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Parkinson’s disease (PD) is a degenerative neurological disorder, the origin of which remains unclear. The efficacy of treatments is limited due to the small number of remaining neurons. Diffusion magnetic resonance imaging (MRI) has revolutionized clinical neuroimaging. This noninvasive and quantitative method gathers in vivo microstructural information to characterize pathological processes that modify nervous tissue integrity. The changes in signal intensity result from the motion of the water molecules; they can be quantified by diffusivity measures. Diffusion MRI has revealed “biomarkers” in several brain regions that could be useful for PD diagnosis. These regions include the olfactory tracts, putamen, white matter, superior cerebellar peduncles, middle cerebellar peduncle, pons, cerebellum, and substantia nigra. There are encouraging preliminary data that differentiate PD from atypical parkinsonian diseases based on these microstructural changes.
Faculty of Engineering, Department of Biomedical Engineering, Universidad ECCI, Bogotá, Colombia
Shengdong Nie
Institute of Medical Imaging and Engineering School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology USST, Shanghai, China
Juan Ramírez
Faculty of Engineering, Universidad Distrital Francisco José de Caldas, Bogotá, Colombia
*Address all correspondence to: g_milena@yahoo.com
1. Introduction
Parkinson’s disease (PD) was first described in 1817 by James Parkinson and is characterized by the selective loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) [1, 2, 3]. Although PD has been known for more than two centuries, its origin remains unclear. The motor symptoms in patients with PD appear when at least 50–80% of dopaminergic neurons have been lost in the substantia nigra (SN). For this reason the quantity of remaining neurons limits the efficacy of treatments. PD begins with a reduction in dopamine signaling from the SN to the basal ganglia, which causes a decrease in the neuronal excitation localized in the thalamus. This abnormal condition is reflected by the symptoms of bradykinesia (slow or difficult movements), rigidity, postural instability, resting tremor, and non-motor symptoms in conjunction with fatigue, reduced facial expressions, sleep and smell disturbances, depression, and cognitive decline [4].
Conventional magnetic resonance imaging (MRI) does not provide adequate contrast to study changes in the brain of patients with PD. Indeed, conventional 1.5 T T1- and T2-weighted sequences do not collect information for the SNpc. Hence, conventional MRI cannot detect structural lesions that cause PD and cannot differentiate PD from characteristic alterations of atypical parkinsonism diseases (APD), such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). Conventional MRI neuroimaging is not specifically recommended for routine diagnosis in clinical practice of the difficulty in PD [5].
Diffusion MRI is an evolution of conventional MRI and has the potential to differentiate between PD and APD. This ability includes identifying the principal changes in the SN and the lower part of the putamen/caudate complex, the location of most nigrostriatal dopaminergic neurons. Changes in these areas in patients with PD could provide valuable information to aid in the diagnosis and assess disease progression. Diffusion MRI involves two techniques: (1) diffusion-weighted imaging (DWI) shows the change in a particular water molecule diffusing from one location to another over a given period of time estimated by the apparent diffusion coefficient (ADC). (2) Diffusion tensor imaging (DTI) is a useful method to measure the directionality of water inside living systems, which is estimated by fractional anisotropy (FA). The fundamental aims of the use of diffusion MRI in PD are: (1) to contribute to the differential clinical diagnosis between PD and APD; (2) to determine biomarkers of disease progression and, therefore, to demonstrate the usefulness of potential therapies that delay or improve disease progression; (3) to allow presymptomatic diagnosis in people with PD; and (4) to identify in advance the motor and non-motor complications.
This chapter reviews the available data on the use of diffusion MRI to determine the pathophysiological mechanisms responsible for PD and APD. This technique could be used to identify microstructural changes earlier and thus initiate treatment more quickly after PD onset. It also offers the potential to differentiate between PD and APD.
Diffusion is the physical property that describes the Brownian (random) movement of water molecules in biological tissue in response to thermal energy [5]. The human body is composed of 75% water, which is located in three compartments: intravascular, intracellular, and extracellular (Figure 1). The movement of water molecules at the microscopic level of these compartments is sensitive to the diffusion sequence. Of note, it is the movement of water molecules in the extracellular space that is most useful to identify quantifiable markers that reflect tissue alterations. Microscopic displacement of water molecules occurs within brain tissue by following diffusion [7, 8]. Identifying these alterations in these movements could be useful to characterize neurodegenerative diseases, such as PD.
Figure 1.
A model of biological tissue described by three compartments: extravascular, intravascular, and intracellular. In healthy brain, water (H2O, which forms the basis for the magnetic resonance signal) is present and exchanged among all three compartments. This figure is based on the model from Anderson et al. [6].
In 1965, Stejskal and Tanner [9] were the first to apply the property of diffusion to MR sequences. In 1980, researchers reported the first biological tissues imaged based on the principles of nuclear magnetic resonance established by Carr et al. [10]. In 1986, Le Bihan et al. developed the first diffusion image from a brain MRI [11]. In 1992, Warach et al. [12] first applied this technique to study cerebral infarction. An advantage of this technique is its noninvasive nature and it does not require ionizing radiation and paramagnetic contrast. There is a great interest in MRI use to measure water diffusion. This application could provide maps of the diffusion coefficients in tissues, particularly in vivo [7]. Identifying areas of interest could be useful in defining biomarkers that could improve the diagnosis or traceability of a specific pathology.
2.1 Brief background of diffusion MRI
Diffusion MRI, also known as DWI, is a procedure of MRI based upon measuring the motion of water molecules within a voxel of biological tissue. Diffusion MRI detected the Brownian motion that is observed in the random or uncontrolled movement of particles in a fluid as they constantly collide with other molecules [13]. The pulsed gradient spin echo sequence, shown in Figure 2, is the most used acquisition scheme to generate diffusion weighting in an MRI image. It is also widely used to measure the displacement of water molecules in tissue. It consists of two radiofrequency (RF) pulses, one at 90° and the second at 180°, and two magnetic gradients with intensity G and pulse duration δ, before and after the 180° RF pulse.
Figure 2.
The Stejskal-Tanner pulsed-gradient spin echo (PGSE) sequence [9]. δ is the pulse duration, G is the pulse gradient, Δ is the diffusion time and echo time (TE) is the time to echo [14, 15].
In the MRI literature, the sequence parameters (see Figure 2) are commonly represented by a single diffusion parameter, b. It can be calculated according to Eq. (1):
b=γ2G2δ2∆−δ3.E1
Diffusion MRI quantifies the motion of water molecules (see Table 1). Microstructural changes in neuronal tissue are determined by quantifying the diffusion coefficients, measured by applying a diffusion-sensitizing gradient using the isotropic signal decay formulated by Stejskal-Tanner, which is called the apparent diffusion coefficient (ADC). This measure allows for evaluating the average diffusion in the area of interest of a tissue. Isotropic diffusion refers to the lack of a preferred direction for diffusion. An example is cerebrospinal fluid in which the diffusion rate of molecules is equal in all directions [16, 17]. The ADC map is created with the mono-exponential model by applying a square noise filter to define the intensity scale based on b-values (Figure 3).
Diffusion imaging
Measures
Details
Diffusion-weighted imaging
Apparent diffusion coefficient (ADC), or trace (D) diffusion coefficient is a measure of the strength (velocity) of diffusion in tissue.
Isotropic diffusion are called the distance to travel by the water molecules in the tissue, without barriers that restrictand the move nor the direction.
Diffusion tensor imaging
Fractional anisotropy
The molecules are limited to a determined direction of the tissue, generating a tensor that has three diffusion components on each axis (x, y, and z).
Table 1.
Diffusion MRI techniques.
Figure 3.
PD-DWI images use two different b-values, 43-year-old patient PD, male. Apparent diffusion coefficient (ADC) maps created from the linear representation of the mono-exponential model in patients with Parkinson’s disease. The signal obtained with the b-value provides information about the diffusion constant (made by the authors).
DTI was first described by Basser et al. [18]. It provides information about the local tissue when diffusion depends on the direction and is restricted by the normal architecture of the brain and the neuronal tracts, a condition known as anisotropy. Hence, DTI allows for calculating fractional anisotropy (FA) [19]. Anisotropic diffusion is not equal in all directions. An example is diffusion in neural tracts, where water molecules diffuse more longitudinally along the tract than to the sides. This directionality is largely determined by the cellularity and cell integrity in the tissues [16, 17]. FA is an important measure to detect any structural change with respect to a direction defined by the neuronal tissue. DTI is a sensitive, noninvasive method to detect the early stages of PD [20]. It even differentiates microstructural changes in PD (Figures 4 and 5) [21].
Figure 4.
Random barriers are present. Information on the microscopic motion of water protons (made by the authors).
Figure 5.
Coherent axonal bundle. Information on diffusion directionality, for example, it is possible to reconstruct axonal or muscle fiber images (made by the authors).
PD and APD are characterized by progressive dopaminergic dysfunction. Diagnosis and treatment of diseases in their early stages can be complicated [20]. While conventional MRI has provided information on these diseases (Table 2), diffusion MRI can help to provide additional information and specific biomarkers to help distinguish among them (Figures 6–8) [29].
The putamen and cerebellum are both affected in MSA, and nigral dopaminergic neuronal loss is observed in both MSA and PD [23]. Increased putaminal diffusivity in a patients with MSA. ADC is increased in the area of the lenticular nucleus in the patient with MSA [24].
PSP is characterized by postural instability and supranuclear gaze palsy; it is sometimes called Richardson’s syndrome [25]
Pathological changes in the SCP and dentate nucleus. Extensive atrophy in the brain stem, particularly in the midbrain, and also in the basal ganglia and cortex [24]
CBS includes apraxia, the alien-limb phenomenon, and disturbed epicritic sensitivity [26]
The most common motor feature in CBS is asymmetrical parkinsonism affecting a limb, typically an arm.
Table 2.
The main diagnosis of parkinsonian diseases.
Abbreviations: ADC: apparent diffusion coefficient; CBS: corticobasal syndrome; FLAIR: fluid-attenuated inversion recovery; MSA: multiple system atrophy; MSA-C: multiple system atrophy with predominant cerebellar dysfunction; MSA-P: multiple system atrophy with predominant parkinsonian features; PD: Parkinson’s disease; PSP: Progressive supranuclear palsy; SCP: superior cerebellar peduncle.
Figure 6.
The area of the lenticular nucleus 43-year-old patient PD, male (made by the authors).
Figure 7.
DWI images of a patient with PSP. (A) Enlargement of the third ventricle (B). Internal-1 and external-2 interpeduncular angles show midbrain atrophy. (C) Quadrigeminal thickness showing atrophy. (D) Periaqueductal hypersignal. Adapted from Barsottini et al. [27].
Figure 8.
Corticobasal degeneration. T2-weighted spin echo (b) demonstrates thinning of the sulci in the parietal cortex combined with subtle hyperintensity of the subcortical white matter. Adapted from Mascalchi et al. [28].
3.1 Diffusional MRI findings in PD
DWI and DTI provide quantifiable information to detect microstructural changes in PD. Neuronal loss alters the structural architecture of the central nervous system, producing potential biomarkers that could be assessed with imaging to diagnose PD (Table 3) (Figures 9–20) [28, 29, 32, 51, 52, 53].
Technique and region
Diffusion MRI findings
Key diffusion measures
Reference
DWI in olfactory tracts
Patients with PD showed significant increases in trace of diffusion (D) values in both olfactory tracts in a cohort of patients with PD versus healthy controls. Adapted from Ref. [30].
Understanding the neurological substrates of olfactory dysfunction in early PD could be used in combination with clinical markers. Identify evidence of white matter areas with increased/decreased connectivity in patients with PD with complete or severe loss of olfaction.
Schocke et al. [33] provided trace (D) imaging, which appears to be more accurate to separate patients with MSA-P from patients with PD, as rADC values in one direction are dependent on the slice orientation relative to the directions of fiber tracts. The ADC maps in the y-direction and z-direction clearly show the bilateral putaminal hyperintensity in a patient with MSA, indicating increased putaminal rADCs and rTrace (D) values. The putaminal hyperintensity is poorly demarcated on the ADC map in the x-direction.
Putamen Increased putaminal diffusivity: rADC in the y- and z-direction as well as trace (D) clearly show bilateral putaminal hyperintensity. Patients with MSA-P rADC in the y-direction = 1.011 ± 0.196 × 10−3 mm2/s rADC in the x-direction = 0.750 ± 0.180 × 10−3 mm2/s Trace (D) = 0.926 ± 0.208 × 10−3 mm2/s Patients with PD rADC in the y-direction = 0.766 ± 0.036 × 10−3 mm2/s rADC in the x-direction = 0.591 ± 0.0058 × 10−3 mm2/s Trace (D) = 0.718 ± 0.030 × 10−3 mm2/s Healthy controls rADC in the y-direction = 0.769 ± 0.025 × 10−3 mm2/s rADC in the x-direction = 0.637 ± 0.071 × 10−3 mm2/s Trace (D) = 0.745 ± 0.024 × 10−3 mm2/s
Significant differences in trace (D) of the caudate nucleus between patients with MSA-P and patients with PD. The caudate nucleus also shows significant differences in the rADC in the y-direction between patients with MSA-P or PD and healthy controls.
Caudate nucleus Patients with PD Trace (D) = 0.725 ± 0.035 × 10−3 mm2/s Patients with MSA-P Trace (D) = 0.802 ± 0.125× 10−3 mm2/s Patients with PD rADC in y-direction = 0.808 ± 0.043× 10−3 mm2/s Patients with MSA-P rADC in y-direction = 0.914 ± 0.120× 10−3 mm2/s Healthy controls rADC in y-direction = 0.823 ± 0.051× 10−3 mm2/s
Putaminal trace (D) in patients with MSA-P has been mapped at the level of the mid-striatum. The diffuse hyperintensity corresponding to increased trace (D) in the putaminal region of the patient with MSA [36].
The patient with MSA Putamen Trace (D) >0.80 × 10−3 mm2/s Posterior putamen Trace (D) >0.80 × 10−3 mm2/s
DWI of the middle cerebellar peduncle to differentiate between patients with MSA-P, PSP or PD
Increased middle cerebellar peduncle rADC. The images show patients with MSA without cruciform hyperintensity and patients with MSA with cruciform hyperintensity [37].
Increased middle cerebellar peduncle rADC differentiates patients with MSA-P from patients with PSP and PD. Patients with MSA-P Median rADC = 0.93 × 10−3 mm2/s (P < 0.001) Patients with PSP Median rADC = 0.82 × 10−3 mm2/s Patients with PD Median rADC = 0.79 × 10−3 mm2/s (P < 0.001) Healthy controls Median rADC = 0.81 × 10−3 mm2/s (P < 0.001)
DWI of the middle cerebellar peduncle and rostral pons to differentiate between patients with MSA-P, PSP, or PD (caudal and rostral)
The optimal cut-off level to discriminate patients with MSA-P from patients with PSP was a middle cerebellar peduncle rADC of ≥0.733 × 10−3 mm2/s (sensitivity = 91%, specificity = 84%). ADC measurements may have been utilized as surrogate markers in trials of disease-modifying medications [38].
Increased rADC in the middle cerebellar peduncle and rostral pons in patients with MSA-P compared with patients with PSP or PD. Pons (caudal): Patients with PSP rADC = 0.785 ± 0.090 × 10−3 mm2/s Patients with MSA rADC = 0.845 ± 0.133 × 10−3 mm2/s Patients with PD rADC = 0.771 ± 0.101 × 10−3 mm2/s Healthy controls rADC = 0.763 ± 0.079 × 10−3 mm2/s Pons (rostral): Patients with PSP rADC = 0.745 ± 0.110 × 10−3 mm2/s
Significantly higher SCP ADC in patients with PSP compared with patients with CBS or PD and healthy controls. The median ADC in the higher-valued hemisphere was significantly increased in patients with CBS. The hemispheric symmetry ratio in patients with CBS was lower than in patients with RS or PD and healthy controls.
Putaminal ADC provides good discrimination between patients with PD and patients with APD (RS and CBS). Patients with CBS 0.77 (0.75–0.79) × 10−3 mm2/s Patients with RS 0.75 (0.74–0.79) × 10−3 mm2/s Patients with PD 0.72 (0.71–0.73) × 10−3 mm2/s Healthy controls 0.70 (0.69–0.71) × 10−3 mm2/s
DTI of the pons, cerebellum, and putamen to differentiate between patients with MSA-P and patients with PD.
FA and ADC detected early pathological involvement prior to magnetic resonance signal changes in patients with MSA-P. Early FA reduction and ADC increase are likely to be associated with subtle early degenerative processes in patients with MSA-P.
Increased ADC in the pons, cerebellum, and putamen, and reduced FA in patients with MSA compared with patients with PD and healthy controls. FA Pons = 0.38 Cerebellum = 0.30 Putamen = 0.35 ADC Pons = 0.98 × 10−3 mm2/s Cerebellum = 0.96 × 10−3 mm2/s Putamen = 0.83 × 10−3 mm2/s Sensitivity and specificity of FA: 70.0% and 100.0% in the pons; 70.0% and 63.6% in the cerebellum; and 70.0% and 87.5% in the putamen.
The neuromelanin value was significantly lower and the diffusion tensor values except FA were significantly higher in the RBD and PD groups than in the healthy group. Diffusion MRI detects nigrostriatal changes in RBD and early PD.
Neuromelanin/mean diffusivity value. Patients with RBD SNpc = 0.76/0.82 Patients with PD SNpc = 0.83/0.80
The reduced volume of the SN in the patient with PD is attributable to iron deposition. FA was lower in the patient with PD than in the patient without PD (0.425 vs. 0.581), indicating a loss of neuronal integrity.
FA was increased in the three nigral subareas in patients with PD (P < 0.01). The right SN had higher FA than the left in all subareas (P < 0.01). The left middle cerebellar peduncle had increased FA (P < 0.001).
Putaminal diffusivity measurements to distinguish MSA-P from PD.
Prominent neuronal loss in the putamen; structural damage in the putamen would lead to enhanced diffusivity. Meta-analysis showed an overall sensitivity of 90% and specificity of 93%.
DTI of the rostral, middle and caudal SN and cerebral peduncle
Assessment of FA in the rostral, middle, and caudal regions of the SN. SN distinguishes early-stage de novo patients with PD from healthy controls.
Decreased FA in the caudal part of the substantial nigra with increased sensitivity and specificity even between individual subjects. Rostral region t = 1.5; P = 0.12 Middle region t = 3.7; P = 0.001 Caudal region t = 11.9; P = 0.00001
The FA is decreased in the nigrostriatal projection in parkinsonian patients, even during the early clinical stages
Decreased FA in the ROI along a line between the SN and the lower part of the putamen/caudate complex in patients with PD, even during the early clinical stages of the disease. FA in patients with PSP was decreased in most of the ROIs except for those in the neostriatum of parkinsonian patients showed a significant decrease in FA of the subthalamic ROI beside the SN. FA in the white matter of the premotor cortices was significantly smaller in patients with PSP or advanced PD compared with healthy controls.
Abbreviations: ADC: apparent diffusion coefficient; APD: atypical parkinsonism diseases; CBS: corticobasal syndrome; DBS: deep brain stimulation; DTI: diffusion tensor imaging; DWI: diffusion-weighted imaging; FA: fractional anisotropy; MSA: multiple system atrophy; MSA-P: multiple system atrophy with predominant parkinsonian features; PD: Parkinson’s disease; PSP: progressive supranuclear palsy; rADC: regional apparent diffusion coefficient; RBD: rapid eye movement sleep behavior disorder; ROI: region of interest; RS: Richardson’s syndrome; rTrace (D): regional trace (D); SCP: superior cerebellar peduncles; SN: substantial nigra; Unified Parkinson’s Disease Rating Scale (UPDRS). AC: anterior commissure; CN: caudate nucleus; Ctr: age matched normal subjects as control; GP: globus pallidus; GPe: globus pallidus lateral segment; GPi: globus pallidus medial segment; PC: posterior commissure; PD12: Parkinson’s disease in the early-stage group; PD345: Parkinson’s disease in the advanced stage group. ROI: region of interest; SN: substantia nigra; SNc: substantia nigra pars compacta; SNr: substantia nigra pars reticulate; STN: subthalamic nucleus; VL: nucleus ventralis lateralis.
Figure 9.
DWI, 43-year-old patient PD, male (made by the authors).
Figure 10.
Superior cerebellar peduncles (SCP) on the ROI map from 43-year-old patient PD, male. Adapted from results with interesting ROI (made by the authors).
Figure 11.
Adapted from results with putaminal ROI from 43-year-old patient PD (made by the authors).
Figure 12.
ROIs in the pons (A), cerebellum (B), and putamen (C). Adapted from Ito et al. [40].
Figure 13.
DWI image in a 66-year-old-patient without PD (A), an axial slice of the midbrain shows a delineated SN (black circle), showing well-defined cleavage with the red nucleus (white circle). In a 68-year-old patient with PD (B), an axial slice of the midbrain on susceptibility-DWI shows a poorly delineated. Adapted from Oliveira et al. [43].
Figure 14.
Anterior, middle, and posterior SN in a 43-year-old patient PD (Adapted from results by the authors).
Figure 15.
The overall specificity of putaminal diffusivity to discriminate MSA-P from PD. Adapted from Bajaj et al. [29].
Figure 16.
Anatomy of the extrapyramidal system in the paramedian sagittal view (A). Fibers of nigro-neostriatal projection, which are selectively lost in PD, are illustrated by black lines originating from the SN. FA images are derived from diffusion tensor images (B–D). FA in the extrapyramidal system of normal subjects and patients (E). Adapted from Ref. [45].
Figure 17.
Axial sequences depicting the SN and red nucleus (blue arrow) from a 43-year-old patient PD (adapted by the authors).
Figure 18.
Image illustrating the location of the SN in T2-weighted images (A) and the co-registered ROIs on the R2* (B) and FA (C) maps on both axial (top row) and coronal (bottom row) sections. Adapted from Du et al. [47].
Figure 19.
ROIs of gray matter structures: (A) substantia nigra (sn), (B) caudate (c), putamen (p), globus pallidus (gp), and (C) thalamus (t), drawn on axial diffusion tensor DTI images on the FA map. Adapted from Chan et al. [49].
Figure 20.
Significant voxel-wise correlations (P < 0.05, corrected) between decreased FA and increased total UPDRS scores were detected in the white matter at the level of the SN. Adapted from Zhan et al. [21].
Diffusion MRI, including isotropic and anisotropic techniques, has become increasingly important in the evaluation and diagnosis of patients with PD, and even in other neurodegenerative diseases. The most common quantitative biomarkers are ADC and FA. Moreover, diffusion MRI has the advantages of being noninvasive, repeatable, and quantifiable, and has the ability to localize damage. It is likely that neuroimaging methods will become important research techniques in the area of biomarkers in future. In conclusion, the parameters estimated with diffusion MRI in patients with moderate-stage PD can distinguish between patients with PD or APD and healthy controls.
Greatly appreciated to the authors who allowed the use of the images as part of the construction of the chapter and to the Chinese Academy of Sciences for supporting this publication. It is necessary to clarify that the main author was affiliated with the Universidad Manuela Beltran and the Universidad ECCI as a research professor, but it is published with the authors’ own resources without any financial interest.
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Written By
Gloria Cruz, Shengdong Nie and Juan Ramírez
Submitted: 02 September 2022Reviewed: 04 January 2023Published: 23 August 2023
Open access peer-reviewed chapter
