Comparison of ischemic and hemorrhagic stroke in the thalamus

Introduction

Stroke is the second leading cause of death worldwide and the third leading cause of death and disability, with an increasing burden over the past 30 years (1). Globally, ischemic strokes account for approximately 62–68% of all strokes, whereas hemorrhagic strokes represent about 32–38% (2). Among these, thalamic involvement occurs in approximately 2–3% of ischemic strokes and 2–8% of hemorrhagic strokes (3-6). Although thalamic strokes constitute a relatively small proportion, they are clinically significant due to the thalamus’ central role in relaying and integrating motor, sensory, and cognitive functions. Damage to this region can lead to distinct and debilitating syndromes, including thalamic pain, sensory loss, and cognitive dysfunction.

Despite their distinct pathophysiological mechanisms, ischemic and hemorrhagic strokes may present with overlapping symptoms, such as sudden onset contralateral hemiparesis, sensory loss, or vertical gaze palsy (7,8), which can complicate early recognition. Accurate differentiation is critical, as therapeutic strategies differ diametrically; for instance, acute ischemic stroke may require thrombolysis or antiplatelet therapy, which are strictly contraindicated in hemorrhage (9).

Unlike previous studies that compared ischemic and hemorrhagic strokes across heterogeneous brain regions, which introduces significant confounding related to lesion location, our study restricts the analysis to the thalamus. This anatomically controlled design minimizes location-related bias and allows for a direct comparison of the distinct pathophysiological mechanisms (e.g., small vessel disease burden) and prognostic factors affecting the same deep gray matter structure. In contrast, restricting analysis to the thalamus—a relatively homogeneous and anatomically well-defined structure—allows for a more controlled comparison of clinical characteristics, imaging findings, and outcomes between the two subtypes. This approach may provide more reliable insights into the clinical and prognostic differences between ischemic and hemorrhagic thalamic strokes and inform clinical decision-making.

Accordingly, this study aimed to investigate the differences in risk factors, functional outcomes, and neuroimaging markers between ischemic and hemorrhagic strokes confined to the thalamus. We hypothesized that despite the shared anatomical location, thalamic ICH and infarction would exhibit distinct risk factor profiles—particularly regarding small vessel disease burden—and that these differences would differentially influence functional outcomes. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1394/rc).

Methods

Study population

We identified patients diagnosed with acute stroke at a hospital between January 2021 and July, 2023. Our inclusion criteria were intracerebral hemorrhage (ICH) or infarction in the thalamus (Figure 1). Initially, 133 and 88 patients met the criteria for thalamic ICH and infarction, respectively. Among 133 patients diagnosed with thalamic ICH, 84 were excluded because of concomitant intraventricular hemorrhage. Consequently, the final study population comprised 49 and 88 patients in the thalamic ICH and infarction groups, respectively. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of Jeonbuk National University Hospital (No. 2024-10-017) and individual consent for this retrospective analysis was waived.

Figure 1 Thalamic infarction vs. hemorrhage. (A) Right thalamic infarction in magnetic resonance diffusion weighted image. (B) Right thalamic hemorrhage in computed tomography.

Clinical analysis

Baseline data including age, sex, body mass index (BMI), and lesion location (right/left) were collected. We analyzed the following risk factors for stroke: hypertension (HTN), diabetes mellitus (DM), atrial fibrillation, dyslipidemia, history of stroke, ischemic heart disease, smoking, and alcohol consumption. HTN was defined as a previous diagnosis, current antihypertensive medication use, or blood pressure measurement of ≥140 mmHg systolic or ≥90 mmHg diastolic. DM was defined as a previous diagnosis of DM with ongoing medication, fasting glucose ≥126 mg/dL, 2-hour postprandial glucose ≥200 mg/dL, or hemoglobin A1c (HbA1c) ≥6.5%. Atrial fibrillation included previous or new diagnoses during hospitalization. Dyslipidemia was defined as a previous diagnosis, ongoing lipid-lowering medication use, or laboratory findings of low-density lipoprotein (LDL) cholesterol ≥160 mg/dL, high-density lipoprotein (HDL) cholesterol <40 mg/dL (men) or <50 mg/dL (women), or triglycerides ≥175 mg/dL. Previous stroke history included ischemic and hemorrhagic strokes. Ischemic heart disease included previous diagnoses with ongoing medication, or a history of intervention or surgery. Smoking status and alcohol consumption were assessed on admission. Current smokers or those who had quit smoking within the past year were classified as smokers, and those who consumed >1 drink per month were classified as alcohol drinkers. Laboratory findings included white blood cell count, hemoglobin level, platelet count, erythrocyte sedimentation rate, glomerular filtration rate, sodium, potassium, C-reactive protein, aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, albumin, blood urea nitrogen, creatinine, triglyceride, HDL, LDL, total cholesterol, calcium, HbA1c, thyroid-stimulating hormone, free thyroxine, fibrinogen, homocysteine, and uric acid levels.

We analyzed the prognosis of thalamic ICH and infarction using the modified Rankin Scale (mRS) at admission, discharge, and 3 months after stroke incidence. The mRS, a common measure of global disability in patients with stroke, comprises six grades and is clinician-reported (10). Owing to loss to follow-up, the 3-month mRS scores were available for 41 and 69 patients in the thalamic ICH and thalamic infarction groups, respectively. We compared the 3-month mRS scores to analyze the long-term prognostic differences between thalamic ICH and infarction. Consistent with previous studies, we defined mRS scores of 0–2 as good outcomes (11-13).

Image analysis

In the present study, we measured hemorrhage and infarction size in patients with thalamic ICH and infarction. Neuroimaging modalities were selected according to standard clinical protocols: computed tomography (CT) was primarily used for patients with ICH because of its rapid accessibility and accuracy in detecting acute hemorrhage, whereas magnetic resonance imaging (MRI) was the modality of choice for infarction owing to its superior sensitivity in detecting small and acute ischemic lesions. MRI scans were acquired using a 3.0-T scanner (Verio; Siemens, Erlangen, Germany). Susceptibility-weighted imaging (SWI) was acquired with the following parameters: repetition time (TR) =27 ms; echo time (TE) =20 ms; flip angle =15°; slice thickness =1.5 mm; and matrix size =256×224. The imaging protocol included: (I) DWI (TR/TE =6,000/90 ms; slice thickness =5 mm; gap =1 mm; b values =0, 1,000 s/mm²); (II) T2-fluid attenuated inversion recovery (FLAIR) (TR/TE =9,000/90 ms; inversion time =2,500 ms; slice thickness =5 mm); and (III) SWI (TR/TE =27/20 ms; flip angle =15°; slice thickness =1.5 mm). CT scans were performed using a dual-source scanner (Somatom Definition Flash; Siemens) with 5-mm slice thickness. Lesion size was measured using CT in patients with ICH and MRI in patients with infarction using the ABC/2 method, as previously described (14,15). The ABC/2 method calculates volume, where A is the longest dimension along the x-axis, B is the longest dimension perpendicular to the x-axis, and C is the total length along the z-axis. When calculating C, slices with lesion volume ˂25% of the maximum lesion volume were not counted; those between 25% and 75% were multiplied by 0.5, and those exceeding 75% were multiplied by 1, following the ellipsoid volume calculation method validation by Kothari et al. (16). Acute thalamic infarction was defined as a lesion showing high signal intensity on diffusion-weighted imaging (DWI) with corresponding low signal intensity on apparent diffusion coefficient (ADC) maps. To differentiate small lacunar infarcts from dilated perivascular spaces (PVS), we excluded lesions that were <3 mm in diameter, isointense to cerebrospinal fluid on T2-FLAIR without restricted diffusion, or located in the lower basal ganglia typical of PVS.

White matter hyperintensities (WMHs) were graded according to the Fazekas scale, a measure of global hyperintense signal abnormalities around the ventricle or deep white matter (17). Because WMHs are most sensitively detected on T2-FLAIR sequences of brain MRI (18), WMHs were assessed only in patients with available T2-FLAIR (86 infarction, 17 ICH); patients without T2-FLAIR were excluded from the WMH analysis. Using the Fazekas scale, periventricular white matter lesions were classified as follows: 0, absent; 1, caps or pencil-thin lining; 2, smooth halo; 3, irregular periventricular signal extending into the deep white matter. Deep white matter lesions were classified as follows: 0, absent; 1, punctate foci; 2, beginning of confluence; and 3, large confluent areas.

SWI demonstrates the highest sensitivity for detecting microbleeds (MBs) (19). Accordingly, MBs were analyzed only in patients who underwent MRI with SWI (85 infarction, 15 ICH); patients without SWI were excluded from the MB analysis. Consistent with previous studies, MB severity was categorized based on the number of signal loss lesions as absent, mild (1–2), moderate (3–10), or severe (>10) (20).

Statistical analysis

We conducted a comparative analysis of demographic data, risk factors, and clinical outcomes between the thalamic infarction and ICH groups. The thalamic infarction group was further divided into good (3-month mRS, 0–2) and poor (3-month mRS, 3–6) outcome subgroups for analysis. We identified factors affecting poor outcomes in the thalamic infarction group. Finally, we analyzed the relationship between thalamic infarction lesion size (cm³) and National Institutes of Health Stroke Scale (NIHSS) scores. To mitigate the risk of type I errors associated with multiple comparisons without applying overly conservative corrections, statistical analyses were structured into three distinct domains: (I) comparison of baseline demographics and risk factors between stroke subtypes, (II) evaluation of small vessel disease imaging markers (WMH, MBs), and (III) identification of independent prognostic factors. In all analyses, descriptive statistics for categorical variables were presented as frequencies (%) and continuous variables as means ± standard deviations. Categorical variables were compared using Pearson’s Chi-squared test or Fisher’s exact test, whereas continuous variables were analyzed using Student’s t-test. The results of the multivariate logistic regression analysis were presented as P values, adjusted odds ratios, and 95% confidence intervals. To identify the factors associated with thalamic infarction and poor outcomes, we conducted univariate logistic regression analysis, selecting independent variables with P values ≤0.05 for inclusion in the multivariate logistic regression analysis. Given the exploratory design, no correction for multiple comparisons was applied at the univariate stage. Linear regression analysis was performed to examine the relationship between thalamic infarction lesion size and the NIHSS score. The explanatory power of the model was assessed using the coefficient of determination (R²), and multicollinearity was examined using the tolerance and variance inflation factor (VIF). Statistical significance was set at P<0.05. All analyses were performed using SPSS (version 29.0; IBM Corp., Armonk, NY, USA).

Results

We analyzed the differences between the thalamic infarction and thalamic ICH groups by comparing their clinical and demographic characteristics (Table 1). Patients in the thalamic infarction group were significantly older, whereas those in the thalamic ICH group had higher rates of WMH and MB. Representative SWI images of thalamic infarction and ICH showing MBs are presented in Figure 2. The thalamic infarction group demonstrated significantly lower mRS scores at admission and three months after stroke onset. With regard to stroke risk factors, the thalamic ICH group had higher rates of HTN, alcohol consumption, and smoking, whereas the thalamic infarction group had higher rates of DM and dyslipidemia. Notably, HTN was significantly more common in the thalamic ICH group compared to the thalamic infarction group (69.4% vs. 50.0%, P=0.028). The mean lesion volume was 4.14±4.54 cm³ in the thalamic infarction group and 7.82±6.91 cm³ in the thalamic ICH group. Laboratory findings revealed significantly higher levels of LDL and total cholesterol in the thalamic infarction group.

Figure 2 Representative SWI images of thalamic microbleeds. (A) Microbleeds in thalamic infarction. (B) Microbleeds in thalamic intracerebral hemorrhage. SWI, susceptibility-weighted imaging.

Univariate logistic regression analysis showed significant differences in Fazekas scale grade 3 WMH, MB, HTN, DM, smoking, and alcohol consumption between the groups. Multivariate logistic regression analysis revealed that MBs were significantly associated with thalamic ICH (Table 2). We compared the good- and poor-outcome subgroups in the thalamic infarction group (Table 3). Patients in the good outcome group were significantly younger and had lower Fazekas scale grades, higher BMI, and lower DM rates. Logistic regression analysis of the factors affecting poor outcomes in patients with thalamic infarction (Table 4) revealed that Fazekas scale grade 3 WMH, DM, and age were significant factors in univariate and multivariate analyses.

Linear regression analysis of the effect of lesion size on NIHSS scores (Figure 3, Table 5) showed an R² of 0.601, indicating that lesion size explained 60.1% of the variation in NIHSS scores, demonstrating a good fit for the regression model. A regression coefficient (B) of 1.610 suggested that for every unit increase in lesion size, the NIHSS score increased by an average of 1.610. A standardized regression coefficient (ß) of 0.775 indicated a substantial influence of lesion size on NIHSS scores. A VIF of 1.000 confirmed the absence of multicollinearity issues (Figure 3).

Figure 3 Linear regression analysis of thalamic infarction lesion size and the NIHSS score. NIHSS, National Institutes of Health Stroke Scale.

Discussion

Previous studies have attempted to compare ischemic and hemorrhagic stroke. However, most studies have focused on stroke in general without considering specific stroke locations, thus examining the risk factors or prognosis in isolation. Considering the diverse locations and causes of stroke, the results of previous studies are inevitably heterogeneous and often controversial. In addition, although neuroimaging markers of cerebral small vessel disease, such as WMH and MB, have been associated with stroke risk and prognosis, most studies have either examined all strokes collectively or focused on a single subtype (hemorrhagic or ischemic). Our study addressed this gap by comparing two major stroke subtypes in the thalamus.

In our cohort, thalamic infarctions were more frequent on the left side, consistent with previous reports attributing this to recognition bias, as left-sided lesions are more readily identified due to language and cognitive symptoms (21). In contrast, thalamic ICH showed a tendency toward right-sided predominance. This cannot be fully explained by recognition bias alone, since left-sided symptoms are generally more apparent. Previous studies have reported inconsistent effects of laterality in ICH: some have shown higher short-term mortality in right hemispheric hemorrhage (22), whereas others have linked left thalamic hemorrhage to worse long-term outcomes (13). These heterogeneous findings suggest that hemispheric side may influence ICH in complex ways, and our observation of right-sided predominance should therefore be interpreted with caution.

WMH burden is widely known to be associated with poor outcomes, infarct growth, recurrence, and mortality in ischemic stroke (23-25). However, a greater WMH burden is a risk factor for spontaneous ICH (26), and a meta-analysis demonstrated that WMHs increase the risk of ischemic and hemorrhagic stroke (27). In the present study, severe WMH (Fazekas scale grade 3) showed a higher proportion in the thalamic ICH group than in the thalamic infarction group. In addition to age, HTN causes arteriosclerosis, lipohyalinosis, and fibrinoid necrosis, leading to vessel wall thickening and lumen restriction, and is considered a common risk factor for small-vessel disease (28-30). The higher proportion of patients with HTN in the thalamic ICH group than that in the thalamic infarction group may have contributed to the higher rates of high-grade WMHs. In addition, the proportion of MB, another marker of small vessel disease, was significantly higher in the thalamic ICH group. Considering that a previous study indicated concurrent increases in MB and WMH in patients with acute stroke, this may have affected the WMH results (31). Future research should elucidate the mechanisms underlying WMH and ICH to develop appropriate management strategies for WMH and stroke.

MBs are considered markers of cerebral small-vessel disease, along with WMH. In our study, moderate or high MB was higher in the ICH group. MB primarily results from hypertensive vasculopathy and cerebral amyloid angiopathy, with damaged vessel walls forming microaneurysms. Massive hemorrhage occurs when blood leakage exceeds compensatory mechanisms. Recent studies have suggested that MBs are associated with an increased risk of ICH and ischemic stroke in the general population, although with a relatively larger effect size in ICH (32,33). According to the Trial of Org 10172 in the Acute Stroke Treatment classification, MB is associated with a higher incidence of lacunar infarction than large artery atherosclerosis or cardioembolism (34). While prior studies indicate that thalamic infarctions have a high MB burden compared to other ischemic stroke subtypes, our direct comparison within this study cohort confirmed that MBs were significantly more prevalent and severe in the thalamic ICH group than in the thalamic infarction group. This finding highlights the significant relationship between MBs and ICH.

Although numerous studies have attempted to compare the prognoses of ischemic and hemorrhagic strokes, the results remain inconclusive and are currently debated (35-37). However, studies focusing on isolated thalamic stroke have consistently reported worse long-term outcomes in patients with hemorrhagic stroke than in those with ischemic stroke (38). In the present study, hemorrhagic stroke in the thalamus was associated with poor functional outcomes. It is important to note that the inherent volume difference between the two pathologies—with ICH typically presenting as larger lesions due to hematoma mass—is a fundamental characteristic distinguishing the two conditions rather than a confounder that can be simply matched without introducing selection bias. This disparity may be attributed to several factors: (I) the direct mechanical disruption and mass effect of the hematoma, which contrasts with the potentially reversible penumbra in ischemia; (II) secondary neuronal injury caused by the neurotoxicity of blood breakdown products (e.g., thrombin, iron); and (III) the significantly higher burden of MBs in the ICH group, indicating a more fragile vascular bed. Moreover, thalamic infarctions are generally caused by the occlusion of small vessels such as the thalamogeniculate and tuberothalamic arteries, resulting in relatively small lesions. Conversely, thalamic hemorrhages can expand with hematomas, potentially extending into the internal capsule, third ventricle, or midbrain. This parenchymal extension exerts direct mass effect and disrupts adjacent white matter tracts, which likely contributes to the more severe neurological deficits and poorer outcomes observed in the ICH group compared to the infarction group. Our study further investigated the effect of lesion size on NIHSS scores in patients with thalamic stroke using linear regression analysis. The results revealed a trend of increasing NIHSS scores correlated with larger lesion sizes (Figure 3, Table 5). This difference in lesion characteristics may explain the observed disparity in outcomes between thalamic ischemic and hemorrhagic stroke.

Seizures are a well-recognized complication of cortical infarction but are far less common after subcortical strokes (39). Experimental studies suggest that cortical injury can disinhibit thalamic relay neurons, resulting in thalamic hyperexcitability and contributing to seizure propagation through thalamocortical circuits (40). These observations indicate that, although the thalamus may play a modulatory role in post-stroke epileptogenesis, seizures directly attributable to thalamic infarction are considered rare.

When analyzing factors associated with good and poor prognoses in the thalamic infarction groups categorized by the mRS score, severe WMH (Fazekas scale grade 3) were associated with poor prognosis in thalamic infarction and remained an independent factor in the multivariate logistic regression analysis. WMH burden is associated with poor 3-month functional outcomes in ischemic stroke (41-43). These studies attributed the WMH burden to structural changes that decrease cortical neuronal death, brain plasticity, and arteriosclerotic narrowing (36). The prognostic value of WMH may be particularly significant in thalamic infarction because of its pathophysiological similarity to small vessel diseases.

This study had some limitations. First, because this was a single-center study with a small sample size, the results may not be generalizable to the entire population of patients with thalamic stroke. Second, the retrospective nature of the study introduced the possibility of selection bias. Second, lesion volume was measured using different modalities (CT for ICH, MRI for infarction) consistent with clinical standards. While direct volumetric comparison has limitations, we applied the standardized ABC/2 method to both modalities to minimize calculation methodology bias. Finally, our analysis of WMH burden relied solely on MRI data. Only a subset of patients with ICH who underwent both CT and MRI was included in the analysis, which may have affected the statistical results. Fourth, although the thalamus is composed of functionally distinct sub-nuclei, we analyzed the thalamus as a unitary structure. Due to the retrospective clinical nature of the data, precise segmentation of individual nuclei was not feasible. Future studies utilizing high-resolution imaging and lesion network mapping are needed to elucidate nucleus-specific outcomes. Despite these limitations, this study is significant because it focused on stroke in a specific location, the thalamus, in contrast to previous studies that analyzed hemorrhagic and ischemic stroke in broader regions. Furthermore, by analyzing not only the prognosis but also the risk factors and neuroimaging markers, this study expands the understanding of thalamic stroke beyond the traditional symptom-based approach. Notably, the analysis of imaging markers related to small-vessel disease highlights the potential utility of these imaging findings for future stroke evaluations.

Conclusions

This study demonstrated that thalamic ICH has a poorer prognosis than thalamic infarction, and that MBs are independently associated with thalamic ICH. In addition, high-grade WMHs are associated with poor outcomes in patients with thalamic infarctions. Future studies should explore the potential of small vessel disease-related imaging markers as useful tools for the diagnosis and prognostic evaluation of stroke. Identifying these specific risk profiles helps clinicians anticipate prognosis and highlights the importance of aggressive small vessel disease management (e.g., blood pressure control) to prevent recurrence, particularly in the high-risk ICH group.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1394/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1394/dss

Funding: This paper was supported by Fund of Biomedical Research Institute, Jeonbuk National University Hospital.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1394/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of Jeonbuk National University Hospital (No. 2024-10-017) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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