Background: Endometrial Cancer (EC) is a highly heterogeneous cancer comprising both histological and molecular subtypes. Using a non-invasive modality method to trigger these subtypes as early as possible can aid clinicians in establishing individualized treatment.
Purpose: The study aimed to clarify the value of the Apparent Diffusion Coefficient (ADC) of EC MRI in determining molecular subtypes.
Material And Methods: We retrospectively recruited 109 patients with pathologically proven EC (78 endometrioid cancers and 31 non-endometrioid cancers) with available molecular classification from a tertiary centre. MRI was prospectively performed a month prior to surgery; images were blindly interpreted by two experienced radiologists with consensus reading. The ADC value was measured by an experienced radiologist on the commercially available processing workstation. Interoperator measurement consistency was calculated.
Results: Our sample comprised 17 PLOE, 32 MSI-H, 31 NSMP, and 29 P53abn ECs. Clinical information did not differ significantly among the groups. The maximum diameter and volume of the lesions differed among the groups. The ADC value in the maximal area (ADCarea) or region of interest (ROI, ADCroi) in the P53abn group was higher than that in the other groups (894.0 ±12.6 and 817.5 ± 83.3 x10-6 mm2/s). The ADC mean values were significantly different between the P53abn group and the other groups (P = 0.000). The nomogram showed the highest discriminative ability to distinguish P53abn EC from other types (AUC: 0.859).
Conclusion: Our results have suggested the quantitative MR characteristics (ADC values) derived from preoperative EC MRI to provide useful information in preoperatively determining P53abn cancer.
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http://dx.doi.org/10.2174/0115734056289592240408061811 | DOI Listing |
Sci Rep
January 2025
Department of Physical Chemistry, University of Chemistry and Technology, Prague, Technická 5, 166 28, Prague 6, Czech Republic.
Bulk properties of two-phase systems comprising methane and liquid p-xylene were derived experimentally using neutron imaging and theoretically predicted using molecular dynamics (MD). The measured and predicted methane diffusivity in the liquid, Henry's law constant, apparent molar volume, and surface tension compared well within the experimentally studied conditions (273.15 to 303.
View Article and Find Full Text PDFNeurooncol Adv
December 2024
Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden.
Purpose: To implement and evaluate deep learning-based methods for the classification of pediatric brain tumors (PBT) in magnetic resonance (MR) data.
Methods: A subset of the "Children's Brain Tumor Network" dataset was retrospectively used ( = 178 subjects, female = 72, male = 102, NA = 4, age range [0.01, 36.
BMC Med Imaging
January 2025
Department of Radiology, Suzhou Ninth People's Hospital, Ludang Street 2666#, Suzhou, Jiangsu, 215200, PR China.
Objective: This study was to develop a multi-parametric MRI radiomics model to predict preoperative Ki-67 status.
Materials And Methods: A total of 120 patients with pathologically confirmed breast cancer were retrospectively enrolled and randomly divided into a training set (n = 84) and a validation set (n = 36). Radiomic features were derived from both the intratumoral and peritumoral regions, extending 5 mm from the tumor boundary, using magnetic resonance imaging (MRI).
Cancers (Basel)
December 2024
Laboratory of Experimental Radiotherapy, Department of Oncology, University of Leuven, 3000 Leuven, Belgium.
Background: This study aimed to explore the differences in quantitative diffusion-weighted (DW) MRI parameters in oropharyngeal squamous cell carcinoma (OPC) based on Human Papillomavirus (HPV) status before and during radiotherapy (RT).
Methods: Echo planar DW sequences acquired before and during (chemo)radiotherapy (CRT) of 178 patients with histologically proven OPC were prospectively analyzed. The volumetric region of interest (ROI) was manually drawn on the apparent diffusion coefficient (ADC) map, and 105 DW-MRI radiomic parameters were extracted.
Neuroradiol J
January 2025
Division of Diagnostic Radiology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand.
Objective: Predicting treatment response in patients with vestibular schwannomas (VSs) remains challenging. This study aimed to evaluate the use of pre-treatment normalized apparent diffusion coefficient (nADC) values and magnetic resonance (MR) imaging characteristics in predicting treatment outcomes in patients with VSs undergoing radiosurgery.
Methods: The MR images of 44 patients with VSs who underwent radiosurgery at our institution were retrospectively reviewed, and the patients were categorized into tumor control ( = 28) and progression ( = 16) groups based on treatment response after treatment initiation, with a median follow-up duration of 29.
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