Luetmer, Patrick H

BACKGROUND: The impact of covert cerebrovascular disease on falls in the general population is not well-known. Here, we determine the time to a first fall following incidentally detected covert cerebrovascular disease during a clinical neuroimaging episode. METHODS: This longitudinal cohort study assessed computed tomography (CT) and magnetic resonance imaging from 2009 to 2019 of patients aged >50 years registered with Kaiser Permanente Southern California which is a healthcare organization combining health plan coverage with coordinated medical services, excluding those with before stroke/dementia. We extracted evidence of incidental covert brain infarcts (CBI) and white matter hyperintensities/hypoattenuation (WMH) from imaging reports using natural language processing. We examined associations of CBI and WMH with falls requiring medical attention, using Cox proportional hazards regression models with adjustment for 12 variables including age, sex, ethnicity multimorbidity, polypharmacy, and incontinence. RESULTS: We assessed 241 050 patients, mean age 64.9 (SD, 10.42) years, 61.3% female, detecting covert cerebrovascular disease in 31.1% over a mean follow-up duration of 3.04 years. A recorded fall occurred in 21.2% (51 239/241 050) during follow-up. On CT, single fall incidence rate/1000 person-years (p-y) was highest in individuals with both CBI and WMH on CT (129.3 falls/1000 p-y [95% CI, 123.4–135.5]), followed by WMH (109.9 falls/1000 p-y [108.0–111.9]). On magnetic resonance imaging, the incidence rate was the highest with both CBI and WMH (76.3 falls/1000 p-y [95% CI, 69.7–83.2]), followed by CBI (71.4 falls/1000 p-y [95% CI, 65.9–77.2]). The adjusted hazard ratio for single index fall in individuals with CBI on CT was 1.13 (95% CI, 1.09–1.17); versus magnetic resonance imaging 1.17 (95% CI, 1.08–1.27). On CT, the risk for single index fall incrementally increased for mild (1.37 [95% CI, 1.32–1.43]), moderate (1.57 [95% CI, 1.48–1.67]), or severe WMH (1.57 [95% CI, 1.45–1.70]). On magnetic resonance imaging, index fall risk similarly increased with increasing WMH severity: mild (1.11 [95% CI, 1.07–1.17]), moderate (1.21 [95% CI, 1.13–1.28]), and severe WMH (1.34 [95% CI, 1.22–1.46]). CONCLUSIONS: In a large population with neuroimaging, CBI and WMH are independently associated with greater risks of an index fall. Increasing severities of WMH are associated incrementally with fall risk across imaging modalities.

Background Covert cerebrovascular disease (CCD) has been shown to be associated with dementia in population‐based studies with magnetic resonance imaging (MRI) screening, but dementia risk associated with incidentally discovered CCD is not known. Methods and Results Individuals aged ≥50 years enrolled in the Kaiser Permanente Southern California health system receiving head computed tomography (CT) or MRI for nonstroke indications from 2009 to 2019, without prior ischemic stroke/transient ischemic attack, dementia/Alzheimer disease, or visit reason/scan indication suggestive of cognitive decline or stroke were included. Natural language processing identified incidentally discovered covert brain infarction (id‐CBI) and white matter disease (id‐WMD) on the neuroimage report; white matter disease was characterized as mild, moderate, severe, or undetermined. We estimated risk of dementia associated with id‐CBI and id‐WMD. Among 241 050 qualified individuals, natural language processing identified 69 931 (29.0%) with id‐WMD and 11 328 (4.7%) with id‐CBI. Dementia incidence rates (per 1000 person‐years) were 23.5 (95% CI, 22.9–24.0) for patients with id‐WMD, 29.4 (95% CI, 27.9–31.0) with id‐CBI, and 6.0 (95% CI, 5.8–6.2) without id‐CCD. The association of id‐WMD with future dementia was stronger in younger (aged <70 years) versus older (aged ≥70 years) patients and for CT‐ versus MRI‐discovered lesions. For patients with versus without id‐WMD on CT, the adjusted HR was 2.87 (95% CI, 2.58–3.19) for younger and 1.87 (95% CI, 1.79–1.95) for older patients. For patients with versus without id‐WMD on MRI, the adjusted HR for dementia risk was 2.28 (95% CI, 1.99–2.62) for younger and 1.48 (95% CI, 1.32–1.66) for older patients. The adjusted HR for id‐CBI was 2.02 (95% CI, 1.70–2.41) for younger and 1.22 (95% CI, 1.15–1.30) for older patients for either modality. Dementia risk was strongly correlated with id‐WMD severity; adjusted HRs compared with patients who were negative for id‐WMD by MRI ranged from 1.41 (95% CI, 1.25–1.60) for those with mild disease on MRI to 4.11 (95% CI, 3.58–4.72) for those with severe disease on CT. Conclusions Incidentally discovered CCD is common and associated with a high risk of dementia, representing an opportunity for prevention. The association is strengthened when discovered at younger age, by increasing id‐WMD severity, and when id‐WMD is detected by CT scan rather than MRI.

Introduction There is increased interest in the use of artificial intelligence-based (AI) software packages in the evaluation of neuroimaging studies for acute ischemic stroke. We studied whether, compared to standard image interpretation without AI, Brainomix e-ASPECTS software improved interobserver agreement and accuracy in detecting ASPECTS regions affected in anterior circulation LVO. Methods We included 60 consecutive patients with anterior circulation LVO who had TICI 3 revascularization within 60 minutes of their baseline CT. A total of 16 readers, including senior neuroradiologists, junior neuroradiologists and vascular neurologists participated. Readers interpreted CT scans on independent workstations and assessed final ASPECTS and evaluated whether each individual ASPECTS region was affected. Two months later, readers again evaluated the CT scans, but with assistance of e-ASPECTS software. We assessed interclass correlation coefficient for total ASPECTS and interobserver agreement with Fleiss’ Kappa for each ASPECTS region with and without assistance of the e-ASPECTS. We also assessed accuracy for the readers with and without e-ASPECTS assistance. In our assessment of accuracy, ground truth was the 24 hour CT in this cohort of patients who had prompt and complete revascularization. Results Interclass correlation coefficient for total ASPECTS without e-ASPECTS assistance was 0.395, indicating fair agreement compared, to 0.574 with e-ASPECTS assistance, indicating good agreement (P < 0.01). There was significant improvement in inter-rater agreement with e-ASPECTS assistance for each individual region with the exception of M6 and caudate. The e-ASPECTS software had higher accuracy than the overall cohort of readers (with and without e-ASPECTS assistance) for every region except the caudate. Conclusions Use of Brainomix e-ASPECTS software resulted in significant improvements in inter-rater agreement and accuracy of ASPECTS score evaluation in a large group of neuroradiologists and neurologists. e-ASPECTS software was more predictive of final infarct/ASPECTS than the overall group interpreting the CT scans with and without e-ASPECTS assistance.