Nguyen Thi Phuong, Mai Hong Son, Mai Huy Thong, Le Ngoc Ha
{"title":"临床病理因素和FDG PET/CT代谢参数预测放射性碘难治性分化甲状腺癌的无进展生存期[18F]。","authors":"Nguyen Thi Phuong, Mai Hong Son, Mai Huy Thong, Le Ngoc Ha","doi":"10.1186/s12880-024-01525-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Identifying prognostic markers for clinical outcomes is crucial in selecting appropriate treatment options for patients with radioiodine-refractory (RAI-R) differentiated thyroid carcinoma (DTC). The aim of this study was to investigate the prognostic value of clinico-pathological features and semiquantitative [<sup>18</sup>F]FDG PET/CT metabolic parameters in predicting progression-free survival (PFS) in DTC patients with RAI-R.</p><p><strong>Patients and methods: </strong>This prospective cohort study included 110 consecutive RAI-R DTC patients who were referred for [<sup>18</sup>F]FDG PET/CT imaging. The lesion standard uptake values (SUV)s, including SUVmax, SUVmean, SULpeak as well astotal metabolic tumor volume (tMTV)and total lesion glycolysis (tTLG) were measured. Disease progression was assessed using the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 and/or Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST) 1.0. PFS curves were plotted using Kaplan-Meier analysis. Univariate and multivariate Cox regression analyses were performed to identify the prognostic factors for PFS.</p><p><strong>Results: </strong>[<sup>18</sup>F]FDG PET/CT metabolic parameters demonstrate predictive value for PFS in RAI-R DTC patients, with sensitivity ranging from 70.7% to 81% and specificity from 75% to 92.3% (p < 0.001). PFS was significantly worse in patients with SUVmax > 6.39 g/ml, SUVmean > 3.68 g/ml, SULpeak > 3.14 g/ml, tTLG > 4.23 g/ml × cm<sup>3</sup>, and tMTV > 1.24 cm<sup>3</sup>. Clinico-pathological factors including age > 55, aggressive variant and follicular histological subtype, extra-thyroidal extension of the primary tumor, stage III - IV disease at initial DTC diagnosis, distant metastases detected on [<sup>18</sup>F]FDG PET/CT, and metabolic parameters of [<sup>18</sup>F]FDG PET/CT associated with PFS in univariate analysis (p < 0.01). In multivariate analysis, extra-thyroidal extension (HR: 2.25; 95% CI: 1.22 - 4.16; p = 0.01), distant metastases on [<sup>18</sup>F]FDG PET/CT (HR: 2.98; 95%CI: 1.62 - 5.5; p < 0.001), and tMTV > 1.24 cm<sup>3</sup> (HR: 4.17; 95% CI: 2.02 - 8.6; p < 0.001), were independent prognostic factors for PFS.</p><p><strong>Conclusions: </strong>In addition to classic clinico-pathological factors, the semiquantitative [<sup>18</sup>F]FDG PET/CT metabolic parameters can be utilized for dynamic risk stratification for progression in RAI-R DTC patients. Furthermore, extra-thyroidal extension of the primary tumor, distant metastases, and tMTV > 1.24 cm<sup>3</sup> are independent prognostic factors for PFS.</p>","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":"24 1","pages":"344"},"PeriodicalIF":2.9000,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11661047/pdf/","citationCount":"0","resultStr":"{\"title\":\"Clinico-pathological factors and [<sup>18</sup>F]FDG PET/CT metabolic parameters for prediction of progression-free survival in radioiodine refractory differentiated thyroid carcinoma.\",\"authors\":\"Nguyen Thi Phuong, Mai Hong Son, Mai Huy Thong, Le Ngoc Ha\",\"doi\":\"10.1186/s12880-024-01525-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Identifying prognostic markers for clinical outcomes is crucial in selecting appropriate treatment options for patients with radioiodine-refractory (RAI-R) differentiated thyroid carcinoma (DTC). The aim of this study was to investigate the prognostic value of clinico-pathological features and semiquantitative [<sup>18</sup>F]FDG PET/CT metabolic parameters in predicting progression-free survival (PFS) in DTC patients with RAI-R.</p><p><strong>Patients and methods: </strong>This prospective cohort study included 110 consecutive RAI-R DTC patients who were referred for [<sup>18</sup>F]FDG PET/CT imaging. The lesion standard uptake values (SUV)s, including SUVmax, SUVmean, SULpeak as well astotal metabolic tumor volume (tMTV)and total lesion glycolysis (tTLG) were measured. Disease progression was assessed using the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 and/or Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST) 1.0. PFS curves were plotted using Kaplan-Meier analysis. Univariate and multivariate Cox regression analyses were performed to identify the prognostic factors for PFS.</p><p><strong>Results: </strong>[<sup>18</sup>F]FDG PET/CT metabolic parameters demonstrate predictive value for PFS in RAI-R DTC patients, with sensitivity ranging from 70.7% to 81% and specificity from 75% to 92.3% (p < 0.001). PFS was significantly worse in patients with SUVmax > 6.39 g/ml, SUVmean > 3.68 g/ml, SULpeak > 3.14 g/ml, tTLG > 4.23 g/ml × cm<sup>3</sup>, and tMTV > 1.24 cm<sup>3</sup>. Clinico-pathological factors including age > 55, aggressive variant and follicular histological subtype, extra-thyroidal extension of the primary tumor, stage III - IV disease at initial DTC diagnosis, distant metastases detected on [<sup>18</sup>F]FDG PET/CT, and metabolic parameters of [<sup>18</sup>F]FDG PET/CT associated with PFS in univariate analysis (p < 0.01). In multivariate analysis, extra-thyroidal extension (HR: 2.25; 95% CI: 1.22 - 4.16; p = 0.01), distant metastases on [<sup>18</sup>F]FDG PET/CT (HR: 2.98; 95%CI: 1.62 - 5.5; p < 0.001), and tMTV > 1.24 cm<sup>3</sup> (HR: 4.17; 95% CI: 2.02 - 8.6; p < 0.001), were independent prognostic factors for PFS.</p><p><strong>Conclusions: </strong>In addition to classic clinico-pathological factors, the semiquantitative [<sup>18</sup>F]FDG PET/CT metabolic parameters can be utilized for dynamic risk stratification for progression in RAI-R DTC patients. Furthermore, extra-thyroidal extension of the primary tumor, distant metastases, and tMTV > 1.24 cm<sup>3</sup> are independent prognostic factors for PFS.</p>\",\"PeriodicalId\":9020,\"journal\":{\"name\":\"BMC Medical Imaging\",\"volume\":\"24 1\",\"pages\":\"344\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-12-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11661047/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Medical Imaging\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12880-024-01525-9\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Medical Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12880-024-01525-9","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Clinico-pathological factors and [18F]FDG PET/CT metabolic parameters for prediction of progression-free survival in radioiodine refractory differentiated thyroid carcinoma.
Objective: Identifying prognostic markers for clinical outcomes is crucial in selecting appropriate treatment options for patients with radioiodine-refractory (RAI-R) differentiated thyroid carcinoma (DTC). The aim of this study was to investigate the prognostic value of clinico-pathological features and semiquantitative [18F]FDG PET/CT metabolic parameters in predicting progression-free survival (PFS) in DTC patients with RAI-R.
Patients and methods: This prospective cohort study included 110 consecutive RAI-R DTC patients who were referred for [18F]FDG PET/CT imaging. The lesion standard uptake values (SUV)s, including SUVmax, SUVmean, SULpeak as well astotal metabolic tumor volume (tMTV)and total lesion glycolysis (tTLG) were measured. Disease progression was assessed using the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 and/or Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST) 1.0. PFS curves were plotted using Kaplan-Meier analysis. Univariate and multivariate Cox regression analyses were performed to identify the prognostic factors for PFS.
Results: [18F]FDG PET/CT metabolic parameters demonstrate predictive value for PFS in RAI-R DTC patients, with sensitivity ranging from 70.7% to 81% and specificity from 75% to 92.3% (p < 0.001). PFS was significantly worse in patients with SUVmax > 6.39 g/ml, SUVmean > 3.68 g/ml, SULpeak > 3.14 g/ml, tTLG > 4.23 g/ml × cm3, and tMTV > 1.24 cm3. Clinico-pathological factors including age > 55, aggressive variant and follicular histological subtype, extra-thyroidal extension of the primary tumor, stage III - IV disease at initial DTC diagnosis, distant metastases detected on [18F]FDG PET/CT, and metabolic parameters of [18F]FDG PET/CT associated with PFS in univariate analysis (p < 0.01). In multivariate analysis, extra-thyroidal extension (HR: 2.25; 95% CI: 1.22 - 4.16; p = 0.01), distant metastases on [18F]FDG PET/CT (HR: 2.98; 95%CI: 1.62 - 5.5; p < 0.001), and tMTV > 1.24 cm3 (HR: 4.17; 95% CI: 2.02 - 8.6; p < 0.001), were independent prognostic factors for PFS.
Conclusions: In addition to classic clinico-pathological factors, the semiquantitative [18F]FDG PET/CT metabolic parameters can be utilized for dynamic risk stratification for progression in RAI-R DTC patients. Furthermore, extra-thyroidal extension of the primary tumor, distant metastases, and tMTV > 1.24 cm3 are independent prognostic factors for PFS.
期刊介绍:
BMC Medical Imaging is an open access journal publishing original peer-reviewed research articles in the development, evaluation, and use of imaging techniques and image processing tools to diagnose and manage disease.