Background: Diagnostic accuracies of standard NCCT, CTA, CTA-SI, FLAIR, and DWI to detect the diffusion-perfusion mismatch (DPM) were compared.
Methods: Stroke patients considered for endovascular therapy within 8 hours of onset were enrolled. DPM was defined as at least 160% mismatch between DWI and PWI volume.
Results: DPM was seen in 35 (71%) of 49 patients. ASPECTS on NCCT, CTA-SI, and DWI was 9 (8-9), 8 (6-9), and 7 (5-9) in mismatch group, and 6 (4-9), 6 (2-7), 5 (2-6) in nonmismatch group, respectively (P = .027, .006, and .001). Ischemic volume on CTA-SI and DWI was 4.6 (.2-13.0) cm(3) and 21.5 (9.7-44.0) cm(3) in mismatch group, and 61.5 (6.6-101.1) cm(3) and 94.9 (45.7-139.8) cm(3) in nonmismatch group (P = .003 and <.001). Significant collateralization on CTA-SI and FLAIR was seen in 80% and 88% in mismatch group, and 42% and 58% in nonmismatch group (P = .026 and .039). Odds ratios (95% CI) of DWI volume of ≤ 70 cm(3) to predict the mismatch was 30.17 (2.06-442.41) after adjusting for ASPECTSs on NCCT, CTA-SI, and DWI, 44.90 (2.75-732.73) for ischemic volume on CTA-SI, and 42.80 (3.05-601.41) for significant collateralization on CTA-SI and FLAIR (P = .013, .008, and .005).
Conclusions: DWI volume was the best predictor of DPM.
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http://dx.doi.org/10.1111/jon.12107 | DOI Listing |
Stroke
October 2024
Department of Neurology, Dell Medical School, The University of Texas at Austin. Neurology Division, Ascension Texas, Austin.
In the 2024 David G. Sherman Lecture, Steven J. Warach, illustrating with examples from his research, walks through the history of magnetic resonance imaging in acute stroke from the 1990s and early 2000s with the introduction, validation, and application of diffusion-weighted imaging, penumbral imaging (the diffusion-perfusion mismatch), and other imaging markers of the acute stroke pathology into routine clinical practice and stroke trials.
View Article and Find Full Text PDFCureus
August 2023
Internal Medicine, Malla Reddy Institute of Medical Sciences, Hyderabad, IND.
Introduction Magnetic resonance imaging (MRI) is well known to detect ischemic brain tissue and evaluate the tissue vulnerable to infarction. Diffusion-weighted imaging (DWI) has been a mainstay of stroke evaluation but has a few shortcomings, as it generally indicates only the core of ischemia and does not provide information regarding the tissue at risk or the ischemic penumbra surrounding the infarct. Perfusion imaging identifies brain tissue that has reduced blood flow as a potential target for reperfusion therapy.
View Article and Find Full Text PDFMagn Reson Imaging
June 2023
Department of Radiology, Haikou People's Hospital, Affiliated Haikou Hospital of Xiangya Medical school, Central South University, Haikou, Hainan Province, China. Electronic address:
Purpose: Amide proton transfer-weighted (APTw) imaging was an effective tool to reveal the tissue acidosis of acute ischemic stroke. This study aimed to evaluate the ability of APTw MRI to distinguish progressive penumbra and benign oligemia in the diffusion-perfusion mismatch region.
Materials And Methods: 38 acute cerebral infarction patients who underwent a comprehensive MRI examination, including diffusion-weighted imaging (DWI), perfusion-weighted imaging (PWI), APT imaging, and a follow-up scan in one week were recruited.
J Cardiothorac Surg
January 2023
Department of Cardiac Surgery, Aichi Medical University Hospital, 1-1 Yazako Karimata, Nagakute, Aichi, 480-1195, Japan.
It is considered acceptable to conservatively manage coronary artery bypass grafting patients with carotid artery disease without the need for preoperative corrective carotid revascularization. However, in the present case, rapidly progressive stroke symptoms with penumbra suggested in the arterial spin labeling, carotid artery stenting was performed successfully.
View Article and Find Full Text PDFNeuroimage Clin
March 2023
Department of Radiology, Stanford University, CA, USA. Electronic address:
Background: For prognosis of stroke, measurement of the diffusion-perfusion mismatch is a common practice for estimating tissue at risk of infarction in the absence of timely reperfusion. However, perfusion-weighted imaging (PWI) adds time and expense to the acute stroke imaging workup. We explored whether a deep convolutional neural network (DCNN) model trained with diffusion-weighted imaging obtained at admission could predict final infarct volume and location in acute stroke patients.
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