RecruitingNCT06822413

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

A Novel Raman Spectroscopy-Based Method for Pan-Cancers Early Diagnosis Supported by Deep Learning: A Prospective, Single-Arm, Multicentre Study

Sponsor

Second Affiliated Hospital, School of Medicine, Zhejiang University

Enrollment

600 participants

Start Date

Sep 1, 2022

Study Type

OBSERVATIONAL

Conditions

Gastric Cancers Esophageal Cancer Cancer Screening Colorectal Cancer (CRC)Cancer Diagnosis Liver Cancer, Adult Pancreatic Cancer, Adult Pancreatitis Normal Physiology Raman Spectroscopy Deep Learning Model Malignant Tumours Precancerous Conditions Adenoma Colon Polyp Gastric Ulcer Oesophagitis Cirrhoses, Liver

Summary

The goal of this observational study is to explore whether a Raman-based, deep learning-assisted approach can be used to develop an effective method for early pan-cancer screening. The study includes healthy individuals, patients at risk of cancer, and patients with diagnosed cancers. The main questions it aims to answer are: * Evaluating the deep-learning model's accuracy and specificity in identifying cancer-specific features in Raman spectral data and determining whether this method can accurately classify patients based on risk. * Identifying which model is more adaptable to the Raman spectrum * Providing an interpretable analysis of the model-generated diagnosis Participants are already being diagnosed and follow-up to determine the type of cancer.

Eligibility

Inclusion Criteria4

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 Criteria2

Patients with metastatic tumors or in the condition with two or more kinds of malignant tumors at the same time
Post-cancer treatment patients.

Interventions

OTHERNo Interventions

All blood samples from participating patients were obtained from routine clinical blood tests conducted during hospital admission or other necessary medical evaluations, followed by serum extraction.