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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