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

Habitat Fragmentation02:31

Habitat Fragmentation

21.4K
Habitat fragmentation describes the division of a more extensive, continuous habitat into smaller, discontinuous areas. Human activities such as land conversion, as well as slower geological processes leading to changes in the physical environment, are the two leading causes of habitat fragmentation. The fragmentation process typically follows the same steps: perforation, dissection, fragmentation, shrinkage, and attrition.
21.4K
Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

253
Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
253
Diffusion01:12

Diffusion

218.6K
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...
218.6K
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
Facilitated Diffusion01:16

Facilitated Diffusion

1.3K
The plasma membrane, a critical structure in cellular biology, houses an array of transporters, or carrier proteins, interspersed within its lipid bilayer. These proteins play a crucial role in solute transport through facilitated diffusion, a form of passive diffusion that uses transporters to move the molecules across the membrane.
In this process, substrates such as organic compounds and ions interact with a transporter on one side, triggering conformational changes in proteins that enable...
1.3K
Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion03:48

Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion

31.3K
Although gaseous molecules travel at tremendous speeds (hundreds of meters per second), they collide with other gaseous molecules and travel in many different directions before reaching the desired target. At room temperature, a gaseous molecule will experience billions of collisions per second. The mean free path is the average distance a molecule travels between collisions. The mean free path increases with decreasing pressure; in general, the mean free path for a gaseous molecule will be...
31.3K

You might also read

Related Articles

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

Sort by
Same author

Quality of life results of addition of androgen deprivation therapy and pelvic lymph node treatment to prostate bed salvage radiotherapy: NRG Oncology/RTOG 0534 SPPORT.

International journal of radiation oncology, biology, physics·2026
Same author

Participant Heterogeneity in the Prostate Cancer Biobank of the NRG: An Obstacle to Broadening the Reach of Precision Oncology.

JCO precision oncology·2026
Same author

Intra-alveolar Adhesive Biomaterial Preserves Ridge Height After Tooth Extraction in Dogs.

Journal of the American Animal Hospital Association·2026
Same author

Simulation-Based Power Analysis for Time-Dependent Area Under Receiver Operating Characteristic Curve Using Approximate Bayesian Computation.

Statistics in medicine·2026
Same author

Impact of intraoperative intravenous heparin bolus on clinical outcomes during radical nephrectomy and IVC tumor thrombectomy in renal cell carcinoma with level I-IV IVC thrombus: A multi-institutional study.

Urologic oncology·2026
Same author

Multiparametric MRI in prostate cancer active surveillance: results from the Miami Active Surveillance Trial (MAST) trial.

BJU international·2026

Related Experiment Video

Updated: Feb 2, 2026

Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
09:11

Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy

Published on: April 9, 2019

22.4K

Automatic Detection of Prostate Tumor Habitats using Diffusion MRI.

Yohann Tschudi1, Alan Pollack1, Sanoj Punnen2

  • 1Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA.

Scientific Reports
|November 16, 2018
PubMed
Summary

This study developed a method to automatically identify prostate cancer risk using Apparent Diffusion Coefficient (ADC) thresholds. The findings show that these automatically delineated volumes strongly correlate with cancer aggressiveness, aiding in risk stratification.

More Related Videos

MicroRNA Detection in Prostate Tumors by Quantitative Real-time PCR qPCR
08:30

MicroRNA Detection in Prostate Tumors by Quantitative Real-time PCR qPCR

Published on: May 16, 2012

25.1K
Role of Diffusion MRI Tractography in Endoscopic Endonasal Skull Base Surgery
09:53

Role of Diffusion MRI Tractography in Endoscopic Endonasal Skull Base Surgery

Published on: July 5, 2021

4.3K

Related Experiment Videos

Last Updated: Feb 2, 2026

Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
09:11

Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy

Published on: April 9, 2019

22.4K
MicroRNA Detection in Prostate Tumors by Quantitative Real-time PCR qPCR
08:30

MicroRNA Detection in Prostate Tumors by Quantitative Real-time PCR qPCR

Published on: May 16, 2012

25.1K
Role of Diffusion MRI Tractography in Endoscopic Endonasal Skull Base Surgery
09:53

Role of Diffusion MRI Tractography in Endoscopic Endonasal Skull Base Surgery

Published on: July 5, 2021

4.3K

Area of Science:

  • Radiology and Medical Imaging
  • Oncology
  • Biomedical Engineering

Background:

  • Accurate prostate cancer risk stratification is crucial for treatment decisions.
  • Multiparametric MRI (mpMRI) provides valuable information for detecting and characterizing prostate cancer.
  • Standardizing the analysis of diffusion-weighted imaging (DWI) for prostate cancer is an ongoing challenge.

Purpose of the Study:

  • To develop and validate a procedure for identifying optimal Apparent Diffusion Coefficient (ADC) thresholds for automatic delineation of prostatic lesions.
  • To assess the relationship between the size of automatically delineated Volumes of Interest (VOIs) and Gleason Score (GS) across different patient cohorts.
  • To establish ADC thresholds for estimating low, intermediate, and high cancer risk in the peripheral zone (PZ) and transition zone (TZ) of the prostate.

Main Methods:

  • A search algorithm was employed to identify optimal ADC thresholds in 50 µm²/s increments.
  • VOIs were automatically delineated based on ADC thresholds and matched to radical prostatectomy (RP) tumor nodules.
  • Analysis included patients undergoing RP, MRI-ultrasound fusion (MRI-US), and template biopsies.

Main Results:

  • Three distinct ADC thresholds were identified for low, intermediate, and high cancer risk in both PZ and TZ.
  • Correlation coefficients demonstrated a strong relationship between VOI size and GS, particularly for high and intermediate risk categories.
  • Area under the curve (AUC) values showed high discriminatory power for intermediate (0.852) and high (0.952) risk VOIs in predicting cancer aggressiveness.

Conclusions:

  • The developed procedure enables automatic delineation of prostatic lesions with restricted diffusion.
  • The size of these automatically delineated VOIs strongly correlates with prostate cancer aggressiveness and Gleason Score.
  • This method offers a promising tool for objective and reproducible prostate cancer risk stratification using mpMRI.