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Zhu Q, Sun J, Zhu W, Chen W, Ye J. Spectral CT imaging versus conventional CT post-processing technique in differentiating malignant and benign renal tumors. Br J Radiol 2023; 96:20230147. [PMID: 37750940 PMCID: PMC10607386 DOI: 10.1259/bjr.20230147] [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: 02/12/2023] [Revised: 08/02/2023] [Accepted: 08/04/2023] [Indexed: 09/27/2023] Open
Abstract
OBJECTIVE Quantitative comparison of the diagnostic value of spectral CT imaging and conventional CT post-processing technique in differentiating malignant and benign renal tumors. METHODS A total of 209 patients with renal tumors who had undergone CT enhancement were assigned to three groups-clear cell renal cell carcinoma (ccRCC, n = 106), non-ccRCC (n = 60), and benign renal tumor (n = 43) groups. Parametric CT enhancement of each tumor based on spectral CT and conventional CT was performed using in-house software, and the iodine concentration, water content, slope, and density values among the three groups were compared. The receiver operating characteristic (ROC) curve analysis was performed to determine the optimum diagnostic thresholds, the area under the ROC curve (AUC), sensitivity, specificity, and accuracy of the above parameters. RESULTS The iodine concentration, slope, and density values were higher in the ccRCCs group compared to the non-ccRCCs and benign renal tumor groups (p < 0.05). Moreover, the iodine concentration, slope, and density values were higher in benign renal tumors compared to non-ccRCCs (p < 0.05). According to the ROC curve analysis, iodine concentration presented the highest diagnostic efficacy in differentiating ccRCCs/non-ccRCCs from benign renal tumors. The pairwise comparisons of the ROC curves and the diagnostic efficacies revealed that ROI-based CT enhancement was worse than the spectral CT imaging analysis in terms of density (p < 0.05). CONCLUSION Iodine concentration presented the highest diagnostic efficacy in differentiating ccRCCs/non-ccRCCs from benign renal tumors. ADVANCES IN KNOWLEDGE 1. The iodine concentration, slope, and density values were higher for the ccRCCs compared to non-ccRCCs and benign renal tumors.2. Iodine concentration presented the highest diagnostic efficacy in differentiating ccRCCs/non-ccRCCs from benign renal tumors.3. Spectral CT imaging analysis performed better than conventional CT in differentiating malignant and benign renal tumors.
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Affiliation(s)
- Qingqiang Zhu
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Jun Sun
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Wenrong Zhu
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Wenxin Chen
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Jing Ye
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
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2
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Lim W, Sodemann EB, Büttner L, Jonczyk M, Lüdemann WM, Kahn J, Geisel D, Jann H, Aigner A, Böning G. Spectral Computed Tomography-Derived Iodine Content and Tumor Response in the Follow-Up of Neuroendocrine Tumors-A Single-Center Experience. Curr Oncol 2023; 30:1502-1515. [PMID: 36826076 PMCID: PMC9954990 DOI: 10.3390/curroncol30020115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 01/08/2023] [Accepted: 01/18/2023] [Indexed: 01/24/2023] Open
Abstract
Spectral computed tomography (SCT) allows iodine content (IC) calculation for characterization of hypervascularized neoplasms and thus might help in the staging of neuroendocrine tumors (NETs). This single-center prospective study analyzed the association between SCT-derived IC and tumor response in the follow-up of metastasized NETs. Twenty-six patients with a median age of 70 years (range 51-85) with histologically proven NETs and a total of 78 lesions underwent SCT for staging. Because NETS are rare, no primary NET types were excluded. Lesions and intralesional hotspots were measured in virtual images and iodine maps. Tumor response was classified as progressive or nonprogressive at study endpoint. Generalized estimating equations served to estimate associations between IC and tumor response, additionally stratified by lesion location. Most commonly affected sites were the lymph nodes, liver, pancreas, and bones. Median time between SCT and endpoint was 64 weeks (range 5-260). Despite statistical imprecision in the estimate, patients with higher IC in lymphonodular metastases had lower odds for disease progression (adjusted OR = 0.21, 95% CI: 0.02-2.02). Opposite tendencies were observed in hepatic and pancreatic metastases in unadjusted analyses, which vanished after adjusting for therapy and primary tumor grade.
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Affiliation(s)
- Winna Lim
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353 Berlin, Germany
- Correspondence:
| | - Elisa Birgit Sodemann
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353 Berlin, Germany
| | - Laura Büttner
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353 Berlin, Germany
| | - Martin Jonczyk
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353 Berlin, Germany
| | - Willie Magnus Lüdemann
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353 Berlin, Germany
| | - Johannes Kahn
- Institute of Neuroradiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353 Berlin, Germany
| | - Dominik Geisel
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353 Berlin, Germany
| | - Henning Jann
- Department of Hepatology and Gastroenterology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353 Berlin, Germany
| | - Annette Aigner
- Institute of Biometry and Clinical Epidemiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Charité Mitte, Charitéplatz 1, 10117 Berlin, Germany
| | - Georg Böning
- Department of Radiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353 Berlin, Germany
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3
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Graafen D, Müller L, Halfmann M, Düber C, Hahn F, Yang Y, Emrich T, Kloeckner R. Photon-counting detector CT improves quality of arterial phase abdominal scans: A head-to-head comparison with energy-integrating CT. Eur J Radiol 2022; 156:110514. [PMID: 36108479 DOI: 10.1016/j.ejrad.2022.110514] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 08/26/2022] [Accepted: 09/03/2022] [Indexed: 11/19/2022]
Abstract
PURPOSE Photon-counting detector (PCD)-CT is expected to have a substantial impact on oncologic abdominal imaging. We compared subjective and objective image quality between PCD-CT and conventional energy-integrating detector (EID-)CT arterial phase abdominal scans. METHODS This study included 84 patients undergoing both types of abdominal CT. EID-CT scans were acquired with a tube voltage of 100 kVp. With PCD-CT, acquired with 120-kVp, we reconstructed polychromatic T3D images and virtual monoenergetic images (VMIs) in 10-keV intervals from 40 to 90 keV. Quantitative image analysis included noise and contrast-to-noise ratio (CNR) of hepatic vessels, kidney cortex, and hypervascular liver lesions to liver parenchyma. Three raters used a 5-point Likert scale for qualitative image analysis of image noise and contrast, lesion conspicuity, and overall image quality. Radiation dose exposure (CT dose index) was compared between the two CT types. RESULTS Mean CT dose index and effective dose were respectively 18 % and 26 % lower with PCD-CT versus EID-CT. Compared with EID-CT, CNRs of kidney cortex and vessel to liver parenchyma were significantly higher in PCD-CT VMIs at energies ≤ 60 keV and in polychromatic T3D images (p < 0.004). Overall image quality of PCD-CT VMIs at 50 and 60 keV was rated as significantly better (p < 0.01) than the EID-CT images (inter-reader agreement alpha = 0.80). Lesion conspicuity was significantly better in low-keV VMIs (p < 0.03) and worse in > 70-keV VMIs. CONCLUSIONS With low-keV VMI, PCD-CT yields significantly improved objective and subjective quality of arterial phase oncological imaging compared with EID-CT. This advantage may translate into higher diagnostic confidence and lower radiation dose protocols.
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Affiliation(s)
- D Graafen
- Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
| | - L Müller
- Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - M Halfmann
- Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany; German Center for Cardiovascular Research (DZHK), Partner-Site Rhine-Main, Mainz, Germany
| | - C Düber
- Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - F Hahn
- Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Y Yang
- Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - T Emrich
- Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany; German Center for Cardiovascular Research (DZHK), Partner-Site Rhine-Main, Mainz, Germany
| | - R Kloeckner
- Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
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Mroueh N, Cao J, Kambadakone A. Dual-Energy CT in the Pancreas. JOURNAL OF GASTROINTESTINAL AND ABDOMINAL RADIOLOGY 2022. [DOI: 10.1055/s-0042-1744494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
Abstract
AbstractDual-energy computed tomography (DECT) is an evolving imaging technology that is gaining popularity, particularly in different abdominopelvic applications. Essentially, DECT uses two energy spectra simultaneously to acquire CT attenuation data which is used to distinguish among structures with different tissue composition. The wide variety of reconstructed image data sets makes DECT especially attractive in pancreatic imaging. This article reviews the current literature on DECT as it applies to imaging the pancreas, focusing on pancreatitis, trauma, pancreatic ductal adenocarcinoma, and other solid and cystic neoplasms. The advantages of DECT over conventional CT are highlighted, including improved lesion detection, radiation dose reduction, and enhanced image contrast. Additionally, data exploring the ideal protocol for pancreatic imaging using DECT is reviewed. Finally, limitations of DECT in pancreatic imaging as well as recommendations for future research are provided.
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Affiliation(s)
- Nayla Mroueh
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
| | - Jinjin Cao
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
| | - Avinash Kambadakone
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
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5
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Jiang L, Liu D, Long L, Chen J, Lan X, Zhang J. Dual-source dual-energy computed tomography-derived quantitative parameters combined with machine learning for the differential diagnosis of benign and malignant thyroid nodules. Quant Imaging Med Surg 2022; 12:967-978. [PMID: 35111598 DOI: 10.21037/qims-21-501] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Accepted: 08/12/2021] [Indexed: 01/05/2023]
Abstract
Background This study aimed to investigate the ability of quantitative parameter-derived dual-source dual-energy computed tomography (DS-DECT) combined with machine learning to distinguish between benign and malignant thyroid nodules. Methods Patients with thyroid nodules and pathological surgical results who underwent preoperative DS-DECT were selected. Quantitative parameter-derived DS-DECT was applied to classify benign and malignant nodules. Then, machine learning and binary logistic regression analysis models were constructed using the DS-DECT quantitative parameters to distinguish between benign and malignant nodules. The receiver operating characteristic curve was used to assess the diagnostic performance. The DeLong test was used to compare the diagnostic efficacy. Results One hundred and thirty patients with 139 confirmed thyroid nodules were involved in the study. The malignant group had a significantly higher iodine concentrationnodule (arterial phase) (P=0.001), normalized iodine concentration (arterial phase) (P=0.002), iodine concentration difference (P<0.001), spectral curve slope (nonenhancement) (P=0.007), spectral curve slope (arterial phase) (P=0.001), effective atomic number (nonenhancement) (P<0.001), and effective atomic number (arterial phase) (P=0.039) than the benign group. The binary logistic regression analysis model had an AUC (area under the curve) of 0.76, a sensitivity of 0.821, and a specificity of 0.667. The machine learning model had an AUC of 0.86, a sensitivity of 0.822, specificity of 0.791 in the training cohort, an AUC of 0.84, a sensitivity of 0.727, and specificity of 0.750 in the testing cohort. Conclusions Multiple quantitative parameters of DS-DECT combined with machine learning could differentiate between benign and malignant thyroid nodules.
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Affiliation(s)
- Liling Jiang
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.,Chongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Daihong Liu
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.,Chongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Ling Long
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.,Chongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Jiao Chen
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.,Chongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Xiaosong Lan
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.,Chongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Jiuquan Zhang
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.,Chongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China
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Voss BA, Khandelwal A, Wells ML, Inoue A, Venkatesh SK, Lee YS, Johnson MP, Fletcher JG. Impact of dual-energy 50-keV virtual monoenergetic images on radiologist confidence in detection of key imaging findings of small hepatocellular carcinomas using multiphase liver CT. Acta Radiol 2021; 63:1443-1452. [PMID: 34723681 DOI: 10.1177/02841851211052993] [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: 11/15/2022]
Abstract
BACKGROUND Dual-energy virtual monoenergetic images can increase iodine signal, potentially increasing the conspicuity of hepatic masses. PURPOSE To determine if dual-energy 50-keV virtual monoenergetic images improve visualization of key imaging findings or diagnostic confidence for small (≤2 cm) hepatocellular carcinomas (HCC) at multiphase, contrast-enhanced liver computed tomography (CT). MATERIAL AND METHODS Patients with chronic liver disease underwent multiphase dual-energy CT imaging for HCC, with late arterial and delayed phase dual-energy 50-keV images reconstructed. Two non-reader subspecialized gastrointestinal (GI) radiologists established the reference standard, determining the location and diagnosis of all hepatic lesions using predetermined criteria. Three GI radiologists interpreted mixed kV CT images without or with dual-energy 50-keV images. Radiologists identified potential HCCs and rated their confidence (0-100 scales) in imaging findings of arterial enhancement, enhancing capsule, tumor washout, and LI-RADS 5 (2018) category. RESULTS In total, 45 patients (14 women; mean age = 59.5 ± 10.9 years) with chronic liver disease were included. Of them, 19 patients had 25 HCCs ≤2 cm (mean size = 1.5 ± 0.4 cm). There were 17 LI-RADS 3 and 4 lesions and 19 benign lesions. Reader confidence in imaging findings of arterial enhancement, enhancing capsule, and non-peripheral washout significantly increased with dual-energy images (P ≤ 0.022). Overall confidence in HCC diagnosis increased significantly with dual-energy 50-keV images (52.4 vs. 68.8; P = 0.001). Dual-energy images demonstrated a slight but significant decrease in overall image quality. CONCLUSION Radiologist confidence in key imaging features of small HCCs and confidence in imaging diagnosis increases with use of dual-energy 50-keV images at multiphase, contrast-enhanced liver CT.
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Affiliation(s)
| | | | | | - Akitoshi Inoue
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - Yong S Lee
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Matthew P Johnson
- Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
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Adam SZ, Rabinowich A, Kessner R, Blachar A. Spectral CT of the abdomen: Where are we now? Insights Imaging 2021; 12:138. [PMID: 34580788 PMCID: PMC8476679 DOI: 10.1186/s13244-021-01082-7] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 08/16/2021] [Indexed: 12/14/2022] Open
Abstract
Spectral CT adds a new dimension to radiological evaluation, beyond assessment of anatomical abnormalities. Spectral data allows for detection of specific materials, improves image quality while at the same time reducing radiation doses and contrast media doses, and decreases the need for follow up evaluation of indeterminate lesions. We review the different acquisition techniques of spectral images, mainly dual-source, rapid kV switching and dual-layer detector, and discuss the main spectral results available. We also discuss the use of spectral imaging in abdominal pathologies, emphasizing the strengths and pitfalls of the technique and its main applications in general and in specific organs.
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Affiliation(s)
- Sharon Z Adam
- Department of Diagnostic Radiology, Tel Aviv Sourasky Medical Center, 6 Weizmann St., 6423906, Tel Aviv, Israel. .,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
| | - Aviad Rabinowich
- Department of Diagnostic Radiology, Tel Aviv Sourasky Medical Center, 6 Weizmann St., 6423906, Tel Aviv, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Rivka Kessner
- Department of Diagnostic Radiology, Tel Aviv Sourasky Medical Center, 6 Weizmann St., 6423906, Tel Aviv, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Arye Blachar
- Department of Diagnostic Radiology, Tel Aviv Sourasky Medical Center, 6 Weizmann St., 6423906, Tel Aviv, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
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Spectral CT Hybrid Images in the Diagnostic Evaluation of Hypervascular Abdominal Tumors-Potential Advantages in Clinical Routine. Diagnostics (Basel) 2021; 11:diagnostics11091539. [PMID: 34573880 PMCID: PMC8471266 DOI: 10.3390/diagnostics11091539] [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: 06/24/2021] [Revised: 08/18/2021] [Accepted: 08/23/2021] [Indexed: 12/04/2022] Open
Abstract
Background: This study aimed to investigate the use of spectral computed tomography (SCT) hybrid images combining virtual monoenergetic images (VMIs) and iodine maps (IMs) as a potentially efficient search series for routine clinical imaging in patients with hypervascular abdominal tumors. Methods: A total of 69 patients with hypervascular abdominal tumors including neuroendocrine neoplasms (NENs, n = 48), renal cell carcinoma (RCC, n = 10), and primary hepatocellular carcinoma (HCC, n = 11) were analyzed retrospectively. Two radiological readers (blinded to clinical data) read three CT image sets (1st a reference set with 70 keV; 2nd a 50:50 hybrid 140 keV/40 keV set; 3rd a 50:50 hybrid 140 keV/IM set). They assessed images subjectively by rating several parameters including image contrast, visibility of suspicious lesions, and diagnostic confidence on five-point Likert scales. In addition, reading time was estimated. Results: Median subjective Likert scores were highest for the 1st set, except for image contrast, for which the 2nd set was rated highest. Scores for diagnostic confidence, artifacts, noise, and visibility of suspicious lesions or small structures were significantly higher for the 1st set than for the 2nd or 3rd set (p < 0.001). Regarding image contrast, the 2nd set was rated significantly higher than the 3rd set (p < 0.001), while the median did not differ significantly compared with the 1st set. Agreement between the two readers was high for all sets. Estimated potential reading time was the same for hybrid and reference sets. Conclusions: Hybrid images have the potential to efficiently exploit the additional information provided by SCT in patients with hypervascular abdominal tumors. However, the use of rigid weighting did not significantly improve diagnostic performance in this study.
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Spectral CT in clinical routine imaging of neuroendocrine neoplasms. Clin Radiol 2021; 76:348-357. [PMID: 33610290 DOI: 10.1016/j.crad.2020.12.027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 12/24/2020] [Indexed: 12/14/2022]
Abstract
AIM To evaluate the potential of new spectral computed tomography (SCT)-based tools in patients with neuroendocrine neoplasms (NEN). MATERIAL AND METHODS Eighty-eight consecutive patients with NENs were included prospectively. The patients underwent multiphase CT with spectral and standard mode. The signal-to-noise ratio (SNR)/contrast-to-noise-ratio (CNR)tumour-to-liver, iodine concentrations (ICs, total tumour/hotspot) and attenuation slopes in virtual monochromatic images (VMIs) were used to assess NEN-specific SCT values in primary tumours and metastatic lesions and investigate a possible lesion contrast improvement as well as possible correlations of SCT parameters to primary tumour location and tumour grade. Furthermore, the usability of SCT parameters to differentiate between the primary tumour and metastatic lesions, and to predict tumour response after 6-months follow-up was analyzed. The applied dose of spectral and standard mode was compared intra-individually. RESULTS SNR/CNRtumour-to-liver significantly increased in low-energy VMIs. NENs showed significant differences in ICs between primary and metastatic lesions for both absolute and normalised values (p<0.001) regardless of whether the total tumour or the hotspot was measured. There was also a significant difference in the attenuation slope (p<0.001). No significant correlations were found between SCT and tumour grade. A tumour response prediction by SCT parameters was not possible. The applied dose was comparable between the scan modes. CONCLUSION SCT was comparable regarding applied dose, improved tumour contrast, and contributed to differentiation between primary NEN and metastasis.
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Generation of Brain Dual-Energy CT from Single-Energy CT Using Deep Learning. J Digit Imaging 2021; 34:149-161. [PMID: 33432448 DOI: 10.1007/s10278-020-00414-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 12/03/2020] [Accepted: 12/18/2020] [Indexed: 12/21/2022] Open
Abstract
Deep learning (DL) has shown great potential in conversions between various imaging modalities. Similarly, DL can be applied to synthesize a high-kV computed tomography (CT) image from its corresponding low-kV CT image. This indicates the feasibility of obtaining dual-energy CT (DECT) images without purchasing a DECT scanner. In this study, we investigated whether a low-to-high kV mapping was better than a high-to-low kV mapping. We used a U-Net model to perform conversions between different kV CT images. Moreover, we proposed a double U-Net model to improve the quality of original single-energy CT images. Ninety-eight patients who underwent brain DECT scans were used to train, validate, and test the proposed DL-based model. The results showed that the low-to-high kV conversion was better than the high-to-low kV conversion. In addition, the DL-based DECT images had better signal-to-noise ratios (SNRs) than the true (original) DECT images, but at the expense of a slight loss in spatial resolution. The mean CT number differences between the true and DL-based DECT images were within [Formula: see text] 1 HU. No statistically significant difference in CT number measurements was found between the true and DL-based DECT images (p > 0.05). The DL-based DECT images with improved SNR could produce low-noise virtual monoenergetic images. Our preliminary results indicate that DL has the potential to generate brain DECT images using single-energy brain CT images.
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11
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Liu C, Huang H. Noise reduction in dual‐energy computed tomography virtual monoenergetic imaging. J Appl Clin Med Phys 2019; 20:104-113. [PMID: 31390137 PMCID: PMC6753738 DOI: 10.1002/acm2.12694] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 06/05/2019] [Accepted: 07/23/2019] [Indexed: 12/15/2022] Open
Abstract
Purpose Virtual monoenergetic images (VMIs) derived from dual‐energy computed tomography (DECT) have been explored for several clinical applications in recent years. However, VMIs at low and high keVs have high levels of noise. The aim of this study was to reduce image noise in VMIs by using a two‐step noise reduction technique. Methods VMI was first denoised using a modified highly constrained backprojection (HYPR) method. After the first‐step denoising, a general‐threshold filtering method was performed. Two sets of anthropomorphic phantoms were scanned with a clinical dual‐source DECT system. DECT data (80/140Sn kV) were reconstructed as VMI series at 12 different energy levels (range, 40‐150 keV, interval, 10 keV). For comparison, the averaged VMIs obtained from 10 repeated DECT scans were used as the reference standard. The signal‐to‐noise ratio (SNR), contrast‐to‐noise ratio (CNR) and root‐mean‐square error (RMSE) were used to evaluate the quality of VMIs. Results Compared to the original HYPR method, the proposed two‐step image denoising method could provide better performance in terms of SNR, CNR, and RMSE. In addition, the proposed method could achieve effective noise reduction while preserving edges and small structures, especially for low‐keV VMIs. Conclusion The proposed two‐step image denoising method is a feasible method for reducing noise in VMIs obtained from a clinical DECT scanner. The proposed method can also reduce edge blurring and the loss of intensity in small lesions.
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Affiliation(s)
- Chi‐Kuang Liu
- Department of Medical Imaging Changhua Christian Hospital Changhua City Taiwan
| | - Hsuan‐Ming Huang
- Institute of Medical Device and Imaging, College of Medicine National Taiwan University Taipei Taiwan
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