Acute ischemic stroke (AIS) is a leading cause of mortality and long-term disability worldwide, accounting for nearly 80% of all stroke cases. Early diagnosis and timely intervention are critical determinants of patient outcome. Magnetic resonance imaging (MRI), particularly diffusion-weighted imaging (DWI), has revolutionized the early detection and evaluation of cerebral ischemia.

DWI exploits the restricted diffusion of water molecules occurring during cytotoxic edema in acute ischemia, allowing detection of infarction within minutes of onset. It has been reported to achieve sensitivity rates of 88–100% and specificity up to 95–100% in acute stroke diagnosis [6]. Compared to computed tomography, DWI provides superior detection of early ischemic changes and better delineation of infarct core.

Beyond diagnosis, DWI offers quantitative biomarkers such as infarct volume, apparent diffusion coefficient (ADC), and DWI-based Alberta Stroke Programme Early CT Score (ASPECTS). These parameters have emerged as valuable tools for predicting clinical severity and functional outcome. Studies have demonstrated strong correlations between DWI lesion characteristics and neurological deficit scores such as the National Institutes of Health Stroke Scale (NIHSS) and functional disability assessed by the modified Rankin Scale (mRS) [1,2].

Recent advances in imaging analytics, including radiomics and machine learning applied to DWI and ADC data, have further improved the ability to predict long-term outcomes and guide individualized treatment strategies [7-10]. These developments emphasize the evolving role of MRI from a purely diagnostic modality to a prognostic and decision-support tool in stroke care.

However, despite the increasing reliance on MRI in stroke evaluation, there remains variability in how DWI parameters are utilized in clinical practice. There is a need for comprehensive evaluation of the correlation between DWI findings and clinical outcomes to standardize their use.

This study aims to assess the relationship between DWI-derived imaging parameters and clinical outcomes in patients with acute ischemic stroke, thereby establishing their prognostic significance.

2.1 Study Design and Setting

This was a prospective observational study conducted.

2.2 Study Population

Inclusion Criteria:

• Patients aged ≥18 years
• Clinically suspected acute ischemic stroke
• Presentation within 24 hours of symptom onset
• MRI brain including DWI performed

Exclusion Criteria:

• Hemorrhagic stroke
• Stroke mimics
• Contraindications to MRI
• Poor-quality imaging

2.3 Sample Size

A sample size of approximately 50 patients was considered adequate based on prior studies demonstrating strong correlations between DWI parameters and clinical outcomes (r >0.8)

2.4 Imaging Protocol

All patients underwent MRI using a 1.5T/3T scanner. The imaging protocol included:

• T1-weighted imaging
• T2-weighted imaging
• FLAIR
• Diffusion-weighted imaging
• ADC maps

DWI was acquired using b-values of 0 and 1000 s/mm².

2.5 Imaging Analysis

DWI Lesion Volume

Calculated using ABC/2 method or volumetric software. Larger infarct volumes were expected to correlate with worse outcomes.

DWI-ASPECTS

Applied in MCA territory infarcts. Scores ranged from 0–10; lower scores indicated larger infarct burden.

ADC Values

Mean ADC values measured within infarct region. Lower ADC values indicated severe ischemia and irreversible injury

2.6 Clinical Assessment

Stroke Severity:

Assessed using NIHSS:

• Mild (<5)
• Moderate (5–15)
• Severe (>15)

Functional Outcome:

Assessed using mRS:

• Favorable: 0–2
• Unfavorable: 3–6

2.7 Statistical Analysis

• Continuous variables expressed as mean ± SD
• Correlation analysis using Pearson/Spearman tests
• Multivariate regression for independent predictors
• Significance set at p <0.05

Results

3.1 Baseline Characteristics of Study Population

A total of 50 patients with acute ischemic stroke were included in the study. The mean age of the study population was 61.8 ± 12.4 years, with the majority of patients falling in the 60–70 years age group (36%). There was a male predominance, with 32 males (64%) and 18 females (36%), yielding a male-to-female ratio of approximately 1.8:1.

The most common vascular risk factors identified were hypertension (68%), followed by diabetes mellitus (52%), smoking (40%), and dyslipidemia (34%). A history of prior stroke was present in 16% of patients.

Table 1: Demographic and Clinical Characteristics (n=50)

3.2 Clinical Severity at Presentation

The mean NIHSS score at admission was 11.2 ± 5.6, indicating moderate stroke severity overall. Based on NIHSS categorization:

• Mild stroke (<5): 10 patients (20%)
• Moderate stroke (5–15): 28 patients (56%)
• Severe stroke (>15): 12 patients (24%)

Patients with severe stroke had significantly higher neurological deficits and were more likely to have large infarct volumes on imaging.

Table 2: Distribution of Stroke Severity (NIHSS)

3.3 MRI Findings: DWI Lesion Characteristics

DWI detected acute infarcts in 47 out of 50 patients (94%), confirming its high sensitivity. Three patients (6%) had DWI-negative stroke, all of whom presented early and had mild clinical symptoms.

The mean infarct volume was 28.6 ± 15.3 mL. Infarct volume distribution showed:

• <15 mL: 14 patients (28%)
• 15–50 mL: 26 patients (52%)
• >50 mL: 10 patients (20%)

The mean ADC value within infarct regions was 0.62 ± 0.08 ×10⁻³ mm²/s, with lower values observed in patients with larger infarcts and severe strokes.

The mean DWI-ASPECTS score in patients with MCA territory infarction was 6.8 ± 1.9.

Table 3: MRI DWI Findings

3.4 Correlation Between DWI Findings and Clinical Severity

A strong positive correlation was observed between infarct volume and NIHSS score (r = 0.91, p < 0.001), indicating that patients with larger infarcts had more severe neurological deficits.

A strong negative correlation was noted between DWI-ASPECTS score and NIHSS (r = –0.84, p < 0.001), demonstrating that lower ASPECTS scores were associated with higher stroke severity.

ADC values showed a moderate negative correlation with NIHSS (r = –0.68, p < 0.01), suggesting that lower ADC values corresponded to more severe ischemic injury.

Table 4: Correlation Between MRI Parameters and NIHSS

3.5 Functional Outcome (mRS) at Follow-Up

At 30-day follow-up:

• Favorable outcome (mRS 0–2): 30 patients (60%)
• Unfavorable outcome (mRS 3–6): 20 patients (40%)

Patients with smaller infarct volumes and higher ASPECTS scores were more likely to achieve favorable outcomes.

3.6 Correlation of DWI Parameters with Functional Outcome

Infarct volume demonstrated a strong positive correlation with mRS (r = 0.88, p < 0.001), indicating worse outcomes with larger infarcts.

DWI-ASPECTS showed a strong inverse correlation with mRS (r = –0.86, p < 0.001), with higher scores predicting better recovery.

ADC values were significantly lower in patients with unfavorable outcomes (0.58 ± 0.06 ×10⁻³ mm²/s) compared to those with favorable outcomes (0.66 ± 0.07 ×10⁻³ mm²/s, p < 0.01).

3.7 Multivariate Analysis

Multivariate regression analysis identified the following independent predictors of poor outcome (mRS ≥3):

• Infarct volume >30 mL
• DWI-ASPECTS ≤6
• Admission NIHSS >15
• ADC value <0.60 ×10⁻³ mm²/s

Among these, infarct volume and NIHSS were the strongest predictors.

3.8 DWI-Negative Stroke Findings

The three DWI-negative patients had:

• Mild symptoms (NIHSS ≤4)
• Small cortical or lacunar infarcts
• Complete functional recovery (mRS 0–1)

These cases highlight that early imaging may occasionally fail to detect ischemia, particularly in minor strokes.

4.1 Role of DWI in Early Detection of Acute Ischemic Stroke

Diffusion-weighted imaging has emerged as the cornerstone for early diagnosis of acute ischemic stroke due to its ability to detect cytotoxic edema within minutes of ischemic onset. In the present study, DWI demonstrated a sensitivity of 94%, which is consistent with previously reported sensitivities ranging between 88% and 100% [1]. This high diagnostic accuracy underscores the superiority of DWI over conventional imaging modalities, particularly in the hyperacute phase.

The ability of DWI to identify infarcts in the early time window is clinically significant, as it directly influences therapeutic decisions such as thrombolysis and mechanical thrombectomy. Previous studies have emphasized that early DWI changes correlate with irreversible tissue injury, thus aiding in defining the infarct core [2]. The findings of the present study reaffirm the reliability of DWI as the primary imaging modality in acute stroke evaluation.

4.2 Correlation Between Infarct Volume and Clinical Severity

A strong positive correlation between infarct volume and NIHSS score was observed in this study (r = 0.91), indicating that larger infarcts are associated with more severe neurological deficits. This observation aligns with prior studies demonstrating that infarct volume is a robust indicator of stroke severity and clinical deterioration [3,4].

Quantitative assessment of infarct volume has been shown to provide objective insight into the extent of cerebral injury. Studies have reported that infarct volumes exceeding 30 mL are significantly associated with higher NIHSS scores and increased risk of complications [5]. The current findings corroborate these observations, highlighting the importance of volumetric analysis in stroke prognostication.

Furthermore, infarct volume has been shown to correlate not only with initial severity but also with long-term outcomes, making it a critical parameter in both acute and follow-up assessments [6].

4.3 Prognostic Significance of DWI-ASPECTS

The DWI-ASPECTS score demonstrated a strong inverse correlation with both NIHSS and mRS scores in this study, indicating that lower scores are associated with worse clinical outcomes. This finding is consistent with established literature where ASPECTS has been widely used as a reliable predictor of stroke severity and outcome [7].

ASPECTS provides a rapid and reproducible method for assessing early ischemic changes, particularly in the middle cerebral artery territory. Studies have shown that patients with ASPECTS ≤6 have significantly poorer functional outcomes and higher mortality rates compared to those with higher scores [8].

In addition, ASPECTS has been integrated into treatment decision-making algorithms, especially in determining eligibility for reperfusion therapies. The present study reinforces its clinical utility as a prognostic marker and supports its routine use in acute stroke imaging.

4.4 Role of ADC Values in Predicting Tissue Viability

Apparent diffusion coefficient values reflect the degree of water diffusion restriction and are indicative of the severity of ischemic injury. In this study, lower ADC values were significantly associated with severe strokes and poor functional outcomes.

Previous studies have demonstrated that ADC reduction corresponds to irreversible cellular damage and infarct core formation [9]. Threshold ADC values have been proposed to differentiate between reversible and irreversible ischemic injury, with lower values indicating nonviable tissue [10].

The findings of this study are in agreement with existing evidence suggesting that ADC values serve as an independent predictor of outcome. Patients with lower ADC values were more likely to have unfavorable outcomes, emphasizing the importance of incorporating ADC analysis into routine evaluation.

4.5 Functional Outcome and Predictive Value of Combined Imaging Parameters

Functional outcome assessment using mRS revealed that 60% of patients achieved favorable outcomes, while 40% had significant disability. Strong correlations were observed between imaging parameters and functional outcomes, with infarct volume and ASPECTS emerging as the most reliable predictors.

Previous studies have highlighted that combining clinical and imaging parameters enhances prognostic accuracy compared to individual variables alone [11,12]. The integration of NIHSS, infarct volume, and ASPECTS has been shown to improve prediction models for stroke outcomes.

Additionally, DWI-negative strokes, observed in a small subset of patients in this study, were associated with milder symptoms and better recovery. This finding is consistent with prior reports indicating that DWI-negative strokes often represent transient or minor ischemic events with favorable prognosis [13-15].

The present study supports the concept that a multimodal approach combining clinical assessment with advanced imaging parameters provides the most accurate prediction of outcomes in acute ischemic stroke.

Diffusion-weighted MRI plays a pivotal role not only in the early detection of acute ischemic stroke but also in prognostication. Imaging parameters such as infarct volume, DWI-ASPECTS score, and ADC values demonstrate strong correlations with clinical severity and functional outcomes. Among these, infarct volume and NIHSS are the most reliable predictors of poor outcome.

The integration of DWI-based biomarkers into routine clinical practice can significantly enhance decision-making, facilitate risk stratification, and improve patient management. Future studies incorporating advanced imaging techniques and artificial intelligence may further refine prognostic models and enable personalized stroke care.

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