Abstract
Peripheral arterial disease (PAD) is characterized by atherosclerotic blockages of the arteries supplying the lower extremities, which cause a progressive accumulation of ischemic injury to the skeletal muscles of the lower limbs. This injury includes altered metabolic processes, damaged organelles, and compromised bioenergetics in the affected muscles. The objective of this study was to explore the association of Raman spectral signatures of muscle biochemistry with the severity of atherosclerosis in the legs as determined by the Ankle Brachial Index (ABI) and clinical presentation. We collected muscle biopsies from the gastrocnemius (calf muscle) of five patients with clinically diagnosed claudication, five patients with clinically diagnosed critical limb ischemia (CLI), and five control patients who did not have PAD. A partial least squares regression (PLSR) model was able to predict patient ABI with a correlation coefficient of 0.99 during training and a correlation coefficient of 0.85 using a full cross‐validation. When using the first three PLS factor scores in combination with linear discriminant analysis, the discriminant model was able to correctly classify the control, claudicating, and CLI patients with 100% accuracy, using a full cross‐validation procedure. Raman spectroscopy is capable of detecting and measuring unique biochemical signatures of skeletal muscle. These signatures can discriminate control muscles from PAD muscles and correlate with the ABI and clinical presentation of the PAD patient. Raman spectroscopy provides novel spectral biomarkers that may complement existing methods for diagnosis and monitoring treatment of PAD patients.
Highlights
Peripheral arterial disease (PAD), characterized by atherosclerotic blockages of the arteries supplying the lower extremities in association with muscle damage and limb dysfunction, produces a considerable public health burden affecting 12–20% of Americans age 65 and older (Mahoney et al 2008, 2010; Roger et al 2011)
When using the first three PLS factor scores in combination with linear discriminant analysis a discriminant model is able to correctly classify the control, claudicating, and critical limb ischemia (CLI) patients with 100% accuracy
Evaluating the discriminant model performance and stability using a cross-validation procedure yielded 100% accuracy in patient classification
Summary
Peripheral arterial disease (PAD), characterized by atherosclerotic blockages of the arteries supplying the lower extremities in association with muscle damage and limb dysfunction, produces a considerable public health burden affecting 12–20% of Americans age 65 and older (Mahoney et al 2008, 2010; Roger et al 2011). Ankle Brachial Index (ABI, a measure of limb hemodynamics) is the standard, noninvasive method for diagnosing presence and severity of atherosclerotic blockages in arteries supplying the legs and for monitoring the hemodynamic effects of treatment interventions for PAD. Other more detailed methods of arterial assessment, such as ultrasonography and angiography (based on computerized tomography, magnetic resonance, or standard X-Raybased evaluation), are used by clinicians to evaluate patients with PAD. All of these methods, like ABI, focus on the diseased arterial tree and their main limitation is that they do not evaluate the effects of PAD on the chronically ischemic end-organ which is the leg and its muscles
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