Background Coronary artery disease (CAD) is the number one cause of death in the U.S. [1]. 720,000 Americans are projected to undergo coronary attacks in 2014. 215,000 of these attacks are expected to be repeat episodes [2], which implies a deficiency in the current CAD percutaneous coronary interventions. Angioplasty and stenting are the most common treatment options, but these methods can trigger an injury response, swelling, and restenosis. Currently, the outcomes of alternative plaque removing treatments like excimer atherectomy or mechanical atherectomy are similar to stenting, so their use has been limited to procedures not well suited for balloon angioplasty and stenting [3]. The creation of an accurate and reliable tissue-identification sensor may enable the control of atherectomy procedures by verifying that the tissue in the ablation zone is the correct tissue to remove in between each laser pulse. A sensor with this capability would increase the safety and effectiveness of minimally invasive interventions. An optics-based sensor may be the most suited for direct application as it could utilize the optical fibers already present in the laser atherectomy catheters. Additionally, evidence suggests that fiber-optic diffuse reflectance spectroscopy (DRS) provides an accurate means of classifying tissue. The sensitivities and specificities for Stelzle et al. are generally around 90% and reach 100% for certain tissue pairs (e.g., fat and muscle) [4]. Rocha et al. provided and reviewed some of the strongest evidence that this can be used to distinguish atherosclerotic plaque and healthy tissue [5]. Accounting for contact force, however, still remains a challenge, as it can significantly alter DRS spectra [6]. Building on the prior art mentioned above and our previous investigations [7], this work aims to explore the ability of contact DRS to discriminate tissue-specific spectra under typical intravascular conditions such as variable-contact force, the inclusion of ablation effects, and immersion in blood or saline.