Background and objectives:Cerebral cortical microinfarcts (CMIs) are a novel MRI-marker of cerebrovascular disease (CeVD) that predicts accelerated cognitive decline. Presence of CMIs is known to be associated with global cortical atrophy, although the mechanism linking the two is unclear. Our primary objective was to examine the relation between CMIs and cortical atrophy and establish possible perilesional atrophy surrounding CMIs. Our secondary objective was to examine the role of cortical atrophy in CMI-associated cognitive impairment.Methods:Patients were recruited from two Singapore memory clinics between December 2010 and September 2013 and included if they received the diagnosis no objective cognitive impairment, cognitive impairment (with or without a history of stroke) or Alzheimer’s or vascular dementia. Cortical thickness, chronic cortical microinfarcts and MRI-markers of CeVD were assessed on 3T MRI. Patients underwent cognitive testing. Cortical thickness was compared globally between patients with and without CMIs, regionally within individual patients with CMIs comparing brain regions with CMIs to the corresponding contralateral region without CMIs and locally within individuals patients in a 50 mm radius of CMIs. Global cortical thickness was analyzed as mediator in the relation between CMI and cognitive performance.Results:Of the 238 patients (mean age 72.5 SD 9.1 years) enrolled, 75 had ≥1 CMIs. Patient with CMIs had a 2.1% lower global cortical thickness (B=-.049 mm, 95% CI [.091; -.007] p=.022) compared to patients without CMIs, after correction for age, sex, education and intracranial volume. In patients with CMIs, cortical thickness in brain regions with CMIs was 2.2 % lower than in contralateral regions without CMIs (B=-.048 mm [-.071; -.026] p<.001). In a 20 mm radius area surrounding the CMI-core, cortical thickness was lower than in the area 20-50 mm from the CMI-core (Mean difference -.06 mm 95% CI [-.10; -.02] p=.002). Global cortical thickness was a significant mediator in the relationship between CMI presence and cognitive performance as measure with the Mini-Mental State Examination (B=-.12 [-.22; -.01] p=.025).Discussion:We found cortical atrophy surrounding CMIs, suggesting a perilesional effect in a cortical area many times larger than the CMI-core. Our findings support the notion that CMIs affect brain structure beyond the actual lesion site.
Background Instead of a single value for mammographic sensitivity, a sensitivity function based on tumor size more realistically reflects mammography’s detection capability. Because previous models may have overestimated size-specific sensitivity, we aimed to provide a novel approach to improve sensitivity estimation as a function of tumor size. Methods Using aggregated data on interval and screen-detected cancers, observed tumor sizes were back-calculated to the time of screening using an exponential tumor growth model and a follow-up time of 4 years. From the observed number of detected cancers and an estimation of the number of false-negative cancers, a model for the sensitivity as a function of tumor size was determined. A univariate sensitivity analysis was conducted by varying follow-up time and tumor volume doubling time (TVDT). A systematic review was conducted for external validation of the sensitivity model. Results Aggregated data of 22,915 screen-detected and 10,670 interval breast cancers from the Dutch screening program were used. The model showed that sensitivity increased from 0 to 85% for tumor sizes from 2 to 20 mm. When TVDT was set at the upper and lower limits of the confidence interval, sensitivity for a 20-mm tumor was 74% and 93%, respectively. The estimated sensitivity gave comparable estimates to those from two of three studies identified by our systematic review. Conclusion Derived from aggregated breast screening outcomes data, our model’s estimation of sensitivity as a function of tumor size may provide a better representation of data observed in screening programs than other models.
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