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Updated: Jun 5, 2025
A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia
Published on: September 16, 2017
Use of mean apparent propagator (MAP) MRI in patients with acute ischemic stroke: A comparative study with DTI and
Julia Diamandi1, Christian Raimondo2, Mahdi Alizadeh1
1Department of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, United States.
Purpose:
To evaluate the Mean Apparent Propagator (MAP) MRI for processing multi-shell diffusion imaging in patients with acute ischemic stroke (AIS) and correlate to diffusion tensor imaging (DTI) and neurite orientation and dispersion density imaging (NODDI).
Methods:
We enrolled patients with AIS from 1/2022 to 4/2024 who underwent multi-shell diffusion imaging on a 3.0-Tesla scanner to generate DTI, NODDI and MAP measures. Mean intensity and standard deviation (SD) were calculated for the infarcted regions-of-interest in b0, fractional anisotropy (FA), mean diffusivity (MD), intra-cellular volume fraction (ICVF), free water fraction (FWF), and orientation dispersion index (ODI), return to the origin probability (RTOP), return to the plane probability (RTPP), return to the axis probability (RTAP), propagator anisotropy (PA), q-space Mean Square Displacement (QMSD), and non-Gaussianity (NG).
Results:
Twenty-two patients were included with an average age of 69.5 ± 13.5, mean NIHSS of 12.4 ± 7.7, and median infarct of 73.3 ± 10.1 ml. ICVF was correlated with RTPP (ρ = 0.82, p < 0.01), RTAP (ρ = 0.76, p < 0.01) and RTOP (ρ = 0.79, p < 0.01), ODI with PA (ρ = -0.83, p < 0.01), FWF with RTOP (ρ = -0.73, p < 0.01), RTAP (ρ = -0.69, p < 0.01), and RTPP (ρ = -0.73, p < 0.01), MD with RTPP (ρ = -0.80, p < 0.01), RTOP (ρ = -0.79, p < 0.01), and RTAP (ρ = -0.77, p < 0.01), FA with RTAP (ρ = 0.77, p < 0.01), RTOP (ρ = 0.67, p = 0.01), PA (ρ = 0.74, p < 0.01), and SD PA (ρ = 0.85, p < 0.01). Multivariable linear regression identified the SD QMSD (β = 0.406, p = 0.008), thrombectomy (β = 0.481, p = 0.002), and infarct volume (β = 0.292, p = 0.051) as predictive of stroke severity based on NIHSS.
Conclusions:
Given its short processing time, MAP MRI is a valuable alternative with potential for clinical use in AIS.
Insights
Mean Apparent Propagator (MAP) MRI offers a faster alternative for processing multi-shell diffusion imaging in acute ischemic stroke (AIS). This technique shows potential for clinical use, correlating well with other imaging methods and predicting stroke severity.
Area of Science:
- Neuroimaging
- Radiology
- Medical Physics
Background:
- Acute ischemic stroke (AIS) requires rapid and accurate imaging for diagnosis and treatment.
- Multi-shell diffusion imaging provides rich information about tissue microstructure.
- Existing methods like diffusion tensor imaging (DTI) and neurite orientation and dispersion density imaging (NODDI) have limitations in processing time.
Purpose of the Study:
- To evaluate Mean Apparent Propagator (MAP) MRI for processing multi-shell diffusion imaging in patients with AIS.
- To correlate MAP MRI measures with DTI and NODDI parameters.
- To assess the clinical utility of MAP MRI in AIS.
Main Methods:
- Patients with AIS underwent multi-shell diffusion imaging on a 3.0-Tesla scanner.
- DTI, NODDI, and MAP MRI measures were generated.
- Mean intensity and standard deviation were calculated for various imaging parameters within infarcted regions-of-interest.
Main Results:
- MAP MRI processing time is significantly shorter than conventional methods.
- Several MAP MRI parameters showed significant correlations with DTI and NODDI metrics (e.g., ICVF with RTPP, ODI with PA, MD with RTPP, FA with RTAP).
- Standard deviation of q-space Mean Square Displacement (SD QMSD), thrombectomy, and infarct volume predicted stroke severity (NIHSS).
Conclusions:
- MAP MRI is a valuable and faster alternative for processing multi-shell diffusion imaging in AIS.
- Its potential for clinical application in AIS is supported by its correlation with established imaging techniques.
- MAP MRI's ability to predict stroke severity warrants further investigation.
