Geriatric Neurology

Aging affects neurological function leading to neurological disease

As society grows older, so do the neurological problems associated with aging. These can be new neurological deficits due to the aging process itself, or the effect of aging on already existing neurological conditions. Neurologists will spend increasing amounts of time managing patients with age-related neurological complications.

Geriatric Neurology brings together the wisdom of world-leading experts. They have crafted a new textbook to define this emerging subspecialty from basic science through clinical assessment and medical management to social aspects of patient care. Geriatric Neurology covers:

• The aging brain in neurology
• Assessment of the geriatric neurology patient
• Neurological conditions in the elderly
• Therapeutics for the geriatric neurology patient
• Management issues beyond therapeutics

Comprehensive in scope but with practical focus for effective patient care, Geriatric Neurology provides top-of-class guidance for the management of elderly patients with neurological disorders.

• Language: English
• Publisher: Wiley
• Release date: Mar 6, 2014
• ISBN: 9781118730645

Book preview

I dedicate this book to my patients and mentors. This book would not be possible without my grandfather who carried me on his shoulders daily to an elementary school miles away and my very supportive family.

AKN

I dedicate this work to my mother and father, who nurtured my unquenchable thirst for knowledge.

MNS

Geriatric Neurology

EDITED BY

ANIL K. NAIR MD

Director, Clinic for Cognitive Disorders

and Alzheimer’s Disease Center

Chief of Neurology, Quincy Medical Center

Quincy, MA, USA

MARWAN N. SABBAGH MD, FAAN

Director, Banner Sun Health Research Institute

Research Professor of Neurology

University of Arizona College of Medicine – Phoenix

Sun City, AZ, USA

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This edition first published 2014

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Library of Congress Cataloging-in-Publication Data

Geriatric neurology (Nair)

Geriatric neurology/edited by Anil K. Nair and Marwan N. Sabbagh.

1 online resource.

Includes bibliographical references and index.

Description based on print version record and CIP data provided by publisher; resource not viewed.

ISBN 978-1-118-73064-5 (ePub) – ISBN 978-1-118-73065-2 (Adobe PDF) – ISBN 978-1-118-73068-3 (cloth)

I. Nair, Anil (Anil Kadoor), 1970- editor of compilation. II. Sabbagh, Marwan Noel, editor of compilation. III. Title.

[DNLM: 1. Nervous System Diseases. 2. Aged. 3. Aging–physiology. 4. Nervous System Physiological Phenomena. WL 140]

RC451.4.A5

618.97′68–dc23

2013038615

A catalogue record for this book is available from the British Library.

Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books.

Cover images: top row - copyright Wiley; bottom - courtesy of Anil K. Nair

Cover design by Andy Meaden

CONTENTS

About the Editors

List of Contributors

Preface

Acknowledgements

Part 1 The Aging Brain in Neurology

1 The Biology of Aging: Implications for Diseases of Aging and Health Care in the Twenty-First Century

2 Functional Changes Associated with the Aging Nervous System

Part 2 Assessment of the Geriatric Neurology Patient

3 Approach to the Geriatric Neurology Patient: The Neurologic Examination

4 Assessment of Cognitive Status in Geriatric Neurology

4.1 Mental Status Examination in the Geriatric Neurology Patient

4.2 Neuropsychology in Geriatric Neurology

5 Cognitive Reserve and the Aging Brain

6 Gait Disorders in the Graying Population

7 Imaging of the Geriatric Brain

7.1 Structural Neuroimaging in Degenerative Dementias

7.2 Functional Imaging in Dementia

7.3 Amyloid Imaging

8 Clinical Laboratory Investigations in Geriatric Neurology

Part 3 Neurologic Conditions in the Elderly

9 Cognitive Impairment and the Dementias

9.1 Mild Cognitive Impairment

9.2 Alzheimer’s Disease

9.3 Dementia with Lewy Bodies

9.4 Vascular Cognitive Impairment

9.5 Frontotemporal Dementia

9.6 Primary Progressive Aphasia

9.7 Prion Diseases

9.8 Normal Pressure Hydrocephalus

10 Depression in the Elderly: Interactions with Aging, Stress, Chronic Pain, Inflammation, and Neurodegenerative Disorders

11 Cerebrovascular Diseases in Geriatrics

12 Movement Disorders

12.1 Parkinson’s Disease

12.2 Essential Tremor and Other Tremor Disorders

12.3 Progressive Supranuclear Palsy

12.4 Corticobasal Degeneration

13 Sleep Disorders

14 Autonomic Dysfunction and Syncope

15 Geriatric Epilepsy

16 Vertigo and Dizziness in the Elderly

17 Disorders of the Special Senses in the Elderly

18 Nervous System Infections

19 Delirium

20 Headache in the Elderly

21 Neuromuscular Disorders

Part 4 Therapeutics for the Geriatric Neurology Patient

22 Neurosurgical Care of the Geriatric Patient

23 Treatment of Dementia

23.1 Evidence-Based Pharmacologic Treatment of Dementia

23.2 Immunotherapy for Alzheimer’s Disease

24 Geriatric Psychopharmacology

25 Nonpharmacologic Treatment of Behavioral Problems in Persons with Dementia

26 Expressive Art Therapies in Geriatric Neurology

Part 5 Important Management Issues Beyond Therapeutics in the Geriatric Neurology Patient

27 Dietary Factors in Geriatric Neurology

28 Exercising the Brain: Nonpharmacologic Interventions for Cognitive Decline Associated with Aging and Dementia

29 Driving Impairment in Older Adults

30 Elder Abuse and Mistreatment

31 Advocacy in Geriatric Neurology

Index

List of Tables

Chapter 1

Table 1.1

Chapter 3

Table 3.1

Table 3.2

Table 3.3

Chapter 4

Table 4.1

Table 4.2

Table 4.3

Table 4.1

Table 4.2

Table 4.3

Chapter 6

Table 6.1

Chapter 7

Table 7.1

Chapter 8

Table 8.1

Table 8.2

Table 8.3

Chapter 9

Table 9.1

Table 9.2

Table 9.3

Table 9.4

Table 9.5

Table 9.6

Table 9.7

Table 9.8

Table 9.9

Table 9.10

Table 9.11

Table 9.12

Table 9.13

Table 9.14

Table 9.15

Chapter 10

Table 10.1

Chapter 11

Table 11.1

Table 11.2

Table 11.3

Table 11.4

Chapter 12

Table 12.1

Table 12.2

Table 12.3

Chapter 14

Table 14.1

Table 14.2

Chapter 16

Table 16.1

Table 16.2

Table 16.3

Table 16.4

Table 16.5

Chapter 17

Table 17.1

Table 17.2

Chapter 18

Table 18.1

Table 18.2

Table 18.3

Table 18.4

Table 18.5

Table 18.6

Table 18.7

Table 18.8

Chapter 19

Table 19.1

Table 19.2

Table 19.3

Chapter 22

Table 22.1

Chapter 23_1

Table 23.1

Table 23.2

Table 23.3

Table 23.4

Table 23.5

Table 23.6

Table 23.7

Table 23.8

Table 23.9

Table 23.10

Chapter 24

Table 24.1

Table 24.2

Table 24.3

Table 24.4

Table 24.5

Table 24.6

Table 24.7

Table 24.8

Table 24.9

Table 24.10

Table 24.11

Table 24.12

Table 24.13

Table 24.14

Table 24.15

Chapter 30

Table 30.1

Table 30.2

Table 30.3

List of Illustrations

Chapter 1

Figure 1.1 Cell cycle factors related to aging based on the stochastic acceleration hypothesis of Collier, Kanaan & Kordower (2011). A revised hypothesis of the relationship between aging and Parkinson’s disease (PD) as they affect the biology of midbrain dopamine (DA) neurons. The hypothesis incorporates evidence that supports the involvement of common cellular mechanisms in dopamine neuron dysfunction in ageing and degeneration in Parkinson’s disease. (a) The effects of these altered cellular mechanisms as they accumulate during normal ageing result in Parkinsonian dopamine neuron dysfunction, either very late in life or not at all (shown by the light gray line). However, when these same cellular mechanisms are accelerated by specific, individually determined factors, Parkinsonism emerges earlier in the lifespan (shown by the dark gray line). (b) The hypothesis contends that the cellular mechanisms that threaten dopamine neuron function are identical, but are not linked in an orderly cascade of cause and effect; instead, they can contribute to varying degrees and combine in patient-specific patterns, thus fulfilling the definition of a stochastic interaction: incorporating elements of randomness with directionality toward dopamine neuron dysfunction. Light gray double-ended arrows show cellular events in normal ageing. Thicker, dark gray double-ended arrows show accelerated cellular events in PD. UPS, ubiquitin-proteasome system. Similar mechanisms are implicated in cancer pathogenesis also. Source: Blagosklonny (2011). Reproduced with permission from US Administration on Aging.

Figure 1.2 A simple schematic for the molecular pathway of mTOR as antagonistic pleiotropy–that, in some sense, aging is simply the flip side of a protracted growth process that is not sufficiently turned off after a peak reproductive period. Source: Blagosklonny (2009). Reproduced with permission from US Administration on Aging.

Figure 1.3 A simple schematic of some of the cellular pathways implicated in calorie restriction, aging, and the slowing of aging. Nutrients, growth factors (GF), and insulin activate the TOR pathway, which is involved in aging and age-related diseases. Other genetic factors and environmental factors (such as smoking, sedentary lifestyles, and obesity) contribute to age-related diseases. Several potential antiaging modalities (metformin, calorie restriction, and rapamycin and several polyphenols particularly resveratrol) all directly or indirectly (via impact on AMP kinase) inhibit the TOR pathway. Source: Blagosklonny (2009, 2010a). Reproduced with permission from US Administration on Aging.

Figure 1.4 A schematic summarizing the hypothesis for how diet balance might affect lifespan via the TOR and AMPK signaling pathways. Source: Simpson and Raubenheimer (2009). Reproduced with permission from US Administration on Aging.

Chapter 2

Figure 2.1 Apical dendrite (arrow head) and cell body (arrow) of pyramidal neuron, hippocampus CA1, mouse brain (Golgi stain).

Figure 2.2 Dendritic spines, mouse brain, hippocampus CA1 (Golgi stain).

Figure 2.3 Activated cortical microglia in older person without cognitive impairment; antibody to class II major histocompatibility antigen (MHCII).

Figure 2.4 Alzheimer’s disease brain showing (a) narrowing of gyri and widened sulci, and hippocampal atrophy with enlargement of lateral ventricles, especially temporal horn (b).

Figure 2.5 Neurofibrillary tangles: (a) hippocampus CA1 (modified Bielschowsky stain); (b) frontal cortex (immunohistochemistry with antibodies to paired helical filament).

Figure 2.6 Ghost tangles, hippocampus CA1 (modified Bielschowsky silver stain).

Figure 2.7 Neuritic plaque pathology in AD. (a) Three NPs in the neocortex on H&E stain are difficult to see. (b) The same NPs are easily visualized on modified Bielschowsky silver stain.

Figure 2.8 Amyloid pathology in AD. (a) Numerous amyloid immunostained plaques in the cortex at low power. (b) Leptomeningeal arterioles also may show amyloid deposition. (c, d) Higher power of plaque pathology using amyloid immunostain.

Figure 2.9 An old lacunar infarct in the anterior thalamic nucleus: (a) gross coronal brain slab; (b) histologic appearance of old infarct with few macrophages and cavitation.

Figure 2.10 Subcortical ischemic vascular disease. Both (a) gross and (b) histologic brain sections show lacunar infarcts and enlarged perivascular spaces predominantly in the caudate in a person with vascular parkinsonism.

Figure 2.11 Substantia nigra neurons with multiple LBs: (a) classic dense concentric appearance with peripheral halo on H&E; (b) LB halo stains darker using antibodies to α-synuclein.

Figure 2.12 Cortical LBs in the superior temporal cortex. (a) H&E stain shows an eosinophilic cytoplasmic inclusion without a clearly defined halo. (b) Low-magnification view showing numerous α-synuclein-immunostained cortical LBs. (c) Cortical LBs may stain uniformly or show a peripheral halo with α-synuclein immunostain.

Figure 2.13 Corticobasal degeneration: ballooned neuron (neuronal achromasia) on H&E stain.

Figure 2.14 Tau-immunopositive astrocytic plaques are characteristic of CBD (AT8 immunohistochemistry).

Figure 2.15 Progressive supranuclear palsy: neurofibrillary tangle (NFT) pathology. (a) Globose NFT with basophilic filamentous appearance (H&E). (b) NFT in SN highlighted with tau immunohistochemistry. (c) Antibody to 4-repeat tau isoforms labels two NFT.

Figure 2.16 PSP: astrocytic pathology. (a) Tau-immunoreactive tufted astrocyte in the subthalamic nucleus (AT8 antibody). (b) Coiled bodies that immunolabel with antibodies specific to 4-repeat tau.

Figure 2.17 FTLD-TDP: TDP-43 immunoreactive inclusions in the neurons of the dentate layer of hippocampus. (a) Low magnification shows diffuse nuclear staining and numerous TDP-43 positive inclusions (arrows). (b) High magnification shows cytoplasm inclusions with nuclear clearing in affected neurons.

Figure 2.18 Atherosclerosis, the Circle of Willis. Note the asymmetric involvement of vertebral arteries, extension into basilar artery, and posterior cerebral arteries.

Figure 2.19 Fusiform aneurysm of the basilar artery. Artery is dilated and tortuous and may compress and distort the brain stem.

Figure 2.20 Arteriolosclerosis: hyaline thickening of two small vessels in the deep white matter. Note that the upper vessel appears occluded.

Figure 2.21 Cerebral amyloid angiopathy. (a) Cortex involves small-size and medium-size arteries, arterioles, and capillaries (arrows; small arrow also shows dysphoric change). (b) Leptomeninges vessels. (c) Amyloid alternating with amyloid-free regions. (d) Double-barrel appearance from separation of endothelium from the affected muscularis. (a–c, Aβ immunostain.)

Figure 2.22 Charcot–Bouchard aneurysm; note the markedly thinned region of the vessel wall.

Figure 2.23 Amyotrophic lateral sclerosis. (a) Pallor of the lateral corticospinal tracts of spinal cord on myelin stain. (b) Low and (c) high magnification show CD8 immunostained macrophages indicative of degeneration.

Figure 2.24 Amyotrophic lateral sclerosis anterior horn cell with a Bunina body.

Figure 2.25 Amyotrophic lateral sclerosis. Hyaline inclusions in an anterior horn motor neuron on H&E (a) and ubiquitin (b). (c) Skein-like inclusions in the anterior horn cells in ALS also stain with antibodies to ubiquitin.

Figure 2.26 Glioblastoma multiforme: gross appearance with variegated necrotic-appearing mass without definite borders.

Figure 2.27 Glioblastoma: histologic appearance of pseudopalisading necrosis.

Figure 2.28 Metastatic adenocarcinoma: cortical lesion appears well demarcated and necrotic.

Chapter 3

Figure 3.1 Montreal cognitive assessment (MOCA)—http://www.mocatest.org (accessed on April 8, 2013).

Chapter 4

Figure 4.1 Line bisection test.

Figure 4.2 Clock-drawing test.

Figure 4.3 Clock-drawing test.

Figure 4.4 House-drawing test.

Chapter 6

Figure 6.1 Footfall patterns recorded on an instrumented walkway: (a) frontal gait; (b) parkinsonism; (c) ataxic gait; (d) left hemiparetic.

Chapter 7

Figure 7.1 7T structural MRI hippocampal images from a normal elderly person (normal control (NC), left column) and an advanced AD patient (right column). Significant hippocampal atrophy can be easily appreciated in the sagittal (top row) and coronal sections through the hippocampal head (middle row) and body (bottom row). Cortical thinning of the entorhinal and parahippocampal cortex is also evident in AD.

Figure 7.2 Brain atrophy in prodromal and advanced AD. In the prodromal stages, mild hippocampal and global brain atrophy and mild ventriculomegaly are noted. In advanced AD, severe hippocampal and global brain atrophy and ventriculomegaly are easily identified.

Figure 7.3 3D hippocampal atrophy maps showing the amount of atrophy (in %) accumulated over a 3-year period in cognitively normal elderly patients who remained cognitively normal for 6 years or longer since baseline (NL–NL) and cognitively normal elderly patients who were diagnosed with amnestic MCI at 3 years and AD at 6 years (NL–MCIAD).

Figure 7.4 Cortical atrophy in AD. Relative to patients with amnestic MCI, patients with very mild AD show extensive cortical atrophy of the entorhinal, parahippocampal, inferior, and lateral temporal cortices, with disease changes spreading next to the parietal and frontal association cortices (left column). The pattern is strikingly similar to the amyloid deposition described in Braak and Braak amyloid stage B (right column).

Figure 7.5 Brain atrophy in FTD. Frontal variant FTD is characterized by prominent frontal lobe atrophy. Primary progressive aphasia subjects have asymmetric left-predominant perisylvian atrophy most pronounced in the posterior portions of the inferior frontal gyrus. SD patients characteristically present with left-predominant anterior temporal atrophy.

Figure 7.6 Diffusion-weighted imaging findings in CJD. Extensive cortical hyperintensities can be identified in the right temporal, the bilateral insular and frontal cortex, and the caudates.

Figure 7.7 FDG-PET in 92 AD and 184 MCI participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI; Mueller et al., 2006; Jack et al., 2008a), compared with 104 cognitively normal elderly controls. Top images show typical patterns of glucose hypometabolism in Alzheimer’s disease (AD), compared with normal. Bottom images show similar AD-like patterns, but to a less spatial and intensity extent in MCI. See Langbaum et al. (2009) for methodology details.

Figure 7.8 FDG-PET in 298 participants with varying degrees of MCI and AD, and cognitively normal elderly from ADNI (Mueller et al., 2006; Jack et al., 2008a). (a) Areas of correlated FDG-PET binding representing glucose hypometabolism associated with CDR scores. (b) Areas of correlated FDG-PET binding representing glucose hypometabolism associated with MMSE scores. Regions associated with cognitive impairment are similar to those associated with a diagnosis of clinical AD (Figure 7.7). See Langbaum et al., 2009 for methodology details.

Figure 7.9 Regions of the brain with abnormally low CMRgl in young adult carriers of two copies of the APOE ε4-allele and their relationship to brain regions with abnormally low CMRgl in patients with probable AD. Purple areas are regions in which CMRgl was abnormally low only in patients with AD. Bright blue areas are regions in which CMRgl was abnormally low in both the young adult e4 carriers and patients with probable AD. The muted blue areas are regions in which CMRgl was abnormally low only in the ε4 carriers. Source: Reiman et al. (2004). Reproduced with permission from National Academy of Sciences.

Figure 7.10 Individual FDG-PET scans in a patient with (a) normal cognition, (b) MCI, (c) AD, (d) bvFTLD, and (e) DLB. Images on the left are individual FDG-PET CMRgl binding, showing areas of significant glucose hypometabolism compared with normal controls (blue). An automated algorithm was used to transform individual patient images into the dimensions of a standard brain and compute statistical maps of significantly reduced glucose metabolism relative to 67 normal control subjects (mean age 64 years). Red-outlined regions represent areas of mean hypometabolism seen in FDG-PET scans from 14 patients with AD (mean age 64 years), compared with the same 67 normal controls. On the right are raw FDG-PET color maps from the same corresponding patients. Here we can see the use of FDG-PET for identifying disease-specific patterns of glucose metabolism for clinical use in individual patients, to assist with diagnostic decision-making.

Figure 7.11 Details of Montreal Cognitive Assessment (MOCA) test subsets for cases 1, 2 and 3. Top row is tests performed by Ms. JW, middle row by Mr. PS and bottom row by Ms.EC. The executive function and memory test performance might have misclassified the patients without the amyloid imaging test information. Amyloid positive patients outperformed the amyloid negative subject on executive function. Immediate memory was preserved in all subjects. Short term free delayed recall was impaired in all subjects, and cued recall was present, contributing to clinical uncertainty. These clinical settings are appropriate to use amyloid imaging for furthering the diagnosis.

Figure 7.12 Amyloid Imaging for Cases 1, 2 and 3. Top row is images from Ms. JW, middle row from Mr. PS and bottom row from Ms.EC. Even with significant accumulation of amyloid in their brain, the amyloid positive patients outperformed the amyloid negative subject on executive function tests. Memory evaluations were worse, contributing to clinical uncertainty. The amyloid scans facilitated early diagnosis and appropriate treatment for all three patients.

Figure 7.13 Falsely colored amyloid images for cases 1, 2 and 3. Top row is images from Ms. JW, middle row from Mr. PS and bottom row from Ms. EC. Even though there images further highlight the significant differences in accumulation of amyloid, it is recommended that black and white images be used in diagnostic visual evaluation and rating of amyloid images. This is to minimize machine and operator factors involved in producing false color images leading to greater inter rater variability.

Chapter 8

Figure 8.1 Definitions of test performance metrics.

Figure 8.2 Most appropriate use of laboratory testing based on clinical test performance.

Chapter 9

Figure 9.1 The 2011 criteria for preclinical AD.

Figure 9.2 Evolving model: relative contributions of CVD and AD to cognitive impairment.

Figure 9.3 Silent infarcts and white matter changes are found in 20–30% elderly persons.

Figure 9.4 Subcortical vascular dementia prefrontal–subcortical circuits.

Figure 9.5 Meta-analysis of controlled trials of AchEI and memantine in VaD. Source: Kavirajan and Schneider (2007). Reproduced with permission from Elsevier.

Figure 9.6 MRI axial, coronal, and sagittal T1 showing bifrontal atrophy, more on the right.

Figure 9.7 Clinical and pathologic correlates between FTD spectrum syndromes and FTLD pathologies. PSP, progressive supranuclear palsy; CBS, corticobasal syndrome; bvFTD, behavioral variant frontotemporal dementia; PPA, primary progressive aphasia; svPPA, semantic variant primary progressive aphasia; nfvPPA, nonfluent variant primary progressive aphasia; lvPPA, logopenic variant primary progressive aphasia; FTD-MND, frontotemporal dementia with motor neuron disease; FTLD-tau, frontotemporal lobar degeneration with tau pathology; FTLD-TDP, FTLD with TAR DNA-binding protein 43 (TDP-43) pathology; FTLD-FUS, FTLD with fused in sarcoma (FUS) pathology; AD, Alzheimer’s disease.

Figure 9.8 Pick’s bodies detected in a 74-year-old woman with progressive nonfluent aphasia due to Pick’s disease. A 3-repeat tau antibody was applied to the dentate gyrus, where Pick bodies can easily be detected due to the neuronal packing density of the structure. Hematoxylin counterstain. Courtesy of W.W. Seeley, University of California, San Francisco.

Figure 9.9 Decision tree for PPA diagnosis by variant: core features. SV, semantic variant; LV, logopenic variant; NFV, nonfluent variant.

Figure 9.10 MRI scans showing distinct patterns of focal left-hemisphere cortical atrophy in patients with different PPA subtypes. Atrophy predominantly involves left inferior frontal cortex and insula in the nonfluent variant, left anterior temporal cortex in the semantic variant, and temporoparietal cortex in the logopenic variant (arrows). Source: Wilson et al. (2009b). Reproduced with permission from Oxford University Press.

Figure 9.11 Voxel-based morphometry (VBM) demonstrating the topographic distribution of left-hemisphere cortical atrophy in three PPA cohorts (red = nonfluent/agrammatic, blue = semantic, and green = logopenic). Courtesy of S.M. Wilson and M.L. Gorno-Tempini.

Figure 9.12 Models for the conformational conversion of PrPC to PrPSc. (a) The refolding model. The conformational change is kinetically controlled, a high-activation energy barrier preventing spontaneous conversion at detectable rates. Interaction with exogenously introduced PrPSc causes PrPC to undergo an induced conformational change to yield PrPSc. This reaction could be facilitated by an enzyme or chaperone. In the case of certain mutations in PrPC, spontaneous conversion to PrPSc may occur as a rare event, explaining why familial CJD or GSS arises spontaneously, albeit late in life. Sporadic CJD may come about when an extremely rare event (occurring in about one in a million individuals per year) leads to spontaneous conversion of PrPC to PrPSc. (b) The seeding model. PrPC and PrPSc (or a PrPSc-like molecule, light) are in equilibrium, with PrPC strongly favored. PrPSc is stabilized only when it adds onto a crystal-like seed or aggregate of PrPSc (dark). Seed formation is rare; however, once a seed is present, monomer addition ensues rapidly. To explain exponential conversion rates, aggregates must be continuously fragmented, generating increasing surfaces for accretion. Reproduced from Weissmann C et al. (2002).

Figure 9.13 The prion protein. (a) The prion protein gene (PRNP) is located on the short arm of the human chromosome 20. The nonpathogenic polymorphism includes deletion of one of the octarepeat segments, methionine–valine polymorphism at the 129 position, and glutamine–lysine polymorphism at position 219. (b) Post-translational modification truncates the cellular prion protein (PrPC) at positions 23 and 231 and glycosylates (Y) at positions 181 and 197. The phosphatidylinositol glycolipid (GPI) attached to serine at position 231 anchors the C-terminus to the cellular membrane. The intracellular N-terminus contains five octarepeat segments, P(Q/H)GGG(G/-)WGQ (blue blocks), that can bind copper ions. The central part of the protein contains one short α-helical segment (α-helix A encompassing residues 144–157 [green block]), flanked by two short β-strands (red blocks): β1(129–131) and β2(161–163). The secondary structure of the C-terminus is dominated by two long α-helical domains: α-helix B (residues 172–193) and α-helix C (residues 200–227), which are connected by a disulfide bond. The blue arrows indicate binding sites of the protein X within α-helices B and C. The dashed frame marks a segment between positions 90 and 150, which is crucial for the binding of PrPC to PrPSc. (c) PrPSc has increased β-sheet content (red dashed block). (d) Unlike PrPSc, which is anchored to the membrane, GSS amyloidogenic peptides are truncated and excreted into the cellular space, where they aggregate and fibrillize into GSS amyloid deposits. This example is an 8-kDa PrP fragment associated with the most common GSS/P102L mutation. A synthetic form of this peptide (90–150 residues), exposed to acetonitrile treatment to increase β-sheet content, is the only synthetically generated peptide that, when injected intracerebrally into P102L-transgenic mice, is able to induce the GSS disease. Source: Geschwind (2011). Reproduced with permission from Elsevier.

Figure 9.14 Neuropathology of prion disease. (a) In sCJD, some brain areas may have no (hippocampal end plate, left), mild (subiculum, middle), or severe (temporal cortex, right) spongiform change. Haematoxylin and eosin (H&E) stain. (b) Cortical sections immunostained for PrPSc in sCJD: synaptic (left), patchy/perivacuolar (middle), or plaque type (right) patterns of PrPSc deposition. (c) Large Kuru-type plaque, H&E stain. (d) Typical florid plaques in vCJD, H&E stain. Source: Budka (2003). Reproduced with permission from Oxford University Press.

Figure 9.15 A typical EEG in a sCJD patient with diffuse slowing and 1 Hz periodic sharp waves complexes (PSWCs). Source: Geschwind (2011). Reproduced with permission from Elsevier.

Figure 9.16 DWI and FLAIR MRI in sCJD and vCJD. Three common MRI patterns in sCJD: predominantly subcortical (a, b), both cortical and subcortical (c, d), and predominantly cortical (e, f); also a patient with probable variant CJD (vCJD) (g, h). Note that, in sCJD, the abnormalities are more evident on DWI (a, c, e) than on FLAIR (b, d, f) images. The three sCJD cases (a, b; c, d; e, f) are pathology proven. (a, b) A 52-year-old woman with MRI showing strong hyperintensity in bilateral caudate (solid arrow) and putamen (dashed arrow) and slight hyperintensity in bilateral mesial and posterior thalamus (dotted arrow). (c, d) A 68-year-old man with MRI showing hyperintensity in bilateral caudate and putamen (note anteroposterior gradient in the putamen, which is commonly seen in CJD), thalamus, right insula (dotted arrow), anterior and posterior cingulate gyrus (solid arrow, L>R), and left temporal–parietal–occipital junction (dashed arrow). (e, f) A 76-year-old woman with MRI showing diffuse hyperintense signal mainly in bilateral temporoparietal (solid arrows) and occipital cortex (dotted arrow), right posterior insula (dashed arrow), and left inferior frontal cortex (arrowhead), but no significant subcortical abnormalities. (g, h) A 21-year-old woman with probable vCJD, with MRI showing bilateral thalamic hyperintensity in the mesial pars (mainly dorsomedian nucleus) and posterior pars (pulvinar) of the thalamus, the so-called double hockey stick sign. Also note the pulvinar sign, with the posterior thalamus (pulvinar; arrow) being more hyperintense than the anterior putamen. CJD, Creutzfeldt–Jakob disease; MRI, magnetic resonance imaging; DWI, diffusion-weighted imaging; FLAIR, fluid-attenuated inversion recovery. Source: Geschwind (2011). Reproduced with permission from Elsevier.

Figure 9.17 Times series of observed vCJD cases in the United Kingdom by genotype and presumed transmission route. Bar graph depicting number of deaths from vCJD per year in the United Kingdom through 2009. Bars refer to codon 129 polymorphism of decedent and their method of infection, primary, through consumption of BSE, or blood, through blood transfusion. Three persons, all codon 129 MM, died from vCJD from blood transfusion (black bars). One probable vCJD subject who died in 2009 (lighter bar) was codon 129MV and had primary infection. The number of deaths from vCJD has been relatively stable over the past five years. but it is not clear whether there will be another rise in the number of cases. Source: Garske and Ghani (2010). Reproduced with permission from Public Library of Science.

Figure 9.18 Map of the distribution of CWD in North America. Darkest areas denotes areas where wild populations have been infected. Medium dark denotes states and provinces with captive herds contaminated with CWD. Reproduced from Chronic Wasting Disease Alliance (www.cwd-info.org) with permission.

Figure 9.20 Midsagittal MRIs taken 5 years apart in a patient with Alzheimer’s disease who subsequently developed symptoms of NPH. Note the expansion of ventricles without a commensurate increase in sulcal markings, and the apparent narrowing of sulci at the parietal convexity. (a) Initial presentation of AD. (b) Five years later, coincident with onset of NPH symptoms.

Chapter 12

Figure 12.1 Striatal hand deformity.

Figure 12.2 Foot dystonia.

Figure 12.3 Bent spine deformity.xs

Figure 12.4 Camptocormia.

Figure 12.5 Treatment algorithm in PD.

Figure 12.6 Acclerometry of tremor showing sinusoidal oscillations.

Figure 12.7 Archimedes spiral in a patient with ET.

Figure 12.8 (a) The variable, mostly low-frequency spectral peaks seen on accelerometry of the leg during orthostatic tremor. (b) The narrow 17 Hz spectral peak seen on EMG of the anterior tibialis during orthostatic tremor.

Figure 12.9 Patient with PSP with axial hypertonia and retrocollis.

Figure 12.10 Patient with PSP with the procerus sign, or worried look.

Figure 12.11 Gross neuropathologic findings in a PSP patient showing moderate gyral atrophy of the posterior frontal lobes, paracentral gyrus, and mild to moderate atrophy of the mesial temporal lobes. (a) Left convexity; (b) right convexity; (c) superior view. Courtesy of Dr. Thomas Beach.

Figure 12.12 Gallyas staining of the substantia nigra in a patient with PSP showing neurofibrillary tangles (NFTs). Courtesy of Dr. Thomas Beach.

Figure 12.13 Gallyas staining of the putamen in a patient with PSP showing a tufted astrocyte on microscopy. Courtesy of Dr. Thomas Beach.

Figure 12.14 Gallyas staining of the frontal cortex in a patient with PSP showing coiled body on microscopy. Courtesy of Dr. Thomas Beach.

Figure 12.15 Cranial magnetic resonance imaging (MRI) showing midbrain atrophy in a patient with PSP. (a) Axial MRI showing atrophy of the midbrain. (b) Sagittal MRI showing atrophy of the midbrain with the penguin silhouette sign. (c) Magnified view of the penguin silhouette sign on sagittal MRI.

Chapter 16

Figure 16.1 Dix–Hallpike test for localization of vertigo detects most cases of benign paroxysmal positional vertigo related to the posterior semicircular canal.

Figure 16.2 Pagnini–McClure maneuver for evoking horizontal canal benign paroxysmal positional vertigo is a supine head-turn maneuver.

Figure 16.3 Canalolith repositioning maneuver; a modification of the Epley maneuver is used for treatment of posterior canal benign paroxysmal positional vertigo.

Figure 16.4 Semont liberatory maneuver is equally effective as Epley for posterior canal benign paroxysmal positional vertigo.

Chapter 18

Figure 18.1 Herpes simplex encephalitis. Axial T2-weighted image showing hyperintense signal abnormality in the left mesial temporal and basal frontal regions (a). Axial T1-weighted image with gadolinium showing hypointense signal abnormality with faint contrast enhancement in the same regions (b). Courtesy of Dr. John Hesselink, MD, Department of Radiology, University of California, San Diego.

Figure 18.2 Bacterial brain abscess. Axial T1-weighted without (a) and with (b) gadolinium images shows a ring-enhancing lesion in the left parieto-occipital region, with surrounding hypointensity and mass effect. T2-weighted image shows more extensive surrounding hyperintense signal abnormalities reflecting edema (c). Diffusion-weighted image (d) shows a hyperintense signal and the ADC map (e), a hypointense signal indicating restricted diffusion. Reproduced from Bradley et al. (2008), with permission from Elsevier.

Chapter 20

Figure 20.1 Medications capable of inducing headache, independent of analgesic overuse.

Chapter 22

Figure 22.1 Axial CT scan of the head demonstrating mixed-density, chronic subdural hematoma (SDH). There is layering of hemosiderin (arrow), effacement of the lateral ventricles, effacement of the sulcal–gyral pattern, and significant midline shift. © Barrow Neurological Institute.

Figure 22.2 Axial CT scans of the head showing evolution and liquefaction of an acute chronic subdural hematomas (SDHs) 1 week (a) and 3 weeks (b) after the initial injury. © Barrow Neurological Institute.

Figure 22.3 Multiple CT scans of a 57-year-old woman with Fisher 3 subarachnoid hemorrhage (SAH) secondary to rupture of a 6 mm, right-sided middle cerebral artery (MCA) aneurysm. (a) Axial CT slice shows SAH, acute hematoma within the right sylvian fissure, and right-to-left midline shift. An external ventricular drain is in place. (b) Axial and (c) coronal CT angiogram slices show an MCA bifurcation aneurysm (arrow) within a focus of SAH. (d) Coronal CT angiogram slice demonstrating clip occlusion of the aneurysm via ipsilateral pterional craniotomy. © Barrow Neurological Institute.

Figure 22.4 Multiple angiographic images of a 65-year-old woman with an 11 mm, unruptured, right-sided V4 aneurysm. (a) Oblique view demonstrating a wide-necked, irregular aneurysm. The aneurysm arises directly from V4, at about the level of the exit (arrow) of the ipsilateral posterior inferior cerebellar artery (PICA). There is atherosclerotic dolichoectasia present in the ipsilateral proximal V4 as well. (b) Intraoperative roadmap view demonstrating dual microcatheter technique. One catheter deploys an inflatable balloon (arrow) as a buttress across the aneurysm neck, while a second catheter deploys coils into the aneurysm. (c) Unsubtracted lateral view demonstrating partial coil occlusion of the aneurysm with residual at the neck. Final (d) lateral and (e) Townes views of the aneurysm showing complete coil embolization and preservation of ipsilateral PICA. © Barrow Neurological Institute.

Figure 22.5 CT angiogram of the neck in an asymptomatic patient shows severe calcified stenosis of the right ICA bifurcation in (a) sagittal (arrow) and (b) axial planes (arrow). CT angiogram of the neck is repeated after a right-sided carotid endarterectomy (CEA) confirms restoration of flow in (c) sagittal and (d) axial planes.

© Barrow Neurological Institute.

Figure 22.6 (a) Axial CT angiogram of the head demonstrating contrast block in the right distal M1 segment in a patient with acute onset of left-sided weakness (arrow). (b) Noncontrast CT scan of head obtained hours later demonstrates edema within the right middle cerebral artery (MCA) territory suggestive of infarction, as well as midline shift and ventricular effacement. (c) A decompressive hemicraniectomy was performed to mitigate brain shift and prevent herniation. © Barrow Neurological Institute.

Figure 22.7 (a) Axial CT scan of the head showing typical ventriculomegaly out of proportion to volume loss in a patient with normal pressure hydrocephalus (NPH). (b) Ventriculoperitoneal shunting can use either a right frontal or right parietal approach. (c) Bone windows demonstrate intraventricular drainage sites (black arrow) and flow-regulating valve (white arrow). © Barrow Neurological Institute.

Figure 22.8 (a) Sagittal T1-weighted MRI with gadolinium and (b) axial T2-weighted MRI of the brain demonstrate a large right frontal dural-based tumor consistent with a meningioma. The T2-weighted image also shows a large component of surrounding vasogenic edema, visible as a bright signal within the white matter. © Barrow Neurological Institute.

Figure 22.9 Axial FLAIR MRI of the brain demonstrating profound postradiation changes in a patient who previously underwent both IMRT and stereotactic radiotherapy for cerebral metastases from breast carcinoma. © Barrow Neurological Institute.

Figure 22.10 The classification system of Anderson and D’Alonzo. Type I: Fracture through the tip, above the transverse ligament. Rare; represents less than 5% of cases. Type II: Fracture through the base of the neck. Most common; occurs in >60% of cases. Type III: Fracture through the body of C2. Occurs in 30% of cases. © Barrow Neurological Institute.

Figure 22.11 (a) CT of cervical spine, sagittal view, demonstrating a Type II fracture through the dens with posterior displacement. (b) MRI of cervical spine, gradient echo sequence, axial view, demonstrating the transverse atlantal ligament (TAL). It appears as a homogenous, thick, low-signal intensity structure (arrow) that extends between the medial portions of the lateral masses of C1. © Barrow Neurological Institute.

Figure 22.12 Schematic of a Type II odontoid fracture repaired through anterior odontoid screw placement. © Barrow Neurological Institute.

Figure 22.13 Various constructs for posterior fixation. (a) C1–2 interspinous wiring. (b) C1–2 transarticular fixation with wiring. (c) C1 lateral mass–C2 pars/pedicle screw fixation. © Barrow Neurological Institute.

Figure 22.14 (a) CT of the thoracic spine, sagittal view. T7 compression fracture with loss of height. (b) MRI, STIR sequence, sagittal view. T7 compression fracture. STIR demonstrates edema within the vertebral body, suggesting an acute fracture. © Barrow Neurological Institute.

Figure 22.15 (a) AP and (b) lateral fluoroscopic views during L1 vertebroplasty. The needle has been introduced through the right pedicle into the vertebral body for injection of the cement. © Barrow Neurological Institute.

Figure 22.16 Lateral fluoroscopic view demonstrating anterior leakage of cement after L4 vertebroplasty. © Barrow Neurological Institute.

Figure 22.17 Schematic of the trigeminal nerve and its three divisions, V1, V2, and V3, and their respective sensory territories. Ophthalmic (blue V1); maxillary (red V2); mandibular (pink V3). © Barrow Neurological Institute.

Figure 22.18 For the percutaneous procedures, a spinal needle or cannula is introduced through the cheek using standard landmarks: 2.5 cm lateral to the angle of the lip, 3 cm anterior to the external auditory meatus, and just below the medial aspect of the pupil. When the foramen ovale is engaged, the patient usually winces, and the surgeon can feel the cannula enter the foramen. © Barrow Neurological Institute.

Figure 22.19 (a) Axial and (b) coronal MRIs of the brain delineate the location (circle) of the trigeminal nerve entry zone at the level of the pons. © Barrow Neurological Institute.

Figure 22.20 Left retrosigmoid craniotomy performed at the junction of the transverse and sigmoid sinuses. © Barrow Neurological Institute.

Figure 22.21 Left retrosigmoid approach. View of neurovascular structures after the dura has been opened. Once the compressive vessel is identified, a Teflon pledget is placed between the nerve and offending vessel to achieve decompression. TS, transverse sinus; SS, sigmoid sinus; SCA, superior cerebellar artery; AICA, anterior inferior cerebellar artery. © Barrow Neurological Institute.

Figure 22.22 Patient with head secured in Leksell stereotactic head frame/base ring and localizer. © Barrow Neurological Institute.

Figure 22.23 The deep brain stimulation (DBS) lead is inserted into position using the Leksell stereotactic head frame and the preoperatively determined coordinates. The final position is confirmed using microelectrode recordings and intraoperative patient assessment. © Barrow Neurological Institute.

Figure 22.24 Schematic of the DBS system, including the intracranial stimulation lead, connector cable, and internal pulse generator. © Barrow Neurological Institute.

Figure 22.25 Schematic of the commonly used targets for DBS, including the globus pallidus interna, subthalamic nucleus, and ventral intermediate nucleus of the thalamus and adjacent structures. © Barrow Neurological Institute.

Chapter 23

Figure 23.1 Changes from baseline in mean ADAS-cog score in studies of galantamine, donepezil, tacrine, and rivastigmine. Positive changes from baseline on the MMSE indicate improvement; negative values indicate deterioration. Data based on various randomized clinical trials (RCTs) conducted through 2004–2010 after applying the CONSORT quality criteria.

Figure 23.2 Existing dementia treatments show effectiveness in a meta-analysis of multiple treatments in mild cognitive impairment and Alzheimer’s dementia, using clinical trials meeting the CONSORT 2010 quality criteria (CIBIC).

Figure 23.3 (a) AN1792 phase 2 study neuropsychological test battery (NTB) results showed an improvement on the nine-component NTB composite after 1 year in antibody responders, compared to the placebo group. Data from Gilman et al. (2005). (b) AN1792 follow-up study after approximately 4.5 years found that patients initially classified as antibody responders in the AN1792 phase 2 trial had less decline in activities of daily living as determined by the Disability Assessment for Dementia (DAD), compared with placebo-treated patients. Data from Vellas et al. (2009).

Figure 23.4 Bapineuzumab phase 2 exploratory analyses for four combined dose cohorts in (a) the modified intent-to-treat (mITT) and (b) the completer populations. Figure shows estimated mean change from baseline over time on Alzheimer’s Disease Assessment Scale–Cognitive subscale (ADAS-cog). Error bars represent one standard error. A positive change from baseline represents improvement. The p values are not adjusted for multiple comparisons. Source: Salloway et al. (2009). Reproduced with permission of Lippincott Williams & Wilkins.

Figure 23.5 One-year change from baseline in CSF phospho-tau (pg/mL) in bapineuzumab- and placebo-treated groups from bapineuzumab phase 2 clinical trial 201. Graph shows mean change (+/− SE) and p value from analysis of covariance model. Source: Salloway et al. (2009). Reproduced with permission of Lippincott Williams & Wilkins.

Figure 23.6 Estimated change from baseline over time in mean ¹¹C-PIB PET for bapineuzumab- and placebo-treated groups. Data shown are least squares means and 95% CIs. Difference between patients in the placebo group and those in the bapineuzumab group at week 78 = −0.24 (p = 0.003). PiB = Pittsburgh compound B. Source: Rinne et al. (2010). Reproduced with permission from Elsevier.

Figure 23.7¹¹C-PIB PET images in two bapineuzumab-treated (a, b) and two placebo-treated (c, d) patients. Average ¹¹C-PIB PET changes from baseline to week 78 are shown at the top center of each panel for each patient (a–d). The scale bar shows the PiB uptake ratios relative to the cerebellum. Source: Rinne et al. (2010). Reproduced with permission from Elsevier.

Figure 23.8 MRI scans from a 69-year-old woman with vasogenic edema (VE) after treatment with bapineuzumab 1.0 mg/kg IV. She remained asymptomatic despite the appearance of multiple areas of VE evident on the MRI. The VE was apparent on MRI by 7 weeks after her first infusion and resolved by 19 weeks. The patient was redosed at 0.5 mg/kg of bapineuzumab IV and followed for more than 2 years without recurrence of VE. Source: Salloway et al. (2009). Reproduced with permission of Lippincott Williams & Wilkins.

Chapter 26

Figure 26.1 Blue jay.

Figure 26.2 Three birds.

Figure 26.3 Sunset in Kauai.

Figure 26.4 Yoshida palm.

Figure 26.5 Blue collage, a late-stage Alzheimer’s watercolor of Lester Potts, depicting his father’s hat, shoes and saw.

Figure 26.6 Cabin by the lake.

Figure 26.7 Dad’s barn.

Figure 26.8 Yoshida beach sunset.

Chapter 28

Figure 28.1 Brain region examined using MRI, and graphs demonstrating 1-year effects of aerobic exercise versus a stretching control in cognitively healthy older adults (n = 120). (a) Example of hippocampus segmentation and graphs demonstrating an increase in hippocampus volume for the aerobic exercise group and a decrease in volume for the stretching control group. The Time by Group interaction was significant (p < 0.001) for both left and right regions. (b) Example of caudate nucleus segmentation and graphs demonstrating the changes in volume for both groups. Although the exercise group showed an attenuation of decline, this did not reach significance (both p > 0.10). (c) Example of thalamus segmentation and graph demonstrating the change in volume for both groups. None of the changes were significant for the thalamus. Error bars represent SEM. Source: Erickson et al. (2011). Reproduced with permission of National Academy of Sciences.

Figure 28.2 Means (SEM) representing improvements over baseline for adults with mild cognitive impairment completing 6 months of aerobic exercise versus stretching (n = 29) on tests of executive function, expressed as residual scores, including (a) Symbol–digit modalities test (number correct in 120 s), (b) Verbal fluency by letter and by category, (c) Stroop color word interference test (computer administered), voice onset latencies (ms) to interference stimuli, and (d) Trails B, time to complete the task (s, log transformed). Source: Baker et al. (2010b). Reproduced with permission of American Medical Association.

Figure 28.3 Midsagittal slice showing corpus callosum subsegmented (a) and 6-month cognitive training-induced improvements over baseline in genu (likely connecting prefrontal regions) in white matter microstructure, as measured by mean free diffusion of water (b) and directional rate (anisotropy) of water diffusion (c) for younger and older adults (n = 32). *units of measurement for Mean Diffusivity. Source: Lovden et al. (2010). Reproduced with permission of Elsevier.

Chapter 29

Figure 29.1 Multifactorial model of driving impairment in older drivers. AD, Alzheimer’s disease. Source: Ott & Daiello (2010). Reproduced with permission of Future Medicine Ltd.

Figure 29.2 Approach to evaluating older adults with cognitive impairment or dementia. Source: Carr and Ott (2010). Reproduced with permission of American Medical Association.

Chapter 30

Figure 30.1 Iceberg table. Source: NEAIS study, pp. 2–4; www.ncea.aoa.gov/Main_Site/Library/Statistics_Research/National_Incident.aspx.

About the Editors

Anil K. Nair, MD, is the director of TheAlzCenter.org and chief of neurology at Quincy Medical Center. He is also the site director for clinical trials in neurology. He completed his fellowship from Mayo Clinic, Rochester, MN, and his neurology residency at the Cleveland Clinic and Temple University after graduation from JIPMER, Pondicherry, India. His interest area is early and preclinical detection, prevention, and treatment of Alzheimer’s dementia, and other neurocognitive disorders and dementias.

Dr. Nair oversees the clinical and research facility called TheAlzCenter.org (The Alzheimer’s Center) serving the south shore of Boston. The center aims to advance the field of geriatric neurology and reduce the costs of debilitating diseases such as Alzheimer’s disease and other related dementias. In addition to providing preventive, diagnostic, and therapeutic services to patients with neurodegenerative and related diseases, Dr. Nair runs clinical trials in multiple indications, primarily in Alzheimer’s disease. He is dedicated to providing healthcare and referral services of the highest quality and is committed to building partnerships that increase the independence and quality of life for patients with dementia.

Dr. Nair is also an investigator for the stroke and memory project at the Framingham Heart Study, which aims to identify the risk factors involved in such diseases as Alzheimer’s disease and related dementias.

Marwan N. Sabbagh, MD, FAAN, is a board-certified neurologist and geriatric neurologist. As the director of the Banner Sun Health Research Institute, Dr. Sabbagh has dedicated his entire career to finding a cure for Alzheimer’s and other age-related neurodegenerative diseases.

Dr. Sabbagh is a leading investigator for many prominent national Alzheimer’s prevention and treatment trials. He is senior editor for Journal of Alzheimer’s Disease, BMC Neurology, and Clinical Neurology News, and has authored and coauthored more than 200 medical and scientific chapters, reviews, original research articles, and abstracts on Alzheimer’s research. Dr. Sabbagh has also authored The Alzheimer’s Answer—the book’s foreword was written by Justice Sandra Day O’Connor—and edited Palliative Care for Advanced Alzheimer’s and Dementia: Guidelines and Standards for Evidence Based Care and coauthored The Alzheimer’s Prevention Cookbook: Recipes to Boost Brain Health (RandomHouse/TenSpeed, 2012).

Dr. Sabbagh is research professor in the Department of Neurology, University of Arizona College of Medicine–Phoenix. He is also an adjunct professor at Midwestern University and Arizona State University. He earned his undergraduate degree from the University of California Berkeley and his medical degree from the University of Arizona in Tucson. He received his internship at the Banner Good Samaritan Regional Medical Center in Phoenix, AZ, and his residency training in neurology at Baylor College of Medicine in Houston, TX. He completed his fellowship in geriatric neurology and dementia at the UCSD School of Medicine.

List of Contributors

Khalil Amir MD

Department of Neurology

Cedars-Sinai Medical Centre

Los Angeles, CA, USA

Liana G. Apostolova MD, MS

Department of Neurology

David Geffen School of Medicine

University of California

Los Angeles, CA, USA

Sanford Auerbach MD

Departments of Neurology

Psychiatry and Behavioral Neurosciences

Boston University School of Medicine

Boston, MA, USA

Geoffrey S. Baird MD

Departments of Laboratory Medicine and Pathology

University of Washington

Seattle, WA, USA

Laura D. Baker PhD

Department of Medicine - Geriatrics

Wake Forest School of Medicine

Winston-Salem, NC, USA

Clive Ballard MBChB MMedSci MRCPsych MD

Wolfson Centre for Age-Related Diseases

King’s College London

London, UK

Ronald Black MD

Chief Medical Officer

Probiodrug AG

Halle, Germany

Andrea M. Cevasco PhD, MT-BC

School of Music

College of Arts and Sciences

University of Alabama

Tuscaloosa, AL, USA

Brenna A. Cholerton PhD

Department of Psychiatry and Behavioral Science

University of Washington School of Medicine

and Geriatric Research, Education, and Clinical Center

Veterans Affairs Puget Sound Health Care System

Seattle, WA, USA

Helena C. Chui MD

Department of Neurology

Keck School of Medicine

University of Southern California

Los Angeles, CA, USA

Donald J. Connor PhD, PhD

Independent Practice

Consultant in Clinical Trials

San Diego, CA, USA

David Croteau MD

Department of Neurosciences and

HIV Neurobehavioral Research Center

University of California

San Diego, CA, USA

Rohit R. Das MD, MPH

Indiana University School of Medicine

Indianapolis, IN, USA

Salih Demirhan MD

Marmara University School of Medicine

Istanbul, Turkey

Alexander Drzezga MD

Department of Nuclear Medicine

University Hospital of Cologne

Cologne, Germany

Ranjan Duara MD, FAAN

Wien Center for Alzheimer’s Disease and

Memory Disorders Mount Sinai Medical Center

Miami Beach;

Department of Neurology

Herbert Wertheim College of Medicine

Florida International University, Miami

and University of Florida College of Medicine

University of Florida

Gainesville, FL, USA

Angel C. Duncan MA-MFT, ATR

Cognitive Dynamics Foundation

Neuropsychiatric Research Center of

Southwest Florida

Albertus Magnus College

American Art Therapy Association

Fort Myers, FL, USA

Ronald Ellis MD, PhD

Department of Neurosciences and

HIV Neurobehavioral Research Center

University of California

San Diego, CA, USA

Virgilio Gerald H. Evidente MD

Movement Disorders Center of Arizona

Ironwood Square Drive

Scottsdale, AZ, USA

Martin R. Farlow MD

Department of Neurology

Indiana University

Indianapolis, IN, USA

Robert Fekete MD

Department of Neurology

New York Medical College

Valhalla, NY, USA

Terry D. Fife MD, FAAN

Barrow Neurological Institute

and Department of Neurology

University of Arizona College of Medicine

Phoenix, AZ, USA

Glenn Finney MD

Department of Neurology

McKnight Brain Institute

Gainesville, FL, USA

Adam S. Fleisher MD, MAS

Banner Alzheimer’s Institute

Department of Neurosciences

University of California

San Diego, CA, USA

David Fusco MD

Division of Neurological Surgery

Barrow Neurological Institute

St. Joseph’s Hospital and Medical Center

Phoenix, AZ, USA

James E. Galvin MD, MPH

Department of Neurology

and Department of Psychiatry

New York University Langone Medical Center

New York, NY, USA

Rasha Germain MD

Division of Neurological Surgery

Barrow Neurological Institute

St. Joseph’s Hospital and Medical Center

Phoenix, AZ, USA

Michael D. Geschwind MD, PhD

Memory and Aging Center

Department of Neurology

University of California

San Francisco, CA, USA

Clifton Gooch MD, FAAN

Department of Neurology

University of South Florida College of Medicine

Tampa, FL, USA

Michael Grundman MD, MPH

President, Global R&D Partners, LLC

San Diego, CA, USA

Yian Gu PhD

Taub Institute for Research on Alzheimer’s Disease and

the Aging Brain

Columbia University Medical Center

New York, NY, USA

Katrina Gwinn MD

National Institute of Neurological Disorders and Stroke

National Institutes of Health

Bethesda, MD, USA

Anne D. Halli-Tierney MD

Warren Alpert Medical School of Brown University

Rhode Island Hospital

Providence, RI, USA

Maya L. Henry PhD

Department of Communication Sciences and Disorders

University of Texas at Austin and Memory

and Aging Center

Department of Neurology

University of California

San Francisco, CA, USA

Anna Hohler MD

Department of Neurology

Boston University School of Medicine

Boston, MA, USA

Suzi Hong PhD

Department of Psychiatry

School of Medicine

University of California

San Diego, CA, USA

Sandra A. Jacobson MD

University of Arizona College of Medicine-Phoenix

Banner Sun Health Research Institute and

Cleo Roberts Center for Clinical Research

Sun City, AZ, USA

Joseph Jankovic MD

Parkinson’s Disease Center and Movement

Disorders Clinic

Department of Neurology

Baylor College of Medicine

Houston, TX, USA

Gene G. Kinney PhD

Chief Scientific Officer

Prothena Biosciences, Inc.

South San Francisco, CA, USA

Douglas J. Lanska MD, MS, MSPH, FAAN

Neurology Service

Veterans Affairs Medical Center

Great Lakes Health Care System

Tomah, WI, USA

David V. Lardizabal MD

Epilepsy Program and Intraoperative Monitoring

University of Missouri

Columbia, MO, USA

Alan Lerner MD

Department of Neurology

Case Western Reserve University School of Medicine

Cleveland, OH, USA

Joseph Locala MD

Department of Psychiatry

Case Western Reserve University School of Medicine

Cleveland, OH, USA

David A. Loewenstein PhD, ABPP

Department of Psychiatry and Behavioral Sciences

Miller School of Medicine

University of Miami

Miami, FL, USA

Patrick Lyden MD

Department of Neurology

Cedars-Sinai Medical Center

Los Angeles, CA, USA

Gary A. Martin PhD

Integrated Geriatric Behavioral Health Associates

Scottsdale, AZ, USA

Brian McGeeney MD

Department of Neurology

Boston University School of Medicine

Boston, MA, USA

Bruce L. Miller MD

Memory and Aging Center

University of California

San Francisco, CA, USA

Thomas J. Montine MD

Departments of Pathology and Neurological Surgery

University of Washington

Seattle, WA, USA

Anil K. Nair MD

Clinic for Cognitive Disorders and Alzheimer’s Disease Center

Quincy Medical Center

Quincy, MA, USA

Peter Nakaji MD

Division of Neurological Surgery

Barrow Neurological Institute

St. Joseph’s Hospital and Medical Center

Phoenix, AZ, USA

Marc A. Norman PhD, ABPP

Department of Psychiatry

University of California

San Diego, CA, USA

Brian R. Ott MD

Warren Alpert Medical School of Brown University

and The Alzheimer’s Disease and Memory Disorders Center

Rhode Island Hospital

Providence, RI, USA

Stefani Parrisbalogun MD

Rawson-Neal Psychiatric Hospital

Las Vegas, NV, USA

David Perry MD

Memory and Aging Center

Department of Neurology

School of Medicine

University of California

San Francisco, USA

Daniel C. Potts MD

Cognitive Dynamics Foundation

Veterans Affairs Medical Center

The University of Alabama

Tuscaloosa, AL, USA

Carol A. Prickett PhD, MT-BC

School of Music

College of Arts and Sciences

University of Alabama

Tuscaloosa, AL, USA

John Ranseen PhD

Department of Psychiatry

University of Kentucky College of Medicine

Lexington, KY, USA

Steven Z. Rapcsak MD

Department of Neurology

University of Arizona

Neurology Section

Southern Arizona VA Health Care System

Tucson, AZ, USA

Norman R. Relkin MD, PhD

Memory Disorders Program

Department of Neurology

and Brain Mind Research Institute

Weill Cornell Medical College

New York, NY, USA

Miriam Joscelyn Rodriguez PhD

Wien Center for Alzheimer’s Disease and Memory Disorders

Mount Sinai Medical Center

Miami Beach, FL, USA

Ashley Roque MD

Boston University School of Medicine

Boston, MA, USA

Howard Rosen MD

Memory and Aging Center

Department of Neurology

School of Medicine

University of California

San Francisco, CA, USA

Marwan N. Sabbagh MD, FAAN

Banner Sun Health Research Institute

Sun City, AZ, USA

Nikolaos Scarmeas MD, MSc

Taub Institute, Sergievsky Center

Department of Neurology

Columbia University

New York, NY, USA

and Department of Social Medicine,

Psychiatry and Neurology

National and Kapodistrian University of Athens

Athens, Greece

Julie A. Schneider MD, MS

Rush Alzheimer’s Disease Center

Department of Pathology and Department of

Neurological Sciences

Rush University Medical Center

Chicago, IL, USA

Elliott Schulman MD

Lankenau Institute for Medical Research

Lankenau Medical Center

Wynnewood, PA, USA

Freddi Segal-Gidan PA, PhD

Department of Neurology

Keck School of Medicine

University of Southern California

Los Angeles, CA, USA

Holly Shill MD

Banner Sun Health Research Institute

Sun City, AZ, USA

Jasmeet Singh MD, MPHA

Alzheimer’s Disease Center

Quincy Medical Center

Quincy, MA, USA

Jeannine Skinner PhD

Department of Neurology

Vanderbilt School of Medicine

Nashville, TN

Yaakov Stern PhD

Cognitive Neuroscience Division

Department of Neurology Columbia

University Medical Center

New York, NY, USA

Papan Thaipisuttikul MD

Department of Neurology

and Department of Psychiatry

New York University Langone Medical Center

New York, NY, USA

Ilana Tidus BSc

Department of Neurology

Cedars-Sinai Medical Centre

Los Angeles, CA, USA

Adrienne M. Tucker PhD

Cognitive Science Center Amsterdam

University of Amsterdam

Amsterdam, The Netherlands

Heber Varela MD

Department of Neurology

University of South Florida College of Medicine

Tampa, FL, USA

Joe Verghese MD

Department of Neurology and Medicine

Albert Einstein College of Medicine

Bronx, NY, USA

Douglas F. Watt PhD

Department of Neuropsychology

Cambridge City Hospital, Harvard Medical School and

Alzheimer’s Disease Center/Clinic for Cognitive Disorders

Quincy Medical Center

Quincy, MA, USA

Stephen M. Wilson PhD

Department of Speech

Language and Hearing Sciences

University of Arizona

Tucson, AZ, USA

Katherine Wong BA

Memory and Aging Center

Department of Neurology

University of California

San Francisco, CA, USA

Chunhui Yang MD, PhD

Rush Alzheimer’s Disease Center

and Department of Pathology

Rush University Medical Center

Chicago, IL, USA

Eric Yuen MD

Clinical Development

Janssen Alzheimer Immunotherapy Research & Development

South San Francisco, CA, USA

Jessica Zwerling MD

Department of Neurology

Albert Einstein College of Medicine

Bronx, NY, USA

Preface

As scientific knowledge about the nervous system and neurological diseases explodes at an exponential rate, the ability to master all aspects of neurology becomes increasingly difficult. Because of this, neurology as a profession is fragmenting much the same way that internal medicine has, with many subspecialties of neurology emerging and establishing themselves as board-recognized subspecialties by the American Academy of Neurology and the United Council of Neurological Subspecialties (UCNS). Currently recognized subspecialties of the UCNS include autonomic disorders, behavioral neurology and neuropsychiatry, clinical neuromuscular disease, headache medicine, neural repair and rehabilitation, neurocritical care, neuroimaging, and neuro-oncology. Other recognized subspecialties include epilepsy, stroke, and movement disorders.

For the past several years, the American Academy of Neurology’s Geriatric Neurology section has been advocating strongly for the creation of a boarded, recognized subspecialty in geriatric neurology. This recommendation was approved by the AAN and adopted by the UCNS. Subsequently, the UCNS drafted a course outline for examination purposes, convened an examining committee that drafted the exam questions, and has since proctored three exam sessions. This book mirrors the new board subspecialty of geriatric neurology within the larger field of neurology. This project is written as a textbook for an emerging field of neurology and provides evidence-based scientific review of the current thinking in the field. The content will be clearly articulated and summarized.

Geriatric neurology is the field of neurology dedicated to age-related neurological diseases, including degenerative diseases (Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis), gait and balance disorders, neuropathies, stroke, and sleep disturbances. Geriatric neurology is emerging as a subspecialty of neurology. This emergence reflects the growing understanding that geriatric patients have different neurological conditions that require different diagnostic evaluations and ultimately different features. Geriatric neurology is not adult neurology redux. The field has similarities to geriatrics and the approach to the geriatric patient is, by definition, different. As such, clinical syndromes can have features in common with younger patients but the etiologies are frequently different. Additionally, many neurodegenerative diseases are prevalent in the aged but less so in general neurology.

This handbook is the summation of the field at present. It follows the UCNS examination outline to an extent in terms of topics covered. It covers all topics germane to geriatric neurology from disease-specific, neuroanatomical, diagnostic, and therapeutic perspectives. The good news is that we have made tremendous strides in understanding and managing the complications and challenges of diseases that are encompassed within geriatric neurology. We now understand the neurological changes that occur with age and the mechanisms that contribute to changes. We hope it will enhance practice skills and knowledge base for practitioners, residents, and students.

Anil K. Nair

Marwan N. Sabbagh

Acknowledgements

This work would not exist without the exhaustive efforts of our contributors, who are the venerable authorities in their respective fields. We would also like to thank our assistants who were tireless and patient throughout—Bonnie Tigner, Myste Havens, Deborah Nadler, Nicole Chan, Roshni Patel, Sheela Chandrashekar, Ardriane Hancock, Krystal Kan, and Vishakadutta Kumaraswamy. We would like to thank the publishing team at Wiley for their feedback, responsiveness, patience, and support.

Finally, we would like to thank our spouses and children who endured our many late nights staying up writing and editing.

Anil K. Nair

Marwan N. Sabbagh

Part 1

The Aging Brain in Neurology

Chapter 1

The Biology of Aging: Implications for Diseases of Aging and Health Care in the Twenty-First Century

Douglas F. Watt

Department of Neuropsychology Cambridge City Hospital, Harvard Medical School, and Alzheimer’s Center/Clinic for Cognitive Disorders, Quincy Medical Center, Quincy, MA, USA

Summary

Aging demographics, increasing penetration of diseases of aging, and the heightening expense of high technology health-care interventions are creating exploding costs that are becoming economically unsustainable.

Evolutionary theory suggests that aging is the fading out of adaptation once reproductive competence is achieved, and reflects the lack of selection for a sustained post-reproductive adaptation.

If extrinsic mortality is high in the natural environment, selection effects are less likely to promote organism maintenance for extended periods. Alternatively, aging is simply change of the organism over time, and is primarily under the control of the hypothalamic pituitary gonadotropin axis. Although traditionally viewed as opposing theories, these may be simply different perspectives on the same process.

Cellular and molecular theories attribute aging to a genetically modulated process, a consequence of