Raman Spectroscopy-Based Deep Learning Model for Early Pan-Cancer Early Diagnosis

Launched by SECOND AFFILIATED HOSPITAL, SCHOOL OF MEDICINE, ZHEJIANG UNIVERSITY · Feb 5, 2025

Keywords

ClinConnect Summary

This clinical trial is exploring a new way to detect cancer early using a technology called Raman spectroscopy, which analyzes light to identify cancerous changes in tissues. The study aims to develop a deep learning model that can accurately recognize specific features related to different types of cancer. It includes both healthy individuals and patients who are at risk for cancer or already have a cancer diagnosis, focusing on common cancers like colorectal, gastric, liver, pancreatic, and esophageal cancers.

To participate, individuals must have a confirmed diagnosis of a malignant tumor, be healthy without any cancer, or have precancerous conditions. However, those who have already undergone cancer treatment or have multiple types of cancer at once cannot join. Participants will have their Raman spectral data analyzed to see how well the model can classify their cancer risk. This study is currently recruiting, and it aims to provide valuable insights into better cancer screening methods for everyone.

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • Histopathological diagnosis of malignant tumors, including colorectal cancer, gastric cancer, hepatic cancer, pancreatic cancer, and esophageal cancer.
• • Patients in normal physiological conditions without any malignant tumors or precancerous lesions.
• • Patients with malignant tumor without recieving any interventions, including chemotherapy, surgery, radiotherapy, immunotherapy or other anti-tumor treatments.
• • Patients with a histopathological diagnosis of any precancerous lesions or non-malignant disease.
• Exclusion Criteria:
• • Patients with metastatic tumors or in the condition with two or more kinds of malignant tumors at the same time
• • Post-cancer treatment patients.