Prediction of vascular invasion using a 7-point scale computed tomography grading system in adrenal tumors in dogs

Computed tomographic anatomic variations of the phrenicoabdominal veins in cats

There are no published reports describing the anatomic variations of the phrenicoabdominal (PhAbd) veins in cats. The aim of this study was to evaluate the anatomic variations of the PhAbd veins in cats without adrenal disease. This is an anatomic study. Abdominal CT images of cats acquired from January 2021 to February 2023 were retrospectively reviewed. Inclusion criteria were the presence of pre- and postcontrast CT images of the abdomen and the absence of any abdominal diseases that compromise the left and right PhAbd veins visualization. A total of 128 cats were included. Three different vascular anatomic variations were found in the distal pericaval segment of the left phrenicoabdominal (LPhAbd) vein. In the first type, found in 65 cases (50.8%), the LPhAbd vein drained directly into the caudal vena cava. In the second type defined IIa, found in 25 cases (19.5%), the LPhAbd vein drained into the distal third of the left renal vein, less than 5 mm from its opening into the caudal vena cava. In the third type defined IIb, found in 38 cases (29.7%), the LPhAbd vein drained into the distal third of the left renal vein, more than 5 mm from its opening into the caudal vena cava. The right phrenicoabdominal vein had a consistent path and drained into the caudal vena cava in all cases. The knowledge of these vascular variations is expected to help the surgeon during adrenalectomy due to masses with vascular invasion in cats.

Artificial intelligence in veterinary diagnostic imaging: Perspectives and limitations

The field of veterinary diagnostic imaging is undergoing significant transformation with the integration of artificial intelligence (AI) tools. This manuscript provides an overview of the current state and future prospects of AI in veterinary diagnostic imaging. The manuscript delves into various applications of AI across different imaging modalities, such as radiology, ultrasound, computed tomography, and magnetic resonance imaging. Examples of AI applications in each modality are provided, ranging from orthopaedics to internal medicine, cardiology, and more. Notable studies are discussed, demonstrating AI's potential for improved accuracy in detecting and classifying various abnormalities. The ethical considerations of using AI in veterinary diagnostics are also explored, highlighting the need for transparent AI development, accurate training data, awareness of the limitations of AI models, and the importance of maintaining human expertise in the decision-making process. The manuscript underscores the significance of AI as a decision support tool rather than a replacement for human judgement. In conclusion, this comprehensive manuscript offers an assessment of the current landscape and future potential of AI in veterinary diagnostic imaging. It provides insights into the benefits and challenges of integrating AI into clinical practice while emphasizing the critical role of ethics and human expertise in ensuring the wellbeing of veterinary patients.

Feasibility study of computed tomography texture analysis for evaluation of canine primary adrenal gland tumors

Objective

This study aimed to investigate the feasibility of computed tomography (CT) texture analysis for distinguishing canine adrenal gland tumors and its usefulness in clinical decision-making.

Materials and methods

The medical records of 25 dogs with primary adrenal masses who underwent contrast CT and a histopathological examination were retrospectively reviewed, of which 12 had adenomas (AAs), 7 had adenocarcinomas (ACCs), and 6 had pheochromocytomas (PHEOs). Conventional CT evaluation of each adrenal gland tumor included the mean, maximum, and minimum attenuation values in Hounsfield units (HU), heterogeneity of the tumor parenchyma, and contrast enhancement (type, pattern, and degree), respectively, in each phase. In CT texture analysis, precontrast and delayed-phase images of 18 adrenal gland tumors, which could be applied for ComBat harmonization were used, and 93 radiomic features (18 first-order and 75 second-order statistics) were extracted. Then, ComBat harmonization was applied to compensate for the batch effect created by the different CT protocols. The area under the receiver operating characteristic curve (AUC) for each significant feature was used to evaluate the diagnostic performance of CT texture analysis.

Results

Among the conventional features, PHEO showed significantly higher mean and maximum precontrast HU values than ACC (p < 0.05). Eight second-order features on the precontrast images showed significant differences between the adrenal gland tumors (p < 0.05). However, none of them were significantly different between AA and PHEO, or between precontrast images and delayed-phase images. This result indicates that ACC exhibited more heterogeneous and complex textures and more variable intensities with lower gray-level values than AA and PHEO. The correlation, maximal correlation coefficient, and gray level non-uniformity normalized were significantly different between AA and ACC, and between ACC and PHEO. These features showed high AUCs in discriminating ACC and PHEO, which were comparable or higher than the precontrast mean and maximum HU (AUC = 0.865 and 0.860, respectively).

Conclusion

Canine primary adrenal gland tumor differentiation can be achieved with CT texture analysis on precontrast images and may have a potential role in clinical decision-making. Further prospective studies with larger populations and cross-validation are warranted.

Preemptively planned en bloc resection of an extensive right adrenal pheochromocytoma involving the right hepatic division, caval thrombus and segmental caudal vena cava in a dog with Budd-Chiari-like syndrome

BACKGROUND

Surgical resection is the treatment of choice for canine adrenal pheochromocytomas (PHEOs). Information on en bloc resection of adrenal PHEO with tumour thrombus, right hepatic division and segmental caudal vena cava (CVC) running through the adrenal tumour and right hepatic division is limited.

OBJECTIVE

To describe the preemptively planned en bloc resection of an extensive right adrenal PHEO involving the right hepatic division, the caval thrombus and the segmental CVC in a dog with Budd-Chiari-like syndrome (BCLS).

METHODS

A 13-year-old castrated male miniature dachshund was referred for surgical treatment due to anorexia, lethargy and severe abdominal distension caused by abundant ascites. Preoperative computed tomography (CT) revealed a large mass in the right adrenal gland with a large caval thrombus obstructing the CVC and hepatic veins, which caused BCLS. Additionally, collateral vessels were formed between the CVC and azygos veins. No findings suggested obvious metastases. Based on CT findings, an en bloc resection of the adrenal tumour with caval thrombus, right hepatic division and segmental CVC was planned.

RESULTS

The preoperatively planned resection was feasible; the tumour was completely resected grossly. The operation time and total Pringle manoeuvre time were 162 min and 16 min 56 s, respectively. There was no postoperative hindlimb oedema, renal dysfunction, ascites or abdominal distention. The patient's clinical signs, including appetite, fully improved. Hospitalization lasted 16 days. However, the patient died on the 130th postoperative day due to suspected metastases and cachexia.

CONCLUSIONS

Even in case of an extensive infiltration of adrenal PHEO causing BCLS, an en bloc resection might be successfully achieved based on the preoperative CT findings speculating the collateral vessels formed for caudal venous return.

Anatomical variations of the canine adrenal vessels

The canine adrenal glands receive blood from the celiac artery, cranial mesenteric artery, caudal phrenic artery, cranial abdominal artery, phrenicoabdominal trunk, abdominal aorta, renal artery and lumbar artery. These are classified into three types: cranial, middle and caudal adrenal branches. It is also known that the adrenal vein flows into the phrenicoabdominal vein. However, individual differences in the branching pattern of adrenal vessels have not been systematically analysed. We evaluated adrenal vessels in dogs that underwent contrast-enhanced abdominal computed tomography (CT). There were 255 arteries travelling to the adrenal glands in 47 cases, with 1-6 arteries travelling per adrenal gland. The arteries included 67 caudal phrenic arteries, 62 aortic arteries, 60 cranial abdominal arteries, 39 renal arteries, 12 phrenicoabdominal trunks, 8 cranial mesenteric arteries, 6 celiac arteries and 1 lumbar artery. Most of the branches were from the aorta and caudal phrenic artery on the left side, and the cranial abdominal and caudal phrenic artery on the right side. A total of 110 adrenal veins were identified. Inflow into the phrenicoabdominal vein and into the right and left renal veins was observed, and we identified no inflow into other veins. This study demonstrated two points: laterality and individual differences in adrenal blood vessels. When evaluating adrenal blood vessels with abdominal contrast-enhanced CT, it is recommended to take images under general anaesthesia with breath-holding and observe them using multiplanar reconstruction.