David M. Cash

Faciobrachial dystonic seizures: the influence of immunotherapy on seizure control and prevention of cognitive impairment in a broadening phenotype.

Voltage-gated potassium channel complex antibodies, particularly those directed against leucine-rich glioma inactivated 1, are associated with a common form of limbic encephalitis that presents with cognitive impairment and seizures. Faciobrachial dystonic seizures have recently been reported as immunotherapy-responsive, brief, frequent events that often predate the cognitive impairment associated with this limbic encephalitis. However, these observations were made from a retrospective study without serial cognitive assessments. Here, we undertook the first prospective study of faciobrachial dystonic seizures with serial assessments of seizure frequencies, cognition and antibodies in 10 cases identified over 20 months. We hypothesized that (i) faciobrachial dystonic seizures would show a differential response to anti-epileptic drugs and immunotherapy; and that (ii) effective treatment of faciobrachial dystonic seizures would accelerate recovery and prevent the development of cognitive impairment. The 10 cases expand both the known age at onset (28 to 92 years, median 68) and clinical features, with events of longer duration, simultaneously bilateral events, prominent automatisms, sensory aura, and post-ictal fear and speech arrest. Ictal epileptiform electroencephalographic changes were present in three cases. All 10 cases were positive for voltage-gated potassium channel-complex antibodies (346-4515 pM): nine showed specificity for leucine-rich glioma inactivated 1. Seven cases had normal clinical magnetic resonance imaging, and the cerebrospinal fluid examination was unremarkable in all seven tested. Faciobrachial dystonic seizures were controlled more effectively with immunotherapy than anti-epileptic drugs (P = 0.006). Strikingly, in the nine cases who remained anti-epileptic drug refractory for a median of 30 days (range 11-200), the addition of corticosteroids was associated with cessation of faciobrachial dystonic seizures within 1 week in three and within 2 months in six cases. Voltage-gated potassium channel-complex antibodies persisted in the four cases with relapses of faciobrachial dystonic seizures during corticosteroid withdrawal. Time to recovery of baseline function was positively correlated with time to immunotherapy (r = 0.74; P = 0.03) but not time to anti-epileptic drug administration (r = 0.55; P = 0.10). Of 10 cases, the eight cases who received anti-epileptic drugs (n = 3) or no treatment (n = 5) all developed cognitive impairment. By contrast, the two who did not develop cognitive impairment received immunotherapy to treat their faciobrachial dystonic seizures (P = 0.02). In eight cases without clinical magnetic resonance imaging evidence of hippocampal signal change, cross-sectional volumetric magnetic resonance imaging post-recovery, after accounting for age and head size, revealed cases (n = 8) had smaller brain volumes than healthy controls (n = 13) (P < 0.001). In conclusion, faciobrachial dystonic seizures can be prospectively identified as a form of epilepsy with an expanding phenotype. Immunotherapy is associated with excellent control of the frequently anti-epileptic drug refractory seizures, hastens time to recovery, and may prevent the subsequent development of cognitive impairment observed in this study.

Regional variability of imaging biomarkers in autosomal dominant Alzheimer’s disease

Significance Beta-amyloid plaque accumulation, glucose hypometabolism, and neuronal atrophy are hallmarks of Alzheimer’s disease. However, the regional ordering of these biomarkers prior to dementia remains untested. In a cohort with Alzheimer’s disease mutations, we performed an integrated whole-brain analysis of three major imaging techniques: amyloid PET, [18F]fluro-deoxyglucose PET, and structural MRI. We found that most gray-matter structures with amyloid plaques later have hypometabolism followed by atrophy. Critically, however, not all regions lose metabolic function, and not all regions atrophy, even when there is significant amyloid deposition. These regional disparities have important implications for clinical trials of disease-modifying therapies. Major imaging biomarkers of Alzheimer’s disease include amyloid deposition [imaged with [11C]Pittsburgh compound B (PiB) PET], altered glucose metabolism (imaged with [18F]fluro-deoxyglucose PET), and structural atrophy (imaged by MRI). Recently we published the initial subset of imaging findings for specific regions in a cohort of individuals with autosomal dominant Alzheimer’s disease. We now extend this work to include a larger cohort, whole-brain analyses integrating all three imaging modalities, and longitudinal data to examine regional differences in imaging biomarker dynamics. The anatomical distribution of imaging biomarkers is described in relation to estimated years from symptom onset. Autosomal dominant Alzheimer’s disease mutation carrier individuals have elevated PiB levels in nearly every cortical region 15 y before the estimated age of onset. Reduced cortical glucose metabolism and cortical thinning in the medial and lateral parietal lobe appeared 10 and 5 y, respectively, before estimated age of onset. Importantly, however, a divergent pattern was observed subcortically. All subcortical gray-matter regions exhibited elevated PiB uptake, but despite this, only the hippocampus showed reduced glucose metabolism. Similarly, atrophy was not observed in the caudate and pallidum despite marked amyloid accumulation. Finally, before hypometabolism, a hypermetabolic phase was identified for some cortical regions, including the precuneus and posterior cingulate. Additional analyses of individuals in which longitudinal data were available suggested that an accelerated appearance of volumetric declines approximately coincides with the onset of the symptomatic phase of the disease.

Cortical surface registration for image-guided neurosurgery using laser-range scanning

In this paper, a method of acquiring intraoperative data using a laser range scanner (LRS) is presented within the context of model-updated image-guided surgery. Registering textured point clouds generated by the LRS to tomographic data is explored using established point-based and surface techniques as well as a novel method that incorporates geometry and intensity information via mutual information (SurfaceMI). Phantom registration studies were performed to examine accuracy and robustness for each framework. In addition, an in vivo registration is performed to demonstrate feasibility of the data acquisition system in the operating room. Results indicate that SurfaceMI performed better in many cases than point-based (PBR) and iterative closest point (ICP) methods for registration of textured point clouds. Mean target registration error (TRE) for simulated deep tissue targets in a phantom were 1.0 /spl plusmn/ 0.2,2.0 /spl plusmn/ 0.3, and 1.2 /spl plusmn/ 0.3 mm for PBR, ICP, and SurfaceMI, respectively. With regard to in vivo registration, the mean TRE of vessel contour points for each framework was 1.9 /spl plusmn/ 1.0, 0.9 /spl plusmn/ 0.6, and 1.3 /spl plusmn/ 0.5 for PBR, ICP, and SurfaceMI, respectively. The methods discussed in this paper in conjunction with the quantitative data provide impetus for using LRS technology within the model-updated image-guided surgery framework.

Presymptomatic cognitive and neuroanatomical changes in genetic frontotemporal dementia in the Genetic Frontotemporal dementia Initiative (GENFI) study: a cross-sectional analysis

BACKGROUND Frontotemporal dementia is a highly heritable neurodegenerative disorder. In about a third of patients, the disease is caused by autosomal dominant genetic mutations usually in one of three genes: progranulin (GRN), microtubule-associated protein tau (MAPT), or chromosome 9 open reading frame 72 (C9orf72). Findings from studies of other genetic dementias have shown neuroimaging and cognitive changes before symptoms onset, and we aimed to identify whether such changes could be shown in frontotemporal dementia. METHODS We recruited participants to this multicentre study who either were known carriers of a pathogenic mutation in GRN, MAPT, or C9orf72, or were at risk of carrying a mutation because a first-degree relative was a known symptomatic carrier. We calculated time to expected onset as the difference between age at assessment and mean age at onset within the family. Participants underwent a standardised clinical assessment and neuropsychological battery. We did MRI and generated cortical and subcortical volumes using a parcellation of the volumetric T1-weighted scan. We used linear mixed-effects models to examine whether the association of neuropsychology and imaging measures with time to expected onset of symptoms differed between mutation carriers and non-carriers. FINDINGS Between Jan 30, 2012, and Sept 15, 2013, we recruited participants from 11 research sites in the UK, Italy, the Netherlands, Sweden, and Canada. We analysed data from 220 participants: 118 mutation carriers (40 symptomatic and 78 asymptomatic) and 102 non-carriers. For neuropsychology measures, we noted the earliest significant differences between mutation carriers and non-carriers 5 years before expected onset, when differences were significant for all measures except for tests of immediate recall and verbal fluency. We noted the largest Z score differences between carriers and non-carriers 5 years before expected onset in tests of naming (Boston Naming Test -0·7; SE 0·3) and executive function (Trail Making Test Part B, Digit Span backwards, and Digit Symbol Task, all -0·5, SE 0·2). For imaging measures, we noted differences earliest for the insula (at 10 years before expected symptom onset, mean volume as a percentage of total intracranial volume was 0·80% in mutation carriers and 0·84% in non-carriers; difference -0·04, SE 0·02) followed by the temporal lobe (at 10 years before expected symptom onset, mean volume as a percentage of total intracranial volume 8·1% in mutation carriers and 8·3% in non-carriers; difference -0·2, SE 0·1). INTERPRETATION Structural imaging and cognitive changes can be identified 5-10 years before expected onset of symptoms in asymptomatic adults at risk of genetic frontotemporal dementia. These findings could help to define biomarkers that can stage presymptomatic disease and track disease progression, which will be important for future therapeutic trials. FUNDING Centres of Excellence in Neurodegeneration.

STEPS: Similarity and Truth Estimation for Propagated Segmentations and its application to hippocampal segmentation and brain parcelation

Anatomical segmentation of structures of interest is critical to quantitative analysis in medical imaging. Several automated multi-atlas based segmentation propagation methods that utilise manual delineations from multiple templates appear promising. However, high levels of accuracy and reliability are needed for use in diagnosis or in clinical trials. We propose a new local ranking strategy for template selection based on the locally normalised cross correlation (LNCC) and an extension to the classical STAPLE algorithm by Warfield et al. (2004), which we refer to as STEPS for Similarity and Truth Estimation for Propagated Segmentations. It addresses the well-known problems of local vs. global image matching and the bias introduced in the performance estimation due to structure size. We assessed the method on hippocampal segmentation using a leave-one-out cross validation with optimised model parameters; STEPS achieved a mean Dice score of 0.925 when compared with manual segmentation. This was significantly better in terms of segmentation accuracy when compared to other state-of-the-art fusion techniques. Furthermore, due to the finer anatomical scale, STEPS also obtains more accurate segmentations even when using only a third of the templates, reducing the dependence on large template databases. Using a subset of Alzheimers Disease Neuroimaging Initiative (ADNI) scans from different MRI imaging systems and protocols, STEPS yielded similarly accurate segmentations (Dice=0.903). A cross-sectional and longitudinal hippocampal volumetric study was performed on the ADNI database. Mean±SD hippocampal volume (mm(3)) was 5195 ± 656 for controls; 4786 ± 781 for MCI; and 4427 ± 903 for Alzheimers disease patients and hippocampal atrophy rates (%/year) of 1.09 ± 3.0, 2.74 ± 3.5 and 4.04 ± 3.6 respectively. Statistically significant (p<10(-3)) differences were found between disease groups for both hippocampal volume and volume change rates. Finally, STEPS was also applied in a multi-label segmentation propagation scenario using a leave-one-out cross validation, in order to parcellate 83 separate structures of the brain. Comparisons of STEPS with state-of-the-art multi-label fusion algorithms showed statistically significant segmentation accuracy improvements (p<10(-4)) in several key structures.

Compensating for intraoperative soft-tissue deformations using incomplete surface data and finite elements

Image-guided liver surgery requires the ability to identify and compensate for soft tissue deformation in the organ. The predeformed state is represented as a complete three-dimensional surface of the organ, while the intraoperative data is a range scan point cloud acquired from the exposed liver surface. The first step is to rigidly align the coordinate systems of the intraoperative and preoperative data. Most traditional rigid registration methods minimize an error metric over the entire data set. In this paper, a new deformation-identifying rigid registration (DIRR) is reported that identifies and aligns minimally deformed regions of the data using a modified closest point distance cost function. Once a rigid alignment has been established, deformation is accounted for using a linearly elastic finite element model (FEM) and implemented using an incremental framework to resolve geometric nonlinearities. Boundary conditions for the incremental formulation are generated from intraoperatively acquired range scan surfaces of the exposed liver surface. A series of phantom experiments is presented to assess the fidelity of the DIRR and the combined DIRR/FEM approaches separately. The DIRR approach identified deforming regions in 90% of cases under conditions of realistic surgical exposure. With respect to the DIRR/FEM algorithm, subsurface target errors were correctly located to within 4 mm in phantom experiments.

Incorporation of a laser range scanner into image‐guided liver surgery: Surface acquisition, registration, and tracking

As image guided surgical procedures become increasingly diverse, there will be more scenarios where point-based fiducials cannot be accurately localized for registration and rigid body assumptions no longer hold. As a result, procedures will rely more frequently on anatomical surfaces for the basis of image alignment and will require intraoperative geometric data to measure and compensate for tissue deformation in the organ. In this paper we outline methods for which a laser range scanner may be used to accomplish these tasks intraoperatively. A laser range scanner based on the optical principle of triangulation acquires a dense set of three-dimensional point data in a very rapid, noncontact fashion. Phantom studies were performed to test the ability to link range scan data with traditional modes of image-guided surgery data through localization, registration, and tracking in physical space. The experiments demonstrate that the scanner is capable of localizing point-based fiducials to within 0.2 mm and capable of achieving point and surface based registrations with target registration error of less than 2.0 mm. Tracking points in physical space with the range scanning system yields an error of 1.4 +/- 0.8 mm. Surface deformation studies were performed with the range scanner in order to determine if this device was capable of acquiring enough information for compensation algorithms. In the surface deformation studies, the range scanner was able to detect changes in surface shape due to deformation comparable to those detected by tomographic image studies. Use of the range scanner has been approved for clinical trials, and an initial intraoperative range scan experiment is presented. In all of these studies, the primary source of error in range scan data is deterministically related to the position and orientation of the surface within the scanners field of view. However, this systematic error can be corrected, allowing the range scanner to provide a rapid, robust method of acquiring anatomical surfaces intraoperatively.

A method to track cortical surface deformations using a laser range scanner

This paper reports a novel method to track brain shift using a laser-range scanner (LRS) and nonrigid registration techniques. The LRS used in this paper is capable of generating textured point-clouds describing the surface geometry/intensity pattern of the brain as presented during cranial surgery. Using serial LRS acquisitions of the brains surface and two-dimensional (2-D) nonrigid image registration, we developed a method to track surface motion during neurosurgical procedures. A series of experiments devised to evaluate the performance of the developed shift-tracking protocol are reported. In a controlled, quantitative phantom experiment, the results demonstrate that the surface shift-tracking protocol is capable of resolving shift to an accuracy of approximately 1.6 mm given initial shifts on the order of 15 mm. Furthermore, in a preliminary in vivo case using the tracked LRS and an independent optical measurement system, the automatic protocol was able to reconstruct 50% of the brain shift with an accuracy of 3.7 mm while the manual measurement was able to reconstruct 77% with an accuracy of 2.1 mm. The results suggest that a LRS is an effective tool for tracking brain surface shift during neurosurgery.

A data-driven model of biomarker changes in sporadic Alzheimer's disease

Young et al. reformulate an event-based model for the progression of Alzheimers disease to make it applicable to a heterogeneous sporadic disease population. The enhanced model predicts the ordering of biomarker abnormality in sporadic Alzheimers disease independently of clinical diagnoses or biomarker cut-points, and shows state-of-the-art diagnostic classification performance.

Making short-term climate forecasts useful: Linking science and action

This paper discusses the evolution of scientific and social understanding that has led to the development of knowledge systems supporting the application of El Niño-Southern Oscillation (ENSO) forecasts, including the development of successful efforts to connect climate predictions with sectoral applications and actions “on the ground”. The evolution of “boundary-spanning” activities to connect science and decisionmaking is then discussed, setting the stage for a report of outcomes from an international workshop comprised of producers, translators, and users of climate predictions. The workshop, which focused on identifying critical boundary-spanning features of successful boundary organizations, included participants from Australia, Hawaii, and the Pacific Islands, the US Pacific Northwest, and the state of Ceará in northwestern Brazil. Workshop participants agreed that boundary organizations have multiple roles including those of information broker, convenor of forums for engagement, translator of scientific information, arbiter of access to knowledge, and exemplar of adaptive behavior. Through these roles, boundary organizations will ensure the stability of the knowledge system in a changing political, economic, and climatic context. The international examples reviewed in this workshop demonstrated an interesting case of convergent evolution, where organizations that were very different in origin evolved toward similar structures and individuals engaged in them had similar experiences to share. These examples provide evidence that boundary organizations and boundary-spanners fill some social/institutional roles that are independent of culture.