Finite sample size errors in the context of multiple error sources in quantitative medical imaging: An evaluation for breast magnetic resonance diffusion-weighted imaging

Jessica V. Eberle, Sebastian Bickelhaupt, Lorenz A. Kapsner, Sabine Ohlmeyer, Evelyn Wenkel, Michael Uder, Dominika Skwierawska, Katharina Tkotz, Dominique Hadler, Tristan A. Kuder, Frederik B. Laun

Abstract:

Selecting appropriate sample sizes in magnetic resonance imaging studies is a complex process that requires to balance statistical rigor with the practical challenges of measuring a large patient population. In this Institutional Review Board approved study.
Introduction

Choosing an adequate sample size is a key task in research, whether for planning a study, obtaining institutional review board approval, or during the publication review process. Established methods to determine an adequate sample size are often based on (estimated) effect sizes, the desired significance level, and statistical power.

Methods

This retrospective study was approved by the ethics committee of the Friedrich-Alexander Universität (FAU) Erlangen-Nürnberg, Erlangen, Germany, waiving the need for informed consent. The data for research purposes was accessed from April 1, 2021 until December 31, 2021.

Results:

In total, 171 lesions were included in our in-house study. The mean ADCs per class (0.79 µm²/ms for malignant lesions and 1.32 µm²/ms for benign lesions) and their respective standard deviations (0.20 µm²/ms and 0.32 µm²/ms) are given in Table 2.

Discussion

In this study, we investigated the size of two common error types in DWI ADC-based assessments of breast lesions: finite N errors represented by the standard error  of the AUC and precision errors represented by . For the in-house study and the 24 considered published studies, we generally found  with two exceptions (studies 7 [19] and 16 [28]).

Acknowledgments

This present work was performed by the first author, J.V.E., in fulfillment of the requirements for the degree “Dr. med.” at the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). Chat GPT-4-turbo was partly used to improve the manuscript text with the command “Improve the text.

Citation: Eberle JV, Bickelhaupt S, Kapsner LA, Ohlmeyer S, Wenkel E, Uder M, et al. (2026) Finite sample size errors in the context of multiple error sources in quantitative medical imaging: An evaluation for breast magnetic resonance diffusion-weighted imaging. PLoS One 21(6): e0341201. https://doi.org/10.1371/journal.pone.0341201

Editor: Pascal A. T. Baltzer, Medical University of Vienna, AUSTRIA

Received: July 26, 2025; Accepted: May 15, 2026; Published: June 4, 2026

Copyright: © 2026 Eberle et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: ADC, apparent diffusion coefficient; AUC, area under the receiver operating characteristic curve; BI-RADS, Breast Imaging Reporting and Data System; COV, coefficient of variation; DWI, diffusion-weighted imaging; MRI, magnetic resonance imaging; PDF, probability density function; Std, standard deviation