Computed Tomography Angiography Markers and Intraluminal Thrombus Morphology as Predictors of Abdominal Aortic Aneurysm Rupture

Abstract

Background: Abdominal aortic aneurysm (AAA) is a complex vascular disease characterized by progressive and irreversible local dilatation of the aortic wall. Currently, the indication for repair is linked to the transverse diameter of the abdominal aorta, using computed tomography angiography imagery, which is one of the most used markers for aneurysmal growth. This study aims to verify the predictive role of imaging markers and underlying risk factors in AAA rupture. Methods: The present study was designed as an observational, analytical, retrospective cohort study and included 220 patients over 18 years of age with a diagnosis of AAA, confirmed by computed tomography angiography (CTA), admitted to Vascular Surgery Clinic of Mures County Emergency Hospital in Targu Mures, Romania, between January 2018 and September 2022. Results: Patients with a ruptured AAA had higher incidences of AH (p = 0.006), IHD (p = 0.001), AF (p < 0.0001), and MI (p < 0.0001), and higher incidences of all risk factors (tobacco (p = 0.001), obesity (p = 0.02), and dyslipidemia (p < 0.0001)). Multivariate analysis showed that a high baseline value of all imaging ratios markers was a strong independent predictor of AAA rupture (for all p < 0.0001). Moreover, a higher baseline value of DA_max (OR:3.91; p = 0.001), SA_max (OR:7.21; p < 0.001), and SLumen_max (OR:34.61; p < 0.001), as well as lower baseline values of DA_renal (OR:7.09; p < 0.001), DA_CT (OR:12.71; p < 0.001), DA_femoral (OR:2.56; p = 0.005), SA_renal (OR:4.56; p < 0.001), SA_CT (OR:3.81; p < 0.001), and SThrombus_max (OR:5.27; p < 0.001) were independent predictors of AAA rupture. In addition, AH (OR:3.33; p = 0.02), MI (OR:3.06; p = 0.002), and PAD (OR:2.71; p = 0.004) were all independent predictors of AAA rupture. In contrast, higher baseline values of SA_max/Lumen_max (OR:0.13; p < 0.001) and ezetimibe (OR:0.45; p = 0.03) were protective factors against AAA rupture. Conclusions: According to our findings, a higher baseline value of all imaging markers ratios at CTA strongly predicts AAA rupture and AH, MI, and PAD highly predicted the risk of rupture in AAA patients. Furthermore, the diameter of the abdominal aorta at different levels has better accuracy and a higher predictive role of rupture than the maximal diameter of AAA.

1. Introduction

Abdominal aortic aneurysm (AAA) is a complex vascular disease characterized by progressive and irreversible local dilatation of the aortic wall. It is one of the most lethal pathologies, occupying 13th place in the USA [1]. The dilatation may occur along the entire thoracic and abdominal aorta but generally affects the infrarenal part [2,3,4,5]. Among the most important risk factors for AAA are age, smoking habits, hypertension, and family history [6,7].

Although AAA is heavily studied, there are still deficiencies in the early diagnosis of its most feared complication. This downfall appears because most aneurysms are asymptomatic, and are thus discovered by chance [4,5]. Currently, the indication for repair is linked to the transverse diameter of the abdominal aorta, using computed tomography angiography imagery, which is one of the most used markers for aneurysmal growth [8,9].

According to multiple studies, aneurysmal growth of more than 5 cm is associated with a significant risk of rupture [10,11], and a 6-month ultrasonography surveillance is recommended for AAAs with a diameter exceeding 4 cm [12]. The rate of growth is also a significant predictor; hence, a rate of 0.5–1 cm/year is associated with a greater risk of rupture [13].

Numerous diagnostic and prognostic techniques have been presented and evaluated in relation to aneurysmal diameter growth and implicit AAA rupture, but the results have not been consistent and differ from one scientific study to the next. Aortic compliance, mean wall stress (MWS), peak wall stress (PWS), peak wall rupture index (PWRI), and aorta calcifications are among the biomechanical features of the aortic wall that have a role in increasing aneurysmal diameter and the risk of rupture [14,15,16,17,18,19,20]. In the prediction of asymptomatic AAA rupture, Polzer et al. [21] proved that biomechanical rupture risk assessment (BRRA) outperforms maximal aneurysmal diameter.

In a recent study, Jusko et al. [22] revealed that the ratio of the maximum aneurysmal diameter to the aorta diameter at the aneurysmal neck is a better imaging marker for AAA rupture than the maximum diameter (as indicated by the area under the curve (AUC) values using ROC analysis, AUC: 0.783 versus 0.650).

The aims of this study were as follows: (1) to determine the role of imaging markers in AAA rupture risk and (2) to evaluate the risk factors associated with the risk of rupture in AAA patients.

2. Materials and Methods

2.1. Study Design

The present study was designed as an observational, analytical, retrospective cohort study and included 220 patients over 18 years of age with a diagnosis of AAA, confirmed by computed tomography angiography (CTA), admitted to Vascular Surgery Clinic of Mures County Emergency Hospital in Targu Mures, Romania, between January 2018 and September 2022. Exclusion criteria were as follows: patients with juxta renal AAA, patients with AAA at the level of the iliac and femoral arteries, and saccular AAA.

Regarding the presence of rupture at admission, all patients enrolled in this study were initially divided into two groups named “uAAA” and “rAAA”. The ideal cut-off value for all imaging markers was used to calculate the risk of rupture.

2.2. Data Collection

The patient’s age and gender were extracted from the hospital’s electronic database. Regarding comorbidities, the following cardiac pathologies were recorded: arterial hypertension (AH), atrial fibrillation (AF), ischemic heart disease (IHD), history of myocardial infarction (MI), chronic heart failure (CHF), and chronic obstructive pulmonary disease (COPD). Other recorded pathologies included: chronic kidney disease (CKD), peripheral arterial disease (PAD), cerebrovascular accident (CVA), and diabetes mellitus (DM).

2.3. CTA Markers

CTA Markers were determined from the measurements of the abdominal aorta at different levels, and the ratios were calculated using the equations as seen in Table 1 and Figure 1. Moreover, intraluminal thrombus (ILT) morphology was divided into four categorizations: eccentric (anterior, posterior, and lateral) and concentric.

Table 1.

Imaging markers definitions.

Markers	Definition
DAmax	maximum diameter of the AAA
DArenal	diameter of the aorta at renal level
DACT	diameter of the aorta at celiac trunk level
DAfemoral	diameter of the femoral artery
SAmax	surface of the AAA at maximum diameter
SArenal	surface of the aorta at renal level
SACT	surface of the aorta at celiac trunk level
SAfemoral	surface of the femoral artery
SLumenmax	surface of the lumen at maximum diameter of the AAA
SThrombusmax	surface of the thrombus at maximum diameter of the AAA
DAmax/Arenal	$\frac{\mathrm{maximum}\mathrm{diameter}\mathrm{of}\mathrm{the}\mathrm{AAA}}{\mathrm{diameter}\mathrm{of}\mathrm{the}\mathrm{aorta}\mathrm{at}\mathrm{renal}\mathrm{level}}$
DAmax/ACT	$\frac{\mathrm{maximum}\mathrm{diameter}\mathrm{of}\mathrm{the}\mathrm{AAA}}{\mathrm{diameter}\mathrm{of}\mathrm{the}\mathrm{aorta}\mathrm{at}\mathrm{celiac}\mathrm{trunk}\mathrm{level}}$
SAmax/Arenal	$\frac{\mathrm{surface}\mathrm{of}\mathrm{the}\mathrm{AAA}\mathrm{at}\mathrm{maximum}\mathrm{diameter}}{\mathrm{surface}\mathrm{of}\mathrm{the}\mathrm{aorta}\mathrm{at}\mathrm{renal}\mathrm{level}}$
SAmax/ACT	$\frac{\mathrm{surface}\mathrm{of}\mathrm{the}\mathrm{AAA}\mathrm{at}\mathrm{maximum}\mathrm{diameter}}{\mathrm{surface}\mathrm{of}\mathrm{the}\mathrm{aorta}\mathrm{at}\mathrm{celiac}\mathrm{trunk}\mathrm{level}}$
SAmax/Lumenmax	$\frac{\mathrm{surface}\mathrm{of}\mathrm{the}\mathrm{AAA}\mathrm{at}\mathrm{maximum}\mathrm{diameter}}{\mathrm{surface}\mathrm{of}\mathrm{the}\mathrm{lumen}\mathrm{at}\mathrm{maximum}\mathrm{diameter}\mathrm{of}\mathrm{the}\mathrm{AAA}}$
SLumenmax/Thrombusmax	$\frac{\mathrm{surface}\mathrm{of}\mathrm{the}\mathrm{lumen}\mathrm{at}\mathrm{maximum}\mathrm{diameter}\mathrm{of}\mathrm{the}\mathrm{AAA}}{\mathrm{surface}\mathrm{of}\mathrm{the}\mathrm{thrombus}\mathrm{at}\mathrm{maximum}\mathrm{diameter}\mathrm{of}\mathrm{the}\mathrm{AAA}}$

Figure 1.

CT angiography: (A) maximal diameter of AAA (axial section); (B) surface of AAA at maximal diameter (yellow) and surface of lumen (orange); (C) diameter and surface of aorta at renal level; and (D) diameter and surface of aorta at celiac trunk level.

2.4. Study Outcomes

The primary endpoint was the risk of AAA rupture. The outcome was stratified based on the optimal cut-off value of imaging markers.

2.5. Statistical Analysis

For statistical analysis, SPSS for Mac OS version 28.0.1.0 was utilized (SPSS, Inc., Chicago, IL, USA). To analyze the correlations of the ratios with categorical factors, chi-square tests were performed. T-Student or Mann–Whitney tests were used to assess differences in continuous variables. The receiver operating characteristic (ROC) curve analysis was used to assess the prediction capability and to set the cut-off values for all imaging indicators. The Youden index was utilized to calculate the optimal imaging marker cut-off values (Youden Index = Sensitivity + Specificity 1, ranging from 0 to 1). A multivariate logistic regression analysis with factors of p < 0.1 was performed to establish independent predictors of AAA rupture.

3. Results

During the studied period, 220 patients were enrolled, from whom 173 patients (78.63%) were diagnosed with AAA without rupture, and 47 patients (21.37%) were diagnosed with ruptured AAA. Of the patients, 123 were male (55.91%), and the mean age was 71.68 ± 9.78 (47–95). The rest of the recorded variables are presented in Table 2.

Table 2.

The baseline characteristics data of all patients, divided according to the AAA rupture risk.

Variables	All Patients n = 220	uAAA n = 173	rAAA n = 47	p Value (OR; CI 95%)
Age mean ± SD (min–max)	71.68 ± 9.78 (47–95)	71.58 ± 10.13 (47–95)	72.06 ± 8.44 (55–88)	0.74
Male/Female sex no. (%)	123 (55.91%) 97 (44.09%)	95 (54.91%) 78 (45.09%)	28 (59.57%) 19 (40.43%)	0.14 (1.45; 0.87–2.42)
Comorbidities and Risk factors, no. (%)
AH, no. (%)	175 (79.54%)	134 (77.45%)	41 (87.23%)	0.006 (2.30; 1.26–4.19)
IHD, no. (%)	159 (72.27%)	120 (69.36%)	39 (82.97%)	0.001 (2.32; 1.38–3.89)
AF, no. (%)	62 (28.18%)	48 (27.74%)	14 (29.78%)	<0.0001 (3.23; 1.90–5.48)
CHF, no. (%)	73 (33.18%)	57 (32.94%)	16 (34.04%)	0.77 (1.09; 0.60–1.98)
MI, no. (%)	44 (20%)	27 (15.6%)	17 (36.17%)	<0.0001 (3.16; 1.83–5.44)
DM, no. (%)	66 (30%)	52 (30.05%)	14 (29.78%)	0.25 (1.37; 0.79–2.35)
CKD, no. (%)	33 (15%)	25 (14.45%)	8 (17.02%)	0.74 (1.11; 0.58–2.10)
COPD, no. (%)	24 (10.9%)	17 (9.82%)	7 (14.89%)	0.74 (1.11; 0.58–2.10)
PAD, no. (%)	103 (46.81%)	71 (41.04%)	32 (68.08%)	0.64 (1.14; 0.63–2.06)
CVA, no. (%)	64 (29.09%)	46 (26.58%)	18 (38.29%)	0.74 (1.11; 0.58–2.10)
Tobacco, no. (%)	58 (26.36%)	41 (23.69%)	17 (36.17%)	0.001 (2.55; 1.46–4.46)
Obesity, no. (%)	50 (22.72%)	31 (17.91%)	19 (40.42%)	0.02 (1.90; 1.10–3.28)
Dyslipidemia, no. (%)	39 (17.72%)	30 (17.34%)	9 (19.14%)	<0.0001 (5.27; 3.07–9.02)
Computed Tomography Angiography Markers, median [Q1–Q3]
DAmax	6.75 [5.71–8.15]	6.42 [5.64–8.1]	7.63 [6.31–8.41]	0.003
DArenal	2.15 [1.64–2.50]	2.26 [1.88–2.56]	1.59 [1.27–2.04]	<0.0001
DACT	2.38 [1.83–2.86]	2.56 [2.13–2.95]	1.78 [1.53–2.04]	<0.0001
DAfemoral	0.93 [0.78–1.12]	0.95 [0.80–1.13]	0.84 [0.72–0.98]	0.005
SAmax	53.7 [39.51–74.26]	48.3 [36.01–69.94]	75.73 [57.83–91.78]	<0.0001
SArenal	4.95 [3.89–5.91]	5.29 [4.34–6.31]	3.89 [3.53–4.79]	<0.0001
SACT	5.33 [4.44–6.69]	5.55 [4.69–6.95]	4.59 [4.01–5.42]	<0.0001
SAfemoral	1.19 [0.87–1.61]	1.24 [0.89–1.59]	1.15 [0.81–1.98]	0.12
SLumenmax	28.98 [13.01–44.77]	23.47 [10.42 = 35.31]	55.31 [42.79–65.64]	<0.0001
SThrombusmax	21.81 [13.38–34.23]	22.9 [14.21–34.42]	16.41 [11.72–29.09]	0.052
DAmax/Arenal	3.29 [2.49–4.37]	3.04 [2.34–3.92]	4.60 [3.86–5.41]	<0.0001
DAmax/ACT	2.92 [2.26–3.97]	2.71 [2.03–3.39]	4.29 [3.45–5.15]	<0.0001
DAmax/Afemoral	7.40 [5.83–9.06]	7.10 [5.46–8.81]	8.81 [6.89–10.36]	0.01
SAmax/Arenal	10.65 [7.47–16.12]	8.89 [7.03–12.98]	18.9 [15.9–21.05]	<0.0001
SAmax/ACT	9.41 [6.8–14.66]	7.79 [6.38–12.02]	15.6 [12.89–20.76]	<0.0001
SAmax/Afemoral	42.44 [26.79–72.19]	38.61 [25.73–57.67]	82.22 [32.17–106.3]	<0.0001
SAmax/Lumenmax	1.72 [1.35–2.89]	2.06 [1.49–3.89]	1.32 [1.20–1.56]	<0.0001
SAmax/Thrombusmax	2.37 [1.52–3.80]	1.94 [1.34–3.007]	4.04 [2.75–5.89]	<0.0001
SLumenmax/Thrombusmax	1.37 [0.52–2.80]	0.94 [0.34–2.007]	3.04 [1.75–4.89]	<0.0001
Intraluminal Thrombus Morphology, no. (%)
Posterior-Eccentric	77 (35%)	61 (35.26%)	16 (34.04%)	0.87 (0.94; 0.48–1.86)
Anterior-Eccentric	49 (22.27%)	31 (17.92%)	18 (38.3%)	0.003 (2.84; 1.40–5.75)
Lateral-Eccentric	62 (28.18%)	49 (28.32%)	13 (27.66%)	0.92 (0.96; 0.47–1.98)
Concentric	32 (14.55%)	30 (17.34%)	2 (4.26%)	0.03 (0.21; 0.04–0.92)

AH = arterial hypertension; IHD = ischemic heart disease; AF = atrial fibrillation; CHF = chronic heart failure; MI = myocardial infarction; CKD = chronic kidney disease; COPD = chronic obstructive pulmonary disease; PAD = peripheral arterial disease; CVA = cerebrovascular accident.

Patients with rAAA had higher incidences of AH (p = 0.006), IHD (p = 0.001), AF (p < 0.0001), and MI (p < 0.0001) and higher incidences of all risk factors (tobacco (p = 0.001), obesity (p = 0.02), and dyslipidemia (p < 0.0001)) as seen in Table 2.

Regarding the CTA markers, patients in the rAAA group had higher values of DA_max (p = 0.003), SA_max (p < 0.0001), SLumen_max (p < 0.0001), DA_max/A_renal (p < 0.0001), DA_max/A_CT (p < 0.0001), DA_max/A_femoral (p = 0.01), SA_max/A_renal (p < 0.0001), SA_max/A_CT (p < 0.0001), SA_max/A_femoral (p < 0.0001), SA_max/Thrombus_max (p < 0.0001), SLumen_max/Thrombus_max (p < 0.0001), as well lower values of DA_renal (p < 0.0001), DA_CT (p < 0.0001), DA_femoral (p = 0.005), SA_renal (p < 0.0001), SA_CT (p < 0.0001), and SA_max/Lumen_max (p < 0.0001). In terms of ILT morphology, there was a higher incidence of anterior-eccentric distribution (p = 0.003), as well as a lower incidence of concentric distribution (p = 0.03) in the rAAA group.

The ROC curves of all imaging markers were created to determine whether the baseline of these markers was predictive of AAA rupture (Figure 2 and Figure 3). The optimal cut-off value obtained from Youden’s index, areas under the curve (AUC), and the predictive accuracy of the markers are listed in Table 3.

Figure 2.

The ROC curve analysis concerning AAA rupture for the (A) DA_max (AUC: 0.630; p = 0.006), (B) DA_renal (AUC: 0.744; p < 0.0001), (C) DA_CT (AUC: 0.802; p < 0.0001), (D) DA_femoral (AUC: 0.620; p = 0.01), (E) SA_max (AUC: 0.789; p < 0.0001), (F) SA_renal (AUC: 0.746; p < 0.0001), (G) SA_CT (AUC: 0.684; p < 0.0001), (H) SA_femoral (AUC: 0.556; p = 0.24), (I) SLumen_max (AUC: 0.887; p < 0.0001), and (J) SThrombus_max (AUC: 0.577; p = 0.10).

Figure 3.

The ROC curve analysis concerning AAA rupture for the (A) DA_max/A_renal (AUC: 0.810; p < 0.0001), (B) DA_max/A_CT (AUC: 0.850; p < 0.0001), (C) DA_max/A_femoral (AUC: 0.687; p < 0.0001), (D) SA_max/A_renal (AUC: 0.890; p < 0.0001), (E) SA_max/A_CT (AUC: 0.846; p < 0.0001), (F) SA_max/A_femoral (AUC: 0.709; p < 0.0001), (G) SA_max/Thrombus_max (AUC: 0.809; p < 0.0001), (H) SA_max/Lumen_max (AUC: 0.809; p < 0.0001), and (I) SLumen_max/Thrombus_max (AUC: 0.809; p < 0.0001).

Table 3.

The AUC of the ROC curve, 95% confidence interval, sensitivity, and specificity of the imaging markers.

Variables	Cut-Off	AUC	Std. Error	95% CI	Sensitivity	Specificity	p Value
AAA Rupture
DAmax	6.11	0.630	0.041	0.549–0.711	83%	44.5%	0.006
DArenal	1.73	0.744	0.043	0.660–0.828	81.5%	61.7%	<0.0001
DACT	2.08	0.802	0.037	0.730–0.875	77.5%	78.7%	<0.0001
DAFemoral	0.84	0.620	0.049	0.524–0.716	71.1%	51.1%	0.01
SAmax	65.16	0.789	0.034	0.723–0.856	70.2%	75.1%	<0.0001
SArenal	4.72	0.746	0.037	0.673–0.819	63.6%	72.3%	<0.0001
SACT	5.09	0.684	0.042	0.603–0.766	64.2%	68.1%	<0.0001
SAfemoral	0.91	0.556	0.051	0.457–0.655	73.4%	40.4%	0.24
SLumenmax	35.94	0.887	0.023	0.842–0.932	91.5%	76.3%	<0.0001
SThrombusmax	17.48	0.577	0.047	0.485–0.669	64.7%	51.1%	0.10
DAmax/Arenal	3.27	0.810	0.036	0.740–0.880	87.2%	64.2%	<0.0001
DAmax/ACT	3.07	0.850	0.029	0.794–0.907	80.9%	75.7%	<0.0001
DAmax/Afemoral	6.78	0.687	0.044	0.600–0.773	83%	49.1%	<0.0001
SAmax/Arenal	14.27	0.890	0.023	0.844–0.935	89.4%	81.5%	<0.0001
SAmax/ACT	9.85	0.846	0.027	0.793–0.898	93.6%	67.6%	<0.0001
SAmax/Afemoral	58.19	0.709	0.047	0.618–0.800	66%	75.1%	<0.0001
SAmax/Lumenmax	1.57	0.809	0.031	0.749–0.870	71.7%	78.7%	<0.0001
SAmax/Thrombusmax	2.75	0.809	0.031	0.749–0.870	78.7%	71.7%	<0.0001
SLumenmax/Thrombusmax	1.75	0.809	0.031	0.749–0.870	78.7%	71.7%	<0.0001

The risk of AAA rupture was further analyzed after dividing the patients into paired groups according to the optimal cut-off value of imaging markers. Moreover, as seen in Table 4, there was a higher incidence of AAA rupture risk for all the imaging markers, with exceptions for DA_renal, DA_CT, SA_renal, SA_CT, SA_max/SLumen_max, where lower incidences of AAA rupture were reported.

Table 4.

Univariate analysis of imaging markers and risk of AAA rupture.

	rAAA		rAAA
Low-DAmax vs. High-DAmax	14/144 (9.72%) vs. 33/76 (43.42%) p < 0.0001	Low-DAmax/Arenal vs. High-DAmax/Arenal	6/117 (5.13%) vs. 41/103 (39.81%) p < 0.0001
High-DArenal vs. Low-DArenal	18/159 (11.32%) vs. 29/61 (47.5%) p < 0.0001	Low-DAmax/ACT vs. High-DAmax/ACT	3/120 (2.5%) vs. 44/100 (44%) p < 0.0001
High-DACT vs. Low-DACT	10/144 (6.94%) vs. 37/76 (48.68%) p < 0.0001	Low-DAmax/AFemoral vs. High-DAmax/AFemoral	3/120 (2.5%) vs. 44/100 (44%) p < 0.0001
Low-DAFemoral vs. High-DAFemoral	23/146 (15.7%) vs. 24/74 (32.43%) p = 0.005	Low-SAmax/Arenal vs. High-SAmax/Arenal	10/134 (7.46%) vs. 37/86 (43.02%) p < 0.0001
Low-SAmax vs. High-SAmax	14/144 (9.72%) vs. 33/76 (43.42%) p < 0.0001	Low-SAmax/ACT vs. High-SAmax/ACT	3/120 (2.5%) vs. 44/100 (44%) p < 0.0001
High-SArenal vs. Low-SArenal	13/123 (10.5%) vs. 34/97 (35.05%) p < 0.0001	Low-SAmax/AFemoral vs. High-SAmax/AFemoral	16/146 (10.96%) vs. 31/74 (41.9%) p < 0.0001
Low-SACT vs. High-SACT	3/120 (2.5%) vs. 44/100 (44%) p < 0.0001	Low-SAmax/SLumenmax vs. High-SAmax/SLumenmax	35/84 (41.67%) vs. 12/136 (8.82%) p < 0.0001
Low-SLumenmax vs. High-SLumenmax	4/136 (2.94%) vs. 43/84 (51.19%) p < 0.0001	Low-SLumenmax/Thrombusmax vs. High-SLumenmax/Thrombusmax	10/134 (7.46%) vs. 37/86 (43.02%) p < 0.0001
Low-SAmax/Thrombusmax vs. High-SAmax/Thrombusmax		10/134 (7.46%) vs. 37/86 (43.02%) p < 0.0001

A multivariate analysis was used to determine the association between the imaging markers, underlying risk factors, and AAA rupture risk. A high baseline value of all imaging ratio markers was a strong independent predictor of AAA rupture (for all p < 0.0001). Moreover, as shown in Table 5, higher baseline values of DA_max (OR:3.91; p = 0.001), SA_max (OR:7.21; p < 0.001), and SLumen_max (OR:34.61; p < 0.001), as well as lower baseline values of DA_renal (OR:7.09; p < 0.001), DA_CT (OR:12.71; p < 0.001), DA_femoral (OR:2.56; p = 0.005), SA_renal (OR:4.56; p < 0.001), SA_CT (OR:3.81; p < 0.001), and SThrombus_max (OR:5.27; p < 0.001) were independent predictors of AAA rupture. Furthermore, AH (OR:3.33; p = 0.02), MI (OR:3.06; p = 0.002), PAD (OR:2.71; p = 0.004), and anterior-eccentric morphology of ILT (OR:2.84; p = 0.004) were all independent predictors of AAA rupture. In contrast, the higher baseline values of SA_max/Lumen_max (OR:0.13; p < 0.001) and concentric morphology of ILT (OR:0.21; p = 0.03) were protective factors against AAA rupture (Table 5).

Table 5.

Multivariate analysis for predictors AAA rupture.

	rAAA
Variables	OR	95% CI	p Value
Comorbidities and Risk Factors
AH	3.33	1.13–9.86	0.02
MI	3.06	1.48–6.31	0.002
PAD	2.71	1.38–5.33	0.004
Tobacco	1.41	0.70–2.86	0.33
Obesity	0.52	0.22–1.26	0.15
Intraluminal Thrombus Morphology
Anterior-Eccentric	2.84	1.40–5.75	0.004
Concentric	0.21	0.04–0.92	0.03
Computed Tomography Angiography Markers
High-DAmax	3.91	1.72–8.85	0.001
Low-DArenal	7.09	3.51–14.32	<0.001
Low-DACT	12.71	5.80–27.85	<0.001
Low-DAfemoral	2.56	1.32–4.95	0.005
High-SAmax	7.12	3.49–14.55	<0.001
Low-SArenal	4.56	2.24–9.29	<0.001
Low-SACT	3.81	1.92–7.59	<0.001
High-SLumenmax	34.61	11.72–102.20	<0.001
Low-SThrombusmax	5.27	3.07–9.02	<0.001
High-DAmax/Arenal	12.23	4.91–30.43	<0.001
High-DAmax/ACT	11.93	5.03–28.32	<0.001
High-DAmax/Afemoral	4.60	2.03–10.41	<0.001
High-SAmax/Arenal	37.01	13.56–100.96	<0.001
High-SAmax/ACT	30.64	9.11–102.97	<0.001
High-SAmax/Afemoral	5.85	2.92–11.73	<0.001
High-SAmax/Lumenmax	0.13	0.06–0.28	<0.001
High-SAmax/Thrombusmax	9.36	4.32–20.28	<0.001
High-SLumenmax/Thrombusmax	9.36	4.32–20.28	<0.001

AH = arterial hypertension; MI = myocardial infarction; PAD = peripheral arterial disease.

4. Discussion

The primary outcome of this research is that CT angiography imaging markers are highly predictive of AAA rupture risk. As seen in Table 5, cardiovascular diseases (AH, MI, and PAD) and the distribution of intraluminal thrombus predict AAA rupture. To the best of our knowledge, this is the first conducted research to evaluate the diameter of the abdominal aorta at different levels, intraluminal thrombus distribution, specific imaging markers, and the risk of AAA rupture.

AAA is a serious public health issue worldwide, with a high incidence ranging from 1.3% to 12.5% depending on sex. High mortality rates exist in the case of a ruptured AAA [23,24]. In 2019, 172,000, deaths were reported in patients who presented with a ruptured AAA, indicating a rise of more than 80% over the previous 20 years [25,26].

Cardiovascular diseases and risk factors such as smoking, and obesity are among the possible causes involved in the growth and risk of AAA rupture. Similar to our finding, numerous research [27,28,29] considers the occurrence of AH to also be a risk factor. Furthermore, several studies have shown that the presence of PAD, IHD, a history of MI, and coronary artery disease is associated with the presence of AAA and an increased risk of AAA rupture [30,31,32,33,34].

The role of the intraluminal thrombus in the case of AAA evolution has been extensively debated in the specialized literature, with mixed results. Some studies emphasize the protective role of the thrombus [35,36,37,38], while others show the involvement of the thrombus in increasing aneurysmal diameter, weakening the aortic wall, and increasing the risk of rupture [39,40,41]. As shown in Table 5, the circumferential arrangement of the intraluminal thrombus has a protective effect in the case of AAA rupture (OR: 6.41, p < 0.001).

Zhu et al. [42] demonstrated in the multivariate analysis that the basal diameter of the AAA (p = 0.001) and the presence of ILT (p = 0.02) are positively associated with the growth rate of the aneurysmal diameter. Additionally, in the systematic review and meta-analysis published by Singh et al. [18], which included eight studies and a total of 672 patients, they discovered an increase in ILT volume in patients with a ruptured AAA (p = 0.005). Recently, Kontopodis et al. [43] demonstrated that the relative volume of the ILT (37.5% vs. 73.5%; p = 0.004) and maximum thickness (14.5 mm vs. 28 mm; p = 0.001) presented lower values in patients with AAA rupture. Moreover, an ILT volume greater than 51.6% correlates with severe adverse events, as shown in a multivariate analysis (HR: 2.90; p = 0.04) in a study published by Ding et al. [44], which studied the case of 184 patients with AAA following endovascular aneurysm repair. In contrast, the descriptive review published by Boyd et al. [45] emphasized the protective role of ILT by reducing wall stress.

Maximum aneurysmal diameter is the most often utilized imaging marker in evaluating the risk of AAA rupture [42,46,47,48,49,50,51,52,53,54,55]. The current guidelines of the European Society of Vascular and Endovascular Surgery (ESVES) propose a surgical or endovascular resolution of AAA with dimensions higher than 5.5 cm in male patients and less than 5 cm in female patients [56]. In addition, Choksy et al. [57] and Hall et al. [58] observed an AAA rupture rate of 7.4% in AAAs with a diameter of less than 6 cm, and 7.5% in patients with AAAs with a diameter of less than 5 cm. As a result, it is required to study and suggest novel imaging methods for AAA rupture prognosis.

Similar to our study, Siika et al. [59] discovered that a greater diameter of the aortic lumen area (p = 0.02) and a lower ILT area ratio (p = 0.03) are related to an increased risk of AAA rupture. Chung et al. [16] indicated that aneurysmal sac analysis provides us with useful information in stratifying AAA with risk, and hence, PWS (p = 0.003) and MWS (p = 0.02) have higher values in the group with unstable AAA.

This study complements the studies carried out by Jusko et al. [22], Fillinger et al. [60], Di Martino et al. [61], and Kimura et al. [62], who demonstrated that the geometric analysis of the AAA provides valuable information, with a predictive role superior to that of the maximum diameter in the case of the risk of AAA rupture.

According to our study, among the imaging markers analyzed in the multivariate analysis, the high basal values of SA_max/A_renal (OR:37.01; p < 0.001), SLumen_max (OR:34.61; p < 0.001), and SA_max/A_CT (OR:30.64; p < 0.001), show the greatest predictive role of AAA rupture, and are superior to DA_max (OR:3.92; p = 0.001) or SA_max (OR:7.12; p < 0.001), as seen in Table 5.

The strength of this study is represented by the multitude of imaging markers analyzed, for which the predictive roles were demonstrated. However, despite the significant results and the increased sensitivity and specificity of the analyzed markers, our study has numerous limitations. Firstly, it is a retrospective, monocentric study. Secondly, we did not follow the evolution of the patients and did not record the type of intervention for each patient. Moreover, given the retrospective design, we did not have data on chronic medication before the hospitalization of the patients. In the future, we propose to analyze the proposed markers in a study in which we will follow their predictive role in AAA growth. Additional studies are also needed to validate the results obtained in this study.

5. Conclusions

According to our findings, a higher baseline value of all imaging marker ratios at CTA strongly predicts AAA rupture. In addition, AH, MI, and PAD highly predict the risk of rupture in AAA patients. Furthermore, the diameter of the abdominal aorta at different levels has better accuracy and a higher predictive role of rupture than the maximal diameter of AAA. Given the significant risk of mortality in cases with ruptured AAA and the ease with which the measurements for the imaging markers proposed in this study are determined, the measurements can be used to identify patients at high risk of rupture, improve patient care, and develop predictive patterns.

Author Contributions

Conceptualization, methodology, writing—original draft preparation, E.M.A. (Emil Marian Arbănași) and A.V.M.; software, E.M.A. (Eliza Mihaela Arbănași), R.K. and A.D.I.; formal analysis, investigation, C.M.C. and R.C.F.; resources, S.T.V., R.N. and I.H.; writing—review and editing, E.M.A. (Emil Marian Arbănași); data curation, project administration, visualization, supervision, L.M., S.S., T.V.C. and E.R.; validation, all authors. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Targu Mures Emergency County Hospital, Romania (protocol code 26368, on 26 October 2022).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

Funding Statement

This research received no external funding.