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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., (© 2022. The Author(s).)

To date, a wide variety of potential PET-apoptosis imaging radiopharmaceuticals targeting apoptosis-induced cell membrane asymmetry and acidification, as well as caspase 3 activation (substrates and inhibitors) have been developed with the purpose of rapidly assessing the response to treatment in cancer patients. Many of these probes were shown to specifically bind to their apoptotic target in vitro and their uptake to be enhanced in the in vivo-xenografted tumours in mice treated by means of chemotherapy, however, to a significantly variable degree. This may, in part, relate to the tumour model used given the fact that different tumour cell lines bear a different sensitivity to a similar chemotherapeutic agent, to differences in the chemotherapeutic concentration and exposure time, as well as to the different timing of imaging performed post-treatment. The best validated cell membrane acidification and caspase 3 targeting radioligands, respectively 18 F-ML-10 from the Aposense family and the radiolabelled caspase 3 substrate 18 F-CP18, have also been injected in healthy individuals and shown to bear favourable dosimetric and safety characteristics. However, in contrast to, for instance, the 99m Tc-HYNIC-Annexin V, neither of both tracers was taken up to a significant degree by the bone marrow in the healthy individuals under study. Removal of white and red blood cells from the bone marrow through apoptosis plays a major role in the maintenance of hematopoietic cell homeostasis. The major apoptotic population in normal bone marrow are immature erythroblasts. While an accurate estimate of the number of immature erythroblasts undergoing apoptosis is not feasible due to their unknown clearance rate, their number is likely substantial given the ineffective quote of the erythropoietic process described in healthy subjects. Thus, the clinical value of both 18 F-ML-10 and 18 F-CP18 for apoptosis imaging in cancer patients, as suggested by a small number of subsequent clinical phase I/II trials in patients suffering from primary or secondary brain malignancies using 18 F-ML-10 and in an ongoing trial in patients suffering from cancer of the ovaries using 18 F-CP18, remains to be proven and warrants further investigation.