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Comparison of multi-phase contrast-enhanced T1-weighted volumetric interpolated breath-hold examination and fat-suppressed T2-weighted combined with diffusion-weighted magnetic resonance imaging in anal fistula evaluation.
Quant Imaging Med Surg
December 2024
Department of Medical Imaging, the People's Hospital of Liuyang, Liuyang, China.
Background: Anal fistula is a common anorectal disorder that significantly diminishes the quality of life for affected patients. Accurate preoperative evaluation of the fistula's traits is essential for customizing surgical strategies, improving patient outcomes, and reducing the likelihood of the disease returning. This study aimed to evaluate the diagnostic accuracy of multi-phase contrast-enhanced fat-suppressed T1-weighted imaging using three-dimensional gradient echo sequence volumetric interpolated breath-hold examination (CE-FS-T1-3D-VIBE) and fat-suppressed T2-weighted imaging combined with diffusion-weighted imaging (FS-T2WI-DWI) sequence in delineating the characteristics of anal fistulas.
View Article and Find Full Text PDFPerineural spread evaluation of cranial nerves in nasopharyngeal carcinoma: superiority and reliability of isovolumetric MR imaging.
Front Oncol
November 2024
Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
Purpose: The purpose of this study was to investigate the advantage of three-dimensional liver acquisition with volume acceleration-flexible (3D LAVA_Flex) for perineural spread (PNS) status of nasopharyngeal carcinoma (NPC) in comparison with two-dimensional magnetic resonance sequences.
Materials And Methods: Sixty pathological proved NPC patients were prospective enrolled. A protocol included T2-weighted imaging with fat suppression (T2WI fs), T1-weighted imaging (T1WI) without and with contrast enhancement (T1WI ce), and 3D LAVA_Flex was applied for the recruited subject.
Altered orbitofrontal and pars opercularis cortical thickness in betel quid dependence chewers.
Ther Adv Psychopharmacol
December 2024
Department of Radiology, Hainan General Hospital (Hainan Afliated Hospital of Hainan Medical University), No. 19, Xiuhua Street, Xiuying District, Haikou 570311, Hainan,China.
Background: Altered cerebral cortex's structural organization has been found in individuals with betel quid dependence (BQD). However, the neurological underpinnings of the BQD-related abnormalities in cortical thickness and brain circuitry deficit are largely unknown.
Objective: This study aimed to investigate potential abnormalities of brain circuitry in the cortical thickness of BQD individuals by applying the surface-based morphometry (SBM) method.
Assessment of Age-Related Microstructure Changes in Thigh Skeletal Muscle Based on Neurite Orientation Dispersion and Density Imaging.
J Magn Reson Imaging
December 2024
Department of Medical Imaging, The Third Affiliated Hospital Southern Medical University, Guangzhou, China.
Background: Neurite orientation dispersion and density imaging (NODDI) could offer information about the morphological properties of tissue. Diffusion microstructure imaging has been widely used, but the applicability of NODDI in skeletal muscle imaging remains to be explored.
Purpose: To evaluate microstructure parameters variations in skeletal muscle as indicators of age-related changes.
Automatic three-dimensional analysis of posterosuperior full-thickness rotator cuff tear size on MRI.
J Shoulder Elbow Surg
December 2024
School for Biomedical and Precision Engineering, Personalised Medicine Research, University of Bern, Bern, Switzerland.
Background: Tear size and shape are known to prognosticate the efficacy of surgical rotator cuff (RC) repair however, current manual measurements on magnetic resonance images (MRI), exhibit high interobserver variabilities and exclude three-dimensional (3D) morphological information. This study aimed to develop algorithms for automatic 3D analyses of posterosuperior full-thickness RC tear to enable efficient and precise tear evaluation and 3D tear visualization.
Methods: - A deep-learning network for automatic segmentation of the tear region in coronal and sagittal multicenter MRI was trained with manually segmented (consensus of 3 experts) pd- and T2 weighted MRI of shoulders with full-thickness posterosuperior tears (n=200).
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