QUANTITATIVE MRI PERFUSION-DIFFUSION MISMATCH: THE ROLE OF USER-INDEPENDENT SOFTWARE

Background: Mechanical thrombectomy (MT) is considered as the standard therapy in patients with acute stroke caused by large vessel occlusion of the anterior circulation. When performing MT in an extended time window up to 24 hours after onset of clinical symptoms, advanced imaging is needed. Theref...

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Bibliographic Details
Published in:Clinical neuroradiology (Munich) 2019-09, Vol.29 (S1), p.S49
Main Authors: Hinteregger, Nicole, Wiesspeiner, Ulrike, Kneihsl, Markus, Fandler-Hofler, Simon, Deutschmann, Hannes, Fazekas, Franz, Reishofer, Gernot
Format: Article
Language:English
Subjects:
Brain damage
Healthcare industry software
Magnetic resonance imaging
Software
Stroke (Disease)
Technology application
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Summary:Background: Mechanical thrombectomy (MT) is considered as the standard therapy in patients with acute stroke caused by large vessel occlusion of the anterior circulation. When performing MT in an extended time window up to 24 hours after onset of clinical symptoms, advanced imaging is needed. Therefore, software applications for quantitative MRI perfusion-diffusion mismatch calculations have been developed to support decision making. The aim of our study was to compare two established software applications (RAPID[R] and Olea Sphere[R]) in terms of apparent diffusion coefficient (ADC) lesions volumes, volume of hypoperfused brain tissue and calculated mismatch volumes. Methods: MRI examinations of 86 patients with a large vessel occlusion of the anterior circulation were analyzed. Perfusion-diffusion mismatch was calculated automatically with RAPID[R] software and recalculated with Olea Sphere[R] software. For both software applications, the results included the automatically calculated ADC values, the volume of hypoperfused brain tissue and the mismatch volume (all given in ml). The calculated parameters from both methods were compared quantitatively using statistical methods. Result: Both software applications showed a good mean concordance for the volume of hypoperfused brain tissue and ADC lesions volume with no significant differences. However, a statistically significant difference of perfusion-diffusion mismatch volume could be observed. For individual patients, the differences of all evaluated parameters were found to be dramatically large. Conclusion: Despite the undoubted benefits of automated imaging software to support clinical decisions, proposed limits, such as the volume of the perfusion-diffusion mismatch, are only partially transferable to a variety of software platforms. We observed that volume segmentation plays a crucial role for the evaluation of perfusion-diffusion mismatch. Therefore, decision-relevant parameters should be determined individually for each software system
ISSN:1869-1439