Journal of Shandong University (Health Sciences) ›› 2022, Vol. 60 ›› Issue (10): 62-67.doi: 10.6040/j.issn.1671-7554.0.2022.0438

Previous Articles     Next Articles

Correlation between baseline CT features and progression of abdominal aortic aneurysm in 71 cases

WANG Ying1,2, GU Hui2, YU Xinxin1, HU Jinzhuo2, WANG Ruopeng2, WANG Ximing1,2   

  1. 1. Shandong University, Jinan 250012, Shandong, China;
    2. Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250021, Shandong, China
  • Published:2022-09-30

PDF (PC)

98

Abstract: Objective To evaluate the baseline CT features associated with the progression of abdominal aortic aneurysm(AAA)so as to provide a reference for the clinical treatment of AAA. Methods Clinical and imaging data of 83 AAA patients who underwent at least two enhanced CT scans during Jan. 2012 and Dec. 2021 were selected for analysis, with an interval of 3 months or more between the two scans. Baseline CT features such as aneurysm diameter, area, length, curvature, and thrombus area were measured, and the annual rate of AAA progression was calculated based on the aneurysm diameter. Patients with progression were divided into slow progression group(progression rate ≤0.25 cm/y)and rapid progression group(progression rate >0.25 cm/y). Independent samples t-test or Mann-Whitney U nonparametric test was used for comparison between groups; univariate and multivariate linear regression analyses were applied to determine baseline CT characteristics associated with AAA progression. Results Progression was present in 71 patients, including 35 in the slow progression group and 36 in the rapid progression group. The baseline aneurysm length was significantly longer in the rapid progression group than in the slow progression group(P=0.03). Multivariate analysis showed that aneurysm area(β=0.048, P=0.020)and length(β=0.051, P=0.007)were independently and positively correlated with the rate of progression, and aneurysm curvature(β=-0.005, P=0.034)and thrombus area(β=-0.034, P=0.013)were independently and negatively correlated with the rate of progression. Conclusion Among the baseline CT features of AAA patients, aneurysm area, length, curvature, and thrombus area are significantly associated with progression.

Key words: Abdominal aortic aneurysm, Computed tomography, Growth rate, Aneurysm area, Intraluminal thrombus

CLC Number: 

  • R816.2
[1] Toczek J, Boodagh P, Sanzida N, et al. Computed tomography imaging of macrophage phagocytic activity in abdominal aortic aneurysm[J]. Theranostics, 2021, 11(12): 5876-5888.
[2] Sakalihasan N, Michel JB, Katsargyris A, et al. Abdominal aortic aneurysms[J]. Nat Rev Dis Primers, 2018, 4(1): 34. doi: 10.1038/s41572-018-0030-7.
[3] Golledge J. Abdominal aortic aneurysm: update on pathogenesis and medical treatments[J]. Nat Rev Cardiol, 2019, 16(4): 225-242.
[4] 吴建强, 王威, 郑月宏. 血管老化在腹主动脉瘤发病中的作用及潜在的治疗靶点[J]. 中国医学科学院学报, 2021, 43(6): 962-968. WU Jianqiang, WANG Wei, ZHENG Yuehong. Role of vascular aging in the pathogenesis of abdominal aortic aneurysm and potential therapeutic targets[J]. Acta Academiae Medicinae Sinicae, 2021, 43(6): 962-968.
[5] Chaikof EL, Dalman RL, Eskandari MK, et al. The society for vascular surgery practice guidelines on the care of patients with an abdominal aortic aneurysm[J]. J Vasc Surg, 2018, 67(1): 2-77.
[6] Schanzer A, Oderich GS. Management of abdominal aortic aneurysms[J]. N Engl J Med, 2021, 385(18): 1690-1698.
[7] Boyd AJ. Biomechanical prediction of abdominal aortic aneurysm rupture potential[J]. J Vasc Surg, 2020, 71(2): 627. doi: 10.1016/j.jvs.2019.03.052.
[8] Chandrashekar A, Handa A, Lapolla P, et al. Prediction of abdominal aortic aneurysm growth using geometric assessment of computerised tomography images acquired during the aneurysm surveillance period[J]. Ann Surg, 2020, 29: 10. doi: 10.1097/SLA.0000000000004711.
[9] Zur G, Andraous M, Bercovich E, et al. CT-ultrasound fusion for abdominal aortic aneurysm measurement[J]. AJR Am J Roentgenol, 2020, 214(2): 472-476.
[10] Akkoyun E, Gharahi H, Kwon ST, et al. Defining a master curve of abdominal aortic aneurysm growth and its potential utility of clinical management[J]. Comput Methods Programs Biomed, 2021, 208: 106256. doi: 10.1016/j.cmpb.2021.106256.
[11] Zhu C, Leach JR, Wang Y, et al. Intraluminal thrombus predicts rapid growth of abdominal aortic aneurysms[J]. Radiology, 2020, 294(3): 707-713.
[12] Olson SL, Wijesinha MA, Panthofer AM, et al. Evaluating growth patterns of abdominal aortic aneurysm diameter with serial computed tomography surveillance[J]. JAMA Surg, 2021, 156(4): 363-370.
[13] Panthofer AM, Olson SL, Rademacher BL, et al. Anatomic eligibility for endovascular aneurysm repair preserved over 2 years of surveillance[J]. J Vasc Surg, 2021, 74(5): 1527-1536.
[14] 张韬, 郭伟. 腹主动脉瘤诊断和治疗中国专家共识(2022版)[J].中国实用外科杂志, 2022, 42(4): 380-387. ZHANG Tao, GUO Wei. Chinese expert consensus on the diagnosis and treatment of abdominal aortic aneurysm(2022 edition)[J]. Chinese Journal of Practical Surgery, 2022, 42(4): 380-387.
[15] Nana P, Spanos K, Dakis K, et al. Imaging predictive factors of abdominal aortic aneurysm growth[J]. J Clin Med, 2021, 10(9): 1917. doi: 10.3390/jcm10091917.
[16] Doyle BJ, Bappoo N, Syed MBJ, et al. Biomechanical assessment predicts aneurysm related events in patients with abdominal aortic aneurysm[J]. Eur J Vasc Endovasc Surg, 2020, 60(3): 365-373.
[17] Martufi G, Lindquist LM, Sakalihasan N, et al. Local diameter, wall stress, and thrombus thickness influence the local growth of abdominal aortic aneurysms[J]. J Endovasc Ther, 2016, 23(6): 957-966.
[18] Polzer S, Gasser TC, Vlachovsky R, et al. Biomechanical indices are more sensitive than diameter in predicting rupture of asymptomatic abdominal aortic aneurysms[J]. J Vasc Surg, 2020, 71(2): 617-626.
[19] Lindquist LM, Hultgren R, Gasser TC, et al. Volume growth of abdominal aortic aneurysms correlates with baseline volume and increasing finite element analysis-derived rupture risk[J]. J Vasc Surg, 2016, 63(6): 1434-1442.
[20] Hendy K, Gunnarson R, Golledge J. Growth rates of small abdominal aortic aneurysms assessed by computerised tomography-a systematic literature review[J]. Atherosclerosis, 2014, 235(1): 182-188.
[21] Spanos K, Nana P, Kouvelos G, et al. Anatomical differences between intact and ruptured large abdominal aortic aneurysms[J]. J Endovasc Ther, 2020, 27(1): 117-123.
[22] Olson SL, Panthofer AM, Blackwelder W, et al. Role of volume in small abdominal aortic aneurysm surveillance[J]. J Vasc Surg, 2022, 75(4): 1260-1267.
[23] Fillinger MF, Racusin J, Baker RK, et al. Anatomic characteristics of ruptured abdominal aortic aneurysm on conventional CT scans: Implications for rupture risk[J]. J Vasc Surg, 2004, 39(6): 1243-1252.
[24] Cameron SJ, Russell HM, Owens AP. Antithrombotic therapy in abdominal aortic aneurysm: beneficial or detrimental[J]. Blood, 2018, 132(25): 2619-2628.
[25] Moreno DH, Cacione DG, Baptista-Silva JC. Controlled hypotension versus normotensive resuscitation strategy for people with ruptured abdominal aortic aneurysm[J]. Cochrane Database Syst Rev, 2018, 6: CD011664. doi: 10.1002/14651858.CD011664.pub3.
[26] Haller SJ, Crawford JD, Courchaine KM, et al. Intraluminal thrombus is associated with early rupture of abdominal aortic aneurysm[J]. J Vasc Surg, 2018, 67(4): 1051-1058.
[27] Barrett HE, Cunnane EM, Hidayat H, et al. On the influence of wall calcification and intraluminal thrombus on prediction of abdominal aortic aneurysm rupture[J]. J Vasc Surg, 2018, 67(4): 1234-1246.
[28] 周治军, 王哲, 赵珅宇, 等. 基于计算流体力学的腹主动脉瘤破裂风险研究[J]. 介入放射学杂志, 2020, 29(8): 763-767. ZHOU Zhijun, WANG Zhe, ZHAO Shenyu, et al. Study on the rupture risks of abdominal aortic aneurysm based on computational fluid dynamics[J]. Journal of Interventional Radiology, 2020, 29(8): 763-767.
[29] Meyrignac O, Bal L, Zadro C, et al. Combining volumetric and wall shear stress analysis from CT to assess risk of abdominal aortic aneurysm progression[J]. Radiology, 2020, 295(3): 722-729.
[30] Ullery BW, Hallett RL, Fleischmann D. Epidemiology and contemporary management of abdominal aortic aneurysms[J]. Abdom Radiol(NY), 2018, 43(5): 1032-1043.
[31] Chun KC, Anderson RC, Smothers HC, et al. Risk of developing an abdominal aortic aneurysm after ectatic aorta detection from initial screening[J]. J Vasc Surg, 2020, 71(6): 1913-1919.
[32] Nordness MJ, Baxter BT, Matsumura J, et al. The effect of diabetes on abdominal aortic aneurysm growth over 2 years[J]. J Vasc Surg, 2022, 75(4): 1211-1222.
[1] WANG Xin, HOU Yingyue, GUO Jing. Differences in the upper airway morphology among various sagittal skeletal profiles in adolescents aged 12 to 15 years [J]. Journal of Shandong University (Health Sciences), 2022, 60(8): 79-83.
[2] GAO Lin, YU Xinxin, KANG Bing, ZHANG Shuai, WANG Ximing. Predictive value of CT-based radiomics nomogram for the invasiveness of lung pure ground-glass nodules [J]. Journal of Shandong University (Health Sciences), 2022, 60(5): 87-97.
[3] WANG Yu, YIN Zengzheng, NIE Xiaokun, MA Zhide, XIONG Shijiang. Detection of middle mesial canal in 1,125 permanent mandibular first molars using CBCT and related factors [J]. Journal of Shandong University (Health Sciences), 2022, 60(3): 100-109.
[4] YIN Zengzheng, NIE Xiaokun, WANG Yu, MA Zhide, XIONG Shijiang. Morphological observation of the CBCT image about the furcation groove and root canal of 800 maxillary first premolars [J]. Journal of Shandong University (Health Sciences), 2021, 59(8): 74-79.
[5] LIU Xueye, LI Qiming, TANG Hongyi, XU Qiuping, CHEN Wenqian, GUO Jing. Relationship among the volume and surface area of the temporomandibular joint condyle and the sagittal position of disc in young adults [J]. Journal of Shandong University (Health Sciences), 2021, 59(6): 117-121.
[6] CHENG Xiaoguang, LU Yanhui. Osteoporosis in men: a chronically overlooked problem [J]. Journal of Shandong University (Health Sciences), 2021, 59(6): 5-9.
[7] GUAN Shuai, DUAN Shifei, XIA Xiaona, MENG Xiangshui, MA Xiangxing. Diagnostic value of dual-energy photons CT in gout [J]. Journal of Shandong University (Health Sciences), 2021, 59(2): 66-70.
[8] ZHANG Jiahao, LIU Dongxu. Transverse characteristics of skeletal class Ⅱ malocclusion molars and basal bone in 70 cases with different vertical facial types [J]. Journal of Shandong University (Health Sciences), 2021, 59(2): 76-82.
[9] WU Mengtao, WU Peng, YANG Yanfei, TANG Dianjun, MIAO Xiangling, LI Fandong. Application of CT venography in the diagnosis and treatment of recurrent lower extremity varicose veins [J]. Journal of Shandong University (Health Sciences), 2020, 1(9): 21-26.
[10] NIE Xiaokun, HAO Xinyu, ZHANG Shucun, GE Tangna, XIONG Shijiang. A cone-beam computed tomographic study on the distolingual root of the permanent mandibular first molars [J]. Journal of Shandong University (Health Sciences), 2019, 57(3): 85-90.
[11] QI Meng, HUANG Yan, WU Shanshan, LIU Bo, ZHANG Siwei. Effects of single-energy metal artifact reduction algorithm: a systematic review and Meta-analysis [J]. Journal of Shandong University (Health Sciences), 2018, 56(9): 59-64.
[12] HAO Xinyu, LI Jianhua, ZHANG Jing, NIE Xiaokun, XIONG Shijiang. Cone beam computed tomography on the anatomical structure of maxillary first molars root canal [J]. Journal of Shandong University (Health Sciences), 2018, 56(4): 87-91.
[13] DI Yu, YAN Lei, YANG Feilong, LI Dawei, XU Zhonghua. Computed tomography and intravenous pyelography signs of medullary sponge kidney stone [J]. Journal of Shandong University (Health Sciences), 2018, 56(3): 60-65.
[14] WANG Shanrong, DING Yueyun, ZHU Zongping, SHI Dedao, LIU Wanxia, ZHENG Feibo. Validity of SPECT/CT bone fusing imaging in the diagnosis of single bone metastasis of lung cancer [J]. Journal of Shandong University (Health Sciences), 2018, 56(2): 41-46.
[15] ZHANG Jing, YANG Xinghua, LI Jianhua, GE Tangna, ZHANG Shucun, XIONG Shijiang. C-shaped root canal in mandibular posterior teeth evaluated by cone-beam computed tomography [J]. Journal of Shandong University (Health Sciences), 2018, 56(2): 56-61.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] SUO Dongyang, SHEN Fei, GUO Hao, LIU Lichang, YANG Huimin, YANG Xiangdong. Expression and mechanism of Tim-3 in animal model of drug-induced acute kidney injury[J]. Journal of Shandong University (Health Sciences), 2020, 1(7): 1 -6 .
[2] MA Qingyuan, PU Peidong, HAN Fei, WANG Chao, ZHU Zhoujun, WANG Weishan, SHI Chenhui. Effect of miR-27b-3p regulating SMAD1 on osteosarcoma cell proliferation, migration and invasion[J]. Journal of Shandong University (Health Sciences), 2020, 1(7): 32 -37 .
[3] LONG Tingting, XIE Ming, ZHOU Lu, ZHU Junde. Effect of Noggin protein on learning and memory abilities and the dentate gyrus structure after cerebral ischemia reperfusion injury in mice[J]. Journal of Shandong University (Health Sciences), 2020, 1(7): 15 -23 .
[4] LI Ning, LI Juan, XIE Yan, LI Peilong, WANG Yunshan, DU Lutao, WANG Chuanxin. Expression of LncRNA AL109955.1 in 80 cases of colorectal cancer and its effect on cell proliferation, migration and invasion[J]. Journal of Shandong University (Health Sciences), 2020, 1(7): 38 -46 .
[5] ZHANG Baowen, LEI Xiangli, LI Jinna, LUO Xiangjun, ZOU Rong. miR-21-5p targeted TIMP3 to inhibit proliferation and extracellular matrix accumulation of mesangial cells in Type II diabetic nephropathy mice[J]. Journal of Shandong University (Health Sciences), 2020, 1(7): 7 -14 .
[6] FU Jieqi, ZHANG Man, ZHANG Xiaolu, LI Hui, CHEN Hong. Molecular mechanism of Toll-like receptor 4 in the aggravation of blood lipid accumulation by inhibiting the peroxisome proliferator-activate receptor γ[J]. Journal of Shandong University (Health Sciences), 2020, 1(7): 24 -31 .
[7] XU Yuxiang, LIU Yudong, ZHANG Peng, DUAN Ruisheng. A retrospective analysis of risk factors of cerebral microbleeds in 101 patients with cerebral small vessel disease[J]. Journal of Shandong University (Health Sciences), 2020, 1(7): 67 -71 .
[8] DING Xiangyun, YU Qingmei, ZHANG Wenfang, ZHUANG Yuan, HAO Jing. Correlation of the expression of insulin-like growth factor II in granulosa cells and ovulation induction outcomes of 84 patients with polycystic ovary syndrome[J]. Journal of Shandong University (Health Sciences), 2020, 1(7): 60 -66 .
[9] SHI Shuang, LI Juan, MI Qi, WANG Yunshan, DU Lutao, WANG Chuanxin. Construction and application of a miRNAs prognostic risk assessment model of gastric cancer[J]. Journal of Shandong University (Health Sciences), 2020, 1(7): 47 -52 .
[10] XIAO Juan, XIAO Qiang, CONG Wei, LI Ting, DING Shouluan, ZHANG Yuan, SHAO Chunchun, WU Mei, LIU Jianing, JIA Hongying. Comparison of diagnostic efficacy of two kinds of thyroid imagine reporting and data systems[J]. Journal of Shandong University (Health Sciences), 2020, 1(7): 53 -59 .
Copyright 2018 © Editorial office of Journal of Shandong University (Health Sciences)
Supported by Beijing Magtech Co.Ltd