Evidence map›Paper›PMID 42323412›Full record

ArticleSurgical endoscopy2026

Quantitative optimisation of indocyanine green fluorescence for parathyroid imaging in robotic BABA thyroidectomy: a prospective cohort study.

Hao Chi, Chengqiu Sui, Mingyu Yang, Dongyuan Lan, Kecheng Bai, Francesco Brucchi, Gianlorenzo Dionigi, Daqi Zhang

Abstract read
PubMed Publisher
In one paragraph

Article in Surgical endoscopy, 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

8 authors.

Hao ChiDivision of Thyroid Surgery, China-Japan Union Hospital of Jilin University, Jilin Provincial Key Laboratory of Thyroid Disease, Jilin Provincial Precision Medicine Laboratory of Molecular Biology and Translational Medicine on Differentiated Thyroid Carcinoma, 126 Xiantai Street, Changchun, 130033, Jilin, China.
Chengqiu SuiDivision of Thyroid Surgery, China-Japan Union Hospital of Jilin University, Jilin Provincial Key Laboratory of Thyroid Disease, Jilin Provincial Precision Medicine Laboratory of Molecular Biology and Translational Medicine on Differentiated Thyroid Carcinoma, 126 Xiantai Street, Changchun, 130033, Jilin, China.
Mingyu YangDivision of Thyroid Surgery, China-Japan Union Hospital of Jilin University, Jilin Provincial Key Laboratory of Thyroid Disease, Jilin Provincial Precision Medicine Laboratory of Molecular Biology and Translational Medicine on Differentiated Thyroid Carcinoma, 126 Xiantai Street, Changchun, 130033, Jilin, China.
Dongyuan LanDivision of Thyroid Surgery, China-Japan Union Hospital of Jilin University, Jilin Provincial Key Laboratory of Thyroid Disease, Jilin Provincial Precision Medicine Laboratory of Molecular Biology and Translational Medicine on Differentiated Thyroid Carcinoma, 126 Xiantai Street, Changchun, 130033, Jilin, China.
Kecheng BaiDivision of Thyroid Surgery, China-Japan Union Hospital of Jilin University, Jilin Provincial Key Laboratory of Thyroid Disease, Jilin Provincial Precision Medicine Laboratory of Molecular Biology and Translational Medicine on Differentiated Thyroid Carcinoma, 126 Xiantai Street, Changchun, 130033, Jilin, China.
Francesco BrucchiDivision of General and Endocrine Surgery, Istituto Auxologico Italiano, IRCCS (Istituto di Ricovero e Cura a Carattere Scientifco), Milan, Italy.
Gianlorenzo DionigiDivision of General and Endocrine Surgery, Istituto Auxologico Italiano, IRCCS (Istituto di Ricovero e Cura a Carattere Scientifco), Milan, Italy.
Daqi ZhangDivision of Thyroid Surgery, China-Japan Union Hospital of Jilin University, Jilin Provincial Key Laboratory of Thyroid Disease, Jilin Provincial Precision Medicine Laboratory of Molecular Biology and Translational Medicine on Differentiated Thyroid Carcinoma, 126 Xiantai Street, Changchun, 130033, Jilin, China. zhangdq@jlu.edu.cn.ORCID http://orcid.org/0000-0001-8214-1971

Funding

Jilin Provincial Scientific and Technological Development Program 20240304036SF
6 · The paper itself

Abstract

objectiveTo develop and validate a quantitative framework for intraoperative indocyanine green (ICG) fluorescence imaging of the parathyroid glands during robotic bilateral axillo-breast approach (BABA) thyroidectomy and to identify technical and clinical factors associated with optimal image quality.

backgroundICG fluorescence is increasingly used to aid parathyroid identification and perfusion assessment in thyroid surgery, but there is no consensus on optimal dosing, image quantification, or patient selection, particularly in the context of robotic thyroidectomy. A robust, objective definition of "good" imaging is needed to standardise protocols and support broader clinical adoption.

methodsIn this single-centre prospective study (June 2024-January 2025), 72 consecutive patients with low-risk papillary thyroid carcinoma underwent robotic BABA thyroidectomy with ICG fluorescence using the da Vinci Xi system. A cyclic dosing protocol (1.5, 2.0, 2.5, 3.0 mL) was applied in eligible cases. For each patient, a 12-s fluorescence sequence was recorded from the onset of visible ICG uptake, and 12 frames (1 frame per second) were extracted. In each frame, the parathyroid region (Zone A) and periparathyroid background (Zone C) were manually segmented, and the relative fluorescence intensity ratio (RFIR = A/C) was calculated. Image quality was independently graded on a 3-point scale (0-2) and classified as clear (mean score ≥ 1) or unclear (< 1). Receiver operating characteristic analysis was used to derive an RFIR threshold for "good" imaging. Univariable and multivariable logistic regression were performed to explore associations between imaging quality and clinical variables (demographics, biochemistry, thyroiditis, fasting blood glucose [FBG], intraoperative haemodynamics) and ICG dose.

resultsAn RFIR cut-off of 1.07 yielded an area under the curve of 0.832 for discrimination between clear and unclear images. At the case level, imaging was defined as good when at least 6 of 12 frames (≥ 50%) had RFIR ≥ 1.07. In univariable analysis, higher body mass index was positively associated with good imaging (odds ratio [OR] 1.18, 95% confidence interval [CI] 1.03-1.36; P = 0.020), whereas an ICG dose of 3.0 mL was negatively associated (OR 0.11, 95% CI 0.02-0.50; P = 0.004). In multivariable analysis, elevated FBG (OR 0.25, 95% CI 0.08-0.86; P = 0.027) and an ICG dose of 3.0 mL (OR 0.01, 95% CI 0.00-0.17; P = 0.001) remained independently associated with reduced odds of good imaging, while other clinical and haemodynamic variables were not significant. Interaction analyses showed that low FBG combined with lower doses (1.5-2.0 mL) provided the highest predicted probability of optimal imaging, whereas high FBG with higher doses (2.5-3.0 mL) yielded the poorest performance.

conclusionsICG fluorescence imaging of the parathyroid glands during robotic BABA thyroidectomy can be standardised using an RFIR threshold of 1.07 and a frame-based majority rule to define good imaging. Lower ICG doses (1.5-2.0 mL) and favourable metabolic status (low FBG) are key determinants of optimal image quality, whereas higher doses (3.0 mL) and elevated FBG are associated with over-saturation and reduced contrast. These findings support tailored, low-dose ICG protocols and provide a quantitative benchmark for future multi-centre studies linking fluorescence metrics to postoperative calcium and parathyroid function outcomes.

Indexed as

Indocyanine GreenOptical ImagingParathyroid GlandsRobotic Surgical ProceduresThyroid Cancer, PapillaryThyroidectomyThyroid NeoplasmsAdultAgedColoring AgentsFemaleHumansMaleMiddle AgedProspective StudiesColoring AgentsIndocyanine GreenBilateral axillo-breast approach (BABA)Image-guided surgeryIndocyanine green (ICG)Near-infrared fluorescence imagingParathyroid perfusionRobotic thyroid surgery

Identifiers

What OpenQuestion holds

Textmetadata
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.