Int J Stomatol

Int J Stomatol ›› 2026, Vol. 53 ›› Issue (3): 344-351.doi: 10.7518/gjkq.2026215

• Original Articles • Previous Articles    

A 12-month longitudinal evaluation using cone beam computed tomography in patients with mandibular odontogenic cysts

Baotian Zhang(),Yutao Xiong,Zhang’ao Li,Rui Ju,Wei Liu,Wei Zeng,Chang Liu,Wei Tang()   

  1. State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Dept. of Oral and Maxillofacial Trauma and Plastic Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
  • Received:2024-11-14 Revised:2025-11-11 Online:2026-05-01 Published:2026-04-24
  • Contact: Wei Tang E-mail:baotianzhang@foxmail.com;mydrtw@vip.sina.com
  • Supported by:
    Sichuan Science and Technology Program(2024NSFSC0659);Research and Develop Program of West China School of Stomatology, Sichuan University(RD-03-202303)

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Abstract:

Objective This study aimed to investigate the prognostic factors associated with the recurrence of mandibular odontogenic cysts post-enucleation via cone beam computed tomography (CBCT) images. Methods Patients who underwent enucleation for mandibular odontogenic cysts in West China Hospital of Stomatology, Sichuan University were retrospectively selected from 2017 to 2021. Their clinical baseline data and histological diagnoses were collected, as well as measurements (longest diameters, volumes, and grey values) based on CBCT data before the surgery and at 6 and 12 months after the surgery. Univariate analyses, repeated measures ANOVA, and multivariate Logistic regression were conducted. Results A total of 90 patients aged 38.4±15.5 years were included in this study, including 26 patients with dentigerous cysts, 30 with radicular cysts, and 34 with odontogenic keratocysts. We found a significant difference in longest diameters across three histological diagnoses over time. The results of multivariate Logistic regression analysis indicated that pa-thological diagnosis was the sole independent influen-cing factor for the recurrence of odontogenic cyst after enucleation. Conclusion Histological diagnosis alone was correlated with the recurrence rate. Odontogenic cysts with high recurrence rates such as odontogenic keratocysts require close follow-up.

Key words: odontogenic cyst, odontogenic keratocyst, cone beam computed tomography, prognosis, cohort study

CLC Number: 

  • R782

TrendMD: 

Fig 1

Typical case"

Fig 2

Inclusion and exclusion process diagram"

Tab 1

Baseline characteristics of patients"

因素DCRCOKCF/χ2值P值
年龄/岁37.6±18.537.6±14.540.0±14.30.1830.833
性别/例女1316150.5890.804
男131419
D1/mm43.3±7.642.1±7.542.8±6.00.2160.806
V1/mm310 097.5±2 960.39 833.9±3 329.49 894.9±2 474.00.0610.941
GV1203.9±41.9201.3±37.9204.1±41.20.0470.954
GVSD178.7±31.394.3±37.187.9±32.61.4960.230

Tab 2

Univariate comparison of prognostic factors in the cured and recurrent groups"

因素治愈组（n=76）复发组（n=14）F/χ2值P值
年龄/岁38.1±15.839.6±14.50.1110.740
性别/例女3680.4520.569
男406
组织学诊断/例DC2608.8940.010*
RC255
OKC259
D1/mm42.5±7.144.0±6.40.5400.464
V1/mm39 794.2±2 851.410 687.4±3 092.61.1310.291
GV1202.1±38.2208.7±49.60.3250.570
GVSD188.5±33.581.3±37.10.5340.467

Tab 3

RM-ANOVA results"

因素DVGV
时期T1D1（42.7±7.0）V1（9 933.1±2 890.5）GV1（203.1±39.9）
T2D2（34.9±5.7）V2（6 762.3±1 979.0）GV2（285.9±53.1）
T3D3（4.8±11.3）V3（814.8±1 979.4）GV3（423.3±58.8）
P值时间0.000*0.000*0.000*
年龄0.8300.3330.352
性别0.6650.6630.471
组织学诊断0.2270.6770.543
时间×年龄0.7570.4590.739
时间×性别0.5020.8120.522
时间×组织学诊断0.016*0.0660.460

Tab 4

Multivariate Logistic regression analysis (using the Enter method)"

因素回归系数标准误差wald χ2P值OR（95%CI）
年龄0.0200.0250.6300.4270.816（0.536，1.243）
性别（以女性为对照组）0.8560.355
男性0.6550.7080.8560.3551.924（0.481，7.701）
组织学诊断（以DC为对照组）1.0160.602
RC-20.4237 571.6540.0000.9980.000（0.000，-）
OKC-0.7010.6951.0160.3140.496（0.127，1.939）
D1-0.2030.2150.8940.3440.816（0.536，1.243）
V10.0010.0001.6630.1971.001（1.000，1.002）
GV10.0090.0081.1400.2861.009（0.992，1.026）
GVSD1-0.0100.0101.0300.3100.990（0.970，1.010）
回归模型截距β?-0.7784.8490.0260.873-

Tab 5

Multivariate Logistic regression analysis (using the Forward Wald method)"

变量回归系数标准误差wald χ2P值OR（95%CI）
组织学诊断（以DC为对照组）0.8830.643
RC-20.1817 882.4900.0000.9980.000（0.000，-）
OKC-0.5880.6250.8830.3470.556（0.163，1.893）
回归模型截距β?-1.0220.3896.9070.009*-

Fig 3

The distribution of the longest diameter, volume and means of grey values in T1, T2, T3 of the cured group (blue) and the recurrence group (red)"

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