Characterization of stroke lesions using a histogram-based data analysis including diffusion- and perfusion-weighted imaging

Alexander Grzesik; Johannes Bernarding; Juergen Braun; Hans-Christian Koennecke; Karl Juergen Wolf; Thomas Tolxdorff

doi:10.1117/12.383408

20 April 2000 Characterization of stroke lesions using a histogram-based data analysis including diffusion- and perfusion-weighted imaging

Alexander Grzesik, Johannes Bernarding, Juergen Braun, Hans-Christian Koennecke, Karl Juergen Wolf, Thomas Tolxdorff

Author Affiliations +

Proceedings Volume 3978, Medical Imaging 2000: Physiology and Function from Multidimensional Images; (2000) https://doi.org/10.1117/12.383408
Event: Medical Imaging 2000, 2000, San Diego, CA, United States

Abstract

Diffusion- and perfusion-weighted magnetic resonance imaging (DWI, PWI) allows the diagnosis of ischemic brain injury at a time when ischemic lesions may not yet be detectable in computer tomography or T2-weighted (T2w) MRI. However, regions with pathologic apparent diffusion coefficients (ADC) do not necessarily match with regions of prolonged mean transit times (MTT) or pathologic relative cerebral blood flow (rCBF). Mismatching parts are thought to correlate with tissues that can be saved by appropriate treatment. Ten patients with cerebral ischemia underwent standard T1w and T2w imaging as well as single-shot echo planar imaging (EPI) DWI, and PWI. Multidimensional histograms were constructed from T2w images, DWI, ADC, rCBF, and MTT maps. After segmenting different tissues, signal changes of ischemic tissues relative to unaffected parenchyma were calculated. Combining different information allowed the segmentation of lesions and unaffected tissues. Acute infarcts exhibited decreased ADC values as well as hypo- and hyperperfused areas. Correlating ADC, T2w, and rCBF with clinical symptoms allowed the estimation of age and perfusion state of the lesions. Combining DWI, PWI, and standard imaging overcomes strongly fluctuating parameters such as ADC values. A multidimensional parameter-set characterizes unaffected and pathologic tissues which may help in the evaluation of new therapeutic strategies.

Citation Download Citation

Alexander Grzesik, Johannes Bernarding, Juergen Braun, Hans-Christian Koennecke, Karl Juergen Wolf, and Thomas Tolxdorff "Characterization of stroke lesions using a histogram-based data analysis including diffusion- and perfusion-weighted imaging", Proc. SPIE 3978, Medical Imaging 2000: Physiology and Function from Multidimensional Images, (20 April 2000); https://doi.org/10.1117/12.383408

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