La Radiologia medica
-
La Radiologia medica · Jul 2021
ReviewInterventional Radiology ex-machina: impact of Artificial Intelligence on practice.
Artificial intelligence (AI) is a branch of Informatics that uses algorithms to tirelessly process data, understand its meaning and provide the desired outcome, continuously redefining its logic. AI was mainly introduced via artificial neural networks, developed in the early 1950s, and with its evolution into "computational learning models." Machine Learning analyzes and extracts features in larger data after exposure to examples; Deep Learning uses neural networks in order to extract meaningful patterns from imaging data, even deciphering that which would otherwise be beyond human perception. Thus, AI has the potential to revolutionize the healthcare systems and clinical practice of doctors all over the world. ⋯ Related in spirit to Artificial intelligence are Augmented Reality, mixed reality, or Virtual Reality, which are able to enhance accuracy of minimally invasive treatments in image guided therapies by Interventional Radiologists. The potential applications of AI in IR go beyond computer vision and diagnosis, to include screening and modeling of patient selection, predictive tools for treatment planning and navigation, and training tools. Although no new technology is widely embraced, AI may provide opportunities to enhance radiology service and improve patient care, if studied, validated, and applied appropriately.
-
La Radiologia medica · May 2021
Multicenter StudyAcute pulmonary embolism in hospitalized patients with SARS-CoV-2-related pneumonia: multicentric experience from Italian endemic area.
To analyze pulmonary embolism (PE) on chest computed tomography pulmonary angiography (CTPA) in hospitalized patients affected by SARS-CoV-2, according to the severity of lung disease based both on temporal CT features changes and on CT-severity lung involvement (CT-severity score), along with the support of clinical and laboratory findings. ⋯ Patients hospitalized for SARS-CoV-2 infection present a higher cumulative incidence of PE compared to the general population of hospitalized patients, regardless of the severity of lung inflammation or the temporal stage of the disease.
-
La Radiologia medica · Apr 2021
COVID-19 pneumonia: computer-aided quantification of healthy lung parenchyma, emphysema, ground glass and consolidation on chest computed tomography (CT).
To calculate by means of a computer-aided tool the volumes of healthy residual lung parenchyma, of emphysema, of ground glass opacity (GGO) and of consolidation on chest computed tomography (CT) in patients with suspected viral pneumonia by COVID-19. ⋯ We demonstrated that, using a computer-aided tool, the COVID-19 pneumonia was mirrored with a percentage median value of GGO of 19.50% and that only GGO volume had a difference significant between the patients with suspected or non-suspected CT for COVID-19 infection.
-
La Radiologia medica · Feb 2021
Quantitative Chest CT analysis in discriminating COVID-19 from non-COVID-19 patients.
COVID-19 pneumonia is characterized by ground-glass opacities (GGOs) and consolidations on Chest CT, although these CT features cannot be considered specific, at least on a qualitative analysis. The aim is to evaluate if Quantitative Chest CT could provide reliable information in discriminating COVID-19 from non-COVID-19 patients. ⋯ Quantification of GGOs and fibrotic alterations on Chest CT could be able to identify patients with COVID-19.