Evidence map›Paper›PMID 34341731›Full record

ArticleQuantitative imaging in medicine and surgery2021

Unicentric Castleman disease: multidetector computed tomography classification with surgical and pathologic correlation.

Xiaoli Sun, Ye Du, Ying Zhang, Rengui Wang, Dailun Hou

Open access · diamondAbstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 42% of its field
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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. [The clinicopathologic features of unicentric Castleman disease in the children's neck].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2024
    Observational
  4. Unicentric Castleman Disease: A Rare Diagnosis of Radiological and Histological Correlation.Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India · 2023
    Article
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

5 authors at 3 institutions in 1 country.

Xiaoli SunDepartment of Radiology, Beijing Shijitan Hospital, Peking University Ninth School of Clinical Medicine, Capital Medical University, Beijing, China.
Ye DuDepartment of Nephrology, Beijing Shijitan Hospital, Peking University Ninth School of Clinical Medicine, Capital Medical University, Beijing, China.
Ying ZhangDepartment of Pathology, Beijing Shijitan Hospital, Peking University Ninth School of Clinical Medicine, Capital Medical University, Beijing, China.
Rengui WangDepartment of Radiology, Beijing Shijitan Hospital, Peking University Ninth School of Clinical Medicine, Capital Medical University, Beijing, China.
Dailun HouDepartment of Radiology, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Capital Medical University · CNBeijing Chest Hospital · CNBeijing Shijitan Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to correlate multidetector computed tomography (MDCT) classification of unicentric Castleman disease with the surgical and pathologic features.

methodsThe imaging manifestations of 63 cases of unicentric Castleman disease confirmed by pathology were retrospectively analyzed. Every patient underwent an MDCT examination. Classification based on imaging manifestations, surgical, histopathological, and imaging features were simultaneously reviewed and analyzed by two radiologists, with any disagreements resolved by consensus.

resultsSixty-three patients with unicentric Castleman disease were divided into I-IV types by imaging manifestations: type I, single mass with smooth margin (n=5); type II, single mass with irregular or lobulated margin (n=33); type III, single invasive mass with blurred margin (n=20); and type IV, multiple fused masses (n=5). Thirty-eight cases of type I and type II were diagnosed as hyaline-vascular type by pathology after complete surgical resection; 20 cases were type III, in which eight cases were partially resected, 17 cases were pathologically diagnosed as hyaline-vascular type, and the remaining three cases were a mixed type. In five cases of type IV that could not be completely resected, four cases were hyaline-vascular type, and one case was plasma cell type.

conclusionsMDCT is an excellent tool for the detection and diagnosis of unicentric Castleman disease. Classification by MDCT features is a reliable method for evaluating tumor infiltration and growth mode, which helps surgical optimization.

Indexed as

classificationmultidetector computed tomographyUnicentric Castleman disease (UCD)

Identifiers

PMID34341731
PMCPMC8245968
OpenAlexW3162802614

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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.