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Randomized clinical trials, while often viewed as the highest evidentiary barby which to judge the quality of a medical intervention, are far from perfect.In silico imaging trials are computational studies that seek to ascertain theperformance of a medical device by collecting this information entirely viacomputer simulations. The benefits of in silico trials for evaluating newtechnology include significant resource and time savings, minimization ofsubject risk, the ability to study devices that are not achievable in thephysical world, allow for the rapid and effective investigation of newtechnologies and ensure representation from all relevant subgroups. To conductin silico trials, digital representations of humans are needed. We review thelatest developments in methods and tools for obtaining digital humans for insilico imaging studies. First, we introduce terminology and a classification ofdigital human models. Second, we survey available methodologies for generatingdigital humans with healthy and diseased status and examine briefly the role ofaugmentation methods. Finally, we discuss the trade-offs of four approaches forsampling digital cohorts and the associated potential for study bias withselecting specific patient distributions.

The stochastic digital human is now enrolling for in silico imaging trials -- Methods and tools for generating digital cohorts