VAMPIRE® fundus image analysis algorithms: Validation and diagnostic relevance in hypertensive cats
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Published on: February 15, 2022
Alessandro Cirla1,2, Michele Drigo3, Lucia Ballerini4
1Department of Ophthalmology, San Marco Veterinary Clinic and Laboratory, Veggiano, Italy.
Insights
The VAMPIRE® software effectively diagnoses feline hypertension by analyzing retinal vasculature. This tool objectively measures changes in feline retinal arteries and veins, aiding in early detection of systemic hypertension.
Area of Science:
- Veterinary Ophthalmology
- Comparative Medicine
- Medical Imaging Analysis
Background:
- Systemic hypertension in cats can lead to significant ocular complications.
- Objective diagnostic tools are needed to assess retinal vascular changes in feline hypertension.
- The VAMPIRE® (Vascular Assay and Measurement Platform for Images of the Retina) software, developed for human use, has potential applications in veterinary medicine.
Purpose of the Study:
- To validate the VAMPIRE® software for analyzing feline retinal vasculature.
- To assess the clinical utility of VAMPIRE® in identifying hypertensive cats.
- To investigate the correlation between retinal vascular parameters and systemic hypertension in felines.
Main Methods:
- 105 healthy cats (normal group) and 43 hypertensive cats (clinical group) were enrolled.
- Digital retinal images were analyzed using VAMPIRE® software, measuring 11 vascular points (veins, arteries, bifurcations).
- Repeatability and reproducibility were assessed by two independent operators; data analyzed using Mann-Whitney and Tukey box plots (P < 0.05).
Main Results:
- 210 retinal images yielded 2310 measurements; mean vein diameter was 9.1 pixels, mean artery diameter was 6.1 pixels.
- Arteriolar bifurcation angles averaged 73.6°, 76.9°, and 85.4° for first, second, and third bifurcations, respectively.
- Hypertensive cats showed significantly reduced arteriolar diameter (3.3 pixels) and branch angles (55°, 47.8°, 59.9°) with increased vein diameter (24.15 pixels) compared to healthy cats.
Conclusions:
- The VAMPIRE® algorithm is a viable tool for objective diagnosis of retinal vascular changes in cats.
- The software demonstrated clinical utility in differentiating hypertensive from healthy feline subjects.
- VAMPIRE® can serve as an additional diagnostic aid for feline systemic hypertension, extending human medical imaging techniques to veterinary applications.
Objectives:
To validate a retinal imaging software named VAMPIRE® (Vascular Assay and Measurement Platform for Images of the Retina) in feline patients and test the clinical utility in hypertensive cats.
Animals Studied:
One hundred and five healthy cats were enrolled. They represented the normal dataset used in the validation (group 1). Forty-three hypertensive cats with no noticeable retinal abnormalities were enrolled for the clinical validity of the software (group 2).
Procedures:
Eleven points (4 veins, 4 arteries, and 3 arterial bifurcations) were measured for each digital image. Repeatability and reproducibility of measurements were assessed using two independent operators. Data were statistically analyzed by the Mann-Whiney and Tukey box plot. Significance was considered when P < 0.05.
Results:
Two hundred and ten retinal images were analyzed for a total of 2310 measurements. Total mean was 9.1 and 6.1 pixels for veins and arteries, respectively. First, second, and third arteriolar bifurcations angles were 73.6°, 76.9°, and 85.4°, respectively. A comparison between groups 1 and 2 showed a statistically significant reduction in arteriolar diameter (mean 3.3 pixels) and branch angle (55°, 47.8° and 59.9°) associated with increasing vein diameter (mean 24.15 pixels).
Conclusions:
Current image analysis techniques used in human medicine were investigated in terms of extending their use to veterinary medicine. The VAMPIRE® algorithm proved useful for an objective diagnosis of retinal vasculature changes secondary to systemic hypertension in cats, and could be an additional diagnostic test for feline systemic hypertension.
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Data Validation
Key parameters for method validation include:

