Pilot measurement of the microvascular blood flow of thyroid nodules by diffuse optics

Author(s):  
Giuseppe Lo Presti ◽  
Gloria Aranda ◽  
Davide Contini ◽  
Lorenzo Cortese ◽  
Alberto Dalla Mora ◽  
...  
2019 ◽  
Author(s):  
Gloria Aranda Velazquez ◽  
Giuseppe Lo Presti ◽  
Davide Contini ◽  
Lorenzo Cortese ◽  
Alberto Dalla Mora ◽  
...  

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Gloria Beatriz Aranda Velazquez ◽  
Giuseppe Lo Presti ◽  
Lorenzo Cortese ◽  
Davide Contini ◽  
Alberto Dalla Mora ◽  
...  

Abstract BACKGROUND: The most common tool to test malignancy in the study of thyroid nodules (NT) is ultrasound and fine needle aspiration biopsy (FNAB). However, the sensitivity and specificity of the method and the effectiveness in thyroid cancer are limited; therefore new methods to study thyroid nodules are required. In this way our goal is to introduce hybrid diffuse optical instruments that are capable to measure and discriminate altered microvascular blood flow, blood volume and tissue scattering coefficients of TN. Near-infrared diffuse optical technologies aim to overcome the shortcomings of present techniques while screening for malignant thyroid nodules for early and fast diagnosis of cancer. This idea was based on the previous experience in breast cancers with diffuse optical techniques. METHODS: We have developed a device based on near-infrared diffuse correlation spectroscopy (DCS), which is a technology aimed at retrieving the microvascular flow of a certain region of tissue by mean of low power near-infrared laser light, and used in combination with a commercial ultrasound system (US). In order to combine these devices, we have developed a probe enabling multimodal data acquisition and subsequently we have analyzed the optical properties and the blood flow index in the thyroid lobes of eleven subjects who presented a thyroid nodule. RESULTS: Four subjects have required FNAB: P4 and P7 were reported as being malignant (Bethesda VI and IV respectively) while P6 and P8 were evaluated as being benign (Bethesda II). Surgical removal confirmed papillary thyroid carcinoma in P4, while denied the result of FNAB for P7 (Multinodular thyroid hyperplasia). We have considered the contralateral lobe as intra-subject reference to validate the feasibility of the DCS system in a very absorbing tissue as thyroid is. The difference between the blood flow index of the nodule and the contralateral lobe is maximum for subject P4, while the difference in benign subjects is lower. T-test showed no significant difference between benign nodules and contralateral lobes. Subject P7 showed a small difference as for other benign subjects despite the FNAB results indicating presence of malignancy. CONCLUSION: Apparently diffuse optics technologies would be able to differentiate malignant thyroid nodules from benign thyroid nodules, but more measurements require confirming our preliminary results as that diffuse optical technology can complement the current techniques such as US and FNAB. A new measurement campaign is being scheduled with a completed, fully integrated device that was developed within the LUCA project (http://www.luca-project.eu).


Author(s):  
Rickson C. Mesquita ◽  
Turgut Durduran ◽  
Guoqiang Yu ◽  
Erin M. Buckley ◽  
Meeri N. Kim ◽  
...  

Diffuse optics has proven useful for quantitative assessment of tissue oxy- and deoxyhaemoglobin concentrations and, more recently, for measurement of microvascular blood flow. In this paper, we focus on the flow monitoring technique: diffuse correlation spectroscopy (DCS). Representative clinical and pre-clinical studies from our laboratory illustrate the potential of DCS. Validation of DCS blood flow indices in human brain and muscle is presented. Comparison of DCS with arterial spin-labelled MRI, xenon-CT and Doppler ultrasound shows good agreement (0.50< r <0.95) over a wide range of tissue types and source detector distances, corroborating the potential of the method to measure perfusion non-invasively and in vivo at the microvasculature level. All-optical measurements of cerebral oxygen metabolism in both rat brain, following middle cerebral artery occlusion, and human brain, during functional activation, are also described. In both situations, the use of combined DCS and diffuse optical spectroscopy/near-infrared spectroscopy to monitor changes in oxygen consumption by the tissue is demonstrated. Finally, recent results spanning from gene expression-induced angiogenic response to stroke care and cancer treatment monitoring are discussed. Collectively, the research illustrates the capability of DCS to quantitatively monitor perfusion from bench to bedside, providing results that match up both with literature findings and with similar experiments performed with other techniques.


Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1715-P
Author(s):  
KATHERINE ROBERTS-THOMSON ◽  
RYAN D. RUSSELL ◽  
DONGHUA HU ◽  
TIMOTHY M. GREENAWAY ◽  
ANDREW C. BETIK ◽  
...  

1996 ◽  
Vol 270 (5) ◽  
pp. H1696-H1703 ◽  
Author(s):  
D. Mitchell ◽  
K. Tyml

Nitric oxide (NO) has been shown to be a potent vasodilator released from endothelial cells (EC) in large blood vessels, but NO release has not been examined in the capillary bed. Because the capillary bed represents the largest source of EC, it may be the largest source of vascular NO. In the present study, we used intravital microscopy to examine the effect of the NO synthase inhibitor, NG-nitro-L-arginine methyl ester (L-NAME), on the microvasculature of the rat extensor digitorum longus muscle. L-NAME (30 mM) applied locally to a capillary (300 micron(s) from the feeding arteriole) reduced red blood cell (RBC) velocity [VRBC; control VRBC = 238 +/- 58 (SE) micron/s; delta VRBC = -76 +/- 8%] and RBC flux (4.4 +/- 0.7 to 2.8 +/- 0.7 RBC/s) significantly in the capillary, but did not change feeding arteriole diameter (Dcon = 6.3 +/- 0.7 micron, delta D = 5 +/- 7%) or draining venule diameter (Dcon = 10.1 +/- 0.6 micron, delta D = 4 +/- 2%). Because of the VRBC change, the flux reduction was equivalent to an increased local hemoconcentration from 1.8 to 5 RBCs per 100 micron capillary length. L-NAME also caused an increase in the number of adhering leukocytes in the venule from 0.29 to 1.43 cells/100 micron. L-NAME (30 mM) applied either to arterioles or to venules did not change capillary VRBC. Bradykinin (BK) locally applied to the capillary caused significant increases in VRBC (delta VRBC = 111 +/- 23%) and in arteriolar diameter (delta D = 40 +/- 5%). This BK response was blocked by capillary pretreatment with 30 mM L-NAME (delta VRBC = -4 +/- 27%; delta D = 5 +/- 9% after BK). We concluded that NO may be released from capillary EC both basally and in response to the vasodilator BK. We hypothesize that 1) low basal levels of NO affect capillary blood flow by modulating local hemoconcentration and leukocyte adhesion, and 2) higher levels of NO (stimulated by BK) may cause a remote vasodilation to increase microvascular blood flow.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ossama Mahmoud ◽  
Mahmoud El-Sakka ◽  
Barry G. H. Janssen

AbstractMicrovascular blood flow is crucial for tissue and organ function and is often severely affected by diseases. Therefore, investigating the microvasculature under different pathological circumstances is essential to understand the role of the microcirculation in health and sickness. Microvascular blood flow is generally investigated with Intravital Video Microscopy (IVM), and the captured images are stored on a computer for later off-line analysis. The analysis of these images is a manual and challenging process, evaluating experiments very time consuming and susceptible to human error. Since more advanced digital cameras are used in IVM, the experimental data volume will also increase significantly. This study presents a new two-step image processing algorithm that uses a trained Convolutional Neural Network (CNN) to functionally analyze IVM microscopic images without the need for manual analysis. While the first step uses a modified vessel segmentation algorithm to extract the location of vessel-like structures, the second step uses a 3D-CNN to assess whether the vessel-like structures have blood flowing in it or not. We demonstrate that our two-step algorithm can efficiently analyze IVM image data with high accuracy (83%). To our knowledge, this is the first application of machine learning for the functional analysis of microvascular blood flow in vivo.


2021 ◽  
Vol 117 ◽  
pp. 110241
Author(s):  
Alberto Coccarelli ◽  
Supratim Saha ◽  
Tanjeri Purushotham ◽  
K. Arul Prakash ◽  
Perumal Nithiarasu

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