False Discovery Rates in PET and CT Studies with Texture Features: A Systematic Review.

ABSTRACT:

Purpose

A number of recent publications have proposed that a family of image-derived indices, called texture features, can predict clinical outcome in patients with cancer. However, the investigation of multiple indices on a single data set can lead to significant inflation of type-I errors. We report a systematic review of the type-I error inflation in such studies and review the evidence regarding associations between patient outcome and texture features derived from positron emission tomography (PET) or computed tomography (CT) images.

Methods

For study identification PubMed and Scopus were searched (1/2000-9/2013) using combinations of the keywords texture, prognostic, predictive and cancer. Studies were divided into three categories according to the sources of the type-

SUBMITTER: Chalkidou A 

PROVIDER: S-EPMC4418696 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature