Evidence map›Paper›PMID 36766617›Full record

ArticleDiagnostics (Basel, Switzerland)2023

Diagnostic Usefulness of Diffusion-Weighted MRI for Axillary Lymph Node Evaluation in Patients with Breast Cancer.

Pyeonghwa Cho, Chang Suk Park, Ga Eun Park, Sung Hun Kim, Hyeon Sook Kim, Se-Jeong Oh

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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.

Pyeonghwa ChoDepartment of Radiology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 21431, Republic of Korea.
Chang Suk ParkDepartment of Radiology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 21431, Republic of Korea.ORCID 0000-0002-0854-0111
Ga Eun ParkDepartment of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 06591, Republic of Korea.
Sung Hun KimDepartment of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 06591, Republic of Korea.ORCID 0000-0003-4478-9720
Hyeon Sook KimDepartment of Radiology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 21431, Republic of Korea.
Se-Jeong OhDepartment of General Surgery, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 21431, Republic of Korea.ORCID 0000-0002-2583-4218

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to determine whether apparent diffusion coefficient (ADC) and morphological features on diffusion-weighted MRI (DW-MRI) can discriminate metastatic axillary lymph nodes (ALNs) from benign in patients with breast cancer. Two radiologists measured ADC, long and short diameters, long-to-short diameter ratio, and cortical thickness and assessed eccentric cortical thickening, loss of fatty hilum, irregular margin, asymmetry in shape or number, and rim sign of ALNs on DW-MRI and categorized them into benign or suspicious ALNs. Pathologic reports were used as a reference standard. Statistical analysis was performed using the Mann-Whitney U test and chi-square test. Overall sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of DW-MRI were calculated. The ADC of metastatic ALNs was 0.905 × 10

Indexed as

apparent diffusion coefficient (ADC)axillabreast cancerdiffusion-weighted imaginglymph nodes

Identifiers

PMID36766617
PMCPMC9914452

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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.