Background: There are different types of computed tomography (CT) contrast enhancement patterns of the uterus. It is not known whether these are hormonally dependent.
Purpose: To assess the relationship between these patterns and the menstrual cycle in non-users of hormonal contraception, and the possible impact of hormonal contraception.
Material And Methods: Prospective observational study of abdominal CT scans of 53 premenopausal women of whom 28 were non-users and 25 users of hormonal contraception. The non-users were divided according to menstrual cycle phase: follicular (n = 12); ovulatory (n = 1); and luteal (n = 12). The pattern and intensity of contrast enhancement of the uterine myometrium were assessed.
Results: The dominant pattern of contrast enhancement of the myometrium was the diffuse homogeneous type in both non-users and users. The intensity of the enhancement measured in Hounsfield units (HU) was higher in the follicular phase (median 102, range 73-130) compared to the luteal phase in non-users (median 92, range 57-130); however this was not statistically significant ( = 0.2). The HU values observed in users (median 95, range 45-160) were at the same levels compared to those of the luteal phase in non-users.
Conclusion: The dominant pattern of contrast enhancement in the portal venous phase of the myometrium in fertile ages is the diffuse homogeneous type and is independent of menstrual cycle phase or the use of hormonal contraception. However, these factors seem to play a role in the intensity of contrast enhancement, with a tendency of higher HU values in the follicular phase of non-users.
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http://dx.doi.org/10.1177/0284185120958404 | DOI Listing |
Arch Gynecol Obstet
January 2025
Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No. 6 Shuangyong Road, Nanning, 530021, Guangxi, China.
Purpose: This case report aims to present a rare case of endometrial carcinosarcoma, a highly malignant tumor with a poor prognosis. The primary objective is to describe this unique case's clinical presentation, multimodal magnetic resonance imaging (MRI) features, typical histopathological characteristics and surgical treatment.
Methods: A detailed analysis of the patient's medical history, preoperative imaging evaluation, and treatment approach was conducted.
J Comput Chem
January 2025
Instituto de Química, Universidade de Brasília, Brasília, Brazil.
This study aims to shed light on the mechanism and kinetics of 1,4-dioxane degradation by hydroxyl radical (OH) across various solvation conditions to evaluate electronic and structural properties at the MP2/aug-cc-pVTZ level. Transition states (TS) structures determined in the gas phase and SMD solvation model reveal similar hydrogen abstraction patterns. In contrast, the explicit solvation model (ES) introduces significant changes, suggesting a kinetic preference for axial pathways.
View Article and Find Full Text PDFJ Clin Med
January 2025
Department of Radiology, Bursa Yuksek Ihtisas Training and Research Hospital, 16310 Bursa, Turkey.
: This study aimed to evaluate the diagnostic performance of the Kaiser score (KS) on the modified abbreviated breast magnetic resonance imaging (AB-MRI) protocol for characterizing breast lesions by comparing it with full-protocol MRI (FP-MRI), using the histological data as the reference standard. : Breast MRIs detecting histologically verified contrast-enhancing breast lesions were evaluated retrospectively. A modified AB-MRI protocol was created from the standard FP-MRI, which comprised axial fat-suppressed T2-weighted imaging (T2WI), pre-contrast T1-weighted imaging (T1WI), and first, second, and fourth post-contrast phases.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Faculty of Science and Technology, Keio University, Yokohama 223-8522, Japan.
Person identification is a critical task in applications such as security and surveillance, requiring reliable systems that perform robustly under diverse conditions. This study evaluates the Vision Transformer (ViT) and ResNet34 models across three modalities-RGB, thermal, and depth-using datasets collected with infrared array sensors and LiDAR sensors in controlled scenarios and varying resolutions (16 × 12 to 640 × 480) to explore their effectiveness in person identification. Preprocessing techniques, including YOLO-based cropping, were employed to improve subject isolation.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Computer Science, Hubei University of Technology, Wuhan 430068, China.
Large visual language models like Contrastive Language-Image Pre-training (CLIP), despite their excellent performance, are highly vulnerable to the influence of adversarial examples. This work investigates the accuracy and robustness of visual language models (VLMs) from a novel multi-modal perspective. We propose a multi-modal fine-tuning method called Multi-modal Depth Adversarial Prompt Tuning (MDAPT), which guides the generation of visual prompts through text prompts to improve the accuracy and performance of visual language models.
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