BackgroundPatients with the dementia subtype idiopathic normal pressure hydrocephalus (iNPH) may improve clinically following cerebrospinal fluid (CSF) diversion (shunt) surgery, though the predictors of shunt response remain debated. Currently, radiological features play an important role in the diagnosis of iNPH, but it is not well established which radiological markers most precisely predict shunt responsive iNPH.ObjectiveTo conduct a systematic review and meta-analysis to identify radiological predictors of shunt responsiveness, evaluate their diagnostic effectiveness, and recommend the most predictive radiological features.MethodsEmbase, MEDLINE, Scopus, PubMed, Google Scholar, and JSTOR were searched for original studies investigating radiological predictors of shunt response in iNPH patients. Included studies were assessed using the ROBINS-1 tool, and eligible studies were evaluated using a univariate meta-analysis.ResultsOverall, 301 full-text papers were screened, of which 28 studies were included, and 26 different radiological features were identified, 5 of these met the inclusion criteria for the meta-analysis: disproportionately enlarged subarachnoid space (DESH), callosal angle, periventricular white matter changes, cerebral blood flow (CBF), and computerized tomography cisternography. The meta-analysis showed that only callosal angle and periventricular white matter changes significantly differentiated iNPH shunt responders from non-responders, though both markers had a low diagnostic odds ratio (DOR) of 1.88 and 1.01 respectively. None of the other radiological markers differentiated shunt responsive from shunt non-responsive iNPH.ConclusionCallosal angle and periventricular changes are the only diagnostically effective radiological predictors of shunt responsive iNPH patients. However, due to the DORs approximating 1, they are insufficient as sole predictors and are advised to be used only in combination with other diagnostic tests of shunt response. Future research must evaluate the combined use of multiple radiological predictors, as it may yield beneficial additive effects that may allow for more robust radiological shunt response prediction.