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Related Concept Videos

Serum Laboratory Studies, Stool Test, Breath Test01:30

Serum Laboratory Studies, Stool Test, Breath Test

Gastrointestinal (GI) diagnostic studies are pivotal in confirming, ruling out, diagnosing, or staging various diseases, including cancers. Following diagnosis, allocating time for discussions with the patient and providing informational resources is crucial. Diagnostic assessments of the GI tract often occur in outpatient settings like endoscopy suites or GI labs. Preparation for these tests may include dietary restrictions, fasting, liquid bowel preparations, laxatives, enemas, and the...
Raman Spectroscopy Instrumentation: Overview01:26

Raman Spectroscopy Instrumentation: Overview

A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
The monochromatic laser source, typically using visible or near-infrared radiation, generates a highly focused beam of light. This light interacts with the molecules of the sample, scattering some of the light. Liquid and gaseous samples are usually tested in ordinary glass capillaries, while solids can be analyzed as powders packed in capillaries or as potassium...
Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

The underlying principle of Raman spectroscopy is based on the interaction between light and matter, specifically molecules' inelastic scattering of photons. When a monochromatic beam of light, typically from a laser source, interacts with a sample, most scattered light has the same frequency as the incident light. This is known as Rayleigh scattering.
However, a small fraction of the scattered light exhibits a frequency shift due to the exchange of energy between the incident photons and the...

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Related Experiment Video

Updated: Jun 11, 2026

Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing
15:17

Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing

Published on: September 25, 2011

A Novel Blood-Based Screening Test for Colorectal Cancer Using Raman Spectroscopy.

Jett Karolewski1,2, Georgia Carroll1,2,3, Rosemary Carroll1

  • 1Division of Surgery, John Hunter Hospital, New Lambton Heights, New South Wales, Australia.

ANZ Journal of Surgery
|June 10, 2026
PubMed
Summary
This summary is machine-generated.

Raman spectroscopy combined with machine learning shows promise for colorectal cancer (CRC) detection. This method achieved high accuracy in identifying CRC, potentially improving screening compliance.

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Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing
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Surface-enhanced Resonance Raman Scattering Nanoprobe Ratiometry for Detecting Microscopic Ovarian Cancer via Folate Receptor Targeting
07:54

Surface-enhanced Resonance Raman Scattering Nanoprobe Ratiometry for Detecting Microscopic Ovarian Cancer via Folate Receptor Targeting

Published on: March 25, 2019

Area of Science:

  • Oncology
  • Biotechnology
  • Spectroscopy

Background:

  • Colorectal cancer (CRC) screening traditionally uses immunochemical faecal occult blood (iFOBT) tests with low compliance in Australia.
  • Label-free vibrational spectroscopy, specifically Raman spectroscopy, offers a novel approach for cancer diagnostics.
  • Machine learning (ML) integrated with spectroscopic techniques holds significant potential for oncology screening and diagnostics.

Purpose of the Study:

  • To evaluate the efficacy of Raman spectroscopy for detecting colorectal cancer (CRC).
  • To assess the potential of Raman spectroscopy as a screening tool for CRC.

Main Methods:

  • Plasma samples from 370 participants (117 CRC patients, 253 iFOBT-positive controls) were analyzed.
  • The control group included individuals with advanced adenomas, non-advanced adenomas, colitis, or no disease.
  • Raman spectra were analyzed using ML algorithms in separate training (n=222) and validation (n=148) cohorts.

Main Results:

  • The Raman spectroscopy ML model achieved 84% sensitivity and 93% specificity for CRC detection in the validation cohort.
  • In subcategory analysis, 95% of CRC patients would be recommended for colonoscopy.
  • Approximately 42% of individuals testing positive via iFOBT could potentially avoid colonoscopy.

Conclusions:

  • This exploratory study demonstrates the high accuracy of a Raman spectroscopy-based ML model for CRC detection.
  • The developed model shows potential as a tool for colorectal cancer screening, possibly improving upon current methods.