Association between carotid artery perivascular fat density and cerebral small vessel disease

Predicting progression of cerebral small vessel disease: relevance of carotid perivascular fat density based on computed tomography angiography

Background

Symptomatic carotid lesions surrounded by perivascular fat have been found to be associated with the presence of cerebral small vessel disease (CSVD). In this study, we investigated the possible relationship of perivascular fat density (PFD) with CSVD and its progression, independent of the presence of carotid stenosis.

Methods

This study retrospectively evaluated consecutive patients without carotid stenosis who underwent carotid computed tomography angiography (CTA), computed tomography perfusion (CTP), and two brain magnetic resonance imaging (MRI) scans at Zhejiang Provincial People's Hospital (hospital I) from January 2019 to March 2024. Patients were categorized into three groups: without CSVD (n=34), with CSVD without progression (n=83), and with CSVD progression (n=146) according to MRI markers of CSVD. Additionally, 65 patients (including 22 with CSVD without progression and 43 with CSVD progression) were collected from Hangzhou Traditional Chinese Medicine Hospital (hospital II) for external validation. PFD was quantified using a dedicated software. The association between perfusion status on CTP and CSVD was assessed. The associations of PFD and imaging markers with the progression of CSVD were also analyzed. Six models based on PFD, significant clinical factors, and radiomic signatures were developed and validated to predict the CSVD progression.

Results

PFD values were positively associated with lacunes, cerebral microbleeds (CMBs), and white matter hyperintensities (WMH) (all P<0.05). In addition, patients with CSVD progression had higher PFD than those without [-51.38±7.35 vs. -57.19±7.31 Hounsfield unit (HU); P<0.001]. Multivariate analysis indicated that diabetes, coronary artery disease, PFD, and radiomic signatures were independent predictors of CSVD progression. Moreover, the hybrid model showed enhanced performance and yielded the highest area under the receiver operating characteristic curve (AUC) of the receiver operator characteristic curve [training: AUC =0.818, 95% confidence interval (CI): 0.758-0.876; internal validation: AUC =0.805, 95% CI: 0.690-0.908; external validation: AUC =0.807, 95% CI: 0.676-0.921].

Conclusions

This study showed that, in participants without carotid stenosis, PFD was predictive of CSVD progression, suggesting the possible involvement of the inflammation present in perivascular fat in the pathogenesis of CSVD.

Shear Wave Elastography for Carotid Artery Stiffness: Ready for Prime Time?

Carotid artery stiffness is associated with aging and atherosclerotic disease, leading to cerebrovascular events. Shear Wave Elastography (SWE) is a novel ultrasound technique offering a direct, quantitative assessment of the arterial wall elasticity. The aim of this study is to validate the technical feasibility of SWE in measuring carotid stiffness (CS). A literature search was performed across the PubMed and Scopus databases, with keywords including "carotid stiffness", "Shear Wave Elastography", "atherosclerosis", and "vascular elasticity". The findings reveal the potential of SWE in quantifying carotid Intima-Media Complex (IMC) stiffness, with implications for the early diagnosis of vascular disease, aiding in clinical decision making and prognostic assessment. Based on the findings of the literature search, a small pilot study was conducted involving 10 participants, using the Philips EPIQ Elite system for the SWE measurements. The technical analysis revealed optimizing the region of interest (ROI) size, probe positioning, and cine-loop analysis as crucial factors for obtaining accurate results. The results of the literature review and small pilot study demonstrate the potential of SWE as a non-invasive method for assessing carotid stiffness. Certain technical adjustments, such as smaller ROIs and careful probe placement, improved the accuracy and repeatability of carotid SWE measurements. Further studies are needed to assess and standardize carotid SWE across larger patient populations.

Carotid Pericarotid Fat Density: A New Predictor of Recurrent Ischemic Stroke or Transient Ischemic Attack

AIM

This study assessed the predictive value of pericarotid fat density (PFD) on carotid computed tomography angiography (CTA) for recurrent ischemic stroke or transient ischemic attack (TIA).

METHODS

In total, 739 patients who underwent CTA between January 2014 and December 2021 were retrospectively included in this study. The PFD was evaluated using carotid CTA. The clinical endpoint was recurrent ischemic stroke or transient ischemic attack (TIA). The association between PFD and the endpoint was examined using Kaplan-Meier and Cox analyses. The combination model was established using significant clinical imaging risk factors and PFD. The predictive performance of the model was assessed using the receiver operating characteristic curve (ROC).

RESULTS

A total of 739 patients (mean age: 64.28±9.44 years old, 496 males) completed a median of 3.31 years of follow-up (interquartile range, 2.11-4.05). During the follow-up period, 166 patients reached the clinical end point. The event-free survival (EFS) rate was lower in the high-PFD group than in the low-PFD group (log-rank P＜0.001). Multivariate Cox analyses showed that the PFD was associated with recurrent stroke or TIA (all P＜0.05). The combination model demonstrated excellent performance in predicting the clinical endpoint (area under the curve = 0.89). In addition, the endpoint event prognostic value was significantly improved by adding the PFD to the baseline model (C-statistic improvement: 0.61-0.84).

CONCLUSION

CTA-assessed PFD is an independent predictor of recurrent stroke or TIA.

Pericarotid Fat as a Marker of Cerebrovascular Risk

Vascular inflammation is widely recognized as an important factor in the atherosclerotic process, particularly in terms of plaque development and progression. Conventional tests, such as measuring circulating inflammatory biomarkers, lack the precision to identify specific areas of vascular inflammation. In this context, noninvasive imaging modalities can detect perivascular fat changes, serving as a marker of vascular inflammation. This review aims to provide a comprehensive overview of the key concepts related to perivascular carotid fat and its pathophysiology. Additionally, we examine the existing literature on the association of pericarotid fat with features of plaque vulnerability and cerebrovascular events. Finally, we scrutinize the advantages and limitations of the noninvasive assessment of pericarotid fat.

A novel imaging biomarker for prediction of cerebrovascular ischemic events: Pericarotid fat density

BACKGROUND

To investigate the relationship between pericarotid fat density measured in carotid CTA and vulnerable carotid plaque.

METHODS

This retrospective study included 374 participants who underwent carotid CTA between June 1, 2021, and December 1, 2021 (234 males, median age 68 years [interquartile range: 61-75]). Two groups, symptomatic and asymptomatic, were defined based on either diffusion-weighted MRI or a clinical history of acute ischemia or TIA within 6 months before or after CTA. The relationship between pericarotid fat density and cerebrovascular ischemic events was assessed using receiver operating characteristic analysis and binary logistic regression analysis.

RESULTS

In the symptomatic group (n = 135), mean pericarotid fat density (-63.3 ± 21.7 vs. -81.7 ± 16.9 HU, respectively; p < 0.001) and median maximum plaque thickness (4 [interquartile range: 3-6] vs. 3.7 [interquartile range: 2.6-4.7] mm, respectively; p = 0.002) were higher, while plaque density (42.1 ± 19.6 vs. 50.6 ± 20.4 HU, respectively; p = 0.001) was lower compared to the asymptomatic group. Pericarotid fat density (OR: 1.038, 95% CI: 1.023-1.053, p < 0.001) was identified as an independent predictor for symptomatic patients. The optimal cut-off value for pericarotid fat density predicting symptomatic patients was estimated as -74 HU (area under the curve: 0.753, 95% CI:0.699-0.808, p < 0.001). Inter-reader agreement for pericarotid fat density was found to be almost perfect (intraclass correlation coefficient: 0.818, 95% CI: 0.770-0.856, p < 0.001).

CONCLUSION

Pericarotid fat density may serve as an imaging biomarker in predicting acute cerebrovascular ischemic events.

Carotid Artery Perivascular Adipose Tissue Density and Response to Intravenous Tissue Plasminogen Activator in Acute Ischemic Stroke

The importance of Carotid Artery Perivascular Adipose Tissue Density (CAPATd), a parameter that can be readily evaluated on emergency computed tomographic angiography (CTA), in acute stroke has not been adequately clarified. We created exploratory logistic regression models to detect the interaction between the effect of CAPATd and intravenous (IV) tissue plasminogen activator (tPA) in 174 patients (mean age 71 ± 14 years, 94 women) with acute ischemic stroke treated with IV-tPA alone. The CAPATd-average mean (-60.6 ± 18.7 vs -89.8 ± 25.3 Hounsfield units (HU), P = .002) and CAPATd-maximum (14.8 ± 68.9 vs -20.5 ± 39.8 HU, P = .020) values were higher on the ipsilateral side of carotid artery stenosis >60%. CAPATd-maximum ipsilateral emerged as an independent predictor for both modified Rankin's Score 0-2 (52%) [exp(β) = .984] and mRS 0-1 outcome (32%) [exp(β) = .828] in addition to admission National Institutes of Health Stroke Scale, age and carotid plaque burden. CAPATd-maximum ipsilateral was acceptably accurate (Area under the Receiver operating characteristic Curve was .607, P = .0109 for mRS 0-2 and .613, P = .0102 for mRS 0-1). Ipsilateral CAPATd ≥ -25 HU predicted both mRS >3 and mRS >2 with usable sensitivity (59.8% and 66.07%) and specificity (63.6% and 59.68%). In conclusion, higher maximum CAPATd measured on emergency CTA indicates poorer functional prognosis in acute stroke patients treated with IV-tPA.

A new predictor of coronary artery disease in acute ischemic stroke or transient ischemic attack patients: pericarotid fat density

OBJECTIVES

The study aims to evaluate the incremental predictive value of pericarotid fat density (PFD) on head and neck computed tomography angiography (CTA) for the obstructive coronary artery disease (CAD) (≥ 50% stenosis) relative to a clinical risk model (Framingham risk score (FRS)) and the degree of carotid artery stenosis and plaque type in acute ischemic stroke (AIS) or transient ischemic attack (TIA) patients without a known history of CAD.

METHODS

In a cohort of 134 consecutive stable patients diagnosed with AIS or TIA undergoing head and neck CTA between January 2010 and December 2021, pericarotid adipose tissue density (PFD) was quantified using a dedicated software. We collected demographic and clinical data, assessed the risk of CAD using the FRS, and analyzed coronary and carotid artery CTA images. Univariate and multivariate logistic regression analyses were performed to assess associations between FRS, PFD, CTA variables, and obstructive CAD risk. Four prediction models were established to evaluate the incremental predictive value of PFD relative to FRS, stenosis degree, and plaque types. Receiver operating characteristic (ROC) curves were generated, and the areas under the curves (AUC) were compared.

RESULTS

Increasing FRS, stenosis degree, and PFD values were positively correlated with obstructive CAD (all p < 0.05). In the predictive models for obstructive CAD, the model incorporating carotid stenosis exhibited superior predictive performance compared to FRS alone (p < 0.05). Moreover, the predictive model integrating PFD demonstrated enhanced performance and yielded the highest AUC of the receiver operator characteristic curve (AUC = 0.783), with sensitivity and specificity values of 86.89% and 65.75%, respectively.

CONCLUSION

CTA-derived PFD measurements offer supplementary predictive value for obstructive CAD beyond FRS and stenosis, thereby facilitating improved risk stratification of TIA or stroke patients without a history of CAD history.

CLINICAL RELEVANCE STATEMENT

CTA-derived PFD provides incremental predictive value for obstructive coronary artery disease in acute ischemic stroke or transient ischemic attack patients without CAD history, beyond Framingham risk score and carotid artery stenosis degree, improving risk stratification.

KEY POINTS

• Pericarotid fat density is associated with obstructive coronary artery disease in acute ischemic stroke or transient ischemic attack patients. • Higher pericarotid fat density corresponds to an increased risk of obstructive coronary artery disease. • Estimation of pericarotid fat density using computed tomography angiography imparts additional predictive value for obstructive CAD in risk stratification of acute ischemic stroke or transient ischemic attack patients.

Peri-Carotid Adipose Tissue and Atherosclerosis at Carotid Bifurcation

Vulnerable carotid plaques are responsible for 20% of the ischemic strokes. The identification of these asymptomatic carotid plaques that will become symptomatic is essential but remains unclear. Our main goal was to investigate whether the amount of the peri-carotid adipose tissue, estimated by the extra-media thickness (EMT), is associated with the atherosclerotic characteristics at the carotid bifurcation in patients with PAD. An observational, prospective, single-center, longitudinal study was conducted. Overall, 177 patients were subjected to carotid Doppler ultrasound at the study admission. The following data were collected: EMT, intima-media thickness (IMT), the presence of carotid plaques, the area of the highest plaque, the presence of "acute culprit" carotid stenosis, and the grade of internal carotid stenosis. "Acute culprit" carotid stenosis was defined as a significant atherosclerotic plaque that leads to a neurologic event within 15 days. From each carotid bifurcation, a right and a left EMT were determined. We analyzed both the mean EMTs (calculated as the mean between the right and the left EMT) and the EMT ipsilateral to the carotid bifurcation. The presence of carotid plaques was associated with a higher mean EMT [Median = 1.14; IQR = 0.66 versus Median = 0.97; IQR = 0.40; p = 0.001]. A positive correlation was found between the mean EMT and IMT (right: ρ = 0.20; p = 0.010; left: ρ = 0.21; p = 0.007) and between the mean EMT and the area of the largest carotid plaque (right: ρ = 0.17; p = 0.036; left: ρ = 0.22; p = 0.004). Left carotid stenosis ≥ 70% was associated with higher ipsilateral EMT [Median = 1.56; IQR = 0.70 versus Median = 0.94; IQR = 0.42; p = 0.009]. Patients with "acute culprit" carotid stenosis had a higher ipsilateral EMT [left ipsilateral EMT: Median = 1.46; IQR = 0.63; "non-acute": Median = 0.94; IQR = 0.43; p = 0.009; right ipsilateral EMT: Median = 2.25; IQR = 0.62; "non-acute": Median = 1.00; IQR = 0.51; p = 0.015]. This difference was not found in the contra-lateral EMT. Six months after the neurologic event, EMT ipsilateral to an "acute culprit" carotid stenosis decreased (p = 0.036). The amount of peri-carotid adipose tissue, estimated with EMT, was associated with atherosclerosis at the carotid arteries. The mean EMT was associated with the features of chronic atherosclerosis lesions: the presence of carotid plaques, IMT, and the area of the highest plaque. Ipsilateral EMT was linked with "acute culprit" atherosclerotic plaque.

Associations between preprocedural carotid artery perivascular fat density and early in-stent restenosis after carotid artery stenting

Objectives

This study investigated the association between perivascular fat density (PFD) via preoperative computed tomographic angiography (CTA) and early in-stent restenosis (ISR) after carotid artery stenting (CAS).

Methods

We retrospectively evaluated 248 consecutive patients who had undergone initial CAS and received a preoperative cervical CTA examination between January 2019 and October 2020. The patients were categorized into two according to whether they sustained ISR during the 2 years postoperative follow-up period. Correlations between PFD and ISR were assessed, and multivariate regression for evaluating predictors of ISR was conducted. Receiver operating characteristic (ROC) curves were used to determine the cutoff value for the PFD.

Results

A total of 181 eligible patients (mean age 61.25 ± 10.35 years, 57 male) were enrolled. The ISR group had a higher proportion of closed-cell stents (48.8% versus 27.5%; p = 0.009) and a greater degree of residual stenosis (28[20,33] % versus 20[14.75,30] %; p < 0.001) than the non-ISR group. The ISR group had a higher mean HU value of PFD than the non-ISR group on the operated side (-42.26 ± 6.81 versus -59.66 ± 10.75; p < 0.001). The degree of residual stenosis (OR 1.146, 95%CI 1.071-1.226, p < 0.001) and PFD on the operated side (OR1.353, 95%CI 1.215-1.506, p < 0.001) were significantly associated with the ISR.

Conclusions

The occurrence of the early ISR after CAS is associated with a higher PFD on the operated side. The results indicate that PFD is a promising marker to predict the ISR after CAS.

Perfusion heterogeneity of cerebral small vessel disease revealed via arterial spin labeling MRI and machine learning

Cerebral small vessel disease (CSVD) is associated with altered cerebral perfusion. However, global and regional cerebral blood flow (CBF) are highly heterogeneous across CSVD patients. The aim of this study was to identify subtypes of CSVD with different CBF patterns using an advanced machine learning approach. 121 CSVD patients and 53 healthy controls received arterial spin label MRI, T1 structural MRI and clinical measurements. Regional CBF were used to identify distinct perfusion subtypes of CSVD via a semi-supervised machine learning algorithm. Statistical analyses were used to explore alterations in CBF, clinical measures, gray and white matter volume between healthy controls and different subtypes of CSVD. Correlation analysis was used to assess the association between clinical measures and altered CBF in each CSVD subtype. Three subtypes of CSVD with distinct CBF patterns were found. Subtype 1 showed decreased CBF in the temporal lobe and increased CBF in the parietal and occipital lobe. Subtype 2 exhibited decreased CBF in the right hemisphere of the brain, and increased CBF in the left cerebrum. Subtype 3 demonstrated decreased CBF in the posterior part of the brain, and increased CBF in anterior part of the brain. The three subtypes also differed significantly in gender (p = 0.005), the proportion of subjects with lacune (p = 0.002), with periventricular white matter hyperintensity (p = 0.043), and CSVD burden score (p = 0.048). In subtype 3, it was found that widespread decreased CBF was correlated with total CSVD burden score (r = -0.324, p = 0.029). Compared with healthy controls, the three CSVD subtypes also showed distinct volumetric patterns of white matter. The current results associate different subtypes with different clinical and imaging phenotypes, which can improve the understanding of brain perfusion alterations of CSVD and can facilitate precision diagnosis of CSVD.