Principal component analysis of texture features derived from FDG PET images of melanoma lesions.

BACKGROUND: The clinical utility of radiomics is hampered by a high correlation between the large number of features analysed which may result in the "bouncing beta" phenomenon which could in part explain why in a similar patient population texture features identified and/or cut-off values of prognostic significance differ from one study to another. Principal component analysis (PCA) is a technique for reducing the dimensionality of large datasets containing highly correlated variables, such as texture feature datasets derived from FDG PET images, increasing data interpretability whilst at the same time minimizing information loss by creating new uncorrelated variables that successively maximize variance. Here, we report on PCA of a texture feature dataset derived from 123 malignant melanoma lesions with a significant range in lesion size using the freely available LIFEx software. RESULTS: Thirty-eight features were derived from all lesions. All features were standardized. The statistical assumptions for carrying out PCA analysis were met. Seven principal components with an eigenvalue > 1 were identified. Based on the "elbow sign" of the Scree plot, only the first five were retained. The contribution to the total variance of these components derived using Varimax rotation was, respectively, 30.6%, 23.6%, 16.1%, 7.4% and 4.1%. The components provided summarized information on the locoregional FDG distribution with an emphasis on high FDG uptake regions, contrast in FDG uptake values (steepness), tumour volume, locoregional FDG distribution with an emphasis on low FDG uptake regions and on the rapidity of changes in SUV intensity between different regions. CONCLUSIONS: PCA allowed to reduce the dataset of 38 features to a set of 5 uncorrelated new variables explaining approximately 82% of the total variance contained within the dataset. These principal components may prove more useful for multiple regression analysis considering the relatively low numbers of patients usually included in clinical trials on FDG PET texture analysis. Studies assessing the superior differential diagnostic, predictive or prognostic value of principal components derived using PCA as opposed to the initial texture features in clinical relevant settings are warranted.

A novel assessment method for COVID-19 humoral immunity duration using serial measurements in naturally-infected and vaccinated subjects.

BackgroundIt is crucial for medical decision-making and vaccination strategies to collect information on sustainability of immune responses after infection or vaccination, and how long-lasting antibodies against SARS-COV-2 could provide a humoral and protective immunity, preventing reinfection with SARS-CoV-2 or its variants. The aim of this study is to present a novel method to quantitatively measure and monitor the diversity of SARS-CoV-2 specific antibody profiles over time. MethodsTwo collections of serum samples were used in this study: A collection from 20 naturally infected subjects (follow-ups to 1 year) and a collection from 83 subjects vaccinated with one or two doses of Pfizer BioNtech vaccine (BNT162b2/BNT162b2) (follow-ups to 6 months). The Multi-SARS-CoV-2 assay, a multiparameter serology test, developed for the serological confirmation of past-infections was used to determine the reactivity of six different SARS-CoV-2 antigens. For each patient sample, 3 dilutions (1/50, 1/400 and 1/3200) were defined as an optimal set over the six antigens and their respective linear ranges, allowing accurate quantitation of the corresponding six specific antibodies. Nonlinear mixed-effects modelling was applied to convert intensity readings from 3 determined dilutions to a single quantification value for each antibody. ResultsMedian half-life for the 20 naturally infected vs 74 vaccinated subjects (two doses) was respectively 120 vs 50 days for RBD, 127 vs 53 days for S1 and 187 vs 86 days for S2 antibodies. Respectively, 90% of the antibody concentration wanes after 398 vs 158 days for RBD, 420 vs 171 days for S1, and 620 vs 225 days for S2 after the second vaccine shot. ConclusionThe newly proposed method, based on a series of a limited number of dilutions, can convert a conventional qualitative assay into a quantitative assay. This conversion helps define the sustainability of specific immune responses against each relevant viral antigen and can help in defining the protection characteristics after an infection or a vaccination.