Recommendations for research design and reporting in computer-assisted diagnosis to facilitate meta-analysis

Computer-assisted diagnosis (CAD) describes a diverse, heterogeneous range of applications rather than a single entity. The aims and functions of CAD systems vary considerably and comparing studies and systems is challenging due to methodological and design differences. In addition, poor study quality and reporting can reduce the value of some publications. Meta-analyses of CAD are therefore difficult and may not provide reliable conclusions. Aiming to determine the major sources of heterogeneity and thereby what CAD researchers could change to allow this sort of assessment, this study reviews a sample of 147 papers concerning CAD used with imaging for cancer diagnosis. It discusses sources of variability, including the goal of the CAD system, learning methodology, study population, design, outcome measures, inclusion of radiologists, and study quality. Based upon this evidence, recommendations are made to help researchers optimize the quality and comparability of their trial design and reporting.

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► It is problematic to assess computer-assisted diagnosis (CAD) using meta-analyses.
► Sources of heterogeneity researchers should be aware of include testing methodology, reporting, and the CAD system itself.
► It is possible to optimize CAD trials for collective and comparative assessment during the design and reporting stages.
► A set of recommendations are provided to help CAD researchers.