Post Surgical Management of WHO Grade II Meningiomas: Our Experience, the Role of Gamma Knife and a Literature Review.

Grade II meningiomas are rarer than Grade I, and when operated on, bear a higher risk of local recurrence, with a 5-year progression free survival (PFS) ranging from 59 to 90%. Radiotherapy (RT) or radiosurgery, such as Gamma Knife radiosurgery (GKRS) can reduce the risk of relapse in patients with residual disease, even if their role, particularly after gross total resection (GTR), is still under debate. Main goal of this study was to compare the outcomes of different post-surgical management of grade II meningiomas, grouped by degree of surgical removal (Simpson Grade); next in order we wanted to define the role of GKRS for the treatment of residual disease or relapse.

A hybrid machine learning/deep learning COVID-19 severity predictive model from CT images and clinical data.

COVID-19 clinical presentation and prognosis are highly variable, ranging from asymptomatic and paucisymptomatic cases to acute respiratory distress syndrome and multi-organ involvement. We developed a hybrid machine learning/deep learning model to classify patients in two outcome categories, non-ICU and ICU (intensive care admission or death), using 558 patients admitted in a northern Italy hospital in February/May of 2020. A fully 3D patient-level CNN classifier on baseline CT images is used as feature extractor.

F-formation detection: individuating free-standing conversational groups in images.

Detection of groups of interacting people is a very interesting and useful task in many modern technologies, with application fields spanning from video-surveillance to social robotics. In this paper we first furnish a rigorous definition of group considering the background of the social sciences: this allows us to specify many kinds of group, so far neglected in the Computer Vision literature. On top of this taxonomy we present a detailed state of the art on the group detection algorithms.

Sentinel lymph node as a new marker for therapeutic planning in breast cancer patients.

Background And Objectives: Literature review suggests that the sentinel lymph node (sN) represents a reliable predictor of axillary lymph node status in breast cancer patients; however, some important issues, such as the optimisation of the technique for the intraoperative identification of the sN, the role of intraoperative frozen section examination of the sN, and the clinical implications of sN metastasis as regards the surgical management of the axilla, still require further confirmation. The authors aimed (1) to assess the feasibility of sN identification with a combined approach (vital blue dye lymphatic mapping and radioguided surgery, RGS) and the specific contribution of either techniques to the detection of the sN, (2) to determine the accuracy and usefulness of intraoperative frozen section examination of the sN in order to perform a one-stage surgical procedure, and (3) to define how the sN might modulate the therapeutic planning in different stages of disease.

Materials And Methods: From October 1997 to June 2001, 334 patients with early-stage (T(1-2) N(0) M(0)) invasive mammary carcinoma underwent sN biopsy; the average age of patients was 61.

Imaging characteristics evaluation of a digital radiography system.

Purpose: To evaluate the physical imaging characteristics of an indirect digital radiography system used for general radiography.

Material And Methods: The performance of the two 41x41 cm2 CsI:Tl/a-Si flat-panel detectors of a GE-Revolution XR/d digital radiography system was evaluated. Signal uniformity, dose linearity, pre-sampling and expectation Modulation Transfer Function (MTF), Noise Power Spectrum (NPS) and Detective Quantum Efficiency (DQE) were measured at 70 kVp, varying the incident dose levels, according to IEC 62220-1.