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

Assessment of Diffusion and Perfusion01:17

Assessment of Diffusion and Perfusion

1.5K
Understanding and evaluating diffusion and perfusion is critical in assessing a patient's respiratory and circulatory health. These processes play key roles in maintaining the body's internal environment, ensuring that tissues receive adequate oxygen while waste products are efficiently removed.
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this...
1.5K
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

280
DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
280
Imaging Studies IV: Magnetic Resonance Imaging01:27

Imaging Studies IV: Magnetic Resonance Imaging

219
Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...
219
Imaging Studies VII: Vascular Imaging01:19

Imaging Studies VII: Vascular Imaging

303
DefinitionRenal angiography, also known as renal arteriography, is an imaging technique used to obtain a comprehensive view of blood flow and the vascular structure of blood vessels in the kidneys and surrounding areas.PurposeRenal angiography detects blood vessel abnormalities in the kidneys, such as aneurysms, stenosis, thrombosis, vascular tumors, and renal artery stenosis. It evaluates kidney function and guides interventional treatments like angioplasty or stent placement.Pre-Procedure...
303
Imaging Studies II: Positron Emission Tomography and Scintigraphy01:25

Imaging Studies II: Positron Emission Tomography and Scintigraphy

493
Positron Emission Tomography (PET) is a medical imaging technique that provides crucial insights into the body's physiological functions at a molecular level. It is an indispensable resource for diagnosing, staging, and monitoring various illnesses, notably cancer, neurological disorders, and cardiovascular conditions.
Fundamental Principles of PET
493
Radiological Investigation II: MRI and Ventilation Perfusion Scan01:30

Radiological Investigation II: MRI and Ventilation Perfusion Scan

521
Description
Magnetic Resonance Imaging (MRI) and Ventilation Perfusion Scans are two radiological investigations that offer detailed diagnostic images of the body, particularly lung structures.
MRI
MRI uses magnetic fields and radiofrequency signals to distinguish between normal and abnormal tissues. This technology provides a more detailed diagnostic image than CT scans, enabling it to characterize pulmonary nodules, stage bronchogenic carcinoma, and evaluate inflammatory activity in...
521

You might also read

Related Articles

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

Sort by
Same author

Correction: He et al. An Edge-Computing-Based Emotion-Aware Adaptive Lighting System for Intelligent Cockpits. <i>Sensors</i> 2026, <i>26</i>, 3489.

Sensors (Basel, Switzerland)·2026
Same author

A pulsar escaping an ancient open cluster via tidal stripping.

Science bulletin·2026
Same author

MXene-Configured Intelligent Mask for Long-Term Sleep Breathing Assessment during Assisted Ventilation.

ACS sensors·2026
Same author

R-loops and D-loops: a delicate balance in genomic stability and instability.

Cell communication and signaling : CCS·2026
Same author

Dynamic Valence-State-Adaptive Ta Single-Atom Sites for Artificial H<sub>2</sub>O<sub>2</sub> Photosynthesis.

Journal of the American Chemical Society·2026
Same author

Prediction models for mortality in patients with acute on chronic liver failure: systematic review and critical appraisal.

Frontiers in medicine·2026

Related Experiment Video

Updated: Jan 13, 2026

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

23.1K

AI-driven diffusion weighted imaging-based non-contrast protocol for breast cancer diagnosis: a multicentre,

Yulu Liu1,2, Haoquan Chen1, Jiaqi Zhao3

  • 1Department of Radiology, Peking University People's Hospital, Beijing, 100044, China.

Eclinicalmedicine
|January 7, 2026
PubMed
Summary

A deep learning model using diffusion-weighted imaging (DWI) accurately diagnoses breast cancer, matching enhanced MRI performance while reducing interpretation time. This AI tool offers a faster, safer alternative for breast cancer diagnosis.

Keywords:
Breast cancerDeep learningDiagnostic modelDiffusion weighted MRIMultireader multicase study

More Related Videos

Multi-modal Imaging of Angiogenesis in a Nude Rat Model of Breast Cancer Bone Metastasis Using Magnetic Resonance Imaging, Volumetric Computed Tomography and Ultrasound
12:23

Multi-modal Imaging of Angiogenesis in a Nude Rat Model of Breast Cancer Bone Metastasis Using Magnetic Resonance Imaging, Volumetric Computed Tomography and Ultrasound

Published on: August 14, 2012

14.8K
Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring
17:16

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Published on: December 9, 2010

10.7K

Related Experiment Videos

Last Updated: Jan 13, 2026

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

23.1K
Multi-modal Imaging of Angiogenesis in a Nude Rat Model of Breast Cancer Bone Metastasis Using Magnetic Resonance Imaging, Volumetric Computed Tomography and Ultrasound
12:23

Multi-modal Imaging of Angiogenesis in a Nude Rat Model of Breast Cancer Bone Metastasis Using Magnetic Resonance Imaging, Volumetric Computed Tomography and Ultrasound

Published on: August 14, 2012

14.8K
Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring
17:16

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Published on: December 9, 2010

10.7K

Area of Science:

  • Radiology and Medical Imaging
  • Artificial Intelligence in Healthcare
  • Oncology

Background:

  • Contrast-enhanced breast MRI is sensitive but complex, time-consuming, and uses contrast agents.
  • Noncontrast diffusion-weighted imaging (DWI) is fast but lacks diagnostic accuracy for standalone use.
  • Investigating a deep learning (DL) model to improve DWI accuracy for breast cancer diagnosis.

Purpose of the Study:

  • To develop and validate a deep learning (DL) model for breast cancer diagnosis using only diffusion-weighted imaging (DWI).
  • To compare the diagnostic performance of the DWI-DL model against abbreviated enhanced-based (AE-DL) models and expert radiologists.
  • To evaluate the clinical utility of the DWI-DL model in a selective contrast-enhanced workflow.

Main Methods:

  • A DWI-based DL model (DWI-DL) was developed using data from 1286 patients.
  • Independent testing involved three external cohorts (n=661) and a prospective cohort (n=546).
  • Multireader multicase validation assessed the AI-guided selective sequence protocol's performance and interpretation time.

Main Results:

  • The DWI-DL model showed diagnostic performance comparable to the AE-DL model across all cohorts (AUC: 0.771-0.912 vs. 0.780-0.898).
  • DWI-DL outperformed expert radiologists interpreting DWI alone (AUC: 0.781-0.858 vs. 0.714-0.770).
  • The AI-guided selective protocol was non-inferior to the full protocol (AUC: 0.834 vs. 0.835) and reduced interpretation time by 55.5%.

Conclusions:

  • A DL model utilizing only noncontrast DWI can accurately diagnose breast cancer.
  • The DWI-DL model offers robust performance, surpassing human DWI interpretation and reducing time.
  • The DWI-DL model combined with selective contrast-enhanced sequences presents a promising tool to streamline breast cancer diagnosis.