Effects of induced arterial hypertension for vasospasm on unruptured and unsecured cerebral aneurysms (growth and rupture). A retrospective case-control study.

OBJECTIVES: Unruptured cerebral aneurysms (UCAs) often coexist with the ruptured one but are typically left unsecured during the weeks following aneurysmal subarachnoid hemorrhage (aSAH). We compared the rate of UCAs rupture or volume growth (≥5 mm3) between patients exposed to induced arterial hypertension (iHTN) for vasospasm and those not exposed (control group). MATERIALS AND METHODS: From 2013 to 2021, we retrospectively included consecutive adult patients with aSAH who had ≥1 UCA. Custom software for digital subtraction angiography (DSA) image analysis characterized UCAs volume, going beyond merely considering UCAs long axis. RESULTS: We analyzed 118 patients (180 UCAs): 45 in the iHTN group (64 UCAs) and 73 in the control group (116 UCAs). Systolic blood pressure in the iHTN group was significantly higher than in the control group for several days after aSAH. During the 107 day-monitoring period [interquartile range(IQR):92;128], no UCA rupture occurred in either group. UCA volume analysis was performed in 44 patients (60 UCAs): none of the UCAs in the iHTN group and 3 out of 42 (7%) in the control group had a >5 mm3 volume growth (p=0.55). Other morphologic parameters did not exhibit any variations that might indicate an increased risk of rupture in the iHTN group compared to the control group. CONCLUSION: iHTN did not increase the risk of rupture or volume growth of UCAs within several weeks following aSAH. These reassuring results encourage not to refrain, because of the existence of UCAs, from iHTN as an option to prevent cerebral infarction during cerebral vasospasm.

Bifurcation geometry remodelling of vessels in de novo and growing intracranial aneurysms: a multicenter study.

BACKGROUND: Geometrical parameters, including arterial bifurcation angle, tortuosity, and arterial diameters, have been associated with the pathophysiology of intracranial aneurysm (IA) formation. The aim of this study was to investigate whether these parameters were present before or if they resulted from IA formation and growth. METHODS: Patients from nine academic centers were retrospectively identified if they presented with a de novo IA or a significant IA growth on subsequent imaging. For each patient, geometrical parameters were extracted using a semi-automated algorithm and compared between bifurcations with IA formation or growth (aneurysmal group), and their contralateral side without IA (control group). These parameters were compared at two different times using univariable models, multivariable models, and a sensitivity analysis with paired comparison. RESULTS: 46 patients were included with 21 de novo IAs (46%) and 25 significant IA growths (54%). The initial angle was not different between the aneurysmal and control groups (129.7±42.1 vs 119.8±34.3; p=0.264) but was significantly wider at the final stage (140.4±40.9 vs 121.5±34.1; p=0.032), with a more important widening of the aneurysmal angle (10.8±15.8 vs 1.78±7.38; p=0.001). Variations in other parameters were not significant. These results were confirmed by paired comparisons. CONCLUSION: Our study suggests that wider bifurcation angles that have long been deemed causal factors for IA formation or growth may be secondary to IA formation at pathologic bifurcation sites. This finding has implications for our understanding of IA formation pathophysiology.

Learning From Mouse CT-Scan Brain Images To Detect MRA-TOF Human Vasculatures.

The earlier studies on brain vasculature semantic segmentation used classical image analysis methods to extract the vascular tree from images. Nowadays, deep learning methods are widely exploited for various image analysis tasks. One of the strong restrictions when dealing with neural networks in the framework of semantic segmentation is the need to dispose of a ground truth segmentation dataset, on which the task will be learned. It may be cumbersome to manually segment the arteries in a 3D volumes (MRA-TOF typically). In this work, we aim to tackle the vascular tree segmentation from a new perspective. Our objective is to build an image dataset from mouse vasculatures acquired using CT-Scans, and enhance these vasculatures in such a way to precisely mimic the statistical properties of the human brain. The segmentation of mouse images is easily automatized thanks to their specific acquisition modality. Thus, such a framework allows to generate the data necessary for the training of a Convolutional Neural Network - i.e. the enhanced mouse images and there corresponding ground truth segmentation - without requiring any manual segmentation procedure. However, in order to generate an image dataset having consistent properties (strong resemblance with MRA images), we have to ensure that the statistical properties of the enhanced mouse images do match correctly the human MRA acquisitions. In this work, we evaluate at length the similarities between the human arteries as acquired on MRA-TOF and the "humanized" mouse arteries produced by our model. Finally, once the model duly validated, we experiment its applicability with a Convolutional Neural Network.

Syndrome de levée d'obstacle : physiopathologie et prise en charge.

RéSUMé: Le syndrome de levée d'obstacle est une polyurie massive faisant suite au traitement d'une insuffisance rénale obstructive. Les mécanismes physiopathologiques sont multiples : un état de surcharge hydrique qui dépend du caractère complet ou incomplet de l'obstacle, des anomalies tubulaires (atteinte de la capacité de dilution et de concentration des urines, diminution de la réabsorption du sodium, fuites de potassium, troubles de l'acidification des urines, insensibilité des cellules tubulaires à l'hormone antidiurétique), ainsi que des facteurs biochimiques et immunologiques sont mis en jeu. La levée d'un obstacle nécessite une surveillance clinique et biologique stricte (diurèse horaire, état hémodynamique, état d'hydratation, créatininémie, urémie, ionogramme sanguin). Le traitement a pour but d'éviter les troubles hémodynamiques et métaboliques graves, et repose sur le principe de la compensation des pertes hydroélectrolytiques.