## 1 Introduction  
Chondrosarcoma (CS) is the second most common form of primary bone tumor worldwide, with almost seven cases per million people registered every year [1]. In the continuous effort to introduce effective and minimally invasive therapies, the ability to grade CS and to distinguish this form of bone cancer from healthy tissues and/or benign tumors, such as enchondroma (EC), represents a crucial goal. The common protocol for the diagnosis of CS is based on an initial examination of radiological and/or magnetic resonance (MRI) images, followed by a histopathological analysis of a tissue biopsy. One of the drawbacks of this procedure is the frequent discrepancies between the response of pre- and post-surgicalhistopathological analysis, mainly due to the presence of tissue inhomogeneities within the same tumor mass. This last feature also determines the presence of not well-defined tumor margins, undoubtedly affecting the outcome of surgical therapies. As previously demonstrated [2], the presence of non-removed tumor margins represents a concrete risk factor, increasing the probability of recurrence and thus decreasing the 5-year survival rate. Setups for image-guided surgery, e.g., computed tomography (CT) and MRI have been introduced to help surgeons in maximizing the size of the excised tumor mass by preserving the surrounding healthy tissues. Despite the progress of these techniques, they still show weaknesses. In particular, CT is based on the use of ionizing radiation, with possible side effects for the patient and/or the operator. Furthermore, MRI employs intense magnetic fields, not suitable for patients with metallic devices implanted within the body. Among the imaging techniques, we also mention ultrasonographic (US) analysis. However, this technique is not yet considered a reliable solution, since it suffers from problems in the detection of soft tissues characterizing bone metastasis [3]. Finally, nuclear medicine, such as positron emission tomography (PET), represents an interesting solution, since it potentially provides additional information about metabolism and drug activity. Despite the large values of sensitivity and specificity in detecting tumor masses, nuclear medicine is characterized by small spatial resolution. This feature has pushed researchers to couple such techniques to other approaches, such as MRI [4]. In the last two decades, RS has been demonstrated to be a promising, easy-to-use, and low-cost solution to respond to the aforementioned needs [5; 6; 7]. RS is based on the measurement of the so-called Raman effect [8], i.e., a light scattering phenomenon produced by the interaction between a beam of photons and virtual molecular energy levels [9]. The difference between the wavelengths of the scattered and the incident photons is strongly correlated to the chemical properties of the molecular target that caused the scattering. Therefore, by performing a spectral analysis of the radiation scattered by a sample of interest, it is possible to retrieve detailed information about the chemical composition of the target under investigation [10]. Since the Raman effect does not involve interaction between photons and well-defined electronic energy levels, the technique is intrinsically not subject to non-radiative relaxation phenomena, a possible source of sample cooling and consequent degradation. This feature makes RS particularly suitable to in vivo applications, e.g., for intraoperative cancer detection, aimed at estimating tumor margins. Unlike the conventional histopathological analysis, requiring staining procedures to bring out the characteristic features of the tissues under investigation, RS is a label-free approach, i.e., applicable directly to the tissue with no preliminary treatments. Despite the aforementioned strengths, RS presents two main limitations for its application in cancer diagnosis: first of all, the low acquisition speed could represent a relevant obstacle if diagnostic times of fractions of seconds are needed, e.g., in intraoperative cancer detection.