Estimation of fetal lung development using quantitative analysis of ultrasonographic images in normal canine pregnancy

Preliminary Evaluation of Cortical and Medullary Echogenicity in Normal Canine Fetal Kidneys during the Last 10 Days of Pregnancy

The objective of this study was to assess changes in the echogenicity of the cortex and medulla of canine fetal kidneys in relation to days before parturition (dbp), maternal size and litter size. Monitoring of 10 healthy pregnant bitches (2-8 years old, 8.8-40.3 kg bw) was conducted from -10 to 0 dbp using ultrasound. A single renal sonogram was obtained by scanning in a longitudinal section the three most caudal fetuses. The mean gray level (MGL) and SD of a manually drawn region of interest (ROI) in the renal cortex and medulla were measured using the Fiji Image J software (Image J 1.51h, Java 1.6 0_24 64 bit). A linear mixed model taking into account the maternal size as a fixed effect, dbp and litter size as covariates and the bitch as a random and repeated effect was used. The regression coefficients (b) were estimated. Cortical SD (C-SD) and cortico-medullary SD (C/M-SD) were influenced by dbp, with a significant decrease at the approaching day of parturition (b = 0.23 ± 0.06, p < 0.001 and b = 0.5 ± 0.02, p = 0.038, respectively). Maternal size had a significant impact on C/M-MGL with differences observed in large-sized (1.95 ± 0.13) compared to small- (1.41 ± 0.10, p = 0.027) and medium-sized bitches (1.51 ± 0.09, p = 0.016). The C/M-MGL was influenced by litter size, showing a decrease as the number of pups increased (b = -0.08 ± 0.03, p = 0.018). C-SD and C/M-SD were exclusively affected by dbp, and not by maternal and litter size. This suggests their potential as valuable parameters, warranting further investigations in future studies.

Biochemical factors affecting newborn survival in dogs and cats

The importance and implications of small animal neonatology were underestimated until recent times. Despite the recent increasing interest for this branch of veterinary medicine, however, perinatal mortality rates in canine and feline species remain high, representing an important challenge for the clinician. In this perspective, the prompt identification of newborns requiring additional and tailored assistance becomes a key to reduce the perinatal losses in small animals. To achieve this goal, clinical and laboratory findings must be carefully evaluated. This paper focuses on biochemical parameters and their reported influence on neonatal survival, guiding through the evaluation of canine and feline newborn laboratory analyses, with a thorough discussion about the use of different biological material in these subjects. Beside blood, other biological material, such as urines and fetal fluids proved to be interesting for the identification of possible prognostic markers, thanks also to their easy and safe collection. However, the correct reading-through the results must consider many variables such as type of delivery, anesthesia protocol in case of Caesarean section, age of the newborn at samples collection, and for blood analysis, also the type of blood, site of collection, modality of collection and storage must be considered. Notwithstanding the recent progress in literature, for most of the parameters more research is needed to define cut-off values with certainty.

Use of a Point-of-Care Progesterone Assay to Predict Onset of Parturition in the Bitch

An assay of circulating progesterone (P4) is commonly used to estimate progress through late gestation in the bitch. Point-of-care assays provide rapid results, a major advantage over laboratory-based assays. This study aims to compare P4 levels determined by the Catalyst® Progesterone point-of-care assay with those determined by chemiluminescent immunoassay (CLIA) and to identify the expected distribution of Catalyst P4 levels at time intervals 3 days prior to the onset of parturition in pregnant bitches. Twenty-eight pregnant bitches carrying two or more fetuses were admitted to a specialist veterinary reproduction hospital 53 days after the onset of cytological diestrus or, when that date was not known, 57 days after the last mating. Vaginal speculum examinations were performed every 6 h until the onset of cervical dilatation (TCD). Serum samples were collected twice daily (08h00 and 18h00) until TCD. For most samples, fresh serum was assayed for P4 immediately using the Catalyst assay (CatP4), then frozen until assayed by CLIA (IMMULITE 2000; ImmP4). However, for some samples, CatP4 was not analyzed prior to freezing. For these data points (n = 33), CatP4 for fresh serum was estimated from CatP4 assayed on frozen-thawed serum, based on a comparison between CatP4 on fresh vs. frozen-thawed sera. In comparison to ImmP4, CatP4 levels up to and including 7 nmol/L appear to have a constant bias of −1.69 nmol/L (limits of agreement −4.91 to 1.52), while levels &gt;7 nmol/L appear to have a proportional bias of −17.9% (limits of agreement −68.6% to 32.7%). Bootstrapped percentiles of CatP4 results spanned 0.4–9 nmol/L within 12 h of TCD, 0.9–11 nmol/L 12–24 h from TCD, and 2.2–13.5 nmol/L 24–36 h from TCD. A CatP4 &gt;9 nmol/L indicates a bitch that is unlikely to reach TCD within 12 h. Bitches with CatP4s below 3.5 nmol/L are likely to reach TCD within 36 h and bitches with a CatP4 below 2.2 nmol/L are likely to reach TCD within 24 h. In conclusion, the Catalyst Progesterone assay provides rapid assessment of circulating P4 in the bitch, with clinical application in the monitoring of late term pregnant bitches.

The use of serum progesterone and prostaglandin F2α metabolite levels to predict onset of parturition in the bitch

The prediction of time to onset of parturition in a preparturient bitch is of great clinical value, particularly for bitches at high risk of dystocia and those lacking relevant clinical data from the time of breeding. In a previous study, four cut-offs for plasma progesterone levels, measured by radioimmunoassay, were shown to be useful for predicting the likelihood of a bitch entering stage one of parturition within defined time intervals. The first aim of the current study was to evaluate these cut-offs in a clinical setting, using serum progesterone samples drawn from preparturient bitches 12-hourly instead of 6-hourly and assessed using chemiluminescence immunoassay. Furthermore, the use of 13,14-dihydro-15-keto-prostaglandin F_2α, (PGFM), a metabolite of prostaglandin F_2α , in predicting the time to onset of parturition was evaluated. Forty bitches carrying two or more foetuses were admitted to a specialist veterinary reproduction hospital 53 d after the onset of cytological dioestrus when that date was known, or 57 d after the last mating. Vaginal speculum examinations were performed every 6 h until cervical dilatation was visualised (time of cervical dilatation; TCD). Serum samples were collected at 08h00 and 18h00 daily until TCD. All bitches underwent elective caesarean section at TCD. Results of this study show that approximately 5% and 10% of preparturient bitches will reach TCD within 12 h despite a serum progesterone level of at least 15.8 nmol/L and 8.7 nmol/L respectively. In addition, there is a 95% probability that a preparturient bitch will reach TCD within 48 h if her serum progesterone level is below 8.7 nmol/L, and a 91% probability of her reaching TCD within 24 h if her serum progesterone level is below 3.18 nmol/L. Around 90% of bitches that demonstrate a 20% increase in PGFM over a 12-hour period are likely to be within 36 h of TCD. These results provide useful benchmarks for the management of canine parturition.

Fetal Lung Echo Texture in Pregnancies at Risk for Pulmonary Hypoplasia

Pulmonary hypoplasia is associated with severe respiratory distress immediately after birth and frequently leads to neonatal death. In this study, we compared the fetal lung echo texture in pregnancies at high and low risk for pulmonary hypoplasia. Ultrasonic tissue heterogeneity was determined by a dynamic range calculation. This quantification uses a dithering technique based on the Floyd-Steinberg algorithm, in which the pixels are transformed into a binary map. Pregnancies at high risk for pulmonary hypoplasia showed decreased fetal lung heterogeneity on ultrasound imaging. This image-processing technique may allow improved risk stratification, patient counseling, and treatment approaches for pulmonary hypoplasia.

Usefulness of Maternal and Fetal Parameters for the Prediction of Parturition Date in Dogs

An accurate parturition timing is of key importance for breeders and veterinarians in order to give professional assistance to parturition in dogs. However, pregnancy length calculated from the breeding date has a wide variability. Different parameters and formulas have been described and calculated, as well as their accuracy which is affected by various factors: stage of pregnancy, litter and maternal size. Therefore, the selection of the most appropriate parameter panel poses the challenge of weighing their influences and impact on the overall accuracy. The aim of this review is to analyze the parameters useful for parturition timing, especially their accuracy, and to propose the addition of fetal maturity and criteria for its evaluation to detect readiness for parturition. Parameters, as described in literature, are classified as: (i) maternal parameters, (ii) fetal parameters, (iii) ultrasonographic assessment of maternal and fetal heart rate and blood flow, (iv) parameters indicating fetal maturity. A focus on recently described parameters-such as fetal gastrointestinal motility and fetal lung development detected by quantitative ultrasound-is reported. Currently, the most accurate way to predict parturition day is represented by a prepartum progesterone drop, but the identification of a panel of ultrasonographic parameters combining their significance and their accuracy throughout pregnancy is still needed.

Diagnostic Accuracy of Delayed Phase Post Contrast Computed Tomographic Images in the Diagnosis of Focal Liver Lesions in Dogs: 69 Cases

To describe the computed tomographic (CT) features of focal liver lesions (FLLs) in dogs, that could enable predicting lesion histotype. Dogs diagnosed with FLLs through both CT and cytopathology and/or histopathology were retrospectively collected. Ten qualitative and 6 quantitative CT features have been described for each case. Lastly, a machine learning-based decision tree was developed to predict the lesion histotype. Four categories of FLLs - hepatocellular carcinoma (HCC, n = 13), nodular hyperplasia (NH, n = 19), other benign lesions (OBL, n = 18), and other malignant lesions (OML, n = 19) - were evaluated in 69 dogs. Five of the observed qualitative CT features resulted to be statistically significant in the distinction between the 4 categories: surface, appearance, lymph-node appearance, capsule formation, and homogeneity of contrast medium distribution. Three of the observed quantitative CT features were significantly different between the 4 categories: the Hounsfield Units (HU) of the radiologically normal liver parenchyma during the pre-contrast scan, the maximum dimension, and the ellipsoid volume of the lesion. Using the machine learning-based decision tree, it was possible to correctly classify NHs, OBLs, HCCs, and OMLs with an accuracy of 0.74, 0.88, 0.87, and 0.75, respectively. The developed decision tree could be an easy-to-use tool to predict the histotype of different FLLs in dogs. Cytology and histology are necessary to obtain the final diagnosis of the lesions.

Use of deep learning to detect cardiomegaly on thoracic radiographs in dogs

The purpose of this study was to develop a computer-aided detection (CAD) device based on convolutional neural networks (CNNs) to detect cardiomegaly from plain radiographs in dogs. Right lateral chest radiographs (n = 1465) were retrospectively selected from archives. The radiographs were classified as having a normal cardiac silhouette (No-vertebral heart scale [VHS]-Cardiomegaly) or an enlarged cardiac silhouette (VHS-Cardiomegaly) based on the breed-specific VHS. The database was divided into a training set (1153 images) and a test set (315 images). The diagnostic accuracy of four different CNN models in the detection of cardiomegaly was calculated using the test set. All tested models had an area under the curve >0.9, demonstrating high diagnostic accuracy. There was a statistically significant difference between Model C and the remainder models (Model A vs. Model C, P = 0.0298; Model B vs. Model C, P = 0.003; Model C vs. Model D, P = 0.0018), but there were no significant differences between other combinations of models (Model A vs. Model B, P = 0.395; Model A vs. Model D, P = 0.128; Model B vs. Model D, P = 0.373). Convolutional neural networks could therefore assist veterinarians in detecting cardiomegaly in dogs from plain radiographs.

A methodological approach for deep learning to distinguish between meningiomas and gliomas on canine MR-images

Background

Distinguishing between meningeal-based and intra-axial lesions by means of magnetic resonance (MR) imaging findings may occasionally be challenging. Meningiomas and gliomas account for most of the total primary brain neoplasms in dogs, and differentiating between these two forms is mandatory in choosing the correct therapy. The aims of the present study are: 1) to determine the accuracy of a deep convolutional neural network (CNN, GoogleNet) in discriminating between meningiomas and gliomas in pre- and post-contrast T1 images and T2 images; 2) to develop an image classifier, based on the combination of CNN and MRI sequence displaying the highest accuracy, to predict whether a lesion is a meningioma or a glioma.

Results

Eighty cases with a final diagnosis of meningioma (n = 56) and glioma (n = 24) from two different institutions were included in the study. A pre-trained CNN was retrained on our data through a process called transfer learning. To evaluate CNN accuracy in the different imaging sequences, the dataset was divided into a training, a validation and a test set. The accuracy of the CNN was calculated on the test set. The combination between post-contrast T1 images and CNN was chosen in developing the image classifier (trCNN). Ten images from challenging cases were excluded from the database in order to test trCNN accuracy; the trCNN was trained on the remainder of the dataset of post-contrast T1 images, and correctly classified all the selected images. To compensate for the imbalance between meningiomas and gliomas in the dataset, the Matthews correlation coefficient (MCC) was also calculated. The trCNN showed an accuracy of 94% (MCC = 0.88) on post-contrast T1 images, 91% (MCC = 0.81) on pre-contrast T1-images and 90% (MCC = 0.8) on T2 images.

Conclusions

The developed trCNN could be a reliable tool in distinguishing between different meningiomas and gliomas from MR images.

Elastographic and echotextural characteristics of foetal lungs and liver during the final 5 days of intrauterine development in dogs

Objective was to evaluate the echotexture and characteristics during terminal development of canine foetal respiratory and hepatic systems through elastographic examinations. Fifteen pregnant bitches were evaluated by ultrasonography twice daily, from the 53rd gestational day until whelping, and images obtained from 120 to 0 h before parturition were analysed. Images of foetal lungs and liver were recorded and then used for computer-assisted analyses to determine quantitative attributes. Acoustic Radiation Force Impulse (ARFI) elastographic of internal organs were classified as 'soft' (white areas) or 'hard' (dark areas) and quantitative analyses determined the mean shear wave velocities (SWV) of foetal lungs and liver. After delivery, canine neonates were clinically evaluated, and their health status was monitored weekly until 60 days post-partum. Sonographic parameters over time were compared by ANOVA and Pearson's correlations were used to determine associations between SWVs and echotextural variables. Foetal lungs and liver had a homogeneous echotexture and pulmonary parenchyma appeared hyperechoic when compared with that of the liver. Mean numerical pixel values (NPVs) of lungs decreased from 120 to 24 h and subsequently increased until parturition (P = 0.04). Lungs and liver mean (± SD) SWVs (0.98 ± 0.12 and 0.84 ± 0.11 m/s, respectively) didn't vary (P >  0.05) over time. Fluctuations in pulmonary NPVs indicated there was a pattern corresponding to structural and functional changes that occur during the terminal stage of pre-natal canine development and hence can be a useful diagnostic tool in veterinary. Foetal lung and liver SWVs were relatively consistent and there was no detectable changes during the pre-partum period for this variable or in echotexture.

Qualitative and quantitative ultrasound attributes of maternal-foetal structures in pregnant ewes

The aim of this study was to examine foetal organs and placental tissue to establish a correlation between the changes in the composition of these structures associated with their maturation and the ultrasonographic characteristics of the images. Twenty-four pregnant ewes were included in the study. Ultrasonography assessments were performed in B-mode, from the ninth gestational week until parturition. The lungs, liver and kidneys of foetuses and placentomes were located in transverse and longitudinal sections to evaluate the echogenicity (hypoechoic, isoechoic, hyperechoic or mixed) and echotexture (homogeneous and heterogeneous) of the tissues of interest. For quantitative evaluation of the ultrasonographic characteristics, it was performed a computerized image analysis using a commercial software (Image ProPlus^® ). Mean numerical pixel values (NPVs), pixel heterogeneity (standard deviation of NPVs) and minimum and maximum pixel values were measured by selecting five circular regions of interest in each assessed tissue. All evaluated tissues presented significant variations in the NPVs, except for the liver. Pulmonary NPVmean, NPVmin and NPVmax decreased gradually through gestational weeks. The renal parameters gradually decreased with the advancement of the gestational weeks until the 17th week and later stabilized. The placentome NPVmean, NPVmin and NPVmax decreased gradually over the course of weeks. The hepatic tissue did not show echogenicity and echotexture variations and presented medium echogenicity and homogeneous echotexture throughout the experimental period. It was concluded that pixels numerical evaluation of maternal-foetal tissues was applicable and allowed the identification of quantitative ultrasonographic characteristics showing changes in echogenicity related to gestational age.