Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Modification of Composite Separation Membranes with Citric Acid and Metal Ion Chelation Coatings for Oil-Water Separation.

Polymers·2026
Same author

Integrated transcriptome and metabolome analysis reveals the molecular mechanism underlying differences in Psa resistance between <i>Actinidia valvata</i> and <i>Actinidia chinensis</i>.

Frontiers in plant science·2026
Same author

Impact of metabolic syndrome on cardiac function and myocardial fibrosis in hypertrophic obstructive cardiomyopathy following septal myectomy assessed by cardiac magnetic resonance.

Quantitative imaging in medicine and surgery·2026
Same author

Efficacy and safety of camrelizumab-based regimens in advanced squamous cell carcinoma patients: a prospective multicenter study.

Frontiers in pharmacology·2026
Same author

Three-dimensional echocardiography-derived myocardial mechanistic insights into obstructive hypertrophic cardiomyopathy with moderate septal hypertrophy.

BMC medical imaging·2026
Same author

Homoepitaxial Seed-Mediated Growth for High-Efficiency FAPbI<sub>3</sub> Perovskite Solar Cells.

ChemSusChem·2026

Related Experiment Video

Updated: Jun 25, 2025

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment
10:39

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

Published on: May 24, 2022

2.3K

Histogram analysis comparison of readout-segmented and single-shot echo-planar imaging for differentiating luminal

Yiqi Hu1, Qilan Hu1, Zhiqiang Liu1

  • 1Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.

Scientific Reports
|May 27, 2024
PubMed
Summary
This summary is machine-generated.

This study found that readout-segmented echo-planar imaging (rs-EPI) diffusion-kurtosis imaging (DKI) metrics, particularly MK75th, are superior to single-shot echo-planar imaging (ss-EPI) for differentiating luminal from non-luminal breast cancer.

Keywords:
LuminalMagnetic resonance imagingNon-luminalRs-EPISs-EPI

More Related Videos

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
15:48

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

22.5K
Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
11:12

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material

Published on: August 1, 2018

8.0K

Related Experiment Videos

Last Updated: Jun 25, 2025

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment
10:39

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

Published on: May 24, 2022

2.3K
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
15:48

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

22.5K
Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
11:12

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material

Published on: August 1, 2018

8.0K

Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Distinguishing between luminal and non-luminal breast cancer subtypes is crucial for treatment selection.
  • Diffusion-weighted imaging (DWI) and diffusion-kurtosis imaging (DKI) offer insights into tissue microstructure.
  • Comparing different DWI acquisition techniques, such as single-shot echo-planar imaging (ss-EPI) and readout-segmented echo-planar imaging (rs-EPI), is important for optimizing diagnostic performance.

Purpose of the Study:

  • To compare the efficacy of DKI and DWI parameters derived from ss-EPI and rs-EPI sequences in differentiating luminal from non-luminal breast cancer using histogram analysis.
  • To identify which imaging sequence and histogram metric provides the best diagnostic performance for breast cancer subtyping.

Main Methods:

  • 160 women with breast lesions (111 luminal, 49 non-luminal) underwent both ss-EPI and rs-EPI DWI sequences on a 3.0T scanner.
  • Histogram metrics, including mean kurtosis (MK), mean diffusion (MD), and apparent diffusion coefficient (ADC), were calculated.
  • Statistical analyses (t-test, Mann-Whitney U) and ROC curve analysis were used to evaluate diagnostic performance.

Main Results:

  • Luminal breast cancer showed significantly higher MKmean, MK50th, and MK75th values compared to non-luminal breast cancer for both DWI sequences (P<0.05).
  • The rs-EPI sequence demonstrated superior diagnostic performance over the ss-EPI sequence in differentiating breast cancer subtypes.
  • MK75th derived from rs-EPI was the most effective single metric, achieving an AUC of 0.891, with 78.4% sensitivity and 87.8% specificity.

Conclusions:

  • Histogram metrics derived from DKI, particularly MK, show promise in differentiating luminal from non-luminal breast cancer.
  • The rs-EPI acquisition technique offers improved diagnostic performance compared to ss-EPI for this differentiation.
  • MK75th from rs-EPI is a highly valuable metric for distinguishing between luminal and non-luminal breast cancer subtypes.