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Updated: May 26, 2026
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Statistical power in quantitative diffusion MRI of tumor response: strategies for future studies
Ted K Yanagihara1, Benjamin Kennedy, Krishna Surapaneni
1Department of Neuroscience, Columbia University, College of Physicians and Surgeons, New York, NY 10032, USA. tky2102@columbia.edu
Rationale And Objectives:
Diffusion magnetic resonance imaging may be useful in tracking tumor growth and response to treatment. However, studies using these measures may lack statistical power to draw definitive conclusions regarding changes in tumor cellularity. Using apparent diffusion coefficient values taken from the literature, the investigators estimated sample sizes for a range of changes to the mean.
Materials And Methods:
A literature search was performed of studies measuring the average apparent diffusion coefficients for various bodily tissues, and the mean and standard deviation from each study were recorded. Analyses of statistical power were then performed using these values and comparing them to a population of healthy controls.
Results:
Tumor cellularity as measured by apparent diffusion coefficients may have high sensitivity, but the analyses indicate that investigations in this field may potentially suffer from low statistical power. For example, the findings indicate that samples of <20 patients may require a mean change of approximately 25% between study conditions.
Conclusions:
Suggestions are offered for improvements in methodologic approaches and in data reporting to assist in overcoming the limitations of small sample sizes. On the basis of this literature review, reference values are provided to help investigators estimate study sample size to achieve adequate statistical power.
