Monitoring microvascular perfusion variations with laser speckle contrast imaging using a view-based temporal template method

Enhancing blood flow prediction in multi-exposure laser speckle contrast imaging through ensemble learning with K-mean clustering

Purpose.Accurately visualizing and measuring blood flow is of utmost importance in maintaining optimal health and preventing the onset of various chronic diseases. One promising imaging technique that aids in visualizing perfusion in biological tissues is Multi-exposure Laser Speckle Contrast Imaging (MELSCI). MELSCI technique allows real-time quantitative measurements using multiple exposure times to obtain precise and reliable blood flow data. Additionally, the application of machine learning (ML) techniques can further enhance the accuracy of blood flow prediction in this imaging modality.Method.Our study focused on developing and evaluating Ensemble Learning ML techniques along with clustering algorithms for predicting blood flow rates in MELSCI. The effectiveness of these techniques was assessed using performance parameters, including accuracy, F1-score, precision, recall, specificity, and classification error rate.Result.Notably, the study revealed that Ensemble Learning with clustering emerged as the most accurate technique, achieving an impressive accuracy rate of 98.5%. Furthermore, it demonstrated a high recall of more than 91%, F1-score, the precision of more than 90%, higher specificity of 99%, and least classification error of 1.5%, highlighting its suitability and sustainability for flow prediction in MELSCI.Conclusion.The study's findings imply that Ensemble Learning can significantly contribute to enhancing the accuracy of blood flow prediction in MELSCI. This advancement holds substantial promise for healthcare professionals and researchers, as it facilitates improved understanding and assessment of perfusion within biological tissues, which will contribute to the maintenance of good health and prevention of chronic diseases.

Laser speckle contrast analysis (LASCA) technology for the semiquantitative measurement of angiogenesis in in-ovo-tumor-model

BACKGROUND

The process of angiogenesis is a key element for tumor growth and proliferation and therefore one of the determining factors for aggressiveness and malignancy. A better understanding of the underlying processes of tumor induced angiogenesis is crucial for superior cancer treatment. Furthermore, the PeriCam perfusion speckle imager (PSI) system high resolution (HR) model by PERIMED presents a noninvasive method for semi-quantitative measurement of blood perfusion, based on laser speckle contrast analysis (LASCA). Aim of the present study was to utilize the chick chorioallantoic membrane (CAM) model as an in-ovo-tumor-model which enables rapid neovascularization of tumors while allowing real-time observation of the microcirculation via LASCA.

METHODS

Fertilized chicken eggs were grafted with embryonal/alveolar rhabdomyosarcoma cells or primary sarcoma tumors. The blood perfusion was measured before and after tumor growth using LASCA. The procedure is accelerated and simplified through the integrated PIMSoft software which provides real-time graphs and color-coded images during the measurement.

RESULTS

Sarcoma cells and primary sarcoma tumors exhibited satisfactory growth processes on the CAM. LASCA visualized microcirculation accurately and enabled an extensive investigation of the angiogenic potential of sarcoma cells on the CAM. We were able to show that sarcoma cells and primary sarcoma tumors induced larger quantities of neovasculature on the CAM than the controls.

CONCLUSIONS

The utilization of LASCA for the investigation of tumor angiogenesis within the CAM model appears to be a highly beneficial, cost-efficient and easily practicable procedure. The proposed model can be used as a drug-screening model for individualized cancer therapy, especially with regards to anti-angiogenic agents.

Application of optical flow algorithms to laser speckle imaging

Since of its introduction in 1980s, laser speckle imaging has become a powerful tool in flow imaging. Its high performance and low cost made it one of the preferable imaging methods. Initially, speckle contrast measurements were the main algorithm for analyzing laser speckle images in biological flows. Speckle contrast measurements, also referred as Laser Speckle Contrast Imaging (LSCI), use statistical properties of speckle patterns to create mapped image of the blood vessels. In this communication, a new method named Laser Speckle Optical Flow Imaging (LSOFI) is introduced. This method uses the optical flow algorithms to calculate the apparent motion of laser speckle patterns. The differences in the apparent motion of speckle patterns are used to identify the blood vessels from surrounding tissue. LSOFI has better spatial and temporal resolution compared to LSCI. This higher spatial resolution enables LSOFI to be used for autonomous blood vessels detection. Furthermore, Graphics Processing Unit (GPU) based LSOFI can be used for quasi real time imaging.

Vascular architecture in free flaps: Analysis of vessel morphology and morphometry in murine free flaps

The aim of this study was to analyze the development of vascular architecture as well as vascular morphometry and morphology of anastomosed microvascular free flaps. Free pectoral skin flaps were raised in 25 rats and anastomosed to the femoral vessels in the groin region. CD31 immunohistology was performed after 3, 7 and 12 d (each 5 animals each) to analyze microvessel density (MVD), microvessel area (MVA) and microvessel size (MVS). Microvascular corrosion casting was performed after 7 and 12 d (5 animals each) to analyze vessel diameter (VD), intervascular distance (IVD), interbranching distance (IBD), and branching angle (BA). Further on, sprout and pillar density as hallmarks of sprouting and intussusceptive angiogenesis were analyzed. Pectoral skin isles from the contralateral side served as controls. A significantly increased MVD was found after 7 and 12 d (p each <0.001). MVA was significantly increased after 3, 7 and 12 d (p each <0.001) and a significantly increased MVS was analyzed after 3 and 7 d (p each <0.001). VD and IVD were significantly increased after 7 and 12 d (p each <0.001). For IBD, a significantly increase was measured after 7 d (p < 0.001). For IBA, sprout and pillar density, no significant differences were found (p each ≥0.05). Significant changes in the vascular architecture of free flaps after successful microvascular anastomosis were seen. Since there was no evidence for sprout and pillar formation within the free flaps, the increased MVD and flap revascularization might be induced by the receiving site.