Exploring CT Texture Parameters as Predictive and Response Imaging Biomarkers of Survival in Patients With Metastatic Melanoma Treated With PD-1 Inhibitor Nivolumab: A Pilot Study Using a Delta-Radiomics Approach

In the era of artificial intelligence and precision medicine, the use of quantitative imaging methodological approaches could improve the cancer patient’s therapeutic approaches. Specifically, our pilot study aims to explore whether CT texture features on both baseline and first post-treatment contrast-enhanced CT may act as a predictor of overall survival (OS) and progression-free survival (PFS) in metastatic melanoma (MM) patients treated with the PD-1 inhibitor Nivolumab. Ninety-four lesions from 32 patients treated with Nivolumab were analyzed. Manual segmentation was performed using a free-hand polygon approach by drawing a region of interest (ROI) around each target lesion (up to five lesions were selected per patient according to RECIST 1.1). Filtration-histogram-based texture analysis was employed using a commercially available research software called TexRAD (Feedback Medical Ltd, London, UK; https://fbkmed.com/texrad-landing-2/) Percentage changes in texture features were calculated to perform delta-radiomics analysis. Texture feature kurtosis at fine and medium filter scale predicted OS and PFS. A higher kurtosis is correlated with good prognosis; kurtosis values greater than 1.11 for SSF = 2 and 1.20 for SSF = 3 were indicators of higher OS (fine texture: 192 HR = 0.56, 95% CI = 0.32–0.96, p = 0.03; medium texture: HR = 0.54, 95% CI = 0.29–0.99, p = 0.04) and PFS (fine texture: HR = 0.53, 95% CI = 0.29–0.95, p = 0.03; medium texture: HR = 0.49, 209 95% CI = 0.25–0.96, p = 0.03). In delta-radiomics analysis, the entropy percentage variation correlated with OS and PFS. Increasing entropy indicates a worse outcome. An entropy variation greater than 5% was an indicator of bad prognosis. CT delta-texture analysis quantified as entropy predicted OS and PFS. Baseline CT texture quantified as kurtosis also predicted survival baseline. Further studies with larger cohorts are mandatory to confirm these promising exploratory results

Multi-detector row computed tomography (MDCT) and magnetic resonance imaging (MRI) in the evaluation of the mandibular invasion by squamous cell carcinomas (SCC) of the oral cavity. Correlation with pathological data

<p>Abstract</p> <p>Background</p> <p>To retrospectively compare the diagnostic accuracy of magnetic resonance imaging (MRI) and multidetector-row computed tomography (MDCT) in the assessment of the mandibular invasion by squamous cell carcinoma (SCC) having histopathological exams as standard of reference.</p> <p>Materials and methods</p> <p>Institutional review board approval with a waiver of informed patient consent was obtained. Of the 147 patients selected from our database who underwent surgical excision of a tumour arising into the oral cavity, thirty-six patients (26 men, 10 women; mean age, 56 years; range, 30-75 years) with hystologically proven SCC who performed both a preoperative MRI and MDCT, composed our final study population.</p> <p>Images were qualitatively analyzed in consensus by two expert radiologist in head and neck imaging. Sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) were assessed for both MRI and MDCT.</p> <p>Differences in sensitivity, specificity, positive and negative predictive values were calculated at a statistical significance of p < .05.</p> <p>Results</p> <p>The sensitivity, the specificity and the accuracy of MRI and MDCT in the detection of the mandibular involvement were respectively 93%, 82%, 86% and 79%, 82%, 81%, while the positive predictive value (PPV) and negative predictive value (NPV) were respectively 76%, 95% and 73%, 86%. There wasn't any statistically significant difference in overall diagnostic accuracy between MRI and MDCT in the evaluation of mandibular tumour invasion (p > .05).</p> <p>Conclusion</p> <p>MRI showed to have a higher sensitivity compare to MDCT in the assessment of mandibular involvement from SCC arising in the oral cavity although none statistically significant differences were noted.</p

Participatory Disease Surveillance Systems: Ethical Framework.

Advances in information technology are changing public health at an unprecedented rate. Participatory surveillance systems are contributing to public health by actively engaging digital (eg, Web-based) communities of volunteer citizens to report symptoms and other pertinent information on public health threats and also by empowering individuals to promptly respond to them. However, this digital model raises ethical issues on top of those inherent in traditional forms of public health surveillance. Research ethics are undergoing significant changes in the digital era where not only participants' physical and psychological well-being but also the protection of their sensitive data have to be considered. In this paper, the digital platform of Influenzanet is used as a case study to illustrate those ethical challenges posed to participatory surveillance systems using digital platforms and mobile apps. These ethical challenges include the implementation of electronic consent, the protection of participants' privacy, the promotion of justice, and the need for interdisciplinary capacity building of research ethics committees. On the basis of our analysis, we propose a framework to regulate and strengthen ethical approaches in the field of digital public health surveillance