Algorithm for Reducing Overall Biological Detriment Caused by PET/CT: an Age-Based Study.

Purpose: This study is to use a simple algorithm based on patient's age to reduce the overall biological detriment associated with PET/CT. Materials and Methods: A total of 421 consecutive patients (mean age 64 ± 14 years) undergoing PET for various clinical indications were enrolled. For each scan, effective dose (ED in mSv) and additional cancer risk (ACR) were computed both in a reference condition (REF) and after applying an original algorithm (ALGO). The ALGO modified the mean dose of FDG and the PET scan time parameters; indeed, a lower dose and a longer scan time were reported in the younger, while a higher dose and a shorter scan time in the older patients. Moreover, patients were classified by age bracket (18-29, 30-60, and 61-90 years). Results: The ED was 4.57 ± 0.92 mSv in the REF condition. The ACR were 0.020 ± 0.016 and 0.0187 ± 0.013, respectively, in REF and ALGO. The ACR for the REF and ALGO conditions were significantly reduced in males and females, although it was more evident in the latter gender (all p < 0.0001). Finally, the ACR significantly reduced from the REF condition to ALGO in all three age brackets (all p < 0.0001). Conclusion: Implementation of ALGO protocols in PET can reduce the overall ACR, mainly in young and female patients.

Vasari Scoring System in Discerning between Different Degrees of Glioma and IDH Status Prediction: A Possible Machine Learning Application?

(1) The aim of our study is to evaluate the capacity of the Visually AcceSAble Rembrandt Images (VASARI) scoring system in discerning between the different degrees of glioma and Isocitrate Dehydrogenase (IDH) status predictions, with a possible application in machine learning. (2) A retrospective study was conducted on 126 patients with gliomas (M/F = 75/51; mean age: 55.30), from which we obtained their histological grade and molecular status. Each patient was analyzed with all 25 features of VASARI, blinded by two residents and three neuroradiologists. The interobserver agreement was assessed. A statistical analysis was conducted to evaluate the distribution of the observations using a box plot and a bar plot. We then performed univariate and multivariate logistic regressions and a Wald test. We also calculated the odds ratios and confidence intervals for each variable and the evaluation matrices with receiver operating characteristic (ROC) curves in order to identify cut-off values that are predictive of a diagnosis. Finally, we did the Pearson correlation test to see if the variables grade and IDH were correlated. (3) An excellent ICC estimate was obtained. For the grade and IDH status prediction, there were statistically significant results by evaluation of the degree of post-contrast impregnation (F4) and the percentage of impregnated area (F5), not impregnated area (F6), and necrotic (F7) tissue. These models showed good performances according to the area under the curve (AUC) values (>70%). (4) Specific MRI features can be used to predict the grade and IDH status of gliomas, with important prognostic implications. The standardization and improvement of these data (aim: AUC > 80%) can be used for programming machine learning software.

Delta-radiomics increases multicentre reproducibility: a phantom study.

Texture analysis (TA) can provide quantitative features from medical imaging that can be correlated to clinical endpoints. The challenges relevant to robustness of radiomics features have been analyzed by many researchers, as it seems to be influenced by acquisition and reconstruction protocols. Delta-texture analysis (D-TA), conversely, consist in the analysis of TA feature variations at different acquisition times, usually before and after a therapy. Aim of this study was to investigate the influence of different CT scanners and acquisition parameters in the robustness of TA and D-TA. We scanned a commercial phantom (CIRS model 467, Gammex, Middleton, WI, USA), that is used for the calibration of electron density, two times by varying the disposition of plugs, using three different scanners. After the segmentation, we extracted TA features with LifeX and calculated TA features and D-TA features, defined as the variation of each TA parameters extracted from the same position by varying the plugs with the formula (Y-X)/X. The robustness of TA and D-TA features were then tested with intraclass coefficient correlation (ICC) analysis. The reliability of TA parameters across different scans, with different acquisition parameters and ROI positions has shown poor reliability in 12/37 and moderate reliability in the remaining 25/37, with no parameters showing good reliability. The reliability of D-TA, conversely, showed poor reliability in 10/37 parameters, moderate reliability in 10/37 parameters, and good reliability in 17/37 parameters. The comparison between TA and D-TA ICCs showed a significant difference for the whole group of parameters (p:0.004) and for the subclasses of GLCM parameters (p:0.033), whereas for the other subclasses of matrices (GLRLM, NGLDM, GLZLM, Histogram), the difference was not significant. D-TA features seem to be more robust than TA features. These findings reinforce the potentiality for using D-TA features for early assessment of treatment response and for developing tailored therapies. More work is needed in a clinical setting to confirm the results of the present study.

Overall survival and progression-free survival in patients with primary brain tumors after treatment: is the outcome of [18F] FDOPA PET a prognostic factor in these patients?

AIM: To investigate the progression-free survival (PFS) and the overall survival (OS) in a population affected by primary brain tumors (PBT) evaluated by [18F]-L-dihydroxyphenylalanine ([18F] FDOPA) positron emission tomography/computed tomography (PET/CT). MATERIALS AND METHODS: 133 subjects with PBT (65 women and 68 men, mean age 45 ± 10 years old) underwent 18F FDOPA PET/CT after treatment. Of them, 68 (51.2%) were Grade II, 34 (25.5%) were Grade III and 31 (23.3%) were Grade IV. PET/CT was scored as positive or negative and standardized uptake value ratio (SUVr) was calculated as the ratio between SUVmax of the lesion vs. that of the background. Patients have been observed for a mean of 24 months. RESULTS: The outcome of [18F] FDOPA PET/CT scan was significantly related to the OS and PFS in Grade II gliomas. In Grade II PBT, the OS proportions at 24 months were 100% in subjects with a negative PET/CT scan and 82% in those with a positive scan. Gehan-Breslow-Wilcoxon test showed a significant difference in the OS curves (P = 0.03) and the hazard-ratio was equal to 5.1 (95% CI of ratio 1.1-23.88). As for PFS, the proportion at 24 months was 90% in subjects with a negative PET/CT scan and 58% in those with a positive scan. Gehan-Breslow-Wilcoxon test showed a significant difference in the OS curves (P = 0.007) and the hazard-ratio was equal to 4.1 (95% CI of ratio 1.3-8). We did not find any significant relationship between PET outcome and OS and PFS in Grade III and IV PBT. CONCLUSIONS: A positive [18F] FDOPA PET/CT scan is related to a poor OS and PFS in subjects with low-grade PBT. This imaging modality could be considered as a prognostic factor in these subjects.