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Tomoaki Suzuki, Christopher J. Stapleton, Matthew J. Koch, Kazutoshi Tanaka, Soichiro Fujimura, Takashi Suzuki, Takeshi Yanagisawa, Makoto Yamamoto, Yukihiko Fujii, Yuichi Murayama and Aman B. Patel

OBJECTIVE

Degenerative cerebral aneurysm walls are associated with aneurysm rupture and subarachnoid hemorrhage. Thin-walled regions (TWRs) represent fragile areas that may eventually lead to aneurysm rupture. Previous computational fluid dynamics (CFD) studies reported the correlation of maximum pressure (Pmax) areas and TWRs; however, the correlation with aneurysm rupture has not been established. This study aims to investigate this hemodynamic correlation.

METHODS

The aneurysmal wall surface at the Pmax areas was intraoperatively evaluated using a fluid flow formula under pulsatile blood flow conditions in 23 patients with 23 saccular middle cerebral artery (MCA) bifurcation aneurysms (16 unruptured and 7 ruptured). The pressure difference (Pd) at the Pmax areas was calculated by subtracting the average pressure (Pave) from the Pmax and normalized by dividing this by the dynamic pressure at the aneurysm inlet side. The wall shear stress (WSS) was also calculated at the Pmax areas, aneurysm dome, and parent artery. These hemodynamic parameters were used to validate the correlation with TWRs in unruptured MCA aneurysms. The characteristic hemodynamic parameters at the rupture points in ruptured MCA aneurysms were then determined.

RESULTS

In 13 of 16 unruptured aneurysms (81.2%), Pmax areas were identified that corresponded to TWRs. In 5 of the 7 ruptured cerebral aneurysms, the Pmax areas coincided with the rupture point. At these areas, the Pd values were not higher than those of the TWRs in unruptured cerebral aneurysms; however, minimum WSS, time-averaged WSS, and normalized WSS at the rupture point were significantly lower than those of the TWRs in unruptured aneurysms (p < 0.01).

CONCLUSIONS

At the Pmax area of TWRs, decreased WSS appears to be the crucial hemodynamic parameter that indicates the risk of aneurysm rupture.

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Felicitas J. Detmer, Sara Hadad, Bong Jae Chung, Fernando Mut, Martin Slawski, Norman Juchler, Vartan Kurtcuoglu, Sven Hirsch, Philippe Bijlenga, Yuya Uchiyama, Soichiro Fujimura, Makoto Yamamoto, Yuichi Murayama, Hiroyuki Takao, Timo Koivisto, Juhana Frösen and Juan R. Cebral

OBJECTIVE

Incidental aneurysms pose a challenge for physicians, who need to weigh the rupture risk against the risks associated with treatment and its complications. A statistical model could potentially support such treatment decisions. A recently developed aneurysm rupture probability model performed well in the US data used for model training and in data from two European cohorts for external validation. Because Japanese and Finnish patients are known to have a higher aneurysm rupture risk, the authors’ goals in the present study were to evaluate this model using data from Japanese and Finnish patients and to compare it with new models trained with Finnish and Japanese data.

METHODS

Patient and image data on 2129 aneurysms in 1472 patients were used. Of these aneurysm cases, 1631 had been collected mainly from US hospitals, 249 from European (other than Finnish) hospitals, 147 from Japanese hospitals, and 102 from Finnish hospitals. Computational fluid dynamics simulations and shape analyses were conducted to quantitatively characterize each aneurysm’s shape and hemodynamics. Next, the previously developed model’s discrimination was evaluated using the Finnish and Japanese data in terms of the area under the receiver operating characteristic curve (AUC). Models with and without interaction terms between patient population and aneurysm characteristics were trained and evaluated including data from all four cohorts obtained by repeatedly randomly splitting the data into training and test data.

RESULTS

The US model’s AUC was reduced to 0.70 and 0.72, respectively, in the Finnish and Japanese data compared to 0.82 and 0.86 in the European and US data. When training the model with Japanese and Finnish data, the average AUC increased only slightly for the Finnish sample (to 0.76 ± 0.16) and Finnish and Japanese cases combined (from 0.74 to 0.75 ± 0.14) and decreased for the Japanese data (to 0.66 ± 0.33). In models including interaction terms, the AUC in the Finnish and Japanese data combined increased significantly to 0.83 ± 0.10.

CONCLUSIONS

Developing an aneurysm rupture prediction model that applies to Japanese and Finnish aneurysms requires including data from these two cohorts for model training, as well as interaction terms between patient population and the other variables in the model. When including this information, the performance of such a model with Japanese and Finnish data is close to its performance with US or European data. These results suggest that population-specific differences determine how hemodynamics and shape associate with rupture risk in intracranial aneurysms.