Journal of neuroscience methods · 2026
A software based, minimally invasive validated image processing approach for the visualization of blood flow dynamics in mice.
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İnan Tolga, Doğru Mehmet Tolga, Sara Mehmet Yıldırım, Bolay Belen Hayrunnisa, Dileköz Ergin
Аннотация
BACKGROUND: The blood flow changes due to various physiological or pathological causes represent the response of the CNS for the maintenance of metabolic and functional requirements of the brain and related structures. Visualization of blood dynamics can enable the monitoring of crucial responses of neuronal tissue and the vasculature to multiple stimuli or insults. Here, we propose an inexpensive and feasible method that can be easily implemented to observe cerebral blood flow dynamics and for heart rate estimation in mice.
NEW METHODS: We developed a custom, MATLAB-based image processing software running at the pixel level to estimate regional cerebral blood flow (CBF) changes from acquired RGB images, also capable of modeling simultaneously operating Laser Doppler Flowmetry (LDF) readouts and heart rate estimation in mice.
RESULTS: Proposed method clearly enabled the visualization of vascular changes associated with cortical spreading depolarizations (CSD) induced in mice. The analysis of RGB intensity variations within pre-definable ROIs allowed the quantitative comparison of blood flow changes. The employment of an artificial neural network (ANN) yielded to successful approximation to simultaneously acquired LDF readings. The heart rates of the mice were also calculated within close proximity to those of obtained by ECG.
COMPARISON WITH EXISTING METHODS: Our method can help reduce the expenses of blood flow monitoring, where previously described methods are not readily accessible, with additional benefit of heart rate estimation in mice.
CONCLUSION: This study suggests a cost-effective and efficient approach for monitoring vascular responses where applicable in relevant research areas.
NEW METHODS: We developed a custom, MATLAB-based image processing software running at the pixel level to estimate regional cerebral blood flow (CBF) changes from acquired RGB images, also capable of modeling simultaneously operating Laser Doppler Flowmetry (LDF) readouts and heart rate estimation in mice.
RESULTS: Proposed method clearly enabled the visualization of vascular changes associated with cortical spreading depolarizations (CSD) induced in mice. The analysis of RGB intensity variations within pre-definable ROIs allowed the quantitative comparison of blood flow changes. The employment of an artificial neural network (ANN) yielded to successful approximation to simultaneously acquired LDF readings. The heart rates of the mice were also calculated within close proximity to those of obtained by ECG.
COMPARISON WITH EXISTING METHODS: Our method can help reduce the expenses of blood flow monitoring, where previously described methods are not readily accessible, with additional benefit of heart rate estimation in mice.
CONCLUSION: This study suggests a cost-effective and efficient approach for monitoring vascular responses where applicable in relevant research areas.