Comparative analysis of biochemical, radiological, and histopathological findings in hepatic lipidosis and iron storage disease of common mynas (Acridotheres tristis)

Abstract

Due to its unique metabolism and digestive traits, the common myna (Acridotheres tristis) is particularly susceptible to liver diseases, including iron storage disease (ISD) and hepatic lipidosis. This study, conducted on 29 mynas referred to veterinary centers in Kermanshah, aimed to evaluate correlations between serological findings, radiographic features, and histopathological changes. Blood biochemical and antioxidant parameters were assessed, and liver size measurements were obtained via radiographs in lateral and ventrodorsal positions. Ultrasound-guided fine-needle core biopsies provided tissue samples for histopathological evaluation and disease severity assessment. Results showed that serum cholesterol > 129.5 mg/dL (p = 0.0012) and triglycerides > 55 mg/dL (p = 0.0071) were significantly associated with hepatic lipidosis. The mean Malondialdehyde (MDA) concentration in affected birds was 0.8384 nM, correlating with larger liver sizes. Radiographs indicated liver sizes > 67.45 mm, with receiver operating characteristic (ROC) analysis revealing 83.33% sensitivity and 87.5% specificity for detecting hepatic conditions. Serum ferritin > 1.955 ng/mL was identified as a reliable diagnostic indicator for ISD. However, radiographic liver size alone was insufficient for definitive differentiation between hepatic lipidosis and ISD. Using Periodic Acid-Schiff (PAS) and Prussian blue staining, histopathological examination confirmed lipid and glycogen deposition in hepatic lipidosis and hemosiderin accumulation in ISD, validating the biochemical findings. This study highlights the necessity of multimodal diagnostic approach integrating biochemical, radiological, and histopathological techniques for accurate diagnosis and management of hepatic diseases in mynas.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12917-026-05697-0.

Introduction

Liver disease in birds: Birds are susceptible to a wide variety of metabolic and toxic liver diseases. Hepatic disease can cause impaired body condition, decreased reproductive capacity, immune suppression, and death [28]. Liver disease is a problem that can affect any bird, but it is well-documented in cockatiels (Nymphicus hollandicus), budgies (Melopsittacus undulatus), Gray parrots (Psittacus erithacus), as well as lorries and mynahs. In caged birds, metabolic diseases such as hepatic lipidosis and iron deposition disease can be serious health threats due to their effects on important processes such as fat metabolism and energy homeostasis. It accentuates the significance of the bird's liver for bird care [18].

Hepatic lipidosis is a pathological condition characterized by the abnormal accumulation of lipids, primarily triglycerides (TG), within hepatocytesthis condition is commonly associated with high-fat, energy-dense diets and impaired hepatic lipid metabolism. Increased spontaneous lipid accumulation may cause dyslipidemia, hepatocellular injury, and liver failure [13]. Obesity is reported as the most common cause of this disease in captive birds, and high-fat, low-protein diets are the primary culprit. Under normal conditions, fatty acids in the blood are metabolized by the liver, but if the liver’s function is compromised, fat enters hepatocytes, which promotes the occurrence of hepatic lipidosis [26].

Common mynas in captivity are prone to metabolic disorders, including obesity, hepatic lipidosis, atherosclerosis, and hemochromatosis largely due to their high intestinal iron absorption capacity and dietary imbalances. These are related to the genetic background of high iron absorption and iron retention disorders [11, 18]. Mynas have better intestinal iron absorption than other birds, such as chickens, leading to non-physiological iron deposition, mainly in the liver. However, diagnosis of ECs is difficult because of clinical signs that include abdominal distension, feather discoloration, respiratory distress, anorexia, and cachexia. These signs are similar to those that would be expected to be seen concurrently with underlying hepatic lipidosis. Thus, timely and accurate diagnosis is essential to prevent disease progression and improve survival outcomes [20, 3].

Diseases of birds can be caused by malnutrition, vectors of disease, or toxic exposures, with signs including anorexia, depression, emaciation, altered feces, and abdominal distention. Early diagnosis and treatment can dramatically improve outcomes and avoid the evolution of irreparable hepatic injury. Diagnosis of hepatic lipidosis can be carried out based on clinical inspection and biochemical characterization of liver enzymes and degree of fatty liver; imaging such as radiography and ultrasonography may show a history of hepatomegaly. The gold standard for accurate diagnosis is usually obtained via liver biopsy and histopathological examination. Those include serum iron parameters (ferritin and transferrin saturation) as well as liver histology (special staining, e.g., Prussian blue) diagnosis of iron storage disease [4, 2, 17].

Here, a microscopic grading system is established for histopathological hepatic lipid accumulation in captive common mynas. The grading cannot be used to set absolute cut-offs for physiological vs pathological lipid retention, but is designed as the basis for further investigations. A combination of laboratory assays with radiological studies, such as liver size and iron content measurement, provides improved diagnostic accuracy and prognostic prediction. Our main aim was to achieve a comprehensive, statistically based histopathological, radiological, and biochemical evaluation and to identify a number of quantitative markers that could assist veterinarians in reliable diagnosis. This multimodal approach makes it possible to find useful chemical markers to distinguish among different metabolic diseases with positive applications to individual diagnostics and directed therapy.

Materials and methods

Sample population

The present study was reviewed and approved by the Animal Ethics Committee of Razi University, Kermanshah, Iran (Ethics code: IR.RAZI.AEC.1403.009). The study included 29 Common myna birds (Acridotheres tristis) referred to veterinary clinics in Kermanshah, Iran, between October 2024 and August 2025. Birds were adults aged 4–12 years (mean ± SD: 7.2 ± 2.1 years), comprising 17 males (58.6%) and 12 females (41.4%). Inclusion criteria were: clinical signs of hepatic disease (e.g., abdominal distension, lethargy, anorexia), radiographic evidence of hepatomegaly, and owner consent. Based on the radiographic evidence of hepatomegaly, birds were initially categorized into low- and high-risk groups as a clinical risk stratification tool. However, as radiography lacks the specificity to definitively distinguish between various hepatic pathologies, this classification was considered a preliminary screening. The definitive diagnosis and differentiation between hepatic lipidosis and ISD were strictly established via histopathological examination, which served as the gold standard in this study. Exclusion criteria included: confirmed viral (e.g., avian bornavirus, polyomavirus), bacterial, or parasitic infections via PCR/serology; neoplasia; or concurrent non-hepatic diseases. All birds were screened negative for these via routine diagnostics. Diets were categorized as commercial (pelleted avian feed with 12% protein from soybean meal, 5% fat from vegetable oils, vitamins A/D/E supplemented; n = 13), homemade (seeds, fruits, bread; high in carbohydrates from grains, fats from nuts; n = 5), or mixed (n = 11). Housing: caged (n = 15) or free-range indoors (n = 14).

Sampling

Birds were blood-sampled from the wing vein, and blood samples were stored in blood collection vials with EDTA. Blood films were made and examined. Then, the blood samples were centrifuged for plasma separation, stored at − 80c◦, and used for the subsequent analyses of biochemical and antioxidants. The birds were also sedated or anesthetized by inhalation anesthesia for blood sampling if needed to ensure that stress or injury did not occur.

Diet composition

Commercial diets consisted of balanced pelleted food (e.g., containing 12–15% crude protein from soybean and fish meal, 4–6% fat from corn/soybean oil, 50–60% carbohydrates from grains, supplemented with vitamins (A: 10,000 IU/kg, D3: 2,000 IU/kg, E: 50 mg/kg) and minerals (iron: < 100 mg/kg). Diet composition was categorized based on owner-reported feeding practices.

Lipid profile

Serum cholesterol and triglyceride concentrations were measured by enzymatic methods using a Biochemistry Auto-analyzer (Alpha Classic, Iran).

Iron status

Serum Iron Estimation of the serum iron concentration in plasma was performed using a colorimetric endpoint method. Ferritin concentration was determined with a quantitative ELISA kit (Invitrogen). The ratio of iron to ferritin was determined to explore iron status even more.

Lipid peroxidation

As a lipid peroxidation biomarker, MDA was quantified in plasma for all samples using a standard spectrophotometric method with commercial assay kits Nalondi™ according to the manufacturer’s guide (Navand Salamat, Urmia, Iran).

Radiology

Lateral (L) and ventrodorsal (VD) radiographs were obtained. X-rays were obtained with a Poskom® Vet 20BT X-ray machine and developed on an Agfa-30X digital X-ray processor. Images were assessed by two experienced national board-certified radiologists with more than 2 years of avian radiology experience in a blind manner. Hepatomegaly was considered to be present if there was an impaired hourglass effect due to enlargement of the liver shadow from the coracoacetabular axis on VD projection and from the sternum on the L view [16, 28].

Biopsy and histopathology

Liver biopsies were performed via ultrasound guidance using a G18 needle biopsy gun, and fine-needle tissue core samples were obtained from sedated birds by way of intramuscular injection of Ketamine (30 mg/kg) and Midazolam (2 mg/kg). No complications followed. Specimens were fixed in 10% buffered formalin, sectioned, and stained with Hematoxylin and Eosin (H&E) and Prussian blue for the assessment of iron accumulation. Ten fields per liver section were examined by a pathologist blinded to the clinical data. Hepatic lipidosis was diagnosed by macrovesicular steatosis, while ISD was confirmed via Prussian blue staining. In cases with concurrent pathologies, the primary diagnosis was based on the predominant feature. Steatosis and hepatic necroinflammatory grading were performed according to Brunt et al.(1999) and the Knodell histological activity index (HAI) system [15]. For nonalcoholic steatohepatitis (NASH) in nonalcoholic fatty liver disease (NAFLD). Lesions of the liver were scored as follows: macrovesicular steatosis and hepatocellular ballooning (I), periportal and/or bridging necrosis (II), intralobular degeneration and focal necrosis (IV), intra-acinar inflammation (V) and portal tract inflammation (VI) (Table 1). The necroinflammatory activity was graded according to portal inflammation (P), intralobular inflammation (L), piecemeal necrosis (PN), and focal necrosis (BN), and the sum of P, L, and twice the sum of PN and BN, each ranging from 1 to 4, was calculated as the lesion severity score.

Table 1.

HAI for numerical scoring of liver biopsy specimens

I. Steatosis	Score	II. hepatocellular ballooning	Score	III. Periportal ± bridging necrosis	Score	IV. Intralobular degeneration and focal necrosis	Score	V. Lobular inflammation	Score	VI. Portal inflammation	Score
A. None	0	A. None	0	A. None	0	A. None	0	A. None	0		0
B. Up to 33% of hepatocytes	1	A. Few balloons’ cells	1	B. Mild piecemeal necrosis	1	B. Mild (acidophilic bodies, ballooning degeneration, and/or scattered foci of hepatocellular necrosis in < 1/3 of lobules or nodules)	1	B. < 2 foci per 200 × field	1	A. Mild	1
C. 33–66% of hepatocytes	2	B. Many cells/prominent ballooning	2	C. Moderate piecemeal necrosis (involves less than 50% of the circumference of most portal tracts)	3	C. Moderate (involvement of 1/3–2/3 of lobules or nodules)	3	C. 2–4 foci per 200 × field	2	B. Moderate	2
D. > 66% of hepatocytes	3			D. Marked piecemeal necrosis (involves more than 50% of the circumference of most portal tracts)	4	D. Marked (involvement of  > 2/3 of lobules or nodules)	4	D. > 2 foci per 200 × field	3	C. Severe	3
				E. Moderate piecemeal necrosis plus bridging necrosis	5
				F. Marked piecemeal necrosis plus bridging necrosis	6
				G. Multilobular necrosis	10

Quantitative analysis of PAS and Prussian blue staining

Digital images at 640 × 400 pixels and × 40 magnification were captured from various liver regions, analyzing five randomly selected points per slide for PAS and Prussian blue staining percentages with a microscope-attached camera. Adobe Photoshop processed the images to enhance contrast. ImageJ software (version 1.47) was used for analyzing iron and glycogen percentages through the following steps:

• Open images via File > Open.

• Adjust brightness and contrast via Image > Adjust > Brightness/Contrast.

• Remove image noise through Option > Process > Filters > Median.

• Analyze enhanced images using plugins for PAS and Prussian blue staining via Plugins > Color Deconvolution > Selection "H PAS” and “H&E DAB” from the ROI window.

• Convert the target-stained area into a binary red mask with Image > Adjust > Threshold.

• Calculate the area percentage of the target stain using Analyze > Set Measurement > Select Area & Limit to Threshold > Measure.

Statistical analysis

The statistical analysis was conducted with GraphPad Prism, version 10. The normality of the distribution of data was evaluated using the Shapiro–Wilk test. Descriptive statistical methods (i.e., frequency, percentage, mean, and standard deviation) were used. A one-way ANOVA was used to compare parameters between diet categories. A comparison of low-risk versus high-risk groups was conducted using an independent t-test. The non-parametric Mann–Whitney test was used where the data were not normally distributed. Pearson correlation coefficient was used for correlation analysis between the parameters, as well as Receiver Operating Characteristic (ROC) curve analysis was applied for diagnostic value. Statistical tests were considered significant at P < 0.05.

Results

Frequency distribution of the studied parameters in common mynah birds

The birds presented to the clinic examined in this report were 29 common myna birds with a history of presenting various clinical signs on 22 October 2024 and 22 August 2025. Radiographs (ventrodorsal and lateral) were taken following exhaustive clinical examination. About 2.0 ml of blood was taken from the brachial vein of each bird and kept in EDTA tubes for biochemical and antioxidant assays. When possible, some birds also had other procedures (liver biopsy or other). The obtained samples were histopathologically studied by hematoxylin and eosin (H & E), Periodic Schiff (PAS), and Prussian blue stains.

The percentage of birds studied that were kept in a cage only was 65.52, and the proportion kept loose in the house was 34.48%. Based on the owners' reports regarding diet composition, 44.83% were given commercial diets, 20.69% were fed mixed commercial and homemade foods, and 17.24% were given only homemade diets. The serum cholesterol concentration varied from 20 to 200 mg/dL; 100 mg/dL (23.77%) was the most frequent level. The median cholesterol value was 116.50 mg/dL, and the mean and standard deviation were 115.55 mg/dL and 57.54 mg/dL, respectively. Similarly, for triglyceride ranges from 20 to 130 mg/dL, the most frequent (at 33.63%) was 70 mg/dL. The median triglyceride level was 64.50 mg/dL, and the mean level was 55.54, with SD 31.64 mg/dL. The malondialdehyde (MDA) levels were 0.076 −0.897 nM, and almost 62% of the samples were 0.25 nM. The mean and median for MDA levels were 0.299 and 0.242 nM, respectively, with a standard deviation of 0.178 (Fig. 1).

Fig. 1.

Frequency Distribution of Parameters in Common Mynah Birds. This figure showcases the frequency distribution of parameters measured in 29 common mynah birds. A illustrates diet types—commercial food, mixed commercial, and homemade. B displays housing conditions—the percentage of birds kept only in cages compared to those allowed free flight at home. C shows the distribution of triglyceride (TG) serum levels. D highlights the distribution of cholesterol (Chol) serum levels. E presents the distribution of malondialdehyde (MDA) serum concentration. F depicts the distribution of serum iron levels. G shows the distribution of serum ferritin concentration. H. illustrates the distribution of the iron-to-ferritin ratio. I. depicts the distribution of the radiographic liver length to abdomen length ratio. Relative frequencies (%) are hown to emphasize the variation among the birds

The serum’s iron ranged between 55.50–263 µg/dL, with the highest frequency in iron level (21.43%) at 100 µg/dL. The median iron was 114.50 µg/dL with a mean (± standard deviation) of 122.36 ± 48.11 µg/dL. Serum ferritin ranged from 1.638 to 3.501 ng/mL; the most frequent level was 1.8 ng/mL (31.03%). The median and mean ferritin concentrations at baseline were 2.017 ng/mL and 2.179 ng/mL, with an SD of 0.517. The mean iron-to-ferritin ratio was also determined, with the most common value being 30 (21.43%). This ratio was between 30 and 130, with the median being 48.4, the mean 59.38, and the standard deviation 28.50 (Fig. 1).

Radiographic visualization of the liver includes the assessment of maximum liver width to abdominal cavity width. The liver-to-abdominal width ratio ranged from 48 to 78, with the lowest and highest values noted in 4.17% of birds. The median and mean values of the ratios were 59.24 and 60.67, respectively.

Comparison of biochemical and radiological parameters based on dietary groups

There was a significant difference in ferritin levels between commercial and homemade diets (p = 0.0200) and commercial and mixed diets (p = 0.0463). However, the difference between the homemade and mixed diet groups was insignificant (p = 0.9267). The homemade diet group showed a statistically significant difference in iron intake compared to the commercial diet group (p = 0.0057) and the mixed diet group (p = 0.0060). However, there was no significant difference between the commercial and mixed diet groups (p = 0.9568). The relative iron to ferritin ratio was also compared among the three diets; the homemade diet showed a significant difference from the mixed diet (p = 0.0325), suggesting that the homemade diet was heterogeneous from the mixed commercial diet. The difference between commercial and mixed diet groups was insignificant (p = 0.9470). The findings suggest that birds on a homemade diet had higher triglyceride concentrations compared to other groups; however, these observations should be interpreted cautiously due to the limited sample size and lack of precise dietary quantification. However, according to p values, the differences in triglyceride levels between the homemade and mixed diet groups and between the commercial and mixed diet groups were insignificant. However, A difference was observed between the homemade and commercial diets (p = 0.0268). The level of MDA of the homemade and commercial diet group showed a significant difference (p = 0.0081). No difference was detected between the homemade and mixed diet groups.

Pearson correlation analysis between biochemical parameters in different dietary groups

In the present study, CF denotes the commercial food diet, and HF is the homemade food diet, which mixes commercial and homemade food. The heatmap employs gradient coloring, and the closer the color is too purple, the more positive the correlation coefficient, and the greener it is, the more negative. The closer the value is to + 1, the stronger the direct relationship between the two compared parameters. Conversely, negative values indicate an inverse relationship between the parameters (Fig. 2, H).

Fig. 2.

Distribution and Correlation of Serum Parameters in Common Mynah Birds Based on Diet Types. This figure illustrates the distribution of various serum parameters measured in 29 common mynah birds fed different diets, including homemade, commercial, and a mixture of both. Panels A to G present boxplots that compare triglycerides (TG), cholesterol (Chol), malondialdehyde (MDA), iron (Iron), ferritin, and the iron-to-ferritin ratio across these diet groups, with green annotations indicating statistically significant differences. Panel G displays a correlation matrix that highlights the relationships between serum parameters within each diet group (CF = Commercial Food, Mix = Mixed Diet, HF = Homemade Food), where the purple-to-green color gradient signifies positive to negative correlations. Panel G also shows the distribution of the liver-to-abdomen length ratio derived from radiographic images. This figure emphasizes the significant variations and interrelationships among biochemical markers influenced by diet type in common mynah birds. Finally, Panel H illustrates Pearson Correlation Analysis Between Biochemical Parameters in Different Dietary Groups

Assessment of biochemical parameters in low-risk and high-risk groups based on radiographic findings

According to the radiographic image, the samples were classified into low-risk (LR) and high-risk (HR) groups, an approach that can be applied clinically and is easy to perform. This radiological classification is valuable because imaging is less invasive and more available than invasive diagnostic procedures to enable clinicians to promptly recognize patients who are at high risk of liver diseases to stratify patients. The p values for differences between groups were determined for each biochemical factor. Also, cholesterol and triglyceride in a high-risk group were higher (p = 0.0012 and p = 0.0071, respectively) than they were for the at-risk target of plasma lipids for disease. Iron (p = 0.5373) and ferritin (p = 0.6169) were not significant compared to %AUC0–180, nor was Fe:L (p = 0.1970). The level of oxidative stress marker MDA was higher in a high-risk group (p = 0.0246). Radiographic liver size exhibited high statistical significance for the high-risk group (p = 0.0001), indicating the diagnostic value of the examination (Fig. 3). Analysis of Pearson's correlation among the biochemical markers during the follow-up Visit a Pearson's correlation of the two study groups revealed some correlations between the biochemical markers. Positive (purple) and negative (green) correlations emphasize the complex biochemistry necessary for liver function. This study also indicates that the combination of radiologic images and biochemical tests is a powerful method that allows the screening of patients at risk with liver diseases (Fig. 3, H).

Fig. 3.

This figure compares serum biochemical markers and liver size metrics between two groups classified by risk level (Low Risk vs. High Risk). Panels A to F present boxplots indicating significant variances in triglycerides (TG), cholesterol (Chol), and malondialdehyde (MDA) levels, all of which are heightened in the High-Risk group. Conversely, iron (Iron), ferritin, and the iron-to-ferritin ratio do not demonstrate statistically significant differences. Green annotations indicate p-values that denote significance. Panel G examines the liver-to-abdomen length ratio for the groups, showing a notably larger liver size in the High-Risk group (p < 0.0001). Panel H features a Pearson correlation matrix that portrays relationships among biochemical parameters and liver size within each risk group. The gradient from purple to green symbolizes positive to negative correlations, effectively illustrating the interconnectedness of biochemical dynamics linked to risk stratification

Analysis of ROC curve for biochemical integrity markers

A plasma triglyceride level over 55.00 mg/dL had an Area Under the Curve (AUC) of 0.8462 (p = 0.0041; 95% CI: 0.6711 to 1.000). At > 55 mg/dl, sensitivity was 100% with specificity at 72.73%, indicating strong correlation in the high-risk group. Plasma cholesterol > 129.5 mg/dL demonstrated an AUC of 0.9107 (p = 0.0004; 95% CI: 0.8033–1.000), with sensitivity at 71.43% and specificity at 91.67%, showing good discrimination for high-risk cases. A plasma iron cutoff of > 106.6 mcg/dL yielded an AUC of 0.7462 (p = 0.0270; 95% CI: 0.5570–0.9353), with sensitivity and specificity at 84.62% and 66.67%, respectively, suggesting moderate risk classification efficiency. The AUC for plasma ferritin > 1.955 ng/mL was 0.7163 (p = 0.0485; 95% CI: 0.5193–0.9134), with sensitivity and specificity of 84.62% and 68.75%, showing fair discriminatory ability. The iron-to-ferritin ratio cutoff > 53.60 had an AUC of 0.8036 (p = 0.0047; 95% CI: 0.6327–0.9744), with sensitivity at 85.71% and specificity at 81.25%, indicating it as a good marker for high-risk identification. Plasma MDA at a cutoff of 0.3100 nM resulted in an AUC of 0.7163 (p = 0.0485; 95% CI: 0.4333 to 0.8685), with sensitivity at 38.46 and specificity at 92.31%, showing lower sensitivity but high specificity. Cholesterol and triglycerides provided the best diagnostic accuracy among indicators differentiating high- and low-risk groups, while MDA and ferritin had minor predictive potential (Table 2).

Table 2.

Diagnostic Performance of Biomarkers in Assessing Hepatic Dysfunction

	Ferritin ng/ml	Iron	Iron: Ferritin	MDA	TG	Chol
Sensitivity(%)	84.62%	84.62	85.71	38.46	100.00	71.43
Specificity(%)	68.75%	66.67	81.25	92.31	72.73	91.67
AUC	0.7163	0.7462	0.8036	0.7163	0.8462	0.9107
Cut off	> 1.955	> 106.6	> 53.60	> 0.3100	> 55.00	> 129.5
95% CI	0.5193 to 0.9134	0.5570 to 0.9353	0.6327 to 0.9744	0.4333 to 0.8685	0.6711 to 1.000	0.8033 to 1.000
P value	0.0485	0.0270	0.0047	0.0485	0.0041	0.0004

This table summarizes the diagnostic performance of biomarkers for hepatic dysfunction. It includes sensitivity, specificity, AUC (Area Under the Curve), cutoff values, 95% confidence intervals (CI), and p-values for ferritin, iron, iron-to-ferritin ratio, malondialdehyde (MDA), triglycerides (TG), and cholesterol (Chol). All biomarkers show significant diagnostic value, with ferritin, iron, and cholesterol having high sensitivity and AUC values, while MDA and TG provide strong specificity. Cutoff values and p-values indicate significant associations with hepatic dysfunction, particularly for cholesterol and MDA

Radiological findings assessment

According to the radiograph, the low risk in images A and C is a case of absence of hepatomegaly. On the other hand, images B and D are for a case with high risk, which presents clear evidence of hepatomegaly. In the VD view, the right hepatic lobe appears to occupy more than 50% of the right coelomic cavity, and liver margins extend beyond lines drawn from the acetabulum to the shoulder joint. The typical shadow in the liver under the heart, seen as an "hourglass sign," is missing, and the liver margins are rounded instead of having an acute profile. The enlarged liver also pushes the heart cranially, and the proventriculus is displaced away from the ventriculus at a caudodorsal angle as opposed to the standard 35–40° angle. On the lateral view, the air sacs are compressed due to liver enlargement, and the liver margins reach beyond the sternum, indicating an abnormal case. These radiographic findings provide evidence of hepatomegaly in the case shown in Fig. 4, B, and D.

Fig. 4.

Panels A and C represent low-risk cases in ventrodorsal and lateral views, respectively, with normal liver size and contours. In these panels, the right hepatic lobe occupies less than 50% of the right coelomic cavity, clear, sharp liver margins, and preserved hourglass shadow between the liver and heart, consistent with avian radiology standards. Panels B and D depict high-risk cases in ventrodorsal and lateral views, respectively, exhibiting hepatomegaly: the liver extends beyond anatomical landmarks with rounded margins, absent hourglass shadow, cranially displaced heart, caudodorsally shifted proventriculus, and compressed air sacs overlapping the sternum. These radiographic features confirm liver enlargement and are reliable, non-invasive markers for early hepatomegaly diagnosis in clinical avian practice. The letters a, b, c, and d in the images denote specific reference points for measuring liver size and positioning in the radiographs

Histopathological findings

The liver tissues in the low- and high-risk group members were examined histopathologically, and the injuries were graded from weak to strong, as presented in Figs. 5 and 6. Macrovesicular steatosis dominated the image in the high-risk group, in which the cytoplasmic vacuoles of different sizes, with a sharp border, pushed the tight hepatocyte nuclei toward the periphery. These vacuolar changes were spotty, predominantly involving centrilobular hepatocytes, with occasional bridging. Vacuoles were from small pinpoint to large single vacuoles that distended the cytoplasm of the hepatocyte. The low-risk group had mild steatosis with smaller vacuoles in the centrilobular area.

Fig. 5.

Pathological features of bird liver tissues in the low- and high-risk groups (H&E staining). A, D low-risk group, few hepatocytes with macrovesicular steatosis; B, E high-risk group, mild steatosis; C, F high-risk group, moderate steatosis; G, J low-risk group, mild hepatocellular ballooning degeneration; H, K high-risk group, moderate hepatocellular ballooning degeneration; I, L high-risk group, severe hepatocellular ballooning degeneration

Fig. 6.

Pathological features of bird liver tissues in the low- and high-risk groups (H&E staining). A, D low-risk group, mild intralobular inflammation as pinpoint foci; B, E high-risk group, mild intralobular inflammation as large foci; C, F high-risk group, moderate intralobular inflammation; G, J low-risk group, mild hepatocyte degeneration and few necrotic hepatocyte clusters among normal-appearing parenchymal cells; H, K high-risk group, mild hepatocyte degeneration and necrosis; I, L high-risk group, moderate hepatocyte degeneration and necrosis

Hepatocellular ballooning degeneration was more significant in the high-risk group, with limited hepatocyte involvement in the low-risk group. Interlobular inflammation varied from mild occasional aggregates of cells in low-risk cases to severe clusters in high-risk cases. They found moderate mononuclear cell infiltrate, primarily composed of macrophages, with a smaller population of lymphocytes and prominent vascular congestion in portal spaces of the high-risk group in contrast to minimal portal inflammation in the low-risk group.

Interlobular degeneration and focal necrosis were present in 50% of high-risk samples and were moderate to severe, and only 15% of low-risk samples had mild degeneration and necrosis. Critically, there was no evidence of progressive or piecemeal necrosis in either group. Hepatic Activity Index (HAI) Overall Score was significantly higher in the high-risk group as compared to the low-risk group (P < 0.0001).

PAS staining showed increased glycogen accumulation in the high- than in the low-risk group as both coarse and fine pink granules were evenly distributed in the cytoplasm of the hepatocyte; however, the difference was not significant, suggesting that the increase of glycogen might not be the primary cause for the cytoplasmic vacuolar degeneration. Hepatocyte Iron Deposition Prussian blue staining showed that the iron deposition in the hepatocytes of the high-risk group was more than that in the low-risk group, and the iron deposit was blue-black colloidal granules (Fig. 7).

Fig. 7.

PAS and Prussian blue staining of hepatic tissue for glycogen and iron content in the low- and high-risk groups. Glycogen accumulation as coarse and fine pink granules homogenously dispersed within the cytoplasm of the hepatocytes in the low-risk A and high-risk B groups. Iron deposition forms an excellent blue colloidal dispersion within the cytoplasm of the hepatocytes in the low-risk C and high-risk D groups

Discussion

This report underscores the intricate and associated pathomechanism for both hepatic lipidosis and iron storage disease in captive common myna (Acridotheres tristis), stressing the necessity of combining biochemical, radiological, and histopathology techniques for a precise diagnosis and more efficient management. Diseases of the liver in birds affect important metabolic, detoxification, and immunologic function, which ultimately have life-threatening and welfare-threatening consequences for the bird [30, 24]. Due to the unusual aspects of myna metabolism and dietary habits, knowledge of the biochemical and histological bases of these hepatic disorders is essential to aid early therapeutic intervention [18, 11, 25].

Incremented serum cholesterol and high levels of triglycerides in the liver in birds with fatty liver disease, just as those have been described in other avian species, such as psittacines and galliforms, where excessive lipid input overcomes hepatic metabolic capacity, confirm this aspect [29, 5]. The pathogenesis of hepatic lipidosis likely involves impaired mitochondrial β-oxidation of fatty acids, resulting in intracellular triglyceride accumulation and subsequent hepatocellular injury. [9, 23]. This excess of lipid, in turn, induces mitochondrial dysfunction and oxidative stress leading to activation of inflammatory pathways involving cytokine release (TNF-α and IL-6), attraction of Kupffer cells, and triggering hepatocyte apoptosis [19]. Our significant elevation of malondialdehyde (MDA), a well-known lipid peroxidation biomarker, supports the centric role of oxidative stress in pathogenesis [12].

Concomitantly, iron overload in mynas, which is also notorious as the birds possess higher intestinal absorptivity of iron compared to that in other birds, is documented as being well [14],contributes significantly to the hepatic pathology. Excessive iron promotes the Fenton reaction, thereby generating ROS, which triggers mitochondrial DNA damage, lipid peroxidation, and protein oxidation, accelerating the damage as well as apoptosis of cells [27]. Our results support the involvement of iron deposition in hepatic injury, as demonstrated by Prussian blue staining, consistent with previous studies. [21]. Augmented mitochondrial dysfunction induced by iron can lead to compromised lipid metabolism, causing synergistic cytotoxicity and increased development of hepatic steatosis [31].

Radiographically, hepatomegaly (liver size > 67.45 mm) was found to be a sensitive indicator of hepatic disease; however its specifity for differentiating hepatic lipidosis from ISD was limited [28, 22]. However, radiographic appearance demonstrated poor discriminatory power to differentiate lipidosis from ISD, emphasizing the integrated biochemical and histological information required. Specialized imaging techniques, including ultrasonography and computed tomography (CT), have shown potential for improved hepatic architectural iron content assessment. Nevertheless, their potential as functional tools in mynas needs to be further tested [28, 30].

Histopathological features, such as evident macrovesicular steatosis, hepatocellular ballooning, portal inflammation, and iron accumulation, represent the multifactorial cellular response to metabolic and oxidative damage. Ballooning degeneration is considered to represent an intracellular process of hepatocyte enlargement (cell swelling) and alteration in the cytoskeleton, second to the accumulation of toxic lipid byproducts (metabolites) and ROS [4]. Glycogen storage, as demonstrated by PAS staining, although not significantly different in this setting, is indicative of metabolic derangement but is probably not a prime mediator of vacuole degeneration, serving rather as its secondary or compensatory picture [8].

From the mechanistic point of view, the cross-talk between lipid accumulation and iron-induced-oxidative stress forms a vicious circle leading to the amplification of hepatocellular injury. Lipid peroxidation products, e.g., MDA, act not only as markers but also as inflammation mediators by triggering the production of pro-inflammatory cytokines, which are released by cells such as Kupffer cells and promote Kupffer cell activation and hepatocyte apoptosis [10]. At the same time, excessive iron catalyzes continual ROS production, leads to more mitochondrial and cell structure damage, and causes progression to fibrosis and hepatic failure if it is not blocked [1].

In a therapeutic context, antioxidant supplementation (e.g., vitamins E, selenium, and polyphenolic compounds) is effective in reducing oxidative damage in avian hepatic models and would be a potential adjuvant in mynas [7]. Iron-chelation therapy, hepatoprotectant agents, dietary regimen for reduction of excessive nutrient intake, and low-fat and low-iron foods may also become part of the treatment protocol to control iron excess. Commercial feeds do not always meet the specific metabolic demands of mynas, and this underlines the importance of individualized feeding management [6].

The limitations of our study include the limited sample size (n = 29) and absence of longitudinal follow-up to evaluate the progression of chronic diseases. In addition, there are no molecular investigations to determine the gene expression profiles of iron transporters and enzymes related to lipid metabolism, restricting mechanistic understanding. Prospective studies on a larger number of patients, longitudinal studies, and the inclusion of novel molecular techniques are warranted to define genetic predisposition and identify potential new therapeutic targets.

In conclusion, the present study supports that a multimodal diagnostic approach improves the detection and characterization of hepatic diseases in captive common mynas. Prevention or early diagnosis and treatment of HL and ISD is central to improving bird health and welfare. Periodic surveillance with the appropriate dietary and therapeutic interventions according to species-specific metabolic requirements is highly recommended to reduce disease morbidity among this vulnerable avian population. However, the relatively small sample size (n = 29) and the lack of a formal power analysis limit the robustness and generalizability of these findings. Consequently, the statistical results, including the ROC analyses, should be interpreted as exploratory. Further longitudinal and large-scale studies are warranted to validate these preliminary results. Additionally, the dietary information was obtained through owner interviews, which introduces potential recall bias and lacks quantitative precision regarding the exact nutrient composition. Therefore, the links between diet and liver pathologies observed in this study should be interpreted as reported associations rather than causal relationships. Future studies using controlled dietary assessments are necessary to confirm these findings.

Authors’ contributions

A.M. contributed to funding acquisition, sample collection, and preparation of the initial manuscript draft. H.CH. conceived and designed the study, supervised the project, performed laboratory investigations, conducted formal data analysis, and prepared the final version of the manuscript. M.R. was responsible for clinical case management, animal examinations, and clinical consultation. M.H. performed the histopathological evaluations and interpreted the pathological findings. S.S. conducted and interpreted the radiological examinations. All authors critically revised the manuscript and approved the final version.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

This study was conducted on clinical cases of common mynas presented for diagnostic purposes. All procedures were performed in accordance with institutional guidelines and national regulations governing animal welfare (Ethics code: IR.RAZI.AEC.1403.009). Written informed consent was obtained from the owners prior to inclusion.

Consent for Publication

Not applicable.

Competing interests

Hadi Cheraghi is a member of the board of directors of Navand Salamat Co., the manufacturer of the antioxidant assay kits used in this study. The kits were obtained through standard commercial procurement, and the company had no role in the study design, data collection, analysis, interpretation of data, or manuscript preparation. All other authors declare that they have no competing interests.