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# Structural imaging and characterization of the arterial wall and its perivascular adipose tissue

Aïcha Ben Zemzem, Laetitia Vanalderwiert, Xiaowen Liang, Sébastien Blaise, Timm Weitkamp, Manuel Dauchez, Nicolas Passat, Laurent Debelle, Sébastien Almagro

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To cite this version:

Aïcha Ben Zemzem, Laetitia Vanalderwiert, Xiaowen Liang, Sébastien Blaise, Timm Weitkamp, et al.. Structural imaging and characterization of the arterial wall and its perivascular adipose tissue. 17th SOLEIL Users' Meeting (SUM 2023), Jan 2023, Saint-Aubin, France. . hal-03946869

HAL Id: hal-03946869

https://hal.science/hal-03946869

Submitted on 27 Feb 2023

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# Structural imaging and characterization of the arterial wall and its perivascular adipose tissue

Aicha Ben Zemzem<fnref n="1" />, L. Vanalderwiert<fnref n="1" />, X. Liang<fnref n="1" />,<fnref n="2" />, S. Blaise<fnref n="1" />, T. Weitkamp<fnref n="3" />, M. Dauchez<fnref n="1" />, N. Passat<fnref n="2" />, L. Debelle<fnref n="1" /> and S. Almagro<fnref n="1" />.

## Introduction

Blood vessels possess a lumen, where blood circulates, and a wall made of fth ee layers: intima, media and adventitia. These tunica comprise cells surrounded by a dedicated extracellular matrix (ECM) providing scaffolding and structural support for them. Elastin is the ECM protein imparting elasticity to the arterial wall. Its abundan tin the media layer. Besides, the arteries are surrounded by perivascular adipose tissue (PVAT) also providing mechanical support to the vascular wall and controlling vascular physiology (1). PVAT is essential to maintain vascular hemostasis both mechanically and by endocrine/paracrine ways.

Aging is an important risk factor for cardiovascular diseases development. In pathological and physiological conditions, aging is also associated with both ECM(2) and PVAT loss offunctions, due to remodeling and expansion respectively.

## Objectives

Vascular pathologies are accompanied by structural and functional modifications which affects the arterial wall and PVAT. The aim of the present study is to determine how ECM remodeling occurs during healthy and pathological aging by detecting, measuring and quantifying faint structural modifications in the arterial wall(3), and surrounding PVAT.

## Materials and methods

### Samples

* 6-months old male C57BL6 mice (control, db/db).

* Aorta were harvested as follows: after euthanasia, heparin was injected. Heart and aorta were then flushed with PBS using a syringe driver to remove residual blood. The aorta was prefixed for 5 min. After that time, low melting agarose was injected.

* Fixation of heart, aorta and PVAT for 24-48 h.

* Paraffin embedding.

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### Image acquisition and reconstruction

a) Imaging segments of aorta using synchrotron X-ray micro-computed tomography without contrast agent in different anatomical regions (thoracic vs abdominal aorta).

<figure><img src="image_5.png" /><figcaption>SOLEIL synchrotron</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>Sample paraffin embedding</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>Image acquisition</figcaption></figure>

b) Aorta reconstruction (0.65 µm, 2048 x 2048 pixels)

<figure><img src="image_8.png" /><figcaption>control</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>db/db</figcaption></figure>

## Results

### Image processing

We distinguish elastic structures in the arterial wall at a resolution and size never achieved before (0.65 µm) and we visualize PVAT ECM.

#### ☐ Arterial wall and PVAT segmentation

2D Segmentation

<figure><img src="image_10.png" /><figcaption>Artery wall + PVAT</figcaption></figure>

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /><figcaption>Underlying network (as a scaffold)</figcaption></figure>

Volume reconstruction

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

### Image analysis

#### ☐ Methods for assessing parameters

* Arterial wall: intensity profiles (more than 80k measurements / sample)

<figure><img src="image_15.png" /></figure>

<figure><img src="image_16.png" /></figure>

<figure><img src="image_17.png" /></figure>

* PVAT: density

Ratio =

network area
total area

#### ☐ Control vs diabetic

<figure><img src="image_18.png" /><figcaption>control</figcaption></figure>

<figure><img src="image_19.png" /></figure>

<figure><img src="image_20.png" /><figcaption>db/db</figcaption></figure>

<figure><img src="image_21.png" /></figure>

#### ☑ Our algorithm can extract information from the elastic structures:

* No significant differences are observed in elastic lamellae thickness between diabetic and control mice.

* In diabetics mice, lamellae are smooth and stretched while they are wavy in control mice.

* PVAT ECM network is denser and better structured in control mice.

* PVAT ECM density: 21.8 ± 2.4 % in controls 9.3 ± 1.1 % in diabetic mice.

* Expansion and degradation in diabetic mice.

## Discussion and conclusion

Tissue characterization is a fundamental tool for studying and diagnosing pathologies and lesions associated to the vascular tree. Our automatic algorithm is robust and permits the extraction of information from arterial structures. We can image a segment of aorta in 3D in a reproducible manner without cutting the sample. Our results show that important structural differences exist between vascular and PVAT ECM in diabetic vs control mice. These modifications support the view that the diabetic pathology precipitates vascular aging.

## Bibliography

1. Duca L, Blaise S, et al (2016) Matrix ageing and vascular impacts: focus on elastin fragmentation. *Cardiovasc Res* 110:298-308.

2. Brown NK, Zhou Z, et al (2014) Perivascular adipose tissue in vascular function and disease: a review of current research and animal models. *ATVB* 34:1621-30.

3. Ben Zemzem A, Genevaux A, et al (2021) X-ray microtomography reveals a lattice-like network within aortic elastic lamellae. *FASEB J* 35:e21844.

<footnote n="1">1. UMR CNRS 7369 Matrice Extracellulaire et Dynamique Cellulaire, SFR CAP Santé, Université de Reims Champagne Ardenne, UFR Sciences Exactes et Naturelles, moulin de la housse, BP 1039, 51687 Reims cedex 2, France.</footnote>

<footnote n="2">2. CReSTIC EA 3804, Université de Reims Champagne Ardenne, 51687 Reims cedex 2, France.</footnote>

<footnote n="3">3. Synchrotron SOLEIL 91192 Gil-sur-Yvette, France</footnote>