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Automatic protocol for quantifying the vasoconstriction in blood vessel images
Xuelin Xu1,2, Lisheng Lin1, Buhong Li1
1MOE Key Laboratory of OptoElectronic Science and Technology for Medicine, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou, 350117, China.
Abstract:
Vascular targeted photodynamic therapy (V-PDT) has been successfully utilized for various vascular-related diseases. To optimize the PDT dose and treatment protocols for clinical treatments and to elucidate the biological mechanisms for V-PDT, blood vessels in the dorsal skin-fold window chamber (DSWC) of nude mice are often chosen to perform in vivo studies. In this study, a new automatic protocol to quantify the vasoconstriction of blood vessels in the DSWC model is proposed, which focused on tracking the pixels of blood vessels in pre- V-PDT images that disappear after V-PDT. The disappearing pixels indicate that the blood vessels were constricted, and thus, the vasoconstriction image for pixel distribution can be constructed. For this, the image of the circular region of interest was automatically extracted using the Hough transform. In addition, the U-Net model is employed to segment the image, and the Speeded-Up Robust Features algorithm to automatically register the segmented pre- and post- V-PDT images. The vasoconstriction of blood vessels in the DSWC model after V-PDT is directly quantified, which can avoid by the potential of generating new capillaries. The accuracy, sensitivity and specificity of the U-Net model for image segmentation are 90.64%, 80.12% and 92.83%, respectively. A significant difference in vasoconstriction between a control and a V-PDT group was observed. This new automatic protocol is well suitable for quantifying vasoconstriction in blood vessel image, which holds the potential application in V-PDT studies.
Insights
A new automated method quantifies blood vessel constriction after vascular targeted photodynamic therapy (V-PDT) in mice. This technique precisely measures V-PDT effects, aiding in optimizing treatments and understanding mechanisms.
Area of Science:
- Biomedical Engineering
- Photodynamic Therapy
- Vascular Biology
Background:
- Vascular targeted photodynamic therapy (V-PDT) is used for vascular diseases.
- Optimizing V-PDT requires understanding its effects on blood vessels.
- The dorsal skin-fold window chamber (DSWC) model in mice is crucial for in vivo V-PDT research.
Purpose of the Study:
- To develop an automated protocol for quantifying blood vessel vasoconstriction after V-PDT.
- To accurately measure V-PDT-induced changes in blood vessels within the DSWC model.
- To provide a tool for optimizing V-PDT protocols and elucidating biological mechanisms.
Main Methods:
- Utilized the DSWC model in nude mice for in vivo V-PDT studies.
- Developed an automated protocol tracking pixel changes in pre- and post-V-PDT images.
- Employed Hough transform for region extraction, U-Net for image segmentation, and Speeded-Up Robust Features for image registration.
Main Results:
- Achieved high accuracy (90.64%), sensitivity (80.12%), and specificity (92.83%) with the U-Net model for image segmentation.
- Successfully quantified vasoconstriction by tracking disappearing pixels, indicating constricted blood vessels.
- Observed a significant difference in vasoconstriction between V-PDT and control groups.
Conclusions:
- The proposed automated protocol accurately quantifies blood vessel vasoconstriction in the DSWC model.
- This method offers a reliable tool for V-PDT research, avoiding potential issues like new capillary generation.
- The protocol has potential applications in optimizing clinical V-PDT treatments and advancing mechanistic studies.
