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Early detection and accurate diagnosis of colorectal carcinoma are crucial for successful treatment, yet current methods can be invasive and even inaccurate in some cases. In this work, we present a novel approach for in vivo tissue diagnostics of colorectal carcinoma using Raman spectroscopy. This almost non-invasive technique allows for fast and accurate detection of colorectal carcinoma and its precursors, adenomatous polyps, enabling timely intervention and improved patient outcomes. Using several methods of supervised machine learning, we were able to achieve over 91% accuracy in distinguishing colorectal lesions from healthy epithelial tissue and more than 90% classification accuracy for premalignant adenomatous polyps. Moreover, our models enabled the discrimination of cancerous and precancerous lesions with a mean accuracy of almost 92%. Such results demonstrate the potential of in vivo Raman spectroscopy to become a valuable tool in the fight against colon cancer. [ABSTRACT FROM AUTHOR]

Colorectal cancer is one of the most abundant causes of cancer deaths in the world. At an early stage, the established clinical procedures have low reliability and sensitivity. Therefore, we tested a novel approach based on chiroptical methods such as electronic circular dichroism (ECD) and Raman optical activity (ROA). These methods are suitable for detecting slight changes in the 3D structure of chiral biomolecules, some of which may be caused by pathological processes occurring during cancer growth. Fifty-five blood plasma samples were analyzed using the combination of ECD and ROA supplemented by conventional Raman and FT-IR spectroscopy. All obtained spectra were evaluated together by linear discriminant analysis. The accuracy of sample discrimination reached 100% and the subsequent leave-one-out cross-validation resulted in 93% sensitivity and 81% specificity. The achieved results indicate that chiroptical methods supplemented by Raman and FT-IR spectroscopy might be new supporting and minimally invasive tools in the clinical diagnosis of colon cancer. [ABSTRACT FROM AUTHOR]