Parkinson's disease (PD) is characterized by a degeneration of nigrostriatal dopaminergic neurons, which can be imaged with 123I-labeled 2 beta-carbomethoxy-3 beta-(4-iodophenyl) tropane ([123I]beta-CIT) and single-photon emission computed tomography (SPECT). However, the quality of the region of interest (ROI) technique used for quantitative analysis of SPECT data is compromised by limited anatomical information in the images. We investigated whether the diagnosis of PD can be improved by combining the use of SPECT images with morphological image data from magnetic resonance imaging (MRI)/computed tomography (CT). We examined 27 patients (8 men, 19 women; aged 55 +/- 13 years) with PD (Hoehn and Yahr stage 2.1 +/- 0.8) by high-resolution [123I]beta-CIT SPECT (185-200 MBq, Ceraspect camera). SPECT images were analyzed both by a unimodal technique (ROIs defined directly within the SPECT studies) and a multimodal technique (ROIs defined within individual MRI/CT studies and transferred to the corresponding interactively coregistered SPECT studies). [123I]beta-CIT binding ratios (cerebellum as reference), which were obtained for heads of caudate nuclei (CA), putamina (PU), and global striatal structures were compared with clinical parameters. Differences between contra- and ipsilateral (related to symptom dominance) striatal [123I]beta-CIT binding ratios proved to be larger in the multimodal ROI technique than in the unimodal approach (e.g., for PU: 1.2 vs. 0.7). Binding ratios obtained by the unimodal ROI technique were significantly correlated with those of the multimodal technique (e.g., for CA: y = 0.97x + 2.8; r = 0.70; P < 0.001). Concerning the correlations between SPECT data and clinical parameters, the significance levels in the multimodal ROI technique, for example, for the correlation between CA and the UPDRScom subscore (r = -0.49 vs. -0.32). These results show that the impact of [123I]beta-CIT SPECT for diagnosing PD is affected by the method used to analyze the SPECT images. The described multimodal approach, which is based on coregistration of SPECT and morphological imaging data, leads to improved determination of the degree of this dopaminergic disorder.
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http://dx.doi.org/10.1007/s001170050845 | DOI Listing |
J Comput Assist Tomogr
November 2024
From the Diagnostic Radiology Department, Faculty of Medicine, Mansoura University-Egypt, Mansoura, Egypt.
Objective: The aim of the study is to assess the diagnostic performance of quantitative analysis of diffusion-weighted imaging in assessing treatment response in cervical cancer patients.
Methods: A retrospective analysis was done for 50 patients with locally advanced cervical cancer who received concurrent chemoradiotherapy and underwent magnetic resonance imaging and diffusion-weighted imaging. Treatment response was classified into 4 categories according to RECIST criteria 6 months after therapy completion.
Front Neuroinform
December 2024
Institute of Theoretical Physics, Jagiellonian University, Kraków, Poland.
Understanding brain function relies on identifying spatiotemporal patterns in brain activity. In recent years, machine learning methods have been widely used to detect connections between regions of interest (ROIs) involved in cognitive functions, as measured by the fMRI technique. However, it's essential to match the type of learning method to the problem type, and extracting the information about the most important ROI connections might be challenging.
View Article and Find Full Text PDFFront Oncol
December 2024
Department of Radiology, School of Medicine, University of Washington, Seattle, WA, United States.
Introduction: Diffusion weighted MRI (DWI) has emerged as a promising adjunct to reduce unnecessary biopsies prompted by breast MRI through use of apparent diffusion coefficient (ADC) measures. The purpose of this study was to investigate the effects of different lesion ADC measurement approaches and ADC cutoffs on the diagnostic performance of breast DWI in a high-risk MRI screening cohort to identify the optimal approach for clinical incorporation.
Methods: Consecutive screening breast MRI examinations (August 2014-Dec 2018) that prompted a biopsy for a suspicious breast lesion (BI-RADS 4 or 5) were retrospectively evaluated.
World J Urol
January 2025
Department of Urology, National Cancer Center Hospital East, Chiba, Japan.
Purpose: To evaluate the association between the newly developed region of interest (ROI)-modified Mayo Adhesive Probability (MAP) score, in which stranding was re-evaluated by computed tomography (CT) number, for predicting operation time in robot-assisted partial nephrectomy (RAPN).
Methods: The study participants were 119 patients who underwent transperitoneal RAPN. With regard to stranding, ROIs were evaluated, and the mean CT numbers were assigned a score ranging from 0 to 3.
BMC Med Imaging
January 2025
Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong, Road, Nanning, Guangxi Zhuang Autonomous Region, China.
Objectives: To develop ultrasound-based radiomics models and a clinical model associated with inflammatory markers for predicting intrahepatic cholangiocarcinoma (ICC) lymph node (LN) metastasis. Both are integrated for enhanced preoperative prediction.
Methods: This study retrospectively enrolled 156 surgically diagnosed ICC patients.
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