Near-Infrared Imaging in Small Animal Surgical Oncology: Current Applications and Future Directions

The use of near-infrared (NIR) fluorescence imaging has become increasingly widespread in the intraoperative management of human cancer patients, with diverse applications that enhance the visualization of tumors, metastatic lesions, draining lymph nodes, and critical anatomy. In recent years, the adoption of NIR imaging in small animal surgical oncology has grown, with reported applications including nonselective and selective tumor imaging as well as sentinel lymph node (SLN) mapping for staging and surgical guidance. Despite these advances, clinical use in veterinary patients remains in its early stages, and further work is needed to define indications, optimize protocols, and determine its impact on outcomes. This review summarizes the current applications of NIR imaging in companion animal oncologic surgery, including techniques for dye administration, imaging agents, and reported clinical uses across tumor types. Key limitations are discussed, including limited tissue penetration, lack of tumor specificity with commonly used agents such as indocyanine green, variability in protocols, and limited data in certain species. Emerging technologies, including targeted fluorescent agents and advanced imaging approaches, are also highlighted. Overall, NIR imaging represents a promising adjunct in small animal surgical oncology, though further study and standardization are needed to support broader clinical integration.

Authors

Institutions

Publication Details

Journal
Animals
Published
2026-05-21
DOI
https://doi.org/10.3390/ani16101563
Primary Topic
Veterinary Oncology Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Near-Infrared Imaging in Small Animal Surgical Oncology: Current Applications and Future Directions

Maureen A. Griffin
Animals
Veterinary Oncology Research
article

Near-Infrared Imaging in Small Animal Surgical Oncology: Current Applications and Future Directions

Maureen A. Griffin
article en

Abstract

The use of near-infrared (NIR) fluorescence imaging has become increasingly widespread in the intraoperative management of human cancer patients, with diverse applications that enhance the visualization of tumors, metastatic lesions, draining lymph nodes, and critical anatomy. In recent years, the adoption of NIR imaging in small animal surgical oncology has grown, with reported applications including nonselective and selective tumor imaging as well as sentinel lymph node (SLN) mapping for staging and surgical guidance. Despite these advances, clinical use in veterinary patients remains in its early stages, and further work is needed to define indications, optimize protocols, and determine its impact on outcomes. This review summarizes the current applications of NIR imaging in companion animal oncologic surgery, including techniques for dye administration, imaging agents, and reported clinical uses across tumor types. Key limitations are discussed, including limited tissue penetration, lack of tumor specificity with commonly used agents such as indocyanine green, variability in protocols, and limited data in certain species. Emerging technologies, including targeted fluorescent agents and advanced imaging approaches, are also highlighted. Overall, NIR imaging represents a promising adjunct in small animal surgical oncology, though further study and standardization are needed to support broader clinical integration.

AnimalsVol. 16(10)
Colorado State University (US)
Openalex Percentile: Top 6%
Veterinary Oncology Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.