Purpose: Improvements in molecular breast imaging (MBI) have increased the use of MBI as adjunct diagnostic modality and alternative to MRI. We aimed to assess the value of MBI in patients with equivocal breast lesions on conventional imaging, especially in terms of its ability to rule out malignancy.
Methods: We selected patients who underwent MBI in addition to conventional diagnostics due to equivocal breast lesions between 2012 and 2015. All patients underwent digital mammography, target ultrasound and MBI. MBI was performed using a single-head Dilon 6800 gamma camera after administration of 600 MBq 99m Tc-sestamibi. Imaging was reported according to BI-RADS classification and compared with pathology or follow-up of ≥6 months.
Results: Of 226 women included, pathology was obtained in 106 (47%) and (pre)malignant lesions were found in 25 (11%). Median follow-up was 5.4 years (IQR 3.9-7.1). Sensitivity was higher for MBI compared to conventional diagnostics (84% vs. 32%; P = 0.002), identifying malignancy in 21 and 6 patients, respectively, but specificity did not differ (86% vs. 81%; P = 0.161). Positive and negative predictive value were 43% and 98% for MBI and 17% and 91% for conventional diagnostics. MBI was discordant with conventional diagnostics in 68 (30%) patients and correctly changed diagnosis in 46 (20%) patients, identifying 15 malignant lesions. In subgroups with nipple discharge ( N = 42) and BI-RADS 3 lesions ( N = 113) MBI detected 7 of 8 occult malignancies.
Conclusion: MBI correctly adjusted treatment in 20% of patients with diagnostic concerns after conventional work-up, and could rule out malignancy with a high negative predictive value of 98%.
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http://dx.doi.org/10.1097/MNM.0000000000001684 | DOI Listing |
Viruses
January 2025
Department of Microbiology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 5508-900, Brazil.
Dengue fever, caused by the dengue virus (DENV), poses a significant global health challenge, particularly in tropical and subtropical regions. Recent increases in indigenous DENV cases in Europe are concerning, reflecting rising incidence linked to climate change and the spread of mosquitoes. These vectors thrive under environmental conditions like temperature and humidity, which are increasingly influenced by climate change.
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Department of Orthopaedics and Traumatology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.
Periprosthetic joint infections occur in 1-2% of all patients undergoing prosthetic joint surgeries. Although strong efforts have been made to reduce infection rates, conventional therapies like one- or two-stage revisions have failed to lower the infection rates. Cold atmospheric plasma (CAP) has shown promising results in reducing bacterial loads on surfaces.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Shunde Innovation School, University of Science and Technology Beijing, Foshan 528399, China.
Mid-infrared spectral analysis has long been recognized as the most accurate noninvasive blood glucose measurement method, yet no practical compact mid-infrared blood glucose sensor has ever passed the accuracy benchmark set by the USA Food and Drug Administration (FDA): to substitute for the finger-pricking glucometers in the market, a new sensor must first show that 95% of their glucose measurements have errors below 15% of these glucometers. Although recent innovative exploitations of the well-established Fourier-transform infrared (FTIR) spectroscopy have reached such FDA accuracy benchmarks, an FTIR spectrometer is too bulky. The advancements of quantum cascade lasers (QCLs) can lead to FTIR spectrometers of reduced size, but compact QCL-based noninvasive blood glucose sensors are not yet available.
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January 2025
Institute of Artificial Intelligence in Sports, Capital University of Physical Education and Sports, Beijing 100191, China.
This study investigates mental fatigue in sports activities by leveraging deep learning techniques, deviating from the conventional use of heart rate variability (HRV) feature analysis found in previous research. The study utilizes a hybrid deep neural network model, which integrates Residual Networks (ResNet) and Bidirectional Long Short-Term Memory (Bi-LSTM) for feature extraction, and a transformer for feature fusion. The model achieves an impressive accuracy of 95.
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January 2025
Heime (Tianjin) Electrical Engineering Systems Co., Ltd., Tianjin 301700, China.
This paper introduces a novel geometry-based synchrosqueezing S-transform (GSSST) for advanced gearbox fault diagnosis, designed to enhance diagnostic precision in both planetary and parallel gearboxes. Traditional time-frequency analysis (TFA) methods, such as the Synchrosqueezing S-transform (SSST), often face challenges in accurately representing fault-related features when significant mode closely spaced components are present. The proposed GSSST method overcomes these limitations by implementing an intuitive geometric reassignment framework, which reassigns time-frequency (TF) coefficients to maximize energy concentration, thereby allowing fault components to be distinctly isolated even under challenging conditions.
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