Background: This study aimed to validate the application of CT texture analysis in estimating Bone Mineral Density (BMD) in patients with Type 2 Diabetes (T2D) and comparing it with the results of dual-energy X-ray absorptiometry (DXA) in a normative cohort.
Methods: We analyzed a total of 510 cases (145 T2D patients and 365 normal patients) from a single institution. DXA-derived BMD and CT texture analysis-estimated BMD were compared for each participant. Additionally, we investigated the correlation among 45 different texture features within each group.
Results: The correlation between CT texture analysis-estimated BMD and DXA-derived BMD in T2D patients was consistently high (0.94 or above), whether measured at L1 BMD, L1 BMC, total hip BMD, or total hip BMC. In contrast, the normative cohort showed a modest correlation, ranging from 0.66 to 0.75. Among the 45 texture features, significant differences were found in the Contrast V 64 and Contrast V 128 features in the normal group.
Conclusion: In essence, our study emphasizes that the clinical assessment of bone health, particularly in T2D patients, should not merely rely on traditional measures, such as DXA BMD. Rather, it may be beneficial to incorporate other diagnostic tools, such as CT texture analysis, to better comprehend the complex interplay between various factors impacting bone health.
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http://dx.doi.org/10.3390/diagnostics13172784 | DOI Listing |
BMC Med Imaging
January 2025
Faculty of Medicine, Department of Obstetrics and Gynecology, Erciyes University, Yenidogan Neighborhood, Turhan Baytop Street No:1, Kayseri, 38280, Turkey.
Aim: This study aimed to evaluate the effect of maternal vitamin D use during intrauterine life on fetal bone development using ultrasonographic image processing techniques.
Materials And Methods: We evaluated 52 pregnant women receiving vitamin D supplementation and 50 who refused vitamin D supplementation. Ultrasonographic imaging was performed on the fetal clavicle at 37-40 weeks of gestation.
Mar Pollut Bull
January 2025
Suganthi Devadason Marine Research Institute, Tuticorin, Tamil Nadu, India; Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu, India.
This research investigated the relationship between microplastic accumulation and the sediment texture in seagrass meadows across the selected coastal regions of Tuticorin. Sixteen sediment samples were collected by SCUBA divers utilizing a stainless steel grab sampler. Findings indicate significantly elevated microplastic concentrations in seagrass sediments when compared to unvegetated areas.
View Article and Find Full Text PDFNeural Netw
January 2025
Department of Mechanical Engineering, University of South Carolina, Columbia, SC 29208, USA. Electronic address:
Lamb waves are widely used for defect detection in structural health monitoring, and various methods are developed for Lamb wave data analysis. This paper presents an unsupervised Adversarial Transformer model for anomalous Lamb wave pattern detection by analyzing the spatiotemporal images generated by a hybrid PZT-scanning laser Doppler vibrometer (SLDV). The model includes the global attention and the local attention mechanisms, and both are trained adversarially.
View Article and Find Full Text PDFPhys Med Biol
January 2025
Radiological Sciences, University of California Los Angeles, 924 Westwood Blvd, Los Angeles, California, 90095, UNITED STATES.
Objective: The study aims to systematically characterize the effect of CT parameter variations on images and lung radiomic and deep features, and to evaluate the ability of different image harmonization methods to mitigate the observed variations.
Approach: A retrospective in-house sinogram dataset of 100 low-dose chest CT scans was reconstructed by varying radiation dose (100%, 25%, 10%) and reconstruction kernels (smooth, medium, sharp). A set of image processing, convolutional neural network (CNNs), and generative adversarial network-based (GANs) methods were trained to harmonize all image conditions to a reference condition (100% dose, medium kernel).
HPB (Oxford)
December 2024
Institute for Surgical Pathology, Medical Center - University of Freiburg, Germany; Core Facility for Histopathology and Digital Pathology, University of Freiburg, Germany; Faculty of Medicine, University of Freiburg, Germany. Electronic address:
Background: In pancreatic surgery Postoperative pancreatic fistula (POPF) represents the most dreaded complication, for which pancreatic texture is acknowledged as one of the strongest predictors. No consensual objective reference has been defined to evaluate the pancreas composition. The presented study aimed to mine histology data of the pancreatic tissue composition with AI assist and correlate it with clinic-pathological parameters derived from the RECOPANC study.
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