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Abdelkawi MM, Sweed MS, Ali MA, NasrElDin EA. Risk stratification of endometrial cancer and lymph node metastases prediction using 18F-FDG PET/CT: role of metabolic tumor volume and total lesion glycolysis. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2022. [DOI: 10.1186/s43055-022-00716-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Endometrial cancer is the commonest gynecologic malignancy. Pelvic lymph node metastasis is considered one of its most important prognostic factors. Surgery is considered the most important and effective treatment, still there is controversy about indication and necessity of pelvic lymph node dissection. 18F-fluorodeoxyglucose positron emission tomography/computed tomography is investigated in his study to evaluate its value in preoperative detection of lymph node metastases and risk stratification of endometrial cancer.
Results
Reviewing the records of 33 women with endometrial cancer, all 18F-FDG PET/CT studied indices, SUVmax, SUVmean, MTV and TLG, mean difference was statistically significant in all the studied risk categories (tumor grade, Myometrial invasion, lymphovascular space invasion, tumor stage, and risk stratification). SUVmax and TLG showed highest area under the curve for detection of Myometrial invasion > 50% (AUC = 0.911) with cut-off value of SUVmax > 14.55 showing 88.89% sensitivity and 86.67% specificity, and TLG > 192.653 having 88.89% sensitivity and 80% specificity. TLG showed highest AUC (0.889 and 0.921) for detection of LVSI and LNMs with 100% sensitivity and 66.67% specificity for cut-off value > 179.374 and 88.89% sensitivity and 83.33% specificity for cut-off value > 249.366, respectively. Concerning risk stratification of EC, SUVmax and TLG showed highest AUC (0.839) with cut-off value > 14.55 showing 77.27% sensitivity and 90.91% specificity, and > 192.653 having 77.27% sensitivity and 81.82% specificity, respectively.
Conclusion
The results of this study suggest that 18F-FDG PET/CT is a very valuable tool for prediction of lymph node metastases and risk stratification in endometrial cancer patients. Applying TLG cutoff values increases the accuracy and preoperative diagnosis of lymph node metastases which aids in sparing women with low-risk early stage EC unnecessary surgical risk and morbidity of lymphadenectomy.
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Yoon J, Fitzgerald H, Wang Y, Wang Q, Vergalasova I, Elshaikh MA, Dimitrova I, Damast S, Li JY, Fields EC, Beriwal S, Keller A, Kidd EA, Usoz M, Jolly S, Jaworski E, Leung EW, Donovan E, Taunk NK, Chino J, Natesan D, Russo AL, Lea JS, Albuquerque KV, Lee LJ, Hathout L. Does Prophylactic Paraortic Lymph Node Irradiation Improve Outcomes in Women With Stage IIIC1 Endometrial Carcinoma? Pract Radiat Oncol 2022; 12:e123-e134. [PMID: 34822999 DOI: 10.1016/j.prro.2021.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 09/23/2021] [Accepted: 10/06/2021] [Indexed: 11/16/2022]
Abstract
PURPOSE To evaluate the impact of prophylactic paraortic lymph node (PALN) radiation therapy (RT) on clinical outcomes in patients with International Federation of Obstetrics and Gynecology 2018 stage IIIC1 endometrial cancer (EC). METHODS AND MATERIALS A multi-institutional retrospective study included patients with International Federation of Obstetrics and Gynecology 2018 stage IIIC1 EC lymph node assessment, status postsurgical staging, followed by adjuvant chemotherapy and RT using various sequencing regimens. Overall survival (OS) and recurrence-free survival (RFS) rates were estimated by the Kaplan-Meier method. Univariable and multivariable analysis were performed by Cox proportional hazard models for RFS/OS. In addition, propensity score matching was used to estimate the effect of the radiation field extent on survival outcomes. RESULTS A total of 378 patients were included, with a median follow-up of 45.8 months. Pelvic RT was delivered to 286 patients, and 92 patients received pelvic and PALN RT. The estimated OS and RFS rates at 5 years for the entire cohort were 80% and 69%, respectively. There was no difference in the 5-year OS (77% vs 87%, P = .47) and RFS rates (67% vs 70%, P = .78) between patients treated with pelvic RT and those treated with pelvic and prophylactic PALN RT, respectively. After propensity score matching, the estimated hazard ratios (HRs) of prophylactic PALN RT versus pelvic RT were 1.50 (95% confidence interval, 0.71-3.19; P = .28) for OS and 1.24 (95% confidence interval, 0.64-2.42; P = .51) for RFS, suggesting that prophylactic PALN RT does not improve survival outcomes. Distant recurrence was the most common site of first recurrence, and the extent of RT field was not associated with the site of first recurrence (P = .79). CONCLUSIONS Prophylactic PALN RT was not significantly associated with improved survival outcomes in stage IIIC1 EC. Distant metastasis remains the most common site of failure despite routine use of systemic chemotherapy. New therapeutic approaches are necessary to optimize the outcomes for women with stage IIIC1 EC.
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Affiliation(s)
- Jennifer Yoon
- Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey
| | - Halle Fitzgerald
- Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey
| | - Yaqun Wang
- Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey
| | - Qingyang Wang
- Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey
| | | | - Mohamed A Elshaikh
- Departments of Radiation Oncology, Henry Ford Cancer Institute, Detroit, Michigan
| | - Irina Dimitrova
- Departments of Gynecologic Oncology, Henry Ford Cancer Institute, Detroit, Michigan
| | - Shari Damast
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut
| | - Jessie Y Li
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut
| | - Emma C Fields
- Department of Radiation Oncology, Virginia Commonwealth University Health System, Massey Cancer Center, Richmond, Virginia
| | - Sushil Beriwal
- Department of Radiation Oncology, UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Andrew Keller
- Department of Radiation Oncology, UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Elizabeth A Kidd
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California
| | - Melissa Usoz
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California
| | - Shruti Jolly
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Elizabeth Jaworski
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Eric W Leung
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Elysia Donovan
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Neil K Taunk
- Department of Radiation Oncology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Junzo Chino
- Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina
| | - Divya Natesan
- Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina
| | - Andrea L Russo
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | - Jayanthi S Lea
- Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Kevin V Albuquerque
- Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Larissa J Lee
- Department of Radiation Oncology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Lara Hathout
- Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey.
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Huo X, Wang S. A Lymph Node Count-Based AJCC Staging System Facilitates a More Accurate Prediction of the Prognosis of Patients With Endometrial Cancer. Front Oncol 2021; 11:641962. [PMID: 33747965 PMCID: PMC7966708 DOI: 10.3389/fonc.2021.641962] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 01/25/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose Both the International Federation of Gynecology and Obstetrics (FIGO) and the American Joint Committee on Cancer (AJCC) staging system for endometrial cancer (EC) defined the N category by the location of metastatic lymph nodes (LNs) rather than the metastatic LN count. We aimed to compare the accuracy of the AJCC staging system and the LN count-based staging system. Patients and Methods EC patients were selected from the Surveillance, Epidemiology and End Results (SEER) database between 2004 and 2016. Patients' characteristics were collected, including age, race, marital status, histological type, grade, therapeutic measures, the number of metastatic LNs, the number of dissected LNs, vital status, and survival in months. Overall survival (OS) was analyzed by the Kaplan-Meier (KM) method and the concordance index (C-index) was used to compare the prognostic value of the AJCC staging system and the LN count-based staging system. Results We identified 4,276 EC cases from the SEER database, including 2,693 patients with stage IIIC1 and 1,583 patients with stage IIIC2. Multivariate analyses showed that independent prognostic factors for patients with stage IIIC1 included age, race, marital status, grade, histology, chemotherapy, and radiotherapy. Independent prognostic factors for patients with stage IIIC2 included age, marital status, grade, histology, chemotherapy, and radiotherapy. The C-index of the AJCC staging system and the LN count-based staging system were 0.483 and 0.617, respectively. At least six LNs should be dissected to ensure the accuracy of the LN count-based staging system. Conclusion A modified AJCC staging system based on the count of metastatic LNs might be superior to the current AJCC staging system, which still had room for improvement and further refinements were required. For accurate staging, we recommended that at least six LNs should be examined in the modified AJCC staging system.
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Affiliation(s)
- Xinlong Huo
- Department of Oncology, The First Hospital of Qinhuangdao City, Qinhuangdao, China
| | - Shufang Wang
- Department of Obstetrics and Gynecology, Maternal and Child Health Care Hospital of Qinhuangdao, Qinhuangdao, China
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Liu DD, Li J, Li X, Xie L, Qin L, Peng F, Cheng MH. Prognostic value of metabolic tumor volume and total lesion glycolysis from ¹⁸F-FDG PET/CT in lymph node metastases and risk stratification of endometrial carcinoma. J Gynecol Oncol 2020; 30:e89. [PMID: 31576685 PMCID: PMC6779626 DOI: 10.3802/jgo.2019.30.e89] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Revised: 03/01/2019] [Accepted: 04/18/2019] [Indexed: 12/19/2022] Open
Abstract
Objective To investigate the prognostic value of metabolic tumor volume (MTV) and total lesion glycolysis (TLG), measured by preoperative 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT), in risk stratification of patients with endometrial carcinoma (EC). Methods The patients with pathological diagnosis of EC who underwent preoperative 18F-FDG PET/CT imaging were retrospectively selected for analysis of the prognostic values of PET parameters in risk classification and lymph node metastases (LNMs). Receiver-operating-characteristic analysis was used to analyze the correlation of PET parameters cutoff values with deep myometrial invasion (MI), lymphovascular space involvement and LNM for prognostic values in risk stratification. Results The sensitivity, specificity, positive predictive value, negative predictive value and accuracy for detection of LNM are 83.3%, 99.7%, 90.9%, 99.5% and 99.2%, respectively. The MTV and TLG of primary lesion of EC in the patients with LNM are notably higher than those in patients without LNM, p<0.010. The MTV and TLG of the EC primary lesions in high-risk patients are significantly higher than those in low-risk patients (p<0.010), but the maximum standardized uptake value (SUVmax) is not. The MTV and TLG of primary lesions were superior to SUVmax for predicting of deep MI, LNM and high-risk of EC (p<0.005). Conclusion MTV and TLG of primary lesions are more valuable in predicting risk stratification of EC patients. Preoperative 18F-FDG PET/CT imaging is useful in predicting the LNM of EC and may help guide pelvic lymphadenectomy to avoid unnecessary pelvic lymphadenectomy in EC patients with low-risk stratification.
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Affiliation(s)
- Dou Dou Liu
- Department of Nuclear Medicine, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Department of Radiology, FUWAI Central China Cardiovascular Hospital, Zhengzhou, China
| | - Jianfang Li
- Department of Nuclear Medicine, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Xiaomao Li
- Department of Gynecology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Liangjun Xie
- Department of Nuclear Medicine, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Luping Qin
- Department of Nuclear Medicine, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Fangyu Peng
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Mu Hua Cheng
- Department of Nuclear Medicine, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
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