Sensitivity of the Boston criteria version 2.0 in Dutch-type hereditary cerebral amyloid angiopathy.

BACKGROUND AND AIM: The revised Boston criteria v2.0 for cerebral amyloid angiopathy (CAA) add two radiological markers to the existing criteria: severe visible perivascular spaces in the centrum semiovale and white matter hyperintensities (WMHs) in a multispot pattern. This study aims to determine the sensitivity of the updated criteria in mutation carriers with Dutch-type hereditary CAA (D-CAA) in an early and later disease stage. METHODS: In this cross-sectional study, we included presymptomatic and symptomatic D-CAA mutation carriers from our prospective natural history study (AURORA) at the Leiden University Medical Center between 2018 and 2021. 3-Tesla scans were assessed for CAA-related magnetic resonance imaging (MRI) markers. We compared the sensitivity of the Boston criteria v2.0 to the previously used modified Boston criteria v1.5. RESULTS: We included 64 D-CAA mutation carriers (mean age 49 years, 55% women, 55% presymptomatic). At least one white matter (WM) feature was seen in 55/64 mutation carriers (86%: 74% presymptomatic, 100% symptomatic). Fifteen (23%) mutation carriers, all presymptomatic, showed only WM features and no hemorrhagic markers. The sensitivity for probable CAA was similar between the new and the previous criteria: 11/35 (31%) in presymptomatic mutation carriers and 29/29 (100%) in symptomatic mutation carriers. The sensitivity for possible CAA in presymptomatic mutation carriers increased from 0/35 (0%) to 15/35 (43%) with the new criteria. CONCLUSION: The Boston criteria v2.0 increase the sensitivity for detecting possible CAA in presymptomatic D-CAA mutation carriers and, therefore, improve the detection of the early phase of CAA.

Quantitative measurement of cortical superficial siderosis in cerebral amyloid angiopathy.

Cerebral amyloid angiopathy (CAA) is a cerebrovascular disease affecting the small arteries in the brain with hallmark depositions of amyloid-ß in the vessel wall, leading to cognitive decline and intracerebral hemorrhage (ICH). An emerging MRI marker for CAA is cortical superficial siderosis (cSS) as it is strongly related to the risk of (recurrent) ICH. Current assessment of cSS is mainly done on T2*- weighted MRI using a qualitative score consisting of 5 categories of severity which is hampered by ceiling effects. Therefore, the need for a more quantitative measurement is warranted to better map disease progression for prognosis and future therapeutic trials. We propose a semi-automated method to quantify cSS burden on MRI and investigated it in 20 patients with CAA and cSS. The method showed excellent inter-observer (Pearson's 0.991, P < 0.001) and intra-observer reproducibility (ICC 0.995, P < 0.001). Furthermore, in the highest category of the multifocality scale a large spread in the quantitative score is observed, demonstrating the ceiling effect in the traditional score. We observed a quantitative increase in cSS volume in two of the 5 patients who had a 1 year follow up, while the traditional qualitative method failed to identify an increase because these patients were already in the highest category. The proposed method could therefore potentially be a better way of tracking progression. In conclusion, semi-automated segmenting and quantifying cSS is feasible and repeatable and may be used for further studies in CAA cohorts.

Striped occipital cortex and intragyral hemorrhage: Novel magnetic resonance imaging markers for cerebral amyloid angiopathy.

BACKGROUND AND AIM: To investigate whether a striped occipital cortex and intragyral hemorrhage, two markers recently detected on ultra-high-field 7-tesla-magnetic resonance imaging in hereditary cerebral amyloid angiopathy (CAA), also occur in sporadic CAA (sCAA) or non-sCAA intracerebral hemorrhage (ICH). METHODS: We performed 7-tesla-magnetic resonance imaging in patients with probable sCAA and patients with non-sCAA-ICH. Striped occipital cortex (linear hypointense stripes perpendicular to the cortex) and intragyral hemorrhage (hemorrhage restricted to the juxtacortical white matter of one gyrus) were scored on T2*-weighted magnetic resonance imaging. We assessed the association between the markers, other CAA-magnetic resonance imaging markers and clinical features. RESULTS: We included 33 patients with sCAA (median age 70 years) and 29 patients with non-sCAA-ICH (median age 58 years). Striped occipital cortex was detected in one (3%) patient with severe sCAA. Five intragyral hemorrhages were found in four (12%) sCAA patients. The markers were absent in the non-sCAA-ICH group. Patients with intragyral hemorrhages had more lobar ICHs (median count 6.5 vs. 1.0), lobar microbleeds (median count >50 vs. 15), and lower median cognitive scores (Mini Mental State Exam: 20 vs. 28, Montreal Cognitive Assessment: 18 vs. 24) compared with patients with sCAA without intragyral hemorrhage. In 12 (36%) patients, sCAA diagnosis was changed to mixed-type small vessel disease due to deep bleeds previously unobserved on lower field-magnetic resonance imaging. CONCLUSION: Whereas a striped occipital cortex is rare in sCAA, 12% of patients with sCAA have intragyral hemorrhages. Intragyral hemorrhages seem to be related to advanced disease and their absence in patients with non-sCAA-ICH could suggest specificity for CAA.

On the ability to exploit signal fluctuations in pseudocontinuous arterial spin labeling for inferring the major flow territories from a traditional perfusion scan.

In arterial spin labeling (ASL) a magnetic label is applied to the flowing blood in feeding arteries allowing depiction of cerebral perfusion maps. The labeling efficiency depends, however, on blood velocity and local field inhomogeneities and is, therefore, not constant over time. In this work, we investigate the ability of statistical methods used in functional connectivity research to infer flow territory information from traditional pseudo-continuous ASL (pCASL) scans by exploiting artery-specific signal fluctuations. By applying an additional gradient during labeling the minimum amount of signal fluctuation that allows discrimination of the main flow territories is determined. The following three approaches were tested for their performance on inferring the large vessel flow territories of the brain: a general linear model (GLM), an independent component analysis (ICA) and t-stochastic neighbor embedding. Furthermore, to investigate the effect of large vessel pathology, standard ASL scans of three patients with a unilateral stenosis (>70%) of one of the internal carotid arteries were retrospectively analyzed using ICA and t-SNE. Our results suggest that the amount of natural-occurring variation in labeling efficiency is insufficient to determine large vessel flow territories. When applying additional vessel-encoded gradients these methods are able to distinguish flow territories from one another, but this would result in approximately 8.5% lower perfusion signal and thus also a reduction in SNR of the same magnitude.