Panoramic Nailfold Flow Velocity Measurement Method Based on Enhanced Plasma Gap Information.

Area of Science:

• Medical Imaging
• Vascular Biology
• Artificial Intelligence in Medicine

Background:

• Nailfold microcirculation examination is vital for diagnosing and assessing the severity of various diseases.
• Previous nailfold imaging had limited fields of view, hindering panoramic flow velocity measurements.
• Clinical demand for rapid results necessitates efficient, automated analysis of nailfold videos.

Purpose of the Study:

• To develop an efficient panoramic nailfold flow velocity measurement method.
• To address the limitations of small field-of-view equipment and manual video cropping.
• To provide quantitative indicators for vascular disease study and vascular health assessment.

Main Methods:

• A novel panoramic nailfold flow velocity measurement method based on enhanced plasma gap information.
• Utilized a deep learning model to decompose the panoramic measurement into individual vessel measurements.
• Employed frame differencing to enhance plasma gap positional movement information for improved accuracy.

Main Results:

• Achieved a high Pearson correlation coefficient (0.992) with expert manual calculations, indicating no significant difference.
• Demonstrated a low average error of 2.137% compared to expert measurements.
• Successfully obtained concurrent flow rate results for 13 nailfold blood vessels in feasibility experiments.

Conclusions:

• The proposed method offers an efficient and accurate solution for panoramic nailfold multi-vessel flow velocity measurement.
• It overcomes previous limitations, enabling rapid, automated analysis crucial for clinical applications.
• This technique supports the study of vascular diseases and the assessment of vascular health.