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International Journal of Public Health and Preventive Medicine, 2021, 2(4); doi: 10.38007/IJPHPM.2021.020403.

Construction of Early Risk Factors and Intervention Programs of Lower Limb Lymph-edema in Patients with Gynecological Malignant Tumors Combined with CT Images


Yan Cui

Corresponding Author:
Yan Cui

Qilu Institute of Technology, Jinan, China


Lymph-edema of lower limbs is one of the common complications of gynecologic cancer patients. Once lymph-edema of lower extremities appears after treatment, it is difficult to cure, which seriously affects the quality of treatment of patients. Lymph-edema early detection and timely intervention is important. In order to prevent and treat the lymph-edema of lower limbs in patients with gynecological malignancies in the early stage, this paper uses the computer-aided diagnosis method to scan the lower limbs of patients with gynecological malignant tumors by using CT imaging technology, and identify the location of lesions in patients with gynecological malignant tumors, and carry out image enhancement and denoising on the scanned CT images to mark the lesion sites. The incidence rate of incidence of lymph-edema in lower extremities was analyzed according to the patients' basic characteristics. The influence of different treatment methods on the incidence rate of lymph-edema and the incidence rate of lymph-edema in different stages of gynecologic malignancies were also analyzed. Finally, a drop of congestive therapy based on the research literature, three drugs therapy and surgical therapy for lower extremity lymph-edema intervention programs, through the patient's body recovery, lower limb swelling analysis of these three methods to effect the lower extremity lymph-edema, for patients to find a suitable intervention programs. The final results showed that the number of patients between the ages of 40-49 and 60-69 were the largest, reaching 427 and 417 respectively, and the heavier the patient, the higher the incidence. Radiotherapy, chemotherapy and pelvic lymph node dissection resulted in 89.73%, 89.76% and 86.96% of patients with lower limb lymph-edema, which is one of the risk factors for lower limb lymph-edema. Among the three intervention programs for lymph-edema of the lower limbs, decongestant therapy has a slower treatment speed but low cost and no side effects. Drug treatment can only be applied to some patients, and surgical treatment has good results but high cost.


Gynecological Malignancy, Lower Limb Lymph-Edema, Early recognition, Treatment

Cite This Paper

Yan Cui. Construction of Early Risk Factors and Intervention Programs of Lower Limb Lymph-edema in Patients with Gynecological Malignant Tumors Combined with CT Images. International Journal of Public Health and Preventive Medicine (2021), Vol. 2, Issue 4: 26-45. https://doi.org/10.38007/IJPHPM.2021.020403.


[1] Tugral A, Viren T, Bakar Y. Tissue dielectric constant and circumference measurement in the follow-up of treatment related changes in lower limb lymphedema. International Angiology, 2018, 37(1):26-31.

[2] Noori K, Adarsh D, Satheeshan B, et al. The incidence and risk factors for development of lower limb lymphedema after treatment for gynaecological cancers. International Journal of Reproduction Contraception Obstetrics & Gynecology, 2018, 7(3):1168-1171.

[3] Sethi G, Saini B S. Computer aided diagnosis system for abdomen diseases in computed tomography images. Biocybernetics & Biomedical Engineering, 2016, 36(1):42-55.

[4] Agha M, Eid A F, Nouh M. 3T MRI of the breast with computer aided diagnosis, can it help to avoid unnecessary invasive procedures? Alexandria Journal of Medicine, 2016, 52(1):9-18.

[5] Mohebian M R, Marateb H R, Mansourian M, et al. A Hybrid Computer-aided-diagnosis System for Prediction of Breast Cancer Recurrence (HPBCR) Using Optimized Ensemble Learning. Computational & Structural Biotechnology Journal, 2017, 15(C):75-85.

[6] Amir G J, Lehmann H P. After Detection: The Improved Accuracy of Lung Cancer Assessment Using Radiologic Computer-aided Diagnosis. Academic Radiology, 2016, 23(2):186-191.

[7] Dai Y, Qiu D, Wang Y, et al. Research on Computer-Aided Diagnosis of Alzheimer's Disease Based on Heterogeneous Medical Data Fusion. International Journal of Pattern Recognition and Artificial Intelligence, 2019, 33(5):1-17.

[8] Fei, Gao, Yi, et al. Artificial intelligence in computer-aided diagnosis of abdomen diseases. ence China(Life ences), 2019, 62(10):128-131.

[9] Takahashi R, Kajikawa Y. Computer-aided diagnosis: A survey with bibliometric analysis. International Journal of Medical Informatics, 2017, 101(May):58-67.

[10] Hobson P, Lovell B C, Percannella G, et al. Computer Aided Diagnosis for Anti-Nuclear Antibodies HEp-2 Images: Progress and Challenges. Pattern Recognition Letters, 2016, 82(15):3-11.

[11] Wang P, Wang S. Computer-aided CT image processing and modeling method for tibia microstructure. Bio-Design and Manufacturing, 2020, 3(1):71-82.

[12] Cui X Y, Gui Z G, Zhang Q, et al. Learning-Based Artifact Removal via Image Decomposition for Low-Dose CT Image Processing. IEEE Transactions on Nuclear Science, 2016, 63(3):1-1.

[13] Yang W. Finite element model of concrete material based on CT image processing technology. Journal of visual communication & image representation, 2019, 64(Oct.):1-8.

[14] Chen S, Xu L, Yin J, et al. Quantitative characterization of grain internal damage and 3D reconstruction based on Micro-CT image processing. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2017, 33(17):144-151.

[15] Torres F F E, Jacobs R, Ezeldeen M, et al. How image-processing parameters can influence the assessment of dental materials using micro-CT. Imaging ence in Dentistry, 2020, 50(2):161-163.

[16] Selvi C T, Amudha J. Automatic Video Surveillance System for Pedestrian Crossing Using Digital Image Processing. Indian Journal of ence and Technology, 2019, 12(2):1-6.

[17] Pelc N. TU-D-BRB-01: Dual-Energy CT: Techniques in Acquisition and Image Processing. Medical Physics, 2016, 43(6):3746-3746.

[18] Basak P, Nath A. Detection of Different Stages of Lungs Cancer in CT-Scan Images using Image Processing Techniques. International Journal of Innovative Research in Computer and Communication Engineering, 2017, 5(5):9708-9719.

[19] Kim C G. The effect of reducing exposure dose in neurocranium angiography CT scan based on 3D computer image processing. Journal of Advanced Research in Dynamical & Control Systems, 2017, 9(10):170-175.

[20] Taranto G D, Shih‐Heng Chen, Elia R, et al. Free gastroepiploic lymph nodes and omentum flap for treatment of lower limb ulcers in severe lymphedema: Killing two birds with one stone. Journal of Surgical Oncology, 2020, 121(1):168-174.

[21] Chang K, Xia S, Sun Y G, et al. Liposuction combined with lymphatico-venous anastomosis for treatment of secondary lymphedema of the lower limbs: a report of 49 cases. Zhonghua Wai Ke Za Zhi, 2017, 55(4):274-278.

[22] Yasunaga Y, Yanagisawa D, Ohata E, et al. Bioelectrical Impedance Analysis of Water Reduction in Lower-Limb Lymphedema by Lymphaticovenular Anastomosis. Journal of Reconstructive Microsurgery, 2019, 35(04):306-314.

[23] Zeng D, Huang J, Zhang H, et al. Spectral CT Image Restoration via an Average Image-Induced Nonlocal Means Filter. IEEE Transactions on Biomedical Engineering, 2016, 63(5):1044-1057.

[24] Winch C J, Sherman K A, Smith K M, et al. "You're naked, you're vulnerable": Sexual well-being and body image of women with lower limb lymphedema. Body Image, 2016, 18(SEP.):123-134.

[25] Sun D, Yu Z, Chen J, et al. The Value of Using a SkinFibroMeter for Diagnosis and Assessment of Secondary Lymphedema and Associated Fibrosis of Lower Limb Skin. Lymphatic Research & Biology, 2017, 15(1):70-76.