Evidence map›Paper›PMID 42482741›Full record

SynthesisFrontiers in oral health2026

Hyperspectral imaging in oral oncology: a scoping review.

Shamal Kankawale, Amol Jamkhande, Gauri Oka

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in oral health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Shamal KankawaleCentral Research and Publication Unit, Bharati Hospital and Research Centre, Pune, India.
Amol JamkhandeCommunity Dentistry, Bharati Vidyapeeth (Deemed to be University) Dental College, Pune, India.
Gauri OkaCentral Research and Publication Unit, Bharati Vidyapeeth (Deemed to be University) Medical College, Pune, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Oral cancer accounts for 177,000 deaths annually. Despite advances in surgical techniques and adjuvant therapies, the five-year survival rate for oral malignancies has shown limited improvement. Hyperspectral imaging (HSI) is a new non-invasive optical modality that extends medical imaging beyond the visible spectrum. This scoping review aims to map the extent, nature, and methodological characteristics of the existing literature on the application of HSI for the detection and characterization of oral cancer. It explores the clinical applications of HSI in oral oncology, outlines the technical and analytical approaches used, and evaluates its diagnostic performance and translational readiness in clinical practice. Methods: This scoping review used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines and followed the Population-Concept-Context(PCC) framework. A comprehensive search strategy was formulated to search across PubMed, ScienceDirect, Nature, LILACS, and Cochrane Library, and citation searching. Search was conducted by two independent reviewers using predefined inclusion and exclusion criteria. Microsoft Excel was used for data extraction. Descriptive synthesis was used to map the extent and nature of existing evidence, and narrative synthesis was used to identify patterns and methodological characteristics. Results: Out of 1,513 records identified, 15 studies were included. Most studies were published after 2017 and conducted in high-income countries. 13 studies were conducted Conclusion: HSI is a new emerging technology with applications in oral oncology. It provides a non-contact, objective and rapid alternative for margin assessment. With improved standardization, robust analytical models and clinical validation, it has the potential to be integrated into routine oral cancer management. Systematic Review Registration: https://doi.org/10.17605/OSF.IO/JQEGU.

Indexed as

deep learningdiagnostic accuracyhyperspectral imagingintraoperative imagingmachine learningoral canceroral squamous cell carcinoma

Identifiers

PMID42482741
PMCPMC13385111

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.