Several reports have shown that radiomic features are affected by acquisition and reconstruction parameters, thus hampering multicenter studies. We propose a method that, by removing the center effect while preserving patient-specific effects, standardizes features measured from PET images obtained using different imaging protocols. PretreatmentF-FDG PET images of patients with breast cancer were included. In one nuclear medicine department (department A), 63 patients were scanned on a time-of-flight PET/CT scanner, and 16 lesions were triple-negative (TN). In another nuclear medicine department (department B), 74 patients underwent PET/CT on a different brand of scanner and a different reconstruction protocol, and 15 lesions were TN. The images from department A were smoothed using a gaussian filter to mimic data from a third department (department A-S). The primary lesion was segmented to obtain a lesion volume of interest (VOI), and a spheric VOI was set in healthy liver tissue. Three SUVs and 6 textural features were computed in all VOIs. A harmonization method initially described for genomic data was used to estimate the department effect based on the observed feature values. Feature distributions in each department were compared before and after harmonization. In healthy liver tissue, the distributions significantly differed for 4 of 9 features between departments A and B and for 6 of 9 between departments A and A-S ( < 0.05, Wilcoxon test). After harmonization, none of the 9 feature distributions significantly differed between 2 departments ( > 0.1). The same trend was observed in lesions, with a realignment of feature distributions between the departments after harmonization. Identification of TN lesions was largely enhanced after harmonization when the cutoffs were determined on data from one department and applied to data from the other department. The proposed harmonization method is efficient at removing the multicenter effect for textural features and SUVs. The method is easy to use, retains biologic variations not related to a center effect, and does not require any feature recalculation. Such harmonization allows for multicenter studies and for external validation of radiomic models or cutoffs and should facilitate the use of radiomic models in clinical practice.
Occult liver micrometastases in rats generate changes in liver perfusion that can be detected with CT.
Few methodological studies regarding widely used textural indices robustness in MRI have been reported. In this context, this study aims to propose some rules to compute reliable textural indices from multimodal 3D brain MRI. Diagnosis and post-biopsy MR scans including T1, post-contrast T1, T2 and FLAIR images from thirty children with diffuse intrinsic pontine glioma (DIPG) were considered. The hybrid white stripe method was adapted to standardize MR intensities. Sixty textural indices were then computed for each modality in different regions of interest (ROI), including tumor and white matter (WM). Three types of intensity binning were compared [Formula: see text]: constant bin width and relative bounds; [Formula: see text] constant number of bins and relative bounds; [Formula: see text] constant number of bins and absolute bounds. The impact of the volume of the region was also tested within the WM. First, the mean Hellinger distance between patient-based intensity distributions decreased by a factor greater than 10 in WM and greater than 2.5 in gray matter after standardization. Regarding the binning strategy, the ranking of patients was highly correlated for 188/240 features when comparing [Formula: see text] with [Formula: see text], but for only 20 when comparing [Formula: see text] with [Formula: see text], and nine when comparing [Formula: see text] with [Formula: see text]. Furthermore, when using [Formula: see text] or [Formula: see text] texture indices reflected tumor heterogeneity as assessed visually by experts. Last, 41 features presented statistically significant differences between contralateral WM regions when ROI size slightly varies across patients, and none when using ROI of the same size. For regions with similar size, 224 features were significantly different between WM and tumor. Valuable information from texture indices can be biased by methodological choices. Recommendations are to standardize intensities in MR brain volumes, to use intensity binning with constant bin width, and to define regions with the same volumes to get reliable textural indices.
Objective:To evaluate the cytotoxicity of iron nanoparticles on cardiac cells and to determine whether they can modulate the biological activity of 7-ketocholesterol (7KC) involved in the development of cardiovascular diseases. Nanoparticles of iron labeled with Texas Red are introduced in cultures of nonbeating mouse cardiac cells (HL1-NB) with or without 7-ketocholesterol 7KC, and their ability to induce cell death, pro-inflammatory and oxidative effects are analyzed simultaneously.Study design:Flow cytometry (FCM), confocal laser scanning microscopy (CLSM), and subsequent factor analysis image processing (FAMIS) are used to characterize the action of iron nanoparticles and to define their cytotoxicity which is evaluated by enhanced permeability to SYTOX Green, and release of lactate deshydrogenase (LDH). Pro-inflammatory effects are estimated by ELISA in order to quantify IL-8 and MCP-1 secretions. Pro-oxidative effects are measured with hydroethydine (HE).Results:Iron Texas Red nanoparticles accumulate at the cytoplasmic membrane level. They induce a slight LDH release, and have no inflammatory or oxidative effects. However, they enhance the cytotoxic, pro-inflammatory and oxidative effects of 7KC. The accumulation dynamics of SYTOX Green in cells is measured by CLSM to characterize the toxicity of nanoparticles. The emission spectra of SYTOX Green and nanoparticles are differentiated, and corresponding factor images specify the possible capture and cellular localization of nanoparticles in cells.Conclusion:The designed protocol makes it possible to show how Iron Texas Red nanoparticles are captured by cardiomyocytes. Interestingly, whereas these fluorescent iron nanoparticles have no cytotoxic, pro-inflammatory or oxidative activities, they enhance the side effects of 7KC.
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