Objective: The purpose of this study was to evaluate and compare the accuracy of magnetic resonance imaging and transvaginal ultrasonography in myoma diagnosis, mapping, and measurement.
Study Design: This was a double-blind study of 106 consecutive premenopausal women who underwent hysterectomy for benign reasons. Myomas (total, 257) were exactly mapped by magnetic resonance imaging and transvaginal ultrasonography; in each patient, we counted correctly identified myomas with pathologic position as true value.
Results: The presence of myomas was detected with the same high level of precision by both methods (magnetic resonance imaging: sensitivity, 0.99; specificity, 0.86; transvaginal ultrasonography: sensitivity, 0.99; specificity, 0.91). The mean number of correctly identified myomas was significantly higher by magnetic resonance imaging than by transvaginal ultrasonography (mean difference, 0.51 +/- 1.03; P <.001), a difference that narrowed to 0.08 +/- 0.76 (P =.60) in 26 patients with 1 to 4 myomas and uterine volumes <375 mL. Magnetic resonance imaging and transvaginal ultrasonography myoma diameter measurements had equal and high accuracies in patients with 1 to 4 myomas.
Conclusion: Transvaginal ultrasonography is as efficient as magnetic resonance imaging in detecting myoma presence, but its capacity for exact myoma mapping falls short of that of magnetic resonance imaging, especially in large (>375 mL) multiple-myoma (>4) uteri.
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http://dx.doi.org/10.1067/mob.2002.121725 | DOI Listing |
Acta Radiol
January 2025
Department of Radiology, Changi General Hospital, Singapore, Republic of Singapore.
Background: Computed tomography (CT) is the gold standard imaging modality for the assessment of 3D bony morphology but incurs the cost of ionizing radiation exposure. High-resolution 3D magnetic resonance imaging (MRI) with CT-like bone contrast (CLBC) may provide an alternative to CT in allowing complete evaluation of both bony and soft tissue structures with a single MRI examination.
Purpose: To review the technical aspects of an optimized stack-of-stars 3D gradient recalled echo pulse sequence method (3D-Bone) in generating 3D MR images with CLBC, and to present a pictorial review of the utility of 3D-Bone in the clinical assessment of common musculoskeletal conditions.
Circ Heart Fail
January 2025
Aswan Heart Center, Magdi Yacoub Heart Foundation, Egypt (A.M.I., M.R., A. Elsawy, M.H., S.H., W.E., A. Elaithy, A. Elguindy, A. Afifi, Y.A., M.Y.).
Background: Changes in the phenotype and genotype in hypertrophic cardiomyopathy (HCM) are thought to involve the myocardium as well as extracardiac tissues. Here, we describe the structural and functional changes in the ascending aorta of obstructive patients with HCM.
Methods: Changes in the aortic wall were studied in a cohort of 101 consecutive patients with HCM undergoing myectomy and 9 normal controls.
J Cereb Blood Flow Metab
January 2025
A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland.
Zero echo time (zero-TE) pulse sequences provide a quiet and artifact-free alternative to conventional functional magnetic resonance imaging (fMRI) pulse sequences. The fast readouts (<1 ms) utilized in zero-TE fMRI produce an image contrast with negligible contributions from blood oxygenation level-dependent (BOLD) mechanisms, yet the zero-TE contrast is highly sensitive to brain function. However, the precise relationship between the zero-TE contrast and neuronal activity has not been determined.
View Article and Find Full Text PDFEur Heart J Digit Health
January 2025
Kolling Institute, Royal North Shore Hospital, University of Sydney, St Leonards, Sydney, NSW 2065, Australia.
Aims: An explainable advanced electrocardiography (A-ECG) Heart Age gap is the difference between A-ECG Heart Age and chronological age. This gap is an estimate of accelerated cardiovascular aging expressed in years of healthy human aging, and can intuitively communicate cardiovascular risk to the general population. However, existing A-ECG Heart Age requires sinus rhythm.
View Article and Find Full Text PDFHealth Inf Sci Syst
December 2025
School of Mathematics and Computing, University of Southern Queensland, 487-535 West Street, Toowoomba, QLD 4350 Australia.
Purpose: This paper aims to develop a three-dimensional (3D) Alzheimer's disease (AD) prediction method, thereby bettering current predictive methods, which struggle to fully harness the potential of structural magnetic resonance imaging (sMRI) data.
Methods: Traditional convolutional neural networks encounter pressing difficulties in accurately focusing on the AD lesion structure. To address this issue, a 3D decoupling, self-attention network for AD prediction is proposed.
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