Abstract WP10: Automated Methods Of Aneurysm Growth Detection Compared With Clinical Assessment And Follow-up

Abstract

Introduction: In cases where the risk of intracranial aneurysms (IA) rupture is low or secondary to other patient health concerns, unruptured IA may be monitored through imaging. In this work, we applied different computational methods to detect IA growth and compared the results to clinical findings. Hypothesis: We hypothesize that automated methods of IA growth detection are comparable to clinical assessment. Methods: The study cohort consisted of 20 female patients with saccular IA diagnosed between 2005-2011 in UCLA Medical Center. 6 were located at the PcoA, 10 at the superior hypophyseal artery, and 4 at the ophthalmic artery. 8 IA were determined to be growing. Baseline IA size was 3.85±4.30 mm. For each case, initial and first follow-up CTA image studies (interval 2.50±2.75 yrs) were analyzed. Cohort follow-up continued for an average of 8.5±5.75 yrs. Automated methods to detect IA growth included maximum diameter (HMAX), surface area (SA), volume (V), and a novel 2-stage morphing approach which deforms the baseline IA surface mesh to that of the subsequent scan and yields a set of characteristics that describe the changes: dMPL, dSA, dV, and dICDD. Statistical methods used included the Mann-Whitney U test and Chi-Square Test with significance set at p <0.01, and ROC AUC analysis. Results: The stable and growth groups did not significantly differ with respect to case details and medical history, including IA size, location, imaging interval, age, family history, stroke, hypertension, thyroid disease, cancer, and atherosclerosis. Clinically determined change in IA diameter (p=0.007, AUC=0.927), computed HMAX (p=0.0002, AUC=0.958), SA (p=0.001, AUC=0.917), V (p=0.001, AUC=0.927), and dSA (p=0.005, AUC=0.865) were significantly different between the groups. The duration of follow-up significantly differed between the groups (p<0.01), largely due to treatment of growing IA. During follow-up only one IA changing from stable to growing, and 5 of 6 subsequently treated IA were from within the initial growth group. Conclusion: Several automated measures provided comparable performance to clinical size when assessing IA growth. HMAX in particular may be useful to assist clinical evaluation, as it was slightly more effective than recorded clinical size alone.