Arteriolar dysgenesis in ischemic-regenerating skeletal muscle revealed by automated micromorphometry, computational modeling, and perfusion analysis.
Yiwen XuAaron D WardDaniel GoldmanHao YinJohn-Michael ArpinoZengxuan NongJason J LeeCaroline O'NeilJ Geoffrey PickeringPublished in: American journal of physiology. Heart and circulatory physiology (2022)
Rebuilding the local vasculature is central to restoring the health of muscles subjected to ischemic injury. Arteriogenesis yields remodeled collateral arteries that circumvent the obstruction, and angiogenesis produces capillaries to perfuse the regenerating myofibers. However, the vital intervening network of arterioles that feed the regenerated capillaries is poorly understood and is an investigative challenge. We used machine learning and automated micromorphometry to quantify the arteriolar landscape in distal hindlimb muscles in mice that have regenerated after femoral artery excision. Assessment of 1,546 arteriolar sections revealed a striking (>2-fold) increase in arteriolar density in regenerated muscle 14 and 28 days after ischemic injury. Lumen caliber was initially similar to that of control arterioles but after 4 wk lumen area was reduced by 46%. In addition, the critical smooth muscle layer was attenuated throughout the arteriolar network, across a 150- to 5-µm diameter range. To understand the consequences of the reshaped distal hindlimb arterioles, we undertook computational flow modeling, which revealed blunted flow augmentation. Moreover, impaired flow reserve was confirmed in vivo by laser-Doppler analyses of flow in response to directly applied sodium nitroprusside. Thus, in hindlimb muscles regenerating after ischemic injury, the arteriolar network is amplified, inwardly remodels, and is diffusely undermuscularized. These defects and the associated flow restraints could contribute to the deleterious course of peripheral artery disease and merit attention when considering therapeutic innovations. NEW & NOTEWORTHY We report a digital pipeline for interrogating the landscape of arterioles in mouse skeletal muscle, using machine learning and automated micromorphometry. This revealed that in muscle regenerating after ischemic injury, the arteriolar density is increased but lumen caliber and smooth muscle content are reduced. Computational modeling and experimental validation reveal this arteriolar network to be functionally compromised, with diminished microvascular flow reserve.
Keyphrases
- smooth muscle
- skeletal muscle
- machine learning
- single cell
- ischemia reperfusion injury
- deep learning
- peripheral artery disease
- high throughput
- insulin resistance
- healthcare
- public health
- cerebral ischemia
- magnetic resonance imaging
- artificial intelligence
- magnetic resonance
- minimally invasive
- computed tomography
- type diabetes
- big data
- social media
- gene expression
- risk assessment
- network analysis
- high speed
- optical coherence tomography
- human health