Detecting normal benign and malignant colonic tissues by photoacoustic spectroscopy
Trial Snapshot
- Phase
- Not Applicable
- Status
- Recruiting
- Sponsor
- Enrollment
- 44
- Locations
- 1
- Primary Endpoint
- The newly developed photoacoustic endoscopic probe can classify different
Study Overview
Brief Summary
The development of a photoacoustic probe for detecting colonic mucosal conditions is a significant advancement in the diagnosis and treatment of colorectal cancer. This innovative technology aims to offer a quick and real-time method for identifying cancerous tissues. It addresses the limitations of conventional colonoscopy, which only allows for visual inspection without the ability to distinguish between different mucosal conditions like adenoma and carcinoma. The photoacoustic probe uses the unique optical absorption properties of tissue components such as collagen, NADH, elastin, and FAD, which can serve as biomarkers for cancer diagnosis. By detecting the specific spectral patterns of these biomarkers, the probe can accurately identify and differentiate between normal, adenomatous, and carcinomatous tissues. To improve the diagnostic capabilities of this technology, we will develop a machine-learning model. This model will be trained using spectral data obtained from the photoacoustic probe, enabling it to recognize complex patterns associated with different colonic mucosal conditions. Integrating machine learning will not only enhance the accuracy and reliability of the diagnosis but also aid in the development of a highly sensitive and specific diagnostic tool. This approach has the potential to revolutionize colorectal cancer screening by providing a non-invasive, realtime diagnostic method that can lead to early detection and timely treatment, thus improving patient outcomes and reducing the burden of colorectal cancer. The proposed study has the potential to significantly improve cancer diagnosis and treatment. It involves developing a photoacoustic probe specifically for detecting conditions in the colon’s mucosal lining. This technology can be seamlessly integrated into existing endoscopy and colonoscopy procedures, allowing for real-time, accurate diagnosis of colorectal cancers during routine examinations. This can greatly improve the speed and efficiency of cancer detection compared to traditional methods that rely on biopsy and histopathology, which can be timeconsuming and may delay treatment. The photoacoustic probe provides immediate results, enabling healthcare providers to make informed decisions on the spot. This real-time diagnostic capability can lead to earlier detection of malignant tissues, more precise characterization of mucosal abnormalities, and timely intervention, ultimately enhancing patient outcomes. The clinical translation of this technology represents a significant advancement in colorectal cancer screening and diagnosis, potentially setting a new standard in gastroenterological practice.
Study Design
- Study Type
- Interventional
- Allocation
- Na
- Masking
- None
Eligibility Criteria
- Ages
- 19.00 Year(s) to 80.00 Year(s) (—)
- Sex
- All
Inclusion Criteria
- •Adults above the age of 18 years Patients undergoing colonoscopy for any clinical indication Patients undergoing surgical removal of part of the colon for any clinical indication.
Exclusion Criteria
- •Patients are not able to give consent.
- •Emergency colonoscopy procedures.
- •Hemodynamically unstable patients.
- •Patients with serious comorbid illnesses preventing full colonoscopy from being performed.
Outcomes
Primary Outcomes
The newly developed photoacoustic endoscopic probe can classify different
Time Frame: Three years
tissue pathological conditions in colorectal mucosa by utilizing the distinct optical absorption properties
Time Frame: Three years
of biomarkers such as collagen, NADH, elastin, and FAD. These biomarkers allow the probe to
Time Frame: Three years
distinguish between normal, adenomatous, and carcinomatous tissues. Integrating machine learning
Time Frame: Three years
into the system further enhances diagnostic accuracy by recognizing complex patterns in the spectral
Time Frame: Three years
data, offering a non-invasive, real-time tool for early detection and improved treatment of colorectal
Time Frame: Three years
cancer.
Time Frame: Three years
Secondary Outcomes
- This study has the potential for translation into clinical practice.(5 years)
Investigators
Krishna Kishore Mahato
Manipal School of Life Sciences, Manipal Academy of Higher Education
