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Shao L, Yang X, Sun Z, Tan X, Lu Z, Hu S, Dou W, Duan S. Three-dimensional pseudo-continuous arterial spin-labelled perfusion imaging for diagnosing upper cervical lymph node metastasis in patients with nasopharyngeal carcinoma: a whole-node histogram analysis. Clin Radiol 2024; 79:e736-e743. [PMID: 38341343 DOI: 10.1016/j.crad.2024.01.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 01/11/2024] [Accepted: 01/16/2024] [Indexed: 02/12/2024]
Abstract
AIM To evaluate whole-node histogram parameters of blood flow (BF) maps derived from three-dimensional pseudo-continuous arterial spin-labelled (3D pCASL) imaging in discriminating metastatic from benign upper cervical lymph nodes (UCLNs) for nasopharyngeal carcinoma (NPC) patients. MATERIALS AND METHODS Eighty NPC patients with a total of 170 histologically confirmed UCLNs (67 benign and 103 metastatic) were included retrospectively. Pre-treatment 3D pCASL imaging was performed and whole-node histogram analysis was then applied. Histogram parameters and morphological features, such as minimum axis diameter (MinAD), maximum axis diameter (MaxAD), and location of UCLNs, were assessed and compared between benign and metastatic lesions. Predictors were identified and further applied to establish a combined model by multivariate logistic regression in predicting the probability of metastatic UCLNs. Receiver operating characteristic (ROC) curves were used to analyse the diagnostic performance. RESULTS Metastatic UCLNs had larger MinAD and MinAD/MaxAD ratio, greater energy and entropy values, and higher incidence of level II (upper jugular group), but lower BF10th value than benign nodes (all p<0.05). MinAD, BF10th, energy, and entropy were validated as independent predictors in diagnosing metastatic UCLNs. The combined model yielded an area under the curve (AUC) of 0.932, accuracy of 84.42 %, sensitivity of 80.6 %, and specificity of 90.29 %. CONCLUSIONS Whole-node histogram analysis on BF maps is a feasible tool to differentiate metastatic from benign UCLNs in NPC patients, and the combined model can further improve the diagnostic efficacy.
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Affiliation(s)
- L Shao
- Department of Radiology, Affiliated Hospital of Jiangnan University, Wuxi City, Jiangsu, China
| | - X Yang
- Department of Radiology, Affiliated Hospital of Jiangnan University, Wuxi City, Jiangsu, China
| | - Z Sun
- Department of Radiology, Affiliated Hospital of Jiangnan University, Wuxi City, Jiangsu, China.
| | - X Tan
- Department of Radiology, Affiliated Hospital of Jiangnan University, Wuxi City, Jiangsu, China
| | - Z Lu
- Department of Radiology, Affiliated Hospital of Jiangnan University, Wuxi City, Jiangsu, China
| | - S Hu
- Department of Radiology, Affiliated Hospital of Jiangnan University, Wuxi City, Jiangsu, China
| | - W Dou
- General Electric (GE) Healthcare, MR Research China, Beijing, China
| | - S Duan
- General Electric (GE) Healthcare China, Shanghai, China
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Xu Q, Song Q, Wang Y, Lin L, Tian S, Wang N, Wang J, Liu A. Amide proton transfer weighted combined with diffusion kurtosis imaging for predicting lymph node metastasis in cervical cancer. Magn Reson Imaging 2024; 106:85-90. [PMID: 38101652 DOI: 10.1016/j.mri.2023.12.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 12/07/2023] [Accepted: 12/10/2023] [Indexed: 12/17/2023]
Abstract
OBJECTIVE To investigate the value of amide proton transfer weighted (APTw) combined with diffusion kurtosis imaging (DKI) in quantitative prediction of lymph node metastasis (LNM) in cervical carcinoma (CC). METHODS Data of 19 LNM(+) and 50 LNM(-) patients with CC were retrospectively analyzed. 3.0 T MRI scan was performed before the operation, including APTw and DKI. After post-processing, quantitative magnetization transfer ratio asymmetric at 3.5 ppm [MTRasym (3.5 ppm)], mean kurtosis (MK), and mean diffusivity (MD) maps were obtained. The MTRasym(3.5 ppm), MK, and MD values were respectively measured by two observers, and intra-class correlation coefficients (ICC) were used to test the consistency of the results. The independent samples t-test or Mann-Whitney U test was used to compare the differences in the values of each parameter. The ROC curve was used to analyze the predictive performance of parameters with significant differences and their combination parameter. RESULTS The two observers had good agreement in the measurement of each data (ICC > 0.75). The MTRasym(3.5 ppm) and MK values of the LNM(+) group(3.260 ± 0.538% and 0.531 ± 0.202) were higher than those of the LNM(-) group(2.698 ± 0.597% and 0.401 ± 0.148) (P < 0.05), while there was no significant difference in MD values between the two groups(P > 0.05). The area under the curves (AUCs) of MTRasym(3.5 ppm), MK value, and MTRasym(3.5 ppm) + MK value were 0.763, 0.716, and 0.813, respectively, when predicting LNM status of CC. CONCLUSION APTw and DKI can quantitatively predict LNM status of CC, which is of importance in clinical diagnosis and treatment.
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Affiliation(s)
- Qihao Xu
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian,China
| | - Qingling Song
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian,China
| | - Yue Wang
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian,China
| | - Liangjie Lin
- Clinical and Technical Support, Philips Healthcare, Beijing, China
| | - Shifeng Tian
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian,China
| | - Nan Wang
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian,China
| | - Jiazheng Wang
- Clinical and Technical Support, Philips Healthcare, Beijing, China
| | - Ailian Liu
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian,China; Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, China.
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Qu J, Pan B, Su T, Chen Y, Zhang T, Chen X, Zhu X, Xu Z, Wang T, Zhu J, Zhang Z, Feng F, Jin Z. T1 and T2 mapping for identifying malignant lymph nodes in head and neck squamous cell carcinoma. Cancer Imaging 2023; 23:125. [PMID: 38105217 PMCID: PMC10726506 DOI: 10.1186/s40644-023-00648-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 12/04/2023] [Indexed: 12/19/2023] Open
Abstract
BACKGROUND This study seeks to assess the utility of T1 and T2 mapping in distinguishing metastatic lymph nodes from reactive lymphadenopathy in patients with head and neck squamous cell carcinoma (HNSCC), using diffusion-weighted imaging (DWI) as a comparison. METHODS Between July 2017 and November 2019, 46 HNSCC patients underwent neck MRI inclusive of T1 and T2 mapping and DWI. Quantitative measurements derived from preoperative T1 and T2 mapping and DWI of metastatic and non-metastatic lymph nodes were compared using independent samples t-test or Mann-Whitney U test. Receiver operating characteristic curves and the DeLong test were employed to determine the most effective diagnostic methodology. RESULTS We examined a total of 122 lymph nodes, 45 (36.9%) of which were metastatic proven by pathology. Mean T2 values for metastatic lymph nodes were significantly lower than those for benign lymph nodes (p < 0.001). Conversely, metastatic lymph nodes exhibited significantly higher apparent diffusion coefficient (ADC) and standard deviation of T1 values (T1SD) (p < 0.001). T2 generated a significantly higher area under the curve (AUC) of 0.890 (0.826-0.954) compared to T1SD (0.711 [0.613-0.809]) and ADC (0.660 [0.562-0.758]) (p = 0.007 and p < 0.001). Combining T2, T1SD, ADC, and lymph node size achieved an AUC of 0.929 (0.875-0.983), which did not significantly enhance diagnostic performance over using T2 alone (p = 0.089). CONCLUSIONS The application of T1 and T2 mapping is feasible in differentiating metastatic from non-metastatic lymph nodes in HNSCC and can improve diagnostic efficacy compared to DWI.
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Affiliation(s)
- Jiangming Qu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Boju Pan
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Tong Su
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Yu Chen
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
| | - Tao Zhang
- Department of Stomatology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Xingming Chen
- Department of Otolaryngology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Xiaoli Zhu
- Department of Otolaryngology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Zhentan Xu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Tianjiao Wang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Jinxia Zhu
- MR Research Collaboration, Siemens Healthineers Ltd, Beijing, China
| | - Zhuhua Zhang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
| | - Feng Feng
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Zhengyu Jin
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
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Baba A, Kurokawa R, Kurokawa M, Rivera-de Choudens R, Srinivasan A. Performance of axial diameter on MR imaging for identification of retropharyngeal lymph node metastases in head and neck cancer: a systematic review and meta-analysis. Neuroradiology 2023; 65:1363-1369. [PMID: 37522935 DOI: 10.1007/s00234-023-03205-x] [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: 05/15/2023] [Accepted: 07/25/2023] [Indexed: 08/01/2023]
Abstract
PURPOSE To summarize previous studies' data and to calculate the diagnostic performance of minimum axial diameter (MIAD) and maximum axial diameter (MAAD) on each of the cutoff values in retropharyngeal lymph node (RPLNs) metastases in head and neck cancer. METHODS MEDLINE, Scopus, and Embase databases were searched for systematic review. Meta-analysis was performed to summarize estimates of sensitivity, specificity, and diagnostic odds ratio (DOR) and generate summary recipient operator characteristic (sROC). RESULTS The review identified 5 studies with a total of 634 patients (971 lesions) that were eligible for the meta-analysis. The estimated sensitivity, specificity, and DOR at MIAD 5 mm cutoff and MIAD 6 mm cutoff were 89.8% and 74.3%, 82.7% and 92.7%, and 39.1 and 57.9, respectively. The estimated sensitivity, specificity, and DOR at MAAD 7 mm cutoff and MAAD 8 mm cutoff were 90.3% and 84.7%, 62.7% and 79.9%, and 17.8 and 21.7, respectively. The AUCs of sROC at MIAD 5 mm cutoff and MIAD 6 mm cutoff were 0.922 and 0.943. At MAAD 7 mm and MAAD 8 mm, they were 0.840 and 0.888. CONCLUSION The diagnostic performance of the MIAD 6 mm cutoff in RPLN metastases from head and neck cancer was 2% higher than the MIAD 5 mm cutoff. The diagnostic performance of MIAD was higher than that of MAAD.
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Affiliation(s)
- Akira Baba
- Division of Neuroradiology, Department of Radiology, University of Michigan, 1500 E. Medical Center Dr., Ann Arbor, MI, 48109, USA.
- Department of Radiology, The Jikei University School of Medicine, 3-25-8 Nishi-Shimbashi, Minato-ku, Tokyo, 105-8461, Japan.
| | - Ryo Kurokawa
- Division of Neuroradiology, Department of Radiology, University of Michigan, 1500 E. Medical Center Dr., Ann Arbor, MI, 48109, USA
- Department of Radiology, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Mariko Kurokawa
- Division of Neuroradiology, Department of Radiology, University of Michigan, 1500 E. Medical Center Dr., Ann Arbor, MI, 48109, USA
- Department of Radiology, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Roberto Rivera-de Choudens
- Division of Neuroradiology, Department of Radiology, University of Michigan, 1500 E. Medical Center Dr., Ann Arbor, MI, 48109, USA
| | - Ashok Srinivasan
- Division of Neuroradiology, Department of Radiology, University of Michigan, 1500 E. Medical Center Dr., Ann Arbor, MI, 48109, USA
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