Lightwave planar circuits based on organic materials for filtering and sensing

This thesis investigates in detail optical filters based on two phenomena and their applicability in photonics devices. The first phenomenon is called Whispering gallery modes, discovered in 1912 from Lord Rayleigh. The second phenomenon investigated in this thesis is the Braggs’s law, to develop optical filters

Improper use of "radioguided occult lesion localization" (ROLL) technique leads to misleading conclusions

No abstract availabl

Evaluation of response to immunotherapy: new challenges and opportunities for PET imaging

non present

Treating Smalt: A Preliminary SEM-EDX Study of the Effects of Aqueous-based Alkaline Conservation Treatments on Smalt in Wall Paintings

Smalt is a blue cobalt-coloured glass pigment used in European wall paintings from the early Renaissance period that became a popular choice for artists due to its unique tone, availability, and ve..

Intramedullary spinal cord metastases from breast cancer: Detection with 18F-FDG PET/CT

A 35-year-old woman, already treated with surgery, chemotherapy, and radiotherapy for a ductal carcinoma of the left breast, underwent an 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) scan for an increase of the serum markers carcinoembryonic antigen (CEA) and cancer antigen 15.3 (CA15.3). The scan showed multiple FDG-avid lesions in the liver and bone. The images also detected two areas of uptake in the dorsal and lumbar spinal cord, which were suspicious for metastases; magnetic resonance imaging (MRI) confirmed these lesions. © the authors; licensee ecancermedicalscience

Plasmon resonance optical tuning based on photosensitive composite structures

This paper reports a numerical investigation of a periodic metallic structure sandwiched between two quartz plates. The volume comprised between the quartz plates and the metallic structure is infiltrated by a mixture of azo-dye-doped liquid crystal. The exposure to a low power visible light beam modifies the azo dye molecular configuration, thus allowing the wavelength shift of the resonance of the system. The wavelength shift depends on the geometry of the periodic structure and it also depends on the intensity of the visible light beam

is 18f fluorodeoxyglucose uptake by the primary tumor a prognostic factor in breast cancer

Abstract Background We retrospectively investigated 18F-FDG uptake by the primary breast tumor as a predictor for relapse and survival. Patients and methods We studied 203 patients with cT1-T3N0 breast cancer. Standardized uptake value (SUVmax), was measured on the primary tumor. After a median follow-up of 68 months (range 22–80), the relation between SUVmax and tumor factors, disease free-survival (DFS) and overall survival (OS) was investigated. Results In the PET-positive patients, the median FDG uptake by the tumor was 4.7. FDG uptake was significantly related to tumor size, number of involved axillary nodes, grade, negative ER, high Ki-67 and HER2 overexpression. No distant metastases or deaths occurred in the PET-negative group. Five-year DFS was 97% and 83%, respectively in the PET-negative and PET-positive groups (P = 0.096). At univariate analysis, DFS was significantly lower in patients with SUVmax >4.7 compared to the patients with negative PET (P = 0.042), but not to the patients with SUVmax ≤4.7 (P = 0.106). At multivariable analysis, among PET-positive patients, SUVmax was not an independent prognostic factor for DFS (HR>4.7 vs ≤4.7: 1.02 (95% CI 0.45–2.31)). Five-year OS was 100% and 93%, respectively, in the PET-negative and PET-positive groups (P = 0.126). Conclusion FDG uptake by the primary lesion was significantly associated with several prognostic variables, but it was not an independent prognostic factor

A Low-Dose CT-Based Radiomic Model to Improve Characterization and Screening Recall Intervals of Indeterminate Prevalent Pulmonary Nodules.

Lung cancer (LC) is currently one of the main causes of cancer-related deaths worldwide. Low-dose computed tomography (LDCT) of the chest has been proven effective in secondary prevention (i.e., early detection) of LC by several trials. In this work, we investigated the potential impact of radiomics on indeterminate prevalent pulmonary nodule (PN) characterization and risk stratification in subjects undergoing LDCT-based LC screening. As a proof-of-concept for radiomic analyses, the first aim of our study was to assess whether indeterminate PNs could be automatically classified by an LDCT radiomic classifier as solid or sub-solid (first-level classification), and in particular for sub-solid lesions, as non-solid versus part-solid (second-level classification). The second aim of the study was to assess whether an LCDT radiomic classifier could automatically predict PN risk of malignancy, and thus optimize LDCT recall timing in screening programs. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, positive predictive value, negative predictive value, sensitivity, and specificity. The experimental results showed that an LDCT radiomic machine learning classifier can achieve excellent performance for characterization of screen-detected PNs (mean AUC of 0.89 ± 0.02 and 0.80 ± 0.18 on the blinded test dataset for the first-level and second-level classifiers, respectively), providing quantitative information to support clinical management. Our study showed that a radiomic classifier could be used to optimize LDCT recall for indeterminate PNs. According to the performance of such a classifier on the blinded test dataset, within the first 6 months, 46% of the malignant PNs and 38% of the benign ones were identified, improving early detection of LC by doubling the current detection rate of malignant nodules from 23% to 46% at a low cost of false positives. In conclusion, we showed the high potential of LDCT-based radiomics for improving the characterization and optimizing screening recall intervals of indeterminate PNs

Engineering an Environment for the Study of Fibrosis: A 3D Human Muscle Model with Endothelium Specificity and Endomysium

The integration of vascular structures into in vitro cultured tissues provides realistic models of complex tissue-vascular interactions. Despite the incidence and impact of muscle-wasting disorders, advanced in vitro systems are still far from recapitulating the environmental complexity of skeletal muscle. Our model comprises differentiated human muscle fibers enveloped by a sheath of human muscle-derived fibroblasts and supported by a vascular network with mural-like cells. Here, we demonstrate the induction of muscle-specific endothelium and the self-organization of endomysial muscle fibroblasts mediated by endothelial cells. We use this model to mimic the fibrotic environment characterizing muscular dystrophies and to highlight key signatures of fibrosis that are neglected or underestimated in traditional 2D monocultures. Overall, this vascularized meso-scale cellular construct finely recapitulates the human skeletal muscle environment and provides an advanced solution for in vitro studies of muscle physiology and pathology. Bersini et al. demonstrate the generation of a mesoscale model of the human muscle environment and prove its application for the study of fibrosis. This engineered muscle environment promotes the organ-specific differentiation of endothelial cells and the self-assembly of myofibers spontaneously wrapped by a continuous endomysium-like structure