Background: The diagnostic accuracy of colposcopy is poor for detecting precancerous cervical lesions.
Objectives: We assessed the performance of colposcopy for identifying cervical intraepithelial neoplasia grade 2 or worse (CIN2+), before and after including a dynamic spectral imaging (DSI) map that quantifies and maps acetowhitening to assist subsequent biopsy of suspicious lesions.
Methods: Four hundred and twenty-five women were examined at a multi-center setting in Wales, of which 393 women were included in the final analysis.
Results: For all referrals, the sensitivity of conventional colposcopy for histologically confirmed CIN2+ was 51.5%, the specificity was 92.0%, the positive predictive value was 56.7%, and the negative predictive value (NPV) was 90.4%. With the incorporation of the DSI map in predicting CIN2+, these became 84.8, 61.5, 30.8, and 95.3% respectively. The increase of sensitivity was statistically significant (p < 0.001). For the 236 women having colposcopy after low-grade (LG) cytology, with the incorporation of DSI, the sensitivity for CIN2+ increased from 27.3 to 86.4% (p < 0.001) and the NPV from 92.6 to 97.8%.
Conclusions: Colposcopy with DSI results in improved sensitivity to detect CIN2+ and maintains a high NPV for all referrals and especially for those with LG referral cytology.
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http://dx.doi.org/10.1159/000487319 | DOI Listing |
Ultrasound Med Biol
January 2025
Institute of Biomedical Technologies, Auckland University of Technology, Auckland City, 1010, Auckland, New Zealand. Electronic address:
Objective: This study aims to evaluate the viability of a hypothesis for selective targeting of skin cancer cells by exploiting the spectral gap with healthy cells using analytical and numerical simulation.
Methods: The spectral gap was first identified using a viscoelastic dynamic model, with the physical and mechanical properties of healthy and cancerous skin cells deduced from previous experimental studies conducted on cell lines. The outcome of the analytical simulation was verified numerically using modal and harmonic analysis.
Chaos
January 2025
College of Science, Civil Aviation University of China, Tianjin 300300, China.
Adolescent idiopathic scoliosis (AIS), which typically occurs in patients between the ages of 10 and 18, can be caused by a variety of reasons, and no definitive cause has been found. Early diagnosis of AIS or timely recognition of progression is crucial for the prevention of spinal deformity and the reduction of the risk of surgery or postponement. However, it remains a significant challenge.
View Article and Find Full Text PDFAnn Neurol
January 2025
Department of Neurology, Comprehensive Epilepsy Center, Johns Hopkins University, Baltimore, MD, USA.
Objective: Whereas a scalp electroencephalogram (EEG) is important for diagnosing epilepsy, a single routine EEG is limited in its diagnostic value. Only a small percentage of routine EEGs show interictal epileptiform discharges (IEDs) and overall misdiagnosis rates of epilepsy are 20% to 30%. We aim to demonstrate how network properties in EEG recordings can be used to improve the speed and accuracy differentiating epilepsy from mimics, such as functional seizures - even in the absence of IEDs.
View Article and Find Full Text PDFInfect Dis Model
June 2025
Department of Mathematics, Faculty of Science, Silpakorn Universtiy, Nakhon Pathom Province, 73000, Thailand.
Antibiotic treatment failure related to carriers poses a serious problem to physicians and epidemiologists. Due to the sparsity of data, assessing the role in infection dynamics is difficult. In this study, we examined the possibility that a particular therapeutic effectiveness will be regarded as the disease extinction threshold through the mathematical modelling approach.
View Article and Find Full Text PDFR Soc Open Sci
January 2025
Sorbonne Université, Paris Brain Institute (ICM), CNRS UMR7225, INRIA Paris, INSERM U1127, Hôpital de la Pitié Salpêtrière, AP-HP, Paris 75013, France.
The time-resolved analysis of heart rate (HR) and heart rate variability (HRV) is crucial for the evaluation of the dynamic changes of autonomic activity under different clinical and behavioural conditions. Standard HRV analysis is performed in the frequency domain because the sympathetic activations tend to increase low-frequency HRV oscillations, while the parasympathetic ones increase high-frequency HRV oscillations. However, a strict separation of HRV into frequency bands may cause biased estimations, especially in the low-frequency range.
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