Share:
Share this content in WeChat
X
Clinical Article
Combined analysis based on the characteristics of intracranial atherosclerotic plaque and apparent diffusion coefficient histogram in predicting the recurrence of ischemic stroke
LUO Tong  GAO Yang  WU Qiong  HE Jinlong  WANG Zehua 

Cite this article as: LUO T, GAO Y, WU Q, et al. Combined analysis based on the characteristics of intracranial atherosclerotic plaque and apparent diffusion coefficient histogram in predicting the recurrence of ischemic stroke[J]. Chin J Magn Reson Imaging, 2024, 15(12): 94-100. DOI:10.12015/issn.1674-8034.2024.12.014.


[Abstract] Objective To explore the apparent diffusion coefficient (ADC) histogram and plaque characteristics of patients with symptomatic intracranial atherosclerotic stenosis in the prediction of ischemic stroke recurrence.Materials and Methods This study retrospectively analyzed the clinical data of 114 patients with anterior circulation ischemic stroke who were treated in the Affiliated Hospital of Inner Mongolia Medical University from June 2022 to June 2024. According to clinical and imaging data, the patients were divided into initial stroke group (n=56) and recurrent stroke group (n=58). Compare two groups of patients with clinical data, ADC histogram parameters and characteristics of intracranial atherosclerotic plaque. Compare two groups of patients with clinical data, ADC histogram parameters and characteristics of intracranial atherosclerotic plaque. Using multivariable logistic regression model analysis of independent risk factors for recurrence of ischemic stroke, the receiver operating characteristic (ROC) curve was drawn to analyze the predictive value of clinical data, ADC histogram parameters and intracranial atherosclerotic plaque characteristics for recurrence of ischemic stroke patients.Results Among 114 patients with anterior ischemic stroke, 56 had primary stroke and 58 had recurrent stroke. There were significant differences in hyperhomocysteinemia, ADCmin, kurtosis, intracranial atherosclerotic plaque load and plaque enhancement rate between the primary stroke group and the recurrent stroke group (P<0.05). Multivariate logistic regression analysis showed that kurtosis value, plaque enhancement rate and hyperhomocysteinemia were independent risk factors for ischemic stroke recurrence (P<0.05). Logistic regression model had the best overall predictive power (AUC=0.810, 95% CI: 0.734 to 0.887) were higher than any of the independent predictors, such as plaque enhancement rate (AUC=0.714, 95% CI : 0.619 to 0.808) and kurtosis value (AUC=0.702, 95% CI: 0.607 to 0.796).Conclusions The kurtosis of ADC histogram, plaque area, plaque surface irregularity and plaque enhancement rate are independently correlated with the recurrence of anterior circulation ischemic stroke. The combination of ADC histogram and atherosclerotic plaque features have a high predictive value for the recurrence of anterior circulation ischemic stroke, and can provide relevant technical support for early clinical diagnosis and treatment.
[Keywords] vascular wall imaging;stroke;stroke recurrence;plaques;magnetic resonance imaging;apparent diffusion coefficient histogram

LUO Tong   GAO Yang*   WU Qiong   HE Jinlong   WANG Zehua  

Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot010050, China

Corresponding author: GAO Y, E-mail: 1390903990@qq.com

Conflicts of interest   None.

Received  2024-07-26
Accepted  2024-12-10
DOI: 10.12015/issn.1674-8034.2024.12.014
Cite this article as: LUO T, GAO Y, WU Q, et al. Combined analysis based on the characteristics of intracranial atherosclerotic plaque and apparent diffusion coefficient histogram in predicting the recurrence of ischemic stroke[J]. Chin J Magn Reson Imaging, 2024, 15(12): 94-100. DOI:10.12015/issn.1674-8034.2024.12.014.

[1]
JIN D, SU X, JIN Y, et al. Diagnostic value of MRI perfusion-weighted imaging and diffusion-weighted imaging parameters in cerebral apoplexy[J/OL]. Am J Transl Res, 2023, 15(2): 1097-1106 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/36915724/.
[2]
BOOT E, EKKER M S, PUTAALA J, et al. Ischaemic stroke in young adults: a global perspective[J]. J Neurol Neurosurg Psychiatry, 2020, 91(4): 411-417. DOI: 10.1136/jnnp-2019-322424.
[3]
ZHAO Y, SONG P, FENG P, et al. Plaque enhancement predicts recurrence in acute ischemic stroke patients with large artery intracranial atherosclerosis[J/OL]. J Stroke Cerebrovasc Dis, 2023, 32(12): 107406 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/37837801/. DOI: 10.1016/j.jstrokecerebrovasdis.2023.107406.
[4]
SANGHA R S, PRABHAKARAN S, FELDMANN E, et al. Imaging patterns of recurrent infarction in the mechanisms of early recurrence in intracranial atherosclerotic disease (MyRIAD) Study[J/OL]. Front Neurol, 2020, 11: 615094 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/33551972/. DOI: 10.3389/fneur.2020.615094.
[5]
HUANG H T, TUNG T H, LIN M, et al. Characterizing spatiotemporal progression and prediction of infarct lesion volumes in experimental acute ischemia using quantitative perfusion and diffusion imaging[J/OL]. Appl Radiat Isot, 2021, 168: 109522 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/33290998/. DOI: 10.1016/j.apradiso.2020.109522.
[6]
SHENG H, WANG X, JIANG M, et al. Deep learning-based diffusion-weighted magnetic resonance imaging in the diagnosis of ischemic penumbra in early cerebral infarction[J/OL]. Contrast Media Mol Imaging, 2022, 2022: 6270700 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/35291425/. DOI: 10.1155/2022/6270700.
[7]
YU W, YANG J, LIU L, et al. The value of diffusion weighted imaging in predicting the clinical progression of perforator artery cerebral infarction[J/OL]. Neuroimage Clin, 2022, 35: 103117 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/35872435/. DOI: 10.1016/j.nicl.2022.103117.
[8]
NALBANT M O, ERDIL I, AKCAY N, et al. Volumetric apparent diffusion coefficient (ADC) histogram analysis of the brain in paediatric patients with hypoxic ischaemic encephalopathy[J/OL]. Pol J Radiol, 2023, 88: e399-e406 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/37808174/. DOI: 10.5114/pjr.2023.131696.
[9]
HE K, ZHANG Y, LI S, et al. Incremental prognostic value of ADC histogram analysis in patients with high-risk prostate cancer receiving adjuvant hormonal therapy after radical prostatectomy[J/OL]. Front Oncol, 2023, 13: 1076400 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/36761966/. DOI: 10.3389/fonc.2023.1076400.
[10]
HAN T, LIU X, JING M, et al. ADC histogram parameters differentiating atypical from transitional meningiomas: correlation with Ki-67 proliferation index[J]. Acta Radiol, 2023, 64(12): 3032-3041. DOI: 10.1177/02841851231205151.
[11]
BOCA P B, CARAIANI C, POPA L, et al. The utility of ADC first-order histogram features for the prediction of metachronous metastases in rectal cancer: A preliminary study[J/OL]. Biology (Basel), 2022, 11(3): 452 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/35336825/. DOI: 10.3390/biology11030452.
[12]
XU Y, YUAN C, ZHOU Z, et al. Co-existing intracranial and extracranial carotid artery atherosclerotic plaques and recurrent stroke risk: a three-dimensional multicontrast cardiovascular magnetic resonance study[J/OL]. J Cardiovasc Magn Reson, 2016, 18(1): 90 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/27908279/. DOI: 10.1186/s12968-016-0309-3.
[13]
WU G, WANG H, ZHAO C, et al. Large culprit plaque and more intracranial plaques are associated with recurrent stroke: A case-control study using vessel wall imaging[J]. AJNR Am J Neuroradiol, 2022, 43(2): 207-215. DOI: 10.3174/ajnr.A7402.
[14]
TANG M, GAO J, MA N, et al. Radiomics nomogram for predicting stroke recurrence in symptomatic intracranial atherosclerotic stenosis[J/OL]. Front Neurosci, 2022, 16: 851353 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/35495035/. DOI: 10.3389/fnins.2022.851353.
[15]
YANG D, LIU J, YAO W, et al. The MRI enhancement ratio and plaque steepness may be more accurate for predicting recurrent ischemic cerebrovascular events in patients with intracranial atherosclerosis[J]. Eur Radiol, 2022, 32(10): 7004-7013. DOI: 10.1007/s00330-022-08893-2.
[16]
COULL A J, ROTHWELL P M. Underestimation of the early risk of recurrent stroke: evidence of the need for a standard definition[J]. Stroke, 2004, 35(8): 1925-1929. DOI: 10.1161/01.STR.0000133129.58126.67.
[17]
MANDELL D M, MOSSA-BASHA M, QIAO Y, et al. Intracranial vessel wall MRI: Principles and expert consensus recommendations of the American society of neuroradiology[J]. AJNR Am J Neuroradiol, 2017, 38(2): 218-229. DOI: 10.3174/ajnr.A4893.
[18]
GAO Y, LI Z A, ZHAI X Y, et al. An interpretable machine learning model for stroke recurrence in patients with symptomatic intracranial atherosclerotic arterial stenosis[J/OL]. Front Neurosci, 2023, 17:1323270 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/38260008/. DOI: 10.3389/fnins.2023.1323270.
[19]
MA Z, HUO M, XIE J, et al. Wall characteristics of atherosclerotic middle cerebral arteries in patients with single or multiple infarcts: A high-resolution MRI Study[J/OL]. Front Neurol, 2022, 13: 934926 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/36408522/. DOI: 10.3389/fneur.2022.934926.
[20]
DRIER A, TOURDIAS T, ATTAL Y, et al. Prediction of subacute infarct size in acute middle cerebral artery stroke: comparison of perfusion-weighted imaging and apparent diffusion coefficient maps[J]. Radiology, 2012, 265(2): 511-517. DOI: 10.1148/radiol.12112430.
[21]
BROWN T A, LUBY M, SHAH J, et al. Magnetic resonance imaging in acute ischemic stroke patients with mild symptoms: An opportunity to standardize intravenous thrombolysis[J]. J Stroke Cerebrovasc Dis, 2015, 24(8): 1832-1840. DOI: 10.1016/j.jstrokecerebrovasdis.2015.04.012.
[22]
WEI L, PAN X, DENG W, et al. Predicting long-term outcomes for acute ischemic stroke using multi-model MRI radiomics and clinical variables[J/OL]. Front Med (Lausanne), 2024, 11:1328073 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/38495120/. DOI: 10.3389/fmed.2024.1328073.
[23]
WANG H, SUN Y, ZHU J, et al. Diffusion-weighted imaging-based radiomics for predicting 1-year ischemic stroke recurrence[J/OL]. Front Neurol, 2022, 13: 1012896 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/33290998/. DOI: 10.3389/fneur.2022.1012896.
[24]
WANG R, XI Y, YANG M, et al. Whole-volume ADC histogram of the brain as an image biomarker in evaluating disease severity of neonatal hypoxic-ischemic encephalopathy[J/OL]. Front Neurol, 2022, 13: 918554 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/35989925/. DOI: 10.3389/fneur.2022.918554.
[25]
KANG Y, CHOI S H, KIM Y J, et al. Gliomas: Histogram analysis of apparent diffusion coefficient maps with standard- or high-b-value diffusion-weighted MR imaging--correlation with tumor grade[J]. Radiology, 2011, 261(3): 882-890. DOI: 10.1148/radiol.11110686.
[26]
CHENG X, LIU J, LI H, et al. Incremental value of enhanced plaque length for identifying intracranial atherosclerotic culprit plaques: a high-resolution magnetic resonance imaging study[J/OL]. Insights Imaging, 2023, 14(1): 99 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/37227551/. DOI: 10.1186/s13244-023-01449-y.
[27]
JIANG H, REN K, LI T, et al. Correlation of the characteristics of symptomatic intracranial atherosclerotic plaques with stroke types and risk of stroke recurrence: a cohort study[J/OL]. Ann Transl Med, 2022, 10(12): 658 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/35845483/. DOI: 10.21037/atm-22-2586.
[28]
SUN B, WANG L, LI X, et al. Intracranial atherosclerotic plaque characteristics and burden associated with recurrent acute stroke: A 3D quantitative vessel wall MRI study[J/OL]. Front Aging Neurosci, 2021, 13: 706544 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/34393761/. DOI: 10.3389/fnagi.2021.706544.
[29]
HUANG X, TENG Z, CANTON G, et al. Intraplaque hemorrhage is associated with higher structural stresses in human atherosclerotic plaques: an in vivo MRI-based 3D fluid-structure interaction study[J/OL]. Biomed Eng Online, 2010, 9: 86 [2024-07-26]. https://pubmed.ncbi.nlm.nih.gov/21194481/. DOI: 10.1186/1475-925X-9-86.
[30]
RAN Y, WANG Y, ZHU M, et al. Higher plaque burden of middle cerebral artery is associated with recurrent ischemic stroke: A quantitative magnetic resonance imaging study[J]. Stroke, 2020, 51(2): 659-662. DOI: 10.1161/STROKEAHA.119.028405.
[31]
LIBBY P. The changing landscape of atherosclerosis[J]. Nature, 2021, 592(7855): 524-533. DOI: 10.1038/s41586-021-03392-8.
[32]
LIU Z, LI Y, CHENG F, et al. Homocysteine combined with apolipoprotein B as serum biomarkers for predicting carotid atherosclerosis in the oldest-old[J]. Clin Interv Aging, 2023, 18:1961-1972. DOI: 10.2147/CIA.S428776.
[33]
MCCULLY K S. Homocysteine metabolism, atherosclerosis, and diseases of aging[J]. Compr Physiol, 2015, 6(1): 471-505. DOI: 10.1002/cphy.c150021.
[34]
KIM J M, PARK K Y, SHIN D W, et al. Relation of serum homocysteine levels to cerebral artery calcification and atherosclerosis[J]. Atherosclerosis, 2016, 254: 200-204. DOI: 10.1016/j.atherosclerosis.2016.10.023.

PREV A semi-quantitative MRI study on brain developmental abnormalities in infants of gestational diabetic mothers
NEXT Analysis of the characteristics of carotid plaque based on HRMR-VWI and the clinical application value of Plague-RADS score
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn