The ⁶⁸ Ga-prostate-specific membrane antigen ( ⁶⁸ Ga-PSMA) has been recently developed to be used, as a ligand, in positron emission tomography/computed tomography (PET/CT) prostate cancer imaging, to detect prostate disease. The main objective of this review was to collect data and findings from other studies and articles to assess, theoretically, if ⁶⁸ GA-PSMA PET/CT is a more appropriate prostate cancer diagnostic technique in comparison with others available such as CT, ¹⁸ F-fluoro-2-deoxyglucose PET/CT, or ¹⁸ F-fluoromethylcholine ( ¹⁸ F-choline) PET/CT. For that purpose, PubMed, the online scientific articles' database, was consulted where the keywords "PSMA" and "PET" were used to find relevant articles. The clinicaltrials.gov, clinical trials' database, was also consulted where the keywords " ⁶⁸ Ga-PSMA" and "prostate" were used to search clinical trials. Based on the reviewed scientific literature, several studies were conducted to assess and compare the ⁶⁸ Ga-PSMA PET/CT detection rate in prostate cancer with other available techniques. One of those studies, conducted by Giesel et al., concluded, within study sample, that 75% of patients with lymph nodes detected by ⁶⁸ Ga-PSMA PET/CT would have not been identified using other conventional morphological criteria based techniques. In Eiber et al.'s study, ⁶⁸ Ga-PSMA PET detected prostatic disease findings in 67% of patients with prostate-specific antigen levels <1 ng/mL, when compared with choline-based PET that presented detection rates between 19% and 36%. In Bluemel et al.'s study, ⁶⁸ Ga-PSMA identified positive prostatic disease in 43.8% of the patients with negative findings in F-choline PET/CT. Findings from this review demonstrate that ⁶⁸ Ga-PSMA PET/C is more effective in detecting metastases, lymph nodes, and recurrent prostate cancer when compared to ¹⁸ F-choline-based PET/CT and CT. ⁶⁸ Ga-PSMA PET/CT presents also more imaging contrast and can be more cost-effective. ⁶⁸ Ga-PSMA has already been subjected to first-in-human trials, and it is now being tested in Phase II and III trials.

We present the case of a patient with history of colon cancer, referred for the evaluation of indeterminate pulmonary nodules by 18F-FDG PET/CT. A dual–time point protocol was performed, and images were reconstructed using VUE Point HD and a Bayesian-penalized likelihood reconstruction algorithm (Q.Clear). Visually, the quality of the images was considered better when Q.Clear was used with β value of 200, uptake in the smallest nodule (7 mm) was clearly visible only with Q.Clear reconstruction, and uptake in the smaller nodules was best defined in the delayed time point acquisition. Quantitative parameters were also higher for Q.Clear.

This article proposes a fully automated computational solution to segment the incus and malleus ear ossicles in conventional tri-dimensional X-ray computed tomography images. The solution uses a registration-based segmentation paradigm, followed by image segmentation refinement. It was tested against a dataset comprising 21 computed tomography volumetric images of the ear acquired using standard protocols and with resolutions varying from 0.162 × 0.162 × 0.6 to 0.166 × 0.166 × 1.0 mm³. The images used were randomly selected from subjects who had had a computed tomography examination of the ear due to ear-related pathologies. Dice’s coefficient and the Hausdorff distance were used to compare the results of the automated segmentation against those of a manual segmentation performed by two experts. The mean agreement between automated and manual segmentations was equal to 0.956 (Dice’s coefficient), and the mean Hausdorff distance among the shapes obtained was 1.14 mm, which is approximately equal to the maximum distance between the neighbouring voxels in the dataset tested. The results confirm that the automated segmentation of the incus and malleus ossicles in tri-dimensional images acquired from patients with ear-related pathologies, using conventional computed tomography scanners and standard protocols, is feasible, robust and accurate. Thus, the solution developed can be employed efficiently in computed tomography ear examinations to help radiologists and otolaryngologists in the evaluation of bi-dimensional slices by providing the related tri-dimensional model.