_{Published March 7, 2023}

Deposition of protein aggregates and neuronal loss are the likely cause of cognitive decline in neurodegenerative disorders. Protein aggregates such as amyloid and tau can be imaged by amyloid and tau PET, whereas neuronal loss can be revealed by MRI and FDG PET. The pattern of protein deposition and neuro­nal loss may be useful in identifying the type of dementia. Cere­brovascular disease and cerebral amyloid angiopathy can cause cognitive decline on their own, or they can worsen cognitive decline caused by other neurodegenerative disorders. Normal-pressure hydrocephalus (NPH), cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopa­thy (CADASIL) syndrome, Creutzfeldt-Jakob disease, and other conditions are additional important identifiable causes of cogni­tive decline on imaging.

Assessment of the mental function of an individual is done by evaluating the cognitive domains, including memory, attention, executive function, visuospatial function, language, and behavior [1]. Neurodegenerative disorders impair different aspects of these brain functions by affecting neuronal function, connectivity, and loss. Most of these diseases are characterized by accumulation of abnormal protein aggregates, which is theorized to result from dysfunction of the glymphatic system [1–3], abnormal protein processing, microglia-mediated inflammation, and dysregulated autophagy [4]. The neuronal dysfunction and subsequent neuronal loss caused by the accumulation of these protein aggregates can be identified by visual inspection or by quantification of cortical volumes or thickness, or they can be imaged by nuclear medicine techniques, such as FDG PET. The presence of certain abnormal protein deposits, such as amyloid and tau, can also be detected using PET ligands. Advanced MRI perfusion techniques such as arterial spin-labeling (ASL) can serve as a surrogate marker where hypoperfusion is indicative of underlying hypometabolism [5]. Early neuronal loss causes microstructural abnormalities in the white matter of the affected brain regions, which can be detected by quantitative diffusion MRI diffusion-tensor imaging metrics [6].

In this brief review, we will discuss the most common conditions that cause cognitive impairment and dementia.

Alzheimer Disease

Alzheimer disease (AD) is the most common form of dementia, accounting for up to 80% of the cases [1, 7, 8]. Although episodic memory and declarative memory are the most severely affected cognitive functions, patients with AD also have varying degrees of executive, language, and visuospatial function impairment [1, 7, 8]. The amyloid cascade hypothesis, which postulates that β-amyloid has a primary role in the pathophysiology, is the most widely accepted [9–12]. Deposition of tau neurofibrillary tangles, which occurs earliest in the medial temporal lobe structures, is another neuropathologic feature of AD. Tau deposition is more directly linked to neurodegeneration than is amyloid deposition, and the hippocampal and medial temporal volume loss in AD is an established structural biomarker of neuronal injury in AD [9, 12–15]. In terms of a biologic definition, amyloid biomarker positivity (Fig. 1) places an individual’s condition on the continuum of AD, but it is the positivity of both amyloid and tau markers that defines AD [9].

In typical AD, there is involvement of the medial temporal lobe and lateral temporoparietal cortex, precuneus, and lateral frontal lobe, which is manifested by loss of volume and hypometabolism [16]. The Scheltens scale is widely used for visual rating of hippocampal volume loss [17] (Fig. 2).

Fig. 2—Visual assessment of hippocampal atrophy performed using Scheltens scale.
A and B, Coronal T1-weighted MR images of view through hippocampus in patient with normal hippocampus (A) and in patient with mild hippocampal atrophy (B). Visual determination of hippocampal atrophy requires assessment of height of hippocampus, width of choroidal fissure, and width of temporal horn. Note near absence of CSF around hippocampus in patient with normal hippocampus (A) versus decreased hippocampal height and increased width of choroidal fissure and temporal horn in patient with mild hippocampal atrophy (B).

Hypometabolism of the involved structures is seen on FDG PET, which shows decreased activity in the lateral temporoparietal cortex, posterior cingulate cortex, precuneus, and medial temporal lobe (Fig. 3).

Fig. 3—FDG PET z-score maps of patient with Alzheimer disease. (Courtesy of Kleefisch C, Medical College of Wisconsin, Milwaukee, WI)
A–C, Note hypometabolism in temporoparietal (arrows, A), precuneus (white arrow, B), posterior cingulate (black arrow, B), and biparietal (arrows, C) regions.

Logopenic variant primary progressive aphasia (PPA) is the most common atypical presentation of early-onset AD, characterized by predominant language dysfunction. Impaired single-word retrieval and impaired repetition are the core features of logopenic variant PPA [18]. There is a high rate of amyloid and tau positivity [18]. Atrophy is centered at the left temporoparietal junction and the left inferior parietal and superior temporal regions, including the supramarginal and angular gyri, and is associated with concomitant hippocampal volume loss (Fig. 4).

FDG PET shows temporoparietal hypometabolism (left greater than right) [18].

Frontotemporal Lobar Degeneration

Frontotemporal lobar degeneration (FTLD) is a heterogeneous group of disor­ders that typically feature progressive dete­rioration of behavior or language and usu­ally are associated with neurodegeneration in the frontal and temporal lobes. FTLD is most prevalent among individuals 45–64 years old. FTLD includes six subtypes, with three predominant clinical syndromes defining these six subtypes. The most common subtype is a behavioral disorder known as behavioral variant frontotempo­ral degeneration. Language disorders asso­ciated with FTLD include semantic variant PPA and nonfluent or agrammatic variant PPA. Certain motor disorders included in the FTLD classification include progres­sive supranuclear palsy (PSP), corticobas­al degeneration (CBD), and motor neuron disease (MND) [1, 7, 8].

Behavioral variant frontotemporal de­generation is the most common form of FTLD and is characterized by the gradual onset and progression of changes in per­sonality, behavior, and executive function with relative sparing of memory and visuo­spatial functions (in contrast with AD). The frontal and temporal lobes are characteris­tically involved [7, 19, 20]. MRI shows atrophy with knife-edge gyri. On ASL and FDG PET, there is hypoperfusion and hy­pometabolism of the frontal and temporal lobes (Fig. 5) with relative sparing of the parietal lobes (in contrast with AD).

Amy­loid PET may also help differentiate FTD from AD, because FTD typically shows no or very little amyloid binding [7, 19–21].

Semantic variant PPA primarily pres­ents with anomia and single-word compre­hension deficits. Volume loss affects the ventral and lateral portions of the anterior temporal lobes (Fig. 6).

In most patients, the left hemisphere is predominantly af­fected, although bilateral involvement may be seen. Asymmetric hippocampal volume loss is commonly seen on the side where temporal lobe atrophy is present. Tar DNA-binding protein of 43 kilodaltons (TDP-43) proteinopathy is the most com­mon underlying neuropathology [22, 23].

Progressive nonfluent aphasia is another type of PPA on the spectrum of FTLD dis­orders and is associated with accumulation of tau proteins [24–27]. There is predomi­nant involvement of the left inferior frontal region, with additional involvement of the anterior insula, prefrontal regions, supple­mentary motor area, and anterosuperior left temporal lobe [24–27].

Amyotrophic lateral sclerosis (ALS) is part of the FTLD-MND spectrum, with cases primarily presenting with features of either FTD or ALS. Associated FTD is more common in bulbar-onset ALS than in limb-onset ALS, with involvement of the frontal and temporal lobes. Abnormal hyperinten­sity is noted along the corticospinal tracts on T2-weighted and FLAIR MRI, and sus­ceptibility-weighted imaging or gradient-re­called echo (GRE) MRI shows gyriform hy­pointensity along the motor cortexes [28].

PSP and CBD show mixed features of cognitive impairment and parkinsonism and an underlying tauopathy. Language symptoms, when present, are those of non­fluent or agrammatic variant PPA, which is another tauopathy. Due to the damage to the nigrostriatal dopamine pathway, 123I-FP-CIT (fluoropropyl-carbomethoxy-iodophenyl-tropane) SPECT may show ab­normal reduced uptake in the basal ganglia in PSP and CBD.

Characteristic volume loss is noted in the brainstem in PSP [19, 29], manifesting as the “hummingbird” appearance on midsagittal images. Although classically described with PSP, the hummingbird sign is subjective and is commonly seen with advanced brain volume loss developing from other causes. Quantitative evaluation, with a midbrain area of less than 70 mm2 on midsagittal images or an anteroposterior diameter of the midbrain of less than 17 mm on axial T2-weighted im­ages suggesting midbrain atrophy, could be useful [30, 31]. PSP also shows volume loss within the superior cerebellar peduncles.

CBD is rare and is characterized by uni­lateral or asymmetric signs of parkinsonian rigidity, myoclonus, and apraxia. Core clinical features are asymmetric progressive limb dystonia and alien limb phenomenon. The brain is atrophied asymmetrically in the perirolandic region, which is otherwise uncommon in primary neurodegenerative diseases. Other imaging features include unilateral putamen atrophy and increased hypointensity of the globus pallidi and the putamina on T2-weighted MRI and on SWI or GRE MRI. Associated unilateral cerebral peduncle atrophy may also be seen [32].

Dementia With Lewy Bodies

Dementia with Lewy bodies (DLB) is the second most common form of neuro­degenerative dementia in individuals older than 65 years old. Recurrent visual hallu­cinations, fluctuating cognition, rapid eye movement sleep behavior disorder, and motor parkinsonism are the core clinical features. DLB can be differentiated from AD by the relative absence of medial tem­poral lobe atrophy [33, 34] and by greater involvement of the posterior parietal and parietooccipital regions. Atrophy within the striatal structures and brainstem is also seen in DLB. ASL and FDG PET studies show hypometabolism in the posterior pa­rietal and occipital regions, with preserva­tion of normal uptake in the medial tem­poral lobe and posterior cingulate gyrus (the cingulate island sign of DLB). Iodine- 123-labeled FP-CIT SPECT, used for im­aging the dopaminergic pathway, may be useful in the workup of patients with DLB, who show decreased uptake of the tracer in the striatum, as seen in other parkinsonian diseases [33, 34].

Cerebral Amyloid Angiopathy

Deposition of amyloid-β in the media and adventitia of cerebral cortical and leptomeningeal vessels is the hallmark of cerebral amyloid angiopathy (CAA). The amyloid deposition weakens the vessel wall, leading to rupture and hemorrhage. On imaging, this manifests as a spectrum of foci of intraparenchymal lobar hemor­rhage, convexal subarachnoid hemorrhage, and cortical and subcortical microhemor­rhages. Areas of superficial siderosis are seen, indicative of prior subarachnoid hemorrhage. Subcortical white matter long-TR hyperintensities are typical of CAA differentiated from periventricular lesions seen in hypertensive cerebrovascu­lar disease [35].

Acute inflammatory CAA may be seen on a background of chronic changes, in as­sociation with rapidly progressive cognitive decline [36]. On imaging, inflammatory CAA is seen as solitary or multifocal areas of confluent white matter hyperintensity with or without mass effect or patchy areas of enhancement and is often centered around foci of microhemorrhage [36] (Fig. 7).

Normal Pressure Hydrocephalus

Primarily an idiopathic disease, NPH is characterized by progressive gait distur­bance, urinary urgency or incontinence, and cognitive impairment. NPH is largely a clin­ical diagnosis, with imaging playing a sup­portive role. Objective measurements such as the Evans ratio or callosal angle have a low accuracy for diagnosis. A dispropor­tionately enlarged subarachnoid space hy­drocephalus imaging pattern, when present, has been shown to have higher accuracy where ventriculomegaly is seen along with effacement of the sulci at the vertex and multifocal enlarged sulci. Hyperdynamism may be seen on CSF flow studies, character­ized by a streak of flow void through the ce­rebral aqueduct that is best seen on sagittal images. Radionuclide cisternography using 111In- or 99mTc-DTPA (diethylenetriamine­pentaacetic acid) may show abnormal tracer reflux into the lateral ventricles and lack of tracer activity over the convexities 24–48 hours after intrathecal injection. A high vol­ume (30–50 mL) of CSF lumbar puncture may show improved gait and cognitive test­ing. Improvement of gait disturbance after lumbar puncture has a high PPV for favor­able postintervention results [37].

Creutzfeldt-Jakob Disease

A fatal prion disease, CJD presents with rapidly progressive dementia, along with myoclonus, pyramidal, extrapyrami­dal, and cerebellar signs. CJD is mostly sporadic, but it can be familial, infectious (variant CJD), or iatrogenic. There is spon­giform degeneration and gliosis. The MRI sequence with the highest sensitivity and specificity is DWI, which shows the char­acteristic imaging finding of hyperinten­sity of the basal ganglia, thalami, and the cortical regions [38, 39] (Fig. 8).

Symmet­ric involvement of the posterior thalami (pulvinar sign) and the dorsomedial nuclei (hockey-stick sign) is common in vari­ant CJD but can also be seen in sporadic CJD. Bilateral but asymmetric involve­ment of the cortical areas is seen [38, 39]. Enhancement is uncommon. Definitive diagnosis may require brain biopsy. Death ensues in a few months.

Vascular Contributions to Cognitive Impairment and Dementia

Cerebrovascular small-vessel disease is a common complication of uncontrolled hypertension, which frequently affects the periventricular white matter seen as white matter hyperintensities on T2 FLAIR im­aging. Hypertensive arteriopathy, amyloid angiopathy, or genetic causes of cerebro­vascular disease (such as cerebral autoso­mal dominant arteriopathy with subcortical infarcts and leukoencephalopathy [CA­DASIL]) can cause cognitive impairment by interrupting brain networks traversing the affected white matter regions [40, 41]. The likelihood of vascular disease contrib­uting to cognitive dysfunction increases with increasing small-vessel disease and infarct burden.

CADASIL is the most common ge­netic cause of adult-onset cerebrovascular disease. Migraine with aura, stroke, and chronic presentations, such as cognitive de­cline and dementia, are the clinical features. Patients most frequently present in the 3rd decade of life, and most patients present by late middle age. When patients pres­ent earlier than the 3rd decade, subcortical FLAIR white matter hyperintensities are seen, which over the years progress to the characteristic confluent hyperintensities in the anterior temporal poles, superior frontal lobes, and the external capsules [42].

Deposition of protein aggregates and neuronal loss are the likely cause of cogni­tive decline in neurodegenerative disorders. Protein aggregates such as amyloid and tau can be imaged by amyloid and tau PET, whereas neuronal loss can be shown on MRI and FDG PET. The pattern of protein deposition and neuronal loss may be useful in identifying the type of dementia. Cere­brovascular disease and cerebral amyloid angiopathy can cause cognitive decline on their own or worsen cognitive decline due to other neurodegenerative disorders. NPH, CADASIL, CJD, and other conditions are additional important identifiable causes of cognitive decline on imaging.

We thank Christopher Kleefisch of the Medical College of Wisconsin for his con­tribution to the PET images.

References

1. Gliebus GP. Memory dysfunction. Continuum (Min­neap Minn) 2018; 24:727–744
2. Plog BA, Nedergaard M. The glymphatic system in central nervous system health and disease: past, present, and future. Annu Rev Pathol 2018; 13:379– 394
3. Zhang L, Chopp M, Jiang Q, Zhang Z. Role of the glymphatic system in ageing and diabetes melli­tus impaired cognitive function. Stroke Vasc Neurol 2019; 4:90–92
4. Guo F, Liu X, Cai H, Le W. Autophagy in neurode­generative diseases: pathogenesis and therapy. Brain Pathol 2018; 28:3–13
5. Alsop DC, Detre JA, Golay X, et al. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med 2015; 73:102–116
6. Shim G, Choi KY, Kim D, et al. Predicting neurocog­nitive function with hippocampal volumes and DTI metrics in patients with Alzheimer’s dementia and mild cognitive impairment. Brain Behav 2017; 7:e00766
7. Bhogal P, et al. The common dementias: a pictorial review. Eur Radiol 2013; 23:3405–3417
8. Tartaglia MC, Vitali P, Migliaccio R, Agosta F, Rosen H. Neuroimaging in Dementia. Continuum (Minneap Minn) 2010; 16:153–175
9. Jack CR Jr, Bennett DA, Blennow K, et al. NIA-AA research framework: toward a biological definition of Alzheimer’s disease. Alzheimers Dement 2018; 14:535–562
10. Dolci GAM, Damanti S, Scortihini V, et al. Al­zheimer’s disease diagnosis: discrepancy between clinical, neuroimaging, and cerebrospinal fluid biomarkers criteria in an Italian cohort of geriatric outpatients: a retrospective cross-sectional study. Front Med (Lausanne) 2017; 4:203
11. McKhann GM, Knopman DS, Chertkow H, et al. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging–Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 2011; 7:263–269
12. Jack CR Jr, Knopman DS, Jagust WJ, et al. Tracking pathophysiological processes in Alzheimer’s dis­ease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol 2013; 12:207–216
13. Burnham SC, Coloma PM, Li QX, et al. Application of the NIA-AA research framework: towards a bio­logical definition of Alzheimer’s disease using ce­rebrospinal fluid biomarkers in the AIBL study. J Prev Alzheimers Dis 2019; 6:248–255
14. Sperling RA, Aisen PS, Beckett LA, et al. Toward de­fining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging–Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 2011; 7:280–292
15. Fox NC, Schott JM. Imaging cerebral atrophy: nor­mal ageing to Alzheimer’s disease. Lancet 2004; 363:392–394
16. Ferreira D, Verhagen C, Hernández-Cabrera JA, et al. Distinct subtypes of Alzheimer’s disease based on patterns of brain atrophy: longitudinal trajecto­ries and clinical applications. Sci Rep 2017; 7:46263
17. Scheltens P, Leys D, Barkhof F, et al. Atrophy of medial temporal lobes on MRI in “probable” Al­zheimer’s disease and normal ageing: diagnostic value and neuropsychological correlates. J Neurol Neurosurg Psychiatry 1992; 55:967–972
18. Rohrer JD, Rossor MN, Warren JD. Alzheimer’s pa­thology in primary progressive aphasia. Neurobiol Aging 2012; 33:744–752
19. Agosta F, Galantucci S, Magnani G, et al. MRI sig­natures of the frontotemporal lobar degeneration continuum. Hum Brain Mapp 2015; 36:2602–2614
20. Irwin DJ, Cairns NJ, Grossman M, et al. Frontotem­poral lobar degeneration: defining phenotypic di­versity through personalized medicine. Acta Neu­ropathol 2015; 129:469–491
21. Meijboom R, Steketee RME, de Koning I, et al. Func­tional connectivity and microstructural white mat­ter changes in phenocopy frontotemporal demen­tia. Eur Radiol 2017; 27:1352–1360
22. Chen Y, Chen K, Ding J, et al. Brain network for the core deficits of semantic dementia: a neural net­work connectivity–behavior mapping study. Front Hum Neurosci 2017; 11:267
23. Joubert S, Vallet GT, Montembeault M, et al. Com­prehension of concrete and abstract words in se­mantic variant primary progressive aphasia and Al­zheimer’s disease: a behavioral and neuroimaging study. Brain Lang 2017; 170:93–102
24. Gorno-Tempini ML, Miller BL. Primary progressive aphasia as a model to study the neurobiology of language. Brain Lang 2013; 127:105
25. Gorno-Tempini ML, Brambati SM, Ginex V, et al. The logopenic/phonological variant of primary progressive aphasia. Neurology 2008; 71:1227–1234
26. Gorno-Tempini ML, Dronkers NF, Rankin KP, et al. Cognition and anatomy in three variants of prima­ry progressive aphasia. Ann Neurol 2004; 55:335– 346
27. Gorno-Tempini ML, Hillis AE, Weintraub S, et al. Classification of primary progressive aphasia and its variants. Neurology 2011; 76:1006–1014
28. Conte G, Sbaraini S, Morelli C, et al. A susceptibility-weighted imaging qualitative score of the motor cortex may be a useful tool for distinguishing clini­cal phenotypes in amyotrophic lateral sclerosis. Eur Radiol 2021; 31:9
29. Rohrer JD, Warren JD. Phenotypic signatures of ge­netic frontotemporal dementia. Curr Opin Neurol 2011; 24:542–549
30. Warmuth-Metz M, Naumann M, Csoti I, Solymosi L. Measurement of the midbrain diameter on routine magnetic resonance imaging: a simple and accu­rate method of differentiating between Parkinson disease and progressive supranuclear palsy. Arch Neurol 2001; 58:1076–1079
31. Oba H, Yagishita A, Terada H, et al. New and reli­able MRI diagnosis for supranuclear palsy. Neurol­ogy 2005; 64:2050–2055
32. Saeed U, Compagnone J, Aviv RI, et al. Imaging bio­markers in Parkinson’s disease and Parkinsonian syndromes: current and emerging concepts. Transl Neurodegener 2017; 6:8
33. Watson R, O’Brien JT, Barber R, Blamire AM. Pat­terns of gray matter atrophy in dementia with Lewy bodies: a voxel-based morphometry study. Int Psychogeriatr 2012; 24:532–543
34. Watson R, Colloby SJ, Blamire AM, O’Brien JT. Sub­cortical volume changes in dementia with Lewy bodies and Alzheimer’s disease: a comparison with healthy aging. Int Psychogeriatr 2016; 28:529–536
35. Wardlaw JM, et al. Neuroimaging standards for research into small vessel disease and its contri­bution to ageing and neurodegeneration. Lancet Neurol 2013; 12:822–838
36. Salvarani C, et al. Imaging findings of cerebral amy­loid angiopathy, Aβ-related angiitis (ABRA), and ce­rebral amyloid angiopathy-related inflammation: a single-institution 25-year experience. Medicine (Baltimore) 2016; 95:e3613
37. Graff-Radford NR. Normal pressure hydrocephalus. Neurol Clin 2007; 25:809–832
38. Kallenberg K, Schulz-Schaeffer WJ, Jastrow U, et al. Creutzfeldt-Jakob disease: comparative analysis of MR imaging sequences. AJNR 2006; 27:1459–1462
39. Tian HJ, Zhang JT, Lang SY, Wang XQ. MRI sequence findings in sporadic Creutzfeldt-Jakob disease. J Clin Neurosci 2010; 17:1378–1380
40. Koga H, Takashima Y, Murakawa R, Uchino A, Yu­zuriha T, Yao H. Cognitive consequences of mul­tiple lacunes and leukoaraiosis as vascular cogni­tive impairment in community-dwelling elderly individuals. J Stroke Cerebrovasc Dis 18:32–37
41. Sweeney MD, Montagne A, Sagare AP, et al. Vascular dysfunction: the disregarded partner of Alzheimer’s disease. Alzheimers Dement 2019; 15:158–167
42. Ferrante EA, Cudrici CD, Boehm M. CADASIL: new advances in basic science and clinical perspectives. Curr Opin Hematol 2019; 26:193–198