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Background: The aim of this study was to determine the relationship between blood oxygen level dependent (BOLD) cerebrovascular reactivity (CVR) and cerebral blood flow (CBF) obtained from arterial spin labeling (ASL) using different post labeling delays (PLD).
Methods: Forty-two patients with steno-occlusive diseases and impaired CVR were divided into two groups, one scanned with a 1.5-second (1.5-s) and the other with a 2.5-second (2.5-s) PLD ASL protocol. For all patients, a region of interest (ROI) was drawn around the CVR impairment. This affected ROI was then left-right flipped across the brain midline to obtain the control ROI. For both groups, the difference in grey matter CVR between affected and control ROI was first tested to confirm significance. The average grey matter CBF of affected and control ROIs were then compared. The same analysis method was used to compare affected and control hemispheres.
Results: In both groups of 1.5-s and 2.5-s PLD, CVR values in the affected ROI (-0.049±0.055 and -0.042±0.074%/mmHg, respectively) were significantly lower compared to that in the control ROI (0.152±0.054 and 0.152±0.053%/mmHg, respectively, P<0.0001). In the group with the 1.5-s PLD, CBF in the affected ROI (37.62±11.37 mL/100 g/min) was significantly lower compared to CBF in the control ROI (44.13±11.58 mL/100 g/min, P<0.05). However, in the group with the 2.5-s PLD, no significant differences could be seen between CBF in the affected ROI (40.50±14.82 mL/100 g/min) and CBF in the control ROI (39.68±12.49 mL/100 g/min, P=0.73). In the hemisphere-based analysis, CBF was significantly lower in the affected side than in the control side for the group with the 1.5-s PLD (P<0.05) when CVR was impaired (P<0.0001), but not for the group with the 2.5-s PLD (P=0.49).
Conclusions: In conclusion, our study reveals and highlights the value of a shorter-PLD ASL protocol, which is able to reflect CVR impairment. At the same time, we offer a better understanding of the relationship between BOLD CVR and CBF obtained from ASL.
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http://dx.doi.org/10.21037/qims-20-148 | DOI Listing |
Psychiatry Res Neuroimaging
August 2025
Faculty of Social Science, University of Ottawa, Canada.
Background: Childhood sexual abuse (CSA) can cause lasting neurodevelopmental changes, posing significant challenges for survivors. Its specific impact on men remains heavily stigmatized and under-researched. This study examined neurophysiological correlates of CSA in men using diffusion tensor imaging (DTI).
View Article and Find Full Text PDFMed Phys
August 2025
The University of Texas MD Anderson Cancer Houston, Houston, Texas, USA.
Background: To guarantee high-quality patient scans, thorough quality assurance (QA) of SPECT or gamma cameras, including performance, review, and documentation, is essential.
Purpose: We developed a novel Nuclear Medicine Quality Assurance server (NMQA) with an AI deep learning (AIDL) optical character recognition (OCR) system to automate QA data retrieval and review from SPECT and gamma cameras. The system extracts and compares daily and weekly QA data against specifications.
Quant Imaging Med Surg
September 2025
Department of Radiology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, China.
Background: Apathy, a decline in goal-directed motivated behavior, is a common non-motor symptom (NMS) in Parkinson's disease (PD). Previous studies have suggested that PD patients with apathy exhibit increased iron levels in the cerebrospinal fluid (CSF) and the iron levels are positively correlated with the severity of apathy, indicating that apathy in PD may be related with brain iron accumulation. Specifically, quantitative susceptibility mapping (QSM), an emerging brain magnetic resonance imaging (MRI) technique, can be used to sensitively detect the iron deposition in the brain , to reflect the neurodegeneration processes.
View Article and Find Full Text PDFSci Rep
September 2025
Electrical and Electronics Engineering Department, Mugla Sitki Kocman University, 48000, Kotekli, Turkey.
This study aims to highlight the effectiveness of computer vision (CV) techniques in classifying brain tumors using a comprehensive dataset consisting of computed tomography (CT) scans. The proposed framework comprises six types of brain tumors, including benign tumors (Meningioma, Schwannoma, and Neurofibromatosis) and malignant tumors (Glioma, Chondrosarcoma, and Chordoma). The acquired images underwent pre-processing steps to enhance the dataset's quality, including noise reduction through median and Gaussian filters and region of interest (ROIs) extraction using an automated binary threshold-based fuzzy c-means segmentation (ABTFCS) approach.
View Article and Find Full Text PDFFront Neurol
August 2025
Department of Neurology, School of Medicine, Kyungpook National University, Daegu, Republic of Korea.
Objective: The aims of the study were to investigate differences in cortical mean diffusivity (MD) among idiopathic normal-pressure hydrocephalus (INPH) patients, Alzheimer's disease (AD) patients, and healthy controls, and to analyze mean MD among INPH and AD groups in INPH-specific areas showing distinctive cortical MD changes for distinguishing INPH from AD.
Methods: Forty-two INPH patients, 51 AD patients, and 23 healthy controls were imaged with MRI, including diffusion tensor imaging MR images, for surface-based analysis across the entire brain.
Results: Compared with healthy controls, INPH patients showed a statistically significant reduction in MD in the high convexity of the frontal, parietal, and occipital cortical regions.