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Purpose: X-map is a non-contrast dual-energy CT (DECT) application to identify acute ischemic stroke (AIS). Our aim was to verify region-specific characteristics of early ischemic changes (EIC) on X-map compared with simulated 120-kVp mixed-CT image and DWI.
Methods: Fifty AIS patients who underwent DECT and DWI were enrolled (mean age, 76 years; 34 men, 16 women). All datasets including mixed-CT image, X-map, and DWI were transformed into a standard brain atlas with 11 × 2 ROIs based on the ASPECTS + W system. ROIs with EIC on DWI, mixed-CT image, and X-map were defined as DWI-positive, mixed-CT-positive, and X-map-positive, and those with normal finding were DWI-negative, mixed-CT-negative, and X-map-negative respectively, in visual assessment by two neuroradiologists in consensus.
Results: EIC on X-maps were visually relevant to those on the other images: of 221 ROIs with mixed-CT-positive and X-map-positive, 198 (89.6%) were DWI-positive. X-map revealed moderate diagnostic accuracy for AIS compared with DWI in ROC curve analysis (AUC = 0.732). X-map identified EIC in deep white matter more sensitively than mixed-CT image: of 15 ROIs with mixed-CT-negative and X-map-positive in W segments, 14 (93.3%) were DWI-positive. X-map often showed EIC in cortical regions that were not detected on the other images: of 67 ROIs with mixed-CT-negative and X-map-positive in I and M1-M6 segments, 47 (70.1%) were DWI-negative.
Conclusions: X-map is useful to detect EIC, especially in deep white matter, and may also provide additional information in acute ischemic lesions where DWI cannot be detected.
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http://dx.doi.org/10.1007/s11604-023-01490-3 | DOI Listing |
Abdom Radiol (NY)
July 2025
Department of Radiology, Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, China.
Ann Vasc Surg
November 2024
Division of Vascular Surgery, University of Indiana, Indianapolis, IN.
Background: Long-term data surrounding the impact of different endovascular abdominal aortic aneurysm repair (EVAR) surveillance strategies are limited. Therefore, the purpose of this study was to characterize postoperative imaging patterns, as well as to evaluate the association of duplex ultrasound surveillance after the first postoperative year with 5-year EVAR outcomes.
Methods: EVAR patients (2003-2016), who survived at least 1 year without aneurysm rupture, conversion to open repair, and reintervention in the Vascular Implant Surveillance and Interventional Outcomes Network were examined to provide all subjects ≥3 years of follow-up time.
Jpn J Radiol
February 2024
Department of Radiology and Nuclear Medicine, Research Institute for Brain and Blood Vessels-Akita, 6-10 Senshu-Kubota-Machi, Akita, 010-0874, Japan.
PLoS One
November 2022
Faculty of Medicine, Clinical Epidemiology and Clinical Statistics Center and Department of Surgery, Chiang Mai University, Chiang Mai, Thailand.
Objective: To compare diagnostic values between the 40 keV virtual monoenergetic plus (40 keV VMI+) dual source dual energy computed tomography (DSDECT) pulmonary angiography images and the standard mixed (90 and 150 kV) images for the detection of acute pulmonary embolism (PE).
Methods: Chest DSDECTs of 64 patients who were suspected of having acute PE were retrospectively reviewed by two independent reviewers. The assessments of acute PE of all patients on a per-location basis were compared between the 40 keV VMI+ and the standard mixed datasets (reference standard) with a two-week interval.
Proc SPIE Int Soc Opt Eng
April 2022
Department of Computer Science, Vanderbilt University, Nashville, TN, USA.
Deep learning promises the extraction of valuable information from traumatic brain injury (TBI) datasets and depends on efficient navigation when using large-scale mixed computed tomography (CT) datasets from clinical systems. To ensure a cleaner signal while training deep learning models, removal of computed tomography angiography (CTA) and scans with streaking artifacts is sensible. On massive datasets of heterogeneously sized scans, time-consuming manual quality assurance (QA) by visual inspection is still often necessary, despite the expectation of CTA annotation (artifact annotation is not expected).
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