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Background Pectoral muscle removal is a fundamental preliminary step in computer-aided diagnosis systems for full-field digital mammography (FFDM). Currently, two open-source publicly available packages (LIBRA and OpenBreast) provide algorithms for pectoral muscle removal within Matlab environment. Purpose To compare performance of the two packages on a single database of FFDM images. Methods Only mediolateral oblique (MLO) FFDM was considered because of large presence of pectoral muscle on this type of projection. For obtaining ground truth, pectoral muscle has been manually segmented by two radiologists in consensus. Both LIBRA’s and OpenBreast’s removal performance with respect to ground truth were compared using Dice similarity coefficient and Cohen-kappa reliability coefficient; Wilcoxon signed-rank test has been used for assessing differences in performances; Kruskal–Wallis test has been used to verify possible dependence of the performance from the breast density or image laterality. Results FFDMs from 168 consecutive women at our institution have been included in the study. Both LIBRA’s Dice-index and Cohen-kappa were significantly higher than OpenBreast (Wilcoxon signed-rank test P P > 0.05). Conclusion: Libra has a better performance than OpenBreast in pectoral muscle delineation so that, although our study has not a direct clinical application, these results are useful in the choice of packages for the development of complex systems for computer-aided breast evaluation.

Background Since the pioneering reports of the so-called leonine face in cluster headache (CH) patients, cranial and facial features of these patients have been poorly investigated with conflicting results. We aimed to investigate whether abnormalities in craniometric measurements could characterize male CH patients and represent reliable and reproducible diagnostic biomarkers able to identify CH patients. Methods Brain CT images were recorded between 2018 and 2020 in 24 male patients with CH and in 24 matched healthy controls (HC). Then, craniometric measurements were obtained, and logistic regression and receiver operating characteristic curves analyses were used to identify the craniometric abnormalities able to distinguish CH patients from HC. Results Logistic regression analyses showed that frontal bone height and facial width were able to discriminate, one independently from the other, CH patients from HC with an overall accuracy of 77%. The optimal cutoff score in detecting the probable presence of CH was 11.50 cm for frontal bone height and 13.30 cm for facial width. Discussion In the present study we found, for the first time by means of brain 3D computed tomography approach, abnormal craniometric measurements in CH patients when compared with HC. The absence of differences in smoke and alcohol intake suggests that the observed craniometric abnormalities may represent a specific feature of CH patients. Conclusion The craniometric evaluation by means of brain 3D computed tomography could represent a widespread, noninvasive, and accurate tool to support CH diagnosis to avoid frequent misdiagnosis or delay in the diagnostic process.

In the present case the assessment of wound healing and neurosensory function of the inferior alveolar nerve and of the lingual nerve in the immediate postoperative period and at one year follow up was totally satisfactory. Besides, when compared to surgery performed by using traditional rotation instruments, it is reasonable to speculate that the surgical trauma was markedly reduced in this case due to the intrinsic features of the Piezoelectric device, as described above, in conjunction to the specific morphology of the device inserts. We therefore promote the use of Piezoelectric device in surgical cases where risk for noble soft tissue damage is high. In particular, the issue of inferior alveolar nerve injury during the removal of lower third molars is a well known clinical and medico-legal problem so any technique that can reduce the possibility of this damage is worthy of exploration.