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RAJIV GANDHI UNIVERSITY OF HEALTH SCIENCES, KARNATAKA
BANGALORE
ANNEXURE – II
PROFORMA FOR REGISTRATION OF SUBJECT FOR DISSERTATION
1
Name of the Candidate
(in Block Letters)
Dr. SINDU P. GOWDAR
D/O PRAKASH GOWDAR
#3087, 9TH MAIN, 3RD CROSS,
M.C.C ‘B’ BLOCK
DAVANGERE, 577004
KARNATAKA.
Name of the Institution
J.J.M. MEDICAL COLLEGE,
and Address
2
DAVANGERE – 577 004.
3
Course of the Study and Subject
POSTGRADUATE
M.D. IN RADIO-DIAGNOSIS
4
Date of Admission to Course
5
Title of the Topic
1ST JUNE 2012
“MR EVALUATION OF WHITE MATTER
DISEASES”
6.
BRIEF RESUME OF THE INTENDED WORK:
6.1 Need for the study:
Virtually all categories of pathology may cause white matter abnormalities. White
matter abnormalities may be seen in congenital, inflammatory, neoplastic, post traumatic,
metabolic, toxic, vascular, degenerative and demyelinating diseases. The primary white
matter disorders are classically divided into two groups dysmyelinating disorders (usually
metabolic), in which normal myelin fails to form, and the demyelinating diseases, in which
normal myelin has formed and is later destroyed by a myelinoclastic process. Adult
leukoencephalopathies (and white matter disorders which are not age-specific) may be
caused by several categories of disease. Primary demyelinating disorders, infectious,
neoplastic, post-traumatic and metabolic disorders are the most common. When white matter
disease is encountered on an imaging study, it is useful to first characterize the white matter
involvement as multifocal, confluent / diffuse, or selective (geographic). This approach,
combined with the clinical information regarding patient demographics, clinical history and
physical findings, helps the imager limit the differential diagnosis.1
Pediatric white matter diseases are divided into four categories based on highintensity abnormalities seen on long TA images and correlative clinical information:
demyelinating disease, dysmyelinating disease, developmental delay (of myelination), and
white matter abnormalities of unknown origin. The last group of pediatric white matter
diseases is those of unknown origin. It is in this group that perhaps MR had its greatest
impact in lesion-detection capabilities.2
The advent of MR has revolutionized the concept of understanding of white matter
diseases. MRI is considered far superior to CT and the imaging modality of choice in white
matter diseases. However, with the advent of multiecho sequences of MR, even subtle
lesions of demyelination can be detected. A correct diagnosis could be made in majority of
the patients based on MR findings and clinical history alone. MR, in conjunction with
clinical findings, plays a significant role in establishing the diagnosis and in the further
follow up of patients with white matter diseases.3
MRI will play a key role in the diagnostic evaluation of MS in children. Application of
more advanced MRI techniques such as MR spectroscopy (MRS), magnetization transfer
(MT), and diffusion tensor (DT) imaging yield more tissue-specific insights into neuroaxonal and white matter integrity than conventional MRI assessment.4
The difference in water diffusion, namely anisotropic versus isotropic diffusion,
between gray and white matter, can be used to selectively highlight the white matter tracts
and to assess their integrity. Hence, it has been postulated that diffusion- weighted MR
imaging would be a useful tool to monitor the development of the normal brain. Children
with dysmyelination or demyelination of white matter, diffusion-weighted MR imaging
provides information that is not apparent on conventional T1- or T2-weighted MR images.
Diffusion restriction precedes brain myelination and is further increased during
myelination.5
The newly emerging field of axonal fiber tracking from DTI data 43, 44 may have a
major impact on our understanding of the clinical manifestations of degenerative and
inflammatory disease processes. Not only can a primary site of axonal injury be determined
with DTI, but it may be that Wallerian degeneration45 and perhaps even axonal pathways
underpinning cortical remodeling could be visualized.6
A number of inborn errors of metabolism result in neurological disorders that are
associated with white matter abnormalities. MRS can provide more specific information
than MRI and can help in the diagnosis of many of these diseases.7
6.2 Review of literature:
MRI features of 116 children enrolled in the French cohort of acute CNS
demyelination by B. Banwell, MD et al, found that MRI criteria specific for pediatric-onset
multiple sclerosis (MS) and criteria predictive of MS outcome in children experiencing a
first demyelinating event will be challenged by the overlap in MRI features between acute
monophasic demyelinating syndromes and MS, particularly in younger children. Emergence
of new clinically silent lesions on MRI scans separated by at least 3 months is characteristic
of MS. Newer MRI techniques evaluating white matter biochemistry and integrity in the
youngest MS patients may provide new insights into the relative contributions of
inflammation and neurodegeneration in MS.4
In a study of MR evaluation of white matter diseases by BN Lakhkar, M Aggarwal,
JR John it was concluded that MRI due to its excellent gray-white matter resolution is very
sensitive in detecting subtle demyelination, the sensitivity being still further enhanced by
FLAIR sequences. The present study concludes that MRI, in correlation with the clinical
signs and symptoms is an ideal modality in early diagnosis of white matter diseases and aids
in the early institution of therapy so that the curable conditions among them can be treated.3
MR imaging performed by Engelbrecht, MD et al, in 101 of the 173 children
revealed a broad variety of pathologic changes. This study concluded that during early brain
myelination, diffusion restriction in normal white matter increases. Anisotropy precedes
myelination changes that are visible at MR imaging. Compared with T1- and T2-weighted
MR imaging, diffusion-weighted MR imaging in white matter diseases reveals additional
information.5
Whole-brain voxel-wise investigation of both grey matter topography and white
matter integrity (Fractional Anisotropy) were carried out on 25 adolescent-onset
schizophrenic patients and 25 healthy adolescents by Douaud G et al. There was a
widespread reduction of anisotropy in the white matter, especially in the corpus callosum.
We speculate that the anisotropy changes relate to the functional changes in brain
connectivity that are thought to play a central role in the clinical expression of the disease.
We found striking abnormalities in the primary sensorimotor and premotor cortices and in
white matter tracts susbserving motor control (mainly the pyramidal tract). This novel
finding suggests a new potential marker of altered white matter maturation specific to
adolescent-onset schizophrenia.8
A study was done on 14 (11 male, three female) patients with a DSM-IV diagnosis
of schizophrenia (n¼7) or schizoaffective disorder (n¼7) as determined by the Structured
Clinical Interview for the DSM-IV by A. Ardekani et al.
Using a rigorous voxelwise
analysis, they have demonstrated reductions in WM integrity in patients with schizophrenia
or schizoaffective disorder compared to healthy control subjects. The regional distribution of
these differences is consistent with other reported structural brain abnormalities in
schizophrenia. By assessing differences in WM integrity across the whole brain, this method
can inform hypothesis-driven studies of WM integrity in schizophrenia as well as other
disorders of the brain.9
In a study done by van der Voorn, MD et al, Forty-one patients (19 male, 22 female;
mean age, 15.4 years) and 41 control subjects (25 male, 16 female; mean age, 11.3 years)
were included. Twelve patients had a hypomyelinating disorder; 14 had a demyelinating
disorder; five had a disorder characterized by myelin vacuolation; and 10 had a disorder
characterized by cystic degeneration. It was concluded that quantitative MR techniques can
be used to discriminate between different types of white matter disorders and to classify
white matter lesions of unknown origin with respect to underlying pathologic conditions.10
In a recent systemic review with meta-analysis on incidental findings in brain
magnetic resonance imaging by Morris et al, it was found that neoplastic incidental brain
findings had a prevalence of 0.7% (135 of 19559 people out of 16 studies) with increased
prevalence with age. The non-neoplastic incidental findings were even more prevalent at
2.0% (375 of 15559 in 15 studies). The overall prevalence of incidental brain findings on
MRI was 2.7 %, equivalent to one for every 37 subjects scanned.11
In a study by de Leeuw FE et al, a total of 1077 subjects aged between 60–90 years
were randomly sampled from the general population. Of all subjects 8% were completely
free of subcortical white matter lesions, 20% had no periventricular white matter lesions,
and 5% had no white matter lesions in either of these locations. It was concluded that the
prevalence and the degree of cerebral white matter lesions increased with age. Women
tended to have a higher degree of white matter lesions than men. This may underlie the
finding of a higher incidence of dementia in women than in men, particularly at later age.12
In a study by Tourbah A et al, fifty six patients among whom 39 had white matter
diseases had MRI of the brain comparing FLAIR sequence to a conventional proton density
sequence. Flair sequence allowed to detect 18 additional hypersignal (HS) that were not
present on T2 sequence. These HS were located in the periventricular areas for 5 of them,
near the cortical sulci in 10, and in the centrum semi-ovale for 3. FLAIR sequence permitted
analyze 41 other lesions that were not obvious on proton density sequences. Thirty five of
them were thus confirmed to be HS : 31 in the paracortical areas, 3 in the paraventricular
regions and one in the internal capsule, whereas the remaining 6 were normal sulci of the
brain. FLAIR sequence increases the sensitivity of MRI in white matter diseases.13
In a study by Kjos BO et al, seventy-six children with developmental retardation of
unknown cause underwent MR imaging of the brain. Twenty-one (28%) had positive MR
findings, including nine with atrophy, six with delayed myelination, four with multiple focal
white matter lesions, three with hypoplastic white matter, and three with migration
abnormalities. The frequency of abnormality was highest in nonautistic children with
associated neurologic physical findings (61%) but was also significant in nonautistic
children without neurologic findings (23%). They concluded that MR will reveal brain
abnormalities in about one third of nonautistic children with developmental retardation of
unknown cause, and more often in those with neurologic deficits, seizures, or a small head
size.14
In their study, Filippi M. et al compared a fast fluid-attenuated inversion recovery
(fast-FLAIR) sequence to conventional spin-echo (CSE) in the evaluation of brain MRI
lesion loads of seven patients with clinically definite multiple sclerosis. Four hundred and
two lesions were detected in at least one of the two sequences: 128 were seen only on fastFLAIR, 17 only on CSE. 41 lesions were larger on fast-FLAIR, while no lesion was
considered larger on CSE. The numbers of periventricular (P = 0.05), cortical/subcortical (P
= 0.02) and discrete (P = 0.05) lesions detected using fast-FLAIR were higher than those
detected using CSE. The data indicates that fast-FLAIR sequences are more sensitive than
CSE in detecting multiple sclerosis lesion burden and that fast-FLAIR is a promising
technique for natural history studies and clinical trials in multiple sclerosis.15
Because demyelinating disease of the brain occasionally presents with large ringenhancing lesions on computed tomography (CT) scans and magnetic resonance images
(MRIs), Masdeu JC et al, sought to determine whether the ring pattern differed from that
found in other common brain lesions with ring enhancement. The observers rated the
contrast enhancement pattern as (1) open ring, with enhancement in the border of the lesion
abutting the white matter; (2) closed ring; or (3) uncertain. For all diagnostically certain
cases (n = 112), inter-rater agreement was excellent (kappa = 0.75). As an average of the
two reviewers, scans for 11 of 132 cases were read as uncertain; 89% of
adrenoleukodystrophy cases, 41% of the multiple sclerosis cases, 3% of tumors, and 9% of
infections were classified as having the open-ring pattern. Overall, 66% of demyelinating
lesions had an open-ring pattern compared with 7% of the non-demyelinating lesions (chi2 =
41.2, p < 0.0001). An open-ring pattern of enhancement is more likely to be associated with
demyelinating lesions than with nondemyelinating lesions.16
6.3 Objective of the study:
1. To evaluate the role of magnetic resonance imaging in white matter diseases
2. To establish an accurate diagnosis and to narrow down the differential diagnosis in
various white matter diseases
3. To assess the severity and extent of the underlying lesion in various conditions of
white matter diseases.
4. To demonstrate the different patterns of abnormal myelination in white matter
diseases.
7.
MATERIALS AND METHOD
7.1 Source of data
The main source of data for the study is patients from the following teaching hospital
attached to Bapuji Education Association, J.J.M. Medical College, Davangere.
1. Bapuji Hospital
2. Chigateri General Hospital
3. Women and child health care hospital.
Appropriate MR sequences and multiplanar imaging will be performed for every patient.
Technique:
Imaging will be done with 1.5 Tesla Philips Achieva Machine using Sense Head
coils. The following sequences will be selected as required.
1. Localizer sequence conventional spin echo.
2. Sagittal FLAIR, STIR, T1 FS
3. Axial and sagittal T1 images
4. Axial, sagittal and coronal T2 images
5. Proton density images.
6. Diffusion weighted imaging and ADC map
7. Axial Grey matter only and white matter only sequences
OPTIONAL SEQUENCES:
8. DTI and FT; IV contrast study; TOF angiography shall be included in the study as
and when required.
7.2 Method of collection of Data (including sampling procedures if any)
All patients referred to the department of Radio diagnosis with clinical history
suspicious of white matter diseases in a period of 2 years from October 2012 to October
2014 will be subjected for the study.
Initially a minimum of 30 cases are intended to be taken up, however it may be extended
up to 50 cases depending upon the availability of cases within the study period.
Inclusion criteria:
1. Patients with clinical suspicion of white matter diseases.
2. Incidental finding of white matter diseases/ lesions.
3. Patients of all age groups.
Exclusion criteria:
The study will exclude
1. Patients with clinical suspicion of post-traumatic white matter injury.
2. Patients with Intracranial tumors and metastatic disease.
3. Patients having history of claustrophobia.
4. Patient having history of metallic implants insertion, cardiac pacemakers and metallic
foreign body in situ.
Duration of study: 2 years
Data Analysis: Proportion study
7.3 Does the study require any investigations or interventions to be conducted on
patients or other humans or animals? If so please describe briefly.
Yes
The study is mainly based on investigations as radiology itself is a tool of investigation.
The study involves only humans. Informed consent would be taken after explaining about
and before any procedure. Routine investigations, laboratory investigations, ultrasonogram
and CT would be done as and when required.
7.4 Has ethical clearance been obtained from your institution in case of 7.3?
Yes
Ethical clearance has been obtained from the Research and Dissertation
Committee/Ethical Committee of the institution for this study.
8.
LIST OF REFERENCE:
1)
Blake A. Johnson. Practical approach to white matter diseases. Advanced MRI 2002from head to toe. 2002
2)
Martha A. Nowell, Robert I. Grossman, David B. Hackney, Robert A. Zimmerman,
Herbert I. Goldberg, Larissa T. Bilaniuk. MR Imaging of White Matter Diseases.
1988 August AJR 151:359-365, August 1988 0361 -803X/88/1 51 2-0359.
3)
Lakhkar BN, Aggarwal M, John JR. MRI in white matter diseases - clinico
radiological correlation. Indian J Radiol Imaging [serial online] 2002 [cited 2012 Oct
4]; 12:43-50.
4)
Banwell, B, Shroff, M, Ness, JM, et al. MRI features of pediatric multiple sclerosis.
Neurology 2007; 68(Suppl. 2):S46–S53.
5)
Engelbrecht V, Scherer A, Rassek M, et al (2002) Diffusion-weighted MR imaging in
the brain in children: findings in the normal brain and in the brain with white matter
diseases. Radiology 222: 410–418
6)
Mark A. Horsfield, Derek K. Jones. Applications of diffusion-weighted and diffusion
tensor MRI to white matter diseases – a review. 5 DEC 2002
7)
Janet Cochrane Miller, July 2012 – Volume 10, Issue 7
8)
Douaud, G., Smith, S., Jenkinson, M., Behrens, T., Johansen-Berg, H., Vickers, J.,
James, S., Voets, N., Watkins, K., Matthews, P., and James, A. (2007). Anatomicallyrelated grey and white matter abnormalities in adolescent-onset schizophrenia. Brain,
130:2375–2386.
9)
Ardekani BA, Nierenberg J, Hoptman MJ, Javitt DC, Lim KO. MRI study of white
matter diffusion anisotropy in schizophrenia. Neuroreport 2003;14(16):2025–9.
10)
van der Voorn JP, Pouwels PJ, Hart AA, Serrarens J, Willemsen MA, Kremer HP,
Barkhof F, van der Knaap MS (2006) Childhood white matter disorders: quantitative
MR imaging and spectroscopy. Radiology 241:510–517
11)
Cheng. Magnetic Resonance Imaging study of brain and incidental finding of white
matter hyperintensities and microbleeds. Medical Bulletin; 2011 Feb vol 16 No.2
12)
De Leeuw FE, de Groot JC, Achten E. et al. Prevalence of cerebral white matter
lesions in elderly people: a population based magnetic resonance imaging study: the
Rotterdam Scan Study. J Neurol Neurosurg Psychiatry.2001; 70:9-14.
13)
Tourbah A, Deschamps R, Stievenart JL, Lopez A, Zizen IMT, Caen LO et al.
Magnetic resonance imaging using FLAIR pulse sequence in white matter disease.
Neuroradiology 1996; 23(4): 217-222
14)
Kjos BO, Umansky R, Barkovich AJ. MR of the brain in children with developmental
retardation of unknown cause. AJNR 1990; 11: 1035-1040
15)
M. Filippi, C. Baratti, T. Yousry, M. A. Horsfield, S. Mammi, C. Becker, R. Voltz, S.
Spuler, A. Campi, M. F. Reiser, and G. Comi . Quantitative assessment of MRI lesion
load in multiple sclerosis: A comparison of conventional spin-echo with fast fluid
attenuated
inversion
recovery.
Brain
(1996)
119(4):
1349-1355
doi:10.1093/brain/119.4.1349
16)
Masdeu JC, Moreira J, Trasi S, Visintainer P, Cavaliere R, Grundman M. The open
ring. A new imaging sign in demyelinating disease. J Neuroimaging 1996; 6: 104–7.
9
Signature of Candidate
10
Remarks of the Guide
The study is viable and helps in management of
patients of all age groups at an early stage.
11
Name and Designation of
(in block letters)
11.1 Guide
Dr. NAVEEN S. MARALIHALLI
MD
ASSOCIATE PROFESSOR
DEPARTMENT OF RADIO-DIAGNOSIS,
J.J.M. MEDICAL COLLEGE,
DAVANGERE – 577 004.
11.2 Signature
11.3 Co-Guide (if any)
---
11.4 Signature
---
11.5 Head of Department
Dr. J .PRAMOD SETTY MD
PROFESSOR AND HEAD,
DEPARTMENT OF RADIO-DIAGNOSIS,
J.J.M. MEDICAL COLLEGE,
DAVANGERE – 577 004.
11.6 Signature
12
12.1 Remarks of the
Chairman and Principal
12.2 Signature