Blood flow calculation method using blood vessel signal intensity gradient of brain magnetic resonance angiographic examination, and analysis system for cerebrovascular disease and stroke risk using the same

Abstract

To provide a SIG-BF calculation method of a blood vessel site according to a MRA image, and an analysis system for cerebrovascular diseases and stroke risks using the same.SOLUTION: An analytical method for cerebrovascular disease risks calculates SIG-BF of a blood vessel site according to a MRA image and predicts a cerebrovascular disease risk. Thus, it is possible to appropriately diagnose and monitor a cerebral infarction, a cerebrovascular disease, cerebral hemorrhage and the like, to determine a medium-to-long term prognosis, and to choose an optimal therapeutic agent and a therapeutic method, so that risks in treatment can be predicted.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an applied technology of MRA (Magnetic Resonance Angiography), and more particularly to a method and system for analyzing vascular images by MRA, calculating blood flow and related indices, and using the same to analyze the risk of cerebrovascular disease and stroke. [Background technology]

[0002] Cerebrovascular disease and stroke (ischemic and hemorrhagic) are diseases caused by pathological phenomena such as stenosis, blockage, rupture, or regression of blood vessels. In terms of blood flow, it can be expressed as a sudden decrease in blood flow (cerebral infarction) or a continuous low blood flow (cerebrovascular disease, vascular dementia) and blood outflow from blood vessels. Unless the brain maintains a blood flow rate of 50ml / min / 100g or more, normal brain activity is not possible. If the blood flow rate drops suddenly to less than 20-30ml / min / 100g, ischemic cerebral infarction will occur. In addition, when the cerebral blood flow rate is about 30-50ml / min / 100g and there is a lack of cerebral blood flow, degenerative brain diseases may occur due to a chronic lack of energy (oxygen and glucose). These include small vessel disease, dementia, and other neurodegenerative diseases. It is known that changes in blood flow to the area around the hematoma are an important prognostic factor for cerebral hemorrhage, and it is known that cerebral aneurysms, which cause subarachnoid hemorrhage, cause various changes in blood flow rate after rupture. Measurement of cerebral blood flow, especially accurate and continuous measurement according to the clinical changes of the patient, is essential for early diagnosis and long-term prognosis. It is also used as a predictor of disease onset, and is widely used. Cerebral blood flow is typically measured quantitatively using ultrasound (echo) examination or phase contrast MR technique, and the distribution of local blood flow in the brain is measured using SPECT (Single Photon Emission Computed Tomography) and BOLD (Blood Oxygen-Level Dependent) MRI techniques. Ultrasound is used to measure the blood flow velocity and blood vessel diameter of four blood vessels, the left and right common carotid arteries and vertebral arteries, to obtain the blood flow of each, and the total cerebral blood flow can be obtained by adding up the blood flow rates. Phase contrast MR can also be calculated by adding up the values ​​obtained by performing MR imaging on each of the four blood vessels.

[0003] Ultrasound is the most widely used method in clinical practice, but it often depends on the examiner's experience, and it is difficult to accurately grasp the changes in blood vessels, especially since it is not easy to examine the vertebral artery. Phase contrast MR has the advantage of being able to accurately measure blood flow velocity, but it is less accurate in measuring the structure and diameter of blood vessels, and above all, it has the disadvantages of having to perform an examination on each blood vessel, which is time-consuming, and takes a long time to scan, so it is not widely used in clinical practice. Therefore, there is a need for a method that can measure the blood flow rate of four or more blood vessels simultaneously in a single examination in a short time in the clinical field. Summary of the Invention [Problem to be solved by the invention]

[0004] Therefore, the present invention has been made in consideration of the above problems, and an object of the present invention is to provide a method for calculating SIG-BF of a vascular area and its related factors SIG-V, SIG-tCBF, SIG-pCBF, SIG-colBF, ΔSIG ratio and SIG-BF ratio from an MRA image using SIG, and a method and system for diagnosing, predicting and monitoring cerebrovascular disease and stroke using the same. [Means for solving the problem]

[0005] In order to achieve the above-mentioned object, a method for analyzing the risk of cerebrovascular disease according to one embodiment of the present invention includes a step of calculating SIG-BF (Signal Intensity Gradient-Blood Flow) of a vascular region from an MRA image, and a step of predicting the risk of cerebrovascular disease using the calculated SIG-BF. The calculating step calculates SIG-BF using the following formula: SIG-BF=SIG*πr 3 where SIG is the SIG at the vessel site and r is the radius of the vessel. The method for analyzing the risk of cerebrovascular disease according to an embodiment of the present invention further includes a step of calculating SIG-V (SIG-Velocity, SIG blood flow velocity) of a vascular region from an MRA image using the following formula: SIG-Velocity=SIG*r where SIG is the SIG at the vessel site and r is the radius of the vessel. SIG may be the maximum value, the minimum value, or the average value of SIG. SIG-BF includes SIG-tCBF (SIG-total Cerebral Blood Flow), and the calculating step calculates SIG-tCBF using the following formula: SIG-tCBF=SIG rt cca π(r rt cca ) 3 +SIG lt cca π(r lt cca ) 3 +SIGrt va π(r rt va ) 3 +SIG lt va π(r lt va ) 3 Here, SIG rt cca is the SIG at the right common carotid artery site, r rt cca is the radius of the right common carotid artery, SIG lt cca is the SIG at the left common carotid artery site, r lt cca is the radius of the left common carotid artery, SIG rt va is the SIG at the right vertebral artery site, r rt va is the radius of the right vertebral artery, SIG lt va is the SIG at the left vertebral artery site, r lt va is the radius of the left vertebral artery. SIG-BF includes SIG-pCBF (SIG-parenchymal cerebral blood flow), and the calculating step calculates SIG-pCBF using the following formula: SIG-pCBF=SIG rt ica π(r rt ica ) 3 +SIG lt ica π(r lt ica ) 3 +SIG rt va π(r rt va ) 3 +SIG lt va π(r lt va ) 3 Here, SIG rt ica andr rt ica The SIG and radius at the terminal site of the right internal carotid artery anterior to the branches of the anterior and middle cerebral arteries, and the SIG lt ica andr lt ica The SIG and radius at the terminal site of the left internal carotid artery before the branches of the anterior cerebral artery and middle cerebral artery, and the SIG rt va andr rt va The SIG and radius at the branch of the posterior inferior cerebellar artery anterior to the right vertebral artery, and the SIG lt va andr lt va refers to the SIG and radius at the site of the left vertebral artery anterior to the branch of the posterior inferior cerebellar artery. SIG-BF includes SIG-colBF (SIG-collateral Blood Flow), and the calculating step is SIG-colBF = SIG-tCBF - SIG-pCBF Calculate SIG-colBF using the above formula. The SIG-BF includes a SIG-BF ratio, and the calculating step calculates the SIG-BF ratio using the following formula: SIG-BF ratio=(SIG-BF-aneurysm) / (SIG-BF-preaneurysm) Here, SIG-BF-aneurysm is the SIG-BF of the aneurysm where the maximum radius is seen, and SIG-BF-preaneurysm is the SIG-BF of the normal vessel proximal to the aneurysm.

[0006] The method for analyzing the risk of cerebrovascular disease according to an embodiment of the present invention further includes a step of calculating a ΔSIG ratio of a vascular region from an MRA image using the following formula: ΔSIG ratio=(ΔSIG-aneurysm) / (ΔSIG-preaneurysm) Here, ΔSIG-aneurysm is the difference between the maximum SIG and minimum SIG of the aneurysmal vessel, and ΔSIG-preaneurysm is the difference between the maximum SIG and minimum SIG of the normal vessel proximal to the aneurysm. Meanwhile, a system for analyzing risk of cerebrovascular disease according to another embodiment of the present invention includes a processor that calculates SIG-BF of a vascular area from an MRA image and predicts risk of cerebrovascular disease using the calculated SIG-BF, an output unit that outputs calculation results and prediction results by the processor, and a storage unit that provides storage space required by the processor. Effect of the Invention

[0007] As described above, according to an embodiment of the present invention, SIG is used to extract SIG-BF of vascular regions and related factors SIG-V, SIG-tCBF, SIG-pCBF, SIG-colBF, ΔSIG ratio, and SIG-BF ratio from MRA images, enabling qualitative / quantitative analysis of cerebrovascular hemodynamics and blood flow. Furthermore, according to the embodiments of the present invention, by using the above factors, it becomes possible to accurately diagnose and monitor cerebral infarction, cerebrovascular disease, cerebral hemorrhage, etc., depending on various characteristics of vascular diseases, and it becomes possible to determine the mid- to long-term prognosis and select optimal therapeutic agents and treatment methods, thereby making it possible to predict risks in treatment. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing a method for measuring SIG-tCBF using MRA according to an embodiment of the present invention. [Diagram 2] FIG. 1 is a diagram showing a case in which SIG-pCBF is observed in an embodiment of the present invention. [Diagram 3] 1 is a diagram showing an aneurysm measurement method according to an embodiment of the present invention. [Figure 4] 1 is a diagram showing an aneurysm measurement method according to an embodiment of the present invention. [Diagram 5] 1 is a diagram showing an aneurysm measurement method according to an embodiment of the present invention. [Figure 6] 1A and 1B are diagrams showing vascular images of an asymptomatic 74-year-old female and a 37-year-old male with subarachnoid hemorrhage according to an embodiment of the present invention. [Figure 7] FIG. 1 shows a TOF MRA of a 56-year-old female patient with an asymptomatic aneurysm according to an embodiment of the present invention. [Figure 8] 1 is a block diagram showing a system for analyzing a risk of cerebrovascular disease according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] In the following, the invention will be explained in more detail with reference to the drawings. 1. SIG-BF / SIG-V The information obtained from CT, MR, or invasive angiography is all displayed in the Maximum Intensity Projection (MIP) format, which shows blood vessels in white on a black background. This emphasizes the ability to view blood vessels anatomically (e.g., stenosis). In clinical practice, TOF-MRA is similar to other angiography tests in that only MIP images are provided. However, since it is possible to derive a signal intensity gradient (SIG) from TOF-MRA, an embodiment of the present invention provides a method for deriving and imaging the characteristics of blood circulation, which corresponds to blood vessels. Specifically, in an embodiment of the present invention, a method is presented in which such blood circulation characteristics are used to derive blood flow rate, which can then be used to qualitatively / quantify the risk of stroke and cerebrovascular disease, improve diagnosis and disease prediction, and be used for pre- and post-treatment monitoring and for determining treatment methods. The signal intensity gradient-blood flow (SIG-BF) presented in the embodiment of the present invention is as follows: First, according to the Poiseuille equation, shear stress (τ) is defined as in the following Equation 1. [Formula 1] τ=4Qη / (πr 3 ) where τ is the shear stress, Q is the blood flow, η is the blood viscosity, and r is the vessel radius. In Equation 1, if the shear stress (τ) is replaced with SIG, the blood flow rate (Qartery) from the vascular wall of the blood vessel can be converted to the following equation by applying SIG (Signal Intensity Gradient). [Formula 2] Quarterly = (τπr 3 ) / 4η≒SIGπr 3 (Units, SI cm 2 ) In formula 2, SIG means the SIG (maximum, minimum, average value, etc.) at the vascular wall site of the blood vessel, and the blood flow rate obtained thereby is referred to as SIG-BF. On the other hand, in Equation 2, Qartery=velocity*πr 2 Using SIG, the blood flow velocity of the blood vessel can be obtained as follows: [Formula 3] Quarter = velocity*πr 2 ≒SIGπr 3 And in Equation 3, πr on both sides 2 If we eliminate this, we get: [Formula 4] Velocity = SIG*r(Unit, SI) In Equation 4, SIG is the blood flow velocity obtained by using SIG (maximum, minimum, average value, etc.) at the blood vessel site in question using the above Equation 4, and is referred to as SIG-V (SIG-Velocity, SIG blood flow velocity).

[0010] In the Phantom study, mean SIG values ​​obtained by TOF MRA with two 2.1 cm diameter tubes at mean flow rates of 12.5±2.3 and 8.5±2.6 L / min were 2.2±0.4 and 0.9±0.3 SI / min, respectively. SIG-BF values ​​were 8.0±1.45 and 3.27±1.09 SI·cm2, respectively, with a correlation coefficient of b=0.95, p<0.01 between SIG-BF and actual flow rates. The radius of the inner diameter of blood vessels is less than 1 cm, and the average radius of the aorta, the largest artery in the human body, is approximately 0.89 cm. In a clinical study, we have described the correlation between blood flow volume of each vessel obtained by ultrasound examination of the carotid and vertebral arteries and SIG-BF and SIG-V obtained by TOF MRA. We performed ultrasound examinations of 31 vessels in total in eight healthy adults (the right vertebral artery was not observed in one patient). Using ultrasound examinations, the time averaged mean flow velocity and diameter were obtained, and the mean blood flow volume (± standard deviation) of the left and right common carotid arteries and the left and right vertebral arteries was 5.42±0.61, 6.34±1.34, 1.42±0.54, and 0.88±0.37m, respectively. 3 / sec. Furthermore, Carotid TOF MRA was performed and SIG-BF was obtained from four blood vessels based on the above formula 2.

[0011] The mean SIG-BF of the left and right common carotid and vertebral arteries was 5.77 ± 1.67, 5.95 ± 0.48, 1.96 ± 1.00, and 0.89 ± 0.45 SI·cm, respectively. 2 The correlation index between the two tests was 0.93 (P<0.001) for the inter-arterial correlation test results for all four blood vessels, including the left carotid artery (b=0.69), right carotid artery (b=0.71), left vertebral artery (b=0.73), and right vertebral artery (b=0.61, all P values<0.01) (Figure 1). The mean blood flow velocities of the left and right common carotid arteries and vertebral arteries were 39.5±16.2, 41.1±11.8, 29.6±8.4, and 27.1±10.7 cm / sec, and the SIG-V was 16.3±4.0, 17.6±2.9, 13.1±3.5, and 10.0±2.5 SI, respectively. The correlation coefficients between the two tests of these vessels were the left carotid artery (b=0.47), right carotid artery (b=0.68), left vertebral artery (b=0.63), and right vertebral artery (b=0.64, all P values<0.01), etc., and the correlation index of the test results of the interarterial correlation for all four vessels was 0.67 (P<0.001).

[0012] 2.SIG-tCBF Since cerebrovascular diseases are directly or indirectly related to blood flow, total cerebral blood flow (tCBF) is calculated and quantitatively analyzed. In the embodiment of the present invention, a method for obtaining SIG-tCBF (SIG-total cerebral blood flow) using SIG-BF is presented. SIG-tCBF is defined as the sum of the SIG-BF of four vessels, namely, two common carotid arteries (cca) and two vertebral arteries (va), as shown in the following equation 5. [Formula 5] SIG-tCBF (SI cm 2 )=SIG rt cca π(r rt cca ) 3 +SIG lt cca π(r lt cca ) 3 +SIG rt va π(r rt va ) 3 +SIG lt va π(r lt va ) 3 Here, SIG rt cca is the SIG at the right common carotid artery site, r rt cca is the radius of the right common carotid artery, SIG lt cca is the SIG at the left common carotid artery site, r lt cca is the radius of the left common carotid artery, SIG rt va is the SIG at the right vertebral artery site, r rt va is the radius of the right vertebral artery, SIG lt va is the SIG at the left vertebral artery site, r lt va is the radius of the left vertebral artery.

[0013] Clinical studies have shown that SIG-tCBF is highly correlated with total cerebral blood flow obtained through ultrasound examination of the common carotid and vertebral arteries. The mean total cerebral blood flow obtained from ultrasound examination of eight healthy adults using time averaged mean flow velocity was 13.5 ± 1.4 cm 3The mean SIG-total cerebral blood flow obtained after Carotid TOF MRA was 14.6 ± 2.8SI cm 2 Correlation analysis between vascular ultrasound and SIG-tCBF showed a correlation index of b=0.66, p<0.01 (Figure 1). Figure 1 shows the method for measuring SIG-tCBF using MRA. Figure 1A shows the axial (xy-axis) cross-section of two common carotid arteries and two vertebral arteries, and the cross-sectional areas of four blood vessels can be obtained from one cross-section. Figure 1B shows the SIG distribution of the common carotid arteries and vertebral arteries, and the cross-section indicated by the lines is Figure 1A (2D image). The SIG (SI / mm, mean ± SD) of the left and right common carotid arteries and the left and right vertebral arteries were 4.16 ± 1.11, 4.01 ± 0.70, 5.33 ± 1.24, and 5.56 ± 0.91, respectively, and the SIG-BF (SI cm 2 ) were 3.63, 4.01, 0.88, and 0.92, respectively. The SIG-tCBF was 9.45SI cm 2 By the way, the blood flow volume of the left and right common carotid arteries and the left and right vertebral arteries obtained by carotid artery ultrasound was 4.33, 4.67, 0.85, and 0.99 cm3, respectively. 3 / sec, and the total cerebral blood flow was 10.85 cm 3 / sec.

[0014] 3. SIG-pCBF / SIG-colBF Apart from carotid TOF MRA, intracranial TOF MRA is the most widely used angiography in clinical practice. However, intracranial TOF MRA does not scan the common carotid artery or the proximal vertebral artery, but images the internal carotid artery and its distal vessels (middle cerebral artery, anterior cerebral artery), the distal vertebral artery (V4 portion) and the basilar artery. Although it is not suitable for deriving total cerebral blood flow like carotid TOF MRA, intracranial TOF MRA can only determine blood flow to the brain parenchyma and brain stem through the anterior, middle, posterior cerebral artery and the basilar artery. The method utilizes the SIG-BF of four locations: the anterior cerebral artery just before the final branch of the internal carotid artery, the internal carotid artery just before the branch of the middle cerebral artery, and the right vertebral artery before the branch of the posterior inferior cerebellar artery. This selectively determines only the blood flow to the brain stem and brain parenchyma, excluding the blood flow to the external carotid artery and ophthalmic artery. This is named SIG-pCBF (SIG-parenchymal cerebral blood flow) and is defined as the following formula 6. [Formula 6] SIG-pCBF (SI cm 2 )=SIG rt ica π(r rt ica ) 3 +SIG lt ica π(r lt ica ) 3 +SIG rt va π(r rt va ) 3 +SIG lt va π(r lt va ) 3 Here, SIG rt ica andr rt ica The SIG and radius at the terminal site of the right internal carotid artery anterior to the branches of the anterior and middle cerebral arteries, and the SIG lt ica andr lt ica The SIG and radius at the terminal site of the left internal carotid artery before the branches of the anterior cerebral artery and middle cerebral artery, and the SIG rt va andr rt va The SIG and radius at the branch of the posterior inferior cerebellar artery anterior to the right vertebral artery, and the SIG lt va andr lt va refers to the SIG and radius at the site of the left vertebral artery anterior to the branch of the posterior inferior cerebellar artery.

[0015] Figure 2 shows a case in which SIG-pCBF was observed. SIG-pCBF was obtained by adding up the SIG-BF at four locations: the terminals of the left and right internal carotid arteries and the left and right vertebral arteries (anterior to the origin of the posterior inferior cerebellar artery). Figure 2 shows a TOF MRA taken from a healthy adult. The average SIG of the left and right internal carotid arteries and the left and right vertebral arteries was 6.86, 8.48, 9.67, and 11.2 SI / mm, and the SIG-BF (SI cm 2 ) were 1.24, 1.25, 1.30, and 0.73, respectively. The blood flow rate in the cerebrum was similar, while the blood flow rate in the cerebellum and brainstem was higher in the right vertebral artery. The SIG-pCBF was 4.52SI·cm 2 It was. On the other hand, by subtracting SIG-pCBF from the above-mentioned SIG-tCBF, SIG-colBF (SIG-collateral blood flow) to the ophthalmic artery and external carotid artery can be obtained as follows. [Formula 7] SIG-colBF (SI cm 2 )=SIG-tCBF - SIG-pCBF

[0016] 4. ΔSIG ratio / SIG-BF ratio Cerebral hemorrhage is broadly divided into three types: deep cerebral hemorrhage, subarachnoid hemorrhage, and traumatic cerebral hemorrhage. Deep cerebral hemorrhage is known to be closely related to lacunar infarction and small vessel disease, while subarachnoid hemorrhage is known to be caused by the rupture of an aneurysm. Subarachnoid hemorrhage is a very dangerous disease that requires emergency surgery and intensive care, as it can cause loss of consciousness along with a very strong headache. Even if aneurysms are not present at the time of discovery, they are still a potential risk factor for future subarachnoid hemorrhage, and require very careful clinical decision-making: whether to treat the aneurysm with surgery or angioplasty using stents, or to observe the clinical progress. Conventional classification of aneurysms has mainly been based on measuring the pattern and shape. Numerous analyses to date have reported that the main risk factors for aneurysm rupture include size, shape, aspect ratio (Figs. 3 and 4), the presence or absence of blebs, and blood flow angle (Fig. 5). A study using computer simulation (CFD) has reported that cerebral aneurysms with low shear stress have a high risk of rupture. However, it is not easy to accurately measure a 3D aneurysm from 2D concepts such as length and angle of incidence, and there is a high possibility that opinions will differ between observers. It is also difficult to obtain consistent results for all patients using the same environment / techniques using computer simulations such as CFD, while realistically creating various environments such as adjusting the inlet / outlet to suit the patient and setting the appropriate 3D surface.

[0017] The main result of all angiography, including conventional TOF MRA, is to diagnose whether or not an aneurysm exists. Although previous studies have been reported on hemodynamic methods to indicate the risk of aneurysm rupture, there are currently few methods that can be used for screening in actual clinical practice. For example, Figure 6A is an image of a 74-year-old asymptomatic woman, and Figure 6B is an image of a 37-year-old man with subarachnoid hemorrhage. In both cases, an aneurysm is observed in the M2 branch of the left middle cerebral artery, but it is difficult to predict the risk of rupture from the vascular image alone. However, the MRA SIG and SIG-BF presented in the embodiments of the present invention overcome various limitations of conventional methods, provide consistent results for all patients, and can be used to predict risk. As a result of analyzing the MRA SIG of 80 unruptured cerebral aneurysms, each aneurysm could be divided into a region receiving inflow blood flow and a remaining region not receiving inflow blood flow. In other words, the phenomenon of dividing an aneurysm into a region where blood flow enters and a region where inflow blood flow recirculates can be confirmed. Figure 7 shows a TOF MRA of a 56-year-old female patient with an asymptomatic aneurysm. As shown in Figure 7A, an aneurysm is observed at the origin of the M2 of the left middle cerebral artery (arrow). Figure 7B and C show the results of SIG analysis of the aneurysm of the left middle cerebral artery in Figure 7A. The region where a high SIG value is seen from one side of the aneurysm (blood flow inflow region, broken arrow) and the region where a low value is seen on the opposite side (blood flow recirculation region, curved arrow) can be divided. Figure 7C shows an image viewed from above.

[0018] In order to assess the risk of aneurysm rupture, it is important to understand whether the aneurysm is receiving or can receive strong force. Considering the characteristics shown in Figure 7, when the risk of aneurysm rupture is high, the SIG of the blood flow inflow area is high (no problem with blood flow inflow), while at the same time, there are areas in the blood flow recirculation area where very low values ​​are seen (areas at risk of rupture), which means that the blood flow rate of the aneurysm is high. For the quantitative analysis of the risk of rupture of a cerebral aneurysm, the embodiment of the present invention presents the concepts of ΔSIG ratio (ratio of maximum difference value of SIG) and SIG-BF ratio (ratio of SIG-BF). The ΔSIG ratio is defined as follows in Equation 8. [Formula 8] ΔSIG ratio=(ΔSIG-aneurysm) / (ΔSIG-preaneurysm) Here, ΔSIG-aneurysm is the difference between the maximum SIG and the minimum SIG of the aneurysm, and ΔSIG-preaneurysm is the difference between the maximum SIG and the minimum SIG of normal blood vessels proximal to the aneurysm. The SIG-BF ratio is defined as the following Equation 9. [Formula 9] SIG-BF ratio=(SIG-BF-aneurysm) / (SIG-BF-preaneurysm) Here, SIG-BF-aneurysm is the SIG-BF at the point where the maximum radius is observed inside the aneurysm, and SIG-BF-preaneurysm is the SIG-BF of the normal vessel proximal to the aneurysm.

[0019] Analysis of the SIG and SIG-BF of the normal area before the aneurysm and the aneurysm showed that the average ΔSIG ratio of the asymptomatic group was 0.58 and the SIG-BF ratio was 2.47, while the average ΔSIG ratio of the two patients with rupture was 1.39 and the SIG-BF ratio was 11.64, showing a large difference. The area corresponding to the low SIG, which corresponds to the bottom 20% tile within the aneurysm, was 2.81 mm in the asymptomatic group. 2 , and 9.43 mm in the rupture group. 2 In the rupture group, the blood flow recirculation area with a low SIG was found to be wider.

[0020] 5. Analysis system for cerebrovascular disease risk 8 is a block diagram showing an analysis system for cerebrovascular disease risk according to an embodiment of the present invention. The analysis system for cerebrovascular disease risk according to an embodiment of the present invention is a system for predicting the risk of cerebrovascular disease by calculating SIG-BF and factors related thereto using SIG of a vascular region from an MRA image. The cerebrovascular disease risk analysis system according to an embodiment of the present invention can be realized as a computing system including a communication unit 110, an output unit 120, a processor 130, an input unit 140 and a storage unit 150, as shown in the figure. The communication unit 110 communicates with external devices and serves as a means for connecting to an external network, and in this embodiment of the present invention, receives MRA images of a patient from an MRA imaging device. The processor 130 calculates SIG-BF, SIG-V, SIG-tCBF, SIG-pCBF, SIG-colBF, ΔSIG ratio and SIG-BF ratio of a vascular region from an MRA image received via the communication unit 110. Then, the processor 130 predicts the risk of cerebrovascular disease using the calculated factors. Specifically, the processor 130 predicts the risk of cerebrovascular disease based on the correlation between the factors and cerebrovascular disease. There is no restriction on the type and number of factors to be used to predict the risk of cerebrovascular disease. Appropriate factors are applied depending on the disease. The output unit 120 is a display on which the factor values ​​and the predicted cerebrovascular disease risk calculated by the processor 130 are displayed, and the input unit 140 is a means for inputting user commands. The storage unit 150 provides storage space necessary for the processor 130 to calculate factors and predict the risk of cerebrovascular disease.

[0021] 6. Variations So far, we have explained in detail, using preferred embodiments, the method and system for calculating the SIG of a vascular area from an MRA image using the SIG and predicting the risk of cerebrovascular disease from the calculated factors. In the above embodiment, SIG-BF, SIG-V, SIG-tCBF, SIG-pCBF, SIG-colBF, ΔSIG ratio and SIG-BF ratio are presented as factors derived from the SIG of blood vessels in MRA images. Meanwhile, the technical idea of ​​the present invention may also be applied to a computer readable recording medium incorporating a computer program for performing the functions of the apparatus and method according to the present embodiment. The technical idea of ​​various embodiments of the present invention may be realized in the form of computer readable code recorded on a computer readable recording medium. The computer readable recording medium may be any data storage device that can be read by a computer and can store data. For example, the computer readable recording medium may be a ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical disk, hard disk drive, etc. The computer readable code or program stored on the computer readable recording medium may be transmitted via a network connected between computers. Although the preferred embodiment of the present invention has been described in detail above with reference to the accompanying drawings, the present invention is not limited to the above embodiment. It is clear that a person having ordinary knowledge in the technical field to which the present invention pertains can conceive of various modified or altered examples within the scope of the technical intent described in the claims, and it is understood that these also naturally belong to the technical scope of the present invention.

Claims

1. a processor for calculating a signal intensity gradient-blood flow (SIG-BF) of a blood vessel region from an MRA image and predicting a risk of cerebrovascular disease using the calculated SIG-BF; an output unit that outputs the calculation result and the prediction result of the SIG-BF by the processor; and a storage unit for providing a necessary storage space to the processor.

2. In the processor, The calculation of SIG-BF is as follows: This is carried out using the following formula: SIG-BF=SIGπr ３ 2. The system for analyzing risk of cerebrovascular disease according to claim 1, wherein SIG is SIG at a vascular site, and r is a radius of the blood vessel.

3. The processor, The SIG-V (SIG-Velocity, SIG blood flow velocity) of the vascular region was further calculated from the MRA image using the following formula: SIG-Velocity=SIG*r 2. The system for analyzing risk of cerebrovascular disease according to claim 1, wherein SIG is SIG at a vascular site, and r is a radius of the blood vessel.

4. SIG is 4. The system for analyzing risk of cerebrovascular diseases according to claim 2, wherein the SIG is any one of a maximum value, a minimum value, and an average value.

5. SIG-BF is SIG-tCBF (SIG-total Cerebral Blood Flow), The calculation of SIG-BF is as follows: Calculate SIG-tCBF using the following formula: SIG-tCBF=SIG ｒｔ ｃｃａ π(r ｒｔ ｃｃａ ) ３ +SIG ｌｔ ｃｃａ π(r ｌｔ ｃｃａ ) ３ +SIG ｒｔ ｖａ π(r ｒｔ ｖａ ) ３ +SIG ｌｔ ｖａ π(r ｌｔ ｖａ ) ３ Here, SIG ｒｔ ｃｃａ is the SIG at the right common carotid artery site, r ｒｔ ｃｃａ is the radius of the right common carotid artery, SIG ｌｔ ｃｃａ is the SIG at the left common carotid artery site, r ｌｔ ｃｃａ is the radius of the left common carotid artery, SIG ｒｔ ｖａ is the SIG at the right vertebral artery site, r ｒｔ ｖａ is the radius of the right vertebral artery, SIG ｌｔ ｖａ is the SIG at the left vertebral artery site, r ｌｔ ｖａ 2. The system for analyzing risk of cerebrovascular disease according to claim 1, wherein: is a radius of the left vertebral artery.

6. SIG-BF is SIG-pCBF (SIG-parenchymal Cerebral Blood Flow), The calculation of SIG-BF is as follows: SIG-pCBF was calculated using the following formula: SIG-pCBF=SIG ｒｔ ｉｃａ π(r ｒｔ ｉｃａ ) ３ +SIG ｌｔ ｉｃａ π(r ｌｔ ｉｃａ ) ３ +SIG ｒｔ ｖａ π(r ｒｔ ｖａ ) ３ +SIG ｌｔ ｖａ π(r ｌｔ ｖａ ) ３ Here, SIG ｒｔ ｉｃａ To ｒｔ ｉｃａ The SIG and radius at the terminal site of the right internal carotid artery before the branches of the anterior cerebral artery and the middle cerebral artery, SIG ｌｔ ｉｃａ To ｌｔ ｉｃａ The SIG and radius at the terminal site of the left internal carotid artery before the branches of the anterior cerebral artery and middle cerebral artery, SIG ｒｔ ｖａ To ｒｔ ｖａ The SIG and radius at the branch of the posterior inferior cerebellar artery anterior to the right vertebral artery, SIG ｌｔ ｖａ To ｌｔ ｖａ 6. The system for analyzing risk of cerebrovascular disease according to claim 5, wherein the SIG and radius are at the site of the left vertebral artery before the branch of the posterior inferior cerebellar artery.

7. SIG-BF is Contains SIG-colBF (SIG-collateral Blood Flow), The calculation of SIG-BF is as follows: SIG-colBF=SIG-tCBF - SIG-pCBF 7. The system for analyzing the risk of cerebrovascular diseases according to claim 6, wherein the SIG-colBF is calculated using the above formula.

8. SIG-BF is Including the SIG-BF ratio, The SIG-BF ratio is calculated using the following formula: SIG-BF ratio=(SIG-BF-aneurysm) / (SIG-BF-preaneurysm) The system for analyzing the risk of cerebrovascular disease as described in claim 1, characterized in that SIG-BF-aneurysm is the SIG-BF of the maximum radius of the aneurysm, and SIG-BF-preaneurysm is the SIG-BF of normal blood vessels proximal to the aneurysm.

9. The processor, The ΔSIG ratio of the vascular region was further calculated from the MRA image using the following formula: outputting the calculated ΔSIG ratio to the output unit; ΔSIG ratio=(ΔSIG-aneurysm) / (ΔSIG-preaneurysm) Here, ΔSIG-aneurysm is the difference between the maximum SIG and minimum SIG of the aneurysm, and ΔSIG-preaneurysm is the difference between the maximum SIG and minimum SIG of normal blood vessels proximal to the aneurysm.

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