Evidence map›Paper›PMID 40119552›Full record

ArticleHead & neck2025

Early Experience With Indocyanine Green (ICG) Fluorescent Guided Transoral Robotic Surgery With the Da Vinci SP.

Omar A Karadaghy, Michael P Wu, Edward S Sim, Charles D Meyer, Anand T N Kumar, Jeremy D Richmon

Abstract read
In one paragraph

Article in Head & neck, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 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

6 authors.

Omar A KaradaghyDepartment of Otolaryngology-Head and Neck Surgery, University of Kansas Medical Center, Kansas City, Kansas, USA.ORCID 0000-0001-6866-5605
Michael P WuDepartment of Otolaryngology-Head and Neck Surgery, Massachusetts Eye and Ear and Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0003-3881-1020
Edward S SimDepartment of Otolaryngology-Head and Neck Surgery, Massachusetts Eye and Ear and Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0002-1632-286X
Charles D MeyerDepartment of Otolaryngology-Head and Neck Surgery, Massachusetts Eye and Ear and Harvard Medical School, Boston, Massachusetts, USA.
Anand T N KumarAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Jeremy D RichmonDepartment of Otolaryngology-Head and Neck Surgery, Massachusetts Eye and Ear and Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0002-6588-6549

Funding

RESEARCH TRAINING IN OTOLARYNGOLOGYT32DC000020 · NIDCD · MASSACHUSETTS EYE AND EAR INFIRMARY · PI JUNG, DAVID H, SIMONYAN, KRISTINA · 1990 to 2025
$2.4M
Fluorescence lifetime-based tumor contrast enhancement using exogenous probesR01DE033427 · NIDCR · MASSACHUSETTS GENERAL HOSPITAL · PI Anand T.N. Kumar · 2023 to 2026
$1.9M
NIDCD NIH HHS T32 DC000020NIDCR NIH HHS R01 DE033427
6 · The paper itself

Abstract

importanceCarcinoma of Unknown Primary (CUP) presents a clinical challenge for practitioners. The current diagnostic approach often involves extensive imaging and examinations, with variable success. We aimed to evaluate the effectiveness of Indocyanine Green (ICG) injection using the Da Vinci robot to aid in intraoperative decision making.

objectivesTo evaluate the diagnostic utility of ICG use during robotic surgery to aid in either the identification of the primary tumor or to delineate the extent of disease to guide excision.

methodsThis study involved a retrospective review of patients treated at the Massachusetts Eye and Ear who underwent robotic surgery with the utilization of Indocyanine Green (ICG) from October 1, 2022. All patients in the study were operated on using the SP model of the Da Vinci robot. Basic demographic and pathologic data were recorded. Intraoperative data points included assessing the presence of an identifiable primary tumor using white light only and documenting the confidence level of ICG localization.

resultsIn total, 28 patients who underwent robotic surgery using ICG were identified for this study. The mean age of the cohort was 62 years. Twenty-six patients were male, and the primary diagnosis was HPV-related squamous cell carcinoma (SCCa) in 22 patients, HPV-negative SCC in 5 patients, atypia in 1 patient, and metastatic papillary thyroid carcinoma in 1 patient. Nine patients had either PET-localizing or visually identified primary tumors, and ICG was used to guide the surgical extent of resection. The remaining 19 patients had CUP. Within the patients with CUP, the primary was ultimately identified in 16 of the 19 (84.2%) patients. In regard to ICG localization, this resulted in a True Positive detection in 10 patients (52.6%), False Positive detection in 6 patients (31.6%), False Negative detection in 0 patients (0%), and True Negative detection in 3 patients (15.8%). Based on a confusion matrix of the aforementioned values, the calculated sensitivity, specificity, PPV, and NPV were 100%, 33.3%, 62.5%, and 100%, respectively. The discriminatory index of ICG in the detection of unknown primary disease was found to be 66.6%.

conclusionThe integration of systemic ICG injection with the Da Vinci SP robot's real-time imaging capabilities offers a potential option for enhancing primary tumor identification in CUP patients that adds little to no cost, time, and morbidity to the patient. This preliminary analysis suggests that the use of ICG in robotic surgery for CUP holds promise and warrants further investigation to refine surgical techniques and enhance clinical outcomes.

Indexed as

Carcinoma, Squamous CellIndocyanine GreenNeoplasms, Unknown PrimaryRobotic Surgical ProceduresAdultAgedColoring AgentsFemaleHumansMaleMiddle AgedRetrospective StudiesColoring AgentsIndocyanine Greencarcinoma of unknown primaryDa Vinci SP robotdiagnostic accuracyindocyanine greenrobotic surgery

Identifiers

PMID40119552
PMCPMC12254020

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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.