Three-Dimensional Volumetric Assessment Enhances Detection of Growth in Unruptured Intracranial Aneurysms

Three-Dimensional Volumetric Assessment Enhances Detection of Growth in Unruptured Intracranial Aneurysms | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Three-Dimensional Volumetric Assessment Enhances Detection of Growth in Unruptured Intracranial Aneurysms Navami Shenoy, Elena Sagues, Pujit Mekala, Kareem Shoukih, Lidia Diaz, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8347568/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Monitoring unruptured intracranial aneurysms (UIAs) is critical for guiding treatment, but conventional two-dimensional size-based monitoring may miss subtle growth and underestimate rupture risk. Aneurysm volume may offer a more sensitive alternative. This study evaluated the effectiveness of volumetric analysis in detecting significant growth compared to standard size-based assessment in routine clinical management. Patients undergoing UIA surveillance from January 2024 to January 2025 with baseline and follow-up angiographic imaging ≥ 4 months apart were included. Aneurysm size was obtained from clinical records. Volumetric growth was defined using a logistic mixed model-derived threshold; 2D growth was defined as increase in maximal diameter ≥ 1 mm. Logistic regression identified predictors of volumetric growth. Twenty-four out of 123 aneurysms (98 patients) demonstrated significant volumetric growth (≥ 50%), were more frequent in high-risk locations (58% vs 26%, p = 0.006), and had smaller baseline volume (median 14.6 vs 29.6 mm³, p = 0.008) with substantially elevated growth rates (median 35% vs 4% per year, p < 0.0001). Volumetric assessment detected all 2D growth cases (n 8) and identified 16 additional aneurysms that showed minimal 2D growth (median change 4% vs 38%). Logistic regression identified follow-up time (aOR 1.20 (1.03–1.42), p = 0.02) and high-risk location (aOR 6.96 (1.93–33.6), p = 0.006) as predictors of volumetric growth (AUC of 0.79). Volumetric analysis detects aneurysm growth more effectively than 2D assessments in small aneurysms. Growth was associated with longer follow-up and high-risk locations, highlighting the potential of volumetric assessment to improve UIA surveillance and guide decision-making. Health sciences/Diseases Health sciences/Medical research Health sciences/Neurology Biological sciences/Neuroscience Intracranial Aneurysm Angiography Growth Figures Figure 1 Figure 2 Introduction Aneurysmal risk of rupture increases with growth[ 1 – 3 ]. Monitoring aneurysm size is therefore a cornerstone of clinical management of unruptured intracranial aneurysms (UIAs), which is traditionally measured as the maximal diameter of a cross-sectional area of the aneurysm dome[ 4 , 5 ]. However, such two-dimensional (2D) measurements are subject to high interobserver variability and poor reproducibility[ 6 – 8 ]. Nor do they adequately capture the 3D morphology of aneurysms[ 9 – 11 ], potentially missing subtle growth patterns and inaccurately estimating the risk of rupture. Studies have shown that aneurysm volume offers a more comprehensive method for tracking growth than conventional 2D measurements. Volume has been independently correlated with the risk of rupture[ 12 ], and has been shown to be more consistent for both individual size measurements and interval change[ 7 ]. Monitoring volumetric growth effectively quantifies morphological changes over time and has been found to outperform both 2D measurements and more complex 3D morphological metrics in identifying growing aneurysms[ 9 , 13 ]. Despite these advantages, clinical adoption remains limited. Few studies have directly compared volumetric assessments with traditional size-based metrics in routine practice, and the existing literature is constrained by small samples and limited long-term follow-up. We analyzed a large, longitudinal cohort of patients to directly compare volume and 2D assessments during routine clinical follow-up. Our study provides real-world evidence on the sensitivity of volumetric analysis for detecting subtle growth over time. Results A total of 98 patients (70 female; median age 66.5 years (IQR: 57–75)) with 123 UIAs were included (Table 1 ). The final cohort comprised 111 CE-MRA, 6 TOF-MRA, and 6 CTA. The median follow-up time was 2.1 (IQR: 1.1–4.3) years. Baseline and follow-up scans were obtained between 2008–2024 and 2017–2025 respectively. The median 2D aneurysm sizes at baseline and follow-up were 3.6 mm (IQR: 2.5-5.0 mm) and 4.0 mm (IQR: 3.0–5.0 mm), respectively. Median baseline and follow-up volumes were 26 (IQR: 12-65.6) mm 3 and 35 (IQR: 17-79.2) mm 3 , respectively, with a median change in volume of 12.6% (IQR: 2.3–39.8%). Percent changes in aneurysm volume and size differed significantly (p < 0.001; effect size = 0.62, Wilcoxon signed-rank test). Table 1 Population characteristics Total (n = 123) a Growing (n = 24) a Stable (n = 99) a p-value b Number of Patients* 98 21 83 - Sex (Female) 70 (71%) 17 (81%) 58 (70%) 0.39 Age (years) 66 (57–75) 69 (62–75) 66 (56–75) 0.77 Race (White) 91 (93%) 19 (90%) 78 (94%) 0.14 Hypertension 56 (57%) 10 (48%) 47 (57%) 0.24 Smoking 53 (54%) 11 (52%) 46 (55%) 0.79 Prior Subarachnoid Hemorrhage 6 (6%) 3 (14%) 3 (4%) 0.09 Irregularity 18 (15%) 5 (21%) 13 (13%) 0.34 Aneurysm Location ICA 43 (35%) 7 (29%) 36 (36%) 0.67 MCA 40 (32%) 3 (12%) 37 (37%) 0.04 ACA/ACOM/PCOM/Posterior circulation 40 (32%) 14 (58%) 26 (26%) 0.006 Growth (based on size) 8 (6.5%) 8 (33%) 0 (0%) <0.0001 Time to follow-up (years) 2 (1–4) 4 (2–5) 2 (1–4) 0.003 Baseline aneurysm size (mm) 4 (2–5) 3 (2–5) 4 (2–5) 0.33 Follow-up aneurysm size (mm) 4 (3–5) 4 (3–6) 4 (3–5) 1.00 Change in aneurysm size (%) 0 (0–8) 10 (1–20) 0 (0–4) 0.001 Baseline aneurysm volume (mm 3 ) 26 (12–66) 15 (9–23) 30 (14–74) 0.008 Follow-up aneurysm volume (mm 3 ) 35 (17–79) 36 (18–82) 35 (16–79) 0.87 Change in aneurysm volume (%) 13 (2–40) 95 (71–160) 10 (0–20) < 0.0001 Percent volumetric growth rate, (%/year) 7 (1–22) 35 (19–70) 4 (0–13) < 0.0001 a n(%); median (Q1-Q3). b Wilcoxon rank sum test; Chi-Squared test; Fisher's exact test. * Patient level variables (sex, age, hypertension, smoking, prior subarachnoid hemorrhage) were calculated based on n = 98, while n = 123 was used for the remaining aneurysm-specific variables. Abbreviations: ACA = Anterior cerebral artery, ACOM = Anterior communicating artery complex, PCOM = Posterior communicating artery Image Processing and Measurement Reliability To assess the stability of arterial segmentation and registration between timepoints, we quantified the percentage change in arterial volume across 93 cases. The mean percentage change was 3.72 ± 2.76% (margin of error = 0.56%). The ICC for aneurysm volumes in the validation cohort (n = 25) was 0.93 (95% CI: 0.87–0.96). 2D vs 3D Growth Eight aneurysms (7%) had a size increase ≥ 1 mm from baseline, with a median change of 38.1% (IQR: 20.0–50.0). Using logistic mixed regression, a 50% increase in volume or greater corresponded to a 95% probability of representing true growth beyond systematic error. Twenty-four aneurysms (20%) met this volumetric growth threshold (≥ 50%), with a median volume increase of 95% (IQR, 71–160). Growing vs Non-Growing Aneurysms Patient and aneurysm characteristics were compared by volumetric growth status (growth vs. stable; Table 1 ). Growing aneurysms were less frequently located in the MCA (12% vs 37%, p = 0.04), but more common in high-risk regions (ACA/ACOM complex/PCOM/Posterior circulation; 58% vs 26%, p = 0.006). Median follow-up was longer and growth rates were higher for growing aneurysms (4 vs 2 years, p = 0.003; 35 vs 4%/year, p < 0.0001). Volumetric criterion identified all 8 aneurysms that exhibited 2D growth. Median change in volume was 95% (IQR: 71–160) in growing vs 10% (IQR: 0–20) in stable (as per definition). Growing aneurysms were smaller at baseline (median, 14.6 mm³ vs 29.6 mm³; p = 0.008) but did not differ at follow-up (median, 36.3 mm³ vs 34.9 mm³; p = 0.87). Univariate logistic regression identified follow-up time (OR = 1.20 (1.05–1.39), p = 0.01) and high-risk versus internal carotid artery (ICA) location (OR = 2.77 (1.57–10.20), p < 0.01), as significant predictors of 3D growth. After adjusting for baseline volume, age, sex, and MCA location, both follow-up time (aOR = 1.20 (1.03–1.42), p = 0.02) and high-risk location (aOR = 6.96 (1.93–33.6), p = 0.006) remained significant predictors of growth. ROC analysis showed an AUC of 0.7529 for both follow-up time and location, which increased to 0.7875 after adjusting for covariates. (Table 2 ) Table 2 Univariate and multivariate logistic regression assessing factors associated with volumetric growth. OR a 95% CI a p-value a aOR b 95% CI b p-value b Time (years) 1.20 1.05–1.39 0.01 1.20 1.03–1.42 0.02 ACA/ACOM/PCOM/Posterior circulation (vs ICA) 2.77 1.57–10.2 0.004 6.96 1.93–33.6 0.006 MCA location (vs ICA) 0.42 0.258–1.84 0.51 2.54 0.631–12.8 0.21 Age (vs < 65) 1.27 0.517–3.19 0.61 1.65 0.605–4.69 0.33 Sex (Female) 1.81 0.661–5.86 0.28 1.57 0.523–5.36 0.44 Baseline Volume (per mm³) 0.997 0.990–1.00 0.38 0.997 0.989–1.00 0.30 Smoking 0.800 0.325–1.97 0.62 - - - Hypertension 0.526 0.208–1.29 0.16 - - - a Univariate logistic regression. b Multivariable logistic regression model adjusted for each of the covariates. Abbreviations: ACA = Anterior cerebral artery, ACOM = Anterior communicating artery complex, PCOM = Posterior communicating artery, aOR = Adjusted odds ratio Growing Aneurysms Missed by Size Of the 24 aneurysms that showed volumetric growth, two-thirds (n = 16) were “missed” by 2D growth detection and labeled as stable. These aneurysms occurred predominantly in female patients (n = 14, 93%, p = 0.03), who were significantly older, with a median age of 71 years (IQR: 64–76, p = 0.02). Both baseline size and volume were similar between the two groups, follow-up size (p = 0.01) and volume (p = 0.02) were significantly smaller in aneurysms that were not identified by 2D detection. The percentage change in size was significantly lower in aneurysms missed by 2D detection compared with those identified as growing (4% vs. 38%, p < 0.0001). However, the percentage change in volume, though numerically lower in the missed group (89% vs. 164%), did not reach statistical significance (p = 0.21, Fig. 2 and Table 3 ) Table 3 Population characteristics of growing aneurysms Volumetric Growth (n = 24) a 3D Growth Only (n = 16, 67%) a 2D & 3D Growth (n = 8, 33%) a p-value b Number of patients 21 15 7 - Sex (Female) 17 (81%) 14 (93%) 4 (57%) 0.03 Age (years) 69 (62–75) 71 (64–76) 62 (52–64) 0.02 Race (White) 19 (90%) 13 (87%) 6 (86%) 1.00 Hypertension 10 (48%) 8 (53%) 2 (29%) 0.39 Smoking 11 (52%) 8 (53%) 3 (43%) 0.67 Prior Subarachnoid Hemorrhage 3 (14%) 1 (7%) 2 (29%) 0.25 Irregularity 5 (21%) 3 (19%) 2 (25%) 1.00 Aneurysm Location ICA 7 (29%) 4 (25%) 3 (38%) 0.65 MCA 3 (12%) 1 (6%) 2 (25%) 0.25 ACA/ACOM complex/PCOM/Posterior circulation 14 (58%) 11 (69%) 3 (38%) 0.20 Growth (based on size) 8 (33%) 0 (0%) 8 (100%) < 0.0001 Time to follow-up (years) 4 (2–5) 4 (2–4) 4 (3–7) 0.76 Baseline aneurysm size (mm) 3 (2–5) 3 (2–4) 4 (3–5) 0.21 Follow-up aneurysm size (mm) 4 (3–6) 3 (2–4) 6 (4–6) 0.01 Change in aneurysm size (%) 10 (1–20) 4 (0–9) 38 (20–50) < 0.0001 Baseline aneurysm volume (mm 3 ) 15 (9–23) 10 (6–16) 20 (17–32) 0.06 Follow-up aneurysm volume (mm 3 ) 36 (18–82) 21 (12–45) 67 (41–114) 0.02 Change in aneurysm volume (%) 95 (71–160) 89 (67–123) 164 (74–346) 0.21 a n(%); median (Q1-Q3). b Wilcoxon rank sum test; Fisher's exact test. Abbreviations: ACA = Anterior cerebral artery, ACOM = Anterior communicating artery complex, PCOM = Posterior communicating artery Only one aneurysm became symptomatic because of rupture and hence was treated. Of the remaining aneurysms, 20 were treated as electives based on rupture risk or patient preference. Four out of the 8 aneurysms that showed 2D and 3D growth were treated based on patient preference. Three out of the additional 16 aneurysms that showed 3D growth only were also treated. Sensitivity Analysis After excluding 21 large aneurysms with maximum diameters > 5 mm, the median baseline volume remained significantly different between the growing and stable aneurysms (p = 0.003). Other key associations, including the relationship between 3D growth and location, follow-up duration, and 2D growth remained unchanged, except for MCA location (Supplementary Table 2). Discussion Volumetric assessment was more sensitive than 2D detection for identifying aneurysm growth. All aneurysms demonstrating 2D growth were also identified by volumetric assessment. Volumetric analysis detected 16 additional cases missed by 2D growth. In these cases, 2D growth was small (4% vs. 38%, p < 0.0001) and fell below the 1mm threshold (Fig. 2 a). However, there was no significant difference in 3D growth patterns between aneurysms flagged by both methods and those exhibiting 3D growth only (164% vs. 89%, p = 0.21) (Fig. 2 b). This indicates that volumetric assessment did not overestimate growth but rather revealed true growth that 2D detection failed to capture. Aneurysms exhibiting 3D-only growth occurred in older (median 71 vs 62 years; p = 0.0166) and predominantly female patients (93% vs 57%; p = 0.03). Detecting growth in these higher-risk subgroups suggests that volumetric analysis may identify patients at elevated baseline risk of rupture who might otherwise be overlooked by 2D monitoring. Further, baseline diameter was similar between stable and growing aneurysms (4 vs. 3 mm, p = 0.33), whereas baseline volume differed significantly (30 vs. 15 mm³, p = 0.008). That is, most growing aneurysms were small, and this difference was apparent only with volumetric assessment. Together, these findings highlight the shortcomings of 2D growth detection in accurately characterizing aneurysm size and underscore the greater sensitivity of volumetric analysis for detecting subtle but clinically meaningful growth, particularly in small aneurysms. Because aneurysm size in our study was obtained directly from radiological reports, these findings mirror real-world UIA monitoring and accentuate the pitfalls of relying solely on 2D measurements to detect growth. An increase in aneurysm size > 1mm is commonly used to define growth in CTA- and MRA-based studies[ 14 – 16 ]. However, the clinical significance of changes near this threshold (e.g. 0.8 vs. 1.2 mm) remains unclear. Several limitations of 2D assessments contribute to this uncertainty. For instance, follow-up size measurements are typically made using the same image projection as baseline, which may not represent the true direction of growth. Moreover, because growth can occur simultaneously in multiple directions, maximum diameter may fail to account for changes outside the plane in which it was measured. Shape changes, such as new blebs or daughter sacs, are often missed on 2D projections but are readily visible on 3D reconstructions (Fig. 1 d-f). Accordingly, volumetric assessment offers a more sensitive and reliable approach for UIA growth surveillance. Liu et al. proposed a growth threshold defined as a change in volume exceeding twice the coefficient of variance[ 17 ], and classified 36 of 112 aneurysms (32%) as growing. To examine the relationship between 3D morphological changes and aneurysm growth, Timmins et al. applied a modified z-score > 3.5 to detect volumetric outliers[ 9 ], but ultimately relied on traditional 2D definition to define growth. In contrast, our study introduces a simpler and more practical volume-based threshold that can be readily implemented in clinical settings. Previous studies have noted high inter-observer variability and limited reproducibility as major limitations of 2D measurements[ 6 , 7 ]. To ensure the reliability of our volumetric measurements, we implemented multiple strategies. First, parent artery volumes were measured across timepoints as an internal control, which showed minimal changes (margin of error = 0.56%), suggesting that observed aneurysm volume changes were unlikely to be due to systematic errors. Second, duplicate segmentations of 25 randomly selected aneurysms showed excellent inter-observer agreement (ICC = 0.93). Third, to account for residual measurement variability in determining a growth threshold, we analyzed all combinations of the duplicate volume readings in a logistic mixed model. This allowed us to estimate a data-driven threshold that reflects true measurement variability. These steps strengthen the validity of our volumetric analysis and address limitations of prior studies, which often rely on ICC alone without controlling for other sources of variation[ 7 , 18 ]. We observed that growing aneurysms had significantly smaller baseline volumes than stable aneurysms. This appears to contrast with Chien et al.[ 19 ], who found significant volume differences between growing and stable aneurysms only for those > 7 mm. However, their cohort included a broader size range, while ours consisted almost entirely of small aneurysms, with a median baseline size of 3.6 (IQR: 2.5-5.0) mm. A large cohort (n > 1000) study with a similar size distribution (mean 5.5 mm) reported that 59% of growth cases belonged to < 5 mm aneurysms[ 14 ]. Similarly, Leemans et al. found a significant volume difference between growing and stable aneurysms in a cohort with median size 5 mm[ 20 ], supporting our findings. Our findings, together with these studies[ 14 , 20 ], demonstrate that small aneurysms also exhibit meaningful volumetric growth and warrant prolonged active surveillance. In our cohort, growing aneurysms showed > 50% volumetric expansion at a significantly faster rate of growth than stable aneurysms (median 35 vs 4%/year), despite being followed for a longer period (median 4 vs 2 years). This supports the conclusion that volumetric assessment does not “overcall” growth in small aneurysms. Nonetheless, because small aneurysms rarely rupture, growth alone should not be interpreted as an indicator of imminent rupture risk. The absence of ruptures in our cohort further underscores the challenge of determining how growth in these small aneurysms relates to their actual propensity to rupture. Aneurysms located in certain arterial regions are known to carry a greater risk of rupture[ 5 ]. Our findings suggest that volumetric growth may follow a similar location-dependent pattern. Aneurysms that grew were in high-risk locations, whereas fewer growing aneurysms were observed in the MCA. These observations are consistent with findings by Liu et al.[ 17 ], who reported higher growth rates in aneurysms located in the ACA and BA compared to those in the MCA and ICA. This study has several limitations. It is a retrospective, single-center analysis, which may introduce selection bias and limit generalizability. Inclusion was restricted to aneurysms under active longitudinal surveillance, limiting correlation of volumetric growth with long-term outcomes, such as rupture risk. This study considered a single follow-up per aneurysm for simplicity. Monitoring volumetric growth over multiple follow-ups could better identify a growth threshold associated with rupture risk and may address inter-patient variability in follow-up duration. Multi-modal effects were not assessed as the sample predominantly consisted of CE-MRA. Although measures were taken to minimize inter-observer variability, advances in automated segmentation could further reduce bias inherent to manual methods. Such tools could also facilitate clinical integration by lowering the time and effort required to measure volume in clinical settings[ 13 , 21 ]. Lastly, this study focused solely on volume. Incorporating additional 3D morphological features could enhance understanding of aneurysm behavior and its association with 3D growth. Future studies should use prospective, multi-center automated analysis and longitudinal imaging across multiple timepoints to validate volumetric growth as a reliable biomarker for aneurysm growth and rupture risk. Conclusions Volumetric analysis identified more cases of aneurysm growth than conventional 2D criteria in small aneurysms. Growth was also associated with longer follow-up duration, which may highlight the importance of long-term surveillance for UIAs. Volumetric assessment may offer a more sensitive tool for surveillance and could offer additional guidance for clinical management of UIAs. Methods Study Population This study was approved by the University of Iowa Institutional Review Board (ID: 201811813), with informed consent waived due to its retrospective design. The study was conducted according to the ethical standards of our institutional research committee and the Declaration of Helsinki. Patients aged 18 to 90 undergoing follow-up UIA surveillance between January 2024 and January 2025 were consecutively screened. At our institution, the surveillance protocol typically includes imaging 6 to 12 months after initial diagnosis, followed by biannual imaging. Patients who had a baseline and follow-up imaging scan with the same imaging modality (CTA, CE-MRA or TOF-MRA) ≥ 4 months apart were included. In case of multiple follow-up imaging, the latest follow-up scan was selected. Patients with poor imaging quality, and treated, ruptured, or thrombosed aneurysms were excluded. Patient demographic and clinical information were obtained from electronic medical records. Aneurysm measurements were obtained from radiological reports at both timepoints; this measurement is routinely performed by measuring the greatest aneurysm diameter in 2D views[ 11 ]. Shape was adjudicated as regular or irregular based on 3D reconstructions. An aneurysm was considered irregular if it had daughter sacs, blebs, or multiple lobes[ 22 ]. Aneurysm location was considered high risk if it was in the anterior cerebral artery (ACA), anterior communicating artery complex (ACOM), basilar artery (BA), or posterior communicating artery (PCOM)[ 23 ]. Surface Extraction and Volume Quantification Image processing was performed using 3D Slicer (v5.6.2). Baseline and follow-up images underwent rigid registration and resampling to isotropic voxels (0.6 x 0.6 x 0.6 mm 3 ). Aneurysms and the ipsilateral parent artery were manually segmented, and smoothed triangulated surface meshes were generated using a flying edges algorithm to reduce artifacts. Meshes were exported as VTK and loaded into Python (VTK 9.4.2). Enclosed volume was computed using the divergence theorem by summing the signed tetrahedral volumes formed between each triangular face and the coordinate origin. Total volume, \(\:V\:=\:\frac{1}{6}{\sum\:}_{i=1}^{n}Ai\cdot\:\left(Bi\times\:\:Ci\right)\) Where Ai, Bi, and Ci are the 3D coordinates of the triangular vertices, and n is the number of faces[ 24 ]. Final volumes were reported in cubic millimeters (mm 3 ). Volumetric Growth Analysis Variation between imaging timepoints due to registration errors or differing imaging conditions was controlled by measuring volume differences in the parent artery, which were assumed to remain unchanged. The mean percentage change in artery volumes and the corresponding standard deviation (SD) was determined. To assess segmentation consistency, a second blinded investigator re-segmented a random subset of 25 aneurysms. Inter-observer agreement for volume was quantified with the intraclass correlation coefficient (ICC). Growth was defined as (i) 2D growth: increase in maximum diameter ≥ 1 mm, and (ii) 3D volumetric growth: threshold derived from logistic mixed-effects regression. We then calculated the proportion of aneurysms meeting each growth criterion. Statistical Analysis Statistical analysis was performed in R (4.4.2). Normally distributed variables were reported as mean ± SD, and non-normally distributed variables as median and interquartile range (IQR). Normality was determined using the Shapiro-Wilk test. Changes in volume and size from baseline were compared using the paired Wilcoxon signed-rank test. Categorical variables were compared using the chi-squared test or Fisher’s exact test. Continuous variables with Mann-Whitney U test or Kruskal-Wallis test, as appropriate. To establish a reliability threshold for volumetric growth, 25 aneurysms underwent duplicate measurements at baseline and follow-up. For each timepoint, two volume readings were averaged, and a growth ratio was defined as the mean follow-up volume divided by the mean baseline volume. This ratio was dichotomized based as > 1 (growth) or < 1 (no growth). To account for inter-observer and inter-timepoint variability, four ratios representing all baseline–follow-up measurement combinations were used as predictors in a logistic mixed mode, yielding four observations per aneurysm. The binary outcome indicated whether the averaged follow-up-to-baseline ratio exceeded 1. 3D volumetric growth was defined as the percentage change in aneurysm volume from baseline to follow-up exceeding the model-derived growth threshold. The clinical criterion of difference in size ≥ 1mm was used as the definition for 2D growth to ensure consistency with clinical practice. A post-hoc sensitivity analysis excluding aneurysms > 5 mm was performed to account for the predominance of small aneurysms in our cohort and the distinct natural history of larger aneurysms. Univariate logistic regression was used to identify independent predictors of significant volumetric growth. Covariates were entered into a multivariate model based on univariate p < 0.10 or clinical relevance. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUC). Adjusted ORs with 95% CI were reported for each covariate. Statistical significance was set at p < 0.05 for all final analyses. Abbreviations CE = contrast-enhanced TOF = time-of-flight MRA = Magnetic resonance angiography CTA = Computed tomography angiography UIA = Unruptured intracranial aneurysm ACA = Anterior cerebral artery ICA = Internal carotid artery ACOM = Anterior communicating artery complex BA = Basilar artery PCOM = Posterior communicating artery ICC = Intraclass correlation coefficient VTK = Visualization Toolkit Declarations Funding This study did not receive funding. Author Contributions N.S. and E.S. contributed to all aspects of the study and drafted the manuscript. E.A.S. contributed to study design and conceptualization. P.M., K.S., and L.D. collected data and assisted with manuscript drafting and editing. D.C., R.C., and I.S. contributed to data collection. N.S. and L.W. performed statistical analysis. N.S. prepared figures 1-2. A.G., C.D., B.Z., G.P., and R.K. assisted with manuscript drafting and editing. All authors reviewed and approved the final manuscript. Data Availability Statement The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Additional Information Competing Interests Statement The author(s) declare no competing interests. References Villablanca, J. P. et al. Natural history of asymptomatic unruptured cerebral aneurysms evaluated at CT angiography: growth and rupture incidence and correlation with epidemiologic risk factors. Radiology 269 , 258–265. https://doi.org/10.1148/radiol.13121188 (2013). Korja, M., Lehto, H. & Juvela, S. 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Stroke 51 , 2103–2110. https://doi.org/10.1161/STROKEAHA.120.029296 (2020). Chien, A. et al. Nonsphericity Index and Size Ratio Identify Morphologic Differences between Growing and Stable Aneurysms in a Longitudinal Study of 93 Cases. AJNR Am. J. Neuroradiol. 39 , 500–506. https://doi.org/10.3174/ajnr.A5531 (2018). Leemans, E. L. et al. Intracranial aneurysm growth: consistency of morphological changes. Neurosurg. Focus . 47 , E5. https://doi.org/10.3171/2019.4.FOCUS1987 (2019). Yang, Y. et al. Integrated Deep Learning Model for the Detection, Segmentation, and Morphologic Analysis of Intracranial Aneurysms Using CT Angiography. Radiol. Artif. Intell. 7 , e240017. https://doi.org/10.1148/ryai.240017 (2025). Bjorkman, J. et al. Irregular Shape Identifies Ruptured Intracranial Aneurysm in Subarachnoid Hemorrhage Patients With Multiple Aneurysms. Stroke 48 , 1986–1989. https://doi.org/10.1161/STROKEAHA.117.017147 (2017). Greving, J. P. et al. Development of the PHASES score for prediction of risk of rupture of intracranial aneurysms: a pooled analysis of six prospective cohort studies. Lancet Neurol. 13 , 59–66. https://doi.org/10.1016/S1474-4422(13)70263-1 (2014). Zwanenburg, A. et al. The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping. Radiology 295 , 328–338. https://doi.org/10.1148/radiol.2020191145 (2020). Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8347568","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":560692304,"identity":"d2328d04-aba1-4ec7-aaef-c8b2e0c49f6d","order_by":0,"name":"Navami Shenoy","email":"","orcid":"","institution":"University of Iowa","correspondingAuthor":false,"prefix":"","firstName":"Navami","middleName":"","lastName":"Shenoy","suffix":""},{"id":560692305,"identity":"203f00e8-d5d6-49fa-aafa-0266cc92f361","order_by":1,"name":"Elena Sagues","email":"","orcid":"","institution":"University of 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16:51:46","extension":"html","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":110423,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8347568/v1/574842072a60d2f582b0436c.html"},{"id":98283433,"identity":"6d38d538-8956-4b07-828e-81c5163a64bd","added_by":"auto","created_at":"2025-12-16 06:11:11","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1108099,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVolumetric analysis reveals aneurysm growth missed by conventional 2D detection\u003c/strong\u003e. (\u003cstrong\u003ea\u003c/strong\u003e, \u003cstrong\u003eb\u003c/strong\u003e) Axial CE-MRA of a right PICA aneurysm at baseline (\u003cstrong\u003ea\u003c/strong\u003e) measuring 4.7 mm and at 5-month follow-up (\u003cstrong\u003eb\u003c/strong\u003e) measuring 5.0 mm, shows a minimal increase in diameter of 0.3 mm that does not show 2D growth. (\u003cstrong\u003ec\u003c/strong\u003e) 3D reconstruction overlay of the same aneurysm, with baseline measuring 82 mm\u003csup\u003e3\u003c/sup\u003e in volume and follow-up measuring 123 mm\u003csup\u003e3\u003c/sup\u003e. Aneurysm volume increased by 51%. (\u003cstrong\u003ed\u003c/strong\u003e, \u003cstrong\u003ee\u003c/strong\u003e) Coronal CE-MRA of an ACOM aneurysm measuring 10.6 mm at baseline (\u003cstrong\u003ed\u003c/strong\u003e) and 10.8 mm at 4.6-year follow-up (\u003cstrong\u003ee\u003c/strong\u003e), showing a slight diameter change (0.2 mm) below 2D threshold. (\u003cstrong\u003ef\u003c/strong\u003e) 3D overlay reconstruction highlighting morphological change; aneurysm volume increased by 99% from 277 mm\u003csup\u003e3\u003c/sup\u003e to 552 mm\u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8347568/v1/b732c6097fe87ffa7a15a42b.jpg"},{"id":98283434,"identity":"a73ec43e-6ca2-40cb-b072-d375460c2588","added_by":"auto","created_at":"2025-12-16 06:11:11","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":633453,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePercent changes in size and volume in aneurysms showing 3D but not 2D growth.\u003c/strong\u003e (\u003cstrong\u003ea\u003c/strong\u003e) Boxplot shows the percent change in size, comparing aneurysms showed only 3D volumetric growth (“Missed”) with those that demonstrated both 3D and 2D growth (“Agree”). “Missed” aneurysms show a significantly lower size change (median (IQR): 4% (0-9)) than the “Agree” aneurysms (median (IQR): 38% (20-50); Mann Whitney U test, p\u0026lt;0.0001). (\u003cstrong\u003eb\u003c/strong\u003e) Boxplot shows the percent change in volume comparing “Missed” and “Agree” aneurysm groups. Change in volume in “Missed” aneurysms (median (IQR): 89% (67-123)) was not significantly different from “Agree” aneurysms (median (IQR): 164 (74-346); Mann Whitney U test, p=0.21).\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8347568/v1/5be7751924aa44c9b69d1769.jpg"},{"id":98774468,"identity":"36fab5ff-3db7-4f74-85f7-4d97b1234a8f","added_by":"auto","created_at":"2025-12-22 11:28:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2797656,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8347568/v1/e3f87a29-7214-43b5-a7a4-467b7b3eb85e.pdf"},{"id":98435403,"identity":"fb6391d8-10d3-4598-8633-dc09840ce57c","added_by":"auto","created_at":"2025-12-17 16:53:40","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":20433,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-8347568/v1/301b1668a89bccf835674fa3.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Three-Dimensional Volumetric Assessment Enhances Detection of Growth in Unruptured Intracranial Aneurysms","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAneurysmal risk of rupture increases with growth[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Monitoring aneurysm size is therefore a cornerstone of clinical management of unruptured intracranial aneurysms (UIAs), which is traditionally measured as the maximal diameter of a cross-sectional area of the aneurysm dome[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, such two-dimensional (2D) measurements are subject to high interobserver variability and poor reproducibility[\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Nor do they adequately capture the 3D morphology of aneurysms[\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], potentially missing subtle growth patterns and inaccurately estimating the risk of rupture.\u003c/p\u003e \u003cp\u003eStudies have shown that aneurysm volume offers a more comprehensive method for tracking growth than conventional 2D measurements. Volume has been independently correlated with the risk of rupture[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and has been shown to be more consistent for both individual size measurements and interval change[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Monitoring volumetric growth effectively quantifies morphological changes over time and has been found to outperform both 2D measurements and more complex 3D morphological metrics in identifying growing aneurysms[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Despite these advantages, clinical adoption remains limited. Few studies have directly compared volumetric assessments with traditional size-based metrics in routine practice, and the existing literature is constrained by small samples and limited long-term follow-up. We analyzed a large, longitudinal cohort of patients to directly compare volume and 2D assessments during routine clinical follow-up. Our study provides real-world evidence on the sensitivity of volumetric analysis for detecting subtle growth over time.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 98 patients (70 female; median age 66.5 years (IQR: 57\u0026ndash;75)) with 123 UIAs were included (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The final cohort comprised 111 CE-MRA, 6 TOF-MRA, and 6 CTA. The median follow-up time was 2.1 (IQR: 1.1\u0026ndash;4.3) years. Baseline and follow-up scans were obtained between 2008\u0026ndash;2024 and 2017\u0026ndash;2025 respectively. The median 2D aneurysm sizes at baseline and follow-up were 3.6 mm (IQR: 2.5-5.0 mm) and 4.0 mm (IQR: 3.0\u0026ndash;5.0 mm), respectively. Median baseline and follow-up volumes were 26 (IQR: 12-65.6) mm\u003csup\u003e3\u003c/sup\u003e and 35 (IQR: 17-79.2) mm\u003csup\u003e3\u003c/sup\u003e, respectively, with a median change in volume of 12.6% (IQR: 2.3\u0026ndash;39.8%). Percent changes in aneurysm volume and size differed significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; effect size\u0026thinsp;=\u0026thinsp;0.62, Wilcoxon signed-rank test).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePopulation characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;123)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrowing\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;24)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStable\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;99)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Patients*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58 (70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 (57\u0026ndash;75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (62\u0026ndash;75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66 (56\u0026ndash;75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace (White)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91 (93%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78 (94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47 (57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrior Subarachnoid Hemorrhage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIrregularity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAneurysm Location\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37 (37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACA/ACOM/PCOM/Posterior circulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrowth (based on size)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to follow-up (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (2\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (1\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline aneurysm size (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (2\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (2\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFollow-up aneurysm size (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (3\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (3\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (3\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChange in aneurysm size (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0\u0026ndash;8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (1\u0026ndash;20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline aneurysm volume (mm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (12\u0026ndash;66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (9\u0026ndash;23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (14\u0026ndash;74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFollow-up aneurysm volume (mm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (17\u0026ndash;79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (18\u0026ndash;82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35 (16\u0026ndash;79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChange in aneurysm volume (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (2\u0026ndash;40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95 (71\u0026ndash;160)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (0\u0026ndash;20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercent volumetric growth rate, (%/year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (1\u0026ndash;22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (19\u0026ndash;70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (0\u0026ndash;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003e n(%); median (Q1-Q3).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003eb\u003c/sup\u003e Wilcoxon rank sum test; Chi-Squared test; Fisher's exact test.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e*\u003c/sup\u003e Patient level variables (sex, age, hypertension, smoking, prior subarachnoid hemorrhage) were calculated based on n\u0026thinsp;=\u0026thinsp;98, while n\u0026thinsp;=\u0026thinsp;123 was used for the remaining aneurysm-specific variables.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviations: ACA\u0026thinsp;=\u0026thinsp;Anterior cerebral artery, ACOM\u0026thinsp;=\u0026thinsp;Anterior communicating artery complex, PCOM\u0026thinsp;=\u0026thinsp;Posterior communicating artery\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eImage Processing and Measurement Reliability\u003c/h2\u003e \u003cp\u003eTo assess the stability of arterial segmentation and registration between timepoints, we quantified the percentage change in arterial volume across 93 cases. The mean percentage change was 3.72\u0026thinsp;\u0026plusmn;\u0026thinsp;2.76% (margin of error\u0026thinsp;=\u0026thinsp;0.56%). The ICC for aneurysm volumes in the validation cohort (n\u0026thinsp;=\u0026thinsp;25) was 0.93 (95% CI: 0.87\u0026ndash;0.96).\u003c/p\u003e \u003cp\u003e \u003cem\u003e2D vs 3D Growth\u003c/em\u003e \u003c/p\u003e \u003cp\u003eEight aneurysms (7%) had a size increase\u0026thinsp;\u0026ge;\u0026thinsp;1 mm from baseline, with a median change of 38.1% (IQR: 20.0\u0026ndash;50.0).\u003c/p\u003e \u003cp\u003eUsing logistic mixed regression, a 50% increase in volume or greater corresponded to a 95% probability of representing true growth beyond systematic error. Twenty-four aneurysms (20%) met this volumetric growth threshold (\u0026ge;\u0026thinsp;50%), with a median volume increase of 95% (IQR, 71\u0026ndash;160).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGrowing vs Non-Growing Aneurysms\u003c/h3\u003e\n\u003cp\u003ePatient and aneurysm characteristics were compared by volumetric growth status (growth vs. stable; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Growing aneurysms were less frequently located in the MCA (12% vs 37%, p\u0026thinsp;=\u0026thinsp;0.04), but more common in high-risk regions (ACA/ACOM complex/PCOM/Posterior circulation; 58% vs 26%, p\u0026thinsp;=\u0026thinsp;0.006). Median follow-up was longer and growth rates were higher for growing aneurysms (4 vs 2 years, p\u0026thinsp;=\u0026thinsp;0.003; 35 vs 4%/year, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003eVolumetric criterion identified all 8 aneurysms that exhibited 2D growth. Median change in volume was 95% (IQR: 71\u0026ndash;160) in growing vs 10% (IQR: 0\u0026ndash;20) in stable (as per definition). Growing aneurysms were smaller at baseline (median, 14.6 mm\u0026sup3; vs 29.6 mm\u0026sup3;; p\u0026thinsp;=\u0026thinsp;0.008) but did not differ at follow-up (median, 36.3 mm\u0026sup3; vs 34.9 mm\u0026sup3;; p\u0026thinsp;=\u0026thinsp;0.87).\u003c/p\u003e \u003cp\u003eUnivariate logistic regression identified follow-up time (OR\u0026thinsp;=\u0026thinsp;1.20 (1.05\u0026ndash;1.39), p\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.01) and high-risk versus internal carotid artery (ICA) location (OR\u0026thinsp;=\u0026thinsp;2.77 (1.57\u0026ndash;10.20), p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), as significant predictors of 3D growth. After adjusting for baseline volume, age, sex, and MCA location, both follow-up time (aOR\u0026thinsp;=\u0026thinsp;1.20 (1.03\u0026ndash;1.42), p\u0026thinsp;=\u0026thinsp;0.02) and high-risk location (aOR\u0026thinsp;=\u0026thinsp;6.96 (1.93\u0026ndash;33.6), p\u0026thinsp;=\u0026thinsp;0.006) remained significant predictors of growth. ROC analysis showed an AUC of 0.7529 for both follow-up time and location, which increased to 0.7875 after adjusting for covariates. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate logistic regression assessing factors associated with volumetric growth.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eaOR\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.05\u0026ndash;1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.03\u0026ndash;1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACA/ACOM/PCOM/Posterior circulation (vs ICA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.57\u0026ndash;10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.93\u0026ndash;33.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCA location (vs ICA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.258\u0026ndash;1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.631\u0026ndash;12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (vs\u0026thinsp;\u0026lt;\u0026thinsp;65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.517\u0026ndash;3.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.605\u0026ndash;4.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.661\u0026ndash;5.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.523\u0026ndash;5.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline Volume (per mm\u0026sup3;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.990\u0026ndash;1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.989\u0026ndash;1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.325\u0026ndash;1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.208\u0026ndash;1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003eUnivariate logistic regression.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003eb\u003c/sup\u003eMultivariable logistic regression model adjusted for each of the covariates.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: ACA\u0026thinsp;=\u0026thinsp;Anterior cerebral artery, ACOM\u0026thinsp;=\u0026thinsp;Anterior communicating artery complex, PCOM\u0026thinsp;=\u0026thinsp;Posterior communicating artery, aOR\u0026thinsp;=\u0026thinsp;Adjusted odds ratio\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eGrowing Aneurysms Missed by Size\u003c/h3\u003e\n\u003cp\u003eOf the 24 aneurysms that showed volumetric growth, two-thirds (n\u0026thinsp;=\u0026thinsp;16) were \u0026ldquo;missed\u0026rdquo; by 2D growth detection and labeled as stable. These aneurysms occurred predominantly in female patients (n\u0026thinsp;=\u0026thinsp;14, 93%, p\u0026thinsp;=\u0026thinsp;0.03), who were significantly older, with a median age of 71 years (IQR: 64\u0026ndash;76, p\u0026thinsp;=\u0026thinsp;0.02). Both baseline size and volume were similar between the two groups, follow-up size (p\u0026thinsp;=\u0026thinsp;0.01) and volume (p\u0026thinsp;=\u0026thinsp;0.02) were significantly smaller in aneurysms that were not identified by 2D detection. The percentage change in size was significantly lower in aneurysms missed by 2D detection compared with those identified as growing (4% vs. 38%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). However, the percentage change in volume, though numerically lower in the missed group (89% vs. 164%), did not reach statistical significance (p\u0026thinsp;=\u0026thinsp;0.21, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePopulation characteristics of growing aneurysms\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVolumetric Growth\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;24)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3D Growth Only\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;16, 67%)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2D \u0026amp; 3D Growth\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8, 33%)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (93%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 (62\u0026ndash;75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (64\u0026ndash;76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 (52\u0026ndash;64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace (White)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrior Subarachnoid Hemorrhage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIrregularity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAneurysm Location\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACA/ACOM complex/PCOM/Posterior circulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrowth (based on size)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to follow-up (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (2\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (2\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (3\u0026ndash;7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline aneurysm size (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (3\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFollow-up aneurysm size (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (3\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (4\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChange in aneurysm size (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (1\u0026ndash;20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (0\u0026ndash;9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38 (20\u0026ndash;50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline aneurysm volume (mm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (9\u0026ndash;23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (6\u0026ndash;16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (17\u0026ndash;32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFollow-up aneurysm volume (mm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (18\u0026ndash;82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (12\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67 (41\u0026ndash;114)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChange in aneurysm volume (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95 (71\u0026ndash;160)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89 (67\u0026ndash;123)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e164 (74\u0026ndash;346)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003e n(%); median (Q1-Q3).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003eb\u003c/sup\u003eWilcoxon rank sum test; Fisher's exact test.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviations: ACA\u0026thinsp;=\u0026thinsp;Anterior cerebral artery, ACOM\u0026thinsp;=\u0026thinsp;Anterior communicating artery complex, PCOM\u0026thinsp;=\u0026thinsp;Posterior communicating artery\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOnly one aneurysm became symptomatic because of rupture and hence was treated. Of the remaining aneurysms, 20 were treated as electives based on rupture risk or patient preference. Four out of the 8 aneurysms that showed 2D and 3D growth were treated based on patient preference. Three out of the additional 16 aneurysms that showed 3D growth only were also treated.\u003c/p\u003e\n\u003ch3\u003eSensitivity Analysis\u003c/h3\u003e\n\u003cp\u003eAfter excluding 21 large aneurysms with maximum diameters\u0026thinsp;\u0026gt;\u0026thinsp;5 mm, the median baseline volume remained significantly different between the growing and stable aneurysms (p\u0026thinsp;=\u0026thinsp;0.003). Other key associations, including the relationship between 3D growth and location, follow-up duration, and 2D growth remained unchanged, except for MCA location (Supplementary Table\u0026nbsp;2).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eVolumetric assessment was more sensitive than 2D detection for identifying aneurysm growth. All aneurysms demonstrating 2D growth were also identified by volumetric assessment. Volumetric analysis detected 16 additional cases missed by 2D growth. In these cases, 2D growth was small (4% vs. 38%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and fell below the 1mm threshold (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). However, there was no significant difference in 3D growth patterns between aneurysms flagged by both methods and those exhibiting 3D growth only (164% vs. 89%, p\u0026thinsp;=\u0026thinsp;0.21) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). This indicates that volumetric assessment did not overestimate growth but rather revealed true growth that 2D detection failed to capture.\u003c/p\u003e \u003cp\u003eAneurysms exhibiting 3D-only growth occurred in older (median 71 vs 62 years; p\u0026thinsp;=\u0026thinsp;0.0166) and predominantly female patients (93% vs 57%; p\u0026thinsp;=\u0026thinsp;0.03). Detecting growth in these higher-risk subgroups suggests that volumetric analysis may identify patients at elevated baseline risk of rupture who might otherwise be overlooked by 2D monitoring. Further, baseline diameter was similar between stable and growing aneurysms (4 vs. 3 mm, p\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.33), whereas baseline volume differed significantly (30 vs. 15 mm\u0026sup3;, p\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.008). That is, most growing aneurysms were small, and this difference was apparent only with volumetric assessment.\u003c/p\u003e \u003cp\u003eTogether, these findings highlight the shortcomings of 2D growth detection in accurately characterizing aneurysm size and underscore the greater sensitivity of volumetric analysis for detecting subtle but clinically meaningful growth, particularly in small aneurysms. Because aneurysm size in our study was obtained directly from radiological reports, these findings mirror real-world UIA monitoring and accentuate the pitfalls of relying solely on 2D measurements to detect growth.\u003c/p\u003e \u003cp\u003eAn increase in aneurysm size\u0026thinsp;\u0026gt;\u0026thinsp;1mm is commonly used to define growth in CTA- and MRA-based studies[\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, the clinical significance of changes near this threshold (e.g. 0.8 vs. 1.2 mm) remains unclear. Several limitations of 2D assessments contribute to this uncertainty. For instance, follow-up size measurements are typically made using the same image projection as baseline, which may not represent the true direction of growth. Moreover, because growth can occur simultaneously in multiple directions, maximum diameter may fail to account for changes outside the plane in which it was measured. Shape changes, such as new blebs or daughter sacs, are often missed on 2D projections but are readily visible on 3D reconstructions (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ed-f).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAccordingly, volumetric assessment offers a more sensitive and reliable approach for UIA growth surveillance. Liu et al. proposed a growth threshold defined as a change in volume exceeding twice the coefficient of variance[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], and classified 36 of 112 aneurysms (32%) as growing. To examine the relationship between 3D morphological changes and aneurysm growth, Timmins et al. applied a modified z-score\u0026thinsp;\u0026gt;\u0026thinsp;3.5 to detect volumetric outliers[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], but ultimately relied on traditional 2D definition to define growth. In contrast, our study introduces a simpler and more practical volume-based threshold that can be readily implemented in clinical settings.\u003c/p\u003e \u003cp\u003ePrevious studies have noted high inter-observer variability and limited reproducibility as major limitations of 2D measurements[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. To ensure the reliability of our volumetric measurements, we implemented multiple strategies. First, parent artery volumes were measured across timepoints as an internal control, which showed minimal changes (margin of error\u0026thinsp;=\u0026thinsp;0.56%), suggesting that observed aneurysm volume changes were unlikely to be due to systematic errors. Second, duplicate segmentations of 25 randomly selected aneurysms showed excellent inter-observer agreement (ICC\u0026thinsp;=\u0026thinsp;0.93). Third, to account for residual measurement variability in determining a growth threshold, we analyzed all combinations of the duplicate volume readings in a logistic mixed model. This allowed us to estimate a data-driven threshold that reflects true measurement variability. These steps strengthen the validity of our volumetric analysis and address limitations of prior studies, which often rely on ICC alone without controlling for other sources of variation[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe observed that growing aneurysms had significantly smaller baseline volumes than stable aneurysms. This appears to contrast with Chien et al.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], who found significant volume differences between growing and stable aneurysms only for those\u0026thinsp;\u0026gt;\u0026thinsp;7 mm. However, their cohort included a broader size range, while ours consisted almost entirely of small aneurysms, with a median baseline size of 3.6 (IQR: 2.5-5.0) mm. A large cohort (n\u0026thinsp;\u0026gt;\u0026thinsp;1000) study with a similar size distribution (mean 5.5 mm) reported that 59% of growth cases belonged to \u0026lt;\u0026thinsp;5 mm aneurysms[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Similarly, Leemans et al. found a significant volume difference between growing and stable aneurysms in a cohort with median size 5 mm[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], supporting our findings.\u003c/p\u003e \u003cp\u003eOur findings, together with these studies[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], demonstrate that small aneurysms also exhibit meaningful volumetric growth and warrant prolonged active surveillance. In our cohort, growing aneurysms showed\u0026thinsp;\u0026gt;\u0026thinsp;50% volumetric expansion at a significantly faster rate of growth than stable aneurysms (median 35 vs 4%/year), despite being followed for a longer period (median 4 vs 2 years). This supports the conclusion that volumetric assessment does not \u0026ldquo;overcall\u0026rdquo; growth in small aneurysms. Nonetheless, because small aneurysms rarely rupture, growth alone should not be interpreted as an indicator of imminent rupture risk. The absence of ruptures in our cohort further underscores the challenge of determining how growth in these small aneurysms relates to their actual propensity to rupture.\u003c/p\u003e \u003cp\u003eAneurysms located in certain arterial regions are known to carry a greater risk of rupture[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Our findings suggest that volumetric growth may follow a similar location-dependent pattern. Aneurysms that grew were in high-risk locations, whereas fewer growing aneurysms were observed in the MCA. These observations are consistent with findings by Liu et al.[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], who reported higher growth rates in aneurysms located in the ACA and BA compared to those in the MCA and ICA.\u003c/p\u003e \u003cp\u003eThis study has several limitations. It is a retrospective, single-center analysis, which may introduce selection bias and limit generalizability. Inclusion was restricted to aneurysms under active longitudinal surveillance, limiting correlation of volumetric growth with long-term outcomes, such as rupture risk. This study considered a single follow-up per aneurysm for simplicity. Monitoring volumetric growth over multiple follow-ups could better identify a growth threshold associated with rupture risk and may address inter-patient variability in follow-up duration. Multi-modal effects were not assessed as the sample predominantly consisted of CE-MRA. Although measures were taken to minimize inter-observer variability, advances in automated segmentation could further reduce bias inherent to manual methods. Such tools could also facilitate clinical integration by lowering the time and effort required to measure volume in clinical settings[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Lastly, this study focused solely on volume. Incorporating additional 3D morphological features could enhance understanding of aneurysm behavior and its association with 3D growth. Future studies should use prospective, multi-center automated analysis and longitudinal imaging across multiple timepoints to validate volumetric growth as a reliable biomarker for aneurysm growth and rupture risk.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eVolumetric analysis identified more cases of aneurysm growth than conventional 2D criteria in small aneurysms. Growth was also associated with longer follow-up duration, which may highlight the importance of long-term surveillance for UIAs. Volumetric assessment may offer a more sensitive tool for surveillance and could offer additional guidance for clinical management of UIAs.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003e This study was approved by the University of Iowa Institutional Review Board (ID: 201811813), with informed consent waived due to its retrospective design. The study was conducted according to the ethical standards of our institutional research committee and the Declaration of Helsinki. Patients aged 18 to 90 undergoing follow-up UIA surveillance between January 2024 and January 2025 were consecutively screened. At our institution, the surveillance protocol typically includes imaging 6 to 12 months after initial diagnosis, followed by biannual imaging. Patients who had a baseline and follow-up imaging scan with the same imaging modality (CTA, CE-MRA or TOF-MRA)\u0026thinsp;\u0026ge;\u0026thinsp;4 months apart were included. In case of multiple follow-up imaging, the latest follow-up scan was selected. Patients with poor imaging quality, and treated, ruptured, or thrombosed aneurysms were excluded.\u003c/p\u003e \u003cp\u003ePatient demographic and clinical information were obtained from electronic medical records. Aneurysm measurements were obtained from radiological reports at both timepoints; this measurement is routinely performed by measuring the greatest aneurysm diameter in 2D views[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Shape was adjudicated as regular or irregular based on 3D reconstructions. An aneurysm was considered irregular if it had daughter sacs, blebs, or multiple lobes[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Aneurysm location was considered high risk if it was in the anterior cerebral artery (ACA), anterior communicating artery complex (ACOM), basilar artery (BA), or posterior communicating artery (PCOM)[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSurface Extraction and Volume Quantification\u003c/h2\u003e \u003cp\u003eImage processing was performed using 3D Slicer (v5.6.2). Baseline and follow-up images underwent rigid registration and resampling to isotropic voxels (0.6 x 0.6 x 0.6 mm\u003csup\u003e3\u003c/sup\u003e). Aneurysms and the ipsilateral parent artery were manually segmented, and smoothed triangulated surface meshes were generated using a flying edges algorithm to reduce artifacts. Meshes were exported as VTK and loaded into Python (VTK 9.4.2). Enclosed volume was computed using the divergence theorem by summing the signed tetrahedral volumes formed between each triangular face and the coordinate origin.\u003c/p\u003e \u003cp\u003eTotal volume, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:V\\:=\\:\\frac{1}{6}{\\sum\\:}_{i=1}^{n}Ai\\cdot\\:\\left(Bi\\times\\:\\:Ci\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eWhere Ai, Bi, and Ci are the 3D coordinates of the triangular vertices, and n is the number of faces[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Final volumes were reported in cubic millimeters (mm\u003csup\u003e3\u003c/sup\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eVolumetric Growth Analysis\u003c/h2\u003e \u003cp\u003eVariation between imaging timepoints due to registration errors or differing imaging conditions was controlled by measuring volume differences in the parent artery, which were assumed to remain unchanged. The mean percentage change in artery volumes and the corresponding standard deviation (SD) was determined.\u003c/p\u003e \u003cp\u003eTo assess segmentation consistency, a second blinded investigator re-segmented a random subset of 25 aneurysms. Inter-observer agreement for volume was quantified with the intraclass correlation coefficient (ICC). Growth was defined as (i) 2D growth: increase in maximum diameter\u0026thinsp;\u0026ge;\u0026thinsp;1 mm, and (ii) 3D volumetric growth: threshold derived from logistic mixed-effects regression. We then calculated the proportion of aneurysms meeting each growth criterion.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed in R (4.4.2). Normally distributed variables were reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, and non-normally distributed variables as median and interquartile range (IQR). Normality was determined using the Shapiro-Wilk test. Changes in volume and size from baseline were compared using the paired Wilcoxon signed-rank test. Categorical variables were compared using the chi-squared test or Fisher\u0026rsquo;s exact test. Continuous variables with Mann-Whitney U test or Kruskal-Wallis test, as appropriate.\u003c/p\u003e \u003cp\u003eTo establish a reliability threshold for volumetric growth, 25 aneurysms underwent duplicate measurements at baseline and follow-up. For each timepoint, two volume readings were averaged, and a growth ratio was defined as the mean follow-up volume divided by the mean baseline volume. This ratio was dichotomized based as \u0026gt;\u0026thinsp;1 (growth) or \u0026lt;\u0026thinsp;1 (no growth). To account for inter-observer and inter-timepoint variability, four ratios representing all baseline\u0026ndash;follow-up measurement combinations were used as predictors in a logistic mixed mode, yielding four observations per aneurysm. The binary outcome indicated whether the averaged follow-up-to-baseline ratio exceeded 1.\u003c/p\u003e \u003cp\u003e3D volumetric growth was defined as the percentage change in aneurysm volume from baseline to follow-up exceeding the model-derived growth threshold. The clinical criterion of difference in size\u0026thinsp;\u0026ge;\u0026thinsp;1mm was used as the definition for 2D growth to ensure consistency with clinical practice.\u003c/p\u003e \u003cp\u003eA post-hoc sensitivity analysis excluding aneurysms\u0026thinsp;\u0026gt;\u0026thinsp;5 mm was performed to account for the predominance of small aneurysms in our cohort and the distinct natural history of larger aneurysms.\u003c/p\u003e \u003cp\u003eUnivariate logistic regression was used to identify independent predictors of significant volumetric growth. Covariates were entered into a multivariate model based on univariate p\u0026thinsp;\u0026lt;\u0026thinsp;0.10 or clinical relevance. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUC). Adjusted ORs with 95% CI were reported for each covariate. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for all final analyses.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCE = contrast-enhanced\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTOF = time-of-flight\u003c/p\u003e\n\u003cp\u003eMRA = Magnetic resonance angiography\u003c/p\u003e\n\u003cp\u003eCTA = Computed tomography angiography\u003c/p\u003e\n\u003cp\u003eUIA = Unruptured intracranial aneurysm\u003c/p\u003e\n\u003cp\u003eACA = Anterior cerebral artery\u003c/p\u003e\n\u003cp\u003eICA = Internal carotid artery\u003c/p\u003e\n\u003cp\u003eACOM = \u0026nbsp;Anterior communicating artery complex\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBA = Basilar artery\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePCOM = Posterior communicating artery\u003c/p\u003e\n\u003cp\u003eICC = Intraclass correlation coefficient\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVTK = Visualization Toolkit\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not receive funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eN.S. and E.S. contributed to all aspects of the study and drafted the manuscript. E.A.S. contributed to study design and conceptualization. P.M., K.S., and L.D. collected data and assisted with manuscript drafting and editing. D.C., R.C., and I.S. contributed to data collection. N.S. and L.W. performed statistical analysis. N.S. prepared figures 1-2. A.G., C.D., B.Z., G.P., and R.K. assisted with manuscript drafting and editing. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eAdditional Information\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eVillablanca, J. P. et al. 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The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping. \u003cem\u003eRadiology\u003c/em\u003e \u003cb\u003e295\u003c/b\u003e, 328\u0026ndash;338. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1148/radiol.2020191145\u003c/span\u003e\u003cspan address=\"10.1148/radiol.2020191145\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Intracranial Aneurysm, Angiography, Growth","lastPublishedDoi":"10.21203/rs.3.rs-8347568/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8347568/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMonitoring unruptured intracranial aneurysms (UIAs) is critical for guiding treatment, but conventional two-dimensional size-based monitoring may miss subtle growth and underestimate rupture risk. Aneurysm volume may offer a more sensitive alternative. This study evaluated the effectiveness of volumetric analysis in detecting significant growth compared to standard size-based assessment in routine clinical management. Patients undergoing UIA surveillance from January 2024 to January 2025 with baseline and follow-up angiographic imaging\u0026thinsp;\u0026ge;\u0026thinsp;4 months apart were included. Aneurysm size was obtained from clinical records. Volumetric growth was defined using a logistic mixed model-derived threshold; 2D growth was defined as increase in maximal diameter\u0026thinsp;\u0026ge;\u0026thinsp;1 mm. Logistic regression identified predictors of volumetric growth. Twenty-four out of 123 aneurysms (98 patients) demonstrated significant volumetric growth (\u0026ge;\u0026thinsp;50%), were more frequent in high-risk locations (58% vs 26%, p\u0026thinsp;=\u0026thinsp;0.006), and had smaller baseline volume (median 14.6 vs 29.6 mm\u0026sup3;, p\u0026thinsp;=\u0026thinsp;0.008) with substantially elevated growth rates (median 35% vs 4% per year, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Volumetric assessment detected all 2D growth cases (n 8) and identified 16 additional aneurysms that showed minimal 2D growth (median change 4% vs 38%). Logistic regression identified follow-up time (aOR 1.20 (1.03\u0026ndash;1.42), p\u0026thinsp;=\u0026thinsp;0.02) and high-risk location (aOR 6.96 (1.93\u0026ndash;33.6), p\u0026thinsp;=\u0026thinsp;0.006) as predictors of volumetric growth (AUC of 0.79). Volumetric analysis detects aneurysm growth more effectively than 2D assessments in small aneurysms. Growth was associated with longer follow-up and high-risk locations, highlighting the potential of volumetric assessment to improve UIA surveillance and guide decision-making.\u003c/p\u003e","manuscriptTitle":"Three-Dimensional Volumetric Assessment Enhances Detection of Growth in Unruptured Intracranial Aneurysms","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-16 06:11:06","doi":"10.21203/rs.3.rs-8347568/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"70c845e5-c462-402c-9939-b2b22ef35268","owner":[],"postedDate":"December 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59692251,"name":"Health sciences/Diseases"},{"id":59692252,"name":"Health sciences/Medical research"},{"id":59692253,"name":"Health sciences/Neurology"},{"id":59692254,"name":"Biological sciences/Neuroscience"}],"tags":[],"updatedAt":"2025-12-19T16:09:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-16 06:11:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8347568","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8347568","identity":"rs-8347568","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}