Objective: To evaluate the value of 2-dimensional (2D) and 3-dimensional (3D) computed tomography texture analysis (CTTA) models in distinguishing fat-poor angiomyolipoma (fpAML) from chromophobe renal cell carcinoma (chRCC). Methods: We retrospectively enrolled 32 fpAMLs and 24 chRCCs. Texture features were extracted from 2D and 3D regions of interest in triphasic CT images. The 2D and 3D CTTA models were constructed with the least absolute shrinkage and selection operator algorithm and texture scores were calculated. The diagnostic performance of the 2D and 3D CTTA models was evaluated with respect to calibration, discrimination, and clinical usefulness. Results: Of the 177 and 183 texture features extracted from 2D and 3D regions of interest, respectively, 5 2D features and 8 3D features were selected to build 2D and 3D CTTA models. The 2D CTTA model (area under the curve [AUC], 0.811; 95% confidence interval [CI], 0.695-0.927) and the 3D CTTA model (AUC, 0.915; 95% CI, 0.838-0.993) showed good discrimination and calibration ( P > .05). There was no significant difference in AUC between the 2 models ( P = .093). Decision curve analysis showed the 3D model outperformed the 2D model in terms of clinical usefulness. Conclusions: The CTTA models based on contrast-enhanced CT images had a high value in differentiating fpAML from chRCC.
Most oligonucleotides fail to enter a cell and cannot escape from endosomes after endocytosis because of their negative charge and large molecular weight. More efficient cellular delivery of oligonucleotides should be developed for the widespread implementation of antisense imaging. The purpose of this study was to construct a novel antisense nanoprobe, 99m Tc-labeled anti-miRNA oligonucleotides/cell-penetrating peptide PepFect6 ( 99m Tc-AMO/PF6), and to evaluate its efficacy for imaging the miRNA-21 expression in A549 lung adenocarcinoma xenografts. Naked AMO and commercial Lipofectamine 2000-based nanoparticles (AMO/LIP) were used for comparison. The cellular delivery efficiency of AMO/PF6 was first investigated by laser confocal scanning microscopy using Cy5.5-labeled probes and further validated by in vivo fluorescence imaging. Then, the probes were labeled with 99m Tc via hydrazinonicotinamide (HYNIC). The cytotoxicity assay, cellular uptake, and retention kinetics of the probes were evaluated in vitro. The biodistribution of the probes was investigated in A549 lung cancer xenografts, and SPECT imaging was performed in vivo. AMO/PF6 showed lower cytotoxicity than AMO/LIP (P < 0.05) but showed no significant difference with naked AMO. Fluorescence microscopy demonstrated more extensive and scattered signal distribution inside the A549 cells by AMO/PF6 than AMO/LIP. The labeling efficiency of 99m Tc-AMO/PF6 was 72.6 ± 1.42%, and the specific activity was 11.6 ± 0.13 MBq/ng. The cellular uptake of 99m Tc-PF6/AMO peaked at 12 h, with the uptake of 11.24 ± 0.12 mol/cell × 10 −16 , and the cellular retention of 99m Tc-AMO/PF6 was 3.92 ± 0.15 mol/cell × 10 −16 at 12 h after interrupted incubation. AMO/PF6 showed higher cellular uptake and retention than naked AMO and AMO/LIP. The biodistribution study showed that the tumor had the highest radioactivity accumulation, with the uptake ratio of tumor/muscle (T/M) increasing from 14.59 ± 0.67 to 21.76 ± 0.98 between 1 and 6 h after injection, followed by the uptake in the kidneys and the liver. The results of in vivo fluorescence and SPECT imaging were consistent with the results of the biodistribution. The tumor was visualized at 6 h after injection of AMO/PF6 with the highest T/M ratio among these probes (P < 0.05). PF6 improves cellular delivery of antisense oligonucleotides via noncovalent nanoparticles. 99m Tc-AMO/PF6 shows favorable imaging properties and is promising for miRNAs imaging in vivo.
PurposeTo develop and validate the radiomics nomogram that combines clinical factors and radiomics features to estimate overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC), and assess the incremental value of radiomics for OS estimation.Materials and MethodsOne hundred ninety-four ccRCC cases were included in the training cohort and 188 ccRCC patients from another hospital as the test cohort. Three-dimensional region-of-interest segmentation was manually segmented on multiphasic contrast-enhanced abdominal CT images. Radiomics score (Rad-score) was calculated from a formula generated via least absolute shrinkage and selection operator (LASSO) Cox regression, after which the association between the Rad-score and OS was explored. The radiomics nomogram (clinical factors + Rad-score) was developed to demonstrate the incremental value of the Rad-score to the clinical nomogram for individualized OS estimation, which was then evaluated in relation to calibration and discrimination.ResultsRad-score, calculated using a linear combination of the 11 screened features multiplied by their respective LASSO Cox coefficients, was significantly associated with OS. Calibration curves showed good agreement between the OS predicted by the nomograms and observed outcomes. The radiomics nomogram presented higher discrimination capability compared to clinical nomogram in the training (C-index: 0.884; 95% CI: 0.808–0.940 vs. 0.803; 95% CI: 0.705–0.899, P < 0.05) and test cohorts (C-index: 0.859; 95% CI: 0.800–0.921 vs. 0.846; 95% CI: 0.777–0.915, P < 0.05).ConclusionsThe radiomics nomogram may be used for predicting OS in patients with ccRCC, and radiomics is useful to assist quantitative and personalized treatment.
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