UNLABELLED: In patients with cervical cancer, it is important to estimate prognosis at the time of diagnosis. This study using PET with (18)F-FDG was undertaken to determine whether a simple and fast visual analysis of characteristics of the primary tumor before initiation of treatment could achieve this goal. METHODS: Forty-seven patients with cervical cancer who were to be treated by combined radiation therapy and chemotherapy were imaged before beginning treatment. They were then followed for up to 3 y for evidence of recurrence or death. Images of the chest, abdomen, and pelvis were obtained 40-90 min after administration of 370-555 MBq (10-15 mCi) (18)F-FDG. Three observers then independently graded the primary tumor for size (0 = small, 1 = moderate, 2 = large), shape (0 = spherical, 1 = nonspherical), heterogeneity of uptake (0 = none, 1 = moderate, 2 = marked), and presence of lymph nodes (0 = none, 1 = pelvic, 2 = paraaortic, 3 = distant). The scores were summed to achieve a total score. A statistical calculation demonstrated that a score cutoff of 4 best separated patients with a good prognosis from patients with a bad prognosis. Kaplan-Meier analysis was used to compute progression-free survival and overall survival. Evaluation of lymph nodes alone was compared with the grading of tumor characteristics. RESULTS: Observers 1 and 2 scored 26 patients as having a good prognosis and 21 as having a bad prognosis. Observer 3 scored 30 and 17, respectively, a statistically insignificant difference. Survival curves were almost identical for the 3 observers. For progression-free survival, approximately 12% of patients with a good score had disease recurrence whereas approximately 75% with a bad score had disease recurrence. For overall survival, approximately 10% (good) and 80% (bad) died. Evaluation of lymph nodes also separated the groups, but not as well as did visual analysis alone. The combination of the 2 was only slightly superior to visual assessment alone. CONCLUSION: A simple, rapid, and highly reproducible system is described for visual grading of characteristics of the primary tumor in patients with cervical cancer at the time of diagnosis. This approach separates patients with a poor prognosis from those who will do well, thus providing a new tool for accurate estimation of prognosis.
UNLABELLED: In patients with cervical cancer, it is important to estimate prognosis at the time of diagnosis. This study using PET with (18)F-FDG was undertaken to determine whether a simple and fast visual analysis of characteristics of the primary tumor before initiation of treatment could achieve this goal. METHODS: Forty-seven patients with cervical cancer who were to be treated by combined radiation therapy and chemotherapy were imaged before beginning treatment. They were then followed for up to 3 y for evidence of recurrence or death. Images of the chest, abdomen, and pelvis were obtained 40-90 min after administration of 370-555 MBq (10-15 mCi) (18)F-FDG. Three observers then independently graded the primary tumor for size (0 = small, 1 = moderate, 2 = large), shape (0 = spherical, 1 = nonspherical), heterogeneity of uptake (0 = none, 1 = moderate, 2 = marked), and presence of lymph nodes (0 = none, 1 = pelvic, 2 = paraaortic, 3 = distant). The scores were summed to achieve a total score. A statistical calculation demonstrated that a score cutoff of 4 best separated patients with a good prognosis from patients with a bad prognosis. Kaplan-Meier analysis was used to compute progression-free survival and overall survival. Evaluation of lymph nodes alone was compared with the grading of tumor characteristics. RESULTS: Observers 1 and 2 scored 26 patients as having a good prognosis and 21 as having a bad prognosis. Observer 3 scored 30 and 17, respectively, a statistically insignificant difference. Survival curves were almost identical for the 3 observers. For progression-free survival, approximately 12% of patients with a good score had disease recurrence whereas approximately 75% with a bad score had disease recurrence. For overall survival, approximately 10% (good) and 80% (bad) died. Evaluation of lymph nodes also separated the groups, but not as well as did visual analysis alone. The combination of the 2 was only slightly superior to visual assessment alone. CONCLUSION: A simple, rapid, and highly reproducible system is described for visual grading of characteristics of the primary tumor in patients with cervical cancer at the time of diagnosis. This approach separates patients with a poor prognosis from those who will do well, thus providing a new tool for accurate estimation of prognosis.
Authors: Liyuan Chen; Chenyang Shen; Zhiguo Zhou; Genevieve Maquilan; Kevin Albuquerque; Michael R Folkert; Jing Wang Journal: Phys Med Biol Date: 2019-04-12 Impact factor: 3.609
Authors: Federico Boschi; Laura Calderan; Daniela D'Ambrosio; Mario Marengo; Alberto Fenzi; Riccardo Calandrino; Andrea Sbarbati; Antonello E Spinelli Journal: Eur J Nucl Med Mol Imaging Date: 2010-09-30 Impact factor: 9.236
Authors: Jong Doo Lee; Mijin Yun; Jae Myun Lee; Youjeong Choi; Youn-Hee Choi; Ji Su Kim; Se Jong Kim; Kyung Sik Kim; Woo Ick Yang; Young Nyun Park; Kwang-Hyub Han; Woo Jung Lee; Naechun Yoo; Sang Moo Lim; Jeon Han Park Journal: Eur J Nucl Med Mol Imaging Date: 2004-07-28 Impact factor: 9.236
Authors: Bum Soo Kim; In Joo Kim; Seong-Jang Kim; Hyun-Yeol Nam; Kyoung June Pak; Keunyoung Kim; Man Soo Yun Journal: Nucl Med Mol Imaging Date: 2010-11-12