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Gulizia M, Viry A, Jreige M, Fahrni G, Marro Y, Manasseh G, Chevallier C, Dromain C, Vietti-Violi N. Contrast Volume Reduction in Oncologic Body Imaging Using Dual-Energy CT: A Comparison with Single-Energy CT. Diagnostics (Basel) 2025; 15:707. [PMID: 40150050 PMCID: PMC11941575 DOI: 10.3390/diagnostics15060707] [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: 02/05/2025] [Revised: 03/03/2025] [Accepted: 03/07/2025] [Indexed: 03/29/2025] Open
Abstract
Background/Objectives: To evaluate the feasibility of reducing contrast volume in oncologic body imaging using dual-energy CT (DECT) by (1) identifying the optimal virtual monochromatic imaging (VMI) reconstruction using DECT and (2) comparing DECT performed with reduced iodinated contrast media (ICM) volume to single-energy CT (SECT) performed with standard ICM volume. Methods: In this retrospective study, we quantitatively and qualitatively compared the image quality of 35 thoracoabdominopelvic DECT across 9 different virtual monoenergetic image (VMI) levels (from 40 to 80 keV) using a reduced volume of ICM (0.3 gI/kg of body weight) to determine the optimal keV reconstruction level. Out of these 35 patients, 20 had previously performed SECT with standard ICM volume (0.3 gI/kg of body weight + 9 gI), enabling protocol comparison. The qualitative analysis included overall image quality, noise, and contrast enhancement by two radiologists. Quantitative analysis included contrast enhancement measurements, contrast-to-noise ratio, and signal-to-noise ratio of the liver parenchyma and the portal vein. ANOVA was used to identify the optimal VMI level reconstruction, while t-tests and paired t-tests were used to compare both protocols. Results: VMI60 keV provided the highest overall image quality score. DECT with reduced ICM volume demonstrated higher contrast enhancement and lower noise than SECT with standard ICM volume (p < 0.001). No statistical difference was found in the overall image quality between the two protocols (p = 0.290). Conclusions: VMI60 keV with reduced contrast volume provides higher contrast and lower noise than SECT at a standard contrast volume. DECT using a reduced ICM volume is the technique of choice for oncologic body CT.
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Affiliation(s)
- Marianna Gulizia
- Department of Radiology and Interventional Radiology, Lausanne University Hospital, University of Lausanne (UNIL), 1011 Lausanne, Switzerland; (M.G.); (A.V.); (Y.M.)
- Faculty of Biology and Medicine (FBM), University of Lausanne (UNIL), 1015 Lausanne, Switzerland
| | - Anais Viry
- Department of Radiology and Interventional Radiology, Lausanne University Hospital, University of Lausanne (UNIL), 1011 Lausanne, Switzerland; (M.G.); (A.V.); (Y.M.)
| | - Mario Jreige
- Department of Nuclear Medicine, Lausanne University Hospital, University of Lausanne (UNIL), 1011 Lausanne, Switzerland;
| | - Guillaume Fahrni
- Department of Radiology and Interventional Radiology, Lausanne University Hospital, University of Lausanne (UNIL), 1011 Lausanne, Switzerland; (M.G.); (A.V.); (Y.M.)
| | - Yannick Marro
- Department of Radiology and Interventional Radiology, Lausanne University Hospital, University of Lausanne (UNIL), 1011 Lausanne, Switzerland; (M.G.); (A.V.); (Y.M.)
| | - Gibran Manasseh
- Department of Radiology and Interventional Radiology, Lausanne University Hospital, University of Lausanne (UNIL), 1011 Lausanne, Switzerland; (M.G.); (A.V.); (Y.M.)
| | - Christine Chevallier
- Department of Radiology and Interventional Radiology, Lausanne University Hospital, University of Lausanne (UNIL), 1011 Lausanne, Switzerland; (M.G.); (A.V.); (Y.M.)
| | - Clarisse Dromain
- Department of Radiology and Interventional Radiology, Lausanne University Hospital, University of Lausanne (UNIL), 1011 Lausanne, Switzerland; (M.G.); (A.V.); (Y.M.)
| | - Naik Vietti-Violi
- Department of Radiology and Interventional Radiology, Lausanne University Hospital, University of Lausanne (UNIL), 1011 Lausanne, Switzerland; (M.G.); (A.V.); (Y.M.)
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Li S, Yang X, Cao Y, Yuan L, Lu T, Wang Y, Zhao J, Zhang W, Zhou J, Zhang G. Reduced-dose CT scan of colorectal cancer. Abdom Radiol (NY) 2025:10.1007/s00261-024-04660-7. [PMID: 39794537 DOI: 10.1007/s00261-024-04660-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2024] [Revised: 10/24/2024] [Accepted: 10/26/2024] [Indexed: 01/13/2025]
Affiliation(s)
- Shenglin Li
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Lanzhou University, Lanzhou, China
- Lanzhou University Second Hospital, Lanzhou, China
| | - Xinmei Yang
- Lanzhou University, Lanzhou, China
- Lanzhou University Second Hospital, Lanzhou, China
| | - Yuntai Cao
- Qinghai University Affiliated Hospital, Xining, China
| | - Long Yuan
- Lanzhou University, Lanzhou, China
- Lanzhou University Second Hospital, Lanzhou, China
| | - Ting Lu
- Lanzhou University, Lanzhou, China
- Lanzhou University Second Hospital, Lanzhou, China
| | - Yuxuan Wang
- Qinghai University Affiliated Hospital, Xining, China
| | - Jun Zhao
- Lanzhou University Second Hospital, Lanzhou, China
| | | | - Junlin Zhou
- Lanzhou University, Lanzhou, China.
- Lanzhou University Second Hospital, Lanzhou, China.
| | - Guojin Zhang
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
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Bodard S, Kharroubi-Lakouas D, Guinebert S, Dariane C, Gillard P, Sakhi H, Ferriere E, Delaye M, Timsit MO, Correas JM, Hélénon O, Boudhabhay I. [Cancer imaging and prevention of renal failure]. Bull Cancer 2024; 111:663-674. [PMID: 36371283 DOI: 10.1016/j.bulcan.2022.09.011] [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: 06/18/2022] [Revised: 09/15/2022] [Accepted: 09/20/2022] [Indexed: 11/11/2022]
Abstract
The risk of acute renal failure (ARF) following iodinated contrast media injection has long been overestimated because of the previous use of more toxic ICPs and uncontrolled studies. Nowadays, this concept is being questioned. Patients with severe renal failure and/or ARF are the only group still considered at risk. In these patients, it is necessary to discuss an alternative without an iodinated contrast agent. Contrast-enhanced ultrasound, MRI, spectral CT or PET-CT scan can be used instead of contrast-enhanced CT. Preventive measures should be applied when appropriate substitute to CT is not available or not diagnosed (minimum necessary dose of ICP, interruption of some treatments and prior hydration). These recommendations formalized by the European Society of Urogenital Radiology (ESUR) in 2018 address most situations faced by clinicians. In complex situations, an opinion from a nephrologist remains necessary after asking the radiologist about the availability of acceptable substitutes.
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Affiliation(s)
- Sylvain Bodard
- AP-HP, Hôpital Necker Enfants malades, service d'imagerie adulte, 75015 Paris, France; Université de Paris Cité, 75006 Paris, France; Sorbonne université, CNRS, Inserm, laboratoire d'imagerie biomédicale, Paris, France.
| | | | - Sylvain Guinebert
- AP-HP, Hôpital Necker Enfants malades, service d'imagerie adulte, 75015 Paris, France; Université de Paris Cité, 75006 Paris, France
| | - Charles Dariane
- Université de Paris Cité, 75006 Paris, France; AP-HP, hôpital européen Georges Pompidou, service d'urologie, 75015 Paris, France
| | - Paul Gillard
- AP-HP, Hôpital Necker Enfants malades, service d'imagerie adulte, 75015 Paris, France
| | - Hamza Sakhi
- Université de Paris Cité, 75006 Paris, France; AP-HP, hôpital Necker Enfants malades, service de néphrologie et transplantation rénale adulte, 75015 Paris, France
| | - Elsa Ferriere
- Université de Paris Cité, 75006 Paris, France; AP-HP, hôpital Necker Enfants malades, service de néphrologie et transplantation rénale adulte, 75015 Paris, France
| | - Matthieu Delaye
- Institut curie, université Versailles Saint-Quentin, département d'oncologie médicale, Saint-Cloud, France; Groupe de Recherche Interdisciplinaire Francophone en Onco-Néphrologie (GRIFON), Paris, France
| | - Marc-Olivier Timsit
- Université de Paris Cité, 75006 Paris, France; AP-HP, hôpital européen Georges Pompidou, service d'urologie, 75015 Paris, France
| | - Jean-Michel Correas
- AP-HP, Hôpital Necker Enfants malades, service d'imagerie adulte, 75015 Paris, France; Université de Paris Cité, 75006 Paris, France
| | - Olivier Hélénon
- AP-HP, Hôpital Necker Enfants malades, service d'imagerie adulte, 75015 Paris, France; Université de Paris Cité, 75006 Paris, France
| | - Idris Boudhabhay
- Université de Paris Cité, 75006 Paris, France; AP-HP, hôpital Necker Enfants malades, service de néphrologie et transplantation rénale adulte, 75015 Paris, France
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Moore J, Remy J, Altschul E, Chusid J, Flohr T, Raoof S, Remy-Jardin M. Thoracic Applications of Spectral CT Scan. Chest 2024; 165:417-430. [PMID: 37619663 DOI: 10.1016/j.chest.2023.07.4225] [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: 02/20/2023] [Revised: 07/29/2023] [Accepted: 07/31/2023] [Indexed: 08/26/2023] Open
Abstract
TOPIC IMPORTANCE Thoracic imaging with CT scan has become an essential component in the evaluation of respiratory and thoracic diseases. Providers have historically used conventional single-energy CT; however, prevalence of dual-energy CT (DECT) is increasing, and as such, it is important for thoracic physicians to recognize the utility and limitations of this technology. REVIEW FINDINGS The technical aspects of DECT are presented, and practical approaches to using DECT are provided. Imaging at multiple energy spectra allows for postprocessing of the data and the possibility of creating multiple distinct image reconstructions based on the clinical question being asked. The data regarding utility of DECT in pulmonary vascular disorders, ventilatory defects, and thoracic oncology are presented. A pictorial essay is provided to give examples of the strengths associated with DECT. SUMMARY DECT has been most heavily studied in chronic thromboembolic pulmonary hypertension; however, it is increasingly being used across a wide spectrum of thoracic diseases. DECT combines morphologic and functional assessments in a single imaging acquisition, providing clinicians with a powerful diagnostic tool. Its role in the evaluation and treatment of thoracic diseases will likely continue to expand in the coming years as clinicians become more experienced with the technology.
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Affiliation(s)
- Jonathan Moore
- Department of Pulmonary and Critical Care Medicine, Lenox Hill Hospital, Northwell Health Physician Partners, New York, NY
| | - Jacques Remy
- Univ Lille, Department of Thoracic Imaging, Lille, France
| | - Erica Altschul
- Department of Pulmonary and Critical Care Medicine, Lenox Hill Hospital, Northwell Health Physician Partners, New York, NY
| | - Jesse Chusid
- Feinstein Institutes for Medical Research, and Imaging Services, Department of Radiology, Northwell Health, Manhasset, NY
| | - Thomas Flohr
- Department of Computed Tomography Research & Development, Siemens Healthineers, Forchheim, Germany
| | - Suhail Raoof
- Department of Pulmonary and Critical Care Medicine, Lenox Hill Hospital, Northwell Health Physician Partners, New York, NY.
| | - Martine Remy-Jardin
- Univ Lille, Department of Thoracic Imaging, Lille, France; Univ Lille, CHU Lille, Evaluation des technologies de santé et des pratiques médicales, Lille, France
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Hu X, Shi S, Wang Y, Yuan J, Chen M, Wei L, Deng W, Feng ST, Peng Z, Luo Y. Dual-energy CT improves differentiation of non-hypervascular pancreatic neuroendocrine neoplasms from CA 19-9-negative pancreatic ductal adenocarcinomas. LA RADIOLOGIA MEDICA 2024; 129:1-13. [PMID: 37861978 DOI: 10.1007/s11547-023-01733-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 09/28/2023] [Indexed: 10/21/2023]
Abstract
PURPOSE To evaluate the utility of dual-energy CT (DECT) in differentiating non-hypervascular pancreatic neuroendocrine neoplasms (PNENs) from pancreatic ductal adenocarcinomas (PDACs) with negative carbohydrate antigen 19-9 (CA 19-9). METHODS This retrospective study included 26 and 39 patients with pathologically confirmed non-hypervascular PNENs and CA 19-9-negative PDACs, respectively, who underwent contrast-enhanced DECT before treatment between June 2019 and December 2021. The clinical, conventional CT qualitative, conventional CT quantitative, and DECT quantitative parameters of the two groups were compared using univariate analysis and selected by least absolute shrinkage and selection operator regression (LASSO) analysis. Multivariate logistic regression analyses were performed to build qualitative, conventional CT quantitative, DECT quantitative, and comprehensive models. The areas under the receiver operating characteristic curve (AUCs) of the models were compared using DeLong's test. RESULTS The AUCs of the DECT quantitative (based on normalized iodine concentrations [nICs] in the arterial and portal venous phases: 0.918; 95% confidence interval [CI] 0.852-0.985) and comprehensive (based on tumour location and nICs in the arterial and portal venous phases: 0.966; 95% CI 0.889-0.995) models were higher than those of the qualitative (based on tumour location: 0.782; 95% CI 0.665-0.899) and conventional CT quantitative (based on normalized conventional CT attenuation in the arterial phase: 0.665; 95% CI 0.533-0.797; all P < 0.05) models. The DECT quantitative and comprehensive models had comparable performances (P = 0.076). CONCLUSIONS Higher nICs in the arterial and portal venous phases were associated with higher blood supply improving the identification of non-hypervascular PNENs.
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Affiliation(s)
- Xuefang Hu
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China
- Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, 518000, Guangdong, China
| | - Siya Shi
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China
| | - Yangdi Wang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China
| | - Jiaxin Yuan
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China
| | - Mingjie Chen
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China
| | - Luyong Wei
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China
| | - Weiwei Deng
- Clinical and Technical Support, Philips Healthcare China, Shanghai, 200072, China
| | - Shi-Ting Feng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China
| | - Zhenpeng Peng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China.
| | - Yanji Luo
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China.
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Karout L, Digumarthy SR, Savage C, Fahimi R, Garza-Frias E, Kaviani P, Dasegowda G, Kalra MK. Low Contrast Volume Protocol in Routine Chest CT Amid the Global Contrast Shortage: A Single Institution Experience. Acad Radiol 2023; 30:2913-2920. [PMID: 37164818 DOI: 10.1016/j.acra.2023.03.020] [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: 12/19/2022] [Revised: 03/16/2023] [Accepted: 03/17/2023] [Indexed: 05/12/2023]
Abstract
OBJECTIVE To assess the effectiveness of low contrast volume (LCV) chest CT performed with multiple contrast agents on multivendor CT with varying scanning techniques. METHODS The study included 361 patients (65 ± 15 years; M: F 173:188) who underwent LCV chest CT on one of the six 64-256 detector-row CT scanners using single-energy (SECT) or dual-energy (DECT) modes. All patients were scanned with either a fixed-LCV (LCVf, n = 103) or weight-based LCV (LCVw, n = 258) protocol. Two thoracic radiologists independently assessed all LCV CT and patients' prior standard contrast volume (SCV, n = 263) chest CT for optimality of contrast enhancement in thoracic vasculature, cardiac chambers, and in pleuro-parenchymal and mediastinal abnormalities. CT attenuations were recorded in the main pulmonary trunk, ascending, and descending thoracic aorta. To assess the interobserver agreement, pulmonary arterial enhancement was divided into two groups: optimal or suboptimal. RESULTS There was no significant difference among patients' BMI (p = 0.883) in the three groups. DECT had a significantly higher aortic arterial enhancement (250 ± 99HU vs 228 ± 76 HU for SECT, p < 0.001). Optimal enhancement was present in 558 of 624 chest CT (89.4%), whereas 66 of 624 chest CT with suboptimal enhancement was noted in 48 of 258 LCVw (18.6%) and 14 of 103 LCVf (13.6%). Most patients with suboptimal enhancement with LCVw injection protocol were overweight/obese (30/48; 62.5%), (p < 0.001). CONCLUSION LCV chest CT can be performed across complex multivendor, multicontrast media, multiscanner, and multiprotocol CT practices. However, LCV chest CT examinations can result in suboptimal contrast enhancement in patients with larger body habitus.
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Affiliation(s)
- Lina Karout
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, 75 Blossom Court, Boston, Massachusetts, 02114
| | - Subba R Digumarthy
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, 75 Blossom Court, Boston, Massachusetts, 02114
| | - Cristy Savage
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Roshan Fahimi
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, 75 Blossom Court, Boston, Massachusetts, 02114
| | - Emiliano Garza-Frias
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, 75 Blossom Court, Boston, Massachusetts, 02114
| | - Parisa Kaviani
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, 75 Blossom Court, Boston, Massachusetts, 02114
| | - Giridhar Dasegowda
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, 75 Blossom Court, Boston, Massachusetts, 02114
| | - Mannudeep K Kalra
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, 75 Blossom Court, Boston, Massachusetts, 02114.
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Perrella A, Bagnacci G, Di Meglio N, Di Martino V, Mazzei MA. Thoracic Diseases: Technique and Applications of Dual-Energy CT. Diagnostics (Basel) 2023; 13:2440. [PMID: 37510184 PMCID: PMC10378112 DOI: 10.3390/diagnostics13142440] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/06/2023] [Accepted: 07/07/2023] [Indexed: 07/30/2023] Open
Abstract
Dual-energy computed tomography (DECT) is one of the most promising technological innovations made in the field of imaging in recent years. Thanks to its ability to provide quantitative and reproducible data, and to improve radiologists' confidence, especially in the less experienced, its applications are increasing in number and variety. In thoracic diseases, DECT is able to provide well-known benefits, although many recent articles have sought to investigate new perspectives. This narrative review aims to provide the reader with an overview of the applications and advantages of DECT in thoracic diseases, focusing on the most recent innovations. The research process was conducted on the databases of Pubmed and Cochrane. The article is organized according to the anatomical district: the review will focus on pleural, lung parenchymal, breast, mediastinal, lymph nodes, vascular and skeletal applications of DECT. In conclusion, considering the new potential applications and the evidence reported in the latest papers, DECT is progressively entering the daily practice of radiologists, and by reading this simple narrative review, every radiologist will know the state of the art of DECT in thoracic diseases.
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Affiliation(s)
- Armando Perrella
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, 53100 Siena, Italy
| | - Giulio Bagnacci
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, 53100 Siena, Italy
| | - Nunzia Di Meglio
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, 53100 Siena, Italy
| | - Vito Di Martino
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, 53100 Siena, Italy
| | - Maria Antonietta Mazzei
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, 53100 Siena, Italy
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Cheng F, Liu Y, Du L, Wang L, Li L, Shi J, Wang X, Zhang J. Evaluation of optimal monoenergetic images acquired by dual-energy CT in the diagnosis of T staging of thoracic esophageal cancer. Insights Imaging 2023; 14:33. [PMID: 36763193 PMCID: PMC9918671 DOI: 10.1186/s13244-023-01381-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 01/29/2023] [Indexed: 02/11/2023] Open
Abstract
OBJECTIVES The purpose of our study was to objectively and subjectively assess optimal monoenergetic image (MEI (+)) characteristics from dual-energy CT (DECT) and the diagnostic performance for the T staging in patients with thoracic esophageal cancer (EC). METHODS In this retrospective study, patients with histopathologically confirmed EC who underwent DECT from September 2019 to December 2020 were enrolled. One standard polyenergetic image (PEI) and five MEI (+) were reconstructed. Two readers independently assessed the lesion conspicuity subjectively and calculated the contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) of EC. Two readers independently assessed the T stage on the optimal MEI (+) and PEI subjectively. Multiple quantitative parameters were measured to assess the diagnostic performance to identify T1-2 from T3-4 in EC patients. RESULTS The study included 68 patients. Subjectively, primary tumor delineation received the highest ratings in MEI (+) 40 keV of the venous phase. Objectively, MEI (+) images showed significantly higher SNR compared with PEI (p < 0.05), peaking at MEI (+) 40 keV in the venous phase. CNR of tumor (MEI (+) 40 keV -80 keV) was all significantly higher than PEI in arterial and venous phases (p < 0.05), peaking at MEI (+) 40 keV in venous phases. The agreement between MEI (+) 40 keV and pathologic T categories was 81.63% (40/49). Rho values in venous phases had excellent diagnostic efficiency for identifying T1-2 from T3-4 (AUC = 0.84). CONCLUSIONS MEI (+) reconstructions at low keV in the venous phase improved the assessment of lesion conspicuity and also have great potential for preoperative assessment of T staging in patients with EC.
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Affiliation(s)
- Fanrong Cheng
- grid.190737.b0000 0001 0154 0904Department of Radiology, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing University Cancer Hospital, Chongqing, 400030 China ,People’s Hospital of Rongchang District, Chongqing, 402460 China
| | - Yan Liu
- grid.190737.b0000 0001 0154 0904Department of Radiology, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing University Cancer Hospital, Chongqing, 400030 China
| | - Lihong Du
- grid.190737.b0000 0001 0154 0904Department of Radiology, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing University Cancer Hospital, Chongqing, 400030 China
| | - Lei Wang
- grid.190737.b0000 0001 0154 0904Department of Radiology, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing University Cancer Hospital, Chongqing, 400030 China
| | - Lan Li
- grid.190737.b0000 0001 0154 0904Department of Radiology, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing University Cancer Hospital, Chongqing, 400030 China
| | - Jinfang Shi
- grid.190737.b0000 0001 0154 0904Department of Radiology, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing University Cancer Hospital, Chongqing, 400030 China
| | - Xiaoxia Wang
- Department of Radiology, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing University Cancer Hospital, Chongqing, 400030, China.
| | - Jiuquan Zhang
- Department of Radiology, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing University Cancer Hospital, Chongqing, 400030, China.
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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: 10] [Impact Index Per Article: 3.3] [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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10
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Zhang X, Zhang G, Xu L, Bai X, Lu X, Yu S, Sun H, Jin Z. Utilisation of virtual non-contrast images and virtual mono-energetic images acquired from dual-layer spectral CT for renal cell carcinoma: image quality and radiation dose. Insights Imaging 2022; 13:12. [PMID: 35072807 PMCID: PMC8787008 DOI: 10.1186/s13244-021-01146-8] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 12/18/2021] [Indexed: 12/23/2022] Open
Abstract
Background Renal cell carcinoma (RCC) is the most common renal malignant tumour. We evaluated the potential value and dose reduction of virtual non-contrast (VNC) images and virtual monoenergetic images (VMIs) from dual-layer spectral CT (DL-CT) in the diagnosis of RCC. Results Sixty-two patients with pathologically confirmed RCC who underwent contrast-enhanced DL-CT were retrospectively analysed. For the comparison between true non-contrast (TNC) and VNC images of the excretory phase, the attenuation, image noise, signal-to-noise ratio (SNR) and subjective image quality of tumours and different abdominal organs and tissues were evaluated. To compare corticomedullary phase images and low keV VMIs (40 to 100 keV) from the nephrographic phase, the attenuation, image noise, SNR and subjective lesion visibility of the tumours and renal arteries were evaluated. For the tumours, significant differences were not observed in attenuation, noise or SNR between TNC and VNC images (p > 0.05). For the abdominal organs and tissues, except for fat, the difference in attenuation was 100% within 15 HU and 96.78% within 10 HU. The subjective image quality of TNC and VNC images was equivalent (p > 0.05). The attenuation of lesions in 40 keV VMIs and renal arteries in 60 keV VMIs were similar to those in the corticomedullary images (p > 0.05). The subjective lesion visibility in low keV VMIs is slightly lower than that in the corticomedullary images (p < 0.05). Using VNC and VMIs instead of TNC and corticomedullary phase images could decrease the radiation dose by 50.5%. Conclusion VNC images and VMIs acquired from DL-CT can maintain good image quality and decrease the radiation dose for diagnosis of RCC.
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11
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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: 39] [Impact Index Per Article: 9.8] [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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12
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Gentili F, Guerrini S, Mazzei FG, Monteleone I, Di Meglio N, Sansotta L, Perrella A, Puglisi S, De Filippo M, Gennaro P, Volterrani L, Castagna MG, Dotta F, Mazzei MA. Dual energy CT in gland tumors: a comprehensive narrative review and differential diagnosis. Gland Surg 2020; 9:2269-2282. [PMID: 33447579 DOI: 10.21037/gs-20-543] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Dual energy CT (DECT)with image acquisition at two different photon X-ray levels allows the characterization of a specific tissue or material/elements, the extrapolation of virtual unenhanced and monoenergetic images, and the quantification of iodine uptake; such special capabilities make the DECT the perfect technique to support oncological imaging for tumor detection and characterization and treatment monitoring, while concurrently reducing the dose of radiation and iodine and improving the metal artifact reduction. Even though its potential in the field of oncology has not been fully explored yet, DECT is already widely used today thanks to the availability of different CT technologies, such as dual-source, single-source rapid-switching, single-source sequential, single-source twin-beam and dual-layer technologies. Moreover DECT technology represents the future of the imaging innovation and it is subject to ongoing development that increase according its clinical potentiality, in particular in the field of oncology. This review points out recent state-of-the-art in DECT applications in gland tumors, with special focus on its potential uses in the field of oncological imaging of endocrine and exocrine glands.
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Affiliation(s)
- Francesco Gentili
- Unit of Diagnostic Imaging, Department of Radiological Sciences, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Susanna Guerrini
- Unit of Diagnostic Imaging, Department of Radiological Sciences, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Francesco Giuseppe Mazzei
- Unit of Diagnostic Imaging, Department of Radiological Sciences, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Ilaria Monteleone
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Nunzia Di Meglio
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Letizia Sansotta
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Armando Perrella
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Sara Puglisi
- Unit of Radiology, Department of Medicine and Surgery, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Massimo De Filippo
- Unit of Radiology, Department of Medicine and Surgery, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Paolo Gennaro
- Department of Maxillofacial Surgery, University of Siena, Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - Luca Volterrani
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Maria Grazia Castagna
- Unit of Endocrinology, Department of Medical, Surgical and Neuro Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Francesco Dotta
- Unit of Diabetology, Department of Medical, Surgical and Neuro Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Maria Antonietta Mazzei
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
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