Complex Morphologic Analysis of Cerebral Aneurysms Through the Novel Use of Fractal Dimension as a Predictor of Rupture Status: A Proof of Concept Study.

BACKGROUND: Aneurysm morphology has been correlated with rupture. Previous reports identified several morphologic indices that predict rupture status, but they measure only specific qualities of the morphology of an aneurysm in a semiquantitative fashion. Fractal analysis is a geometric technique whereby the overall complexity of a shape is quantified through the calculation of a fractal dimension (FD). By progressively altering the scale of measurement of a shape and determining the number of segments required to incorporate the entire shape, a noninteger value for the dimension of the shape is derived. We present a proof-of-concept study to calculate the FD of an aneurysm for a small cohort of patients with aneurysms in 2 specific locations to determine whether FD is associated with aneurysm rupture status. METHODS: Twenty-nine aneurysms of the posterior communicating and middle cerebral arteries were segmented from computed tomography angiograms in 29 patients. FD was calculated using a standard box-counting algorithm extended for use with three-dimensional shapes. Nonsphericity index and undulation index (UI) were used to validate the data against previously reported parameters associated with rupture status. RESULTS: Nineteen ruptured and 10 unruptured aneurysms were analyzed. Through logistic regression analysis, lower FD was found to be significantly associated with rupture status (P = 0.035; odds ratio, 0.64; 95% confidence interval, 0.42-0.97 per FD increment of 0.05). CONCLUSIONS: In this proof-of-concept study, we present a novel approach to quantify the geometric complexity of intracranial aneurysms through FD. These data suggest an association between FD and patient-specific aneurysm rupture status.

An algorithm to improve lateralization accuracy of inferior petrosal sinus sampling: procedural nuances for complex patterns of venous drainage. Patient series.

BACKGROUND: Inferior petrosal sinus sampling (IPSS) is a useful technique in the diagnosis of Cushing's disease (CD) when the imaging finding is negative or equivocal. Different authors have reported considerable variability in the ability to determine tumor laterality with IPSS. Here the authors present a retrospective case series of 7 patients who underwent IPSS using a systematic algorithm to improve lateralization accuracy by identifying optimal sampling sites on the basis of individual cavernous sinus drainage patterns in each patient. OBSERVATIONS: Of the 7 patients identified, 6 were determined to have CD and subsequently underwent surgery. IPSS was accurate in all patients from whom laterality was predicted. Arterial and venous angiography were used to define cavernous sinus drainage patterns and determine optimal sampling sites. All patients who underwent surgery achieved hormonal cure. LESSONS: All IPSS predictions of lateralization were correct when available, and all patients who underwent surgery achieved hormonal cure. Advances in angiographic techniques for identification of the site of primary drainage from the cavernous sinus and subsequent optimization of microcatheter placement may improve the ability to predict tumor laterality.