# Assessment of Skin Deep Layer Biochemical Profile Using Spatially Offset Raman Spectroscopy
## 1 Introduction  
Skin cancer is currently the most common type of cancer in Caucasian populations with annual estimates of cases and deaths to be constantly rising (more than 7000 deaths in the USA for 2019) [1]. The three main skin cancer types are basal cell carcinoma, squamous cell carcinoma and melanoma, named after the skin cell where the cancer initially develops and varying in recurrence rate and metastatic nature. Non-melanoma cancers [2] derive either from the innermost layer of the epidermis (basal cell layer) forming basal cell carcinoma or from the upper part of the epidermis (squamous cells), resulting in the squamous cell carcinoma. Melanoma on the other hand develops in the skin's melanocytes, which reside at the dermal-epidermal junction [3]. The current gold standard for the clinical diagnosis of skin cancer is based on visual examination followed by biopsy. However, the accuracy of diagnosis can vary depending on the clinician, experience and training [4]. Additionally, biopsy removal remains an invasive procedure and cannot be used for the spatial evaluation of tumor growth or asoften as required for lesion monitoring with time. Therefore, there is imminent need for a non-invasive approach able to effectively assess the tumor growth and spread. Raman spectroscopy (RS) is an emerging group of non-invasive and highly chemically specific techniques relying on light-matter interaction to provide information of the sample (i.e., skin cells) on a molecular level. Among numerous biomedical applications [5; 6], Raman spectroscopy has been extensively employed to skin cancer diagnosis with most of the studies involving measuring skin tissue of various pathologies ex vivo [7; 8], and real-time in vivo skin measurements [9]. Although, depending on the skin cancer type, the origin of the cancer can be found in different depths of the tissue, most recent studies are focused on the surface of the skin using confocal measurements where better resolution and therefore, malignancy discrimination, can be achieved [10]. Deep Raman spectroscopy and specifically Spatially Offset Raman Spectroscopy (SORS), is a relatively recent development [11] able to look deeper inside the skin tissue and collect Raman photons with a bias towards deeper skin layers where skin cancer initially spreads. In SORS measurements, the excitation and collection area on the sample surface are decoupled and the distance between them (which is defined as the \"offset\") tends to correlate with the depth of Raman photon origin [12]. In vivo SORS measurements on humans have currently recovered bone signal underneath the skin [13] using an inverse SORS system, and glucose in the blood below the epidermis using defocused Raman [14] which is also a SORS variant. Although SORS measurements have demonstrated the potential of assessing the quality of deeper layers of salmon skin itself [15], similar measurements have never been performed on human skin before. The most relevant reports to our study include the in vivo employment of Raman fiber probes which are able to probe a greater depth in the sample compared to typical microscopy, reportedly up to 200 \(\upmu\)m in the skin [16; 17; 18]. However, none of those studies employed a spatially offset mode to explore the skin deep layer profile with a potential applicability to skin cancer screening. Unlike breast cancer studies where SORS has been successfully applied to recover a signal of in tissue-depth suspicious calcifications [19], it remains unclear whether there is a benefit for the deep Raman modality to be employed in the case of skin cancer. This is mainly due to the lack of a specific biomarker of adequate concentration and strong Raman scattering cross-section (comparable with calcifications, bone, or glucose in blood) which spontaneous RS would be able to pick up through the skin. In this study we attempt a novel approach to explore the skin biochemical profile with a potential applicability to skin cancer screening by employing both human skin tissue and equivalent phantoms.