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Correlation between Cerebral Microbleeds and White Matter Changes on MRI using Microbleed Anatomical Rating and Fazekas Scales: A Cross-sectional Study |
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Samanvitha Gode, Anand Kalegowda 1. Senior Resident, Department of Radiology, Kidwai Memorial Institute of Oncology, Bengaluru, Karnataka, India. 2. Professor, Department of Radiology, M.S. Ramaiah Medical College, Bengaluru, Karnataka, India. |
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Correspondence Address : Samanvitha Gode, S-99, KEC Colony, 3rd Stage, 3rd Cross, Basaveshwara Nagar, Bengaluru-560079, Karnataka, India. E-mail: sami3669@gmail.com |
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| ABSTRACT |  | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
: Introduction: Cerebral Microbleeds (CMBs) are small perivascular haemosiderin deposits in the brain that indicate bleeding events. The location of CMBs can provide insights into their underlying causes. CMBs found in peripheral lobar locations are often associated with cerebral amyloid angiopathy, while those occurring in deeper brain regions are more likely linked to hypertensive arteriopathy. White matter changes, known as Leukoaraiosis, have been linked to adverse cognitive functions, share risk factors with hypertension and microbleeds, and are associated with the severity of CMBs. Aim: To determine the correlation between CMBs and white matter changes on Magnetic Resonance Imagning (MRI) using the Microbleed Anatomical Rating Scale (MARS) and Fazekas scales. Materials and Methods: An analytical cross-sectional study was conducted in the Department of Radiodiagnosis, MS Ramaiah Hospitals, Bengaluru, Karnataka, India between November 2019 and June 2021, involving 65 subjects who underwent MRI brain scans at a tertiary care institute and were found to have microbleeds. Brain MRIs were performed using a 1.5 Tesla MRI Scanning Unit. Microbleeds were graded using the MARS, while white matter changes were graded using the Fazekas scale. The Chi-square test was employed to assess the significance of categorical data, and Spearman’s correlation was used to determine the correlation between MARS and Fazekas scale variables. Results: The subjects had a mean age range of 61 to 70 years, with a male-to-female ratio of 2:1. There was a significant correlation between MARS grade and Fazekas scale (p<0.001) with a correlation coefficient (r-value) of 1. The most commonly associated stroke subtype was lacunar infarct. Conclusion: There is a significant correlation between Leukoaraiosis (LA) and CMBs, indicating the end results of small vessel ischaemia and bleeding. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Keywords : Cerebral amyloid angiopathy, Cognitive dysfunction, Hypertension, Magnetic resonance imagning, Stroke | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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DOI and Others :
DOI: 10.7860/IJARS/2024/66333.2962
Date of Submission: Jul 01, 2023 Date of Peer Review: Sep 02, 2023 Date of Acceptance: Nov 13, 2023 Date of Publishing: Jan 01, 2024 AUTHOR DECLARATION: • Financial or Other Competing Interests: None • Was Ethics Committee Approval Obtained for this study? Yes • Was informed consent obtained from the subjects involved in the study? Yes • For any images presented appropriate consent has been obtained from the subjects. Yes PLAGIARISM CHECKING METHODS: • Plagiarism X-checker: Jul 05, 2023 • Manual Googling: Nov 06, 2023 • iThenticate Software: Nov 11, 2023 (13%) Etymology: Author Origin Emendations: 7 |
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| INTRODUCTION |
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The Cerebral Microbleeds (CMBs) are defined as small, well-defined low signal lesions in the lobar or deeper cerebrum observed on T2* Gradient Recalled Echo (GRE) MRI brain studies. They are bleeding events associated with cerebral Small Vessel Disease (SVD), occurring as small perivascular haemosiderin deposits (usually within macrophages) in the brain (1),(2). Risk factors associated with CMBs include age, hypertension, a history of stroke (both ischaemic and haemorrhagic), imaging markers of SVD including white matter changes/Leukoaraiosis (LA), and lacunar infarcts (3),(4),(5). Smoking, alcohol, and Chronic Obstructive Pulmonary Disease (COPD) have also been proposed as risk factors for CMBs. Impaired kidney function and Chronic Kidney Disease (CKD) are associated with CMBs, mostly of the deep and infratentorial types (3),(4),(5). Some other recently discovered associations include Alzheimer’s disease, multiple sclerosis, and Parkinson’s disease. Genetics also play a role and are linked to sporadic microbleeds and, less commonly, mutations seen in familial conditions. The most common gene polymorphism associated with sporadic microbleeds is the Apolipoprotein E (APOE) gene on chromosome 19 (5). The location of CMBs may indicate the underlying aetiology, with those occurring in peripheral lobar locations more likely to be associated with cerebral amyloid angiopathy, and those in deeper brain locations more likely linked to hypertensive arteriopathy (1),(2),(3),(4),(5),(6). On MRI, white matter changes or LA are defined as areas of high signal on the T2WI and FLAIR sequences, which may be seen in the periventricular location or in the deep white matter. They are hypothesised to be caused by reduced blood supply (ischaemia) or dilation of the perivascular spaces surrounding normal arterioles (7). The presence of LA has been previously shown to be related to adverse cognitive functions and shares risk factors with hypertension and microbleeds (8). It is also associated with the severity of Cerebral Microbleeds (CMBs) (5),(9),(10). These findings in the literature may indicate a relationship between the different locations, aetiologies, and demographic factors of patients with CMBs in relation to the presence of LA. However, only a few studies (1),(9) have been conducted to establish a relationship between Fazekas grading of SVD and the MARS scale of CMBs, if any. Among these studies, there have been no attempts to quantitatively correlate the severity of microbleeds with that of the white matter changes. Therefore, present study aimed to determine if, such a correlation exists between the two scales. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Material and Methods |
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An analytical cross-sectional study was conducted at the Department of Radiodiagnosis, MS Ramaiah Hospitals, Bengaluru, Karnataka, India from November 2019 to June 2021. The study obtained approval from the Ethics Committee (ECR number-MRMC/EC/AP-32/10-2019), and informed consent was obtained from the participants. The sample population consisted of patients who underwent brain magnetic resonance imaging and were diagnosed with CMBs. Sample size calculation: The sample size was calculated based on a previous study conducted by Yamada S et al., which reported a correlation of 0.48 between CMBs and periventricular hyperintensities (9). In the present study, considering a 1% alpha error and 90% power, the minimum sample size was determined to be 50 subjects. Inclusion criteria: Patients who underwent magnetic resonance imaging of the brain and showed evidence of CMBs were included. Exclusion criteria: Patients with head trauma and post-traumatic haemorrhage, and with intracranial space-occupying lesions, vascular malformations, and cerebral vasculitis and patients with a previous history or imaging evidence of cerebral parenchymal surgery. Study Procedure The study included 65 patients. Detailed clinical history, including admission details, clinical symptoms, medication details, and reports of various blood investigations and other imaging data, were obtained. The MRI images were acquired using a 1.5T, 18-channel Magnetic Resonance (MR) scanner (Magnetom, Avanto, Siemens, Erlangen, Germany) with a matrix coil. T1, T2, Fluid Attenuation Inversion Recovery (FLAIR), Diffusion-Weighted Imaging (DWI), and Susceptibility Weighted Imaging (SWI) sequences were performed for all patients, with additional MR Time of Flight (TOF) angiography and venography performed for selected patients. The presence of CMBs was evaluated on SWI, and grading was performed according to the Microbleed Anatomical Rating Scale (MARS) by three independent observers, as shown in [Table/Fig-1-3]. The severity of white matter changes or LA was assessed on FLAIR images using the Fazekas scale, with guidelines provided in [Table/Fig-4,5]. The severity of MARS was then correlated with the Fazekas scale. All results were correlated with clinical presentations, patient co-morbidities, and laboratory investigations. Statistical Analysis The data were entered into a Microsoft Excel spreadsheet and analysed using Statistical Packages for Social Sciences (SPSS) version 22.0 software. Categorical data were presented as frequencies and proportions. The Chi-square test was used as a significance test for categorical data. Continuous data were presented as mean and standard deviation. Spearman’s correlation was performed to determine the correlation between two variables. A p-value of <0.05 was considered statistically significant, assuming all the rules of statistical tests. MS Excel and SPSS version 22.0 (IBM SPSS Statistics, Somers NY, USA) were used for data analysis (11),(12),(13). | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Results |
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The majority of subjects were in the age group of 61 to 70 years, 33 (50.8%). A total of 43 (66.2%) were males, and 22 (33.8%) were females (Table/Fig 6). The most common clinical presentation was altered sensorium in 31 (47.4%) subjects. Co-morbidities were observed in most subjects, with 61 (93.8%) having Hypertension (HTN), 44 (67.7%) having Diabetes Mellitus (DM), 18 (27.7%) having previous Transient Ischaemic Attack (TIA)/Stroke, and 12 (18.5%) having a previous cardiac event (Table/Fig 7). There were 30 (46.2%) smokers, and 37 (56.9%) were alcoholics. These patients were on common medications, with 47 (72.3%) on statins, 61 (93.8%) on antihypertensives, 43 (66.2%) on Oral Hypoglycemic Agent (OHA)/insulin, and 47 (72.3%) on aspirin/anticoagulant. The distribution of microbleeds showed 6 (9.2%) in the basal ganglia, 12 (18.5%) in the deep region, 18 (27.7%) in the lobar region, and 29 (44.6%) with a mixed distribution of CMBs (Table/Fig 8). Based on Fazekas grading, 4 (6.2%) had Grade-1, 18 (27.7%) had Grade-2, 6 (9.2%) had Grade-3, 17 (26.2%) had Grade-4, 16 (24.6%) had Grade-5, and 4 (6.2%) had Grade-6 (Table/Fig 9). In the study, among subjects with MARS Grade-1, the majority had Fazekas Grade 2 (47.8%); among subjects with MARS Grade-2, the majority had Fazekas Grade-4 (72.7%); and among subjects with MARS Grade-3, the majority of them had Fazekas Grade-5 (41.9%) (Table/Fig 10). There was a significant correlation between MARS grade and Fazekas, i.e., an increase in MARS corresponded to an increase in Fazekas and vice versa (p<0.001) (Table/Fig 11),(Table/Fig 12). No significant interobserver variability was found among the three independent observers (Kappa value=0.95). Periventricular white matter hyperintensities were associated more with cognitive dysfunction than deep white matter hyperintensities. Cognitive dysfunction was observed in 24 (36.9%) of patients in present study, of which 2 (4.6%) had a significant loss of memory. In those with cognitive dysfunction, predominantly lobar microbleeds followed by a mixed distribution of lobar and deep microbleeds were found (Table/Fig 13). A higher systolic blood pressure was found in patients with deep and infratentorial microbleeds (Table/Fig 14). The predominant stroke subtype in present study is the ischaemic subtype, with lacunar infarct being the most common (Table/Fig 15). Patients with higher serum creatinine showed predominantly deep and infratentorial CMBs (Table/Fig 16). | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Discussion |
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The majority of subjects were aged between 61 and 70 years, with 66.1% being males. In a prospective study on stroke outpatients by Yang Q et al., 1289 consecutive patients were screened. The mean age of these patients was 60.49 years, and the proportion of male patients was 53.7% (1). This suggests that age is an independent risk factor for cerebral microbleeds. Among the ischaemic stroke subtypes, microbleeds occur more often in those with lacunar infarction (26-62%). Higher rates of CMBs are found in patients with recurrent ICH (17). In present study, 18 (27.7%) had a previous history of stroke, predominantly of the ischaemic type. The incidence of microbleeds among the stroke outpatients screened in the study by Yang Q et al., was 14.6% (1). The distribution of CMB locations in their study was as follows: 23.4% strictly lobar, 12.2% strictly deep, 6.4% strictly infratentorial, and 58.0% mixed. In the present study, the distribution was 9.2% strictly in the basal ganglia, 18.5% deep and infratentorial, 27.7% lobar, and 44.6% mixed cerebral microbleeds. Mixed CMBs had the highest incidence in both studies. In recent years, there has been increasing interest in the relevance of CMBs for cognition. Cerebral amyloid angiopathy associated with lobar Intracerebral Haemorrhage (ICH) and CMBs has long been known. In the Rotterdam study (18), a higher number of microbleeds was associated with a lower Mini Mental State Examination (MMSE) score and worse performance on tests of information processing speed and motor speed. These associations were most robust in participants with strictly lobar microbleeds. In present study, cognitive dysfunction was observed in 24 (36.9%) of patients, of which 2 (4.6%) experienced significant memory loss. Among these subjects, strictly lobar cerebral microbleeds were found in 9 (37.5%), and a mixed distribution of CMBs was found in 15 (62.5%). In another prospective study by Valenti R et al., it was found that the total number of CMBs was associated with attention/executive and fluency domains. Considering their locations, a significant correlation was found between deep CMBs and attention/executive domains, while lobar CMBs showed a significant correlation with the fluency domain (19). Hypertension is a major risk factor for microbleeds. In present study, 61 subjects (93.8%) were hypertensive, which is consistent with the findings of other research (3),(4),(20),(21). In a study by Liu W et al., systolic blood pressure variability was found to be an independent risk factor for deep and infratentorial CMB progression, while diastolic blood pressure variability was independently associated with CMB development in deep regions (21). In studies by Kakar P et al., Yates PA et al., and Kim BJ and Lee SH, it was found that microbleeds are more frequently associated with intracerebral haemorrhage (prevalence 19-83%) than with ischaemic stroke (15-35%) (2),(5),(22). According to Yang Q et al., the severity and number of CMBs at any location (graded on the MARS scale) correlated with the severity of white matter changes (graded on the Fazekas scale) (1). In another study by Yamada S et al., evidence was found to indicate that white matter hyperintensities-related brain aging is more significantly associated with cerebral microbleeds than actual aging (9). Additionally, the grade of PVH showed a stronger correlation with the number of microbleeds than the grade of DWMH. In a study by Gao T et al., both microbleeds (>grade 2) and LA in severity (>grade 2) were higher in the recurrent stroke group (14.5% and 48.4%) compared to the primary stroke group (3.8% and 7.7%) in a study by Gao T et al., (10). In present study, a statistically significant correlation was found between the grades of cerebral microbleeds and white matter changes. As the severity of microbleeds increased, so did the grade of white matter changes. In a recent study by Liu JY et al., involving 982 participants with CMBs, Diffusion Tensor Imaging (DTI) correlation was conducted. The study found that the presence of CMBs influenced the destruction of microstructural integrity of white matter, as indicated by lower fractional anisotropy, higher mean diffusivity, and higher radial diffusivity in the internal capsule and corpus callosum in these subjects (23). Limitation(s) The correlation between anticoagulants/antiplatelets and the subsequent development of CMBs could not be determined in present study as the temporal evolution of the CMBs was not assessed. The counting-based grading in the MARS scale was not always reproducible and may have led to small discrepancies between two observers. Many subjects with acute stroke did not undergo an MRI brain study based on the SWI protocol, and therefore had to be excluded from the study. As a result, the sample size does not represent the entire population with incidental cerebral microbleeds. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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