The impact of sample size on the reproducibility of voxel-based lesion-deficit mappings

This study investigated how sample size affects the reproducibility of findings from univariate voxel-based lesion-deficit analyses (e.g., voxel-based lesion-symptom mapping and voxel-based morphometry). Our effect of interest was the strength of the mapping between brain damage and speech articulation difficulties, as measured in terms of the proportion of variance explained. First, we identified a region of interest by searching on a voxel-by-voxel basis for brain areas where greater lesion load was associated with poorer speech articulation using a large sample of 360 right-handed English-speaking stroke survivors. We then randomly drew thousands of bootstrap samples from this data set that included either 30, 60, 90, 120, 180, or 360 patients. For each resample, we recorded effect size estimates and p values after conducting exactly the same lesion-deficit analysis within the previously identified region of interest and holding all procedures constant. The results show (1) how often small effect sizes in a heterogeneous population fail to be detected; (2) how effect size and its statistical significance varies with sample size; (3) how low-powered studies (due to small sample sizes) can greatly over-estimate as well as under-estimate effect sizes; and (4) how large sample sizes (N ≥ 90) can yield highly significant p values even when effect sizes are so small that they become trivial in practical terms. The implications of these findings for interpreting the results from univariate voxel-based lesion-deficit analyses are discussed.</p

How distributed processing produces false negatives in voxel-based lesion-deficit analyses

In this study, we hypothesized that if the same deficit can be caused by damage to one or another part of a distributed neural system, then voxel-based analyses might miss critical lesion sites because preservation of each site will not be consistently associated with preserved function. The first part of our investigation used voxelbased multiple regression analyses of data from 359 right-handed stroke survivors to identify brain regions where lesion load is associated with picture naming abilities after factoring out variance related to object recognition, semantics and speech articulation so as to focus on deficits arising at the word retrieval level. A highly significant lesion-deficit relationship was identified in left temporal and frontal/premotor regions. Post-hoc analyses showed that damage to either of these sites caused the deficit of interest in less than half the affected patients (76/162 = 47%). After excluding all patients with damage to one or both of the identified regions, our second analysis revealed a new region, in the anterior part of the left putamen, which had not been previously detected because many patients had the deficit of interest after temporal or frontal damage that preserved the left putamen. The results illustrate how (i) false negative results arise when the same deficit can be caused by different lesion sites; (ii) some of the missed effects can be unveiled by adopting an iterative approach that systematically excludes patients with lesions to the areas identified in previous analyses, (iii) statistically significant voxel-based lesion-deficit mappings can be driven by a subset of patients; (iv) focal lesions to the identified regions are needed to determine whether the deficit of interest is the consequence of focal damage or much more extensive damage that includes the identified region; and, finally, (v) univariate voxel-based lesiondeficit mappings cannot, in isolation, be used to predict outcome in other patients

The Brainbox-a tool to facilitate correlation of brain magnetic resonance imaging features to histopathology

Magnetic resonance imaging (MRI) has limitations in identifying underlying tissue pathology, which is relevant for neurological diseases such as multiple sclerosis, stroke or brain tumours. However, there are no standardized methods for correlating MRI features with histopathology. Thus, here we aimed to develop and validate a tool that can facilitate the correlation of brain MRI features to corresponding histopathology. For this, we designed the Brainbox, a waterproof and MRI-compatible 3D printed container with an integrated 3D coordinate system. We used the Brainbox to acquire post-mortem ex vivo MRI of eight human brains, fresh and formalin-fixed, and correlated focal imaging features to histopathology using the built-in 3D coordinate system. With its built-in 3D coordinate system, the Brainbox allowed correlation of MRI features to corresponding tissue substrates. The Brainbox was used to correlate different MR image features of interest to the respective tissue substrate, including normal anatomical structures such as the hippocampus or perivascular spaces, as well as a lacunar stroke. Brain volume decreased upon fixation by 7% (P = 0.01). The Brainbox enabled degassing of specimens before scanning, reducing susceptibility artefacts and minimizing bulk motion during scanning. In conclusion, our proof-of-principle experiments demonstrate the usability of the Brainbox, which can contribute to improving the specificity of MRI and the standardization of the correlation between post-mortem ex vivo human brain MRI and histopathology. Brainboxes are available upon request from our institution

Biological and protective properties of immune sera directed to the influenza virus neuraminidase

The envelope of influenza A viruses contains two large antigens, hemagglutinin (HA) and neuraminidase (NA). Conventional influenza virus vaccines induce neutralizing antibodies that are predominantly directed to the HA globular head, a domain that is subject to extensive antigenic drift. Antibodies directed to NA are induced at much lower levels, probably as a consequence of the immunodominance of the HA antigen. Although antibodies to NA may affect virus release by inhibiting the sialidase function of the glycoprotein, the antigen has been largely neglected in past vaccine design. In this study, we characterized the protective properties of monospecific immune sera that were generated by vaccination with recombinant RNA replicon particles encoding NA. These immune sera inhibited hemagglutination in an NA subtype-specific and HA subtype-independent manner and interfered with infection of MDCK cells. In addition, they inhibited the sialidase activities of various influenza viruses of the same and even different NA subtypes. With this, the anti-NA immune sera inhibited the spread of H5N1 highly pathogenic avian influenza virus and HA/NA-pseudotyped viruses in MDCK cells in a concentration-dependent manner. When chickens were immunized with NA recombinant replicon particles and subsequently infected with low-pathogenic avian influenza virus, inflammatory serum markers were significantly reduced and virus shedding was limited or eliminated. These findings suggest that NA antibodies can inhibit virus dissemination by interfering with both virus attachment and egress. Our results underline the potential of high-quality NA antibodies for controlling influenza virus replication and place emphasis on NA as a vaccine antigen. IMPORTANCE The neuraminidase of influenza A viruses is a sialidase that acts as a receptor-destroying enzyme facilitating the release of progeny virus from infected cells. Here, we demonstrate that monospecific anti-NA immune sera inhibited not only sialidase activity, but also influenza virus hemagglutination and infection of MDCK cells, suggesting that NA antibodies can interfere with virus attachment. Inhibition of both processes, virus release and virus binding, may explain why NA antibodies efficiently blocked virus dissemination in vitro and in vivo. Anti-NA immune sera showed broader reactivity than anti-HA sera in hemagglutination inhibition tests and demonstrated cross-subtype activity in sialidase inhibition tests. These remarkable features of NA antibodies highlight the importance of the NA antigen for the development of next-generation influenza virus vaccines