Evidence map›Paper›PMID 27127579›Full record

ArticleIranian journal of radiology : a quarterly journal published by the Iranian Radiological Society2016

Significance of Additional Non-Mass Enhancement in Patients with Breast Cancer on Preoperative 3T Dynamic Contrast Enhanced MRI of the Breast.

Yun Hee Cho, Kyu Ran Cho, Eun Kyung Park, Bo Kyoung Seo, Ok Hee Woo, Sung Bum Cho, Jeoung Won Bae

Registry-linked trialOpen access · diamondAbstract read
In one paragraph

Article in Iranian journal of radiology : a quarterly journal published by the Iranian Radiological Society, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04083027 (Patterns of Non-mass Enhancement of Breast MRI Using the BI-RADS Lexicon Fifth Edition With Histopathologic Correlation), which is not on this map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.1field-weighted citation impact, top 10% 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.

NCT04083027 completednot on this mapstarted 2020, after this paper: background citation

Patterns of Non-mass Enhancement of Breast MRI Using the BI-RADS Lexicon Fifth Edition With Histopathologic Correlation

TypeobservationalSponsorAssiut UniversityRan2020 to 2021Enrolled66ConditionsBreast NeoplasmArmsMRI
3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 34 citations in OpenAlex.

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  11. Takeaways from Pre-Contrast T1 and T2 Breast Magnetic Resonance Imaging in Women with Recently Diagnosed Breast Cancer.Iranian journal of radiology : a quarterly journal published by the Iranian Radiological Society · 2016
    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

7 authors at 1 institution in 1 country.

Yun Hee ChoDepartment of Radiology, College of Medicine, Korea University, Seoul, Korea.
Kyu Ran ChoDepartment of Radiology, College of Medicine, Korea University, Seoul, Korea.
Eun Kyung ParkDepartment of Radiology, College of Medicine, Korea University, Seoul, Korea.
Bo Kyoung SeoDepartment of Radiology, College of Medicine, Korea University, Seoul, Korea.
Ok Hee WooDepartment of Radiology, College of Medicine, Korea University, Seoul, Korea.
Sung Bum ChoDepartment of Radiology, College of Medicine, Korea University, Seoul, Korea.
Jeoung Won BaeDepartment of Surgery, College of Medicine, Korea University, Seoul, Korea.
Korea University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn preoperative assessment of breast cancer, MRI has been shown to identify more additional breast lesions than are detectable using conventional imaging techniques. The characterization of additional lesions is more important than detection for optimal surgical treatment. Additional breast lesions can be included in focus, mass, and non-mass enhancement (NME) on MRI. According to the fifth edition of the breast imaging reporting and data system (BI-RADS®), which includes several changes in the NME descriptors, few studies to date have evaluated NME in preoperative assessment of breast cancer.

objectivesWe investigated the diagnostic accuracy of BI-RADS descriptors in predicting malignancy for additional NME lesions detected on preoperative 3T dynamic contrast enhanced MRI (DCE-MRI) in patients with newly diagnosed breast cancer. PATIENTS AND

methodsBetween January 2008 and December 2012, 88 patients were enrolled in our study, all with NME lesions other than the index cancer on preoperative 3T DCE-MRI and all with accompanying histopathologic examination. The MRI findings were analyzed according to the BI-RADS MRI lexicon. We evaluated the size, distribution, internal enhancement pattern, and location of NME lesions relative to the index cancer (i.e., same quadrant, different quadrant, or contralateral breast).

resultsOn histopathologic analysis of the 88 NME lesions, 73 (83%) were malignant and 15 (17%) were benign. Lesion size did not differ significantly between malignant and benign lesions (P = 0.410). Malignancy was more frequent in linear (P = 0.005) and segmental (P = 0.011) distributions, and benignancy was more frequent in focal (P = 0.004) and regional (P < 0.001) NME lesions. The highest positive predictive value (PPV) for malignancy occurred in segmental (96.8%), linear (95.1%), clustered ring (100%), and clumped (92.0%) enhancement. Asymmetry demonstrated a high positive predictive value of 85.9%. The frequency of malignancy was higher for NME lesions located in the same quadrant with the index cancer (P = 0.006), and benignancy was higher in the contralateral breast (P = 0.015). On multivariate analysis, linear (P = 0.001) and segmental (P = 0.005) distributions were significant predictors of malignancy.

conclusionThe possibility of malignancy is strongly indicated when additional NME lesions show linear or segmental enhancement on preoperative 3T DCE-MRI in patients with recently diagnosed breast cancer.

Indexed as

Breast NeoplasmsDiagnosisMagnetic Resonance ImagingNon-Mass EnhancementPreoperative Care

Identifiers

PMID27127579
PMCPMC4841862
OpenAlexW2245882012

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LicenceCC BY-NC
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Registered trials

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.