Objective: To investigate the repeatability of the quantitative magnetic resonance imaging (MRI) metric (apparent diffusion coefficient [ADC]) derived from reduced field-of-view diffusion-weighted (rFOV DWI) on thyroid glands in a clinical setting.
Materials And Methods: Ten healthy human volunteers were enrolled in MRI studies performed on a 3-T MRI scanner. Each volunteer was designed to undergo 3 longitudinal examinations (2 weeks apart) with 2 repetitive sessions within each examination, which included rFOV and conventional full field-of-view (fFOV) DWI scans. Diffusion-weighted images were assessed and scored based on image characteristics. Apparent diffusion coefficient values of thyroid glands from all participants were calculated based on regions of interest. Repeatability analysis was performed based on the framework proposed by the Quantitative Imaging Biomarker Alliance, generating 4 repeatability metrics: within-participant variance ((Equation is included in full-text article.)), repeatability coefficients, intraclass correlation coefficient, and within-participant coefficient of variation. Student t test was used to compare the performance difference between rFOV and fFOV DWI.
Results: The overall image quality from rFOV DWI was significantly higher than that from fFOV DWI (P = 0.04). The ADC values calculated from rFOV DWI were significantly lower than corresponding values from fFOV DWI (P < 0.001). There was no significant difference in ADC values across sessions and examinations in either rFOV or fFOV DWI (P > 0.05). Reduced field-of-view DWI had lower values of (Equation is included in full-text article.), repeatability coefficient, and within-participant coefficient of variation and had a higher value of intraclass correlation coefficient compared with fFOV DWI across either sessions or examinations.
Conclusions: This study demonstrated that rFOV DWI produced more superior-quality DWI images and more repeatable ADC measurements compared with fFOV DWI, thus providing a feasible quantitative imaging tool for investigating thyroid glands in clinical settings.
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http://dx.doi.org/10.1097/RCT.0000000000000227 | DOI Listing |
Magn Reson Imaging
December 2024
Department of Radiology, Zhongshan Hospital, Fudan University, No.180 Fenglin Road, Xuhui District, Shanghai 200032, China; Shanghai Institute of Medical Imaging, No.180 Fenglin Road, Xuhui District, Shanghai 200032, China. Electronic address:
Objectives: To evaluate the performance of diffusion-weighted imaging (DWI) with an optimal b-value and field-of-view in identifying wall inflammation in abdominal aortic aneurysm (AAA) by comparing it to delayed enhancement T1-weighted imaging (DEI).
Methods: Twenty-five males with AAA were prospectively enrolled and underwent fat-suppressed T1-weighted dark-blood imaging (T1WI), full field-of-view (f-FOV) and reduced field-of-view (r-FOV) DWI (b values = 0, 100, 400 and 800 s/mm), and DEI. Corresponding images on f-FOV, r-FOV DWI and DEI at the same level were evaluated qualitatively and quantitatively using the paired t-test and Wilcoxon signed-rank test.
J Magn Reson Imaging
February 2025
Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
Insights Imaging
June 2024
Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Objectives: To investigate whether reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with deep learning reconstruction (DLR) can improve the accuracy of evaluating muscle invasion using VI-RADS.
Methods: Eighty-six bladder cancer participants who were evaluated by conventional full field-of-view (fFOV) DWI, standard rFOV (rFOV) DWI, and fast rFOV with DLR (rFOV) DWI were included in this prospective study. Tumors were categorized according to the vesical imaging reporting and data system (VI-RADS).
Acta Radiol
August 2023
Department of Otolaryngology-Head & Neck Surgery, West China Hospital, Sichuan University, Chengdu, PR China.
Background: Cervical cancer (CC) is the second most common cancer in women worldwide. Diffusion-weighted imaging (DWI) plays an important role in the diagnosis of CC, but the conventional techniques are affected by many factors.
Purpose: To compare reduced-field-of-view (r-FOV) and full-field-of-view (f-FOV) DWI in the diagnosis of CC.
Eur Radiol
October 2023
Institute of Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany.
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