ABSTRACT

Objective: To evaluate the common MRI findings in patients with neurologic disorders.

Method: A retrospective study of 106 patients with neurologic disorders was carried out and their respective findings carefully tabulated according to their age and sex.

Results: MRI showed small multifocal lesions hyperintense on T2 weighted images and FLAIR, with mild or nogadolinium enhancement, mainly in periventricular and subcortical regions, myelopaties in the cervical spines of some patients, white matter abnormalities above all other findings.

Conclusion: It is important to emphasize the role of MRI in the diagnosis and follow-up of these patients.Lesions that are better detected in MRI include hippocampal sclerosis and T2 hyperintensities that form the bulk of abnormalities in the pediatric category. Majority of abnormalities in the adult category like space occupying lesions can be easily picked up by CT whereas refractory seizure, cases with EEG findings suggesting TLE, suspected stroke should preferably undergo MRI brain imaging as    it is much more sensitive in detecting these pathological substrates.

TABLE OF CONTENTS

Title page……………………………………………………………………..i

Dedication………………………………………………………………………ii

Acknowledgement……………………………………………………………….iii

Approval page……………………………………………………………………..iv

Certification………………………………………………………………………v

Abstract …………………………………………………………………………vi

List of tables……………………………………………………………………..vii

CHAPTER ONE

1.1 BACKGROUND OF STUDY…………………………………………….1

1.2 statement of problems………………………………………………………..3

1.3 general objective…………………………………………………………..3

1.4 specific objectives of study………………………………………………..4

1.5 significance of study………………………………………………………4

1.6 scope of study……………………………………………………………..4

1.7 review of related literatures………………………………………………5

1.7.1 Review on the MRI findings in crohn’s disease.………………………5

1.7.2 Mri findings in neuroferritinopathy…………………………………..6

1.7.3MRI findings in 77 Children with Non-Syndromic Autistic Disorder                  …………………………………………………………………………………..12

1.7.4 Stroke……………………………………………………………………26

1.7.5 Research and development agenda……………………………………36

1.7.6 Missed opportunities…………………………………………………..38

CHAPTER TWO.

2.1Definitionof terms………………………………………………….18

2.2 Basic MRI scans……………………………………………………21

2.3   Specialized MRI scans………………………………..………………… 22

          2.4Magnetization transfer MRI…………………………………….……….24

2.5 Interventional MRI……………………………………….…………………25

2.6  Radiationtherapy simulation……………..…………………………….26

2.7 Other specialized MRI techniques…………………………………………27

2.8  Safety………………………………………………..………………………..56

2.9Neuroanatomy……………………………….……………………………34

CHAPTER THREE

3.1 Research design………………………….…………………………………..46

3.2 Area of study…………………..……………………………………………46

3.3 Target population………………………………………………….………46

3.4 Selection criteria……………………………………………………………..46

3.4.1 Inclusion criteria…………………………………………………………..47

3.4.2 Exclusion criteria……………………………………………………….….47

3.5 Sampling……………………………………………………….…………….48

3.5.1 Sampling method…………………………………………………………..48

3.5.2 Sampling procedure…………………………………………………….…48

3.5.3 Sample size: ……………………………………………………..…………51

3.6 Procedure of data collection:……………………………………….52 Methods of data analysis…………………………………………………………52

CHAPTER FOUR………………………………….……………………………53

CHAPTER FIVE ………………………………………….…………………….70

CHAPTER ONE

1. BACKGROUND OF STUDY

Neurological disorders are diseases of the central and peripheral nervous system. In other words, the brain, spinal cord, cranial nerves, peripheral nerves, nerve roots, autonomic nervous system, neuromuscular junction, and muscles. These disorders include epilepsy, Alzheimer disease and other dementias, cerebrovascular diseases including stroke, migraine and other headache disorders, multiple sclerosis, Parkinson’s disease, neuroinfections, brain tumors, traumatic disorders of the nervous system such as brain trauma, and neurological disorders as a result of malnutrition. ^[8]

Hundreds of millions of people worldwide are affected by neurological disorders: For example, 50 million people have epilepsy; 62 million are affected by cerebrovascular disease; 326 million people suffer from migraine; 24 million are affected by Alzheimer disease and other dementias globally.^[4]

MRI is helpful in the evaluation of patients with clinical evidence of neurologic disorders. In most patients MRI is abnormal; Lesions are more likely to occur in the brain stem, basal ganglia, thalamus, internal capsule and spinal cord. When compared to CT, MRI has been found to better delineate lesions seen on CT in addition to show lesions not usually seen on CT. CT lesions in neurologic disorders may reflect a reversible breakdown in the blood-brain barrier, possibly related to inflammation rather than gliosis or infarction^. On the other hand, the presence of focal findings on MRI implies true cerebral disease, which is an important point in differentiating drug effects or primary psychiatric illness^.[10]

The development of anatomical neuroimagingenabled the in vivo visualization of neuropathology in conditions such as stroke, facilitating differential diagnoses and early treatment. Since then scanning techniques have gone beyond structural detail to provide images relating to human brain function, and in the past decade these techniques have been joined by an impressive new imaging tool, functional magnetic resonance imaging (functional MRI). This has a spatial resolution within the millimeter scale and can capture responses in the brain occurring over a few seconds, although reconstruction and processing of the raw data commonly occur after scanning. ^[10]

Also, Functional MRI is non­invasive and safe. It does not require radioactive tracer substances, unlike positronemission tomography (PET) or single photon emission tomography (SPET), and uses the brain’s natural hemodynamic response to neural activity as an endogenous tracer. It can be carried out during the same session as routine magnetic resonance imaging in a clinical scanner. These features are making it increasingly popular in neuropsychiatric research.The commonest form of functional MRI is blood oxygenation level dependent (BOLD) imaging.1 The BOLD signal depends on the ratio of oxygenated to deoxygenatedhemoglobin. ^[11]

1.2 STATEMENT OF PROBLEMS.

1. The mostcommon Magnetic Resonance Imaging findings in patients with neurologic disorders has not been documented in our locality.
2. The diagnostic yields of MRI in neurologic disorders have not been evaluated in our locality.
3. The age range at which certain neurologic disorders manifest more in have not been documented in our locality.
4. As neurologic disorders are the disorders that occur in the brain and spinal cord, the particular part of the CNS where neurologic disorders manifest more in, has not been document in our locality.

1.3 GENERAL OBJECTIVE.

To evaluatethe common MRI findings in patients with neurologic disorders.

1.4 SPECIFIC OBJECTIVES OF STUDY.

1. To characterize the MRI findings in patients presenting with neurologic disorders.
2. To evaluate the prevalence of common neurologic disorders using MRI.
3. To determine the age range at which neurologic disorders manifest more.
4. To determine the particular part of the CNS where neurologic disorders manifest more.
5. To evaluate the diagnostic yield of MRI in the diagnosis of neurologic disorders.

1.5SIGNIFICANCE OF STUDY.

1. The study will characterize the MRI findings in selected patients with neurologic disorders in UITH (University of Ilorin Teaching Hospital).
2. The study will provide data on the prevalence of common neurologic disorders using MRI in our locality.
3. The study will evaluate the significance of MRI in the diagnosis of neurologic disorders.
4. The study will provide data on the age range at which neurologic disorders manifest more in our locality.
5. The study will provide data on the particular part of the CNS where neurologic disorders manifest more.
6. The study will also evaluate the diagnostic yield of MRI in neurologic disorders.

1.6SCOPE OF STUDY.

This retrospective study will involve all categories of patients as regards to age, sex, body type and race presented with neurologic disorders in UITH (University of Ilorin Teaching Hospital.

 1.7                REVIEW OF RELATED LITERATURES

1.7.1Review on the MRI findings in crohn’s disease.

The association of inflammatory bowel disease with neurological involvement is unusual and often controversial.We report the case of a 39-year old man with Crohn’s disease and an intracranial benign primary tumor, detected on MRI scan. The patient had been suffering from extensive perianal fistulas for 8 years, before inflammatory bowel disease was diagnosed six months ago. The patient, beingenrolled in a research protocol, underwent brain MRI examination. Despite the absence of neurological symptoms and electromyography abnormalities, a meningioma was evidenced. Whether this is an incidental finding on brain MRI or whether it might be linked to Crohn’s disease development as an extra intestinal, neurological disorder remains unclear. This information is especially important in view of the ethical and practical issues involved in the management of incidental findings in CD. This report might provide further confirmation of the hypothesis that central neurological disorders occur during CD. Neurological involvement in CD is unusual. Central nervous system disorders could either be part of extra intestinal symptoms in this disease or precede diagnosis ^[12]. However, their frequency is not well known or documented.One study reports two cases of CD and a central nervous system deficit. In both cases, MRI confirmed the presence of T2 hypersignal in the white matter (4). Other reports describe focal white-matter lesions on the brain MRI of patients with inflammatory bowel disease ^[13].Our patient was a 38 year old man with no previous brain MRI.The diagnosis of the tumor was made on the basis of imaging. Pathological confirmation was not obtained, since the tumor did not require surgery and the patient remainedasymptomatic.The rate of growth of meningiomas is typically slow.^[14]and most of them remain asymptomatic throughout life, which explains why 50% are discovered at autopsy ^[15]. The prevalence of meningiomas found at autopsy inpersons over 60 years of age is 3% and the majority of the lesions are less than 1cm in diameter ^[16]. In our case, the tumor was bigger in size at the moment of discovery but it is difficult to prove that the presence of Crohn’s disease mighthave been a factor to accelerate the rate of growth. Nevertheless, it is generally believed that asymptomatic meningiomas require close clinical and radiological follow up to rule out rapidly enlarging tumors ^[17]. Currently, our patient follows close monitoring and the next MRI is scheduled in six months.

In conclusion, whether, this meningioma represents an incidental finding on brain MRI or it might be linked to CD development as an extra intestinal, neurological disorder remains unclear. Further prospective studies are necessary in order to confirm the hypothesis that such central neurological disorders may occur during Crohn’s disease

1.7.2 MRI FINDINGS IN NEUROFERRITINOPATHY.

Neuroferritinopathy is an autosomal dominant neurodegenerative disorder characterized by the deposition of iron and ferritin in the brain and a decreased level of serum ferritin.  The disease is caused by a mutation in the ferritin light chain gene ^[20]. Seven different pathogenic mutations of the ferritin light chain gene have been identified. These mutations are predicted to affect the tertiary structure and stability of the ferritin light chain polypeptide and may cause inappropriate iron release from ferritin polymers ^[21]. It is supposed that the excess iron induces free toxic radical production, which leads to tissue oxidative stress and neuronal cell death ^[22]. The clinical features of neuroferritinopathy are characterized by the adult onset of extra pyramidal motor symptoms: dystonia, chorea, choreoathetosis, Parkinsonism, and tremor. Some patients may present cerebella ataxia, cognitive decline, and pyramidal signs ^[23]. The phenotypic signs of the disease are variable, even among members of the same family .Generally, there are no nonneurological symptoms ^[24], different from in other neurodegenerative brain iron accumulation diseases. The clinical features of neuroferritinopathy are not specific, and they overlap with those of common extra pyramidal disorders. It is difficult to diagnose neuroferritinopathy solely based on the clinical findings. Brain MR imaging in the disease is quite characteristic and it may facilitate differential diagnosis of neuroferritinopathy from other extra pyramidal disorders.

Brain MR Imaging in Neuroferritinopathy

They reviewed the findings in neuroferritinopathy with conventional MRI methods, T1-weighted imaging, T2-weighted imaging, and T2*-weighted imaging. On T1WI, there is a sharp contrast between the parenchyma and ventricles, and it is adequate for evaluating brain atrophy and cystic changes. T2WI is suitable for detecting the pathological processes with an increase in water content, such as gliosis, edema and axonal/neuronal loss, as hyperintense signals. On T2*WI with a gradient echo sequence, the signals are readily influenced by magnetic inhomogeneity. Therefore, T2*WI is sensitive enough to detect paramagnetism such as that of iron.

Signal abnormalities on brain MR imaging were observed in all affected individuals previously reported except for one case ^[25]. Despite the clinical differences, the neuroimaging is similar across cases ^[26]. The findings are usually bilateral and symmetric but sometimes asymmetric. Signal changes are found in widespread areas in the central nervous system.

Radiological findings in patients with neuroferritinopathy have been shown to correlate with the observed pathology. The abnormalities observed on MRI reflect four pathological changes: iron deposition, edema and gliosis, cystic changes, and cortical atrophy ^[28]. Each finding is described individually below.

Iron Deposition

Iron is essential for normal neuronal metabolism, but excessive iron may be harmful ^[29]. It is known that iron overload can cause free-radical formation and neuronal damage.

Physiologically, brain iron appears to be found predominantly in the extra pyramidal system, in particular the globuspallidus, substantianigra, red nucleus, and putamen. It has been shown that moderate levels of iron occur in the striatum, thalamus, cerebral cortex, cerebella cortex, and deep white matter ^[21]. It is also known that iron deposition increases normally with age. The brain histopathology of affected individuals with neuroferritinopathy involves excess iron and ferritin deposits throughout the forebrain and cerebellum, notably in the basal ganglia. The accumulation observed in affected patients exceeds that found in normal elderly individuals. However, these regions still exhibit the general distribution pattern for iron in the normal aging brain ^[21].

On fast spin echo T2WI, iron deposits are demonstrated as low-intensity areas and as signal loss on gradient echo T2*WI. Comparison of T2WI and T2*WI sequences suggests that the T2* one is more sensitive for the detection of iron, while the T2 fast spin echo T2WI sequence is more frequently used in routine clinical practice ^[23]. In particular, the cortical iron deposition in neuroferritinopathy is hardly detectable on T2WI but is easily observed on T2*WI. Generally, iron deposit regions are isointense on T1WI ^[23].

Degeneration

T2 hyper intense abnormalities are seen in the pallidum, putamen, caudate nucleus,thalamus and dentate nucleus, and sometimes in the red nucleus and substantianigra, in patients with neuroferritinopathy. The border of a lesion has a tendency to be unclear and the signal is unequal. These changes are supposed to reflect tissue degeneration with edema and gliosis observed pathologically. Because of the increased water content, the lesions are detected as hyper intense signals on T2WI ^[30]. Around these hyper intense areas, hypo intensity due to iron deposits is frequently seen.

 Cystic Changes

On MRI in neuroferritinopathy, the bilateral cystic changes involving the pallidum and putamen are impressive. Cavities are demonstrated as low-intensity signals on T1WI and high-intensity signals on T2WI, compared with the CSF signal. In the region adjacent to a cystic lesion, severe loss of nerve cells and neurophil is observed pathologically. In one case, Vidal et al. reported that microcavities measuring up to 1.5 mm in diameter were seen in the putamen anatomically and that these cavities were consistent with small hypo intense areas on T1WI and to hyper intense ones on T2WI on MRI ^[20]. This finding is thought to represent the beginning stage of cavity formation.

McNeill et al. analyzed the MRI findings in 21 patients with neuroferritinopathy. In 52% (11/21 patients), they found that the globuspallidus and/or putamen coincided with a confluent area of hyper intensity and that this hyper intense area was likely to be due to fluid within an area of cystic degeneration. It is usually accompanied by a rim of peripheral hypo intensity reflecting iron deposition. This is a characteristic imaging pattern in neuroferritinopathy. The presence of large cysts is thought to be a finding observed at an advanced stage ^[27].

Cortical Atrophy

On brain MRI in neuroferritinopathy, atrophy is sometimes noted in the cerebella cortices and cerebral cortices, notably in the frontal lobe. Atrophy of the cerebella and cerebral cortices has also been anatomically identified. Regarding on clinicoradiologic correlation, patients having cerebella atrophy present ataxia, and ones having cerebral atrophy present cognitive decline ^{[23, 26].}

The Relationship between the Stage of the Disease and MRI Findings

The first MRI change is loss of the T2* signal due to iron deposits. In an early symptomatic stage, and even in an asymptomatic carrier, there is obvious signal loss on T2* imaging in the basal ganglia, especially in the globuspallidus, at considerable frequency. In conventional spin echo MR sequences, the signal change is inconspicuous and is observed as a minor low signal on T2WI ^[20]. There has only been one report of that brain MR T2WI was normal without evidence of iron deposition; however, it was obtained six years after the onset of neuroferritinopathy symptoms. In this case, the T2* sequence was not examined at that time. The follow-up MRI performed 16 years after the onset, however, showed typical abnormalities ^[26].

With disease progression, the T2 hypo intense signal and T2* signal loss become more pronounced ^[31]. The changes eventually extend to the thalamus, dentate nucleus, substantianigra, red nucleus, and cerebral cortex.

In the middle stage of the disorder, T2 hyper intense abnormalities reflecting tissue edema and gliosis are observed. In the basal ganglia, this change is thought to represent precystic degeneration ^[29]. The hyper signal lesions are often intermixed with decreased intensity areas corresponding to iron deposits. The combination of hyper intense and hypointense abnormalities is found in the pallidum, putamen, thalamus, and dentate nucleus frequently and sometimes in the red nucleus and substantianigra^[32].

The characteristic finding on brain MRI at the advanced stage is symmetrical cystic degeneration of the basal ganglia ^[28]. Pathologically, many microcavities due to the loss of neurophils and neurons are observed, which are consistent with hypointense areas on T1WI and with hyperintense ones on T2WI on MRI ^[29]. It is supposed that small cavities merge to form larger cavities with progression of the disease. The large cavities observed on MRI have been confirmed by macropathological investigation ^[33].

1.7.3  MRI Findings in 77 Children with Non-Syndromic Autistic Disorder

Seventy-seven children and adolescents with AD (mean age±sd: 7.4±3.6, age range: 2.3 years–16,6 years; 64 boys) were studied as part of a series of imaging research projects focusing on non-syndromic AD. Children with AD were recruited in three university hospitals with dedicated units labeled as reference centers for autism by the French Health Ministry. This group of children was composed only of children with autistic disorder (AD). Children with Asperger syndrome or pervasive developmental disorder –not otherwise specified (PDD-NOS) were not included in this study. The inclusion criteria were age (range: 2–17 years) and non-syndromic AD diagnosis according to the DSM-IV and ADI-R ^[35] criteria for autism. Diagnosis was performed in these units by a multidisciplinary team including child psychiatrists, child psychologists and speech therapists during 3–7 days of extensive evaluation. The exclusion criteria were: 1) IQ below 40, 2) known infectious, metabolic or genetic diseases, 3) chromosomal abnormalities, 4) seizures, 5) identifiable neurological syndromes or focal neurological signs, 6) significant sensory impairment (e.g., blindness, deafness) or 7) major physical abnormalities.^[37]

Mental retardation was assessed by an intelligence quotient (IQ), determined with the Wechsler Intelligence Scale for Children and the Wechsler Preschool and Primary Scale of Intelligence (WISC-III and WPPSI-III). DQ (Developmental Quotient), classic for assessment of mental retardation) was obtained in all children younger than 6 years old. Developmental quotient (DQ) was determined with the Psycho-Educational-Profile Revised (PEP-R) and the Brunet-Lézine developmental tests.

MRI inspection was also performed in 77 age-matched comparison children. The control MRIs were retrospectively selected from our database of children with cervico-facial pathologies (sinusitis, traumatism, facial dermoid cysts, facial cutaneous vascular malformations) and without neurological and neuro-chirurgical disorders according to three criteria: 1) age matching with AD children group, 2) MRI including all sequences performed in AD children and 3) clinical files providing sufficient information to ensure the lack of neurological or developmental disorders. Radiological description of the main abnormalities

The white matter signal abnormalities (Figure 1 and Table 3) were mainly posterior hyperintensity “plaques-like areas” on T2, which were found in 19 patients (28%). They were relatively symmetrical and were located bilaterally at the posterior horns of the lateral ventricles, without deformation of the adjacent lateral ventricular wall and without involvement of the sub-cortical U fibers. White matter abnormalities were associated with other abnormalities in 17 patients^.[39]

Figure 1. White matter abnormalities in autism.

Two children illustrating the principal categories of white matter signal abnormalities. Figure 1A. Punctate T2 Hyperintensity: Abnormal findings were placed in this category when small (<2 mm) rounded abnormalities were found scattered bilaterally in the white matter (white arrow). They were asymmetric and homogeneous, and no findings suggest that necrosis was present. They were very intense compared with adjacent white matter on T2 and FLAIR sequences, and did not involve the basal ganglia, the periventricular white matter fibers or the sub-cortical U fibers. These abnormalities were generally found in association with other supratentorial abnormalities. Figure 1B. Posterior T2 Hyperintensity. Abnormalities placed in this category were “plaque-like areas” of mild white matter hyperintensity relatively symmetrical bilaterally at the posterior horns of the lateral ventricles (black arrow). There was no deformation of the lateral ventricular contour adjacent to these lesions. No abnormality of the sub-cortical U fibers was observed. ^[40]

Dilated Virchow-Robin spaces in autism.

Virchow-Robin (VR) spaces are fluid-containing dilatations of the perivascular space that surrounds penetrating arteries in the brain (white arrow). We defined abnormal VR spaces when the spaces were >3 mm using the classification system developed by Heier et al ^[36].

Other structural abnormalities were detected only in the temporal lobes (Figure 3 and Table 3). They were found in 20 patients and consisted of sub-cortical hyperintensity on T2-weighted images localized in the temporal poles (n = 17, isolated in three patients) (Fig 3), loss of gray-white matter definition in the temporal poles on FLAIR-weighted images (n = 13, never isolated) and a unilateral nodular temporal lobe mass (n = 1). Sub-cortical temporal pole hyperintensities are usually observed during normal myelination (until four years of age); therefore, we only considered them as abnormal in children older than four years of age.

Figure 3. Temporal pole abnormalities in a child with autism.

Example of a typical sub-cortical hyperintensities on T2-weighted coronal images localized in the temporal poles observed in children with autism (red arrows) and a normal image of a control child without autism. Concerning age and cognitive level, regarding all types of abnormalities there was no significant differences between the group with MRI abnormalities comparing to the group without MRI abnormalities for both age and IQ data. More detailed age analysis showed that in children younger than 4 years, MRI was abnormal in 4 children and normal in 6; from 4–6 years, MRI was abnormal in 12 children and normal in 16 children; from 6–8 years, MRI was abnormal in 10 children and normal in 3 children; from 8–10 years: MRI was abnormal in 7 children and normal in 4 children; MRI was normal in all children older than 10 years old (n = 7). In addition, within the MRI abnormalities, we found some interesting trends. For example, white matter abnormalities are more linked to young children than older (mean age with white matter abnormalities: 5.1±1.3 years old vs. children without white matter abnormalities 7.7±1.4 years old; p<0.01). One explanation of this age difference could be a delayed myelination. This was not the case for temporal lobe abnormalities (mean age with temporal abnormalities: 6.2±1.7 years old vs. children without temporal abnormalities 6.5±2.2 years old; p = 0.2).^[40]

Concerning IQ, temporal abnormalities are more linked to children with higher IQ (mean IQ with temporal abnormalities: 59.3±12.8 vs. children without temporal abnormalities 46.3±7.1; p<0.03). For white matter abnormalities there was no significant difference (mean IQ with white matter abnormalities: 57±13.4 old vs. children without white matter abnormalities 51.6±11.4).

Concerning the ADI sub-scores, the median social score (B) was 29. We found 5 children with temporal abnormalities with B score inferior than 29 and 11 children with B score superior than 29. Three children with white matter abnormalities had B score inferior than 29 and 8 children had B score superior than 29. For communication score (C), the median score was 13.5. We found 6 children with temporal abnormalities with C Score inferior than 13.5 and 10 superior than 13.5. Concerning white matter abnormalities, 5 children had a C score inferior to the median score and 6 superior to the median. So, the autistic children with more severe social deficits and language impairments had more temporal abnormalities.^[42]

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