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Zhang Y, Hu Y, Zhao S, Huang R. The Utility of 18F-FDG-PET-CT Metabolic Parameters in Evaluating the Primary Tumor Aggressiveness and Lymph Node Metastasis of Nasopharyngeal Carcinoma. Clin Med Insights Oncol 2024; 18:11795549231225419. [PMID: 38322667 PMCID: PMC10845995 DOI: 10.1177/11795549231225419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 12/17/2023] [Indexed: 02/08/2024] Open
Abstract
Background Following changes in primary tumor (T) and lymph node (N) staging for nasopharyngeal carcinoma (NPC) in the Eighth Edition AJCC Cancer Staging Manual, simplification of T staging has been proposed. However, a limited range of 2-deoxy-2-[fluorine-18] fluoro-D-glucose positron emission tomography-computed tomography (18F-FDG PET-CT) metabolic parameters has been investigated. Therefore, we aimed to evaluate the primary tumor invasiveness and the lymph node metastasis (LNM) of NPC from a metabolic perspective. Methods A total of 435 NPC patients underwent 18F-FDG PET/CT before treatment were retrospectively examined. The primary endpoint was differences in standard uptake value (SUV), lean body mass-normalized SUV (SUL), body surface area-normalized SUV (SUS), glucose-normalized SUV (GN), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and glucose-normalized total lesion glycolysis (GNTLG) of primary tumors and LNM between different T and N stages. The metabolic parameters associated with T and N staging were identified. Results There were significant differences between all parameters relative to the primary tumor but no significant differences in any parameter relative to the LNM and T stages. Higher mean values of TGNmax, TGNmean, TSUVpeak, and TSUSmax were associated with advanced T stages. Higher mean values of all the LNM parameters were associated with more advanced N stages. Only primary tumor metabolic tumor volume (TMTV), TSUVpeak, TSULmax, and TSUSmax showed a significant positive association with T staging, while lymph node metabolic tumor volume (LNMTV) and TSUSmax were significantly positive in N staging. Conclusions Our findings suggest that metabolic parameters are useful indicators of tumor invasiveness and LNM based on the Eighth Edition manual. Compared with volume-dependent parameters, TGNmax, TGNmean, TSUVpeak, and TSUSmax may be better indicators of local tumor aggressiveness. SUSmax of the primary tumor was associated with LNM. In addition to SUVmax, other metabolic parameters (eg, SULmax, SUSmax, GNmax, and GNmean) could evaluate tumor aggressiveness and LNM better.
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Affiliation(s)
- Yun Zhang
- Department of PET/CT Center, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Yuxiao Hu
- Department of PET/CT Center, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Shuang Zhao
- Department of PET/CT Center, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Rong Huang
- Department of PET/CT Center, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
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Zhang J, Liu Y, Fan H, Wang W, Shao W, Cao G, Shi X. Prediction of Clinical Molecular Typing of Breast Invasive Ductal Carcinoma Using 18F-FDG PET/CT Dual-Phase Imaging. Acad Radiol 2023; 30 Suppl 2:S82-S92. [PMID: 36624021 DOI: 10.1016/j.acra.2022.12.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 11/18/2022] [Accepted: 12/21/2022] [Indexed: 01/09/2023]
Abstract
RATIONALE AND OBJECTIVES To investigate the diagnostic value of Fluorine-18-labeled 2-fluoro-2-deoxy-D-glucose positron emission tomography and computed tomography (18F-FDG PET/CT) dual-phase imaging for the different molecular subtypes of invasive ductal carcinoma of the breast. MATERIALS AND METHODS Clinical imaging data of 164 women with invasive ductal carcinoma of the breast confirmed by pathology who underwent 18F-FDG PET/CT dual-phase imaging were retrospectively analyzed. The maximum standard uptake values (SUVmax) of the early and delayed phases of the lesion were measured and recorded as SUVmax1 and SUVmax2, respectively, and the retention index (RI) was calculated. We analyzed the change rule of SUVmax1, SUVmax2, and RI for the different molecular subtypes and molecular marker expression groups. The diagnostic threshold of different molecular marker expression status was determined using receiver operating characteristic curve analysis. RESULTS SUVmax1 and SUVmax2 were highest in the TNBC group and lowest in the luminal A group (p<0.001). TNBC and HER2 overexpression groups had higher RI than the luminal A and B groups (p<0.001), with no significant difference between the TNBC and HER2 overexpression groups or between the luminal A and B groups (p=0.640 and 0.345, respectively). The ER- and PR-negative groups had significantly higher SUVmax1, SUVmax2, and RI than the PR-positive group (p<0.001). The HER2-positive group had higher SUVmax1 and SUVmax2 than the negative group (p<0.001). The Ki67 overexpression group had higher SUVmax1 and SUVmax2 levels than the low expression group (p<0.001). There was no significant difference in RI between HER2-positive and negative groups or between Ki67 high and low expression groups (p=0.904 and 0.216, respectively). For ER-negative and positive expression status, the maximum area under the curve (AUC) of SUVmax2 was 0.852, diagnostic threshold was 10.87, sensitivity was 79.6%, and specificity was 74.5%. For PR-negative and positive expression status, the AUC of SUVmax2 was 0.858, diagnostic threshold was 10.45, sensitivity was 83.1%, and specificity was 75.3%. For HER2-negative and positive expression status, the AUC of SUVmax1 was 0.714, diagnostic threshold was 9.28, sensitivity was 79.6%, and specificity was 60.9%. For Ki67 high- and low expression status, the AUC of SUVmax2 was 0.915 at maximum, diagnostic threshold was 10.21, sensitivity was 83.4%, and specificity was 93.9%. CONCLUSION 18F-FDG PET/CT dual-phase imaging facilitates the prediction of the expression of molecular markers and subtypes of invasive ductal carcinoma of the breast and the development of more tailored treatment plans for patients with this disease.
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Affiliation(s)
- Jiangong Zhang
- Department of Nuclear Medicine, The First people's Hospital of Yancheng, The Fourth Affiliated Hospital of Nantong University, Yancheng, Jiangsu, P.R. China
| | - Yongbo Liu
- Department of radiology, Peking University Care Lu'an Hospital, Changzhi, P.R. China
| | - Huiwen Fan
- Department of Breast surgery, The First people's Hospital of Yancheng, The Fourth Affiliated Hospital of Nantong University, Yancheng, Jiangsu, P.R. China
| | - Wei Wang
- Department of Nuclear Medicine, The First people's Hospital of Yancheng, The Fourth Affiliated Hospital of Nantong University, Yancheng, Jiangsu, P.R. China
| | - Weiwei Shao
- Department of Pathology Department, The First people's Hospital of Yancheng, The Fourth Affiliated Hospital of Nantong University, Yancheng, Jiangsu, P.R. China
| | - Gang Cao
- Department of radiology, Peking University Care Lu'an Hospital, Changzhi, P.R. China
| | - Xun Shi
- Department of Nuclear Medicine, The First people's Hospital of Yancheng, The Fourth Affiliated Hospital of Nantong University, Yancheng, Jiangsu, P.R. China.
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Zhang J, Zhang Z, Mao N, Zhang H, Gao J, Wang B, Ren J, Liu X, Zhang B, Dou T, Li W, Wang Y, Jia H. Radiomics nomogram for predicting axillary lymph node metastasis in breast cancer based on DCE-MRI: A multicenter study. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2023; 31:247-263. [PMID: 36744360 DOI: 10.3233/xst-221336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
OBJECTIVES This study aims to develop and validate a radiomics nomogram based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to noninvasively predict axillary lymph node (ALN) metastasis in breast cancer. METHODS This retrospective study included 263 patients with histologically proven invasive breast cancer and who underwent DCE-MRI examination before surgery in two hospitals. All patients had a defined ALN status based on pathological examination results. Regions of interest (ROIs) of the primary tumor and ipsilateral ALN were manually drawn. A total of 1,409 radiomics features were initially computed from each ROI. Next, the low variance threshold, SelectKBest, and least absolute shrinkage and selection operator (LASSO) algorithms were used to extract the radiomics features. The selected radiomics features were used to establish the radiomics signature of the primary tumor and ALN. A radiomics nomogram model, including the radiomics signature and the independent clinical risk factors, was then constructed. The predictive performance was evaluated by the receiver operating characteristic (ROC) curves, calibration curve, and decision curve analysis (DCA) by using the training and testing sets. RESULTS ALNM rates of the training, internal testing, and external testing sets were 43.6%, 44.3% and 32.3%, respectively. The nomogram, including clinical risk factors (tumor diameter) and radiomics signature of the primary tumor and ALN, showed good calibration and discrimination with areas under the ROC curves of 0.884, 0.822, and 0.813 in the training, internal and external testing sets, respectively. DCA also showed that radiomics nomogram displayed better clinical predictive usefulness than the clinical or radiomics signature alone. CONCLUSIONS The radiomics nomogram combined with clinical risk factors and DCE-MRI-based radiomics signature may be used to predict ALN metastasis in a noninvasive manner.
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Affiliation(s)
- Jiwen Zhang
- Department of First Clinical Medicine, Shanxi Medical University, Taiyuan, China
| | - Zhongsheng Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Haicheng Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Jing Gao
- School of Medical Imaging, Binzhou Medical University, Yantai, China
| | - Bin Wang
- Department of Breast Surgery, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Jianlin Ren
- Department of Breast Surgery, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Xin Liu
- Department of Breast Surgery, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Binyue Zhang
- Department of First Clinical Medicine, Shanxi Medical University, Taiyuan, China
| | - Tingyao Dou
- Department of First Clinical Medicine, Shanxi Medical University, Taiyuan, China
| | - Wenjuan Li
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Yanhong Wang
- Department of Microbiology and immunology, Shanxi Medical University, Taiyuan, China
| | - Hongyan Jia
- Department of Breast Surgery, First Hospital of Shanxi Medical University, Taiyuan, China
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Lee SW, Kim SJ. Is Delayed Image of 18F-FDG PET/CT Necessary for Mediastinal Lymph Node Staging in Non-Small Cell Lung Cancer Patients? Clin Nucl Med 2022; 47:414-421. [PMID: 35234195 DOI: 10.1097/rlu.0000000000004110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE The purpose of this study was to evaluate the diagnostic accuracies of dual-time-point (DTP) 18F-FDG PET/CT for detection of mediastinal lymph node (LN) metastasis in non-small cell lung cancer (NSCLC) patients through a systematic review and meta-analysis. PATIENTS AND METHODS The PubMed, Cochrane database, and EMBASE database, from the earliest available date of indexing through October 31, 2021, were searched for studies evaluating diagnostic performance of DTP 18F-FDG PET/CT for detection of metastatic mediastinal LN in NSCLC patients. We determined the sensitivities and specificities across studies, calculated positive and negative likelihood ratios (LR+ and LR-), and constructed summary receiver operating characteristic curves. RESULTS Ten studies (758 patients) were included in the current study. In patient-based analysis, early image showed a sensitivity of 0.76 and a specificity of 0.75. Delayed image revealed a sensitivity of 0.84 and a specificity of 0.71. In LN-based analysis, early image showed a sensitivity of 0.80 and a specificity of 0.83. Delayed image revealed a sensitivity of 0.84 and a specificity of 0.87. Retention index or %ΔSUVmax is superior to early or delayed images of DTP 18F-FDG PET/CT for detection of mediastinal LN metastasis. CONCLUSIONS Dual-time-point 18F-FDG PET/CT showed a good diagnostic performances for detection of metastatic mediastinal LNs in NSCLC patients. Early and delayed images of DTP 18F-FDG PET/CT revealed similar diagnostic accuracies for LN metastasis. However, retention index or %ΔSUVmax is superior to early or delayed images of DTP 18F-FDG PET/CT for detection of mediastinal LN metastasis in NSCLC patients. Further large multicenter studies would be necessary to substantiate the diagnostic accuracy of DTP 18F-FDG PET/CT for mediastinal LN staging in NSCLC patients.
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Affiliation(s)
- Sang Woo Lee
- From the Department of Nuclear Medicine, Kyungpook National University, Chilgok Hospital and School of Medicine, Daegu
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Cheng J, Li J, Liu G, Shui R, Chen S, Yang B, Shao Z. Diagnostic performance of a novel high-resolution dedicated axillary PET system in the assessment of regional nodal spread of disease in early breast cancer. Quant Imaging Med Surg 2022; 12:1109-1120. [PMID: 35111608 DOI: 10.21037/qims-21-388] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Accepted: 09/08/2021] [Indexed: 12/16/2022]
Abstract
Background In early breast cancer, a non-invasive method with higher sensitivity and negative predictive value (NPV) is needed to identify and recognize more indolent axillary lymph nodes (ALNs). This study aimed to assess whether a novel high-resolution dedicated ALN positron emission tomography (LymphPET) system could improve sensitivity in detecting early breast cancer (clinical N0-N1 stage). Methods A total of 103 patients with clinical stage T1-2N0-1M0 breast cancer were evaluated by 18F-fluorodeoxyglucose (18F-FDG) LymphPET. The maximum single-voxel PET uptake value of ALNs (maxLUV) and the tumor-to-background ratio (TBR) for fat (TBR1) and muscle (TBR2) tissue were calculated. Then, 78 patients with cN0 stage breast cancer received sentinel lymph node biopsy alone or combined with axillary lymph node dissection (ALND), and 25 patients with cN1 stage breast cancer underwent fine-needle aspiration. Results A total of 99 invasive breast carcinoma cases were included in this study. The diagnostic sensitivity of LymphPET was 88%, specificity was 79%, false-negative rate was 12%, the false-positive rate was 21%, positive predictive value was 75%, NPV was 90%, and accuracy was 83%. The maxLUV was superior to TBR1 and TBR2 in detecting ALNs, with 0.27 being the most optimal cutoff value. Conclusions The 18F-FDG LymphPET system can be used to identify and recognize more indolent ALNs of breast cancer due to greater sensitivity and a much higher NPV.
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Affiliation(s)
- Jingyi Cheng
- Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Nuclear Medicine, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
| | - Junjie Li
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Breast Surgery, Fudan University Shanghai Cancer Center.,Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Guangyu Liu
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Breast Surgery, Fudan University Shanghai Cancer Center.,Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Ruohong Shui
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Sheng Chen
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Breast Surgery, Fudan University Shanghai Cancer Center.,Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Benlong Yang
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Breast Surgery, Fudan University Shanghai Cancer Center.,Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Zhimin Shao
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Breast Surgery, Fudan University Shanghai Cancer Center.,Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
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