Biomedical subjects
Publications and source records attributed to Arya Nabavi.
The authors report the case of a 47-year-old man who suffered a diving accident. After regaining consciousness he experienced severe headache. He was initially treated for barotrauma, but the persistent headache led to diagnostic imaging that revealed an aneurysmal subarachnoid hemorrhage. To the authors' knowledge, this is the first report of a ruptured brain aneurysm associated with barotrauma.
The increased use of image-guided surgery systems during neurosurgery has brought to prominence the inaccuracies of conventional intraoperative navigation systems caused by shape changes such as those due to brain shift. We propose a method to track the deformation of the brain and update preoperative images using intraoperative MR images acquired at different crucial time points during surgery. We use a deformable surface matching algorithm to capture the deformation of boundaries of key structures (cortical surface, ventricles and tumor) throughout the neurosurgical procedure, and a linear finite element elastic model to infer a volumetric deformation. The boundary data are extracted from intraoperative MR images using a real-time intraoperative segmentation algorithm. The algorithm has been applied to a sequence of intraoperative MR images of the brain exhibiting brain shift and tumor resection. Our results characterize the brain shift after opening of the dura and at the different stages of tumor resection, and brain swelling afterwards. Analysis of the average deformation capture was assessed by comparing landmarks identified manually and the results indicate an accuracy of 0.7+/-0.6 mm (mean+/-S.D.) for boundary surface landmarks, of 0.9+/-0.6 mm for landmarks inside the boundary surfaces, and 1.6+/-0.9 mm for landmarks in the vicinity of the tumor.
Surgical navigation systems provide the surgeon with a display of preoperative and intraoperative data in the same coordinate system. However, the systems currently in use in neurosurgery are subject to inaccuracy caused by intraoperative brain deformation (brain shift), since they typically assume that the intracranial structures are rigid. Experiments show brain shift of up to 1 cm, making it the dominant error in the system. We propose a biomechanical-model-based approach for brain shift compensation. Two models are presented: a damped spring-mass model and a model based on continuum mechanics. Both models are guided by limited intraoperative (exposed brain) surface data, with the aim to recover the deformation in the full volume. The two models are compared and their advantages and disadvantages discussed. A partial validation using intraoperative MR image sequences indicates that the approach reduces the error caused by brain shift.
The authors present CT and MRI of a patient with an extremely large arachnoidal cyst (Galassi classification type III). The cyst extended from the base of the skull, posterior to the brain stem, on the base of the temporal lobe over the complete convexity of the left hemisphere. The cyst consisted of multiple compartments with intracystic septa and was accompanied by a chronic subdural hemorrhage in the compartments. After contrast agent application, the typical characteristics of chronic subdural membranes were found. Besides bony deformities, a thinning of the inner table was found. The patient underwent craniotomy for evacuation of the hemorrhage and fenestration of the septa while he was free of symptoms. This is a remarkable case proving that chronic local intracranial pressure does not inevitably lead to neurologic symptoms or intellectual disabilities.