Quantification of hematoma and perihematomal edema volumes in intracerebral hemorrhage study: Design considerations in an artificial intelligence validation (QUANTUM) study.
Natasha IronsideJames PatrieSherman NgDale DingTanvir RizviJeyan S KumarPanagiotis MastorakosMohamed Z HusseinKareem El NaamaniRawad AbbasM Harrison SnyderYan ZhuangKathryn N KearnsKevin T DoanLeah M ShaboSaurabh MarfatiahDavid RohAngela Lignelli-DippleJan ClaassenBradford B WorrallKaren C JohnstonPascal JabbourMin S ParkE Sander ConnollySugoto MukherjeeAndrew M SoutherlandChing-Jen ChenPublished in: Clinical trials (London, England) (2022)
By allowing direct equivalence hypothesis testing, the Quantification of Hematoma and Perihematomal Edema Volumes in Intracerebral Hemorrhage study offers advantages over radiology validation studies which utilize measures of agreement to indirectly infer measurement equivalence and studies which mistakenly try to infer measurement equivalence based on the failure of a comparison two-sided null hypothesis test to reach the significance level for rejection. The equivalence hypothesis testing paradigm applied to artificial intelligence application validation is relatively uncharted and warrants further investigation. The challenges encountered in the design of this study may influence future studies seeking to translate artificial intelligence medical technology into clinical practice.