A method for evaluating the quality of intracranial magnetic resonance vascular wall imaging

Abstract

The present invention discloses a method for evaluating the quality of intracranial magnetic resonance vascular wall imaging, comprising a subjective quality evaluation scale and an objective quality evaluation. The subjective quality evaluation scale assesses three aspects: the vascular wall, blood flow suppression, and motion artifacts. The objective quality evaluation is achieved by calculating three indicators: signal-to-noise ratio, contrast, and contrast-to-noise ratio. To comprehensively evaluate the quality of intracranial magnetic resonance vascular wall imaging, the method divides cerebral vascular regions, locates different segments of the vascular region, and comprehensively evaluates the imaging quality through subjective evaluation and calculation of objective quality indicators.

Description

Technical Field

[0001] The present invention belongs to the technical field of medical imaging, and in particular relates to a method for evaluating the quality of intracranial magnetic resonance vascular wall imaging. Background Art

[0002] High-resolution magnetic resonance vessel wall imaging (MR-VWI) is currently the best imaging method for noninvasively assessing intracranial atherosclerotic plaques. This imaging technique can quantitatively evaluate vulnerability characteristics such as plaque morphology and structural composition, which is of great significance for the prevention of ischemic stroke.

[0003] In clinical practice, imaging quality is affected by a variety of factors, including imaging device hardware parameters, imaging sequence design, and patient compliance. Low-quality imaging results make it difficult to accurately assess plaque characteristics and provide an effective basis for clinical decision-making. Therefore, quality evaluation of high-resolution intracranial MRI wall imaging is of great significance.

[0004] Currently, most image quality assessment (IQA) techniques are designed for evaluating the quality of natural images, with some approaches being explored for medical image quality assessment, including MRI quality assessment. These methods often rely on calculating objective image quality metrics, such as the signal-to-noise ratio (SNR), or on subjective quality assessments based on visual judgment, such as the Likert scale. These techniques often assess the overall image, with few focusing on multiple distinct locations within a medical image. However, intracranial plaques are widely distributed across different cerebral vascular locations, and MRI quality assessment techniques for plaques in different intracranial locations are currently unavailable.

[0005] Reference 1, “Clinical feasibility study of 3D intracranial magnetic resonance angiography using compressed sensing (Lin Z, Zhang X, Guo L, Wang K, Jiang Y, Hu X, Huang Y, Wei J, Ma S, Liu Y, Zhu L, Zhuo Z, Liu J, Wang X. Clinical feasibility study of 3D intracranial magnetic resonance angiography using compressed sensing. J Magn Reson Imaging. 2019 Dec; 50(6): 1843-1851. doi: 10.1002 / jmri.26752. Epub 2019 Apr 13. PMID: 30980468.,” describes a method for evaluating the image quality of intracranial magnetic resonance angiography (MRA), namely the 5-point Likert scale, which subjectively scores the imaging quality of axial source images of MRA:

[0006] 1 point, non-diagnostic. The image quality is not diagnostic due to severe artifacts, image distortion, or poor signal intensity.

[0007] 2 points, poor. Severe artifacts, obvious image distortion, or poor signal intensity, poor diagnostic image quality, and low diagnostic confidence.

[0008] 3 points, moderate. Moderate image quality, moderate reader confidence, moderate artifacts, and moderate image distortion.

[0009] 4 points, good. Good diagnostic image quality: few artifacts, minimal image distortion, and clear vascular contours.

[0010] 5 points, excellent. Excellent image quality: There are almost no artifacts and image distortion, and the major vascular structures mentioned above are well displayed.

[0011] The shortcomings of Document 1 are as follows:

[0012] 1. This scoring method is only subjective;

[0013] 2. This scoring method is not specifically for vessel wall imaging, that is, it does not evaluate the vessel wall display;

[0014] 3. This scoring method does not evaluate the intracranial arteries in segments, but only evaluates them as a whole. It cannot distinguish the differences in image quality of each segment of the blood vessel.

[0015] Reference 2, “Accelerated multi-contrast high isotropic resolution 3D intracranial vesselwall MRI using atailored k-space undersampling and partially parallelreconstruction strategy (Balu N, Zhou Z, Hippe DS, Hatsukami T, Mossa-Basha M, Yuan C. Accelerated multi-contrast high isotropic resolution 3D intracranial vesselwall MRI using atailored k-space undersampling and partially parallelreconstruction strategy. MAGMA. 2019 Jun; 32(3): 343-357. doi: 10.1007 / s10334-018-0730-8. Epub 2019 Jan 3. PMID: 30607664; PMCID: PMC6525120.),” introduces a method for evaluating the image quality of intracranial artery MRI wall imaging. The image quality is scored based on the following four aspects, with each aspect having a score ranging from 3 to 5 points: vessel wall display (wall The details are shown in Table 1:

[0016] Table 1

[0017]

[0018]

[0019] This method divides the intracranial arteries into 19 segments and scores them separately: right cavernous segment of internal carotid artery, left cavernous segment of internal carotid artery, right supraclinoid segment of internal carotid artery, left supraclinoid segment of internal carotid artery, right terminal clinoid segment of internal carotid artery, left terminal clinoid segment of internal carotid artery, right M1 segment, left M1 segment, right M2 / 3 segment, left M2 / 3 segment, right A1 segment, left A1 segment, right A2 / 3 segment, left A2 / 3 segment, right P1 segment, left P1 segment, right P2 / 3 segment, left P2 / 3 segment, and basilar artery segment.

[0020] The shortcomings of Document 2 are as follows:

[0021] 1. This evaluation method is only a subjective score;

[0022] 2. The scoring instructions for each item are not detailed enough. In particular, the evaluation of “vascular wall depiction” has only three categories, and there is a lack of detailed description of the criteria for determining each score, which may lead to low interobserver consistency.

[0023] 3. Although the evaluation is comprehensive, the contents of "image quality" and "vascular wall depiction" are highly correlated and overlapping. For example, poor image quality will inevitably lead to unclear vessel wall depiction.

[0024] Literature 3 "High-Resolution Vessel Wall Magnetic Resonance Imaging of the Middle Cerebral Artery: Comparison of 3D CUBET1-Weighted Sequence with and without Fat Suppression (Wu Y, Li F, Wang Y, Hu T, Xiao L. High-Resolution Vessel Wall Magnetic Resonance Imaging of the Middle Cerebral Artery: Comparison of 3DCUBE T1-Weighted Sequence with and without Fat Suppression. Med Sci Monit. 2020 Nov 7; 26: e928931. doi: 10.12659 / MSM.928931. PMID: 33159730; PMCID: PMC7657061.)" introduces a method specifically for evaluating the quality of magnetic resonance vessel wall imaging of the middle cerebral artery. The image quality score evaluates five aspects: noise, lumen display, vessel wall display, contrast resolution between the vessel wall and surrounding structures, and contrast resolution between plaques and vessel walls. The 5-point scoring method is used:

[0025] 1 point: very poor;

[0026] 2 points: poor;

[0027] 3 points: adequate;

[0028] 4 points: good;

[0029] 5 points: Excellent.

[0030] The shortcomings of Document 3 are as follows:

[0031] 1. This evaluation method is only a subjective score;

[0032] 2. This evaluation method only targets the middle cerebral artery within the skull, not other intracranial blood vessels, and does not specify which segment or segments of the middle cerebral artery are targeted;

[0033] 3. This evaluation method lacks a detailed description of each aspect, and the scoring scale is difficult to grasp.

[0034] Reference 4, "MR Imaging Measures of Intracranial Atherosclerosis in a Population-based Study (Qiao Y, Guallar E, Suri FK, Liu L, Zhang Y, Anwar Z, Mirbagheri S, Xie YJ, Nezami N, Intrapiromkul J, Zhang S, Alonso A, Chu H, Couper D, Wasserman BA. MR Imaging Measures of Intracranial Atherosclerosis in a Population-based Study. Radiology. 2016 Sep; 280(3): 860-8. doi: 10.1148 / radiol.2016151124. Epub 2016 Mar 29. PMID: 27022858; PMCID: PMC5006718)," introduces a method for evaluating the image quality of intracranial artery MR wall imaging. The evaluation was conducted from three aspects: blood flow suppression, wall visualization, and artifacts. Scoring is based on a 0 to 3 point scale (4 levels):

[0035] 0 points: failure;

[0036] 1 point: poor (poor with some information);

[0037] 2 points: moderate (adequate);

[0038] 3 points: excellent.

[0039] The shortcomings of Document 4 are as follows:

[0040] 1. This evaluation method is only a subjective score;

[0041] 2. There is a lack of detailed introduction to the scoring criteria, and the scoring scale is difficult to grasp;

[0042] 3. The intracranial blood vessels are evaluated as a whole, without separate evaluation of each blood vessel / each segment of blood vessel.

[0043] Literature 5 "Carotid plaque morphology and composition: initial comparison between 1.5- and 3.0-T magnetic field strengths (Underhill HR, Yarnykh VL, Hatsukami TS, Wang J, Balu N, Hayes CE, Oikawa M, Yu W, Xu D, Chu B, Wyman BT, Polissar NL, Yuan C. Carotid plaque morphology and composition: initial comparison between 1.5- and 3.0-T magnetic field strengths. Radiology. 2008 Aug; 248(2): 550-60. doi: 10.1148 / radiol.2482071114. Epub 2008 Jun 23. PMID: 18574135; PMCID: PMC2797646)" introduces a method for evaluating the magnetic resonance image quality of carotid atherosclerotic vessels. The carotid artery wall was scored using a 4-point system:

[0044] 1 point, poor quality (arterial wall and lumen edge cannot be identified);

[0045] 2 points, moderate quality (the arterial wall is visible, but some components and substructures are blurred);

[0046] 3 points, good quality (minor motion or flow artifacts, clear boundaries between vessel wall and lumen);

[0047] 4 points, excellent quality (no artifacts, details of the vessel wall structure and plaque composition are clearly visible).

[0048] The shortcomings of Document 5 are as follows:

[0049] 1. This evaluation method is only a subjective score;

[0050] 2. This evaluation method mainly evaluates the condition of the vessel wall (plaque), does not involve blood flow inhibition, and does not independently evaluate artifacts;

[0051] 3. This evaluation method only targets carotid arteries and does not involve intracranial arteries. (This is not a disadvantage in itself, but compared to the intracranial artery evaluation covered by this patent, intracranial arteries are more numerous, have many branches, have thinner lumens, and are tortuous, so a more comprehensive evaluation method may be required.)

[0052] Reference 6, “Visualization of carotid vessel wall and atherosclerotic plaque: T1-SPACE vs. compressed sensing T1-SPACE (Okuchi S, Fushimi Y, Okada T, Yamamoto A, Okada T, Kikuchi T, Yoshida K, Miyamoto S, Togashi K. Visualization of carotid vessel wall and atherosclerotic plaque: T1-SPACE vs. compressed sensing T1-SPACE. Eur Radiol. 2019 Aug; 29(8): 4114-4122. doi: 10.1007 / s00330-018-5862-8. Epub 2018 Dec 6. PMID: 30523455.)” introduces a method for evaluating the quality of 3D magnetic resonance imaging images of carotid atherosclerotic vessels. The evaluation content includes two aspects: plaque and vessel wall, using a 5-point scale:

[0053] 1 point, non-diagnostic;

[0054] 2 points, poor;

[0055] 3 points, medium (acceptable);

[0056] 4 points, good;

[0057] 5 points, excellent.

[0058] The specific scoring rules are shown in Table 2:

[0059] Table 2

[0060]

[0061] The shortcomings of Document 6 are as follows:

[0062] 1. This evaluation method is only a subjective score;

[0063] 2. This scoring method evaluates the (axial) reconstructed MRI images, not the original images;

[0064] 3. This evaluation method mainly evaluates plaque and vessel wall conditions, mixing blood flow inhibition with vessel wall evaluation, and does not involve artifacts;

[0065] 4. This evaluation method only targets carotid arteries and does not involve intracranial arteries. (This is not a disadvantage in itself, but compared to the evaluation of intracranial arteries covered by this patent, intracranial arteries are more numerous, have many branches, have thinner lumens, and are tortuous, so a more comprehensive evaluation method may be required.)

[0066] Reference 7, "Evaluation of 3D multi-contrastjoint intra- and extracranial vessel wall cardiovascular magnetic resonance (Zhou Z, Li R, Zhao X, He L, Wang X, Wang J, Balu N, Yuan C. Evaluation of 3D multi-contrastjoint intra- and extracranial vessel wall cardiovascular magnetic resonance. J Cardiovasc Magn Reson. 2015 May 27; 17(1): 41. doi: 10.1186 / s12968-015-0143-z. PMID: 26013973; PMCID: PMC4446075.)," introduces a method for evaluating the quality of magnetic resonance imaging of the head and neck arterial wall. The vessel wall is scored using four grades:

[0067] 4 points, excellent: The image shows clear boundaries of the entire blood vessel wall.

[0068] 3 points, good: MR images show good vascular wall contours, with only a small part of the boundary being blurred / invisible.

[0069] 2 points, moderate: The vessel wall is well displayed, but the boundary is partially blurred / invisible (no more than one quadrant).

[0070] 1 point, poor: The boundaries of most blood vessel walls are not visible.

[0071] The vascular locations evaluated included 10 locations: the bilateral common carotid arteries, the bilateral carotid bifurcations, the bilateral C2 segments of the internal carotid arteries, the bilateral C5 segments of the internal carotid arteries, and the bilateral M1 segments of the MCAs. Each location was selected in an area with complex blood flow, diverse surrounding tissues, and challenges in suppressing blood flow and delineating the outer wall boundary. Curved surface reconstructions were first obtained from each 3D isotropic image dataset using the open-source software Osirix. Cross-sectional images with 0.5 mm slice thickness were then acquired at all five bilateral locations, and these reconstructed 2D cross-sectional images were analyzed.

[0072] The shortcomings of Document 7 are as follows:

[0073] 1. This evaluation method is only a subjective score;

[0074] 2. This scoring method evaluates the (axial) reconstructed MRI images, not the original images;

[0075] 3. This evaluation method mainly evaluates the condition of the vessel wall and does not involve blood flow inhibition and artifacts;

[0076] Reference 8, "Three-dimensional intra- and extracranial arterial vessel wall joint imaging in patients with cerebrovascular disease (Jia L, Zhang N, Kukun H, Ren L, Zhang L, Lyu J, Liang D, Li Y, Zheng H, Jia W, Liu X. Three-dimensional intra- and extracranial arterial vessel wall joint imaging in patients with cerebrovascular disease. Eur J Radiol. 2020 May; 126:108921. doi:10.1016 / j.ejrad.2020.108921. Epub 2020 Feb 26. PMID:32145599)," introduces a method for evaluating the quality of magnetic resonance imaging of the head and neck arterial walls. The evaluated vessels are divided into three parts: the anterior circulation, the posterior circulation, and the internal carotid artery. The vessel wall is scored using a 4-point scale:

[0077] 1 point, unclear vascular wall contour (less than 50% of the intracranial or carotid artery vascular wall is visible, and the edge is obviously blurred);

[0078] 2 points, the vascular wall contour is acceptable (more than 50% of the intracranial or carotid artery vascular wall is visible, with moderately blurred edges);

[0079] 3 points, the vascular wall contour is well displayed (the intracranial or carotid artery vascular wall is visible, with slightly blurred edges);

[0080] 4 points: excellent vascular wall contour (intracranial or carotid artery vascular wall is visible with sharp edges).

[0081] Disadvantages of Document 8:

[0082] 1. This evaluation method is only a subjective score;

[0083] 2. This evaluation method mainly evaluates the condition of the vessel wall and does not involve blood flow inhibition and artifacts;

[0084] 3. Although this evaluation method includes the main arteries in the neck and the brain, the distinction is relatively rough (both the anterior and posterior circulations include many blood vessels, and the internal carotid artery runs inside and outside the skull and can be divided into several segments), and no segmented evaluation of the blood vessels is performed.

[0085] In summary, there is an urgent need to develop a comprehensive evaluation method for the quality of intracranial magnetic resonance vascular wall imaging. Summary of the Invention

[0086] The purpose of the present invention is to provide a method for evaluating the quality of intracranial magnetic resonance vascular wall imaging, which divides the cerebral vascular area, locates the vascular area of different segments, and makes a comprehensive assessment of the imaging quality through subjective evaluation and objective quality index calculation methods.

[0087] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0088] A first aspect of the present invention provides a method for evaluating the quality of intracranial magnetic resonance vascular wall imaging, comprising a subjective quality evaluation scale and an objective quality evaluation;

[0089] The subjective quality assessment scale evaluates three aspects: vascular wall, blood flow inhibition, and motion artifacts;

[0090] The clear display of the blood vessel wall is the main goal of magnetic resonance imaging of the blood vessel wall and the primary content of image quality evaluation;

[0091] (1) If the evaluation sequence is 3D whole-brain vessel wall imaging, the intracranial vessels are evaluated in segments, including the bilateral internal carotid arteries (intracranial cavernous sinus segment to communicating segment), the bilateral horizontal segments of the middle cerebral arteries (M1 segments), the bilateral intracranial segments of the vertebral arteries (V4 segments), and the basilar artery, a total of 7 segments;

[0092] (2) If the evaluated sequence is 2D vessel wall imaging, the scanned target vessel segment is evaluated;

[0093] The blood vessel wall is scored using a 4-point system, with higher scores representing better image quality.

[0094] 1 point, extremely poor, unable to distinguish the blood vessel wall;

[0095] 2 points, poor, the vessel wall is visible, but the edge is obviously blurred;

[0096] 3 points, moderate, the vessel wall is visible, the edge is moderately blurred, and some component substructures are blurred;

[0097] 4 points, excellent, the vessel wall is visible, the edge is clear and sharp, and the local vessel wall structure may be slightly blurred.

[0098] The blood flow inhibition evaluation is based on a segmented evaluation of the intracranial blood vessels, including the bilateral internal carotid arteries (intracranial cavernous sinus segment to communicating segment), the bilateral horizontal segments of the middle cerebral arteries (M1 segments), the bilateral intracranial segments of the vertebral arteries (V4 segments), and the basilar artery, a total of seven blood vessel segments;

[0099] The blood flow inhibition was scored on a 3-point scale, with higher scores indicating more adequate blood flow inhibition within the vascular lumen.

[0100] 1 point, blood signal suppression failed and the lumen showed high signal;

[0101] 2 points, insufficient suppression of blood signals and uneven lumen signals;

[0102] 3 points: blood signal suppression is sufficient and the lumen shows complete low signal.

[0103] The motion artifact evaluation is to evaluate whether the entire sequence of images has artifacts;

[0104] The motion artifact is scored using a 3-point system, with higher scores representing lighter motion artifacts.

[0105] 1 point, obvious motion artifact;

[0106] 2 points, slight motion artifact;

[0107] 3 points, no motion artifact.

[0108] The objective quality evaluation is quantitatively reflected by calculating three indicators: signal-to-noise ratio (SNR), contrast ratio (CR), and contrast-to-noise ratio (CNR) of the pipe wall area.

[0109] The SNR is calculated as follows:

[0110] SNR A =SI A / S

[0111] SNR A : signal-to-noise ratio of the arterial wall; SI A : signal intensity of the arterial wall; S: standard deviation of the noise.

[0112] The calculation of CR requires the selection of a reference tissue with a relatively stable signal. Previous studies have found that the signal of muscle tissue is relatively stable. Therefore, the muscle signal intensity in the same sequence is used as a reference. The calculation formula is as follows:

[0113] CR=(SI A -SI M ) / (SI A +SI M )

[0114] CR: contrast of arterial wall; SI A : signal intensity of arterial wall; SI M : Signal intensity of reference tissue (muscle).

[0115] The calculation formula of the CNR is as follows:

[0116] CNR=SNR A -SNR M

[0117] CNR: contrast-to-noise ratio of the arterial wall; SNR A : signal-to-noise ratio of the arterial wall; SNR M : Signal-to-noise ratio of reference tissue (muscle).

[0118] The method for evaluating the quality of intracranial magnetic resonance vascular wall imaging of the present invention mainly evaluates diseases such as atherosclerosis, but can also evaluate normal intracranial arteries, including vascular stenosis or occlusion caused by arteritis or thrombosis, but does not include vascular dilation caused by aneurysms and arterial dissections.

[0119] Due to the adoption of the above technical solution, the present invention has the following advantages and beneficial effects:

[0120] To comprehensively evaluate the quality of intracranial arterial wall MRI, the present invention presents a method for evaluating intracranial MRI vessel wall imaging quality. This method divides cerebral vascular regions, locates different segments of the vascular area, and comprehensively assesses imaging quality through subjective evaluation and objective quality index calculation. Compared to existing evaluation methods, this method boasts high repeatability and enhanced feasibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0121] Figure 1 Schematic diagram of the steps of the present invention.

[0122] Figure 2 Schematic diagram of subjective scoring of vascular walls using the 3D T1WI sequence of the present invention.

[0123] Figure 3 Schematic diagram of the subjective scoring of blood flow suppression in the 3D T1WI sequence of the present invention.

[0124] Figure 4 Schematic diagram of subjective scoring of motion artifacts in 3D T1WI sequence of the present invention.

[0125] Figure 5 Schematic diagram of the measurement site for objective quality evaluation of 3D T1WI sequence of the present invention.

[0126] Figure 6 Schematic diagram of subjective scoring of vascular walls using the 2D T2WI sequence of the present invention.

[0127] Figure 7 Schematic diagram of the subjective scoring of blood flow inhibition using the 2D T2WI sequence of the present invention.

[0128] Figure 8 Schematic diagram of subjective scoring of motion artifacts in 2D T2WI sequence of the present invention.

[0129] Figure 9 Schematic diagram of the measurement site for objective quality evaluation of 2D T2WI sequence of the present invention. DETAILED DESCRIPTION

[0130] In order to explain the present invention more clearly, the present invention is further described below in conjunction with preferred embodiments. Those skilled in the art should understand that the following specific description is illustrative rather than restrictive and should not be used to limit the scope of protection of the present invention.

[0131] Example 1

[0132] The following combination Figure 1 , Figure 1 The following is a schematic diagram of the steps of the present invention. Taking the evaluation of the vascular wall imaging quality of the 3D T1WI sequence as an example, for the convenience of description, the sagittal 3D T1WI covering the whole brain is used as an example for introduction.

[0133] A method for evaluating the quality of intracranial magnetic resonance vascular wall imaging includes a subjective quality evaluation scale and an objective quality evaluation; the subjective quality evaluation scale evaluates three aspects: vascular wall, blood flow suppression, and motion artifacts.

[0134] Step S1: Acquire magnetic resonance images

[0135] Generally speaking, 3D MRI is a large-scale thin-slice scan, including whole-brain or head-neck combined scans, and the scanning direction is mostly sagittal or coronal. In this embodiment, sagittal 3D T1WI original images are obtained from the hospital information system for evaluation.

[0136] Step S2: Evaluate the quality of vascular wall imaging

[0137] Clear visualization of the vessel wall is the primary goal of MRI imaging and, therefore, the primary consideration for image quality assessment. Using 3D T1WI sequences, intracranial vessels were evaluated segmentally, including the bilateral internal carotid arteries (from the cavernous sinus segment to the communicating segment), the bilateral horizontal segments of the middle cerebral arteries (M1 segments), the bilateral intracranial segments of the vertebral arteries (V4 segments), and the basilar artery, for a total of seven segments. The vessel wall was scored on a 4-point scale, with higher scores indicating better image quality, as shown in Table 3.

[0138] Table 3 Subjective scoring criteria for vascular wall

[0139]

[0140] Note: When the lumen of a blood vessel is blocked for various reasons, such as severe proximal stenosis leading to distal lumen collapse and occlusion, or the lumen is filled with pathological substances such as atherosclerotic plaques and / or thrombi, the inner contour of the vessel wall is difficult to discern. However, the outer contour of the vessel wall can be evaluated according to the standards in the table above, thereby obtaining a corresponding image quality score.

[0141] Figure 2 This is a schematic diagram of the subjective scoring of the vascular wall using the 3D T1WI sequence of the present invention. The box represents a certain level of the M1 segment of the MCA, with 2A being 1 point, 2B being 2 points, 2C being 3 points, and 2D being 4 points.

[0142] Step S3: Evaluate blood flow inhibition effect

[0143] Blood flow inhibition is also assessed by segmental evaluation of the intracranial vessels, including the bilateral internal carotid arteries (from the cavernous sinus segment to the communicating segment), the bilateral horizontal segments of the middle cerebral arteries (M1 segments), the bilateral intracranial segments of the vertebral arteries (V4 segments), and the basilar artery, for a total of seven segments. Scoring is based on a 3-point scale, with higher scores indicating more adequate blood flow inhibition within the vessel lumen, as shown in Table 4.

[0144] Table 4 Subjective scoring criteria for blood flow inhibition

[0145]

[0146] Note: The image can be appropriately magnified during evaluation, but avoid excessive magnification to assess blood flow inhibition, as otherwise the lumen will rarely contain a pure black signal. If the "vascular wall" cannot be distinguished (1 point), blood flow inhibition cannot be evaluated. Pathological intraluminal high signal filling (e.g., plaque / thrombus / significant wall thickening with occlusion / mixed conditions) is not due to a failure of blood flow signal suppression, but blood flow inhibition is certainly insufficient, so this is assigned a score of 2.

[0147] like Figure 3 As shown, Figure 3 Schematic diagram of subjective scoring of blood flow suppression using 3D T1WI sequences of the present invention. 3A is 2 points, with the arrow indicating blood flow artifacts within the lumen; 3B is 3 points.

[0148] Step S4: Evaluate motion artifacts

[0149] The evaluation of motion artifacts is to assess whether the entire sequence of images has artifacts, without the need for vessel segmentation evaluation. The scoring system uses a 3-point scale, with higher scores indicating lighter motion artifacts. The specific scores are shown in Table 5:

[0150] Table 5 Subjective scoring criteria for motion artifacts

[0151] Fraction Scoring Criteria 1 point Obvious motion artifacts 2 points Slight motion artifacts 3 points No motion artifacts

[0152] like Figure 4As shown, Figure 4 Schematic diagram of subjective scoring of motion artifacts in 3D T1WI sequences of the present invention. 4A is 1 point, 4B is 2 points, and 4C is 3 points.

[0153] Step S4: Calculate objective indicators of the image (objective quality evaluation)

[0154] Objective image quality evaluation is achieved by calculating three indicators: signal-to-noise ratio (SNR), contrast ratio (CR), and contrast-to-noise ratio (CNR).

[0155] In this embodiment, the arterial wall is the main evaluation target, and the SNR is calculated as follows:

[0156] SNR A =SI A / S

[0157] SNR A : signal-to-noise ratio of the arterial wall; SI A : signal intensity of the arterial wall; S: standard deviation of noise. Noise measurement is preferably performed on the empty background surrounding the image (not human tissue or other material). If human tissue fills the image, the air within the sinuses, nasopharynx, or oropharynx is used.

[0158] The calculation of CR requires the selection of a reference tissue with a relatively stable signal. Previous studies have found that muscle tissue has a relatively stable signal, so the muscle signal intensity in the same sequence is used as a reference. Depending on the imaging range, the nuchal muscles, extraocular muscles, or lateral pterygoid muscles within the field of view can be selected as reference tissues. The calculation formula is as follows:

[0159] CR=(SI A -SI M ) / (SI A +SI M )

[0160] CR: contrast of arterial wall; SI A : signal intensity of arterial wall; SI M : Signal intensity of reference tissue (muscle).

[0161] The CNR is calculated as follows:

[0162] CNR=SNR A -SNR M

[0163] CNR: contrast-to-noise ratio of the arterial wall; SNR A : signal-to-noise ratio of the arterial wall; SNR M: Signal-to-noise ratio of reference tissue (muscle).

[0164] Figure 5 This is a schematic diagram of the measurement locations for objective quality evaluation of 3D T1WI sequences in the present invention. The signal intensity of the arterial wall is measured by outlining the wall of the intracranial ICA segment (W), the noise is measured at the edge of the image (N), and the reference tissue is the neck muscle (M). The objective indicator calculation results for this example are: SNR A =14.23, CR=0.61, CNR=9.61.

[0165] Example 2

[0166] The following is an example of evaluating the imaging quality of the vascular wall in the 2D T2WI sequence.

[0167] A method for evaluating the quality of intracranial magnetic resonance vascular wall imaging includes a subjective quality evaluation scale and an objective quality evaluation; the subjective quality evaluation scale evaluates three aspects: vascular wall, blood flow suppression, and motion artifacts.

[0168] Step S1: Acquire magnetic resonance images

[0169] 2D MRI tube wall imaging is typically performed perpendicular to the course of a particular intracranial vessel. The most common scanning directions are oblique sagittal scans perpendicular to the M1 segment of the middle cerebral artery (MCA) or transverse scans perpendicular to the basilar artery (BA). In this example, sagittal 2D T2WI raw images were obtained from a hospital information system for evaluation.

[0170] Step S2: Evaluate the quality of vascular wall imaging

[0171] The clear display of the blood vessel wall was evaluated using the same criteria as in Table 3 in Example 1.

[0172] like Figure 6 As shown, Figure 6 This is a schematic diagram of the subjective scoring of the vascular wall using the 2D T2WI sequence of the present invention. The box represents a certain level of the BA, with 6A being 2 points, 6B being 3 points, and 6C being 4 points.

[0173] Step S3: Evaluate blood flow inhibition effect

[0174] The blood flow inhibitory effect was evaluated using the same criteria as in Table 4 in Example 1.

[0175] like Figure 7 As shown, Figure 7Figure 7A shows a subjective scoring method for blood flow suppression using a 2D T2WI sequence. The image 7A shows a layer of the axial BA. The mixed high signal within the BA lumen in 7A is judged to be a blood flow artifact, so it is scored as 1. The image 7B shows a layer of the axial BA. The mixed high signal within the BA lumen in 7B is judged to be a thrombus or plaque, not a true blood flow artifact, so it is scored as 2. The image 7C shows flocculent high signal blood flow artifacts within the BA, which is scored as 2. The image 7D is scored as 3.

[0176] Step S4: Evaluate motion artifacts

[0177] The motion artifacts were evaluated using the same criteria as those in Table 5 in Example 1.

[0178] Figure 8 Schematic diagram of subjective scoring of motion artifacts in 2D T2WI sequences of the present invention. 8A is 1 point, 8B is 2 points, and 8C is 3 points.

[0179] Step S4: Calculate objective indicators of the image

[0180] The objective quality of the image is calculated in the same manner as in Example 1.

[0181] Figure 9 This is a schematic diagram of the measurement locations for objective quality evaluation of the 2D T2WI sequence of the present invention. In the oblique sagittal 2D T2WI sequence, the target vessel imaged is the horizontal segment of the unilateral MCA. The signal intensity of the arterial wall is measured by outlining the MCA wall (W). Since there is no empty background in the scanning field, the noise measurement location is selected at the maxillary sinus cavity (N), and the reference tissue measurement is selected at the extraocular muscle (M). The objective indicator calculation results of this example are: SNR A =10.23, CR=0.51, CNR=7.61.

[0182] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as above in terms of a preferred embodiment, it is not intended to limit the present invention. Any technician familiar with this patent can make slight changes or modifications to equivalent embodiments using the above technical content without departing from the scope of the technical solution of the present invention. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the solution of the present invention.

Claims

1. A method for evaluating the quality of intracranial magnetic resonance vascular wall imaging, characterized in that: It includes subjective quality evaluation scale and objective quality evaluation; The subjective quality assessment scale evaluates three aspects: vascular wall, blood flow inhibition, and motion artifacts; The clear display of the blood vessel wall is the main goal of magnetic resonance imaging of the blood vessel wall and the primary content of image quality evaluation; The blood flow inhibition evaluation is performed by segmenting the intracranial blood vessels, including the bilateral internal carotid arteries, the bilateral horizontal segments of the middle cerebral arteries, the bilateral intracranial segments of the vertebral arteries, and the basilar artery, a total of 7 blood vessels; The motion artifact evaluation is to evaluate whether the entire sequence of images has artifacts; The objective quality evaluation is quantitatively reflected by calculating the three indicators of signal-to-noise ratio (SNR), contrast ratio (CR), and contrast-to-noise ratio (CNR) of the pipe wall area. The SNR is calculated as follows: SNR A =SIT A / S SNR A : signal-to-noise ratio of the arterial wall; SI A : signal intensity of the arterial wall; S: standard deviation of noise; The calculation of CR requires the selection of a reference tissue with a stable signal. Previous studies have found that the signal of muscle tissue is stable. Therefore, the muscle signal intensity in the same sequence is used as a reference. The calculation formula is as follows: CR=(SI A -SI M ) / (SI A +SI M ) CR: contrast of arterial wall; SI A : signal intensity of arterial wall; SI M : signal intensity of reference tissue; The calculation formula of the CNR is as follows: CNR=SNR A -SNR M CNR: contrast-to-noise ratio of the arterial wall; SNR A : signal-to-noise ratio of the arterial wall; SNR M : Signal-to-noise ratio of the reference tissue.

2. The method for evaluating the quality of intracranial magnetic resonance vascular wall imaging according to claim 1, wherein: If the evaluation sequence is 3D whole-brain vessel wall imaging, the intracranial vessels are evaluated in segments, including the bilateral internal carotid arteries, the bilateral horizontal segments of the middle cerebral arteries, the bilateral intracranial segments of the vertebral arteries, and the basilar artery, a total of 7 segments.

3. The method for evaluating the quality of intracranial magnetic resonance vascular wall imaging according to claim 1, wherein: If the evaluated sequence is 2D vessel wall imaging, the scanned target blood vessel segment is evaluated.

4. The method for evaluating the quality of intracranial magnetic resonance vascular wall imaging according to claim 1, wherein: The vascular wall was scored using a 4-point system, with higher scores indicating better image quality. 1 point, extremely poor, unable to distinguish the blood vessel wall; 2 points, poor, the vessel wall is visible, but the edge is obviously blurred; 3 points, moderate, the vessel wall is visible, the edge is moderately blurred, and some component substructures are blurred; 4 points, excellent, the vessel wall is visible, the edge is clear and sharp, and slight blurring of the local vessel wall structure is allowed.

5. The method for evaluating the quality of intracranial magnetic resonance vascular wall imaging according to claim 1, wherein: The blood flow inhibition was scored on a 3-point scale, with higher scores indicating more adequate blood flow inhibition within the vascular lumen. 1 point, blood signal suppression failed and the lumen showed high signal; 2 points, insufficient suppression of blood signals and uneven lumen signals; 3 points: blood signal suppression is sufficient and the lumen shows complete low signal.

6. The method for evaluating the quality of intracranial magnetic resonance vascular wall imaging according to claim 1, characterized in that: The motion artifact was scored on a 3-point scale, with higher scores indicating lighter motion artifacts. 1 point, obvious motion artifact; 2 points, slight motion artifact; 3 points, no motion artifact.

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