Evidence map›Paper›PMID 30059242›Full record

ArticleThe British journal of radiology2018

Preoperative axillary nodal staging with ultrasound and magnetic resonance imaging: predictive values of quantitative and semantic features.

Won Hwa Kim, Hye Jung Kim, So Mi Lee, Seung Hyun Cho, Kyung Min Shin, Sang Yub Lee, Jae Kwang Lim, Won Kee Lee

Abstract read
In one paragraph

Article in The British journal of radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
0.5field-weighted citation impact, top 41% 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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 13 citations in OpenAlex.

  1. Pooled it
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  9. Review
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  11. Prediction of high nodal burden with ultrasound and magnetic resonance imaging in clinically node-negative breast cancer patients.Cancer imaging : the official publication of the International Cancer Imaging Society · 2019
    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

8 authors at 2 institutions in 1 country.

Won Hwa Kim1 Department of Radiology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital , Daegu , South Korea.
Hye Jung Kim1 Department of Radiology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital , Daegu , South Korea.ORCID http://orcid.org/0000-0002-0263-0941
So Mi Lee1 Department of Radiology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital , Daegu , South Korea.
Seung Hyun Cho1 Department of Radiology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital , Daegu , South Korea.
Kyung Min Shin1 Department of Radiology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital , Daegu , South Korea.
Sang Yub Lee1 Department of Radiology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital , Daegu , South Korea.
Jae Kwang Lim1 Department of Radiology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital , Daegu , South Korea.
Won Kee Lee2 Center of Biostatistics, School of Medicine, Kyungpook National University , Daegu , South Korea.
Kyungpook National University Hospital · KRKyungpook National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objective: Although axillary imaging has recently received renewed interest for preoperative staging in tandem with the evolving minimally invasive surgical approaches, axillary imaging is limited by the lack of standardization in the interpretation. We aimed to classify imaging features in ultrasound and MRI into quantitative and semantic features and evaluate predictive value of each feature for predicting nodal metastases.

methods: A total of 316 breast cancers patients who underwent ultrasound and MRI prior to axillary surgery were included. Retrospective reviews of our breastimaging database were done for the quantitative features [cortical thickness (CT) and CT-derived parameters, long diameter (LD), short diameter (SD), and LD/SD ratio] and semantic features (eccentricity, loss of fatty hilum, and irregularity) of the axillary lymph node in images. Odd ratios (ORs) for each imaging feature were calculated with adjustment for clinicopathological characteristics significantly associated with nodal metastases.

results: All CT-derived parameters were significantly associated with nodal metastases in both ultrasound and MRI (OR, 3.3-3.5 for ultrasound and 3.3-3.9 for MRI, respectively; Ps < .05). For the ultrasound, LD/SD ratio (OR, 2.1), eccentricity (OR, 2.4), and fatty hilum loss (OR, 27.2) were significantly associated with nodal metastases (Ps < .05). For the MRI, SD (OR, 2.1) and eccentricity (OR, 3.0) were significantly associated with nodal metastases (Ps < .05).

conclusion: Among the quantitative features, all CT-derived parameters can be used for predicting nodal metastases. Significant predictors of semantic features were heterogeneous between ultrasound and MRI. ADVANCES IN KNOWLEDGE:: (1) Imaging features of ultrasound and MRI for preoperative axillary nodal staging can be classified into quantitative and semantic features. (2) Predictive values of each imaging features are heterogeneous for predicting nodal metastases.

Indexed as

Magnetic Resonance ImagingUltrasonography, MammaryAdultAgedAged, 80 and overAxillaBreast NeoplasmsFemaleHumansLymphatic MetastasisLymph NodesMiddle AgedNeoplasm StagingPreoperative CareRetrospective Studies

Identifiers

PMID30059242
PMCPMC6319840
OpenAlexW2886493310

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.