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Zhu G, Wang JA, Xiao D, Guo X, Huang Y, Guo L, Li M, Wu H, Zhang Y, Wang Y. Spectral CT for preoperative diagnosis of N2 station lymph node metastasis in solid T1 non-small cell lung cancer. Eur J Radiol 2024; 177:111553. [PMID: 38878500 DOI: 10.1016/j.ejrad.2024.111553] [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: 10/10/2023] [Revised: 02/29/2024] [Accepted: 06/04/2024] [Indexed: 07/24/2024]
Abstract
PURPOSE To evaluate the diagnostic value of spectral CT for the preoperative diagnosis of N2 station lymph nodes metastasis in solid T1 non-small cell lung cancer (NSCLC). METHOD For this retrospective study, dual-phase contrast agent-enhanced CT was performed in patients with NSCLC from September 2019 to June 2023. Quantitative spectral CT parameters measurements were performed by 2 radiologists independently. Logistic regression analysis and Delong test were performed. RESULTS 60 NSCLC patients (mean age, 62.85 years ± 8.49, 44men) were evaluated. A total of 121 lymph nodes (38 with metastasis) were enrolled. There was no significant difference in the slope of the spectral Hounsfield unit curve (λHu) on arterial phase (AP) or venous phase (VP) between primary lesions and metastatic lymph nodes (P > 0.05), but significant difference in VP λHu between primary lesions and non-metastatic lymph nodes (P < 0.001). The CT40KeV, λHu, normalized iodine concentration (nIC), normalized effective atomic number (nZeff) measured during both AP and VP were lower in metastatic lymph nodes than in non-metastatic lymph nodes (all P < 0.05). Short-axis diameter (S) of metastatic lymph nodes was higher than non-metastatic lymph nodes (P < 0.001). Area under the curve (AUC) for S performed the highest (0.788) in diagnosing metastatic lymph nodes. When combined with VP λHu, VP nZeff, AUC increased to 0.871. CONCLUSION Spectral CT is a complementary means for the preoperative diagnosis of N2 station lymph nodes metastasis in solid T1 NSCLC. The combined parameters have higher diagnostic efficiency.
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Affiliation(s)
- Guanbin Zhu
- Department of Radiology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Jin-An Wang
- Department of Radiology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Dongjian Xiao
- Department of Radiology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Xiaoxi Guo
- Department of Radiology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Yimin Huang
- Department of Radiology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Luxin Guo
- Department of Radiology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Minjie Li
- Department of Thoracic Surgery, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Huita Wu
- Department of Oncology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Yongjun Zhang
- Department of Pathology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Yong Wang
- Department of Radiology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
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Ren X, Song Z, Zhang D, Li X, Huang J, Liu Q, Wen Y, Zhang J, Zeng D, Tang Z. Differentiation of benign and malignant lesions in Bethesda III and IV thyroid nodules via dual-energy computed tomography quantitative parameters and morphologic features. Quant Imaging Med Surg 2024; 14:4567-4578. [PMID: 39022257 PMCID: PMC11250302 DOI: 10.21037/qims-23-1511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 05/14/2024] [Indexed: 07/20/2024]
Abstract
Background Thyroid nodules (TNs) cytologically defined as category Bethesda III and IV pose a major diagnostic challenge before surgery, demanding new methods to reduce unnecessary diagnostic thyroid lobectomies for patients with benign TNs. This study aimed to assess whether a model combining dual-energy computed tomography (DECT) quantitative parameters with morphologic features could reliably differentiate between benign and malignant lesions in Bethesda III and IV TNs. Methods Data from 77 patients scheduled for thyroid surgery for Bethesda III and IV TNs (malignant =48; benign =29) who underwent DECT scans were reviewed. DECT quantitative parameters including normalized iodine concentration (NIC), attenuation on the slope of spectral Hounsfield unit (HU) curve, and normalized effective atomic number (Zeff) were measured in the arterial phase (AP) and venous phase (VP). DECT quantitative parameters and morphologic features were compared between the malignant and benign cohorts. The receiver operating characteristic curve was performed to compare the performances of significant DECT quantitative parameters, morphologic features, or the models combining the DECT parameters, respectively, with morphologic features. A nomogram was constructed from the optimal performance model, and the performance was evaluated via the calibration curve and decision curve analysis. Results The areas under the receiver operating characteristic curve with 95% confidence interval (CI) of the NIC in the AP (AP-NIC), slope of spectral HU curve in the AP, and NZeff in the AP were 0.749 (95% CI: 0.641-0.857), 0.654 (95% CI: 0.530-0.778), and 0.722 (95% CI: 0.602-0.842), respectively. The model combining AP-NIC with enhanced blurring showed the highest diagnostic performance, with an area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of 0.808, 0.854, and 0.655, respectively; it was then used to construct a nomogram. The calibration curve showed that the discrepancy between the prediction of the nomogram and actual observations was less than 5%. The decision curve analysis indicated the nomogram had a positive net benefit in threshold risk ranges of 14% to 58% or 60% to 91% for malignant Bethesda III and IV TNs. Conclusions The model combining AP-NIC with enhanced blurring could reliably differentiate between benign and malignant lesions in Bethesda III and IV TNs.
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Affiliation(s)
- Xiaofang Ren
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Zuhua Song
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Dan Zhang
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Xiaojiao Li
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Jie Huang
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Qian Liu
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Youjia Wen
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Jiayan Zhang
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Dan Zeng
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Zhuoyue Tang
- Department of Radiology, Chongqing General Hospital, Chongqing, China
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Jeong J, Ham S, Shim E, Kim BH, Kang WY, Kang CH, Ahn KS, Lee KC, Choi H. Electron density dual-energy CT can improve the detection of lumbar disc herniation with higher image quality than standard and virtual non-calcium images. Eur Radiol 2024:10.1007/s00330-024-10782-9. [PMID: 38755438 DOI: 10.1007/s00330-024-10782-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 03/07/2024] [Accepted: 03/30/2024] [Indexed: 05/18/2024]
Abstract
OBJECTIVES To compare the diagnostic performance and image quality of dual-energy computed tomography (DECT) with electron density (ED) image reconstruction with those of DECT with standard CT (SC) and virtual non-calcium (VNCa) image reconstructions, for diagnosing lumbar disc herniation (L-HIVD). METHODS A total of 59 patients (354 intervertebral discs from T12/L1 to L5/S1; mean age, 60 years; 30 women and 29 men) who underwent DECT with spectral reconstruction and 3-T MRI within 2 weeks were enrolled between March 2021 and February 2022. Four radiologists independently assessed three image sets of randomized ED, SC, and VNCa images to detect L-HIVD at 8-week intervals. The coefficient of variance (CV) and the Weber contrast of the ROIs in the normal and diseased disc to cerebrospinal fluid space (NCR-normal/-diseased, respectively) were calculated to compare the image qualities of the noiseless ED and other series. RESULTS Overall, 129 L-HIVDs were noted on MRI. In the detection of L-HIVD, ED showed a higher AUC and sensitivity than SC and VNCa; 0.871 vs 0.807 vs 833 (p = 0.002) and 81% vs 70% vs 74% (p = 0.006 for SC), respectively. CV was much lower in all measurements of ED than those for SC and VNCa (p < 0.001). Furthermore, NCR-normal and NCR-diseased were the highest in ED (ED vs SC in NCR-normal and NCR-diseased, p = 0.001 and p = 0.004, respectively; ED vs VNCa in NCR-diseased, p = 0.044). CONCLUSION Compared to SC and VNCa images, DECT with ED reconstruction can enhance the AUC and sensitivity of L-HIVD detection with a lower CV and higher NCR. CLINICAL RELEVANCE STATEMENT To our knowledge, this is the first study to quantify the image quality of noiseless ED images. ED imaging may be helpful for detecting L-HIVD in patients who cannot undergo MRI. KEY POINTS ED images have diagnostic potential, but relevant quantitative analyses of image quality are limited. ED images detect disc herniation, with a better coefficient of variance and normalized contrast ratio values. ED images could detect L-HIVD when MRI is not an option.
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Affiliation(s)
- Juhyun Jeong
- Department of Radiology, Korea University Ansan Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Sungwon Ham
- Healthcare Readiness Institute for Unified Korea, Korea University Ansan Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Euddeum Shim
- Department of Radiology, Korea University Ansan Hospital, Korea University College of Medicine, Seoul, South Korea.
| | - Baek Hyun Kim
- Department of Radiology, Korea University Ansan Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Woo Young Kang
- Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Chang Ho Kang
- Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Kyung-Sik Ahn
- Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Kyu-Chong Lee
- Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Hangseok Choi
- Medical Science Research Center, Korea University College of Medicine, Seoul, South Korea
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Wang Y, Hu H, Ban X, Jiang Y, Su Y, Yang L, Shi G, Yang L, Han R, Duan X. Evaluation of Quantitative Dual-Energy Computed Tomography Parameters for Differentiation of Parotid Gland Tumors. Acad Radiol 2024; 31:2027-2038. [PMID: 37730491 DOI: 10.1016/j.acra.2023.08.024] [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: 06/27/2023] [Revised: 08/15/2023] [Accepted: 08/19/2023] [Indexed: 09/22/2023]
Abstract
RATIONALE AND OBJECTIVES To assess the diagnostic performance of quantitative parameters from dual-energy CT (DECT) in differentiating parotid gland tumors (PGTs). MATERIALS AND METHODS 101 patients with 108 pathologically proved PGTs were enrolled and classified into four groups: pleomorphic adenomas (PAs), warthin tumors (WTs), other benign tumors (OBTs), and malignant tumors (MTs). Conventional CT attenuation and DECT quantitative parameters, including iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number (Zeff), electron density (Rho), double energy index (DEI), and the slope of the spectral Hounsfield unit curve (λHU), were obtained and compared between benign tumors (BTs) and MTs, and further compared among the four subgroups. Logistic regression analysis was used to assess the independent parameters and the receiver operating characteristic (ROC) curves were used to analyze the diagnostic performance. RESULTS Attenuation, Zeff, DEI, IC, NIC, and λHU in the arterial phase (AP) and venous phase (VP) were higher in MTs than in BTs (p < 0.001-0.047). λHU in VP and Zeff in AP were independent predictors with an area under the curve (AUC) of 0.84 after the combination. Furthermore, attenuation, Zeff, DEI, IC, NIC, and λHU in the AP and VP of MTs were higher than those of PAs (p < 0.001-0.047). Zeff and NIC in AP and λHU in VP were independent predictors with an AUC of 0.93 after the combination. Attenuation and Rho in the precontrast phase; attenuation, Rho, Zeff, DEI, IC, NIC, and λHU in AP; and the Rho in the VP of PAs were lower than those of WTs (p < 0.001-0.03). Rho in the precontrast phase and attenuation in AP were independent predictors with an AUC of 0.89 after the combination. MTs demonstrated higher Zeff, DEI, IC, NIC, and λHU in VP and lower Rho in the precontrast phase compared with WTs (p < 0.001-0.04); but no independent predictors were found. CONCLUSION DECT quantitative parameters can help to differentiate PGTs.
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Affiliation(s)
- Yu Wang
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.)
| | - Huijun Hu
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.)
| | - Xiaohua Ban
- Department of Radiology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou 510060, Guangdong, China (X.B.)
| | - Yusong Jiang
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.)
| | - Yun Su
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.)
| | - Lingjie Yang
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.)
| | - Guangzi Shi
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.); Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, Guangdong, China (G.S., X.D.)
| | - Lu Yang
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.)
| | - Riyu Han
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.)
| | - Xiaohui Duan
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.); Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, Guangdong, China (G.S., X.D.).
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Zhang W, Liu J, Jin W, Li R, Xie X, Zhao W, Xia S, Han D. Radiomics from dual-energy CT-derived iodine maps predict lymph node metastasis in head and neck squamous cell carcinoma. LA RADIOLOGIA MEDICA 2024; 129:252-267. [PMID: 38015363 DOI: 10.1007/s11547-023-01750-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Accepted: 10/27/2023] [Indexed: 11/29/2023]
Abstract
OBJECTIVE To develop and validate an iodine maps-based radiomics nomogram for preoperatively predicting cervical lymph node metastasis (LNM) in head and neck squamous cell carcinoma (HNSCC). MATERIALS AND METHODS A total of 278 patients who pathologically confirmed as HNSCC were retrospectively recruited from two medical centers between June 2012 and July 2022. The training set (n = 152) and internal set (n = 67) were randomly selected from medical center A, and the patients from medical center B were enrolled as the external set (n = 69). The minority group in the training set was balanced by the adaptive synthetic sampling (ADASYN) approach. Radiomics features were extracted from dual-energy CT-derived iodine maps at arterial phase (AP) and venous phase (VP), respectively. Three radiomics signatures were constructed to predict the LNM by using a random forest algorithm. The independent clinical predictors for LNM were identified by multivariate analysis and combined with radiomics signatures to establish a radiomic-clinical nomogram. The performance of radiomic-clinical nomogram was evaluated with respect to its discrimination and clinical usefulness. RESULTS The AP-VP-incorporated radiomics model exhibited a great predictive performance for LNM prediction with an area under curve (AUC) of 0.885 (95% CI, 0.836-0.933) in ADASYN-training set and confirmed in all validation sets. The nomogram that incorporated AP-VP radiomics signatures, CT-reported LN status, and histological grades yielded AUCs of 0.920 (95% CI, 0.881-0.959) in ADASYN-training set, 0.858 (95% CI, 0.771-0.944) in internal validation, and 0.849 (95% CI, 0.752-0.946) in external validation, with good calibration in all cohorts (p > 0.05). Decision curve analyses indicated the nomogram was clinically useful. In addition, the predictive performance of clinical-radiomics nomogram was also validation in combing cohorts. Stratified analysis confirmed the stability of nomogram, particularly in group negative for CT-reported LNM. CONCLUSION Clinical-radiomics nomogram based on iodine maps exhibited promising performance in predicting LNM and providing valuable information for making individualized therapy decisions.
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Affiliation(s)
- Weiyuan Zhang
- Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Jin Liu
- Center of PET/CT, 920th Hospital of Joint Logistics Support Force, PLA, Kunming, 650032, China
| | - Wenfeng Jin
- Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Ruihong Li
- Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Xiaojie Xie
- Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Wen Zhao
- Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Shuang Xia
- Department of Radiology, The First Central Clinical School, Tianjin Medical University, Tianjin, 300192, China
| | - Dan Han
- Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China.
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Geng D, Zhou Y, Shang T, Su GY, Lin SS, Si Y, Wu FY, Xu XQ. Effect of Hashimoto's thyroiditis on the dual-energy CT quantitative parameters and performance in diagnosing metastatic cervical lymph nodes in patients with papillary thyroid cancer. Cancer Imaging 2024; 24:10. [PMID: 38238870 PMCID: PMC10797959 DOI: 10.1186/s40644-024-00655-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 01/03/2024] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND To evaluate the effect of Hashimoto's thyroiditis (HT) on dual-energy computed tomography (DECT) quantitative parameters of cervical lymph nodes (LNs) in patients with papillary thyroid cancer (PTC), and its effect on the diagnostic performance and threshold of DECT in preoperatively identifying metastatic cervical LNs. METHODS A total of 479 LNs from 233 PTC patients were classified into four groups: HT+/LN+, HT+/LN-, HT-/LN + and HT-/LN - group. DECT quantitative parameters including iodine concentration (IC), normalized IC (NIC), effective atomic number (Zeff), and slope of the spectral Hounsfield unit curve (λHU) in the arterial phase (AP) and venous phase were compared. Receiver operating characteristic curve analyses were performed to evaluate DECT parameters' diagnostic performance in differentiating metastatic from nonmetastatic LNs in the HT - and HT + groups. RESULTS The HT+/LN + group exhibited lower values of DECT parameters than the HT-/LN + group (all p < 0.05). Conversely, the HT+/LN - group exhibited higher values of DECT parameters than the HT-/LN - group (all p < 0.05). In the HT + group, if an AP-IC of 1.850 mg/mL was used as the threshold value, then the optimal diagnostic performance (area under the curve, 0.757; sensitivity, 69.4%; specificity, 71.0%) could be obtained. The optimal threshold value of AP-IC in the HT - group was 2.050 mg/mL. In contrast, in the HT - group, AP-NIC demonstrated the highest area under the curve of 0.988, when an optimal threshold of 0.243 was used. The optimal threshold value of AP-NIC was 0.188 in the HT + group. CONCLUSIONS HT affected DECT quantitative parameters of LNs and subsequent the diagnostic thresholds. When using DECT to diagnose metastatic LNs in patients with PTC, whether HT is coexistent should be clarified considering the different diagnostic thresholds.
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Affiliation(s)
- Di Geng
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, PR China
| | - Yan Zhou
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, PR China
| | - Ting Shang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, PR China
- Department of Radiology, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine of Nanjing University of Chinese Medicine, Nanjing, China
| | - Guo-Yi Su
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, PR China
| | | | - Yan Si
- Department of Thyroid Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Fei-Yun Wu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, PR China.
| | - Xiao-Quan Xu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, PR China.
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Eida S, Fukuda M, Katayama I, Takagi Y, Sasaki M, Mori H, Kawakami M, Nishino T, Ariji Y, Sumi M. Metastatic Lymph Node Detection on Ultrasound Images Using YOLOv7 in Patients with Head and Neck Squamous Cell Carcinoma. Cancers (Basel) 2024; 16:274. [PMID: 38254765 PMCID: PMC10813890 DOI: 10.3390/cancers16020274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 12/28/2023] [Accepted: 01/04/2024] [Indexed: 01/24/2024] Open
Abstract
Ultrasonography is the preferred modality for detailed evaluation of enlarged lymph nodes (LNs) identified on computed tomography and/or magnetic resonance imaging, owing to its high spatial resolution. However, the diagnostic performance of ultrasonography depends on the examiner's expertise. To support the ultrasonographic diagnosis, we developed YOLOv7-based deep learning models for metastatic LN detection on ultrasonography and compared their detection performance with that of highly experienced radiologists and less experienced residents. We enrolled 462 B- and D-mode ultrasound images of 261 metastatic and 279 non-metastatic histopathologically confirmed LNs from 126 patients with head and neck squamous cell carcinoma. The YOLOv7-based B- and D-mode models were optimized using B- and D-mode training and validation images and their detection performance for metastatic LNs was evaluated using B- and D-mode testing images, respectively. The D-mode model's performance was comparable to that of radiologists and superior to that of residents' reading of D-mode images, whereas the B-mode model's performance was higher than that of residents but lower than that of radiologists on B-mode images. Thus, YOLOv7-based B- and D-mode models can assist less experienced residents in ultrasonographic diagnoses. The D-mode model could raise the diagnostic performance of residents to the same level as experienced radiologists.
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Affiliation(s)
- Sato Eida
- Department of Radiology and Biomedical Informatics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan; (S.E.); (I.K.); (Y.T.); (M.S.); (H.M.); (M.K.); (T.N.)
| | - Motoki Fukuda
- Department of Oral Radiology, Osaka Dental University, 1-5-17 Otemae, Chuo-ku, Osaka 540-0008, Japan; (M.F.); (Y.A.)
| | - Ikuo Katayama
- Department of Radiology and Biomedical Informatics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan; (S.E.); (I.K.); (Y.T.); (M.S.); (H.M.); (M.K.); (T.N.)
| | - Yukinori Takagi
- Department of Radiology and Biomedical Informatics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan; (S.E.); (I.K.); (Y.T.); (M.S.); (H.M.); (M.K.); (T.N.)
| | - Miho Sasaki
- Department of Radiology and Biomedical Informatics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan; (S.E.); (I.K.); (Y.T.); (M.S.); (H.M.); (M.K.); (T.N.)
| | - Hiroki Mori
- Department of Radiology and Biomedical Informatics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan; (S.E.); (I.K.); (Y.T.); (M.S.); (H.M.); (M.K.); (T.N.)
| | - Maki Kawakami
- Department of Radiology and Biomedical Informatics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan; (S.E.); (I.K.); (Y.T.); (M.S.); (H.M.); (M.K.); (T.N.)
| | - Tatsuyoshi Nishino
- Department of Radiology and Biomedical Informatics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan; (S.E.); (I.K.); (Y.T.); (M.S.); (H.M.); (M.K.); (T.N.)
| | - Yoshiko Ariji
- Department of Oral Radiology, Osaka Dental University, 1-5-17 Otemae, Chuo-ku, Osaka 540-0008, Japan; (M.F.); (Y.A.)
| | - Misa Sumi
- Department of Radiology and Biomedical Informatics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan; (S.E.); (I.K.); (Y.T.); (M.S.); (H.M.); (M.K.); (T.N.)
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Chen JF, Yang J, Chen WJ, Wei X, Yu XL, Huang DD, Deng H, Luo YD, Liu XJ. Mono+ algorithm assessment of the diagnostic value of dual-energy CT for high-risk factors for colorectal cancer: a preliminary study. Quant Imaging Med Surg 2024; 14:432-446. [PMID: 38223051 PMCID: PMC10784106 DOI: 10.21037/qims-23-291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 10/24/2023] [Indexed: 01/16/2024]
Abstract
Background Risk factors for colorectal cancer (CRC) affect the way patients are subsequently treated and their prognosis. Dual-energy computerized tomography (DECT) is an advanced imaging technique that enables the quantitative evaluation of lesions. This study aimed to evaluate the quality of DECT images based on the Mono+ algorithm in CRC, and based on this, to assess the value of DECT in the diagnosis of CRC risk factors. Methods This prospective study was performed from 2021 to 2023. A dual-phase DECT protocol was established for consecutive patients with primary CRC. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), overall image quality, lesion delineation, and image noise of the dual-phase DECT images were assessed. Next, the optimal energy-level image was selected to analyze the iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number, electron density, dual-energy index (DEI), and slope of the energy spectrum curve within the tumor for the high- and low-risk CRC groups. A multifactor binary logistic regression analysis was used to construct a differential diagnostic regression model for high- and low-risk CRC, receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated to assess the diagnostic value of the model. Results A total of 74 patients were enrolled in this study, of whom 41 had high-risk factors and 33 had low-risk factors. The SNR and CNR were best at 40 keV virtual monoenergetic imaging (VMI) based on the Mono+ algorithm (VMI+) (SNR 8.79±1.27, P<0.001; CNR 14.89±1.77, P=0.027). The overall image quality and lesion contours were best at 60 keV VMI+ and 40 keV VMI+, respectively (P=0.001). Among all the DECT parameters, the arterial phase (AP)-IC, NIC, DEI, energy spectrum curve, and venous phase-NIC differed significantly between the two groups. The AP-IC was the optimal DECT parameter for predicting high- and low-risk CRC with AUC, sensitivity, specificity, and cut-off values of 0.96, 97.06%, 87.80%, and 2.94, respectively, and the 95% confidence interval (CI) of the AUC was 0.88-0.99. Integrating the clinical factors and DECT parameters, the AUC, sensitivity, specificity, and predictive accuracy of the model were 0.99, 100.00%, 92.68%, and 94.67%, respectively, and the 95% CI of the AUC was 0.93-1.00. Conclusions The DECT parameters based on 40 keV noise-optimized VMI+ reconstruction images depicted the CRC tumors best, and the clinical DECT model may have significant implications for the preoperative prediction of high-risk factors in CRC patients.
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Affiliation(s)
| | | | - Wei-Juan Chen
- Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xin Wei
- Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiang-Ling Yu
- Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Dou-Dou Huang
- Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Hao Deng
- Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
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Xie X, Yan H, Liu K, Guan W, Luo K, Ma Y, Xu Y, Zhu Y, Wang M, Shen W. Value of dual-layer spectral detector CT in predicting lymph node metastasis of non-small cell lung cancer. Quant Imaging Med Surg 2024; 14:749-764. [PMID: 38223109 PMCID: PMC10784007 DOI: 10.21037/qims-23-447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 11/13/2023] [Indexed: 01/16/2024]
Abstract
Background The accurate assessment of lymph node metastasis (LNM) is crucial for the staging, treatment, and prognosis of lung cancer. In this study, we explored the potential value of dual-layer spectral detector computed tomography (SDCT) quantitative parameters in the prediction of LNM in non-small cell lung cancer (NSCLC). Methods In total, 91 patients presenting with solid solitary pulmonary nodules (8 mm < diameter ≤30 mm) with pathologically confirmed NSCLC (57 without LNM, and 34 with LNM) were enrolled in the study. The patients' basic clinical data and the SDCT morphological features were analyzed using the chi-square test or Fisher's exact test. The Mann-Whitney U-test and independent sample t-test were used to analyze the differences in multiple SDCT quantitative parameters between the non-LNM and LNM groups. The diagnostic efficacy of the corresponding parameters in predicting LNM in NSCLC was evaluated by plotting the receiver operating characteristic (ROC) curves. A multivariate logistic regression analysis was conducted to determine the independent predictive factors of LNM in NSCLC. Interobserver agreement was assessed using intraclass correlation coefficients (ICCs) and Bland-Altman plots. Results There were no significant differences between the non-LNM and LNM groups in terms of age, sex, and smoking history. Lesion size and vascular convergence sign differed significantly between the two groups (P<0.05), but there were no significant differences in the six tumor markers. The SDCT quantitative parameters [SAR40keV, SAR70keV, Δ40keV, Δ70keV, CER40keV, CER70keV, NEF40keV, NEF70keV, λ, normalized iodine concentration (NIC) and NZeff] were significantly higher in the non-LNM group than the LNM group (P<0.05). The ROC analysis showed that CER40keV, NIC, and CER70keV had higher diagnostic efficacy than other quantitative parameters in predicting LNM [areas under the curve (AUCs) =0.794, 0.791, and 0.783, respectively]. The multivariate logistic regression analysis showed that size, λ, and NIC were independent predictive factors of LNM. The combination of size, λ, and NIC had the highest diagnostic efficacy (AUC =0.892). The interobserver repeatability of the SDCT quantitative and derived quantitative parameters in the study was good (ICC: 0.801-0.935). Conclusions The SDCT quantitative parameters combined with the clinical data have potential value in predicting LNM in NSCLC. The size + λ + NIC combined parameter model could further improve the prediction efficacy of LNM.
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Affiliation(s)
- Xiaodong Xie
- Department of Radiology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China
| | - Hongwei Yan
- Department of Radiology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China
| | - Kaifang Liu
- Department of Radiology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China
| | - Weizheng Guan
- School of Medical Imaging, Bengbu Medical College, Bengbu, China
| | - Kai Luo
- Department of Radiology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China
| | - Yikun Ma
- Department of Radiology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China
| | - Youtao Xu
- Department of Thoracic Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China
| | - Yinsu Zhu
- Department of Radiology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China
| | - Meiqin Wang
- Department of Radiology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China
| | - Wenrong Shen
- Department of Radiology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China
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Baba A, Kurokawa R, Kurokawa M, Rivera-de Choudens R, Srinivasan A. Dual-energy computed tomography for improved visualization of internal jugular chain neck lymph node metastasis and nodal necrosis in head and neck squamous cell carcinoma. Jpn J Radiol 2023; 41:1351-1358. [PMID: 37347457 PMCID: PMC10687157 DOI: 10.1007/s11604-023-01460-9] [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: 01/04/2023] [Accepted: 06/09/2023] [Indexed: 06/23/2023]
Abstract
PURPOSE To evaluate and compare the utility of 40-keV virtual monochromatic imaging (VMI) reconstructed from dual-energy computed tomography (DECT) in the assessment of neck lymph node metastasis with 70-keV VMI, which is reportedly equivalent to conventional 120-kVp single-energy computed tomography. MATERIALS AND METHODS Patients with head and neck squamous cell carcinoma who had neck lymph node metastasis in contact with the sternocleidomastoid muscle (SCM) and underwent contrast-enhanced DECT were included. In 40- and 70-keV VMI, contrast differences and contrast noise ratio (CNR) between the solid component of neck lymph node metastasis (SC) and the SCM and between SC and nodal necrosis (NN) were calculated. Two board-certified radiologists independently and qualitatively evaluated the boundary discrimination between SC and SCM and the diagnostic certainty of NN. RESULTS We evaluated 45 neck lymph node metastases. The contrast difference between SC and SCM and SC and NN were significantly higher at 40-keV VMI than at 70-keV VMI (p < 0.001). The CNR between SC and SCM was significantly higher at 40-keV VMI than at 70-keV VMI (p < 0.001). Scoring of the boundary discrimination between SC and SCM as well as the diagnostic certainty of NN at 40-keV VMI was significantly higher than that at 70-keV VMI (p < 0.001). The inter-rater agreements for these scores were higher at 40-keV VMI than at 70-keV VMI. CONCLUSION Additional employing 40-keV VMI in routine clinical practice may be useful in the diagnosis of head and neck lymph node metastases and nodal necrosis.
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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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Jarunnarumol N, Kamalian S, Lev MH, Gupta R. Neuroradiology Applications of Dual and Multi-energy Computed Tomography. Radiol Clin North Am 2023; 61:973-985. [PMID: 37758364 DOI: 10.1016/j.rcl.2023.05.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
Computed tomography (CT) imaging has become an essential diagnostic tool for most emergent clinical conditions, owing to its speed, accuracy, cost, and few contraindications, compared with MR imaging cross-sectional imaging. Spectral CT, which includes dual, multienergy, and photon-counting CT, is superior to conventional single-energy CT (SECT) in many respects. Spectral information enables differentiation between materials with similar Hounsfield Unit attenuations on SECT; examples include but are not limited to "virtual noncontrast," "virtual noncalcium," and most notably for neuro applications, "hemorrhage versus iodine." This article expands on the many possible benefits of spectral CT in neuroimaging.
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Affiliation(s)
- Natthawut Jarunnarumol
- Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
| | - Shahmir Kamalian
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Michael H Lev
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Rajiv Gupta
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
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Wang T, Fan Z, Zou L, Hou Y. Can quantitative parameters of spectral computed tomography predict lymphatic metastasis in lung cancer? A systematic review and meta-analysis. Radiother Oncol 2023; 183:109643. [PMID: 36990392 DOI: 10.1016/j.radonc.2023.109643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 03/01/2023] [Accepted: 03/20/2023] [Indexed: 03/30/2023]
Abstract
BACKGROUND AND PURPOSE This study evaluated the use of quantitative spectral computed tomography (CT) parameters to identify lymph node metastasis (LM) in lung cancer. MATERIALS AND METHODS Literature about LM in lung cancer diagnosed using spectral CT up to September 2022 was retrieved from the PubMed, EMBASE, Cochrane Library, Web of Science, Chinese National Knowledge Infrastructure, and Wanfang databases. The literature was strictly screened according to the inclusion and exclusion criteria. Data were extracted, quality assessment was performed, and heterogeneity was evaluated. The pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (+LR), -LR, and diagnostic odds ratio (DOR) for normalized iodine concentration (NIC) and spectral attenuation curve (λHU) were calculated. The subject receiver operating characteristic (SROC) curves were used, and the area under the curve (AUC) was calculated. RESULTS Eleven studies, including 1,290 cases, without obvious publication bias were enrolled. In eight articles, the pooled AUC of NIC in the arterial phase (AP) was 0.84 (SEN=0.85, SPE=0.74, +LR=3.3, -LR=0.20, DOR=16) while that of NIC in the venous phase (VP) was 0.82 (SEN=0.78, SPE=0.72). Additionally, the pooled AUC for λHU (AP) was 0.87 (SEN=0.74, SPE=0.84, +LR=4.5, -LR=0.31, DOR=15) and that for λHU (VP) was 0.81 (SEN=0.62, SPE=0.81). Lymph node (LN) short-axis diameter was ranked last, with a pooled AUC of 0.81 (SEN=0.69, SPE=0.79). CONCLUSION Spectral CT is a suitable noninvasive and cost-effective method for determining LM in lung cancer. Additionally, NIC and λHU in the AP have good discrimination ability than short-axis diameter, providing a valuable basis and reference for preoperative evaluation. (registration number INPLASY202290096).
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Affiliation(s)
- Tong Wang
- Department of Radiology, Shengjing Hospital of China Medical University, China
| | - Zheng Fan
- Department of Orthopedics, Shengjing Hospital of China Medical University, China
| | - Lue Zou
- Department of Radiology, Shengjing Hospital of China Medical University, China
| | - Yang Hou
- Department of Radiology, Shengjing Hospital of China Medical University, China.
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