Protocol design and optimization.

Using decision support algorithms, referring physicians will usually choose theappropriate examinationtypes,and many will be aware of the need for appropriate imaging protocols (eg, contrast-enhanced imaging in malignant disease), but they cannot be expected to know the gamut of complex protocols available to radiologists. Ultimately, it is up to radiologists to dictate which protocol is most suitable for a particular patient in a particular situation. But therein lies a problem. Contemporary equipment and the number of available parameters for protocoldesignhavebecome sodiverse and complicated that even many subspecialty radiologists are not always aware of the ideal protocol for ag iven patient with a given disease at a particular time. Furthermore, with the advent and increasing deployment of precision medicine, whereby patient care is rapidly becoming driven and delivered according to unique biomarkerdataandpatientpreferences, it is now too overwhelming for most radiologists to optimally and uniquely tailoreachexamination.Consequently, many departments are unable to uniformly design and deliver optimal protocols for every circumstance. For example,morethan50%ofabdominal CT protocols do not currently adhere to the ACR Appropriateness Criteria � concerning anatomic coverage [1]. Further exacerbating the issue, suffi