Colorectal Lesion Detection
Colorectal Lesion Detection - Related Videos
03:50
ROS Detection with DCFH-DA Staining: Measuring Total ROS in Colorectal Cancer Cell Lines
0 Views •
2023
This video describes the protocol for detecting total cellular reactive oxygen species (ROS) using 2',7'-dichlorodihydrofluorescein diacetate (DCFH-DA). This method helps visualize ROS localization in the adherent cells using a fluorescence microscope and further quantify ROS intensity with a fluorescence plate reader.
03:19
Generating PDOX Mouse Model of Colorectal Cancer: Studying Progression of Colorectal Cancer in a Murine Model
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2023
This video describes the protocol for generating a patient-derived orthotopic xenograft colorectal cancer mouse model to study the progression of colorectal cancer cells in non-obese diabetic/severe combined immunodeficiency (NOD/SCID) mice. This murine model helps in understanding primary tumor growth and metastases pattern.
08:43
Orthotopic Mouse Model of Colorectal Cancer
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Cited by 109 •
2007
Two techniques can be used to establish this model: injection of a cancer cell suspension into the cecal wall or transplantation of a piece of subcutaneous tumor onto the cecum. This model is useful for studying the natural progression of colorectal cancer and testing new therapeutic agents against colorectal cancer.
06:01
A Genetically Engineered Mouse Model of Sporadic Colorectal Cancer
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Cited by 3 •
2017
A protocol for the establishment of a genetically engineered mouse model of colorectal cancer by segmental adeno-cre infection and its surveillance via high-resolution colonoscopy is presented.
14:09
In vitro Functional Characterization of Mouse Colorectal Afferent Endings
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Cited by 21 •
2015
This video demonstrates a protocol for conducting single-fiber electrophysiological recordings on an in vitro mouse colorectum-nerve preparation.
FAQs
Detection depends on comparing the mucosal surface for changes in shape, color, texture, and vascular pattern. These features help clinicians identify areas that differ from surrounding tissue and decide which findings require closer assessment. Evaluating several visual characteristics together supports more consistent recognition of potentially important lesions rather than relying on a single visible abnormality.
Characterization helps distinguish clinically important lesions from benign findings and supports decisions about subsequent management. A lesion’s observed appearance guides whether clinicians should obtain tissue for targeted biopsy or remove it for examination. This distinction matters because detection alone identifies an abnormal area, while characterization helps determine its significance for diagnosis, treatment, and surveillance.
Computer-assisted analysis may support clinicians by analyzing lesion appearance and assisting with detection or classification during evaluation. Its potential value is improving detection accuracy and reducing missed disease, particularly when visual findings are difficult to interpret. These tools complement imaging-based inspection and may provide more consistent assessments without replacing the need for clinical and histopathological evaluation.
Histopathological evaluation examines tissue obtained through targeted biopsy or lesion removal. It provides information that cannot be established from surface appearance alone, helping clarify whether a suspicious finding represents a clinically important lesion or a benign one. This tissue-based assessment strengthens diagnostic interpretation and can inform treatment and surveillance decisions after colonoscopic evaluation.
The evaluation begins with colonoscopic inspection of the mucosal surface, followed by closer assessment of any area with concerning changes in shape, color, texture, or vascular pattern. Clinicians then obtain a targeted biopsy or remove the lesion when appropriate, and submit the tissue for histopathological evaluation. The resulting findings support diagnostic and management decisions.
Its value is greatest when early prevention or diagnosis is the goal. Identifying precancerous polyps can support preventive intervention, while recognizing malignant tumors contributes to diagnosis. Detection and characterization also guide treatment and surveillance decisions, making the process relevant across the continuum from identifying abnormal tissue to planning follow-up after evaluation.
Colorectal lesion detection provides measurable information about whether abnormal tissue is identified and characterized during evaluation. Because lesions can include precancerous polyps and malignant tumors, detection findings can serve as essential endpoints in studies of cancer prevention, diagnosis, imaging, computer-assisted analysis, and lesion classification. These endpoints help assess whether an approach improves accuracy or reduces missed disease.