(1) Background: Clinicians demand new tools for early diagnosis and improved detection of colon lesions that are vital for patient prognosis. Optical coherence tomography (OCT) allows microscopical inspection of tissue and might serve as an optical biopsy method that could lead to in-situ diagnosis and treatment decisions; (2) Methods: A database of murine (rat) healthy, hyperplastic and neoplastic colonic samples with more than 94,000 images was acquired. A methodology that includes a data augmentation processing strategy and a deep learning model for automatic classification (benign vs. malignant) of OCT images is presented and validated over this dataset. Comparative evaluation is performed both over individual B-scan images and C-scan volumes; (3) Results: A model was trained and evaluated with the proposed methodology using six different data splits to present statistically significant results. Considering this, 0.9695 (±0.0141) sensitivity and 0.8094 (±0.1524) specificity were obtained when diagnosis was performed over B-scan images. On the other hand, 0.9821 (±0.0197) sensitivity and 0.7865 (±0.205) specificity were achieved when diagnosis was made considering all the images in the whole C-scan volume; (4) Conclusions: The proposed methodology based on deep learning showed great potential for the automatic characterization of colon polyps and future development of the optical biopsy paradigm.

Ischemia-reperfusion injury is the main cause of flap failure in reconstructive microsurgery. The rat is the preferred preclinical animal model in many areas of biomedical research due to its cost-effectiveness and its translation to humans. This protocol describes a method to create a preclinical free skin flap model in rats with ischemia-reperfusion injury. The described 3 cm x 6 cm rat free skin flap model is easily obtained after the placement of several vascular ligatures and the section of the vascular pedicle. Then, 8 h after the ischemic insult and completion of the microsurgical anastomosis, the free skin flap develops the tissue damage. These ischemia-reperfusion injury-related damages can be studied in this model, making it a suitable model for evaluating therapeutic agents to address this pathophysiological process. Furthermore, two main monitoring techniques are described in the protocol for the assessment of this animal model: transit-time ultrasound technology and laser speckle contrast analysis.

Ischemia-reperfusion injury is the main cause of flap failure in reconstructive microsurgery. The rat is the preferred preclinical animal model in many areas of biomedical research due to its cost-effectiveness and its translation to humans. This protocol describes a method to create a preclinical free skin flap model in rats with ischemia-reperfusion injury. The described 3 cm x 6 cm rat free skin flap model is easily obtained after the placement of several vascular ligatures and the section of the vascular pedicle. Then, 8 h after the ischemic insult and completion of the microsurgical anastomosis, the free skin flap develops the tissue damage. These ischemia-reperfusion injury-related damages can be studied in this model, making it a suitable model for evaluating therapeutic agents to address this pathophysiological process. Furthermore, two main monitoring techniques are described in the protocol for the assessment of this animal model: transit-time ultrasound technology and laser speckle contrast analysis.