Novel Hypodensity Detection Tool improves clinician identification of hypodensity on non-contrast CT in stroke patients.

BackgroundIn acute stroke, identifying early changes (parenchymal hypodensity) on non-contrast CT (NCCT) can be challenging. We aimed to identify whether the accuracy of clinicians in detecting acute hypodensity in ischaemic stroke patients on a non-contrast CT is improved with the use of an automated HDT algorithm using MRI-DWI as the gold standard. MethodsThe study employed a case-crossover within-clinician design, where clinicians were tasked with identifying hypodensity lesions on NCCT scans for five a priori selected patient cases, before and after viewing the HDT. The DICE Similarity Coefficient (DICE score) was the primary measure of accuracy. Statistical analysis compared DICE scores with and without HDT using mixed-effects linear regression, with individual NCCT scans and clinicians as nested random effects. ResultsThe HDT had a mean DICE score of 0.62 for detecting hypodensity across all NCCT scans and clinicians overall mean DICE score of 0.33 (SD 0.31) before HDT implementation and 0.40 (SD 0.27) after implementation. HDT use was associated with an increase of 0.07 (95% CI: 0.02-0.11, p=0.003) in DICE score accounting for individual scan and clinician effects. For scans with small lesions, clinicians achieved a mean increase in DICE score of 0.08 (95% CI: 0.02, 0.13, p=0.004) following HDT use. In a subgroup of 15 trainees, DICE score improved with HDT implementation (mean difference in DICE 0.09 [95% CI: 0.03, 0.14, p=0.004]). ConclusionsThe Hypodensity Detection Tool (HDT) has potential to enhance accuracy of detecting hypodensity in acute stroke diagnosis, especially for smaller lesions, and notably for less experienced clinicians.