The research thesis aims to evaluate the rate of brain artery imaging on computerized tomography images of 256 sequences; Describes common and anatomical variations of the cerebral arteries. Invite you to consult!
1 BACKGROUND The brain has an important role in coordinating all activities of the human body Brain only performs its functions when having normal anatomical structure and adequate blood supply. Inner carotid artery (ICA) and Vertebral artery (VA) are the two main sources supply blood to the brain. Because of its important role in maintaining brain activity, cerebral arteries are the target of many specialties in medicine There are many methods of anatomical research to cerebral arteries, one of which multislice computed tomography (MSCT) angiography, was known for many advantages: rapid performance, less invasive, with the ability to render artery in three dimensions, clear images, which can illustrate small vessels far away from the origin, and a large number of films that allows to compute the rare anatomical variants, as well as easy to store these films for a long time Currently, in the world as well as in Vietnam, there are many studies on anatomical cerebral artery by MSCT imaging; however, they usually focus on the cerebral artery polygon or other arteries. There are not many reports fully the anatomical of cerebral artery, especially those applied MSCT 256. Therefore, we proceed the thesis "Studying anatomy of cerebral arteries images on multislice computed tomography 256" with two objectives: 1. Evaluating the percentage of cerebral artery image displayed on multislice computed tomography 256 2. Describe the common types and anatomical variants of cerebral arteries NEW CONTRIBUTIONS OF THE THESIS Measuring the percentage of cerebral artery image displayed by MSCT 256 for the first time Figuring out the characteristics of Vietnamese cerebral vascular anatomy on length, diameter, branch, angle, morphological variation, and size variation. Suffering analyze the correlation between vascular anatomy and gender and age Full analysis about correlation between vascular anatomy and gender and age 3. Announced 58 types of cerebral artery polygon variations in Vietnam, including many variants that have not been mentioned in previous studies THESIS OUTLINE The thesis consists of 129 pages (excluding references and appendices), with the following main sections: Introduction pages; Chapter 1: Literature review 28 pages; Chapter 2: Subjects and Methods 17 pages; Chapter 3: Results 35 pages; Chapter 4: Discussion 44 pages; Conclusion: 2 pages; Recommendations: page The thesis has 28 tables, figures, 1diagram and 85 images. References included 120 documents. Five articles that are directly related to the thesis have been published. CHAPTER 1: ACKNOWLEDGEMENT 1.1. Multislice Computed tomography angiography 1.1.1. The basic principle of MSCT MSCT: the scanner is designed with a round that allows Xray tubes and receivers to rotate freely 360 degrees, allowing image data to be continuously and quickly captured while the machine is moving. The digital image data set of MSCT angiography is very large, transmitted to the host, processed images by specialized software Patients undergoing MSCT are injected iodine drug of 300400mg /ml, dose of 11.5ml / kg, large intravenous injection at 35 ml/s, total dose from 60100ml. After bolus injection, aortic artery will be observed internally, and the machine automatically scans from vertebral C1 up to the top of the skull. The thickness of slices is from 0.5 to 1.25mm, with 0.6mm rendering 1.1.2. Rendering techniques after capturing images There are many methods of rendering, we choose some methods used in the study: + Maximum Intensity Projection (MIP): technique can be quickly and easily rendered on the computer of the MSCT Images can be made in different thicknesses This technique is based on detecting the highest density pixels in a given ray, which is sensitive to signals that overlap from adjacent bone or venous structures that capture drugs + Curved Reformat (CR): this technique applies when evaluating the entire path of a long and zigzag blood vessel, such as carotid artery and VA. In this image editing technique, the artery is detected along its path with pixels to display the userselected image on successive crosssectional images. CR images are useful for screening ICA and VA + Volume Rendering (VR): nonsurface pixels are also included in the data set. This is an advantage, because when different thresholds are set, the layers of blood vessels can be peeled off or made transparently, thereby showing the underlying structures 1.1.3. The value of computed tomography angiography According to Ayarayman (2004), compared with digitized angiography when evaluating blood vessels, MSCT has 8190% sensitivity and 93% specificity. Li (2009) reported that MSCT 64 had a sensitivity of 99%, a 100% specificity; a positive predictive value (with lesions) was 100% and a negative predictive values (without injury) was 92.3% in diagnosing cerebral artery variants 1.1.4. Multislice Computed tomography 256 MSCT 256 is the 4th generation of computed tomography This is produced by the General Electric company, and is approved by the US Food and Drug (FDA) in 2014 with many advantages, such as 0.28 seconds/1 snapshot time, rotation distance/1 rotation is 16cm, good image quality; radiation dose reduces by 82% compared to previous machine According to SuKiat Chua (2013), when comparing MSCT 256 with MSCT 64 in coronary artery disease research, some conclusions were made: the MSCT 256 had a shorter scan time (4.4 ± 0.6 seconds compared to 5.0 ± 0.7 seconds, p 60 old was 20.57% while that of ≤60 old group was only 15.12% Similarly, total variants of PComA L was 43.43% and 26.75%; total variants of PComA R was 35.43% and 31.39%, respectively. Among two age groups, the group> 60 old with the highest variation rate was 24.57% in PComA R aplasia; the lowest was 2.86% found in AComA hypoplasia; group≤60 old has the highest rate of variation is 18.6% in PComA L hypoplasia; the lowest is 3.49% in AComA. Thus, the higher of age, more anatomical variants in communicating artery of which the most common are variants in PComA. Now, no similar studies have been published, we have added correlation between age and percentage of variants of coronary artery in the anatomical knowledge 4.4.2. Morphological variation of cerebral arteries + Cerebral arteries originating from ICA According to Table 3.7: group>60 old, 72% (31/43) morphological changes by age group, group≤60 old 28% Among group> 60 old, percentage of ACA variation was the highest with 67.7% (21/31); at the same time MCA has no change in this age group For group≤60 old, morphological changes in ACA are the most common in studied arteries 50% (5/10); at the same time, ICA has no change in this age group. Considering each artery being studied, ACA is 60.4% (26/43) of total morphological variations of all studied arteries; and group> 60 old, 80.77% (21/26) ACA variants Thus, the higher age, the greater the variation in ACA. In terms of variation, two artery bodies in group>60 old are the most common in ACA changes with 38.46% (10/26); however, this is rare in age group 60 has no variation. In terms of each type of variation, we did not encounter a bilateral MCA arterial variant at all ages in our study, fenestration form angiogenic variant accounting for 50% (1/2) of total MCA morphological variant and only seen in the age group ≤ 60 old With AComA, variation percentage 23.25% (10/43) of the total variation, of which the age group>60 old 70% (7/10). Thus, the higher the age of AComA was, the higher morphological variation was. Considering each variation, vascular fenestration of group> 60 old was the most 20 common among AComA variants, 40% (4/10) We did not encounter duplication variant in group 60 old (2/2) Considering each variation, we did not encounter the a bilateral ICA arterial variant in the study According to Makowicz, when studying anterior part of cerebral arterial variant, results found that with ACA, fenestration artery variation accounted for about 04% in anatomical studies, ACA azygos 0.32%; with AComA, fenestration artery variation accounted for about 10% With MCA, accessory MCA variant is derived from segment A1 with a percentage 0.34%; the second branch of MCA detached from distance of ICA accounts for about 0.22.9%. According to Dicmic, percentage of variants cerebral arteries is: with AComA, percentage of duplication artery was 18%, fenestration variation accounted for about 5.3%; with ACA, percentage fenestration segment A1 was about 04% when studying images, segment A2 accounted for about 2% when studying autopsy; with MCA, percentage duplication of MCA was 0.22.9%; fenestration of variation accounted for about 1% when studying by anatomy and 0.17% when studying by angiography; with PComA, percentage duplication artery was 2% during autopsy, however, this variation had not recorded this angiography; with ICA, variation was rate very rare, in our study percentage was 0.76% (2/261). However, studies mentioned above did not provide percentage morphological variants of cerebral arteries correlated with age group, and our research has added missing knowledge to the general anatomy knowledge + Cerebral arteries originating from BA According to Table 3.9: variations in group>60 old accounted for 65% (15/23) of morphological variations. Variations in group ≤60 old 35% of morphological variations. Thus, the higher age is, the higher incidence of morphological variation is. In terms of age group, in group>60 old, vascular fenestration variations had the largest percentage with 26.67% (4/15) because other variation groups brought together many different types of variation. When considering each type of variation separately, percentage 21 occurrence was low. Also, in this age group, there was no duplicated variant in VA and PCA, while other variants appeared primarily in PCA. In group ≤60 old, fenestration variant had the highest frequency with 62.5% (5/8); however, this variation did not appear in PCA. Also, in this age group, duplicated variant did not appear in all arteries studied With each artery, VA morphological variations accounted for 17.4% (4/23) of morphological variants of arteries originating from BA, in which fenestration variant 75% (3/4), morphological variation percentage of VA by age group was 1:1. For BA, morphological variations 34.78% (8/23), of which vascular fenestration variants 75% (6/8), and in group ≤60 old, percentage of vascular fenestration variation was times higher than group> 60 old, but if overall prevalence morphological variants of BA was calculated, percentage between groups ≤60 old and >60 old (4:4) equaled. For PCA, variation percentage 52.17% (21/23) morphological variations arteries originating from BA, of which group> 60 old accounted for 83.33%. We did not record either bifurcated or fenestration variants in PCA in our study In terms of each variation: duplicated variant 4.3% (1/23) of morphological variants of arteries originating from BA Especially, this variation appeared only in BA and only found in group> 60 old. In study, we did not find duplicated variant in ≤60 old group in all arteries originating from BA. Fenestration variant 39.13% (9/23) of morphological variants, which was mainly found in BA with 66.67% (6/9). We did not encounter this variation in PCA Fenestration variant had an equivalent distribution with 5: 4 in ≤60 old and >60 old groups. For other variants, incidence was 4.6% (12/261) in total sample size, which was mainly seen in PCA and age group> 60 old. Thus, group> 60 old had higher morphological variation in PCA than group ≤60 old Our team could not find any study assessing correlation between age and morphological variation originating from BA so that we could not compare the results 4.4.3. Variant of cerebral arterial polygon According to Figure 3.4: percentage of patients with normal cerebral arterial polygon according to typical anatomy (7 symmetrical edges) was 32.2%; percentage patients with variation of cerebral arterial polygon in this study was 67.8%; in which single variant (only 1 of the 7 components was variation) was 34.5%; multiple variation (from 2 or more components) was 33.3% Regarding gender factor, with normal cerebral arterial polygon, male 15.7% (41/261), 29.3% (41/140) of total male and 48.8% (41/84) of 22 normal cerebral arterial polygon. Similarly, females 16.5% (43/261); 30.7% (43/121) and 51.2% (43/84), respectively. For artery with single variation, male gender 16% (42/261) of sample size, 29.8% (42/141) of total males, and 46.67% (42/90) of single variants Similarly, females accounted for 18.4% (48/90); 39.67% (48/121) and 53.33% (48/90), respectively. In multiple variations, males accounted for 21.8% (57/261) of total sample, 40.7% (57/140) of total males, and 65.5% (57/87) of total multiple variations Females accounted for 11.6% (30/261); 24.8% (30/121) and 34.5% (30/87), respectively Difference was statistically significant (pfemale) of ophthalmical artery and neck segment of internal carotid artery; Determining the correlation between angle values created by bilateral vertebral arteries with gender and internalexternal carotid artery angles with age groups; Some arteries have a change of origins compared to classical anatomy such as: 1.7% of the posterior cerebral artery were from posterior communicating artery; 12.5% of the superior cerebral artery originates from posterior cerebral artery ; Determining percentage morphological and size of arterial variations; The prevalence of normal cerebral arteries polygon was 32.2%; polygons with single variation was 34.5%; polygons with multiple variation was 33.3%; 26 The study recorded 58 types of cerebral arterial polygon variants, including 18 single and 40 complex variants ... not differ among age groups 3.3. Anatomical variation 3.3.1. Size variation? ?of? ?cerebral? ?arteries? ? +? ?Cerebral? ?arteries? ?originating from ICA Table 3.6: Dimension variation? ?of? ?cerebral? ?arteries? ?originating from ICA... through this study we can confirm that values? ?of? ?angle are not related to age. Our conclusion agrees with Feng Fan 4.4.? ?Anatomy? ?of? ?variant? ?cerebral? ?arteries? ? 4.4.1. Size variation +? ?Cerebral? ?arteries? ?originating from ICA... 6,3 +? ?Cerebral? ?arteries? ?originating from BA Table 3.8: Morphological variation? ?of? ?cerebral? ?arteries? ?originating from BA by age Va Duplica Fenestr Different Variation riation tion ation