Cancer is one of the leading causes of death throughout the world. Advancements in early and improved diagnosis could help prevent a significant number of these deaths. Raman spectroscopy is a vibrational spectroscopic technique which has received considerable attention recently with regards to applications in clinical oncology. Raman spectroscopy has the potential not only to improve diagnosis of cancer but also to advance the treatment of cancer. A number of studies have investigated Raman spectroscopy for its potential to improve diagnosis and treatment of a wide variety of cancers. In this paper the most recent advances in dispersive Raman spectroscopy, which have demonstrated promising leads to real world application for clinical oncology are reviewed. The application of Raman spectroscopy to breast, brain, skin, cervical, gastrointestinal, oral, and lung cancers is reviewed as well as a special focus on the data analysis techniques, which have been employed in the studies. 1. Introduction Cancer continues to persist as one of the most common causes of death throughout the world and remains the second leading cause of death in the United States [1]. This rise in cost coincides with estimates that 1,529,560 new cases of cancer were diagnosed, and 569,490 cancer-related deaths had occurred in 2010 in the US alone [2]. There has been some slight progress recently with recent studies showing a decrease in cancer incidence of 1.7% during the recent period of 2001–2005; and some cancers such as breast cancer have shown a reduction in cancer related mortality over the last 10 years. However, much more progress is needed to improve diagnosis and treatment of cancer in order to ultimately reduce cancer-related suffering and death. Research for cancer diagnosis and treatment has continued to yield advances in chemotherapy regimens, radiation therapy, surgical procedures, and imaging technologies. Biomedical imaging modalities such as magnetic resonance imaging (MRI), positron emission tomography (PET), and computed tomography (CT) for cancer diagnosis have progressed significantly in recent decades [3]. Using these imaging modalities, surgeons have been able to perform surgical procedures with greatly improved accuracy in location of lesions and adjacent anatomical structures yielding better outcomes. However, these conventional modalities have drawbacks, particularly in regards to intraoperative use. Thus, current research has presented an increasing focus on the biomedical applications of optical imaging technologies, known as biophotonics, for clinical
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