago/Turabian Style

Vernunft, Andreas, Anja Eggert, and Klaus-Peter Brüssow. 2023. "Ultrasonographic Monitoring of Fetal Growth and Fetal Weight Calculation in Sows during Gestation" Agriculture 13, no. 1: 16. https://doi.org/10.3390/agriculture13010016

APA Style

Vernunft, A., Eggert, A., & Brüssow, K.-P. (2023). Ultrasonographic Monitoring of Fetal Growth and Fetal Weight Calculation in Sows during Gestation. Agriculture, 13(1), 16. https://doi.org/10.3390/agriculture13010016

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop