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

Treatment Resistant Cancers02:56

Treatment Resistant Cancers

3.8K
Cancer is the second leading cause of death in the United States. A cancer cell is genetically unstable and hence can mutate faster. They can also modify their microenvironment and escape immune surveillance. The difficulties in treating cancer are further compounded by the emergence of rapid resistance to anticancer drugs. The most common ways to attain resistance in cancer cells include alteration in drug transport and metabolism, modification of drug target, elevated DNA damage response, or...
3.8K
Diffusion01:12

Diffusion

219.5K
Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
219.5K
Diffusion01:21

Diffusion

6.4K
Diffusion is a type of passive transport. In passive transport, a substance tends to move from an area of high concentration to an area of low concentration until the concentration is equal across the space. For example, take the diffusion of substances through the air. When someone opens a perfume bottle in a room filled with people, the perfume is at its highest concentration in the bottle and is at its lowest at the edges of the room. The perfume vapor will diffuse, or spread away, from the...
6.4K
Weighted Mean00:57

Weighted Mean

6.4K
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
6.4K
Clinical Trials: Overview01:11

Clinical Trials: Overview

5.0K
Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
5.0K
Trial and Error and Algorithm01:12

Trial and Error and Algorithm

424
A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light...
424

You might also read

Related Articles

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

Sort by
Same author

From Uncertainty to Actionable Management: The Isolated Abnormal Axillary Lymph Node.

AJR. American journal of roentgenology·2026
Same author

Image Quality Assessment of Diffusion-Weighted Imaging (DWI) and Its Impact on Apparent Diffusion Coefficient (ADC) as a Quantitative Imaging Biomarker for Predicting Response to Neoadjuvant Chemotherapy in High-Risk Early Breast Cancer.

Tomography (Ann Arbor, Mich.)·2026
Same author

Deep Learning-Based Synthetic Contrast-Enhanced Breast MRI for Monitoring Response to Neoadjuvant Therapy.

Cancers·2026
Same author

Multimodality Evaluation of Regional Breast Lymph Nodes: Impact of Expected Changes in the Upcoming BI-RADS Sixth Edition.

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

Percutaneous Thermal Ablation for Early-Stage Breast Cancer: A Randomized Phase II "Pick-the-Winner" Trial.

Radiology. Imaging cancer·2026
Same author

Assessment of Early Breast Cancer Response to Chemotherapy with Ultrasound Radiomics.

Diagnostics (Basel, Switzerland)·2026

Related Experiment Video

Updated: Feb 5, 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

23.2K

Diffusion-weighted MRI Findings Predict Pathologic Response in Neoadjuvant Treatment of Breast Cancer: The ACRIN 6698

Savannah C Partridge1, Zheng Zhang1, David C Newitt1

  • 1From the Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (S.C.P.); Department of Biostatistics (Z.Z.) and Center for Statistical Sciences (Z.Z., H.S.M., J.R.), Brown University, Providence, RI; American College of Radiology Imaging Network (ACRIN), Reston, Va (Z.Z., H.S.M., J.R.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (D.C.N., J.E.G., B.N.J., L.J.E., N.M.H.); Department of Radiology/MRI, University of Michigan, Ann Arbor, Mich (T.L.C.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (M.A.R.); Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minn (P.J.B.); American College of Radiology and ECOG-ACRIN Cancer Research Group, Reston, Va (L.C.); Department of Radiology, University of Alabama, Birmingham, Birmingham, Ala (H.R.U.); Department of Radiology, University of California, San Diego, San Diego, Calif (H.O.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex and the University of Texas Southwestern Medical Center, Dallas, Tex (B.D.); Department of Radiology, Oregon Health and Science University, Portland, Ore (K.O.); Department of Radiology, University of Chicago, Chicago, Ill (H.A.); and Department of Diagnostic Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Fla and Department of Women's Imaging, St Joseph's Women's Hospital, Tampa, Fla (J.S.D.).

Radiology
|September 5, 2018
PubMed
Summary

Change in apparent diffusion coefficient (ADC) on MRI predicts pathologic complete response (pCR) to neoadjuvant chemotherapy for breast cancer. Midtreatment ADC change is especially predictive for HR+/HER2- tumors.

More Related Videos

A Multicenter MRI Protocol for the Evaluation and Quantification of Deep Vein Thrombosis
10:26

A Multicenter MRI Protocol for the Evaluation and Quantification of Deep Vein Thrombosis

Published on: June 2, 2015

18.0K
Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer
07:45

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer

Published on: May 18, 2020

7.1K

Related Experiment Videos

Last Updated: Feb 5, 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

23.2K
A Multicenter MRI Protocol for the Evaluation and Quantification of Deep Vein Thrombosis
10:26

A Multicenter MRI Protocol for the Evaluation and Quantification of Deep Vein Thrombosis

Published on: June 2, 2015

18.0K
Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer
07:45

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer

Published on: May 18, 2020

7.1K

Area of Science:

  • Oncologic imaging
  • Breast cancer research
  • Radiomics

Background:

  • Neoadjuvant chemotherapy is a standard treatment for breast cancer.
  • Predicting treatment response is crucial for personalized therapy.
  • Diffusion-weighted MRI (DW-MRI) offers insights into tumor cellularity.

Purpose of the Study:

  • To evaluate if changes in tumor apparent diffusion coefficient (ADC) measured by DW-MRI can predict pathologic complete response (pCR) to neoadjuvant chemotherapy in breast cancer patients.
  • To assess the predictive performance of ADC changes across different breast cancer subtypes.

Main Methods:

  • Prospective multicenter study involving 272 women with breast cancer randomized to neoadjuvant chemotherapy.
  • Serial DW-MRI scans were performed before, during (3 and 12 weeks), and after treatment.
  • Percentage change in tumor ADC (ΔADC) from baseline was calculated at each time point.
  • Area under the receiver operating characteristic curve (AUC) was used to assess the predictive performance of ΔADC for pCR.

Main Results:

  • Of 242 evaluable patients, 80 (33%) achieved pCR.
  • Overall ΔADC moderately predicted pCR at midtreatment (12 weeks, AUC=0.60) and post-treatment (AUC=0.61).
  • Mdtreatment ΔADC was specifically predictive for hormone receptor-positive/HER2-negative (HR+/HER2-) tumors (AUC=0.76).
  • A combined model of tumor subtype and midtreatment ΔADC improved pCR prediction (AUC=0.72).

Conclusions:

  • Change in breast tumor ADC at 12 weeks of neoadjuvant chemotherapy predicts pCR.
  • ADC changes are valuable imaging biomarkers for treatment response assessment in breast cancer.
  • Tumor subtype combined with ADC changes enhances prediction accuracy, particularly for HR+/HER2- disease.