Bio-Inspired Watermarking Method for Authentication of Fundus Images in Computer-Aided Diagnosis of Retinopathy

Nowadays, medical imaging has become an indispensable tool for the diagnosis of some pathologies and as a health prevention instrument. In addition, medical images are transmitted over all types of computer networks, many of them insecure or susceptible to intervention, making sensitive patient information vulnerable. Thus, image watermarking is a popular approach to embed copyright protection, Electronic Patient Information (EPR), institution information, or other digital image into medical images. However, in the medical field, the watermark must preserve the quality of the image for diagnosis purposes. In addition, the inserted watermark must be robust both to intentional and unintentional attacks, which try to delete or weaken it. This work presents a bio-inspired watermarking algorithm applied to retinal fundus images used in computer-aided retinopathy diagnosis. The proposed system uses the Steered Hermite Transform (SHT), an image model inspired by the Human Vision System (HVS), as a spread spectrum watermarking technique, by leveraging its bio-inspired nature to give imperceptibility to the watermark. In addition, the Singular Value Decomposition (SVD) is used to incorporate the robustness of the watermark against attacks. Moreover, the watermark is embedded into the RGB fundus images through the blood vessel patterns extracted by the SHT and using the luma band of Y’CbCr color model. Also, the watermark was encrypted using the Jigsaw Transform (JST) to incorporate an extra level of security. The proposed approach was tested using the image public dataset MESSIDOR-2, which contains 1748 8-bit color images of different sizes and presenting different Diabetic Retinopathy (DR). Thus, on the one hand, in the experiments we evaluate the proposed bio-inspired watermarking method over the entire MESSIDOR-2 dataset, showing that the embedding process does not affect the quality of the fundus images and the extracted watermark, by obtaining average Peak Signal-to-Noise Ratio (PSNR) values higher to 53 dB for the watermarked images and average PSNR values higher to 32 dB to the extracted watermark for the entire dataset. Also, we tested the method against image processing and geometric attacks successfully extracting the watermarking. A comparison of the proposed method against state-of-the-art was performed, obtaining competitive results. On the other hand, we classified the DR grade of the fundus image dataset using four trained deep learning models (VGG16, ResNet50, InceptionV3, and YOLOv8) to evaluate the inference results using the originals and marked images. Thus, the results show that DR grading remains both in the non-marked and marked images

Nongenomic actions of glucocorticosteroids on the airway vasculature in asthma

Inhaled glucocorticosteroids (corticosteroids) continue to be the standard treatment for nonexacerbated asthma because of their anti-inflammatory actions. These include effects on the airway vasculature, which participates in the inflammatory process. Corticosteroids are now known to have genomic as well as nongenomic effects that involve different mechanisms of action. The genomic vascular effects of inhaled corticosteroids include a decrease in airway wall hypervascularity (inhibition of angiogenesis), reversal of the increased airway blood flow, and inhibition of vascular hyperpermeability and leukocyte recruitment. In addition, inhaled corticosteroids decrease airway blood flow acutely (within minutes) and reversibly through a nongenomic action that involves noradrenergic neurotransmission. This effect is likely related to the binding of inhaled corticosteroids to the plasma membrane of and the inhibition of the extraneuronal monoamine transporter on airway vascular smooth muscle cells, thereby increasing norepinephrine concentrations at alpha(1)-adrenoceptors and causing airway vascular smooth muscle contraction and a decrease in airway blood flow. Inasmuch as vascular hyperperfusion is a manifestation of airway inflammation, the acute vasoconstriction could also be considered an anti-inflammatory effect of inhaled corticosteroids

Prediction of death in less than 60 minutes after withdrawal of cardiorespiratory support in potential organ donors after circulatory death

Background: Given the stable number of potential organ donors after brain death, donors after circulatory death have been an increasing source of organs procured for transplant. Among the most important considerations for donation after circulatory death (DCD) is the prediction that death will occur within a reasonable period of time after the withdrawal of cardiorespiratory support (WCRS). Accurate prediction of time to death is necessary for the procurement process. We aimed to develop simple predictive rules for death in less than 60 min and test the accuracy of these rules in a pool of potential DCD donors. Methods: A multicenter prospective longitudinal cohort design of DCD eligible patients (n=318), with the primary binary outcome being death in less than 60 min after withdrawal of cardiorespiratory support conducted in 28 accredited intensive care units (ICUs) in Australia. We used a random split-half method to produce two samples, first to develop the predictive classification rules and then to estimate accuracy in an independent sample. Results: The best classification model used only three simple classification rules to produce an overall efficiency of 0.79 (0.72-0.85), sensitivity of 0.82 (0.73-0.90), and a positive predictive value of 0.80 (0.70-0.87) in the independent sample. Using only intensive care unit specialist prediction (a single classification rule) produced comparable efficiency 0.80 (0.73-0.86), sensitivity 0.87 (0.78-0.93), and positive predictive value 0.78 (0.68-0.86). Conclusion: This best predictive model missed only 18% of all potential donors. A positive prediction would be incorrect on only 20% of occasions, meaning there is an acceptable level of lost opportunity costs involved in the unnecessary assembly of transplantation teams and theatres

Prediction of death in less than 60 minutes following withdrawal of cardiorespiratory support in ICUs

Half of all ICU patients die within 60 minutes of withdrawal of cardiorespiratory support. Prediction of which patients die before and after 60 minutes would allow changes in service organization to improve patient palliation, family grieving, and allocation of ICU beds. This study tested various predictors of death within 60 minutes and explored which clinical variables ICU specialists used to make their prediction

Hopelessness in Patients with Early-Stage Relapsing-Remitting Multiple Sclerosis

Background: Hopelessness is a risk factor for depression and suicide. There is little information on this phenomenon among patients with relapsing-remitting multiple sclerosis (RRMS), one of the most common causes of disability and loss of autonomy in young adults. The aim of this study was to assess state hopelessness and its associated factors in early-stage RRMS. Methods: A multicenter, non-interventional study was conducted. Adult patients with a diagnosis of RRMS, a disease duration ≤ 3 years, and an Expanded Disability Status Scale (EDSS) score of 0– 5.5 were included. The State-Trait Hopelessness Scale (STHS) was used to measure patients´ hopelessness. A battery of patient-reported and clinician-rated measurements was used to assess clinical status. A multivariate logistic regression analysis was conducted to determine the association between patients’ characteristics and state hopelessness. Results: A total of 189 patients were included. Mean age (standard deviation-SD) was 36.1 (9.4) years and 71.4% were female. Median disease duration (interquartile range-IQR) was 1.4 (0.7, 2.1) years. Symptom severity and disability were low with a median EDSS (IQR) score of 1.0 (0, 2.0). A proportion of 65.6% (n=124) of patients reported moderate-to-severe hopelessness. Hopelessness was associated with older age (p=0.035), depressive symptoms (p=< 0.001), a threatening illness perception (p=0.001), and psychological and cognitive barriers to workplace performance (p=0.029) in the multivariate analysis after adjustment for confounders. Conclusion: Hopelessness was a common phenomenon in early-stage RRMS, even in a population with low physical disability. Identifying factors associated with hopelessness may be critical for implementing preventive strategies helping patients to adapt to the new situation and cope with the disease in the long term

Long-term prognosis communication preferences in early-stage relapsing-remitting multiple sclerosis.

Multiple sclerosis is one of the most common causes of neurological disability in young adults with major consequences for their future lives. Improving communication strategies on prognosis may help patients deal with the disease and adjust their long-term life goals. However, there is limited information on patients' preferences of long-term prognosis (LTP) communication and associated factors. The aim of this study was to describe patients' preferences and assess the factors associated with LTP communication preferences in early-stage relapsing-remitting multiple sclerosis (RRMS) patients. A multicenter, non-interventional study was conducted. Adult patients with a diagnosis of RRMS, a disease duration from first attack ≤ 3 years, and an Expanded Disability Status Scale (EDSS) score of 0-5.5 were included. The Prognosis in MS questionnaire was used to assess how much patients want to know about their LTP. Different patient-reported measures were administered to gather information on symptom severity, pain, fatigue, mood/anxiety, quality of life, stigma, illness perception, feeling of hopelessness, self-efficacy, information avoidance and coping strategies. Cognition was assessed using the Symbol Digit Modalities Test (SDMT). A multivariate logistic regression analysis was performed to assess the association between LTP information preference and demographic and clinical characteristics, as well as patients' perspectives. A total of 189 patients were included (mean age: 36.1  ±  9.4 years, 71.4% female, mean disease duration: 1.2  ±  0.8 years). Median EDSS score was 1.0 (IQR = 0.0-2.0). A proportion of 68.5% (n  =  126) of patients had never discussed LTP with their neurologists, whereas 69.2% (n = 126) reported interest in knowing it (73.5% at diagnosis). Bivariate analyses suggested that patients were significantly more likely to have higher LTP information preferences if they were male and had a lower SDMT score. Male gender and a lower SDMT score were predictors of LTP information preferences. Patients with early-stage RRMS want to discuss their LTP shortly after diagnosis. Understanding the factors involved may be useful to design individualized communication strategies