Factors related to failure of autologous cranial reconstructions after decompressive craniectomy

PURPOSE

Cranioplasty is customary after decompressive craniectomy. Many different materials have been developed and used for this procedure. The ideal material does not yet exist, while complication rates in cranioplasties remain high. This study aimed to determine factors related to autologous bone flap failure.

MATERIALS AND METHODS

In this two-center retrospective cohort study, 276 patients underwent autologous bone cranioplasty after initial decompressive craniectomy between 2004 and 2014. Medical records were reviewed regarding patient characteristics and factors potentially related to bone flap failure. Data were analyzed using univariable and multivariable regression analysis.

RESULTS

Independent factors related to overall bone flap failure were: duration of hospitalization after decompressive craniectomy [OR: 1.012 (95%CI: 1.003-1.022); p = 0.012], time interval between decompressive craniectomy and cranioplasty [OR: 1.018 (95%CI: 1.004-1.032); p = 0.013], and follow-up duration [OR: 1.034 (95%CI: 1.020-1.047); p < 0.001]. In patients with bone flap infection, neoplasm as initial diagnosis occurred significantly more often (29.2% vs. 7.8%; RD 21.3%; 95%CI 8.4 -38.3%; NNH 5; 95%CI 3 -12) and duration of hospitalization after decompressive craniectomy tended to be longer (means 54 vs. 28 days, MD 26.2 days, 95%CI -8.6 to 60.9 days). Patients with bone flap resorption were significantly younger (35 vs. 43 years, MD 7.7 years, 95%CI 0.8-14.6 years) and their cranial defect size tended to be wider than in patients without bone flap resorption (mean circumference 39 vs. 37 cm; MD 2.4 cm, 95% CI -0.43-5.2 cm) and follow-up duration was significantly longer (44 vs. 14 months, MD 29 months, 95%CI 17-42 months).

CONCLUSION

A neoplasm as initial diagnosis, longer hospitalization after decompressive craniectomy, larger time interval between decompressive craniectomy and cranioplasty, and longer follow-up duration are associated with a higher risk of failure of autologous bone flaps for cranioplasty. Patients with these risk factors may be better served with an early recovery program after decompressive surgery or an alloplastic material for cranioplasty.

Prevalence of amyloid-β pathology in distinct variants of primary progressive aphasia

OBJECTIVE

To estimate the prevalence of amyloid positivity, defined by positron emission tomography (PET)/cerebrospinal fluid (CSF) biomarkers and/or neuropathological examination, in primary progressive aphasia (PPA) variants.

METHODS

We conducted a meta-analysis with individual participant data from 1,251 patients diagnosed with PPA (including logopenic [lvPPA, n = 443], nonfluent [nfvPPA, n = 333], semantic [svPPA, n = 401], and mixed/unclassifiable [n = 74] variants of PPA) from 36 centers, with a measure of amyloid-β pathology (CSF [n = 600], PET [n = 366], and/or autopsy [n = 378]) available. The estimated prevalence of amyloid positivity according to PPA variant, age, and apolipoprotein E (ApoE) ε4 status was determined using generalized estimating equation models.

RESULTS

Amyloid-β positivity was more prevalent in lvPPA (86%) than in nfvPPA (20%) or svPPA (16%; p < 0.001). Prevalence of amyloid-β positivity increased with age in nfvPPA (from 10% at age 50 years to 27% at age 80 years, p < 0.01) and svPPA (from 6% at age 50 years to 32% at age 80 years, p < 0.001), but not in lvPPA (p = 0.94). Across PPA variants, ApoE ε4 carriers were more often amyloid-β positive (58.0%) than noncarriers (35.0%, p < 0.001). Autopsy data revealed Alzheimer disease pathology as the most common pathologic diagnosis in lvPPA (76%), frontotemporal lobar degeneration-TDP-43 in svPPA (80%), and frontotemporal lobar degeneration-TDP-43/tau in nfvPPA (64%).

INTERPRETATION

This study shows that the current PPA classification system helps to predict underlying pathology across different cohorts and clinical settings, and suggests that age and ApoE genotype should be considered when interpreting amyloid-β biomarkers in PPA patients. Ann Neurol 2018;84:737-748.

Clinical phenotype, atrophy, and small vessel disease in APOEε2 carriers with Alzheimer disease

OBJECTIVE

To examine the clinical phenotype, gray matter atrophy patterns, and small vessel disease in patients who developed prodromal or probable Alzheimer disease dementia, despite carrying the protective APOEε2 allele.

METHODS

We included 36 β-amyloid-positive (by CSF or PET) APOEε2 carriers (all ε2/ε3) with mild cognitive impairment or dementia due to Alzheimer disease who were matched for age and diagnosis (ratio 1:2) to APOEε3 homozygotes and APOEε4 carriers (70% ε3/ε4 and 30% ε4/ε4). We assessed neuropsychological performance across 4 cognitive domains (memory, attention, executive, and language functions), performed voxelwise and region of interest analyses of gray matter atrophy on T1-weighted MRI, used fluid-attenuated inversion recovery images to automatically quantify white matter hyperintensity volumes, and assessed T2*-weighted images to identify microbleeds. Differences in cognitive domain scores, atrophy, and white matter hyperintensities between ε2 carriers, ε3 homozygotes, and ε4 carriers were assessed using analysis of variance analyses, and Pearson χ² tests were used to examine differences in prevalence of microbleeds.

RESULTS

We found that ε2 carriers performed worse on nonmemory domains compared to both ε3 homozygotes and ε4 carriers but better on memory compared to ε4 carriers. Voxelwise T1-weighted MRI analyses showed asymmetric (left > right) temporoparietal-predominant atrophy with subtly less involvement of medial-temporal structures in ε2 carriers compared to ε4 carriers. Finally, ε2 carriers had larger total white matter hyperintensity volumes compared to ε4 carriers (mean 10.4 vs 7.3 mL) and a higher prevalence of microbleeds compared to ε3 homozygotes (37.5% vs 18.3%).

CONCLUSION

APOEε2 carriers who develop Alzheimer disease despite carrying the protective allele display a nonamnestic clinical phenotype with more severe small vessel disease.

Is intracranial volume a suitable proxy for brain reserve?

BACKGROUND

Brain reserve is a concept introduced to explain why Alzheimer's disease (AD) patients with a greater brain volume prior to onset of pathology generally have better clinical outcomes. In this review, we provide a historical background of the emergence of brain reserve and discuss several aspects that need further clarification, including the dynamic or static nature of the concept and its underlying mechanisms and clinical effect. We then describe how brain reserve has been operationalized over the years, and critically evaluate the use of intracranial volume (ICV) as the most widely used proxy for brain reserve. Furthermore, we perform a meta-analysis showing that ICV is associated with higher cognitive performance after adjusting for the presence and amount of pathology. Although we acknowledge its imperfections, we conclude that the use of ICV as a proxy for brain reserve is currently warranted. However, further development of more optimal measures of brain reserve as well as a more clearly defined theoretical framework is essential.

Quantitative PET and Histology of Brain Biopsy Reveal Lack of Selective Pittsburgh Compound-B Binding to Intracerebral Amyloidoma

This single case study examines selective Pittsburgh compound-B (PiB) binding to an intracerebral light-chain amyloidoma using a 90-minute dynamic [11C]PiB-PET scan and brain biopsy tissue. Parametric non-displaceable binding potential (BPND) images showed low specific binding in the amyloidoma (BPND = 0.23), while relative tracer delivery was adequate (R1 = 0.44). Histology of the tissue revealed strong coloring with Congo-red, thioflavin-S, and X-34, indicating presence of amyloid. However, immunological staining with 6F/3D revealed absence of amyloid-β and histofluorescence of 6-CN-PiB, a highly fluorescent derivative of PiB, was at background levels. Our results suggest that PiB does not detect the atypical amyloid pathology associated with an intracerebral light-chain amyloidoma. These findings are of interest to clinicians and researchers applying [11C]PiB-PET to detect atypical forms of amyloid pathology.

Quantification of Tau Load Using [18F]AV1451 PET

Purpose

The tau tracer [¹⁸F]AV1451, also known as flortaucipir, is a promising ligand for imaging tau accumulation in Alzheimer’s disease (AD). Most of the previous studies have quantified tau load using standardized uptake value ratios (SUVr) derived from a static [¹⁸F]AV1451 scan. SUVr may, however, be flow dependent and, especially for longitudinal studies, should be validated against a fully quantitative approach. The objective of this study was to identify the optimal tracer kinetic model for measuring tau load using [¹⁸F]AV1451.

Procedures

Following intravenous injection of 225 ± 16 MBq [¹⁸F]AV1451, 130 min dynamic PET scans were performed in five biomarker confirmed AD patients and five controls. Arterial blood sampling was performed to obtain a metabolite-corrected plasma input function. Next, regional time–activity curves were generated using PVElab software. These curves were analysed using several pharmacokinetic models.

Results

The reversible single tissue compartment model (1T2k_V_B) was the preferred model for all but one control. For AD patients, however, model preference shifted towards a reversible two tissue compartmental model (2T4k_V_B). The simplified reference tissue model (SRTM) derived binding potential (BP_ND) showed good correlation (AD: r² = 0.87, slope = 1.06; controls: r² = 0.87, slope = 0.86) with indirect plasma input binding (distribution volume ratio-1). Standardized uptake value ratios (80–100 min) correlated well with DVR (r² = 0.93, slope = 1.07) and SRTM-derived BP_ND (r² = 0.84, slope = 0.95). In addition, regional differences in tracer binding between subject groups in different tau-specific regions were observed.

Conclusions

Model preference of [¹⁸F]AV1451 appears to depend on subject status and, in particular, V_T. The relationship between model preference and V_T suggests that (higher) tau load may be reflected by a second tissue compartment. Nevertheless, consistent results can be obtained using a 2T4k_V_B model. In addition, SRTM can be used to derive BP_ND.

Electronic supplementary material

The online version of this article (doi:10.1007/s11307-017-1080-z) contains supplementary material, which is available to authorized users.

Prevalence of the apolipoprotein E ε4 allele in amyloid β positive subjects across the spectrum of Alzheimer's disease

INTRODUCTION

Apolipoprotein E (APOE) ε4 is the major genetic risk factor for Alzheimer's disease (AD), but its prevalence is unclear because earlier studies did not require biomarker evidence of amyloid β (Aβ) pathology.

METHODS

We included 3451 Aβ+ subjects (853 AD-type dementia, 1810 mild cognitive impairment, and 788 cognitively normal). Generalized estimating equation models were used to assess APOE ε4 prevalence in relation to age, sex, education, and geographical location.

RESULTS

The APOE ε4 prevalence was 66% in AD-type dementia, 64% in mild cognitive impairment, and 51% in cognitively normal, and it decreased with advancing age in Aβ+ cognitively normal and Aβ+ mild cognitive impairment (P < .05) but not in Aβ+ AD dementia (P = .66). The prevalence was highest in Northern Europe but did not vary by sex or education.

DISCUSSION

The APOE ε4 prevalence in AD was higher than that in previous studies, which did not require presence of Aβ pathology. Furthermore, our results highlight disease heterogeneity related to age and geographical location.

Differential effects of cognitive reserve and brain reserve on cognition in Alzheimer disease

Objective

To examine cross-sectional effects of cognitive reserve (CR) and brain reserve (BR) on cognition across the spectrum of Alzheimer disease (AD).

Methods

We included 663 AD biomarker–positive participants with dementia (probable AD, n = 462) or in the predementia stages (preclinical/prodromal AD, n = 201). Education was used as a proxy of CR and intracranial volume as a proxy of BR. Cognition was assessed across 5 domains (memory, attention, language, visuospatial, and executive functions). We performed multiple linear regression models to examine effects of CR and BR on cognitive domain Z scores, adjusted for cerebral atrophy. Furthermore, we assessed differences in effects according to disease stage and across degrees of total reserve using a 4-level variable (high CR/high BR, high CR/low BR, low CR/high BR, and low CR/low BR).

Results

We found positive, independent effects of both CR and BR across multiple cognitive domains. Stratification for disease stage showed that effects of CR on attention and executive functioning were greater in predementia than in dementia (β = 0.39 vs β = 0.21 [Welch t = 2.40, p < 0.01] and β = 0.46 vs β = 0.26 [t = 2.83, p < 0.01]). Furthermore, we found a linear trend for better cognitive performance in all domains in the high CR/high BR group, followed by high CR/low BR, low CR/high BR, and then low CR/low BR (p for trend <0.05).

Conclusions

CR and BR both independently mitigate cognitive symptoms in AD. The positive effect of CR is most strongly expressed in the predementia stages and the additive effects of high CR and BR are most beneficial.