How Often is the Dynamic Contrast Enhanced Score Needed in PI-RADS Version 2?

Albert T Roh1, Richard E Fan2, Geoffrey A Sonn3

  • 1Department of Radiology, Stanford University, Stanford, CA.

Abstract

Insights

Dynamic contrast enhanced (DCE) imaging is infrequently needed for Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) scoring. Prostate-specific antigen density (PSAD) may reduce or replace the need for DCE in prostate MRI.

Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) guidelines assign a limited role to dynamic contrast enhanced (DCE) imaging.
  • This study investigated the actual utilization frequency of DCE in PI-RADS v2 scoring.

Purpose of the Study:

  • To evaluate the necessity of DCE in PI-RADS v2 scoring for prostate MRI.
  • To explore the potential of prostate-specific antigen density (PSAD) as an alternative to DCE.

Main Methods:

  • Retrospective review of 388 patients undergoing prostate MRI and biopsy (January 2016 - December 2017).
  • DCE was indicated based on specific PI-RADS v2 criteria for peripheral and transition zone lesions.
  • Receiver operating characteristic curve analysis assessed PSAD accuracy for differentiating lesions, compared to DCE using McNemar's test.

Main Results:

  • Only 16% of patients (62/388) required DCE for PI-RADS v2 scoring.
  • Clinically significant cancer (Gleason score ≥7) was found in 14% (10/69) of lesions requiring DCE.
  • In equivocal lesions, PSAD thresholds showed comparable accuracy to DCE in identifying significant cancer.

Conclusions:

  • The limited use of DCE (16%) suggests that initial screening prostate MRI could potentially exclude contrast agents.
  • Prostate-specific antigen density (PSAD) demonstrates potential to reduce or replace the need for DCE in PI-RADS v2 assessments.

Related Concept Videos

PI Controller: Design01:24

PI Controller: Design

Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
1.2K
The Buckingham Pi Theorem01:09

The Buckingham Pi Theorem

The Buckingham Pi theorem provides a structured method to simplify fluid dynamics problems by reducing complex systems of variables to dimensionless terms.
1.6K
Determination of Pi Terms01:15

Determination of Pi Terms

The Buckingham Pi theorem is a valuable method in dimensional analysis, reducing complex relationships between variables into dimensionless terms. Relevant variables in analyzing the lift force on an airplane wing include lift force, air density, wing area, aircraft velocity, and air viscosity. Expressing each variable in terms of fundamental dimensions — mass, length, and time — provides a consistent foundation for constructing these dimensionless terms.
The theorem indicates that the...
624
Self-Evaluation: Self-Enhancement and Self-Verification03:00

Self-Evaluation: Self-Enhancement and Self-Verification

Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...
5.8K
Introduction to z Scores01:06

Introduction to z Scores

A z score (or standardized value) is measured in units of the standard deviation. It tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
z scores...
11.0K
Introduction to z Scores01:05

Introduction to z Scores

A z score (or standardized value) is measured in units of the standard deviation. It indicates how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
z scores...
1.3K