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Value of dynamic contrast-enhanced magnetic resonance imaging quantitative parameters in evaluating the efficacy of neoadjuvant chemoradiotherapy for cervical cancer
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M. Yi   , R. Hong , Zh. Zhang , Z. Xiong , J. Ran |
| Department of Radiology, Chongqing Fifth People's Hospital, Chongqing, 400062, China , songxundou32875378@163.com |
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Abstract: (150 Views) |
Background: this study focused on evaluating the effectiveness of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in patients with cervical cancer (CC) undergoing neoadjuvant chemotherapy and radiation therapy. Materials and Methods: a total of 58 CC patients were included, undergoing examination through DCE-MRI scans. Subsequently, all cases were divided into two groups: the chemotherapy-effective group (32 cases) including complete response (CR) and partial response (PR), and the chemotherapy-ineffective group (26 cases) including stable disease (SD) and disease progression (PD). Results: after treatment, the average maximum diameter of tumors in the chemotherapy and radiation therapy failure group was 4.38 ± 1.23 cm, drastically larger than the 2.51±0.64 cm in the chemotherapy and radiation therapy response group (P < 0.05). Before treatment, the Ktrans of the chemotherapy and radiation therapy response group was superior to that of the failure group, while Ve was inferior to the latter (P < 0.05). After treatment, the Ktrans of the chemotherapy and radiation therapy response group decreased, showing a more drastic reduction compared to the failure group (P < 0.05). The Ktrans of the chemotherapy and radiation therapy response group was drastically inferior to that of the failure group, with statistical significance (P<0.05). The ΔKtrans% in the chemotherapy and radiation therapy response group was negative, inferior to pre-treatment values. In contrast, the ΔKtrans% in the chemotherapy and radiation therapy failure group was positive, superior to pre-treatment values (P < 0.05). Conclusion: DCE-MRI demonstrates excellent scanning performance for CC, accurately monitoring the blood flow signals of CC tumors. Ktrans, Ve, and ΔKtrans have high predictive value in neoadjuvant chemotherapy and radiation therapy. |
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| Keywords: dynamic contrast-enhanced magnetic resonance imaging, quantitative parameters, cervical cancer, neoadjuvant chemotherapy, efficacy evaluation. |
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Full-Text [PDF 1135 kb]
(39 Downloads)
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Type of Study: Original Research |
Subject:
Radiation Biology
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1. 1. Hu Z and Ma D (2018) The precision prevention and therapy of HPV-related cervical cancer: new concepts and clinical implications. Cancer Med, 7(10): 5217-5236. [ DOI:10.1002/cam4.1501] [ PMID] [ ] 2. Anil V, Turukmane A, Nawaf Alhebaishi B, Abdulrhman M, Alshareef (2022) Multispectral image analysis for monitoring by IoT based wireless communication using secure locations protocol and classification by deep learning techniques. Optik, 271: 170122. [ DOI:10.1016/j.ijleo.2022.170122] 3. Saleh M, Virarkar M, Javadi S, Elsherif SB, de Castro Faria S, Bhosale P (2020) Cervical Cancer: 2018 Revised International Federation of Gynecology and Obstetrics Staging System and the Role of Imaging. AJR Am J Roentgenol, 214(5): 1182-1195. [ DOI:10.2214/AJR.19.21819] [ PMID] 4. Gadducci A and Cosio S (2020) Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer: Review of the Literature and Perspectives of Clinical Research. Anticancer Res, 40(9): 4819-4828. [ DOI:10.21873/anticanres.14485] [ PMID] 5. Anupong Wongchai A, Durga rao Jenjeti BA, Indira P (2022) Farm monitoring and disease prediction by classification based on deep learning architectures in sustainable agriculture. Ecological Modelling, 474: 110167. [ DOI:10.1016/j.ecolmodel.2022.110167] 6. Arvind K, Nishant S, Arpit B (2022) Clinical risk assessment of chronic kidney disease patients using genetic programming. Computer Methods in Biomechanics and Biomedical Engineering, 25(8): 887-895. [ DOI:10.1080/10255842.2021.1985476] [ PMID] 7. Benson R, Pathy S, Kumar L, Mathur S, Dadhwal V, Mohanti BK (2019) Locally advanced cervical cancer - neoadjuvant chemotherapy followed by concurrent chemoradiation and targeted therapy as maintenance: A phase II study. J Cancer Res Ther, 15(6): 1359-1364. [ DOI:10.4103/jcrt.JCRT_39_18] [ PMID] 8. Noll F, Palacios Torres AT, Pecci P, Lucchini SM, Heredia F (2021) Neoadjuvant chemotherapy in early-stage cervical cancer (< 2 cm) before conization for fertility preservation: is there any advantage over upfront conization? Int J Gynecol Cancer, 31(3): 379-386. [ DOI:10.1136/ijgc-2020-001751] [ PMID] 9. Harshit B, Pradeep T, Aditi S (2021) EEG-Based Personality Prediction Using Fast FourierTransfoim and DeepLSTM Model. Comput Intell Neurosci, 2021: 6524858. [ DOI:10.1155/2021/6524858] [ PMID] [ ] 10. Lu H, Wu Y, Liu X, Huang H, Jiang H, Zhu C, Man Y, Liu P, Li X, Chen Z, Long X, Pang Q, Deng S, Gu J (2021) The Role of Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Predicting Treatment Response for Cervical Cancer Treated with Concurrent Chemoradiotherapy. Cancer Manag Res, 13: 6065-6078. [ DOI:10.2147/CMAR.S314289] [ PMID] [ ] 11. Zhang A, Song J, Ma Z, Chen T (2020) Combined dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted imaging to predict neoadjuvant chemotherapy effect in FIGO stage IB2-IIA2 cervical cancers. Radiol Med, 125(12): 1233-1242. [ DOI:10.1007/s11547-020-01214-x] [ PMID] 12. Li XX, Lin TT, Liu B, Wei W (2020) Diagnosis of Cervical Cancer with Parametrial Invasion on Whole-Tumor Dynamic Contrast-Enhanced Magnetic Resonance Imaging Combined with Whole-Lesion Texture Analysis Based on T2- Weighted Images. Front Bioeng Biotechnol, 8: 590. [ DOI:10.3389/fbioe.2020.00590] [ PMID] [ ] 13. Zhang Z, Wang Z, Zhao R (2018) Dynamic Contrast-Enhanced Magnetic Resonance Imaging of Advanced Cervical Carcinoma: The Advantage of Perfusion Parameters from the Peripheral Region in Predicting the Early Response to Radiotherapy. Int J Gynecol Cancer, 28(7): 1342-1349. [ DOI:10.1097/IGC.0000000000001308] [ PMID] 14. Treutlein C, Stollberg A, Scherl C, Agaimy A, Ellmann S, Iro H, Lell M, Uder M, Bäuerle T (2020) Diagnostic value of 3D dynamic contrast-enhanced magnetic resonance imaging in lymph node metastases of head and neck tumors: a correlation study with histology. Acta Radiol Open, 9(8): 2058460120951966. [ DOI:10.1177/2058460120951966] [ PMID] [ ] 15. Qin F, Pang H, Ma J, Zhao M, Jiang X, Tong R, Yu T, Luo Y, Dong Y (2021) Combined dynamic contrast enhanced MRI parameter with clinical factors predict the survival of concurrent chemo-radiotherapy in patients with 2018 FIGO IIICr stage cervical cancer. Eur J Radiol, 141: 109787. [ DOI:10.1016/j.ejrad.2021.109787] [ PMID] 16. Bi Q, Chen Y, Chen J, Zhang H, Lei Y, Yang J, Zhang Y, Bi G (2021) Predictive value of T2-weighted imaging and dynamic contrast-enhanced MRI for assessing cervical invasion in patients with endometrial cancer: a meta-analysis. Clin Imaging, 78: 206-213. [ DOI:10.1016/j.clinimag.2021.05.014] [ PMID] 17. Shao J, Zhang Z, Liu H, Song Y, Yan Z, Wang X, Hou Z (2020) DCE-MRI pharmacokinetic parameter maps for cervical carcinoma prediction. Comput Biol Med, 118: 103634. [ DOI:10.1016/j.compbiomed.2020.103634] [ PMID] 18. Lund KV, Simonsen TG, Kristensen GB, Rofstad EK (2019) Pharmacokinetic analysis of DCE-MRI data of locally advanced cervical carcinoma with the Brix model. Acta Oncol, 58(6): 828-837. [ DOI:10.1080/0284186X.2019.1580386] [ PMID] 19. Liu B, Sun Z, Ma WL, Ren J, Zhang GW, Wei MQ, Hou WH, Hou BX, Wei LC, Huan Y, Zheng MW (2020) DCE-MRI Quantitative Parameters as Predictors of Treatment Response in Patients with Locally Advanced Cervical Squamous Cell Carcinoma Underwent CCRT. Front Oncol, 10: 585738. [ DOI:10.3389/fonc.2020.585738] [ PMID] [ ] 20. Hauge A, Gaustad JV, Huang R, Simonsen TG, Wegner CS, Andersen LMK, Rofstad EK (2019) DCE-MRI and Quantitative Histology Reveal Enhanced Vessel Maturation but Impaired Perfusion and Increased Hypoxia in Bevacizumab-Treated Cervical Carcinoma. Int J Radiat Oncol Biol Phys, 104(3): 666-676. [ DOI:10.1016/j.ijrobp.2019.03.002] [ PMID] 21. Lu Y, Peng W, Song J, Chen T, Wang X, Hou Z, Yan Z, Koh TS (2019) On the potential use of dynamic contrast-enhanced (DCE) MRI parameters as radiomic features of cervical cancer. Med Phys, 46(11): 5098-5109. [ DOI:10.1002/mp.13821] [ PMID] 22. Merz J, Bossart M, Bamberg F, Eisenblaetter M (2020) Revised FIGO Staging for Cervical Cancer - A New Role for MRI. Rofo, 192(10): 937-944. English, German. [ DOI:10.1055/a-1198-5729] [ PMID] 23. Girens R, Bukoski A, Maitz CA, Boston SE, Borgatti A, Sprinkle M, Orrego D, Kesl S, Selting K (2019) Use of computed tomography and radiation therapy planning software to develop a novel formula for body surface area calculation in dogs. J Vet Intern Med, 33(2): 792-799. [ DOI:10.1111/jvim.15440] [ PMID] [ ] 24. Li X, Wu S, Li D, Yu T, Zhu H, Song Y, Meng L, Fan H, Xie L (2019) Intravoxel Incoherent Motion Combined with Dynamic Contrast-Enhanced Perfusion MRI of Early Cervical Carcinoma: Correlations Between Multimodal Parameters and HIF-1α Expression. J Magn Reson Imaging, 50(3): 918-929. [ DOI:10.1002/jmri.26604] [ PMID] 25. Bhardwaj R, Boruah DK, Gogoi BB, Zahir F, Sharma A (2022) Added-Value of Diffusion-Weighted Imaging (DWI) and Dynamic Contrast-Enhanced (DCE-MRI) Magnetic Resonance Imaging in the Preoperative Assessment of Cervical Cancer. J Obstet Gynaecol India, 72(4): 330-340. [ DOI:10.1007/s13224-021-01488-9] [ PMID] [ ] |
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Yi M, Hong R, Zhang Z, Xiong Z, Ran J. Value of dynamic contrast-enhanced magnetic resonance imaging quantitative parameters in evaluating the efficacy of neoadjuvant chemoradiotherapy for cervical cancer. Int J Radiat Res 2024; 22 (4) :1067-1074 URL: http://ijrr.com/article-1-5807-en.html
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