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Detection of Pre-Malignant Gastrointestinal Lesions Using Surface-Enhanced Resonance Raman Scattering-Nanoparticle Endoscopy
摘要： Cancers of the gastrointestinal (GI) tract are among the most frequent and most lethal cancers worldwide. An important reason for this high mortality is that early disease is typically asymptomatic, and patients often present with advanced, incurable disease. Even in high-risk patients who routinely undergo endoscopic screening, lesions can be missed due to their small size or subtle appearance. Thus, current imaging approaches lack the sensitivity and specificity to accurately detect incipient GI tract cancers. Here we report our finding that a single dose of a high-sensitivity surface-enhanced resonance Raman scattering nanoparticle (SERRS-NP) enables reliable detection of pre-cancerous GI lesions in animal models that closely mimic disease development in humans. Some of these animal models have not been used previously to evaluate imaging probes for early cancer detection. The studies were performed using a commercial Raman imaging system, a newly-developed mouse Raman endoscope, and finally a clinically applicable Raman endoscope for larger animal studies. We show that this SERRS-NP-based approach enables robust detection of small, pre-malignant lesions in animal models that faithfully recapitulate human esophageal, gastric, and colorectal tumorigenesis. This method holds promise for much earlier detection of GI cancers than currently possible and could lead therefore to marked reduction of morbidity and mortality of these tumor types.
关键词： cancer,Raman,endoscopy,preclinical,early detection,nanoparticle
更新于2025-09-23 15:23:52
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[IEEE 2018 2nd International Conference on Biomedical Engineering (IBIOMED) - Bali, Indonesia (2018.7.24-2018.7.26)] 2018 2nd International Conference on Biomedical Engineering (IBIOMED) - Early Detection of Tuberculosis using Chest X-Ray (CXR) with Computer-Aided Diagnosis
摘要： In this paper, a Computer-aided Diagnosis (CADx) system based on image processing is proposed to assist doctors and radiologists in interpreting Chest X-rays (CXR) for early detection of lung Tuberculosis (TB). CXR can indicate lung abnormalities including TB. However, the interpretations of CXR might vary from one individual to another. It is important to accurately and quickly detect TB because early treatment will prevent more infections and fatal effects from happening. The steps that were performed by the proposed system consisted of preprocessing, segmentation, feature extraction, and classification. In the preprocessing stage homomorphic filter, histogram equalization, median filter, and Contrast-Limited Adaptive Histogram Equalization (CLAHE) were applied to increase image quality. Segmentation was done by using Active Contour Model. Feature extraction was performed by analyzing the image’s first order statistical features. The last stage, classification, was based on the mean values. The results indicated that the system can increase specificity while maintaining sensitivity and accuracy of TB diagnosis. In conclusion, there is a high chance that CADx can assist doctors and radiologists for a more accurate and quick interpretation of CXR in early detection of TB.
关键词： Chest X-ray (CXR),Computer-aided Diagnosis (CADx),Early detection of tuberculosis
更新于2025-09-23 15:21:01
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Ganglion cell layer thickening in well‐controlled patients with type 1 diabetes: an early sign for diabetic retinopathy?
摘要： Purpose: To evaluate early changes in retinal layers using optical coherence tomography (OCT) in patients with long-standing type 1 diabetes (DM1) receiving intensi?ed insulin therapy. Methods: In a cross-sectional case–control study 150 patients with DM1 and 150 age- and sex-matched healthy control participants underwent OCT imaging. Scans of both eyes were analysed for di?erent layers (NFL, GCL (+IPL), INL, outer layer complex (OLC, including OPL, ONL and ELM) and photoreceptors (PR)) in all sub?elds of an ETDRS grid. All analyses were performed semi-automatically using custom software by certi?ed graders of the Vienna Reading Center. ANOVA models were used to compare the mean thickness of the layers between patients and controls. Results: Six hundred eyes with 512 datapoints in 49 b-scans in each OCT were analysed. Mean thickness in patients/controls was 31.35 lm/30.65 lm (NFL, p = 0.0347), 76.7 lm/73.15 lm (GCL, p ≤ 0.0001), 36.29 lm/37.13 lm (INL, p = 0.0116), 114.34 lm/112.02 lm (OLC, p < 0.0001) and 44.71 lm/44.69 lm (PR, p = 0.9401). When evaluating the ETDRS sub?elds separately for clinically meaningful hypotheses, a signi?cant swelling of the GCL in patients could be found uniformly and a central swelling for the OLC, whereas the distribution of NFL and INL thickening suggests that their statistical signi?cance was not clinically relevant. Conclusion: These preliminary results demonstrate that preclinical retinal changes in patients with long-standing DM1 can be found by retinal layer evaluation. However, the changes are layer-speci?c, with signi?cant thickening of the GCL and less so of the OLC suggesting a role as an early sign for di?use swelling and the evolution of DME even in well-controlled diabetes.
关键词： diabetic retinopathy – early detection – early disease – image analysis – OCT
更新于2025-09-11 14:15:04
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Mammographic breast density: how it affects performance indicators in screening programmes?
摘要： Objectives. To investigate how breast density affects screening performance indicators in a digital mammography context. Methods. We assessed the effect of breast density over the screen-detected and interval cancers rates, false-positives, specificity, sensitivity, recall rate, positive predictive value of recall (PPV-1), and PPV of invasive tests (PPV-2). Radiologists classified breast density using the BIRADS System. We used generalized estimating equations to account for within-woman correlation by means of the robust Huber-White variance estimator. Results. We included 177,164 women aged 50-69 years who underwent 499,251 digital mammograms from 2004 to 2015 in Spain. According to the fibroglandular tissue percentage, 24.7% of mammograms were classified as BI-RADS 1 (<25% glandular), 54.7% as BI-RADS 2 (25-50% glandular), 14.0% as BI-RADS 3 (51-75% glandular) and 6.6% as BI-RADS 4 (>75% glandular). Overall, women with BI-RADS 3 had the highest screen-detected cancer rate (5.9 per 1000) and BI-RADS 4 the highest interval cancer rate (2.4 per 1000). Sensitivity decreased from 89.2% in women with BI-RADS 1 to 67.9% in BI-RADS 4. Both PPV-1 and PPV-2 decreased from 10.4% to 5.7% and from 49.8% to 32.4% in women with BI-RADS 1 and BI-RADS 4, respectively. Women aged 60-69 years with BI-RADS 4 had the lowest sensitivity (54.9%) and the highest interval cancer rate (3.8 per 1000). Conclusions. Performance screening measures are negatively affected by breast density, falling to a lower sensitivity and PPV, and higher interval cancer rate as breast density increases. Particularly women aged 60-69 years with >75% glandular breasts had the worst results and therefore may be candidates for screening using other technologies.
关键词： Mammography,Early Detection of Cancer,Breast Neoplasms,Breast Density
更新于2025-09-10 09:29:36