Capillary rarefaction: an early marker of microvascular disease in young hemodialysis patients

Edwards-Richards, Alcia; DeFreitas, Marissa; Katsoufis, Chryso; Seeherunvong, Wacharee; Sasaki, Nao; Freundlich, Michael; Zilleruelo, Gastón; Abitbol, Carolyn

doi:10.1093/ckj/sfu106

Cited by 29 publications

(17 citation statements)

References 32 publications

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“…However, our pediatric patients were not hypertensive and had no classical risk factors for atherosclerosis beyond CKD5 or other age-related comorbidities that might impact the microcirculation. The rarefaction of microvessels of children of all age groups in the omentum, an adipose tissue, in the absence of hypertension could indicate a systemic CKD-induced pathogenesis, and this contention is supported by the finding of microvascular rarefaction in rats with experimental uremia [7, 8, 26] and in the skin [7, 10] and retina [14–17] of patients with CKD. In this perspective, reduced capillary density in CKD patients demonstrated post mortem in the myocardium [11], might be part of a systemic “uremic” microangiopathy and might help explain the extremely high mortality from CVD [27].…”

Section: Discussionmentioning

confidence: 95%

“…Capillary rarefaction was documented in animals with experimental CKD in the myocardium [6, 7] and in the skeletal muscle [8]. Studies of the peripheral microcirculation in patients with CKD stage 3–5 using nailfold microscopy have likewise shown reduced capillary density [9, 10]. In a postmortem study, myocardial capillary density was reduced by almost 50% in dialyzed patients compared to normotensive non-CKD controls [11].…”

Section: Introductionmentioning

confidence: 99%

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Reduced Microvascular Density in Omental Biopsies of Children with Chronic Kidney Disease

et al. 2016

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BackgroundEndothelial dysfunction is an early manifestation of cardiovascular disease (CVD) and consistently observed in patients with chronic kidney disease (CKD). We hypothesized that CKD is associated with systemic damage to the microcirculation, preceding macrovascular pathology. To assess the degree of “uremic microangiopathy”, we have measured microvascular density in biopsies of the omentum of children with CKD.Patients and MethodsOmental tissue was collected from 32 healthy children (0–18 years) undergoing elective abdominal surgery and from 23 age-matched cases with stage 5 CKD at the time of catheter insertion for initiation of peritoneal dialysis. Biopsies were analyzed by independent observers using either a manual or an automated imaging system for the assessment of microvascular density. Quantitative immunohistochemistry was performed for markers of autophagy and apoptosis, and for the abundance of the angiogenesis-regulating proteins VEGF-A, VEGF-R2, Angpt1 and Angpt2.ResultsMicrovascular density was significantly reduced in uremic children compared to healthy controls, both by manual imaging with a digital microscope (median surface area 0.61% vs. 0.95%, p<0.0021 and by automated quantification (total microvascular surface area 0.89% vs. 1.17% p = 0.01). Density measured by manual imaging was significantly associated with age, height, weight and body surface area in CKD patients and healthy controls. In multivariate analysis, age and serum creatinine level were the only independent, significant predictors of microvascular density (r2 = 0.73). There was no immunohistochemical evidence for apoptosis or autophagy. Quantitative staining showed similar expression levels of the angiogenesis regulators VEGF-A, VEGF-receptor 2 and Angpt1 (p = 0.11), but Angpt2 was significantly lower in CKD children (p = 0.01).ConclusionsMicrovascular density is profoundly reduced in omental biopsies of children with stage 5 CKD and associated with diminished Angpt2 signaling. Microvascular rarefaction could be an early systemic manifestation of CKD-induced cardiovascular disease.

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Section: Discussionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Reduced Microvascular Density in Omental Biopsies of Children with Chronic Kidney Disease

et al. 2016

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“…These hallmarks of the Alzheimer's disease, can lead to aberrant remodeling of the blood vessels 1,[6][7][8] . Consequently, capillary rarefaction is frequently used as a marker for vascular damages 9 . Thus, quantitative analysis of the entire brain vasculature including the capillary bed is pivotal to develop a better understanding of physiological and pathological brain function.…”

Section: Introductionmentioning

confidence: 99%

Automated analysis of whole brain vasculature using machine learning

Schoppe

et al. 2019

Preprint

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Tissue clearing methods enable imaging of intact biological specimens without sectioning. However, reliable and scalable analysis of such large imaging data in 3D remains a challenge. Towards this goal, we developed a deep learning-based framework to quantify and analyze the brain vasculature, named Vessel Segmentation & Analysis Pipeline (VesSAP). Our pipeline uses a fully convolutional network with a transfer learning approach for segmentation. We systematically analyzed vascular features of the whole brains including their length, bifurcation points and radius at the micrometer scale by registering them to the Allen mouse brain atlas. We reported the first evidence of secondary intracranial collateral vascularization in CD1-Elite mice and found reduced vascularization in the brainstem as compared to the cerebrum. VesSAP thus enables unbiased and scalable quantifications for the angioarchitecture of the cleared intact mouse brain and yields new biological insights related to the vascular brain function.

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“…Thus, a measurement of microvascular sO 2 can indirectly assess local tissue oxygenation and metabolic function. Alterations to local oxygenation levels are manifested in diseases including cancer, diabetes mellitus, inflammatory processes, and so on [1][2][3][4][5]. In the case of tumor development and diabetes mellitus, angiogenesis is induced by local hypoxia and can be reflected by abnormal local oxygenation levels.…”

Section: Introductionmentioning

confidence: 99%

Quantitative quality-control metrics for in vivo oximetry in small vessels by visible light optical coherence tomography angiography

Liu¹,

Song²,

Backman³

et al. 2019

Biomed. Opt. Express

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Biological functions rely on local microvasculature to deliver oxygen and nutrients and carry away metabolic waste. Alterations to local oxygenation levels are manifested in diseases including cancer, diabetes mellitus, etc. The ability to quantify oxygen saturation (sO 2) within microvasculature in vivo to assess local tissue oxygenation and metabolic function is highly sought after. Visible light optical coherence tomography (vis-OCT) angiography has shown promise in reaching this goal. However, achieving reliable measurements in small vessels can be challenging due to the reduced contrast and requires data averaging to improve the spectral data quality. Therefore, a method for quality-control of the vis-OCT data from small vessels becomes essential to reject unreliable readings. In this work, we present a quantitative metrics to evaluate the spectral data for a reliable measurement of sO 2 , including angiography signal to noise ratio (SNR), spectral anomaly detection and discard, and theory-experiment correlation analysis. The thresholds for each quantity can be flexibly adjusted according to different applications and system performance. We used these metrics to measure sO 2 of C57BL/6J mouse lower extremity microvasculature and validated it by introducing hyperoxia for expected sO 2 changes. After validation, we applied this protocol on C57BL/6J mouse ear microvasculature to conduct in vivo small blood vessel OCT oximetry. This work seeks to standardize the data processing method for in vivo oximetry in small vessels by vis-OCT.

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Capillary rarefaction: an early marker of microvascular disease in young hemodialysis patients

Cited by 29 publications

References 32 publications

Reduced Microvascular Density in Omental Biopsies of Children with Chronic Kidney Disease

Reduced Microvascular Density in Omental Biopsies of Children with Chronic Kidney Disease

Automated analysis of whole brain vasculature using machine learning

Quantitative quality-control metrics for in vivo oximetry in small vessels by visible light optical coherence tomography angiography

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