Clinical Diagnosis of Diabetes Using Surface-enhanced Raman Spectroscopy Liquid Biopsy and Machine Learning

NCT ID: NCT06862778

Last Updated: 2025-03-06

Basic Information

• Recruitment Status: ACTIVE_NOT_RECRUITING
• Clinical Phase: NA
• Total Enrollment: 52 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2024-02-02
• Study Completion Date: 2025-07-31

Brief Summary

This project aims to adapt the gold nanoparticle-based surface-enhanced Raman spectroscopy (SERS) technology to clinical application. In this exploratory study, a measurement protocol will be established to investigate whether SERS (combined with multivariate data analysis or machine learning algorithms) allows the diagnosis of patients with diabetes.

Detailed Description

This study on the clinical application of surface-enhanced Raman spectroscopy (SERS) comprises two parts. First, a SERS measurement protocol will be developed to enhance the interactions between gold nanoparticles and the components of the patient's samples, maximizing Raman spectroscopical signatures. Given the complex composition of human blood, which encompasses numerous biological constituents, the study focuses on serum, a component obtained through centrifugation after removing cells and clotting factors. Fifteen spectra will be recorded per sample. The raw spectra will be post-processed, including removal of the substrate signal, baseline correction, vector normalization, and smoothing steps.

The SERS measurement protocol established in the first section will subsequently be applied to samples of healthy and diabetes patients. Two different approaches will be followed. First, multivariate data analysis will be performed to identify distinctive feature characteristics in the samples that correlate to their group (healthy and diabetes patients), allowing patient diagnosis. Second, different machine learning algorithms and data augmentation strategies will be explored for better patient diagnosis.

Conditions

Diabetes

Study Design

• Allocation Method: NON_RANDOMIZED
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: SINGLE

Study Groups

Healthy

The Raman spectra of healthy patient samples will be measured in the presence of gold nanoparticles, which will enhance the spectroscopic characteristics of serum components via near-field enhancements.

Group Type: EXPERIMENTAL

SERS

Intervention Type: DIAGNOSTIC_TEST

Spectroscopic assessment of serum samples from healthy and diabetic patients to identify characteristics for diagnosis.

Diabetes

The Raman spectra of diabetic patient samples will be measured in the presence of gold nanoparticles, which will enhance the spectroscopic characteristics of serum components via near-field enhancements.

Group Type: EXPERIMENTAL

SERS

Intervention Type: DIAGNOSTIC_TEST

Spectroscopic assessment of serum samples from healthy and diabetic patients to identify characteristics for diagnosis.

Interventions

SERS

Spectroscopic assessment of serum samples from healthy and diabetic patients to identify characteristics for diagnosis.

Intervention Type: DIAGNOSTIC_TEST

Other Intervention Names

Surface-enhanced Raman Spectroscopy

Eligibility Criteria

Inclusion Criteria

• Patient at Nishtar Medical University
• Patient age from 18 to 70 years
• Confirmed disease (for diabetic group)

Exclusion Criteria

• Patients with severe concurrent diseases

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 70 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

University of Agriculture Faisalabad

UNKNOWN

Sponsor Role: collaborator

Nishtar Medical University

OTHER

Sponsor Role: collaborator

University Hospital, Aachen

OTHER

Sponsor Role: lead

Responsible Party

Roger Molto Pallares

Group Leader

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

RWTH Aachen university hospital

Aachen, , Germany

Countries

Germany

Other Identifiers

Diabetes SERS 01

Identifier Type: -

Identifier Source: org_study_id