Deep Learning-Based Intraoperative Dual-tracer Video Analysis of Sentinel Lymph Node Mapping for Metastasis Prediction in cN0 Papillary Thyroid Carcinoma

NCT07391514 | Completed

• 1 other identifier: 1stChongqingMU-sxl
• Study Type: observational
• Target: 131
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this observational study is to learn if a computer program (deep learning) can accurately predict lymph node spread in adults with papillary thyroid cancer who have no signs of lymph node involvement before surgery (called cN0). The main questions it aims to answer are:

• Can video analysis of lymph node mapping during surgery predict if cancer has spread to lymph nodes beyond the first-draining (sentinel) lymph node?
• Can this prediction help surgeons decide how much tissue to remove during surgery? During surgery, participants will receive an injection of two special dyes (carbon nanoparticles and indocyanine green) near the thyroid tumor. These dyes travel through the lymphatic system and help surgeons see the lymph nodes. A special camera records a video of how the dyes move and light up the lymph nodes. Researchers will use computer programs to analyze these videos along with other medical information (such as ultrasound results and tumor characteristics) to predict whether cancer has spread to additional lymph nodes. The predictions will be compared against the actual results from tissue samples examined after surgery. Participants will receive standard thyroid cancer surgery. The study does not change the surgical treatment. The video recording adds no extra risk to participants.

Conditions

Papillary Thyroid Carcinoma

Keywords

Papillary thyroid carcinoma; Sentinel lymph node biopsy; Dual-tracer imaging; Indocyanine green; Carbon nanoparticles; Deep learning

Outcome Measures

Primary Outcomes (4)

• Sentinel Lymph Node Metastasis (SLNM) Status

  The presence or absence of cancer metastasis in the sentinel lymph node, determined by postoperative histopathological examination (paraffin section) as the gold standard. SLNM is classified as positive (macrometastasis or micrometastasis present) or negative (no metastasis). The SLNM rate is calculated as: number of participants with positive sentinel lymph nodes divided by total number of participants with successfully identified sentinel lymph nodes.

  immediately after the surgery

• Sentinel Lymph Node Detection Rate

  The proportion of participants in whom sentinel lymph nodes are successfully identified using each tracer method (ICG alone, CNs alone, or ICG+CNs dual-tracer). A sentinel lymph node is defined as the first lymph node visualized after tracer injection. Detection rate is calculated as: number of participants with successfully identified sentinel lymph nodes divided by total number of participants in each group, expressed as a percentage.

  immediately after the surgery

• Second-Echelon Lymph Node Metastasis (SeLNM)

  The presence or absence of cancer metastasis in second-echelon lymph nodes (lymph nodes beyond the sentinel node in the lymphatic drainage pathway), determined by postoperative histopathological examination. SeLNM is the primary prediction target for the deep learning models in the ICG+CNs group. SeLNM status is classified as positive or negative based on paraffin section pathology results.

  perioperatively

• Non-Sentinel Lymph Node Metastasis (NsLNM)

  The presence or absence of cancer metastasis in any lymph node other than the sentinel lymph node, determined by postoperative histopathological examination. NsLNM includes metastasis in central compartment nodes (prelaryngeal, pretracheal, paratracheal, and nodes posterior to recurrent laryngeal nerve) and lateral compartment nodes when dissected. NsLNM is the second primary prediction target for the deep learning models in the ICG+CNs group.

  perioperatively

Secondary Outcomes (6)

• Sensitivity of Sentinel Lymph Node Mapping

  through study completion, an average of 1 year

• Specificity of Sentinel Lymph Node Mapping

  through study completion, an average of 1 year

• Positive Predictive Value (PPV) of Sentinel Lymph Node Mapping

  through study completion, an average of 1 year

• Negative Predictive Value (NPV) of Sentinel Lymph Node Mapping

  through study completion, an average of 1 year

• Deep Learning Model Performance - Area Under ROC Curve (AUC)

  through study completion, an average of 1 year

Other Outcomes (5)

• Number of Sentinel Lymph Nodes Identified

  immediately after surgery

• Total Number of Lymph Nodes Retrieved

  perioperatively

• Feature Importance from SHAP Analysis

  through study completion, an average of 1 year

Study Arms (3)

ICG Group

Adults with clinically node-negative papillary thyroid carcinoma (cN0-PTC) who undergo intraoperative sentinel lymph node mapping using indocyanine green (ICG) alone. Intervention: 0.2 ml of ICG solution (concentration: 2.5 mg/ml) injected at multiple points around the thyroid tumor under ultrasound guidance. Near-infrared fluorescence imaging is used to visualize lymphatic drainage and identify sentinel lymph nodes. Participants undergo standard thyroid surgery including thyroid lobectomy and central lymph node dissection, with additional dissection based on intraoperative findings.

Diagnostic Test: Carbon nanoparticle (CNs) sentinel lymph node mapping

CNs Group

Adults with clinically node-negative papillary thyroid carcinoma (cN0-PTC) who undergo intraoperative sentinel lymph node mapping using carbon nanoparticles (CNs) alone. Intervention: 0.2 ml of carbon nanoparticle suspension (concentration: 50 mg/ml) injected at multiple points around the thyroid tumor under ultrasound guidance. Black staining is used to visualize lymph nodes during surgery. Participants undergo standard thyroid surgery including thyroid lobectomy and central lymph node dissection, with additional dissection based on intraoperative findings.

Diagnostic Test: Indocyanine green (ICG) sentinel lymph node mapping

ICG+CNs Group (Dual-Tracer)

Adults with clinically node-negative papillary thyroid carcinoma (cN0-PTC) who undergo intraoperative sentinel lymph node mapping using combined indocyanine green and carbon nanoparticles (dual-tracer technique). Intervention: A mixture of 0.1 ml ICG solution (concentration: 2.5 mg/ml) and 0.1 ml carbon nanoparticle suspension (concentration: 50 mg/ml) injected at multiple points around the thyroid tumor under ultrasound guidance. Near-infrared fluorescence imaging combined with visual black staining is used to visualize lymphatic drainage and identify sentinel lymph nodes. This group also undergoes deep learning video analysis of the fluorescence imaging process to predict lymph node metastasis. Participants undergo standard thyroid surgery including thyroid lobectomy and central lymph node dissection, with additional dissection based on intraoperative findings.

Diagnostic Test: Dual-tracer (ICG combined with CNs) sentinel lymph node mapping

Interventions

Indocyanine green (ICG) sentinel lymph node mapping DIAGNOSTIC_TEST

Intraoperative sentinel lymph node mapping using indocyanine green (ICG) with near-infrared fluorescence imaging. Preparation: ICG powder (25 mg) is dissolved in 10 ml sterile water to achieve a concentration of 2.5 mg/ml. Administration: 0.2 ml of ICG solution is injected at multiple points around the thyroid tumor under real-time ultrasound guidance using a precision multi-point stereotactic injection technique. Visualization: A near-infrared fluorescence imaging system (excitation wavelength 750-800 nm, emission wavelength 820 nm) is used to visualize lymphatic channels and identify sentinel lymph nodes in real time during surgery. The sentinel lymph node is defined as the first lymph node that shows fluorescence signal after tracer injection.

Also known as: ICG fluorescence lymphography, Near-infrared fluorescence sentinel lymph node identification

CNs Group

Carbon nanoparticle (CNs) sentinel lymph node mapping DIAGNOSTIC_TEST

Intraoperative sentinel lymph node mapping using carbon nanoparticle suspension with visual identification. Preparation: Carbon nanoparticle suspension is used at the commercial concentration of 50 mg/ml. Administration: 0.2 ml of carbon nanoparticle suspension is injected at multiple points around the thyroid tumor under real-time ultrasound guidance using a precision multi-point stereotactic injection technique. Visualization: Carbon nanoparticles (diameter 150 nm) selectively enter lymphatic channels and accumulate in lymph nodes, producing visible black staining. Surgeons identify sentinel lymph nodes by direct visual inspection of black-stained nodes. The sentinel lymph node is defined as the first lymph node that shows black staining after tracer injection.

Also known as: Carbon nanoparticle suspension lymph node tracing, Nano-carbon lymphatic mapping

ICG Group

Dual-tracer (ICG combined with CNs) sentinel lymph node mapping DIAGNOSTIC_TEST

Intraoperative sentinel lymph node mapping using combined indocyanine green and carbon nanoparticles with near-infrared fluorescence imaging and visual identification. Preparation: 0.1 ml of ICG solution (2.5 mg/ml) is mixed with 0.1 ml of carbon nanoparticle suspension (50 mg/ml) to form a 0.2 ml dual-tracer composite agent. Administration: The mixed tracer is injected at multiple points around the thyroid tumor under real-time ultrasound guidance using a precision multi-point stereotactic injection technique. Visualization: Near-infrared fluorescence imaging captures real-time lymphatic flow dynamics (ICG component), while black staining provides durable visual lymph node identification (CNs component). Video recording documents the entire sentinel lymph node visualization process for at least 5 minutes at 1920x1080 resolution. Deep learning analysis: In this group, video recordings are analyzed using nine deep learning models to extract spatiotemporal features and predict second

Also known as: Combined ICG and carbon nanoparticle lymphatic mapping, Dual-tracer fluorescence and visual lymph node identification

ICG+CNs Group (Dual-Tracer)

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Adults diagnosed with clinically node-negative papillary thyroid carcinoma (cN0-PTC) who are scheduled to undergo surgical treatment at the Department of Breast and Thyroid Surgery, First Affiliated Hospital of Chongqing Medical University, Chongqing, China. Participants are identified through routine clinical care and preoperative evaluation. The study population includes patients with primary PTC confirmed by fine-needle aspiration biopsy who have no evidence of lymph node metastasis on preoperative ultrasound or other imaging studies. Both male and female adults aged 18 years and older are eligible regardless of tumor size, location, or genetic mutation status.

You may qualify if:

• Age 18 years or older at the time of enrollment
• Histologically confirmed papillary thyroid carcinoma (PTC) by preoperative fine-needle aspiration biopsy
• Clinically node-negative (cN0) status confirmed by preoperative imaging (ultrasound and/or cross-sectional imaging showing no evidence of lymph node metastasis)
• Scheduled to undergo thyroid surgery with simultaneous central lymph node dissection
• Willing and able to provide written informed consent
• Complete preoperative clinical data available, including:
• Demographic information (age, sex, body mass index)
• Thyroid ultrasound report with detailed tumor characteristics
• Fine-needle aspiration biopsy pathology report
• Genetic testing results (when available)
• Able to undergo intraoperative dual-tracer sentinel lymph node mapping with near-infrared fluorescence video recording

You may not qualify if:

• History of previous neck surgery (including thyroid surgery, parathyroid surgery, or other cervical operations)
• History of external beam radiotherapy to the head and neck region
• Diagnosis of thyroid malignancy other than papillary thyroid carcinoma (e.g., follicular thyroid carcinoma, medullary thyroid carcinoma, anaplastic thyroid carcinoma, or thyroid lymphoma)
• Known allergy or hypersensitivity to indocyanine green (ICG), iodine, or carbon nanoparticles
• Severe hepatic insufficiency (ICG is metabolized by the liver)
• Pregnancy or breastfeeding
• Incomplete medical records or missing essential preoperative data
• Refusal to undergo dual-tracer imaging procedure
• Inability to obtain satisfactory intraoperative near-infrared fluorescence video recording due to technical issues or poor image quality
• Participation in another interventional clinical trial that may interfere with the current study
• Any condition that, in the investigator's opinion, would compromise the participant's safety or the quality of the study data

Sponsors & Collaborators

• First Affiliated Hospital of Chongqing Medical University: lead

Study Sites (1)

The First Affiliated Hospital of Chongqing Medical University

Chongqing, 400016, China

Location

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• Liang M, Zhu T, Huang N, Zhang L, Yang C, Gao H, Zhang X, Li P, Cheng M, Wang K. Incorporating sentinel chain involvement pattern to predict non-sentinel lymph nodes status in breast cancer after neoadjuvant chemotherapy. Clin Transl Oncol. 2026 Jan;28(1):203-214. doi: 10.1007/s12094-025-03993-z. Epub 2025 Jul 31.

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• Mittendorf EA, Hunt KK, Boughey JC, Bassett R, Degnim AC, Harrell R, Yi M, Meric-Bernstam F, Ross MI, Babiera GV, Kuerer HM, Hwang RF. Incorporation of sentinel lymph node metastasis size into a nomogram predicting nonsentinel lymph node involvement in breast cancer patients with a positive sentinel lymph node. Ann Surg. 2012 Jan;255(1):109-15. doi: 10.1097/SLA.0b013e318238f461.

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• Zhou L, Yao J, Ou D, Li M, Lei Z, Wang L, Xu D. A multi-institutional study of association of sonographic characteristics with cervical lymph node metastasis in unifocal papillary thyroid carcinoma. Front Endocrinol (Lausanne). 2022 Sep 23;13:965241. doi: 10.3389/fendo.2022.965241. eCollection 2022.

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• Khan SU, Fatima K, Malik F, Kalkavan H, Wani A. Cancer metastasis: Molecular mechanisms and clinical perspectives. Pharmacol Ther. 2023 Oct;250:108522. doi: 10.1016/j.pharmthera.2023.108522. Epub 2023 Sep 1.

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• Cao R, Ji H, Feng N, Zhang Y, Yang X, Andersson P, Sun Y, Tritsaris K, Hansen AJ, Dissing S, Cao Y. Collaborative interplay between FGF-2 and VEGF-C promotes lymphangiogenesis and metastasis. Proc Natl Acad Sci U S A. 2012 Sep 25;109(39):15894-9. doi: 10.1073/pnas.1208324109. Epub 2012 Sep 11.

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• Li Y, Chen H, Zhao Y, Yan Q, Chen L, Song Q. circUBE2G1 interacts with hnRNPU to promote VEGF-C-mediated lymph node metastasis of lung adenocarcinoma. Front Oncol. 2024 Nov 27;14:1455909. doi: 10.3389/fonc.2024.1455909. eCollection 2024.

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• Guang Y, Wan F, He W, Zhang W, Gan C, Dong P, Zhang H, Zhang Y. A model for predicting lymph node metastasis of thyroid carcinoma: a multimodality convolutional neural network study. Quant Imaging Med Surg. 2023 Dec 1;13(12):8370-8382. doi: 10.21037/qims-23-318. Epub 2023 Nov 7.

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• Luo QW, Gao S, Lv X, Li SJ, Wang BF, Han QQ, Wang YP, Guan QL, Gong T. A novel tool for predicting the risk of central lymph node metastasis in patients with papillary thyroid microcarcinoma: a retrospective cohort study. BMC Cancer. 2022 Jun 2;22(1):606. doi: 10.1186/s12885-022-09655-5.

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• Popadich A, Levin O, Lee JC, Smooke-Praw S, Ro K, Fazel M, Arora A, Tolley NS, Palazzo F, Learoyd DL, Sidhu S, Delbridge L, Sywak M, Yeh MW. A multicenter cohort study of total thyroidectomy and routine central lymph node dissection for cN0 papillary thyroid cancer. Surgery. 2011 Dec;150(6):1048-57. doi: 10.1016/j.surg.2011.09.003.

  PMID: 22136820 RESULT

• Huang C, Cong S, Shang S, Wang M, Zheng H, Wu S, An X, Liang Z, Zhang B. Web-Based Ultrasonic Nomogram Predicts Preoperative Central Lymph Node Metastasis of cN0 Papillary Thyroid Microcarcinoma. Front Endocrinol (Lausanne). 2021 Sep 7;12:734900. doi: 10.3389/fendo.2021.734900. eCollection 2021.

  PMID: 34557165 RESULT

• Wang Y, Deng C, Shu X, Yu P, Wang H, Su X, Tan J. Risk Factors and a Prediction Model of Lateral Lymph Node Metastasis in CN0 Papillary Thyroid Carcinoma Patients With 1-2 Central Lymph Node Metastases. Front Endocrinol (Lausanne). 2021 Oct 15;12:716728. doi: 10.3389/fendo.2021.716728. eCollection 2021.

  PMID: 34721289 RESULT

• Chun L, Wang D, He L, Li D, Fu Z, Xue S, Su X, Zhou J. Explainable machine learning model for predicting paratracheal lymph node metastasis in cN0 papillary thyroid cancer. Sci Rep. 2024 Sep 27;14(1):22361. doi: 10.1038/s41598-024-73837-3.

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  PMID: 39085674 RESULT

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  PMID: 37271573 RESULT

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  PMID: 34916044 RESULT

• Garau LM, Rubello D, Ferretti A, Boni G, Volterrani D, Manca G. Sentinel lymph node biopsy in small papillary thyroid cancer. A review on novel surgical techniques. Endocrine. 2018 Nov;62(2):340-350. doi: 10.1007/s12020-018-1658-5. Epub 2018 Jul 2.

  PMID: 29968226 RESULT

• Garau LM, Rubello D, Morganti R, Boni G, Volterrani D, Colletti PM, Manca G. Sentinel Lymph Node Biopsy in Small Papillary Thyroid Cancer: A Meta-analysis. Clin Nucl Med. 2019 Feb;44(2):107-118. doi: 10.1097/RLU.0000000000002378.

  PMID: 30418209 RESULT

• Santrac N, Markovic I, Medic Milijic N, Goran M, Buta M, Djurisic I, Dzodic R. Sentinel lymph node biopsy in medullary thyroid microcarcinomas. Endocr J. 2020 Mar 28;67(3):295-304. doi: 10.1507/endocrj.EJ19-0409. Epub 2019 Dec 3.

  PMID: 31801918 RESULT

• Boschin IM, Bertazza L, Scaroni C, Mian C, Pelizzo MR. Sentinel lymph node mapping: current applications and future perspectives in thyroid carcinoma. Front Med (Lausanne). 2023 Oct 24;10:1231566. doi: 10.3389/fmed.2023.1231566. eCollection 2023.

  PMID: 37942415 RESULT

• Likhterov I, Reis LL, Urken ML. Central compartment management in patients with papillary thyroid cancer presenting with metastatic disease to the lateral neck: Anatomic pathways of lymphatic spread. Head Neck. 2017 May;39(5):853-859. doi: 10.1002/hed.24568. Epub 2017 Mar 2.

  PMID: 28252836 RESULT

• Yan X, Zeng R, Ma Z, Chen C, Chen E, Zhang X, Cao F. The Utility of Sentinel Lymph Node Biopsy in Papillary Thyroid Carcinoma with Occult Lymph Nodes. PLoS One. 2015 Jun 5;10(6):e0129304. doi: 10.1371/journal.pone.0129304. eCollection 2015.

  PMID: 26046782 RESULT

• Yan XQ, Ma ZS, Zhang ZZ, Xu D, Cai YJ, Wu ZG, Zheng ZQ, Xie BJ, Cao FL. The utility of sentinel Lymph node biopsy in the lateral neck in papillary thyroid carcinoma. Front Endocrinol (Lausanne). 2022 Jul 25;13:937870. doi: 10.3389/fendo.2022.937870. eCollection 2022.

  PMID: 35957824 RESULT

• Huang H, Xu S, Ni S, Wang X, Liu S. A nomogram for predicting lateral lymph node metastasis in cN0 unifocal papillary thyroid microcarcinoma. BMC Cancer. 2023 Aug 1;23(1):718. doi: 10.1186/s12885-023-11219-0.

  PMID: 37528388 RESULT

• Zhou J, Li D, Xiao Q, Zhuang Y, Yang T, Xue S, Gao H, Su X. Bilateral chylothorax following papillary thyroid carcinoma with cervical lymph node dissection: Case report and comprehensive review of the literature. Medicine (Baltimore). 2024 Nov 8;103(45):e40371. doi: 10.1097/MD.0000000000040371.

  PMID: 39533596 RESULT

• Liu X, Li H, Zhang L, Gao Q, Wang Y. Development and validation of a multidimensional machine learning-based nomogram for predicting central lymph node metastasis in papillary thyroid microcarcinoma. Gland Surg. 2025 Mar 31;14(3):344-357. doi: 10.21037/gs-2024-508. Epub 2025 Mar 26.

  PMID: 40256479 RESULT

• Zheng G, Zhang H, Hao S, Liu C, Xu J, Ning J, Wu G, Jiang L, Li G, Zheng H, Song X. Patterns and clinical significance of cervical lymph node metastasis in papillary thyroid cancer patients with Delphian lymph node metastasis. Oncotarget. 2017 Jul 6;8(34):57089-57098. doi: 10.18632/oncotarget.19047. eCollection 2017 Aug 22.

  PMID: 28915656 RESULT

• Chen Y, Wang Y, Li C, Zhang X, Fu Y. Meta-analysis of the effect and clinical significance of Delphian lymph node metastasis in papillary thyroid cancer. Front Endocrinol (Lausanne). 2024 Jan 19;14:1295548. doi: 10.3389/fendo.2023.1295548. eCollection 2023.

  PMID: 38313842 RESULT

• Tang L, Qu RW, Park J, Simental AA, Inman JC. Prevalence of Occult Central Lymph Node Metastasis by Tumor Size in Papillary Thyroid Carcinoma: A Systematic Review and Meta-Analysis. Curr Oncol. 2023 Aug 2;30(8):7335-7350. doi: 10.3390/curroncol30080532.

  PMID: 37623013 RESULT

• Yao F, Yang Z, Li Y, Chen W, Wu T, Peng J, Jiao Z, Yang A. Real-World Evidence on the Sensitivity of Preoperative Ultrasound in Evaluating Central Lymph Node Metastasis of Papillary Thyroid Carcinoma. Front Endocrinol (Lausanne). 2022 Jun 9;13:865911. doi: 10.3389/fendo.2022.865911. eCollection 2022.

  PMID: 35757396 RESULT

• Gao MZ, Omer TM, Miller KM, Simpson MC, Bukatko AR, Gedion K, Adjei Boakye E, Kost KM, Dickinson JA, Varvares MA, Osazuwa-Peters N. Thyroid Cancer Incidence and Trends in United States and Canadian Pediatric, Adolescent, and Young Adults. Cancers (Basel). 2025 Apr 24;17(9):1429. doi: 10.3390/cancers17091429.

  PMID: 40361355 RESULT

Biospecimen

Retention: SAMPLES WITH DNA

Tissue specimens collected during thyroid cancer surgery include: 1. Sentinel lymph node tissue: The first-draining lymph node identified by dual-tracer mapping, submitted separately for pathological examination. 2. Central compartment lymph node tissue: Specimens from prelaryngeal, pretracheal, paratracheal regions, and lymph nodes posterior to the recurrent laryngeal nerve. 3. Lateral compartment lymph node tissue: When indicated based on intraoperative findings. 4. Thyroid tissue: From lobectomy or thyroidectomy specimens. All specimens undergo: * Intraoperative frozen section analysis for immediate assessment * Postoperative formalin-fixed paraffin-embedded (FFPE) processing for definitive histopathological diagnosis * Genetic testing for mutation analysis (including BRAF mutation status) Tissue samples are stored according to institutional biobank protocols and may be used for future research with appropriate ethical approval.

MeSH Terms

Conditions

Thyroid Cancer, Papillary

Condition Hierarchy (Ancestors)

Adenocarcinoma, Papillary; Adenocarcinoma; Carcinoma; Neoplasms, Glandular and Epithelial; Neoplasms by Histologic Type; Neoplasms; Thyroid Neoplasms; Endocrine Gland Neoplasms; Neoplasms by Site; Head and Neck Neoplasms; Endocrine System Diseases; Thyroid Diseases

Study Officials

• Xinliang Su, MD,PhD

  First Affiliated Hospital of Chongqing Medical University

  STUDY DIRECTOR

• Han Gao, MD,PhD

  Children's Hospital of Chongqing Medical University

  STUDY CHAIR

• Xinliang Su, MD,PhD

  First Affiliated Hospital of Chongqing Medical University

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 12 Months
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Clinical Professor

Study Record Dates

• First Submitted: January 19, 2026
• First Posted: February 6, 2026
• Study Start: April 1, 2024
• Primary Completion: October 31, 2024
• Study Completion: October 31, 2024
• Last Updated: February 6, 2026

Record last verified: 2026-02

Locations

CN (1)