Evidence map›Paper›PMID 41417934›Full record

ArticleInternational journal of surgery (London, England)2026

Ectopic parathyroid adenomas in primary hyperparathyroidism: anatomical classifications, localization strategies, and case series.

Ruiying Zhu, Ning Yue, Yurong Hong, Qin Ye, Zhenyi Han, Zhiyan Luo, Chaoran Xie, Haichao Yan, Xing Yu

Abstract read
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Article in International journal of surgery (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Ruiying ZhuDepartment of Thyroid Surgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Ning YueDepartment of Thyroid Surgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Yurong HongDepartment of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Qin YeDepartment of Pathology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Zhenyi HanDepartment of Thyroid Surgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Zhiyan LuoDepartment of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Chaoran XieCollege of Medicine, Zhejiang University, Hangzhou, China.
Haichao YanDepartment of Thyroid Surgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Xing YuDepartment of Thyroid Surgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.ORCID 0000-0003-4059-3181

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEctopic parathyroid adenomas (EPAs) pose significant challenges in the diagnosis and management of primary hyperparathyroidism (PHPT) due to their atypical locations. This study aims to categorize EPAs based on their anatomical locations, describe the associated diagnostic strategies, and present case studies to illustrate clinical management.

methodsEPAs were retrospectively reviewed based on cases from published literature and our institutional experience. Relevant studies were identified through a systematic search of PubMed and Embase. A comprehensive anatomical classification system was developed, categorizing EPAs into pharyngocranial, cervical, and mediastinal regions.

resultsFrom a total of 1278 screened publications, 137 studies encompassing 875 EPAs were identified and included. Combined with 13 original cases from our institute, these cases were comprehensively analyzed to develop an anatomically based classification system. EPAs were categorized into four types based on anatomical location: Type I (pharyngocranial), Type II (cervical, adjacent to the thyroid), Type III (cervical, distant from the thyroid), and Type IV (mediastinal). A combination of imaging modalities, including ultrasonography, CT, MRI, sestamibi scintigraphy, and SPECT, proved effective for preoperative localization. Case studies highlight clinical outcomes and challenges associated with each type.

conclusionA comprehensive anatomical classification system for EPAs, integrated with advanced imaging modalities and correlated with biochemical profiles, improves preoperative identification and guides targeted treatment strategies.

Indexed as

anatomical classificationectopic parathyroid adenomasimaging modalitieslocalization strategiesprimary hyperparathyroidism

Identifiers

PMID41417934
PMCPMC13105754

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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.