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Mariateresa Sasanellia, Paola Paradiesa*, Valeria Zazaa, Simona D�Amoreb, Beatrice Grecoa, Luigi Cecia, Giuseppe Palascianob, Vincenzo Ostilio Palmierib

a Department of Emergency and Organ Transplantation, Division of Veterinary Clinics and Animal Productions, University �A. Moro� of Bari, Italy 
b Department of Biomedical Sciences and Human Oncology, Unit of Medicine �A. Murri�, University �A. Moro� of Bari, Italy 



*Corresponding author: Paola Paradies, Department of Emergency Surgery and Organ Transplantation, Division of Veterinary Clinics and Animal Productions, University �A. Moro� of Bari, S.P. Casamassima Km 3, Valenzano, Bari, Italy;  HYPERLINK "mailto:paola.paradies@ uniba.it" paola.paradies@uniba.it 
ABSTRACT
Obesity is a common nutritional disorder in dogs and it has adverse effects on health and longevity. In humans, the detrimental health effects of obesity are well known and the regional fat distribution, especially intra-abdominal adiposity, is an important index of cardiovascular and metabolic deterioration. The significance of central obesity has not been well studied in dogs, but there is evidence for the presence of visceral obesity also in dogs. However, a simple and non-invasive method to assess the regional distribution of body fat is not available. The objective of this prospective study was to investigate a possible application of ultrasound to quantify visceral fat and to predict metabolic changes in obese dogs. 
Ultrasound measurements of adipose tissues were compared with morphometric and metabolic parameters of obesity in 54 client-owned dogs. The visceral fat measurement showed the strongest correlation with body condition score, total cholesterol, high density lipoprotein cholesterol and leptin serum concentrations. Results from this study suggest that ultrasonography may be a suitable non-invasive tool to diagnose canine obesity and quantify the regional fat deposition in dogs. Visceral fat measurement well reflect obesity status and it can predict alteration in the serum lipids and leptin concentrations. Further studies are needed to investigate the potential role of ultrasound visceral fat measurement as a suitable and simple indicator of the risk of  negative metabolic consequences of obesity in dogs.

Key words: dogs; ultrasound; lipid profile; visceral fat

INTRODUCTION
Obesity is defined as abnormal or excessive fat accumulation that presents a risk to human health (WHO, 2000). In human medicine accumulating evidence supports an association between obesity and several chronic diseases including hypertension, diabetes mellitus, hyperlipidaemia and cardiovascular diseases (Berker et al., 2010) referred as metabolic syndrome (MS) (Bergman et al., 2007). Insulin resistance is the pathophysiological driver of the MS (Reaven, 2011). Similarly in dogs obesity has harmful effects on health and longevity (German et al., 2011). It is known that obese pets are more prone to orthopaedic diseases (Marshall et al., 2009), metabolic disorders (Gayet et al., 2004), cardiovascular (Massabuau et al., 1997) and respiratory diseases (Bach et al., 2007), but the concept of metabolic syndrome in dogs is controversial. It has been  reported that up to a third of obese dogs suffer from "canine obesity related metabolic dysfunction" defined on the basis of criteria modified by International Diabetes Federation guidelines (Tvarijonaviciute et al., 2012). Nevertheless, it was recently assessed that the term 'metabolic syndrome' in dogs does not appear to have merit because there is no evidence that dogs are prone to develop type 2 diabetes, atherosclerosis, coronary heart disease and stroke in association to the obesity status as it happens in humans (Verkest, 2014). In other words the author reports that dogs can develop some components of the MS including insulin-resistance and hyperlipidaemia as previously reported (Jeusette et al., 2005;Verkest et al., 2011), but they do not exhibit the consequences of the human metabolic syndrome (Verkest, 2014).
In humans the distribution of body fat and in particular the abdominal visceral fat depot is accepted as a determining factor of MS (Kissebah et al., 1982; Lapidus et al., 1984; Kim et al., 2011), thus ultrasonography was proposed to give a direct and practical measurement of regional fat thickness (Armellini et al., 1990). Moreover an ultrasonographic abdominal wall fat index for assessment of the ratio of visceral fat/subcutaneous fat in the abdomen has been established (Suzuki et al., 1993). It showed a positive correlation with some key metabolic alterations of the MS such as triglyceride, basal insulin levels (Suzuki et al., 1993) and oxidative patterns (Palmieri et al., 2006; 2011).
In dogs various methods have been proposed for assessment of whole body fat including clinical evaluation of body condition score (BCS) (Laflamme, 1997), percentage of body fat (%BF) (Burkholder et al., 2000), measurement of total body water (Son et al., 1998) and dual-energy X-ray absorptiometry (Mawby et al., 2004). Computed tomography was proposed in beagles to estimate visceral and subcutaneous fat separately (Ishioka et al., 2005) and magnetic resonance imaging was used in experimental studies to estimate visceral and subcutaneous fat in obese dog model (Kim et al., 2007).
Sonographic measurements have been rarely proposed as indicator of obesity in dogs and they focused on measuring the thickness of subcutaneous fat (Anderson and Corbin, 1982; Wilkinson and McEwan, 1991; Morooka et al., 2001), while no studies are actually available to estimate regional distribution of body fat in dogs using ultrasonography. 
The aims of this prospective study were to investigate a possible application of ultrasonography to quantify visceral fat and to predict metabolic changes in obese dogs.

MATERIALS AND METHODS
Animals 
Data were obtained from 54 client-owned dogs presented for routine visit at the Veterinary Teaching Hospital of  University of Bari between March 2010 and February 2011. 
Owners of all participating animals gave informed written consent.  The Ethical Committee of the Faculty of Veterinary Medicine of the University of Bari approved this study.
Dogs were weighed using an electronic scale; the degree of adiposity was clinically,estimated  by a single investigator for assessing the BCS on the nine-point scoring system developed by Laflamme (1997); where 4 and 5 represent ideal condition; scores 9= grossly obese; and scores 1= emaciated. Dogs with BCS equal to or greater than 4 were enrolled in the study; dogs with BCS 4-5, 6-7 and 8-9 were considered as normal (control population), overweight and obese respectively.
The pelvic circumference (PC) was measured and %BF calculated by the following gender-specific formulas (Burkholder and Toll, 2000): 
males: -1.4(HScm)+0.77(PCcm)+4; females:-1.7(HScm)+0.93(PCcm)+5; (HS = length of right rear limb from hock to stifle).
Dogs showing clinical signs and abnormalities on complete blood count, serum biochemical analysis and urinalysis were excluded from the study. T4 levels were measured in dogs having clinical suspicion of hypothyroidism.

Metabolic variables
Blood samples were collected by jugular venepuncture after a fasting period of 12-16 h and sera stored at -20�.  Serum glucose, total cholesterol, HDL cholesterol, triglycerides concentrations were tested in an automatic analyzer (Lyasis, SEAC�  Company, Calenzano, Italy) with standard commercial kits (Assel S.r.l., Guidonia, Rome). The LDL cholesterol was calculated applying Friedewald formula (Friedewald et al., 1972) derived from human medicine. Serum leptin and C-reactive protein (CRP) concentrations were also determined using specific tests (Canine Leptin ELISA Kit, Canine C-Reactive Protein ELISA Kit, Millipore Corporation, USA&Canada). 

Ultrasonography
Ultrasound (US) examinations were performed in fasted animals by an experienced veterinary ultrasonographer using two dimensional ultrasonography (Mylab30, Esaote) with a 5-8 MHz convex and a 7.5-12 MHz linear probes. 
For US measurements, skin surface of the dogs was gently cleaned with 70% isopropyl alcohol after clipping. For the measurement of the back fat layer, dogs were kept in standing position as previously described (Morooka et al., 2001). The tops of the dorsal spine of the wings of the ileum were selected as guide-points to detect medially the anatomical site of 7th lumbar vertebra (L7) by palpation. The linear-tip probe (7.5 MHz) was then positioned perpendicularly to the skin and moved along the vertebral column to search the top of spinous process of the selected vertebra. The depth of the back fat layer was taken on transverse plane by marking two points between the upper and the bottom line of the fat layer on L7 (Fig. 1).
For the measurements of subcutaneous, preperitoneal and visceral fat in the abdominal region, the methods accepted and  routinely used  in human  medicine (Armellini et al., 1990; Suzuki et al., 1993) were applied to the dogs.
Subcutaneous and preperitoneal abdominal fat measures were taken with the animal in dorsal recumbency and the linear probe (7.5 MHz) was held perpendicularly to the horizontal plane on the skin caudally to the xiphoid process along the linea alba. These two measurements were taken on transverse plane in the same scan; the thickness of the subcutaneuos fat was measured as the distance between the internal limit of the skin and the external surface of the linea alba; the thickness of the preperitoneal fat was measured as the distance between the peritoneum and the internal surface of the linea alba (Fig. 2).
Visceral fat measurement was performed in dorsal recumbency with the convex probe located in the middle abdomen along the linea alba and was measured as the distance between the internal surface of the abdominal wall and the ventral surface of the aorta in longitudinal or transverse plane scanning (Fig. 3). Each measurement was taken three times and the mean value was used for statistical analysis. 
Statistical analysis Descriptive statistics, including means and standard deviations for Gaussian distributed variables, median and quartile ranges for non-Gaussian distributed variables, count and percentages for qualitative variables, were used to characterize the study cases. One way analysis of variance was performed for comparison among independent groups for continuous variables that were Gaussian distributed. Multiple comparison were performed with Tukey�s test. Student�s T test was used to make comparisons between independent sample. For variables not Gaussian distributed non parametric tests were perfomed: Kruskal Wallis for analysis of variance and Wilcoxon test for comparison between independent groups. If comparison was perfomed after Kruskal Wallis test, p-value was adjusted according to Bonferroni, therefore significance was assessed at 0.016.
Differences between proportions were tested by chi-square. To address relationships between parameters, Pearson�s product moment correlation or Spearman�s correlation coefficient (rs) were determined as appropriate. A value of P <0.05 was considered significant. All data analysis were performed using commercially available statistical software (NCSS 2009 Kaysville, UT, USA and SAS 9.2 Cary, NC, USA).
The intra-observer and test-retest reliability of ultrasonographic measurements has been evaluated by the intraclass correlation coefficient.

RESULTS
Fifty-nine dogs have been enrolled in the study of which five were excluded because affected by hypothyroidism (N.3), leishmaniosis (N.1) and pyoderma (N.1). The final study population consisted of 39 females and 15 males; thirty-four females were spayed and 5 intact, 11 males were intact and 4 castrated. 
Breeds represented in the study included crossbreed (N.35) Siberian Husky (N.3), Beagles (N.3), Labradors retrievers (N.2), Pit bull (N.2), Epagneul Breton (N.2), Yorkshire Terrier (N.1), English Pointer (N.1), English setter (N.1), Bull Mastiff (N.1), Spitz (N.1), Pomeranian (N.1) and Maremma shepherd (N.1). The age range was between 1 to14 years (mean 7,3�3,6).and weights ranged from 7.3 to 40.0 Kg (mean 24,2� 9,7).
Characteristics of the dogs enclosed in the study and metabolic and ultrasonographic parameters are reported in the table 1; data have been divided according to BCS. No differences were found for age, sex, body weight, values of fasting glucose, total cholesterol, HDL cholesterol, LDL cholesterol or CRP in relation to the values of BCS. The values of triglycerides and leptin showed a progressive increase according to the BCS values. 
A progressive increase of all the US measurements was evident in relation to the increase of values of BCS except for subcutaneous fat. The analysis of correlation between the novel ultrasonographic parameters and clinical measurements of body weight (including the US measurement of back fat layer used as control) has shown that both visceral and preperitoneal fat were significantly correlated to all clinical measurements except for weight (Table 2). Differently subcutaneous fat measurement resulted significantly correlated only to back fat layer and PC.
Table 3 shows the correlation  between the metabolic variables and measures of adiposity. In particular visceral fat had positive correlation with total cholesterol, HDL cholesterol and leptin levels. Preperitoneal fat had a mild positive correlation only with HDL cholesterol, while subcutaneous fat did not present any significant correlation with the other variables. The intraclass correlation coefficient was 0.96 for visceral fat; 0.86 for subcutaneous fat; 0.93 for preperitoneal fat and 0.97 for back fat layer. 
DISCUSSION
Results from this study suggest that ultrasonography may be a suitable non-invasive tool to quantify regional fat deposition in dogs. Ultrasonographic methodology received a wide application in human medicine (Ribeiro-Filho et al., 2003) representing the best alternative to assess intra-abdominal fat in combination with anthropometric measurements. Among all US measurements tested in this study, the visceral fat measurement seems to be the best to reflect the obesity status. Moreover among the measures of adiposity it shows the best correlation with metabolic parameters of obesity such as serum total cholesterol, serum HDL cholesterol and serum leptin levels, as already demonstrated in humans (Armellini et al., 1990; Ribeiro-Filho et al., 2003; Berker et al., 2010).
The significance of central obesity is not totally defined in dogs anyway available references support the importance of estimation of visceral fat in obese dog model (Kim et al., 2003; 2007); in fact visceral fat contributes to insulin-resistance in acutely fat-fed dogs (Bergman et al., 2006; Lottati et al., 2012). Results of recent experimental studies using MRI show that dogs have the typical abdominal fat compartments (visceral and subcutaneous fat depots) seen in humans; these compartments are enhanced in dogs after a prolonged high-fat diet and are associated with metabolic dysfunction (Richey et al., 2009). It's important to note that in these studies dogs are observed in an experimental set, while results of the present study are reached in naturally obese dogs and thus may better reflect the veterinary clinical practice.
Differently from BCS that is used to estimate the total fat mass, the visceral fat ultrasound measurement provides an estimation of abdominal fat mass that may be of clinical relevance to diagnose the obesity status in dogs and to monitor them during weight loss plan.
This US measurement is a practical and quick method that doesn�t need anaesthesia and that could be learned by vet practitioners having an ultrasound equipment and minimal expertise.
In human medicine the US visceral fat measurement is included in the criteria to define the MS because it is accepted that the development of the insulin- resistance (core of MS) is associated to the visceral fat depot. The controversial question on the existence of the metabolic syndrome in dogs based on the observation that the deleterious consequences of obesity in dogs are distinct from those of obese humans with the MS (Verkest, 2014) make difficult to attribute a role to the US visceral fat measurement to predict the risk of metabolic syndrome in dogs. Anyway it is suggested that this measurement could potentially predict the pathological consequences of obesity also in dogs. 
In agreement with previous reports (Morooka et al., 2001; 2004) we observed during data collection that the post-lumbar region is a suitable site to apply the probe for back fat layer measurement  but the hair clipping in an unusual site could be not appreciated by the owner. 
Back fat layer and visceral fat US measurements seem to reflect the differentiation in BCS groups of dogs examined in this work and are both positively correlated with serum leptin levels. In addition visceral fat measurement showed a better positive correlation than the back fat layer for both serum total cholesterol and HDL cholesterol concentrations. Serum leptin concentration is a reliable marker of adiposity in dog regardless of age, gender and breed variations, and thereby is a useful blood biochemistry test in the small animal clinical practice (Ishioka et al., 2002; Ricci and Bevilacqua, 2012). In our study, serum leptin levels were positively correlated to increasing values of BCS in accordance with previous findings (Sagawa et al., 2002; Jeusette et al., 2005; Radin et al., 2009). 
Subcutaneous fat measurement at abdominal level does not correlate with BCS while the back fat layer measurement does. This is probably due to the fact that fat deposition in the lumbar region is higher than in abdominal area as previously demonstrated both on carcasses of dogs (Anderson and Corbin, 1982) and on living animals (Morooka et al., 2001). Moreover, subcutaneous fat measurement does not show any correlation with metabolic variables.
In this study the estimation of preperitoneal fat is able to differentiate obese dogs from the other two groups on the basis of BCS values. Results from studies in human medicine show that preperitoneal fat is positively correlated with triglyceride and basal insulin levels suggesting that preperitoneal fat shares common properties with visceral fat (Suzuki et al., 1993). Results of the present study show a low correlation between preperitoneal fat measurement and total and HDL cholesterol, but no correlation with serum leptin is registered. Moreover this measurement can be distorted by artefacts caused by dog movements which complicates the standardization of the technique as showed in a study in infants (Holzhauer et al., 2009).
In a recent study (Veiga et al., 2008) lower serum concentrations of CRP have been documented in obese dogs; differently our results do not show any significant difference of CRP among BCS groups and morphometric and ultrasonographic measurements.
In summary, results from this study suggest that ultrasonography may be a suitable non-invasive tool to quantify regional fat deposition in dogs. In particular the visceral fat measurement could be useful to diagnose canine obesity in clinical practice and it can predict alteration in serum lipids and leptin concentrations. Further studies are needed to investigate the potential role of US visceral fat measurement as indicator of the risk of the pathological consequences related to obesity in dogs.
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Table 1. Characteristics of dogs and metabolic and ultrasonographic parameters in relation to the values of Body Condition Score (BCS) (Data are mean+standard deviation (M+SD) or median first quartile-third quartile)
Values of Body Condition Score (BCS)4-56-78-9PSubjects, n162018Age, y (range)6.6�3.9 (1-13)7.6�3.3 (1-12)7.5�3.8 (3-14)n.s.Females, n91515n.s.Males, n753n.s.Spayed females, n91213n.s.Castrated males, n220Weight (Kg) (range)20.1�6.9 (8.8-32)25.1�8.5 (7.3-36)26.9�12.3 (8.9-40)n.s.Pelvic Circumference, cm51.6�8.1ab62.0�8.8a68.5�10.2b<0.0001% Body Fat19.4�4.2cd27.5�5.1ce37.1�6.3de<0.0001Fasting serum glucose, mmol/L5.61 (5.31-5.86)5.86 (5.58-6.11)5.94 (5.61-6.22)n.s.Serum total cholesterol, mmol/L5.58 (4.61-6.65)5.52 (4.72-6.68)5.52 (5.4-7.57)n.s.Serum HDL cholesterol, mmol/L3.57�1.23.85�0.544.0�0.94n.s.Serum LDL cholesterol, mmol/L1.57 (1.07-1.85)1.48 (0.92-1.84)1.8 (0.97-2.18)n.s.Serum triglycerides, mmol/L0.6 (0.45-0.86)f0.8 (0.51-1.19)0.92 (0.7-1.65)f0.03Serum leptin, ng/mL (1)1.85 (0.9-5.1)g7.7 (2.7-10.7)11.4 (7.6-17.6)g0.001C Reactive Protein, mg/dL2.5 (0.10-5)4.5 (1.5-12.5)3 (2-4.5)n.s.Back Fat Layer, mm5.6 (3.8-8.4)hi9.8 (7.1-13.1)hl15.1 (9.4-20.3)il<0.0001Preperitoneal fat, mm11.7 (6.3-17.6)m14.6 (11.0-20.9)19.7 (15.6-29.8)m0.0062Subcutaneous fat, mm3.6 (2.9-4.6)4.7 (3.4-7.3)4.7 (3.8-7.1)n.s.Visceral fat, mm37.2�10.9np55.1�13.1n57.5�18.7p0.0003(*) for technical reasons serum concentration of leptin were measured on 39/54 of dogs
aBCS 4-5 vs BCS 6-7 and bBCS 4-5 vs BCS 8-9 both p<0.05 at Tukey�s multiple comparison;
cBCS 4-5 and BCS 6-7, dBCS 4-5 vs BCS 8-9, eBCS 6-7 vs BCS 8-9, all significantly different at Tukey�s test p<0.05;
fBCS 4-5 vs BCS 8-9 p=0.0087; g BCS 4-5 vs BCS 8-9 p=0.001; hBCS 4-5 vs BCS 6-7 p=0.0046; iBCS 4-5 vs BCS 8-9, p<0,0001; lBCS 6-7 vs BCS 8-9 p=0.0085); mBCS 4-5 vs BCS 8-9 p=0.002
nBCS 4-5 vs BCS 6-7 and pBCS 4-5 vs BCS 8-9 both p<0.05 at Tukey�s multiple comparison;
Table 2. Correlation between ultrasonographic parameters and clinical measures of adiposity and body weight (r, P)

Back Fat LayerPC% BFBCSWeightVisceral fat0.51 
<0.0010.68
0.0000010.50
0.00010.52
<0.00010.54           <0.0001Subcutaneous fat0.42     
0.00140.44      0.00090.265      
n.s.0.24      
 n.s.0.47         0.00029Preperitoneal fat0.32    
0.0190.48    0.00020.37      0.00610.49      0.000140.44         0.0008







*PC= Pelvic Circumference; BF= Body Fat; BCS= Body Condition Score
Table 3. Correlation between metabolic variables and measures of adiposity (r, P)
Fasting serum GlucoseSerum Total CholesterolSerum HDL CholesterolSerum LDL CholesterolSerum TriglyceridesC Reactive ProteinSerum Leptin Visceral fat-0.09
n.s.0.372
0.0050.395
0.0030.21
n.s.0.01           n.s.0.07
n.s.0.54
0.0008Subcutaneous fat0.22     n.s.-0.05      n.s.0.004      n.s.-0.04      n.s.-0.22         n.s.0.28   n.s.0.16 n.s.Preperitoneal fat0.06     n.s.0.26      0.050.31      0.020.12        n.s.0.01           n.s.0.19   n.s.0.31 n.s.Back fat layer-0.14   n.s.0.01        n.s.0.07        n.s.-0.08      n.s.0.18           n.s.0.11   n.s.0.40 0.01PC0.06     n.s.0.20        n.s.0.23        n.s.0.08        n.s.0.03           n.s.0.01   n.s.0.53 0.001%BF 0.001   n.s.0.14        n.s.0.16        n.s.0.01        n.s.0.28         0.03-0.03   n.s.0.41 0.01BCS-0.07   n.s.0.21        n.s.0.23        n.s.0.04        n.s.0.30         0.020.05   n.s.0.52 0.001







FIGURE LEGENDS

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Figure 3. Measurement of visceral fat in the middle abdomen (transverse scan); Ivc = Inferior vena cava, Ao = Aorta. 









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