Evidence map›Paper›PMID 37393536›Full record

ArticleThe British journal of radiology2023

Computed diffusion-weighted imaging with a low-apparent diffusion coefficient-pixel cut-off technique for breast cancer detection.

Toshiki Kazama, Taro Takahara, Jun Endo, Hiroshi Yamamuro, Tatsuya Sekiguchi, Tetsu Niwa, Naoki Niikura, Takuho Okamura, Nobue Kumaki, Jun Hashimoto

Open access · greenAbstract read
In one paragraph

Article in The British journal of radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 34% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Utility of Echo-planar Imaging with Compressed Sensitivity Encoding (EPICS) in the Evaluation of Small Breast Cancers Using Diffusion-weighted Imaging with Background Suppression (DWIBS).Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025
    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

10 authors at 1 institution in 1 country.

Toshiki KazamaDepartment of Diagnostic Radiology, Tokai University School of Medicine, Isehara, Japan.ORCID 0000-0002-5588-4603
Taro TakaharaDepartment of Biomedical Engineering, Tokai University School of Engineering, Hiratsuka, Japan.
Jun EndoDepartment of Diagnostic Radiology, Tokai University School of Medicine, Isehara, Japan.
Hiroshi YamamuroDepartment of Diagnostic Radiology, Tokai University School of Medicine, Isehara, Japan.
Tatsuya SekiguchiDepartment of Diagnostic Radiology, Tokai University School of Medicine, Isehara, Japan.
Tetsu NiwaDepartment of Diagnostic Radiology, Tokai University School of Medicine, Isehara, Japan.
Naoki NiikuraDepartment of Breast Oncology, Tokai University School of Medicine, Isehara, Japan.
Takuho OkamuraDepartment of Breast Oncology, Tokai University School of Medicine, Isehara, Japan.
Nobue KumakiDepartment of Pathology, Tokai University School of Medicine, Isehara, Japan.
Jun HashimotoDepartment of Diagnostic Radiology, Tokai University School of Medicine, Isehara, Japan.
Tokai University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to compare the image quality and diagnostic performance of computed diffusion-weighted imaging (DWI) with low-apparent diffusion coefficient (ADC)-pixel cut-off technique (cDWI cut-off) and actual measured DWI (mDWI).

methodsEighty-seven consecutive patients with malignant breast lesions and 72 with negative breast lesions who underwent breast MRI were retrospectively evaluated. Computed DWI with high b-values of 800, 1200, and 1500 s/mm

resultsWhen an ADC cut-off threshold of 0.3 or 0.6 (× 10

conclusionThe cDWI cut-off provided better diagnostic performance than mDWI for breast cancer detection. ADVANCES IN KNOWLEDGE: Using the low-ADC-pixel cut-off technique, computed DWI can improve diagnostic performance by increasing contrast and eliminating un-suppressed fat signals.

Indexed as

Breast NeoplasmsBreastDiffusion Magnetic Resonance ImagingFemaleHumansRetrospective StudiesSensitivity and Specificity

Identifiers

PMID37393536
PMCPMC10607411
OpenAlexW4382881383

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.