Wound Imaging Study to Gather Clinical References for a Device to Assist Selecting Level-of-amputation in PAD Patients

Amputation Wound, Peripheral Arterial Disease

peripheral arterial disease, re-amputation, optical imaging, Computer Assisted Detection (CADe)

This is a proof-of-concept study to collect images to train a CADe algorithm to predict the correct level of amputation in individuals scheduled for amputation secondary to PAD.

SpectralMD has developed an imaging device (DeepView), which simultaneously performs multispectral imaging (MSI) measurements across the visible and infrared spectrum to obtain a quantitative tissue viability assessment. These optical measurements are integrated using a CADe algorithm to categorize microvascular blood flow and provide a quantitative assessment to aid in selecting the appropriate amputation site. The investigators intend to gather data to train the CADe algorithm to predict ultimate healing status of tissue in the lower extremities of individuals suffering from peripheral arterial disease (PAD). The investigators will demonstrate the feasibility of using such an algorithm to accurately predict the location and extent of small vessel disease prior to amputation. Eventually, the invesitgators expect the DeepView to reduce the rate of re-amputation in patients with peripheral arterial disease if used for routine assessment of patients prior to amputation. The aims of the study are as follows: * Evaluate performance of a Computer Assisted Detection (CADe) algorithm trained to assist selecting the level-of-amputation in patients with PAD. * Identify multispectral signatures that are strongly predictive of viable skin tissue at proposed amputation sites. * Create a representative database for training the CADe algorithm.

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United States