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

O-RADS for assessment of adnexal lesions: current status, challenges and future directions.

Cancer imaging : the official publication of the International Cancer Imaging Society·2026
Same author

Benign Lesions Scored as O-RADS US v2022 4 and 5 Categories: Prevalence and Morphologic Analysis.

Radiology·2026
Same author

Cystic Artery Velocity: Evaluation of Performance in the Sonographic Diagnosis of Acute Cholecystitis.

Academic radiology·2026
Same author

Early Detection and Screening: Making an Impact with Imaging.

Radiologic clinics of North America·2026
Same author

Breast tumor microbiome regulates anti-tumor immunity and T cell-associated metabolites.

Scientific reports·2026
Same author

O-RADS US Assessment: Expert Guidance on Fine-tuning US Images.

Radiographics : a review publication of the Radiological Society of North America, Inc·2026

Related Experiment Video

Updated: Feb 27, 2026

A Coregistered Ultrasound and Photoacoustic Imaging Protocol for the Transvaginal Imaging of Ovarian Lesions
10:21

A Coregistered Ultrasound and Photoacoustic Imaging Protocol for the Transvaginal Imaging of Ovarian Lesions

Published on: March 3, 2023

2.4K

MR Imaging-Pathologic Correlation in Ovarian Cancer.

Erica B Stein1, Ashish P Wasnik2, Andrew P Sciallis3

  • 1Department of Radiology, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI 48109, USA; Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop Street, Pittsburgh, PA 15213, USA.

Magnetic Resonance Imaging Clinics of North America
|July 3, 2017
PubMed
Summary
This summary is machine-generated.

Magnetic resonance (MR) imaging reveals diverse ovarian cancer subtypes. Multiparametric MR aids radiologists in diagnosing ovarian masses by analyzing tissue characteristics, improving clinical decisions.

Keywords:
Epithelial ovarian neoplasmsMagnetic resonance imagingOvarian cystOvarian germ cell tumorOvarian neoplasmSerous tubal intraepithelial carcinoma (STIC)Sex cord–stromal tumors

More Related Videos

Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
08:55

Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence

Published on: November 2, 2014

12.9K
Quantitation of Intra-peritoneal Ovarian Cancer Metastasis
10:58

Quantitation of Intra-peritoneal Ovarian Cancer Metastasis

Published on: July 18, 2016

11.5K

Related Experiment Videos

Last Updated: Feb 27, 2026

A Coregistered Ultrasound and Photoacoustic Imaging Protocol for the Transvaginal Imaging of Ovarian Lesions
10:21

A Coregistered Ultrasound and Photoacoustic Imaging Protocol for the Transvaginal Imaging of Ovarian Lesions

Published on: March 3, 2023

2.4K
Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
08:55

Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence

Published on: November 2, 2014

12.9K
Quantitation of Intra-peritoneal Ovarian Cancer Metastasis
10:58

Quantitation of Intra-peritoneal Ovarian Cancer Metastasis

Published on: July 18, 2016

11.5K

Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Ovarian cancer presents with diverse subtypes and imaging appearances.
  • Accurate diagnosis and risk stratification are crucial for patient management.

Purpose of the Study:

  • To explore how fundamental magnetic resonance (MR) concepts guide ovarian mass diagnosis.
  • To evaluate the role of multiparametric MR in risk stratifying ovarian masses.

Main Methods:

  • Analysis of gross pathology and magnetic resonance (MR) imaging features.
  • Application of multiparametric MR techniques.
  • Correlation of imaging findings with underlying tissue characteristics.

Main Results:

  • Ovarian cancer subtypes exhibit varied presentations on MR imaging.
  • Fundamental MR concepts derived from tissue properties offer diagnostic clues.
  • Multiparametric MR demonstrates potential for risk stratification.

Conclusions:

  • Multiparametric MR imaging is valuable for diagnosing and risk stratifying ovarian masses.
  • Understanding MR characteristics aids radiologists in suggesting diagnoses.
  • Enhanced diagnostic capabilities improve clinical decision-making and patient care.