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Chang Y, Xing H, Shang Y, Liu Y, Yu L, Dai H. Radiomics nomogram: distinguishing benign and malignant pure ground-glass nodules based on dual-layer spectral detector CT. Clin Radiol 2024; 79:e1205-e1213. [PMID: 39013667 DOI: 10.1016/j.crad.2024.06.010] [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: 07/20/2023] [Revised: 06/06/2024] [Accepted: 06/11/2024] [Indexed: 07/18/2024]
Abstract
AIM To investigate the value of the combined model based on spectral quantitative parameters, radiomics features, imaging and clinical features to distinguish the benign and malignant pure ground-glass nodules (pGGNs). MATERIALS AND METHODS A retrospective analysis of 113 patients with single pGGNs who underwent non-contrast enhancement examination of the chest on dual-layer spectral detector CT (SDCT) with two weeks before surgery was performed in our hospital. These patients were randomized into training and testing cohorts. Regions of interest based on the conventional 120 kVp poly energetic image of SDCT were outlined. Then the optimal features were extracted and selected to construct radiomic model. A combined model combining vacuole sign, electron density (ED) value and the rad score of radiomics model was built by logistic regression analysis. A nomogram was built in a training cohort and the performance of the models was evaluated in the training and testing cohorts by receiver operating characteristic curves, calibration curves and decision curve analysis. RESULTS ED value [Odds Ratio (OR):1.100; 95% confidence interval (CI):1.027-1.166)] and vacuole sign (OR:3.343; 95% CI:0.881-12.680) were independent risk factors for the malignant pGGNs in the training cohort. A combined model was constructed using radiomics features, ED value and vacuole sign. And the AUC was 0.910 (95% CI, 0.825-0.997) and 0.850 (95% CI, 0.714-0.981) in the training and testing cohorts, respectively. CONCLUSION The combined model based on SDCT has high specificity and sensitivity for distinguishing the benign and malignant pGGNs, suggesting the model can further improve diagnostic performance, and using a nomogram is helpful for individualized predictions.
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Affiliation(s)
- Y Chang
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, 215006, PR China
| | - H Xing
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, 215006, PR China
| | - Y Shang
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, 215006, PR China
| | - Y Liu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, 215006, PR China
| | - L Yu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, 215006, PR China
| | - H Dai
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, 215006, PR China; Institute of Medical Imaging, Soochow University, Suzhou, Jiangsu Province, 215006, PR China; Suzhou Key Laboratory of Intelligent Medicine and Equipment, Suzhou, Jiangsu Province, 215123, PR China.
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Wang Y, Peng Y, Wang T, Li H, Zhao Z, Gong L, Peng B. The evolution and current situation in the application of dual-energy computed tomography: a bibliometric study. Quant Imaging Med Surg 2023; 13:6801-6813. [PMID: 37869341 PMCID: PMC10585566 DOI: 10.21037/qims-23-467] [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: 04/07/2023] [Accepted: 08/09/2023] [Indexed: 10/24/2023]
Abstract
Background Dual-energy computed tomography (DECT) has received extensive attention in clinical practice; however, a quantitative assessment of published literature in this domain is presently lacking. This study thus aimed to characterize the application conditions, developmental trends, and research hot spots of DECT using bibliometric analysis. Methods All literature on DECT was retrieved from the Web of Science Core Collection (WoSCC) on January 22, 2023. The co-occurrence, cooperation network, and co-citation of countries, institutions, references, authors, journals, and keywords were analyzed using CiteSpace, VOSviewer, and R-bibliometrix software. Results In total, 4,720 original articles and reviews were included. The number of publications related to DECT has rapidly increased since 2006. The USA (n=1,662) and Mayo Clinic (n=178) were found to be the most productive country and institution, respectively. The most cited article was published by Johnson TRC et al., while the article published by McCollough CH et al. in 2015 had the most co-citations. Schoepf UJ ranked first with most articles among 16,838 authors. The journal with the most published articles was European Radiology, with 411 publications. The timeline analysis indicated that material decomposition was the most recent topic, followed by gout, radiomics, proton therapy, and bone marrow edema. Conclusions An increasing number of researchers are committed to researching DECT, with the USA making the most significant contributions in this area. Prior studies have primarily concentrated on cardiovascular diseases, and contemporary hot spots include expansion into to other fields, such as iodine quantification, deep learning, and bone marrow edema.
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Affiliation(s)
- Ya Wang
- Department of Radiology, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yun Peng
- Department of Radiology, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Tongtong Wang
- Department of Radiology, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Hui Li
- Department of Radiology, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Zhen Zhao
- Department of Radiology, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Lianggeng Gong
- Department of Radiology, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Bibo Peng
- Department of Radiology, The Second Affiliated Hospital of Nanchang University, Nanchang, China
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Xu H, Zhu N, Yue Y, Guo Y, Wen Q, Gao L, Hou Y, Shang J. Spectral CT-based radiomics signature for distinguishing malignant pulmonary nodules from benign. BMC Cancer 2023; 23:91. [PMID: 36703132 PMCID: PMC9878920 DOI: 10.1186/s12885-023-10572-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Accepted: 01/20/2023] [Indexed: 01/27/2023] Open
Abstract
OBJECTIVES To evaluate the discriminatory capability of spectral CT-based radiomics to distinguish benign from malignant solitary pulmonary solid nodules (SPSNs). MATERIALS AND METHODS A retrospective study was performed including 242 patients with SPSNs who underwent contrast-enhanced dual-layer Spectral Detector CT (SDCT) examination within one month before surgery in our hospital, which were randomly divided into training and testing datasets with a ratio of 7:3. Regions of interest (ROIs) based on 40-65 keV images of arterial phase (AP), venous phases (VP), and 120kVp of SDCT were delineated, and radiomics features were extracted. Then the optimal radiomics-based score in identifying SPSNs was calculated and selected for building radiomics-based model. The conventional model was developed based on significant clinical characteristics and spectral quantitative parameters, subsequently, the integrated model combining radiomics-based model and conventional model was established. The performance of three models was evaluated with discrimination, calibration, and clinical application. RESULTS The 65 keV radiomics-based scores of AP and VP had the optimal performance in distinguishing benign from malignant SPSNs (AUC65keV-AP = 0.92, AUC65keV-VP = 0.88). The diagnostic efficiency of radiomics-based model (AUC = 0.96) based on 65 keV images of AP and VP outperformed conventional model (AUC = 0.86) in the identification of SPSNs, and that of integrated model (AUC = 0.97) was slightly further improved. Evaluation of three models showed the potential for generalizability. CONCLUSIONS Among the 40-65 keV radiomics-based scores based on SDCT, 65 keV radiomics-based score had the optimal performance in distinguishing benign from malignant SPSNs. The integrated model combining radiomics-based model based on 65 keV images of AP and VP with Zeff-AP was significantly superior to conventional model in the discrimination of SPSNs.
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Affiliation(s)
- Hang Xu
- grid.412467.20000 0004 1806 3501Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004 China
| | - Na Zhu
- grid.416466.70000 0004 1757 959XDepartment of Radiation Oncology, Nanfang Hospital of Southern Medical University, Guangzhou, 510000 China
| | - Yong Yue
- grid.412467.20000 0004 1806 3501Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004 China
| | - Yan Guo
- GE Healthcare, Shenyang, 110004 China
| | - Qingyun Wen
- grid.459518.40000 0004 1758 3257Department of Radiology, Jining First People’s Hospital, Jining, 272000 China
| | - Lu Gao
- Department of Radiology, Liaoning Province Cancer Hospital, Shenyang, 110801 China
| | - Yang Hou
- grid.412467.20000 0004 1806 3501Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004 China
| | - Jin Shang
- grid.412467.20000 0004 1806 3501Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004 China
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Differentiating pulmonary metastasis from benign lung nodules in thyroid cancer patients using dual-energy CT parameters. Eur Radiol 2021; 32:1902-1911. [PMID: 34564746 DOI: 10.1007/s00330-021-08278-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 08/01/2021] [Accepted: 08/16/2021] [Indexed: 01/10/2023]
Abstract
OBJECTIVES To explore the importance of quantitative characteristics of dual-energy CT (DECT) between pulmonary metastasis and benign lung nodules in thyroid cancer. METHODS In this retrospective study, we identified 63 patients from our institution's database with pathologically proven thyroid cancer who underwent DECT to assess pulmonary metastasis. Among these patients, 22 had 55 pulmonary metastases, and 41 had 97 benign nodules. If nodules showed increased iodine uptake on I-131 single-photon emission computed tomography-computed tomography or increased size in follow-up CT, they were considered metastatic. We compared the clinical findings and DECT parameters of both groups and performed a receiver operating characteristic analysis to evaluate the optimal cutoff values of the DECT parameters. RESULTS Patients with metastases were significantly older than patients with benign nodules (p = 0.048). The DECT parameters of the metastatic nodules were significantly higher than those of the benign nodules (iodine concentration [IC], 5.61 ± 2.02 mg/mL vs. 1.61 ± 0.98 mg/mL; normalized IC [NIC], 0.60 ± 0.20 vs. 0.16 ± 0.11; NIC using pulmonary artery [NICPA], 0.60 ± 0.44 vs. 0.15 ± 0.11; slope of the spectral attenuation curves [λHU], 5.18 ± 2.54 vs. 2.12 ± 1.39; and Z-effective value [Zeff], 10.0 ± 0.94 vs. 8.79 ± 0.75; all p < 0.001). In the subgroup analysis according to nodule size, all DECT parameters of the metastatic nodules in all subgroups were significantly higher than those of the benign nodules (all p < 0.05). The cutoff values for IC, NIC, λHU, NICPA, and Zeff for diagnosing metastases were 3.10, 0.29, 3.57, 0.28, and 9.34, respectively (all p < 0.001). CONCLUSIONS DECT parameters can help to differentiate metastatic and benign lung nodules in thyroid cancer. KEY POINTS • DECT parameters can help to differentiate metastatic and benign lung nodules in patients with thyroid cancer. • DECT parameters showed a significant difference between benign lung nodules and lung metastases, even for nodules with diameters ≥ 3 mm and < 5 mm. • Among the DECT parameters, the highest diagnostic accuracy for differentiating pulmonary metastases from benign lung nodules was achieved with the NIC and IC, followed by the NICPA and λHU, and their cutoff values were 0.29, 3.10, 0.28, and 3.57, respectively.
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Fu T, Gad MM, Gupta A. Improved characterization of focal airway lesions using spectral detector dual energy CT. Clin Imaging 2021; 79:326-329. [PMID: 34399288 DOI: 10.1016/j.clinimag.2021.07.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 07/10/2021] [Accepted: 07/30/2021] [Indexed: 10/20/2022]
Abstract
Clinicians should be aware of SDCT as a useful tool in the assessment of focal airway lesions. Spectral detector dual-energy computed tomography (SDCT) is a relatively novel imaging technology which has been utilized to aid in the diagnosis of many cardiothoracic conditions. Specifically, the availability of generated iodine density maps, virtual monoenergetic images, and effective atomic number maps allow for better evaluation of thoracic lesions compared to conventional CT. SDCT has previously been shown to be useful in the differentiation of benign vs malignant pulmonary nodules, pleural lesions, and lymph nodes. We describe 3 cases in which a patient presents with an indeterminate tracheal or bronchial lesion on conventional CT and subsequent SDCT reconstructions provided additional information which helped guide diagnosis or management of the patient. The goal is to help clinicians understand the benefit of SDCT in the detection and workup of airway lesions.
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Affiliation(s)
- Tianyuan Fu
- Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH, United States of America.
| | - Mohamed M Gad
- Department of Medicine, Cleveland Clinic Foundation, Cleveland, OH, United States of America
| | - Amit Gupta
- Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH, United States of America
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Laroia ST, Yadav K, Kumar S, Rastogi A, Kumar G, Sarin SK. Material decomposition using iodine quantification on spectral CT for characterising nodules in the cirrhotic liver: a retrospective study. Eur Radiol Exp 2021; 5:22. [PMID: 34046753 PMCID: PMC8160046 DOI: 10.1186/s41747-021-00220-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Accepted: 04/07/2021] [Indexed: 12/15/2022] Open
Abstract
Background There is limited scientific evidence on the potential of spectral computed tomography (SCT) for differentiation of nodules in the cirrhotic liver. We aimed to assess SCT-generated material density (MD) parameters for nodule characterisation in cirrhosis. Methods Dynamic dual-energy SCT scans of cirrhotic patients performed over 3 years were retrospectively reviewed. They were classified as hepatocellular carcinoma (HCC), regenerative or indeterminate, according to the European Association for the Study of the Liver criteria. MD maps were generated to calculate the area under the curve (AUC) and cutoff values to discriminate these nodules in the hepatic arterial phase (HAP) and portal venous phase (PVP). MD maps included iodine concentration density (ICD) of the liver and nodule, lesion-to-normal liver ICD ratio (LNR) and difference in nodule ICD between HAP and PVP. Results Three hundred thirty nodules belonging to 300 patients (age 53.0 ± 12.7 years, mean ± standard deviation) were analysed at SCT (size 2.3 ± 0.8 cm, mean ± SD). One hundred thirty-three (40.3%) nodules were classified as HCC, 147 (44.5%) as regenerative and 50 (15.2%) as indeterminate. On histopathology, 136 (41.2%) nodules were classified as HCC, 183 (55.5%) as regenerative and 11 (3.3%) as dysplastic. All MD parameters on HAP and the nodule difference in ICD could discriminate pathologically proven HCC or potentially malignant nodules from regenerative nodules (p < 0.001). The AUC was 82.4% with a cutoff > 15.5 mg/mL for nodule ICD, 81.3% > 1.8 for LNR-HAP and 81.3% for difference in ICD > 3.5 mg/mL. Conclusion SCT-generated MD parameters are viable diagnostic tools for differentiating malignant or potentially malignant from benign nodules in the cirrhotic liver. Supplementary Information The online version contains supplementary material available at 10.1186/s41747-021-00220-6.
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Affiliation(s)
- Shalini Thapar Laroia
- Department of Radiology, Institute of Liver and Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India.
| | - Komal Yadav
- Department of Radiology, Institute of Liver and Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India
| | - Senthil Kumar
- Department of HPB Surgery and Liver Transplantation, Institute of Liver & Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India
| | - Archana Rastogi
- Department of Clinical and Hepato-pathology, Institute of Liver and Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India
| | - Guresh Kumar
- Department of Biostatistics and Research, Institute of Liver & Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India
| | - Shiv Kumar Sarin
- Department of Hepatology, Institute of Liver & Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110 070, India
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Lin J, Wang L, Ji X, Zheng X, Tang K. Characterization of 18F-fluorodeoxyglucose metabolic spatial distribution improves the differential diagnosis of indeterminate pulmonary nodules and masses with high fluorodeoxyglucose uptake. Quant Imaging Med Surg 2021; 11:1543-1553. [PMID: 33816190 DOI: 10.21037/qims-20-768] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background The aim of this study was to investigate the value of visual assessment of 18F-fluorodeoxyglucose (18F-FDG) metabolic spatial distribution (V-FMSD) in the diagnosis of indeterminate pulmonary nodules and masses with high 18F-FDG uptake. Methods A total of 301 patients with indeterminate pulmonary nodules or masses who underwent 18F-FDG positron emission tomography/computed tomography (PET/CT) imaging were retrospectively studied. The characteristics of 18F-FDG metabolic spatial distribution (FMSD) in the proximal and distal regions of the lesions were visually analyzed using a 5-point scoring system. The sensitivity, specificity, accuracy, and area under receiver operating characteristic curve (AUC) were compared between V-FMSD and conventional PET/CT methods for the diagnosis of hypermetabolic indeterminate pulmonary nodules and masses. Results The V-FMSD results showed that 180 (92.8%) malignant lesions had a score of ≥3 and 78 (72.9%) benign lesions had a score of ≤2. This indicated that the FMSD in the proximal region of malignant lesions was significantly higher than that of the distal region, and the FMSD in the proximal region of benign lesions was significantly lower than that of the distal region. V-FMSD had a specificity of 72.9%, which was markedly higher than those of the maximum standard uptake value (SUVmax; 0%, P<0.001) and the retention index (RI; 26.2%, P<0.001). The AUC of V-FMSD was 0.886, which was significantly larger than those of the SUVmax (0.626, P<0.001), RI (0.670, P<0.001), and PET/CT (0.788, P<0.05). Conclusions Our study found that pulmonary benign and malignant lesions have distinct FMSD characteristics. V-FMSD can therefore be used as a novel auxiliary marker to improve the diagnostic accuracy of hypermetabolic indeterminate pulmonary nodules and masses.
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Affiliation(s)
- Jie Lin
- Department of PET/CT, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Ling Wang
- Department of Nuclear Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiaowei Ji
- Department of PET/CT, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiangwu Zheng
- Department of PET/CT, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Kun Tang
- Department of PET/CT, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
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Wen Q, Yue Y, Shang J, Lu X, Gao L, Hou Y. The application of dual-layer spectral detector computed tomography in solitary pulmonary nodule identification. Quant Imaging Med Surg 2021; 11:521-532. [PMID: 33532253 DOI: 10.21037/qims-20-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background Differentiating between malignant solitary pulmonary nodules (SPNs) and other lung diseases remains a substantial challenge. The latest generation of dual-energy computed tomography (CT), which realizes dual-energy technology at the detector level, has clinical potential for distinguishing lung cancer from other benign SPNs. This study aimed to evaluate the performance of dual-layer spectral detector CT (SDCT) for the differentiation of SPNs. Methods Spectral images of 135 SPNs confirmed by pathology were retrospectively analyzed in both the arterial phase (AP) and the venous phase (VP). Patients were classified into two groups [the malignant group (n=93) and the benign group (n=42)], with the malignant group further divided into small cell lung cancer (SCLC, n=30) and non-small cell lung cancer (NSCLC, n=63) subtypes. The slope of the spectral Hounsfield Unit (HU) curve (λHU), normalized iodine concentration (NIC), CT values of 40 keV monochromatic images (CT40keV), and normalized arterial enhancement fraction (NAEF) in contrast-enhanced images were calculated and compared between the benign and malignant groups, as well as between the SCLC and NSCLC subgroups. ROC curve analysis was performed to assess the diagnostic performance of the above parameters. Seventy cases were randomly selected and independently measured by two radiologists, and intraclass correlation coefficient (ICC) and Bland-Altman analyses were performed to calculate the reliability of the measurements. Results Except for NAEF (P=0.23), the values of the parameters were higher in the malignant group than in the benign group (all P<0.05). NIC, λHU, and CT40keV performed better in the VP (NICVP, λVPHU, and CTVP40keV) (P<0.001), with an area under the ROC curve (AUC) of 0.93, 0.89, and 0.89 respectively. With respective cutoffs of 0.31, 1.83, and 141.00 HU, the accuracy of NICVP, λVPHU, and CTVP40keV was 91.11%, 85.19%, and 88.15%, respectively. In the subgroup differentiating NSCLC and SCLC, the diagnostic performances of NICAP (AUC =0.89) were greater than other parameters. NICAP had an accuracy of 86.02% when the cutoff was 0.14. ICC and Bland-Altman analyses indicated that the measurement of SDCT has great reproducibility. Conclusions Quantitative measures from SDCT can help to differentiate benign from malignant SPNs and may help with the further subclassification of malignant cancer into SCLC and NSCLC.
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Affiliation(s)
- Qingyun Wen
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yong Yue
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Jin Shang
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xiaomei Lu
- CT Clinical Science, Philips Healthcare, Shenyang, China
| | - Lu Gao
- Department of Radiology, Liaoning Cancer Hospital, Shenyang, China
| | - Yang Hou
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
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Kim C, Kim W, Park SJ, Lee YH, Hwang SH, Yong HS, Oh YW, Kang EY, Lee KY. Application of Dual-Energy Spectral Computed Tomography to Thoracic Oncology Imaging. Korean J Radiol 2020; 21:838-850. [PMID: 32524784 PMCID: PMC7289700 DOI: 10.3348/kjr.2019.0711] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Revised: 01/16/2020] [Accepted: 02/10/2020] [Indexed: 12/20/2022] Open
Abstract
Computed tomography (CT) is an important imaging modality in evaluating thoracic malignancies. The clinical utility of dual-energy spectral computed tomography (DESCT) has recently been realized. DESCT allows for virtual monoenergetic or monochromatic imaging, virtual non-contrast or unenhanced imaging, iodine concentration measurement, and effective atomic number (Zeff map). The application of information gained using this technique in the field of thoracic oncology is important, and therefore many studies have been conducted to explore the use of DESCT in the evaluation and management of thoracic malignancies. Here we summarize and review recent DESCT studies on clinical applications related to thoracic oncology.
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Affiliation(s)
- Cherry Kim
- Department of Radiology, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, Korea
| | - Wooil Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Sung Joon Park
- Department of Radiology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Korea
| | - Young Hen Lee
- Department of Radiology, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, Korea
| | - Sung Ho Hwang
- Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea
| | - Hwan Seok Yong
- Department of Radiology, Korea University Guro Hospital, College of Medicine Korea University, Seoul, Korea
| | - Yu Whan Oh
- Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea
| | - Eun Young Kang
- Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea
| | - Ki Yeol Lee
- Department of Radiology, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, Korea.
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Spectral CT in Lung Cancer: Usefulness of Iodine Concentration for Evaluation of Tumor Angiogenesis and Prognosis. AJR Am J Roentgenol 2020; 215:595-602. [PMID: 32569515 DOI: 10.2214/ajr.19.22688] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE. The purpose of this study was to investigate the correlation between iodine concentration (IC) derived from spectral CT and angiogenesis and the relationships between IC and clinical-pathologic features associated with lung cancer prognosis. SUBJECTS AND METHODS. Sixty patients with lung cancer were enrolled and underwent spectral CT. The IC, IC difference (ICD), and normalized IC (NIC) of tumors were measured in the arterial phase, venous phase (VP), and delayed phase. The microvessel densities (MVDs) of CD34-stained specimens were evaluated. Correlation analysis was performed for IC and MVD. The relationships between the IC index showing the best correlations with MVD and clinical-pathologic findings of pathologic types, histologic differentiation, tumor size, lymph node status, pathologic TNM stage, and intratumoral necrosis were investigated. RESULTS. The mean (± IQR) MVD of all tumors was 42.00 ± 27.50 vessels per field at ×400 magnification, with two MVD distribution types. The MVD of lung cancer correlated positively with the IC, ICD, and NIC on three-phase contrast-enhanced scanning (r range, 0.581-0.800; all p < 0.001), and the IC in the VP showed the strongest correlation with MVD (r = 0.800; p < 0.001). The correlations between IC and MVD, ICD and MVD, and NIC and MVD varied depending on whether the same scanning phase or same IC index was used. The IC in the VP showed statistically significant differences in the pathologic types of adenocarcinoma and squamous cell carcinoma, histologic differentiation, tumor size, and status of intratumoral necrosis of lung cancer (p < 0.05), but was not associated with nodal metastasis and pathologic TNM stages (p > 0.05). CONCLUSION. IC indexes derived from spectral CT, especially the IC in the VP, were useful indicators for evaluating tumor angiogenesis and prognosis.
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Gupta A, Kikano EG, Gupta A, Di Felice C, Gilkeson R, Laukamp KR. Preoperative assessment of lung nodules and lobar function by spectral detector computed tomography. Radiol Case Rep 2020; 15:966-969. [PMID: 32419896 PMCID: PMC7214771 DOI: 10.1016/j.radcr.2020.04.049] [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: 03/14/2020] [Accepted: 04/20/2020] [Indexed: 11/30/2022] Open
Abstract
Conventional computed tomography (CT) plays an important role in detection of lung nodules. However, further characterization is usually limited requiring additional imaging and invasive work up. Spectral Detector CT (SDCT) is an upcoming novel modality that not only allows morphological evaluation but also provides insight into prediction of malignant behavior of lung nodules. Additional quantification capabilities available from the same scan make it a more comprehensive imaging option in oncology patients. This is a first case report demonstrating the potential of single SDCT to provide necessary information for lung cancer diagnosis and preoperative planning, comparable to standard of care imaging.
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Affiliation(s)
- Amit Gupta
- Department of Radiology, University Hospitals Cleveland Medical Center/Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106, USA
| | - Elias George Kikano
- Department of Radiology, University Hospitals Cleveland Medical Center/Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106, USA
| | - Aekta Gupta
- Department of Radiology, University Hospitals Cleveland Medical Center/Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106, USA
| | - Christopher Di Felice
- Department of Pulmonary, Critical Care and Sleep Medicine, University Hospitals Cleveland Medical Center/Case Western Reserve University, Cleveland, OH, USA
| | - Robert Gilkeson
- Department of Radiology, University Hospitals Cleveland Medical Center/Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106, USA
| | - Kai Roman Laukamp
- Department of Radiology, University Hospitals Cleveland Medical Center/Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106, USA.,Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany
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