Evidence map›Paper›PMID 41290850›Full record

ArticleScientific reports2025

Design and development of a portable multiwavelength LED-based diffuse reflectance spectroscopy tool for rapid breast cancer identification.

Arif Mohd Kamal, Kirteyman Singh Rajput, Apurva Dahake, Gayatri Gogoi, Ajay Krishnan Ajith, V S N Sitaramgupta Vangeti, Dilip Kiling, Jayant S Vaidya, Hardik J Pandya

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Arif Mohd KamalDepartment of Electronic Systems Engineering, Indian Institute of Science, Bangalore, India.
Kirteyman Singh Rajput *Department of Electronic Systems Engineering, Indian Institute of Science, Bangalore, India.
Apurva Dahake *Department of Electronic Systems Engineering, Indian Institute of Science, Bangalore, India.
Gayatri GogoiMedical Research Unit Laboratory, Department of Pathology, Assam Medical College, Dibrugarh, India.
Ajay Krishnan AjithDepartment of Electronic Systems Engineering, Indian Institute of Science, Bangalore, India.
V S N Sitaramgupta VangetiDepartment of Electronic Systems Engineering, Indian Institute of Science, Bangalore, India.
Dilip KilingDepartment of Surgery, Assam Medical College, Dibrugarh, India.
Jayant S VaidyaDivision of Surgery and Interventional Science, University College London, London, UK.ORCID 0000-0003-1760-1278
Hardik J PandyaDepartment of Electronic Systems Engineering, Indian Institute of Science, Bangalore, India. hjpandya@iisc.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is the most prevalent cancer among women worldwide, emphasizing the need for rapid and accurate diagnostic tools to improve patient outcomes and survival rates. In this study, we developed a diagnostic tool-a multispectral pen based on diffuse reflectance spectroscopy (DRS)-to enable real-time ex vivo differentiation between malignant and adjacent normal human breast tissues, primarily based on lipid and collagen absorbers. Diffuse reflectance was observed to be higher, while reduced absorbance was lower for malignant tissue compared to adjacent normal tissue across 62 samples (50 formalin-fixed and 12 fresh tissues). Clinical data from 31 patients, with paired adjacent normal and malignant samples per patient, revealed significantly lower mean reduced absorbance values for malignant tissue at three wavelengths: 850 nm (0.13 ± 0.02 vs. 0.28 ± 0.02), 940 nm (0.19 ± 0.01 vs. 0.37 ± 0.02), and 1050 nm (0.25 ± 0.03 vs. 0.43 ± 0.03) with p < 0.0001 across formalin-fixed tissue samples. Using a CatBoost machine learning model, the tool achieved an accuracy of 90%, a sensitivity of 80%, and a specificity of 100% in distinguishing malignant from normal tissues. Limitations include a small sample size and limited patient diversity. Future work aims to integrate the DRS technology with machine learning algorithms to provide real-time intraoperative margin assessment, and testing in a larger study.

Indexed as

Breast NeoplasmsSpectrum AnalysisFemaleHumansMiddle Aged

Identifiers

PMID41290850
PMCPMC12647633

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.