Subatmospheric pressure inside dural sinuses - new insights

Duralni sinusi nalaze se između meningealnog i periostalnog lista intrakranijske dure mater. Tok krvi u ovim venskim strukturama opsežno je opisan u literaturi. Venska krv prolazi kroz nekoliko venskih sinusa koji se ulijevaju jedan u drugi počevši od sinus sagittalis superiora te u konačnici kroz lijevi i desni sinus sigmoideus. Iako je uočeno da promjena položaja tijela mijenja tlak u sinusima da bismo to objasnili izrađen je novi originalni model duralnih sinusa koji anatomskim i biofizičkim karakteristikama imitira duralne sinuse dobivene venografijom kod pacijenata. Postavljena je nova hipoteza prema kojoj tlakovi unutar duralnih sinusa imaju sudbinu koju prema zakonu o mehanici fluida ima tekućina unutar krute cijevi zatvorene na jednom kraju, kao u našem modelu. Rezultati ukazuju da se subatmosferska vrijednost tlaka pojavljuje u uspravnom položaju tijela, a veličina tlaka odgovara hidrostatskoj razini između otvora modela i mjesta gdje se mjerenje obavlja. Naše istraživanje ukazuje da se tlakovi i u likvoru i u duralnim sinusima ponašaju sukladno zakonu o mehanici fluida, te da ne ovise o gibanju tih tekućina.Dural venous sinuses are located between the meningeal and periosteal layer of intracranial dura mater. The blood flow in those vein structures has been extensively described in literature. Venous blood flows through venous sinuses, starting from the superior sagittal sinus and exiting through the left and right sigmoid sinus. It was noticed in literature that the change in body position leads to change in blood pressure in dural venous sinuses. Thus, in order to explore that phenomenon we developed and constructed an original model of venous dural sinuses, which imitates anatomical and biophysical characteristics of dural sinuses acquired through magnetic venograpy in patients. A new hypothesis was proposed, according to which the blood pressure within dural venous sinuses has the same fate as a fluid within a rigid pipe that is plugged on one end and opened at the other, such as in our model, what is in accordance with the law of fluid mechanics. Our results suggest the occurrence of subatmospheric pressure values in upright body position, with the pressure values proportionate to the hydrostatic distance of the measuring position from the opening end of the model. Our research suggests that the pressures of cerebrospinal fluid and venous blood depend on anatomical and biophysical characteristic of intracranial intradural space what is in accordance with the law of fluid mechanics, and do not depend on movement of those fluids

Artificial Intelligence in Radiology

Since its first use in medical purpose in the 1960s, the concept of artificial intelligence has been especially appealing to health care, particularly radiology. With the development of ever more powerful computers from the 1990s to the present, various forms of artificial intelligence have found their way into different medical specialties – most notably radiology, dermatology, ophthalmology, and pathology. Due to the growing presence of such systems, it is paramount for the specialists handling them to get acquainted with them in order to provide the best service for their patients. It is therefore the aim of this article to explain the most basic principles of artificial intelligence, accentuating the most prominent concepts used in radiology today, such as deep learning and neural networks. It will also mention some of the artificial intelligence systems approved for clinical use in the US, such as IDx-DR, used to discover more than mild diabetic retinopathy in patients over 22 years of age; and Arterys, used for cardiac segmentation and discovering liver and lung nodules. Same as in many other fields, there is a constant need for improvement – in construction, testing, and application of these new technologies. Many ethical questions are asked, considering privacy and liability of artificial intelligence systems in clinical use. One of the greatest concerns for radiologists is the possibility of being replaced by these systems. This scenario seems to be far-fetched, at least for the time being. Radiologists should use that time to get to know the “enemy”. If they accomplish this, they might discover that they had had an ally all along