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Huang X, Zhang Z, Wang J, Yang Y, Hao T, Zhang S, Liu L, Wang G. Extracellular volume fraction of liver and pancreas using spectral CT in hypertensive patients: A comparative study. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2024:XST240130. [PMID: 39240616 DOI: 10.3233/xst-240130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/07/2024]
Abstract
BACKGROUND Besides the direct impact on the cardiovascular system, hypertension is closely associated with organ damage in the kidneys, liver, and pancreas. Chronic liver and pancreatic damage in hypertensive patients may be detectable via imaging. OBJECTIVE To explore the correlation between hypertension-related indicators and extracellular volume fraction (ECV) of liver and pancreas measured by iodine maps, and to evaluate corresponding clinical value in chronic damage of liver and pancreas in hypertensive patients. METHODS A prospective study from June to September 2023 included abdominal patients who underwent contrast-enhanced spectral CT. Normal and various grades of hypertensive blood pressure groups were compared. Upper abdominal iodine maps were constructed, and liver and pancreatic ECVs calculated. Kruskal-Wallis and Spearman analyses evaluated ECV differences and correlations with hypertension indicators. RESULTS In 300 patients, hypertensive groups showed significantly higher liver and pancreatic ECV than the normotensive group, with ECV rising alongside hypertension severity. ECVliver displayed a stronger correlation with hypertension stages compared to ECVpancreas. Regression analysis identified hypertension severity as an independent predictor for increased ECV. CONCLUSIONS ECVliver and ECVpancreas positively correlates with hypertension indicators and serves as a potential clinical marker for chronic organ damage due to hypertension, with ECVliver being more strongly associated than ECVpancreas.
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Affiliation(s)
- Xiaoming Huang
- Department of Radiology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Zhen Zhang
- Department of Radiology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jiansheng Wang
- Department of Radiology, Laixi People's Hospital, Laixi, China
| | - Yaqing Yang
- Department of Radiology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
- Graduate School, Dalian Medical University, Dalian, China
| | - Tianqi Hao
- Department of Radiology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
- Graduate School, Dalian Medical University, Dalian, China
| | - Shuai Zhang
- CT Imaging Research Center, GE Healthcare China, Shanghai, China
| | - Ling Liu
- CT Imaging Research Center, GE Healthcare China, Shanghai, China
| | - Guohua Wang
- Department of Radiology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
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Lu W, Tan X, Zhong Y, Wang P, Ge Y, Zhang H, Hu S. Spectral CT in the evaluation of perineural invasion status in rectal cancer. Jpn J Radiol 2024; 42:1012-1020. [PMID: 38709434 DOI: 10.1007/s11604-024-01575-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 04/15/2024] [Indexed: 05/07/2024]
Abstract
PURPOSE To investigate whether preoperative spectral CT quantitative parameters can assess perineural invasion (PNI) status in rectal cancer. METHODS Sixty-two patients diagnosed with rectal cancer who underwent preoperative spectral CT were retrospectively enrolled and divided into positive and negative PNI groups according to histopathologic results. The CT attenuation value (HU) of virtual monochromatic images (40-70 keV), spectral curve slope (K(HU)), effective atomic number (Zeff), and iodine concentration (IC) from spectral CT were compared between these two groups using t test or rank sum test. A nomogram was established by incorporating the independent predictors to assess the overall diagnostic efficacy. The area under the ROC curves (AUCs) were compared using the DeLong test. RESULTS The preoperative spectral CT parameters (40-70 keV attenuation, K(HU), Zeff, and IC) were significantly higher in the PNI-positive group compared to the PNI-negative group (all p < 0.05). The highest predictive efficiency of PNI was observed at 40 keV attenuation, with an area under the curve (AUC), sensitivity, specificity, and accuracy of 0.847, 81.8%, 72.5%, and 75.8%, respectively. Binary logistic regression demonstrated that the clinical feature (cN stage) and 40 keV attenuation were independent predictors of PNI status. The nomogram incorporating these two predictors (cN stage and 40 keV attenuation) exhibited the best evaluation efficacy, with an AUC, sensitivity, specificity, and accuracy of 0.885, 86.4%, 77.5%, and 80.6%. CONCLUSION Spectral CT quantitative parameters proved valuable in the preoperative assessment of PNI status in rectal cancer patients. The combination of spectral CT parameters and clinical features could further enhance the diagnostic efficiency.
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Affiliation(s)
- Wenzheng Lu
- Department of Radiology, Affiliated Hospital, Jiangnan University, No.1000, Hefeng Road, Wuxi, Jiangsu, 214000, China
| | - Xiaoying Tan
- Department of Radiology, Affiliated Hospital, Jiangnan University, No.1000, Hefeng Road, Wuxi, Jiangsu, 214000, China
| | - Yanqi Zhong
- Department of Radiology, Affiliated Hospital, Jiangnan University, No.1000, Hefeng Road, Wuxi, Jiangsu, 214000, China
| | - Peng Wang
- Department of Radiology, Affiliated Hospital, Jiangnan University, No.1000, Hefeng Road, Wuxi, Jiangsu, 214000, China
| | - Yuxi Ge
- Department of Radiology, Affiliated Hospital, Jiangnan University, No.1000, Hefeng Road, Wuxi, Jiangsu, 214000, China
| | - Heng Zhang
- Department of Radiology, Affiliated Hospital, Jiangnan University, No.1000, Hefeng Road, Wuxi, Jiangsu, 214000, China
| | - Shudong Hu
- Department of Radiology, Affiliated Hospital, Jiangnan University, No.1000, Hefeng Road, Wuxi, Jiangsu, 214000, China.
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Leng S, Toia GV, Hoodeshenas S, Ramirez-Giraldo JC, Yagil Y, Maltz JS, Boedeker K, Li K, Baffour F, Fletcher JG. Standardizing technical parameters and terms for abdominopelvic photon-counting CT: laying the groundwork for innovation and evidence sharing. Abdom Radiol (NY) 2024; 49:3261-3273. [PMID: 38769199 DOI: 10.1007/s00261-024-04342-4] [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: 03/01/2024] [Revised: 04/11/2024] [Accepted: 04/15/2024] [Indexed: 05/22/2024]
Abstract
Photon-counting detector CT (PCD-CT) is a new technology that has multiple diagnostic benefits including increased spatial resolution, iodine signal, and radiation dose efficiency, as well as multi-energy imaging capability, but which also has unique challenges in abdominal imaging. The purpose of this work is to summarize key features, technical parameters, and terms, which are common amongst current abdominopelvic PCD-CT systems and to propose standardized terminology (where none exists). In addition, user-selectable protocol parameters are highlighted to facilitate both scientific evaluation and early clinical adoption. Unique features of PCD-CT systems include photon-counting detectors themselves, energy thresholds and bins, and tube potential considerations for preserved spectral separation. Key parameters for describing different PCD-CT systems are reviewed and explained. While PCD-CT can generate multi-energy images like dual-energy CT, there are new types of images such as threshold images, energy bin images, and special spectral images. The standardized terms and concepts herein build upon prior interdisciplinary consensus and have been endorsed by the newly created Society of Abdominal Radiology Photon-counting CT Emerging Technology Commission.
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Affiliation(s)
- Shuai Leng
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Giuseppe V Toia
- Departments of Radiology and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Safa Hoodeshenas
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | | | - Yoad Yagil
- PD CT/AMI R&D Advanced Development, Philips Medical Systems, Haifa, Israel
| | - Jonathan S Maltz
- Molecular Imaging and Computed Tomography, GE Healthcare, Waukesha, WI, USA
| | | | - Ke Li
- Departments of Radiology and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Francis Baffour
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Joel G Fletcher
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
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Greffier J, Faby S, Pastor M, Frandon J, Erath J, Beregi JP, Dabli D. Comparison of low-energy virtual monoenergetic images between photon-counting CT and energy-integrating detectors CT: A phantom study. Diagn Interv Imaging 2024; 105:311-318. [PMID: 38429207 DOI: 10.1016/j.diii.2024.02.009] [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: 02/07/2024] [Revised: 02/17/2024] [Accepted: 02/19/2024] [Indexed: 03/03/2024]
Abstract
PURPOSE The purpose of this study was to assess image quality and dose level using a photon-counting CT (PCCT) scanner by comparison with a dual-source CT (DSCT) scanner on virtual monoenergetic images (VMIs) at low energy levels. MATERIALS AND METHODS A phantom was scanned using a DSCT and a PCCT with a volume CT dose index of 11 mGy, and additionally at 6 mGy and 1.8 mGy for PCCT. Noise power spectrum and task-based transfer function were evaluated from 40 to 70 keV on VMIs to assess noise magnitude and noise texture (fav) and spatial resolution on two iodine inserts (f50), respectively. A detectability index (d') was computed to assess the detection of two contrast-enhanced lesions according to the energy level used. RESULTS For all energy levels, noise magnitude values were lower with PCCT than with DSCT at 11 and 6 mGy, but greater at 1.8 mGy. fav values were higher with PCCT than with DSCT at 11 mGy (8.6 ± 1.5 [standard deviation [SD]%), similar at 6 mGy (1.6 ± 1.5 [SD]%) and lower at 1.8 mGy (-17.8 ± 2.2 [SD]%). For both inserts, f50 values were higher with PCCT than DSCT at 11- and 6 mGy for all keV levels, except at 6 mGy and 40 keV. d' values were higher with PCCT than with DSCT at 11- and 6 mGy for all keV and both simulated lesions. Similar d' values to those of the DSCT at 11 mGy, were obtained at 2.25 mGy for iodine insert at 2 mg/mL and at 0.96 mGy for iodine insert at 4 mg/mL at 40 keV. CONCLUSION Compared to DSCT, PCCT reduces noise magnitude and improves noise texture, spatial resolution and detectability on VMIs for all low-keV levels.
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Affiliation(s)
- Joël Greffier
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, France.
| | - Sebastian Faby
- Department of Computed Tomography, Siemens Healthineers AG, 91301 Forchheim, Germany
| | - Maxime Pastor
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, France
| | - Julien Frandon
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, France
| | - Julien Erath
- Department of Computed Tomography, Siemens Healthineers AG, 91301 Forchheim, Germany
| | - Jean Paul Beregi
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, France
| | - Djamel Dabli
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, France
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Qin T, Wang M, Fan Y, Wang J, Gao Z, Wang F, Li R, Li K, Ruan C, Liang B. Multivendor comparison of quantification accuracy of effective atomic number by Dual-Energy CT: A phantom study. Eur J Radiol 2024; 180:111690. [PMID: 39191039 DOI: 10.1016/j.ejrad.2024.111690] [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: 11/15/2023] [Revised: 03/10/2024] [Accepted: 08/19/2024] [Indexed: 08/29/2024]
Abstract
PURPOSE Our study aimed to compare the accuracy of the effective atomic number (Zeff) of five dual-energy CT (DECT) from three vendors and different generations under different scanning parameters. METHODS Zeff accuracy of five DECT scanners with twelve tube voltage configurations was evaluated by using the TomoTherapy cheese phantom. The potential dose dependence of the Zeff was investigated using three radiation dose (5, 15, and 25 mGy), and the robustness of Zeff was simulated for different organs of the body by placing the inserts at different positional depths. Bias and mean absolute percentage error (MAPE) were used to characterize the accuracy of Zeff. Data underwent analysis using one-way ANOVA, followed by the Turky and LSD post hoc tests, simple linear regression, and linear mixed models. RESULTS All tube voltage configurations had a bias of less than 1. Dual layer detector DECT (dl-DECT) -140 kV has the lowest MAPE (1.79 %±1.93 %). The third generation dual source DECT (ds-DECT) and the second generation rapid switch DECT (rs-DECT) have higher MAPE than their predecessor DECT. The results of the linear mixed model showed that tube voltage configuration (F=16.92, p < 0.001) and insert type (F=53.26, p < 0.001) significantly affect the MAPE. In contrast, radiation dose only has a significant effect on the MAPE of rs-DECT. The inserts position does not affect the final MAPE. CONCLUSION When scanning different inserts, Zeff accuracy varies by vendor and DECT generation. Of all the scanners, dl-DECT had the highest Zeff accuracy. Upgrading DECT generation doesn't lead to higher accuracy, or even lower.
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Affiliation(s)
- Tian Qin
- School of Medical Imaging, Bengbu Medical University, Bengbu, Anhui 233030, China
| | - Mengting Wang
- School of Medical Imaging, Bengbu Medical University, Bengbu, Anhui 233030, China
| | - Yihan Fan
- School of Medical Imaging, Bengbu Medical University, Bengbu, Anhui 233030, China
| | - Jing Wang
- Department of Radiology, Xuzhou Center Hospital, Xuzhou, Jiangsu 221000, China
| | - Zhizhen Gao
- Department of Radiology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, Anhui 233030, China
| | - Fan Wang
- Department of Radiology, Xuzhou First People's Hospital, Xuzhou, Jiangsu 221000, China
| | - Ruomei Li
- Department of Radiology, The Second People's Hospital of Hefei, Hefei, Anhui 230000, China
| | - Kui Li
- Department of Radiology, Xuzhou First People's Hospital, Xuzhou, Jiangsu 221000, China
| | - Chengcheng Ruan
- Department of Radiology, The Second People's Hospital of Hefei, Hefei, Anhui 230000, China
| | - Baohui Liang
- School of Medical Imaging, Bengbu Medical University, Bengbu, Anhui 233030, China.
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Chen Y, Wu T, Zhu Y, Chen J, Gao C, Wu L. Trends and hotspots of energy-based imaging in thoracic disease: a bibliometric analysis. Insights Imaging 2024; 15:209. [PMID: 39143273 PMCID: PMC11324624 DOI: 10.1186/s13244-024-01788-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 07/25/2024] [Indexed: 08/16/2024] Open
Abstract
OBJECTIVE To conduct a bibliometric analysis of the prospects and obstacles associated with dual- and multi-energy CT in thoracic disease, emphasizing its current standing, advantages, and areas requiring attention. METHODS The Web of Science Core Collection was queried for relevant publications in dual- and multi-energy CT and thoracic applications without a limit on publication date or language. The Bibliometrix packages, VOSviewer, and CiteSpace were used for data analysis. Bibliometric techniques utilized were co-authorship analyses, trend topics, thematic map analyses, thematic evolution analyses, source's production over time, corresponding author's countries, and a treemap of authors' keywords. RESULTS A total of 1992 publications and 7200 authors from 313 different sources were examined in this study. The first available document was published in November 1982, and the most cited article was cited 1200 times. Siemens AG in Germany emerged as the most prominent author affiliation, with a total of 221 published articles. The most represented scientific journals were the "European Radiology" (181 articles, h-index = 46), followed by the "European Journal of Radiology" (148 articles, h-index = 34). Most of the papers were from Germany, the USA, or China. Both the keyword and topic analyses showed the history of dual- and multi-energy CT and the evolution of its application hotspots in the chest. CONCLUSION Our study illustrates the latest advances in dual- and multi-energy CT and its increasingly prominent applications in the chest, especially in lung parenchymal diseases and coronary artery diseases. Photon-counting CT and artificial intelligence will be the emerging hot technologies that continue to develop in the future. CRITICAL RELEVANCE STATEMENT This study aims to provide valuable insights into energy-based imaging in chest disease, validating the clinical application of multi-energy CT together with photon-counting CT and effectively increasing utilization in clinical practice. KEY POINTS Bibliometric analysis is fundamental to understanding the current and future state of dual- and multi-energy CT. Research trends and leading topics included coronary artery disease, pulmonary embolism, and radiation dose. All analyses indicate a growing interest in the use of energy-based imaging techniques for thoracic applications.
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Affiliation(s)
- Yufan Chen
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Ting Wu
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yangtong Zhu
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Jiawei Chen
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Chen Gao
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China.
| | - Linyu Wu
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China.
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Grunz JP, Huflage H. Photon-Counting Detector CT Applications in Musculoskeletal Radiology. Invest Radiol 2024:00004424-990000000-00241. [PMID: 39088264 DOI: 10.1097/rli.0000000000001108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
ABSTRACT Photon-counting detectors (PCDs) have emerged as one of the most influential technical developments for medical imaging in recent memory. Surpassing conventional systems with energy-integrating detector technology in many aspects, PCD-CT scanners provide superior spatial resolution and dose efficiency for all radiological subspecialities. Demanding detailed display of trabecular microarchitecture and extensive anatomical coverage frequently within the same scan, musculoskeletal (MSK) imaging in particular can be a beneficiary of PCD-CT's remarkable performance. Since PCD-CT provides users with a plethora of customization options for both image acquisition and reconstruction, however, MSK radiologists need to be familiar with the scanner to unlock its full potential. From filter-based spectral shaping for artifact reduction over full field-of-view ultra-high-resolution scans to postprocessing of single- or dual-source multienergy data, almost every imaging task can be met with an optimized approach in PCD-CT. The objectives of this review were to give an overview of the most promising applications of PCD-CT in MSK imaging to date, to state current limitations, and to highlight directions for future research and developments.
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Affiliation(s)
- Jan-Peter Grunz
- From the Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany (J.G., H.H.); and Department of Radiology, University of Wisconsin-Madison, Madison, WI (J.G.)
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Greffier J, Faby S, Pastor M, Frandon J, Erath J, Beregi JP, Dabli D. Comparison of the spectral performance between two dual-source CT systems on low-energy virtual monoenergetic images: A phantom study. Phys Med 2024; 124:103429. [PMID: 39024963 DOI: 10.1016/j.ejmp.2024.103429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 07/01/2024] [Accepted: 07/08/2024] [Indexed: 07/20/2024] Open
Abstract
PURPOSE To compare the spectral performance of two different DSCT (DSCT-Pulse and DSCT-Force) on virtual monoenergetic images (VMIs) at low energy levels. METHODS An image quality phantom was scanned on the two DSCTs at three dose levels: 11/6/1.8 mGy. Level 3 of an advanced modeled iterative reconstruction algorithm was used. Noise power spectrum and task-based transfer function were computed on VMIs from 40 to 70 keV to assess noise magnitude and noise texture (fav) and spatial resolution (f50). A detectability index (d') was computed to assess the detection of one contrast-enhanced abdominal lesion as a function of the keV level used. RESULTS For all dose levels and all energy levels, noise magnitude was significantly higher (p < 0.05) with DSCT-Pulse than with DSCT-Force (12.6 ± 2.7 % at 1.8 mGy, 9.1 ± 2.9 % at 6 mGy and 4.0 ± 2.7 % at 11 mGy). For all energy levels, fav values were significantly higher (p < 0.05) with DSCT-Pulse than with DSCT-Force at 1.8 mGy (4.8 ± 3.9 %) and at 6 mGy (5.5 ± 2.5 %) but similar at 11 mGy (0.2 ± 3.6 %; p = 0.518). For all energy levels, f50 values were significantly higher with DSCT-Pulse than with DSCT-Force (12.7 ± 5.6 % at 1.8 mGy, 17.9 ± 4.5 % at 6 mGy and 13.1 ± 2.6 % at 11 mGy). For all keV, similar d' values were found with both DSCT-Force and DSCT-Pulse at 11 mGy (-1.0 ± 3.1 %; p = 0.084). For other dose levels, d' values were significantly lower with DSCT-Pulse than with DSCT-Force (9.1 ± 3.2 % at 1.8 mGy and -6.3 ± 3.9 % at 6 mGy). CONCLUSION Compared with the DSCT-Force, the DSCT-Pulse improved noise texture and spatial resolution, but noise magnitude was slightly higher and detectability slightly lower, particularly when the dose level was reduced.
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Affiliation(s)
- Joël Greffier
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30900 Nîmes, France.
| | - Sebastian Faby
- Department of Computed Tomography, Siemens Healthineers AG, Siemensstr. 3, 91301 Forchheim, Germany
| | - Maxime Pastor
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30900 Nîmes, France
| | - Julien Frandon
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30900 Nîmes, France
| | - Julien Erath
- Department of Computed Tomography, Siemens Healthineers AG, Siemensstr. 3, 91301 Forchheim, Germany
| | - Jean-Paul Beregi
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30900 Nîmes, France
| | - Djamel Dabli
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30900 Nîmes, France
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Yu Y, Han C, Gan X, Tian W, Zhou C, Zhou Y, Xu X, Wen Z, Liu W. Predictive value of spectral computed tomography parameters for EGFR gene mutation in non-small-cell lung cancer. Clin Radiol 2024; 79:e1049-e1056. [PMID: 38797609 DOI: 10.1016/j.crad.2024.04.019] [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: 11/27/2023] [Revised: 03/25/2024] [Accepted: 04/27/2024] [Indexed: 05/29/2024]
Abstract
AIM To explore the predictive value of morphological signs and quantitative parameters from spectral CT for EGFR gene mutations in intermediate and advanced non-small-cell lung cancer (NSCLC). MATERIALS AND METHODS This retrospective observational study included patients with intermediate or advanced NSCLC at Xinjiang Medical University Affiliated Tumor Hospital between January 2017 and December 2019. The patients were divided into the EGFR gene mutation-positive and -negative groups. RESULTS Seventy-nine patients aged 60.75 ± 9.66 years old were included: 32 were EGFR mutation-positive, and 47 were negative. There were significant differences in pathological stage (P<0.001), tumor diameter (P=0.019), lobulation sign, intrapulmonary metastasis, mediastinal lymph node metastasis, distant metastasis (P<0.001), bone metastasis (P<0.001), arterial phase normalized iodine concentration (NIC) (P=0.001), venous phase NIC (P=0.001), slope of the energy spectrum curve (λ) (P<0.001), and CT value at 70 keV in arterial phase (P=0.004) and venous phase (P=0.003) between the EGFR mutation-positive and -negative patients. The multivariable logistic regression analysis showed that intrapulmonary metastasis, distant metastasis, venous phase NIC, venous phase λ, and pathological stage were independent factors predicting EGFR gene mutations, with high diagnostic power (AUC = 0.975, 91.5% sensitivity, and 90.6% specificity). CONCLUSION The pathological stage and the spectral CT parameters of intrapulmonary metastasis, distant metastasis, venous phase NIC, and venous phase λ might pre-operatively predict EGFR gene mutations in intermediate and advanced NSCLC.
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Affiliation(s)
- Y Yu
- Department of Radiology, The First Affiliated Hospital of Xinjiang Medical University, Urumchi 830011, China; Department of Radiology, Xinjiang Medical University Affiliated Tumor Hospital, Urumchi 830011, China
| | - C Han
- Department of Laboratory, Traditional Chinese Medical Hospital of Xinjiang Uygur Autonomous Region, Urumchi 830011, China
| | - X Gan
- Department of Radiology, Xinjiang Medical University Affiliated Tumor Hospital, Urumchi 830011, China
| | - W Tian
- Department of Radiology, Xinjiang Medical University Affiliated Tumor Hospital, Urumchi 830011, China
| | - C Zhou
- Department of Radiology, Xinjiang Medical University Affiliated Tumor Hospital, Urumchi 830011, China
| | - Y Zhou
- Department of Radiology, Xinjiang Medical University Affiliated Tumor Hospital, Urumchi 830011, China
| | - X Xu
- Department of Radiology, Xinjiang Medical University Affiliated Tumor Hospital, Urumchi 830011, China
| | - Z Wen
- Department of Radiology, Xinjiang Medical University Affiliated Tumor Hospital, Urumchi 830011, China
| | - W Liu
- Department of Radiology, The First Affiliated Hospital of Xinjiang Medical University, Urumchi 830011, China.
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Boiset GR, Moratta R, Yoshimura EM, Costa PR. TEMPy: a toolkit for the modeling of weighted tissue equivalent material in diagnostic imaging. Phys Med Biol 2024; 69:15NT01. [PMID: 39008980 DOI: 10.1088/1361-6560/ad6371] [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: 04/17/2024] [Accepted: 07/15/2024] [Indexed: 07/17/2024]
Abstract
Objective.Accurate simulation of human tissues is imperative for advancements in diagnostic imaging, particularly in the fields of dosimetry and image quality evaluation. Developing Tissue Equivalent Materials (TEMs) with radiological characteristics akin to those of human tissues is essential for ensuring the reliability and relevance of imaging studies. This study presents the development of a mathematical model and a new toolkit (TEMPy) for obtaining the best composition of materials that mimic the radiological characteristics of human tissues. The model and the toolkit are described, along with an example showcasing its application to obtain desired TEMs.Approach.The methodology consisted of fitting volume fractions of the components of TEM in order to determine its linear attenuation coefficient as close as possible to the linear attenuation coefficient of the reference material. The fitting procedure adopted a modified Least Square Method including a weight function. This function reflects the contribution of the x-ray spectra in the suitable energy range of interest. TEMPy can also be used to estimate the effective atomic number and electron density of the resulting TEM.Main results.TEMPy was used to obtain the chemical composition of materials equivalent to water and soft tissue, in the energy range used in x-ray imaging (10 -150 keV) and for breast tissue using the energy range (5-40 keV). The maximum relative difference between the linear attenuation coefficients of the developed and reference materials was ±5% in the considered energy ranges.Significance.TEMPy facilitates the formulation of TEMs with radiological properties closely mimicking those of real tissues, aiding in the preparation of physical anthropomorphic or geometric phantoms for various applications. The toolkit is freely available to interested readers.
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Affiliation(s)
- Gisell R Boiset
- Institute of Physics, University of São Paulo, São Paulo, SP, Brazil
| | - Raphael Moratta
- Institute of Physics, University of São Paulo, São Paulo, SP, Brazil
| | | | - Paulo R Costa
- Institute of Physics, University of São Paulo, São Paulo, SP, Brazil
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11
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Nezami N, Malayeri AA. Sharper, Smarter, Safer: Unpacking the Potential of Photon-Counting CT in Urolithiasis Imaging. Radiology 2024; 312:e240497. [PMID: 39078304 PMCID: PMC11294758 DOI: 10.1148/radiol.240497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 03/14/2024] [Accepted: 03/15/2024] [Indexed: 07/31/2024]
Affiliation(s)
- Nariman Nezami
- From the Department of Radiology, MedStar Georgetown University
Hospital, 3800 Reservoir Rd NW, CCC Bldg, Rm CG225, Washington, DC 20007 (N.N.);
Georgetown University School of Medicine, Washington, DC (N.N.); Lombardi
Comprehensive Cancer Center, Washington, DC (N.N.); Fischell Department of
Bioengineering, University of Maryland College Park, College Park, Md (N.N.);
and Department of Radiology and Imaging Sciences, National Institutes of Health,
Bethesda, Md (A.A.M.)
| | - Ashkan A. Malayeri
- From the Department of Radiology, MedStar Georgetown University
Hospital, 3800 Reservoir Rd NW, CCC Bldg, Rm CG225, Washington, DC 20007 (N.N.);
Georgetown University School of Medicine, Washington, DC (N.N.); Lombardi
Comprehensive Cancer Center, Washington, DC (N.N.); Fischell Department of
Bioengineering, University of Maryland College Park, College Park, Md (N.N.);
and Department of Radiology and Imaging Sciences, National Institutes of Health,
Bethesda, Md (A.A.M.)
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12
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Macri F. Improved image quality and abdominal lesion detection with photon-counting CT compared to dual-source CT: New evidence from a phantom study. Diagn Interv Imaging 2024:S2211-5684(24)00143-8. [PMID: 38955610 DOI: 10.1016/j.diii.2024.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Accepted: 06/13/2024] [Indexed: 07/04/2024]
Affiliation(s)
- Francesco Macri
- Department of Radiology, Emergency and Trauma Radiology Unit, University Hospitals of Geneva, 1205 Geneva, Switzerland.
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13
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Xiao CH, Liu P, Zhang HH, Yang F, Chen X, Huang F, Liu JB, Tan XZ. Incremental diagnostic value of virtual non-contrast dual-energy CT for the diagnosis of choledocholithiasis over conventional unenhanced CT. Diagn Interv Imaging 2024; 105:292-298. [PMID: 38378382 DOI: 10.1016/j.diii.2024.02.004] [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: 09/27/2023] [Revised: 02/04/2024] [Accepted: 02/06/2024] [Indexed: 02/22/2024]
Abstract
PURPOSE The purpose of this study was to evaluate the incremental diagnostic value of virtual non-contrast (VNC) images derived from unenhanced dual-energy computed tomography (CT) for the diagnosis of choledocholithiasis by comparison with conventional unenhanced CT. MATERIALS AND METHODS Eighty-nine patients with gallbladder stones who had undergone both abdominal unenhanced dual-energy CT and magnetic resonance cholangiopancreatography (MRCP) were retrospectively included. There were 53 men and 36 women, with a mean age of 54 ± 13 (standard deviation) years (age range: 41-67 years). VNC and conventional CT images were generated. Two independent radiologists evaluated the presence of choledocholithiasis in three reading sessions (session 1, conventional unenhanced CT images; session 2, VNC images; session 3, conventional unenhanced CT plus VNC images). The reading time to identify choledocholithiasis was recorded. Inter-reader agreement was measured by using the Cohen kappa (κ) test. Incremental diagnostic value of VNC imaging when combined with conventional unenhanced CT was assessed based on discrimination (area under the curve [AUC]) and clinical utility (decision curve analysis). The diagnostic performance of dual-energy CT and that of MRCP were compared using DeLong test. RESULTS Using the standard of reference, 39 patients (39/89; 44%) had choledocholithiasis. The diagnosis of choledocholithiasis was improved using VNC images in combination with conventional unenhanced CT (AUC, 0.877; 95% confidence interval [CI]: 0.808, 0.947) by comparison with conventional unenhanced CT alone (AUC, 0.789; 95% CI: 0.718, 0.877) (P = 0.033) and achieved almost perfect inter-reader agreement (κ = 0.88; 95% CI: 0.72, 1.00) for the diagnosis of choledocholithiasis, without lengthening the median reading time (16.2 s for the combination of conventional CT and VNC images vs. 14.7 s for conventional CT alone; P= 0.325). Based on decision curve analysis, adding VNC imaging to conventional unenhanced CT resulted in a higher net benefit among most of decision thresholds. No differences in diagnostic performance were found between the combination of conventional unenhanced CT and VNC imaging (AUC, 0.877; 95% CI: 0.808, 0.947) and MRCP (AUC, 0.913; 95% CI: 0.852, 0.974) (P= 0.458). CONCLUSIONS VNC images derived from dual-energy unenhanced CT have incremental diagnostic value for the diagnosis of choledocholithiasis. Unenhanced CT in a dual-energy mode may be a useful tool for the diagnosis of choledocholithiasis.
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Affiliation(s)
- Chang-Hui Xiao
- Department of Radiology, Hunan Provincial People's Hospital, the First Affiliated Hospital of Hunan Normal University, Changsha 410005, China; Department of Radiology, Changde Hospital, Xiangya School of Medicine, Central South University, Changde 415000, Hunan, China
| | - Peng Liu
- Department of Radiology, Hunan Provincial People's Hospital, the First Affiliated Hospital of Hunan Normal University, Changsha 410005, China
| | - Hui-Hui Zhang
- Department of Radiology, Hunan Provincial People's Hospital, the First Affiliated Hospital of Hunan Normal University, Changsha 410005, China
| | - Fan Yang
- Department of Radiology, Hunan Provincial People's Hospital, the First Affiliated Hospital of Hunan Normal University, Changsha 410005, China
| | - Xiang Chen
- Department of Radiology, Hunan Provincial People's Hospital, the First Affiliated Hospital of Hunan Normal University, Changsha 410005, China
| | - Feng Huang
- Department of Radiology, Hunan Provincial People's Hospital, the First Affiliated Hospital of Hunan Normal University, Changsha 410005, China
| | - Jian-Bin Liu
- Department of Radiology, Hunan Provincial People's Hospital, the First Affiliated Hospital of Hunan Normal University, Changsha 410005, China
| | - Xian-Zheng Tan
- Department of Radiology, Hunan Provincial People's Hospital, the First Affiliated Hospital of Hunan Normal University, Changsha 410005, China.
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14
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Calame P, Mulé S. Dual-energy CT: Bridging the gap between innovation and clinical practice. Diagn Interv Imaging 2024; 105:247-248. [PMID: 38461060 DOI: 10.1016/j.diii.2024.02.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Accepted: 02/21/2024] [Indexed: 03/11/2024]
Affiliation(s)
- Paul Calame
- Department of Radiology, University of Bourgogne Franche-Comté, CHRU Besançon, 25030 Besançon, France; EA 4662 Nanomedicine Lab, Imagery and Therapeutics, University of Franche-Comté, 25030 Besançon, France.
| | - Sébastien Mulé
- Department of Radiology, Henri Mondor University Hospital, Faculty of Health, Paris-Est Créteil University, 94000 Créteil, France; INSERM IMRB, U 955, Team 18, 94000 Créteil, France
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15
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Grunz JP, Huflage H. Photon-Counting Computed Tomography: Experience in Musculoskeletal Imaging. Korean J Radiol 2024; 25:662-672. [PMID: 38942460 PMCID: PMC11214923 DOI: 10.3348/kjr.2024.0096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 03/28/2024] [Accepted: 04/19/2024] [Indexed: 06/30/2024] Open
Abstract
Since the emergence of the first photon-counting computed tomography (PCCT) system in late 2021, its advantages and a wide range of applications in all fields of radiology have been demonstrated. Compared to standard energy-integrating detector-CT, PCCT allows for superior geometric dose efficiency in every examination. While this aspect by itself is groundbreaking, the advantages do not stop there. PCCT facilitates an unprecedented combination of ultra-high-resolution imaging without dose penalty or field-of-view restrictions, detector-based elimination of electronic noise, and ubiquitous multi-energy spectral information. Considering the high demands of orthopedic imaging for the visualization of minuscule details while simultaneously covering large portions of skeletal and soft tissue anatomy, no subspecialty may benefit more from this novel detector technology than musculoskeletal radiology. Deeply rooted in experimental and clinical research, this review article aims to provide an introduction to the cosmos of PCCT, explain its technical basics, and highlight the most promising applications for patient care, while also mentioning current limitations that need to be overcome.
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Affiliation(s)
- Jan-Peter Grunz
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany.
| | - Henner Huflage
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany
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16
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Brendel JM, Walterspiel J, Hagen F, Kübler J, Paul JF, Nikolaou K, Gawaz M, Greulich S, Krumm P, Winkelmann M. Coronary artery disease evaluation during transcatheter aortic valve replacement work-up using photon-counting CT and artificial intelligence. Diagn Interv Imaging 2024; 105:273-280. [PMID: 38368176 DOI: 10.1016/j.diii.2024.01.010] [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: 12/11/2023] [Revised: 01/30/2024] [Accepted: 01/31/2024] [Indexed: 02/19/2024]
Abstract
PURPOSE The purpose of this study was to evaluate the capabilities of photon-counting (PC) CT combined with artificial intelligence-derived coronary computed tomography angiography (PC-CCTA) stenosis quantification and fractional flow reserve prediction (FFRai) for the assessment of coronary artery disease (CAD) in transcatheter aortic valve replacement (TAVR) work-up. MATERIALS AND METHODS Consecutive patients with severe symptomatic aortic valve stenosis referred for pre-TAVR work-up between October 2021 and June 2023 were included in this retrospective tertiary single-center study. All patients underwent both PC-CCTA and ICA within three months for reference standard diagnosis. PC-CCTA stenosis quantification (at 50% level) and FFRai (at 0.8 level) were predicted using two deep learning models (CorEx, Spimed-AI). Diagnostic performance for global CAD evaluation (at least one significant stenosis ≥ 50% or FFRai ≤ 0.8) was assessed. RESULTS A total of 260 patients (138 men, 122 women) with a mean age of 78.7 ± 8.1 (standard deviation) years (age range: 51-93 years) were evaluated. Significant CAD on ICA was present in 126/260 patients (48.5%). Per-patient sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy were 96.0% (95% confidence interval [CI]: 91.0-98.7), 68.7% (95% CI: 60.1-76.4), 74.3 % (95% CI: 69.1-78.8), 94.8% (95% CI: 88.5-97.8), and 81.9% (95% CI: 76.7-86.4) for PC-CCTA, and 96.8% (95% CI: 92.1-99.1), 87.3% (95% CI: 80.5-92.4), 87.8% (95% CI: 82.2-91.8), 96.7% (95% CI: 91.7-98.7), and 91.9% (95% CI: 87.9-94.9) for FFRai. Area under the curve of FFRai was 0.92 (95% CI: 0.88-0.95) compared to 0.82 for PC-CCTA (95% CI: 0.77-0.87) (P < 0.001). FFRai-guidance could have prevented the need for ICA in 121 out of 260 patients (46.5%) vs. 97 out of 260 (37.3%) using PC-CCTA alone (P < 0.001). CONCLUSION Deep learning-based photon-counting FFRai evaluation improves the accuracy of PC-CCTA ≥ 50% stenosis detection, reduces the need for ICA, and may be incorporated into the clinical TAVR work-up for the assessment of CAD.
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Affiliation(s)
- Jan M Brendel
- Department of Radiology, Diagnostic and Interventional Radiology, University of Tübingen, 72076 Germany
| | - Jonathan Walterspiel
- Department of Radiology, Diagnostic and Interventional Radiology, University of Tübingen, 72076 Germany
| | - Florian Hagen
- Department of Radiology, Diagnostic and Interventional Radiology, University of Tübingen, 72076 Germany
| | - Jens Kübler
- Department of Radiology, Diagnostic and Interventional Radiology, University of Tübingen, 72076 Germany
| | - Jean-François Paul
- Institut Mutualiste Montsouris, Department of Radiology, Cardiac Imaging, 75014 Paris, France; Spimed-AI, 75014 Paris, France
| | - Konstantin Nikolaou
- Department of Radiology, Diagnostic and Interventional Radiology, University of Tübingen, 72076 Germany
| | - Meinrad Gawaz
- Department of Internal Medicine III, Cardiology and Angiology, University of Tübingen, 72076 Germany
| | - Simon Greulich
- Department of Internal Medicine III, Cardiology and Angiology, University of Tübingen, 72076 Germany
| | - Patrick Krumm
- Department of Radiology, Diagnostic and Interventional Radiology, University of Tübingen, 72076 Germany.
| | - Moritz Winkelmann
- Department of Radiology, Diagnostic and Interventional Radiology, University of Tübingen, 72076 Germany
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17
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Chassagnon G, Revel MP. The trade-off dilemma between radiation dose and image resolution. Diagn Interv Imaging 2024:S2211-5684(24)00141-4. [PMID: 38945780 DOI: 10.1016/j.diii.2024.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Accepted: 06/12/2024] [Indexed: 07/02/2024]
Affiliation(s)
- Guillaume Chassagnon
- Department of Radiology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, 75014 Paris, France; Université Paris Cité, Faculté de Médecine, 75006 Paris, France.
| | - Marie-Pierre Revel
- Department of Radiology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, 75014 Paris, France; Université Paris Cité, Faculté de Médecine, 75006 Paris, France
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18
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Yao J, Ertl-Wagner BB, Dana J, Hanneman K, Kashif Al-Ghita M, Liu L, McInnes MDF, Nicolaou S, Reinhold C, Patlas MN. Canadian radiology: 2024 update. Diagn Interv Imaging 2024:S2211-5684(24)00140-2. [PMID: 38942638 DOI: 10.1016/j.diii.2024.06.004] [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: 06/11/2024] [Accepted: 06/11/2024] [Indexed: 06/30/2024]
Abstract
Radiology in Canada is advancing through innovations in clinical practices and research methodologies. Recent developments focus on refining evidence-based practice guidelines, exploring innovative imaging techniques and enhancing diagnostic processes through artificial intelligence. Within the global radiology community, Canadian institutions play an important role by engaging in international collaborations, such as with the American College of Radiology to refine implementation of the Ovarian-Adnexal Reporting and Data System for ultrasound and magnetic resonance imaging. Additionally, researchers have participated in multidisciplinary collaborations to evaluate the performance of artificial intelligence-driven diagnostic tools for chronic liver disease and pediatric brain tumors. Beyond clinical radiology, efforts extend to addressing gender disparities in the field, improving educational practices, and enhancing the environmental sustainability of radiology departments. These advancements highlight Canada's role in the global radiology community, showcasing a commitment to improving patient outcomes and advancing the field through research and innovation. This update underscores the importance of continued collaboration and innovation to address emerging challenges and further enhance the quality and efficacy of radiology practices worldwide.
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Affiliation(s)
- Jason Yao
- Department of Radiology, McMaster University, Hamilton, ON L8S4K1, Canada.
| | - Birgit B Ertl-Wagner
- Department of Diagnostic Imaging, Division of Neuroradiology, the Hospital for Sick Children, Toronto, ON M5G1X8, Canada; Department of Medical Imaging, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S1A8, Canada
| | - Jérémy Dana
- Department of Radiology, McGill University Health Centre, McGill University, Montreal, QC H3G1A4, Canada
| | - Kate Hanneman
- Department of Medical Imaging, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S1A8, Canada; University Medical Imaging Toronto, Joint Department of Medical Imaging, University Health Network (UHN), Toronto, ON M5G1X6, Canada
| | | | - Lulu Liu
- Department of Radiology, Vancouver General Hospital, University of British Columbia, Vancouver, BC V5Z1M9, Canada
| | - Matthew D F McInnes
- Faculty of Medicine, University of Ottawa, Ottawa, ON K1H8M5, Canada; Departments of Radiology and Epidemiology, University of Ottawa, Ottawa, ON K1H8L6, Canada; The Ottawa Hospital Research Institute, Clinical Epidemiology Program, Ottawa, ON K1H8L6, Canada
| | - Savvas Nicolaou
- Department of Radiology, Vancouver General Hospital, University of British Columbia, Vancouver, BC V5Z1M9, Canada
| | - Caroline Reinhold
- Department of Radiology, McGill University Health Centre, McGill University, Montreal, QC H3G1A4, Canada
| | - Michael N Patlas
- Department of Medical Imaging, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S1A8, Canada; University Medical Imaging Toronto, Joint Department of Medical Imaging, University Health Network (UHN), Toronto, ON M5G1X6, Canada
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19
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Skierbiszewska K, Szałaj U, Turek B, Sych O, Jasiński T, Łojkowski W, Domino M. Radiological properties of nano-hydroxyapatite compared to natural equine hydroxyapatite quantified using dual-energy CT and high-field MR. NANOMEDICINE : NANOTECHNOLOGY, BIOLOGY, AND MEDICINE 2024; 61:102765. [PMID: 38942131 DOI: 10.1016/j.nano.2024.102765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 06/02/2024] [Accepted: 06/13/2024] [Indexed: 06/30/2024]
Abstract
In equine medicine, assisted bone regeneration, including use of biomaterial substitutes like hydroxyapatite (HAP), is crucial for addressing bone defects. To follow-up on the outcome of HAP-based bone defect treatment, the advancement in quantified diagnostic imaging protocols is needed. This study aimed to quantify and compare the radiological properties of the HAP graft and natural equine bone using Magnetic Resonance (MR) and Computed Tomography (CT), both Single (SECT) and Dual Energy (DECT). SECT and DECT, allow for the differentiation of three HAP grain sizes, by progressive increase in relative density (RD). SECT, DECT, and MR enable the differentiation between natural cortical bone and synthetic HAP graft by augmentation in Effective Z and material density (MD) in HAP/Water, Calcium/Water, and Water/Calcium reconstructions, alongside the reduction in T2 relaxation time. The proposed quantification provided valuable radiological insights into the composition of HAP grafts, which may be useful in follow-up bone defect treatment.
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Affiliation(s)
- Katarzyna Skierbiszewska
- Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS - SGGW), 02-797 Warsaw, Poland
| | - Urszula Szałaj
- Laboratory of Nanostructures and Nanomedicine, Institute of High Pressure Physics, Polish Academy of Sciences, 01-142 Warsaw, Poland
| | - Bernard Turek
- Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS - SGGW), 02-797 Warsaw, Poland
| | - Olena Sych
- Laboratory of Nanostructures and Nanomedicine, Institute of High Pressure Physics, Polish Academy of Sciences, 01-142 Warsaw, Poland; Department of Functional Materials for Medical Application, Frantsevich Institute for Problems of Materials Science of NAS of Ukraine, Kyiv 03142, Ukraine
| | - Tomasz Jasiński
- Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS - SGGW), 02-797 Warsaw, Poland
| | - Witold Łojkowski
- Laboratory of Nanostructures and Nanomedicine, Institute of High Pressure Physics, Polish Academy of Sciences, 01-142 Warsaw, Poland
| | - Małgorzata Domino
- Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS - SGGW), 02-797 Warsaw, Poland.
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20
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Greffier J, Soyer P, Dabli D. Improving image quality of the middle ear with ultra-high-resolution CT coupled with deep-learning image reconstruction algorithm. Diagn Interv Imaging 2024; 105:211-212. [PMID: 38395667 DOI: 10.1016/j.diii.2024.02.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 02/09/2024] [Indexed: 02/25/2024]
Affiliation(s)
- Joël Greffier
- Department of Medical Imaging, IMAGINE UR UM 103, Montpellier University, Nîmes University Hospital, Nîmes 30029, France.
| | - Philippe Soyer
- Faculté de Médecine, Université Paris Cité, Paris 75006, France; Department of Radiology, Hopital Cochin, AP-HP, Paris 75014, France
| | - Djamel Dabli
- Department of Medical Imaging, IMAGINE UR UM 103, Montpellier University, Nîmes University Hospital, Nîmes 30029, France
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21
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de Jong CMM, Kroft LJM, van Mens TE, Huisman MV, Stöger JL, Klok FA. Modern imaging of acute pulmonary embolism. Thromb Res 2024; 238:105-116. [PMID: 38703584 DOI: 10.1016/j.thromres.2024.04.016] [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: 11/24/2023] [Revised: 03/16/2024] [Accepted: 04/15/2024] [Indexed: 05/06/2024]
Abstract
The first-choice imaging test for visualization of thromboemboli in the pulmonary vasculature in patients with suspected acute pulmonary embolism (PE) is multidetector computed tomography pulmonary angiography (CTPA) - a readily available and widely used imaging technique. Through technological advancements over the past years, alternative imaging techniques for the diagnosis of PE have become available, whilst others are still under investigation. In particular, the evolution of artificial intelligence (AI) is expected to enable further innovation in diagnostic management of PE. In this narrative review, current CTPA techniques and the emerging technology photon-counting CT (PCCT), as well as other modern imaging techniques of acute PE are discussed, including CTPA with iodine maps based on subtraction or dual-energy acquisition, single-photon emission CT (SPECT), magnetic resonance angiography (MRA), and magnetic resonance direct thrombus imaging (MRDTI). Furthermore, potential applications of AI are discussed.
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Affiliation(s)
- C M M de Jong
- Department of Medicine - Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands
| | - L J M Kroft
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - T E van Mens
- Department of Medicine - Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands
| | - M V Huisman
- Department of Medicine - Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands
| | - J L Stöger
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - F A Klok
- Department of Medicine - Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands.
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22
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Páez-Carpio A, Vollmer I, Zarco FX, Matute-González M, Domenech-Ximenos B, Serrano E, Barberà JA, Blanco I, Gómez FM. Imaging of chronic thromboembolic pulmonary hypertension before, during and after balloon pulmonary angioplasty. Diagn Interv Imaging 2024; 105:215-226. [PMID: 38413273 DOI: 10.1016/j.diii.2024.02.005] [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: 12/27/2023] [Revised: 02/07/2024] [Accepted: 02/09/2024] [Indexed: 02/29/2024]
Abstract
Balloon pulmonary angioplasty (BPA) has recently been elevated as a class I recommendation for the treatment of inoperable or residual chronic thromboembolic pulmonary hypertension (CTEPH). Proper patient selection, procedural safety, and post-procedural evaluation are crucial in the management of these patients, with imaging work-up playing a pivotal role. Understanding the diagnostic and therapeutic imaging algorithms of CTEPH, the imaging features of patients amenable to BPA, all imaging findings observed during and immediately after the procedure and the changes observed during the follow-up is crucial for all interventional radiologists involved in the care of patients with CTEPH. This article illustrates the imaging work-up of patients with CTEPH amenable to BPA, the imaging findings observed before, during and after BPA, and provides a detailed description of all imaging modalities available for CTEPH evaluation.
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Affiliation(s)
- Alfredo Páez-Carpio
- Department of Radiology, CDI, Hospital Clínic Barcelona, Barcelona 08036, Spain; Department of Medical Imaging, University of Toronto, Toronto M5T 1W7, ON, Canada; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain.
| | - Ivan Vollmer
- Department of Radiology, CDI, Hospital Clínic Barcelona, Barcelona 08036, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain
| | - Federico X Zarco
- Department of Radiology, CDI, Hospital Clínic Barcelona, Barcelona 08036, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain
| | | | | | - Elena Serrano
- Department of Radiology, Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat 08907, Spain
| | - Joan A Barberà
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain; Department of Pulmonary Medicine, ICR, Hospital Clínic Barcelona, Barcelona 08036, Spain; Biomedical Research Networking Centre on Respiratory Diseases (CIBERES), Madrid 28029, Spain
| | - Isabel Blanco
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain; Department of Pulmonary Medicine, ICR, Hospital Clínic Barcelona, Barcelona 08036, Spain; Biomedical Research Networking Centre on Respiratory Diseases (CIBERES), Madrid 28029, Spain
| | - Fernando M Gómez
- Interventional Radiology Unit, Department of Radiology, Hospital Universitari i Politècnic La Fe, València 46026, Spain; Interventional Radiology Unit, Department of Radiology, The Netherlands Cancer Institute, Amsterdam 1066 CX, the Netherlands
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23
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Beysang A, Villani N, Boubaker F, Puel U, Eliezer M, Hossu G, Haioun K, Blum A, Teixeira PAG, Parietti-Winkler C, Gillet R. Ultra-high-resolution CT of the temporal bone: Comparison between deep learning reconstruction and hybrid and model-based iterative reconstruction. Diagn Interv Imaging 2024; 105:233-242. [PMID: 38368178 DOI: 10.1016/j.diii.2024.02.001] [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: 12/21/2023] [Revised: 01/31/2024] [Accepted: 02/01/2024] [Indexed: 02/19/2024]
Abstract
PURPOSE The purpose of this study was to evaluate the ability of ultra-high-resolution computed tomography (UHR-CT) to assess stapes and chorda tympani nerve anatomy using a deep learning (DLR), a model-based, and a hybrid iterative reconstruction algorithm compared to simulated conventional CT. MATERIALS AND METHODS CT acquisitions were performed with a Mercury 4.0 phantom. Images were acquired with a 1024 × 1024 matrix and a 0.25 mm slice thickness and reconstructed using DLR, model-based, and hybrid iterative reconstruction algorithms. To simulate conventional CT, images were also reconstructed with a 512 × 512 matrix and a 0.5 mm slice thickness. Spatial resolution, noise power spectrum, and objective high-contrast detectability were compared. Three radiologists evaluated the clinical acceptability of these algorithms by assessing the thickness and image quality of the stapes footplate and superstructure elements, as well as the image quality of the chorda tympani nerve bony and tympanic segments using a 5-point confidence scale on 13 temporal bone CT examinations reconstructed with the four algorithms. RESULTS UHR-CT provided higher spatial resolution than simulated conventional CT at the penalty of higher noise. DLR and model-based iterative reconstruction provided better noise reduction than hybrid iterative reconstruction, and DLR had the highest detectability index, regardless of the dose level. All stapedial structure thicknesses were thinner using UHR-CT by comparison with conventional simulated CT (P < 0.009). DLR showed the best visualization scores compared to the other reconstruction algorithms (P < 0.032). CONCLUSION UHR-CT with DLR results in less noise than UHR-CT with hybrid iterative reconstruction and significantly improves stapes and tympanic chorda tympani nerve depiction compared to simulated conventional CT and UHR-CT with iterative reconstruction.
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Affiliation(s)
- Achille Beysang
- Guilloz Imaging Department, Central Hospital, University Hospital Center of Nancy, 54000, Nancy, France
| | - Nicolas Villani
- Guilloz Imaging Department, Central Hospital, University Hospital Center of Nancy, 54000, Nancy, France
| | - Fatma Boubaker
- Guilloz Imaging Department, Central Hospital, University Hospital Center of Nancy, 54000, Nancy, France
| | - Ulysse Puel
- Guilloz Imaging Department, Central Hospital, University Hospital Center of Nancy, 54000, Nancy, France; Université de Lorraine, INSERM, IADI, 54000, Nancy, France; Université de Lorraine, CIC, Innovation Technologique, University Hospital Center of Nancy, 54000, Nancy, France
| | - Michael Eliezer
- Department of Radiology, Hôpital Lariboisière, AP-HP, 75010 Paris, France
| | - Gabriela Hossu
- Université de Lorraine, INSERM, IADI, 54000, Nancy, France; Université de Lorraine, CIC, Innovation Technologique, University Hospital Center of Nancy, 54000, Nancy, France
| | - Karim Haioun
- Canon Medical Systems Corporation, Kawasaki-shi, 212-0015 Kanagawa, Japan
| | - Alain Blum
- Guilloz Imaging Department, Central Hospital, University Hospital Center of Nancy, 54000, Nancy, France; Université de Lorraine, INSERM, IADI, 54000, Nancy, France; Université de Lorraine, CIC, Innovation Technologique, University Hospital Center of Nancy, 54000, Nancy, France
| | - Pedro Augusto Gondim Teixeira
- Guilloz Imaging Department, Central Hospital, University Hospital Center of Nancy, 54000, Nancy, France; Université de Lorraine, INSERM, IADI, 54000, Nancy, France; Université de Lorraine, CIC, Innovation Technologique, University Hospital Center of Nancy, 54000, Nancy, France
| | - Cécile Parietti-Winkler
- ENT Surgery Department, Central Hospital, University Hospital Center of Nancy, 54000 Nancy, France
| | - Romain Gillet
- Guilloz Imaging Department, Central Hospital, University Hospital Center of Nancy, 54000, Nancy, France; Université de Lorraine, INSERM, IADI, 54000, Nancy, France; Université de Lorraine, CIC, Innovation Technologique, University Hospital Center of Nancy, 54000, Nancy, France.
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Mafeld S. Imaging techniques in balloon pulmonary angioplasty: A bright future ahead. Diagn Interv Imaging 2024; 105:213-214. [PMID: 38493044 DOI: 10.1016/j.diii.2024.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Accepted: 03/04/2024] [Indexed: 03/18/2024]
Affiliation(s)
- Sebastian Mafeld
- Department of Vascular & Interventional Radiology, University Health Network, Toronto, ON M5G 2N2, Canada; Department of Medical Imaging, Toronto General Hospital, University of Toronto, Toronto, ON M5G 2N2, Canada; UMIT, University Medical Imaging Toronto, Toronto, ON M5G 2N2, Canada.
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25
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Haag F, Emmrich SS, Hertel A, Rink JS, Nörenberg D, Schoenberg SO, Froelich MF. Virtual Non-Contrast versus True Native in Photon-Counting CT: Stability of Density of Upper Abdominal Organs and Vessels. Diagnostics (Basel) 2024; 14:1130. [PMID: 38893656 PMCID: PMC11171968 DOI: 10.3390/diagnostics14111130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 05/10/2024] [Accepted: 05/20/2024] [Indexed: 06/21/2024] Open
Abstract
The clinical use of photon-counting CT (PCCT) allows for the generation of virtual non-contrast (VNC) series from contrast-enhanced images. In routine clinical practice, specific issues such as ruling out acute bleeding require non-contrast images. The aim of this study is to evaluate the use of PCCT-derived VNC reconstructions in abdominal imaging. PCCT scans of 17 patients including early arterial, portal venous and native sequences were enrolled. VNC reconstructions have been calculated. In every sequence and VNC reconstruction, 10 ROIs were measured (portal vein, descending aorta, inferior vena cava, liver parenchyma, spleen parenchyma, erector spinae muscle, subcutaneous adipose tissue, first lumbar vertebral body, air, and psoas muscle) and density values were compared. The VNC reconstructions show significant changes in density compared to the contrast-enhanced images. However, there were no significant differences present between the true non-contrast (TNC) and any VNC reconstructions in the observed organs and vessels. Significant differences (p < 0.05) between the measured mean density values in the TNC versus VNC reconstructions were found in fat and bone tissue. The PCCT-derived VNC reconstructions seemed to be comparable to the TNC images, despite some deviations shown in the adipose tissue and bone structures. However, the further benefits in terms of specific clinical issues need to be evaluated.
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Affiliation(s)
- Florian Haag
- Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1–3, 68167 Mannheim, Germany
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26
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Hao W, Xu Z, Lin H, Yan F. Using Dual-source Photon-counting Detector CT to Simultaneously Quantify Fat and Iron Content: A Phantom Study. Acad Radiol 2024:S1076-6332(24)00281-2. [PMID: 38772799 DOI: 10.1016/j.acra.2024.04.044] [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: 03/19/2024] [Revised: 04/21/2024] [Accepted: 04/26/2024] [Indexed: 05/23/2024]
Abstract
RATIONALE AND OBJECTIVES To evaluate the feasibility of using photon-counting detector computed tomography (PCD CT) to simultaneously quantify fat and iron content MATERIALS AND METHODS: Phantoms with pure fat, pure iron and fat-iron deposition were scanned by two tube voltages (120 and 140 kV) and two image quality (IQ) settings (80 and 145). Using an iron-specific three-material decomposition algorithm, virtual noniron (VNI) and virtual iron content (VIC) images were generated at quantum iterative reconstruction (QIR) strength levels 1-4. RESULTS Significant linear correlations were observed between known fat content (FC) and VNI for pure fat phantoms (r = 0.981-0.999, p < 0.001) and between known iron content (IC) and VIC for pure iron phantoms (r = 0.897-0.975, p < 0.001). In fat-iron phantoms, the measurement for fat content of 5-30% demonstrated good linearity between FC and VNI (r = 0.919-0.990, p < 0.001), and VNI were not affected by 75, 150, and 225 µmol/g iron overload (p = 0.174-0.519). The measurement for iron demonstrated a linear range of 75-225 µmol/g between IC and VIC (r = 0.961-0.994, p < 0.001) and VIC was not confounded by the coexisting 5%, 20%, and 30% fat deposition (p = 0.943-0.999). The Bland-Altman of fat and iron measurements were not significantly different at varying tube voltages and IQ settings (all p > 0.05). No significant difference in VNI and VIC at QIR 1-4. CONCLUSION PCD CT can accurately and simultaneously quantify fat and iron, including scan parameters with lower radiation dose.
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Affiliation(s)
- Wanting Hao
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China.
| | - Zhihan Xu
- CT Collaboration, Siemens Healthcare Ltd., No. 278 Zhouzhu Road, Shanghai 200025, China.
| | - Huimin Lin
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China.
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China; Faculty of Medical Imaging Technology, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine.
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Greffier J, Dabli D, Faby S, Pastor M, Croisille C, de Oliveira F, Erath J, Beregi JP. Abdominal image quality and dose reduction with energy-integrating or photon-counting detectors dual-source CT: A phantom study. Diagn Interv Imaging 2024:S2211-5684(24)00120-7. [PMID: 38760277 DOI: 10.1016/j.diii.2024.05.002] [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: 02/29/2024] [Revised: 05/02/2024] [Accepted: 05/03/2024] [Indexed: 05/19/2024]
Abstract
PURPOSE The purpose of this study was to assess image-quality and dose reduction potential using a photon-counting computed tomography (PCCT) system by comparison with two different dual-source CT (DSCT) systems using two phantoms. MATERIALS AND METHODS Acquisitions on phantoms were performed using two DSCT systems (DSCT1 [Somatom Force] and DSCT2 [Somatom Pro.Pulse]) and one PCCT system (Naeotom Alpha) at four dose levels (13/6/3.4/1.8 mGy). Noise power spectrum (NPS) and task-based transfer function (TTF) were computed to assess noise magnitude and noise texture and spatial resolution (f50), respectively. Detectability indexes (d') were computed to model the detection of abdominal lesions: one unenhanced high-contrast task, one contrast-enhanced high-contrast task and one unenhanced low-contrast task. Image quality was subjectively assessed on an anthropomorphic phantom by two radiologists. RESULTS For all dose levels, noise magnitude values were lower with PCCT than with DSCTs. For all CT systems, similar noise texture values were found at 13 and 6 mGy, but the greatest noise texture values were found for DSCT2 and the lowest for PCCT at 3.4 and 1.8 mGy. For high-contrast inserts, similar or lower f50 values were found with PCCT than with DSCT1 and the opposite pattern was found for the low-contrast insert. For the three simulated lesions, d' values were greater with PCCT than with DSCTs. Abdominal images were rated satisfactory for clinical use by the radiologists for all dose levels with PCCT and for 13 and 6 mGy with DSCTs. CONCLUSION By comparison with DSCTs, PCCT reduces image-noise and improves detectability of simulated abdominal lesions without altering the spatial resolution and image texture. Image-quality obtained with PCCT seem to indicate greater potential for dose optimization than those obtained with DSCTs.
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Affiliation(s)
- Joël Greffier
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30900 Nîmes, France.
| | - Djamel Dabli
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30900 Nîmes, France
| | - Sebastian Faby
- Department of Computed Tomography, Siemens Healthineers AG, 91301 Forchheim, Germany
| | - Maxime Pastor
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30900 Nîmes, France
| | - Cédric Croisille
- Department of Computed Tomography, Siemens Healthineers AG, 91301 Forchheim, Germany
| | - Fabien de Oliveira
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30900 Nîmes, France
| | - Julien Erath
- Department of Computed Tomography, Siemens Healthineers AG, 91301 Forchheim, Germany
| | - Jean Paul Beregi
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30900 Nîmes, France
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28
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Deng L, Yang J, Zhang M, Zhu K, Jing M, Zhang Y, Zhang B, Han T, Zhou J. Whole-lesion iodine map histogram analysis versus single-slice spectral CT parameters for determining novel International Association for the Study of Lung Cancer grade of invasive non-mucinous pulmonary adenocarcinomas. Diagn Interv Imaging 2024; 105:165-173. [PMID: 38072730 DOI: 10.1016/j.diii.2023.12.001] [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: 09/18/2023] [Revised: 11/30/2023] [Accepted: 12/02/2023] [Indexed: 05/05/2024]
Abstract
PURPOSE The purpose of this study was to evaluate and compare the performances of whole-lesion iodine map histogram analysis to those of single-slice spectral computed tomography (CT) parameters in discriminating between low-to-moderate grade invasive non-mucinous pulmonary adenocarcinoma (INMA) and high-grade INMA according to the novel International Association for the Study of Lung Cancer grading system of INMA. MATERIALS AND METHODS Sixty-one patients with INMA (34 with low-to-moderate grade [i.e., grade I and grade II] and 27 with high grade [i.e., grade III]) were evaluated with spectral CT. There were 28 men and 33 women, with a mean age of 56.4 ± 10.5 (standard deviation) years (range: 29-78 years). The whole-lesion iodine map histogram parameters (mean, standard deviation, variance, skewness, kurtosis, entropy, and 1st, 10th, 25th, 50th, 75th, 90th, and 99th percentile) were measured for each INMA. In other sessions, by placing regions of interest at representative levels of the tumor and normalizing them, spectral CT parameters (iodine concentration and normalized iodine concentration) were obtained. Discriminating capabilities of spectral CT and histogram parameters were assessed and compared using area under the ROC curve (AUC) and logistic regression models. RESULTS The 1st, 10th, and 25th percentiles of the iodine map histogram analysis, and iodine concentration and normalized iodine concentration of single-slice spectral CT parameters were significantly different between high-grade and low-to-moderate grade INMAs (P < 0.001 to P = 0.002). The 1st percentile of histogram parameters (AUC, 0.84; 95% confidence interval [CI]: 0.73-0.92) and iodine concentration (AUC, 0.78; 95% CI: 0.66-0.88) from single-slice spectral CT parameters had the best performance for discriminating between high-grade and low-to-moderate grade INMAs. At ROC curve analysis no significant differences in AUC were found between histogram parameters (AUC = 0.86; 95% CI: 0.74-0.93) and spectral CT parameters (AUC = 0.81; 95% CI: 0.74-0.93) (P = 0.60). CONCLUSION Both whole-lesion iodine map histogram analysis and single-slice spectral CT parameters help discriminate between low-to-moderate grade and high-grade INMAs according to the novel International Association for the Study of Lung Cancer grading system, with no differences in diagnostic performances.
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Affiliation(s)
- Liangna Deng
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou 730000, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730000, China
| | - Jingjing Yang
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou 730000, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730000, China
| | - Mingtao Zhang
- Second Clinical School, Lanzhou University, Lanzhou 730000, China; Department of Orthopedics, Lanzhou University Second Hospital, 730000, China
| | - Kaibo Zhu
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou 730000, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730000, China
| | - Mengyuan Jing
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou 730000, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730000, China
| | - Yuting Zhang
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou 730000, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730000, China
| | - Bin Zhang
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou 730000, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730000, China
| | - Tao Han
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou 730000, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730000, China
| | - Junlin Zhou
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou 730000, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730000, China.
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29
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Barat M, Pellat A, Terris B, Dohan A, Coriat R, Fishman EK, Rowe SP, Chu L, Soyer P. Cinematic Rendering of Gastrointestinal Stromal Tumours: A Review of Current Possibilities and Future Developments. Can Assoc Radiol J 2024; 75:359-368. [PMID: 37982314 DOI: 10.1177/08465371231211278] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2023] Open
Abstract
Gastrointestinal stromal tumours (GISTs) are defined as CD117-positive primary, spindled or epithelioid, mesenchymal tumours of the gastrointestinal tract, omentum, or mesentery. While computed tomography (CT) is the recommended imaging modality for GISTs, overlap in imaging features between GISTs and other gastrointestinal tumours often make radiological diagnosis and subsequent selection of the optimal therapeutic approach challenging. Cinematic rendering is a novel CT post-processing technique that generates highly photorealistic anatomic images based on a unique lighting model. The global lighting model produces high degrees of surface detail and shadowing effects that generate depth in the final three-dimensional display. Early studies have shown that cinematic rendering produces high-quality images with enhanced detail by comparison with other three-dimensional visualization techniques. Cinematic rendering shows promise in improving the visualization of enhancement patterns and internal architecture of abdominal lesions, local tumour extension, and global disease burden, which may be helpful for lesion characterization and pretreatment planning. This article discusses and illustrates the application of cinematic rendering in the evaluation of GISTs and the unique benefit of using cinematic rendering in the workup of GIST with a specific emphasis on tumour characterization and preoperative planning.
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Affiliation(s)
- Maxime Barat
- Department of Radiology, Hôpital Cochin, Assistance Publique-Hopitaux de Paris, Paris, France
- Université Paris Cité, Faculté de Médecine, Paris, France
| | - Anna Pellat
- Université Paris Cité, Faculté de Médecine, Paris, France
- Department of Gastroenterology and Digestive Oncology, Hôpital Cochin, Assistance Publique-Hopitaux de Paris, Paris, France
| | - Benoit Terris
- Université Paris Cité, Faculté de Médecine, Paris, France
- Department of Pathology, Hôpital Cochin, Assistance Publique-Hopitaux de Paris, Paris, France
| | - Anthony Dohan
- Department of Radiology, Hôpital Cochin, Assistance Publique-Hopitaux de Paris, Paris, France
- Université Paris Cité, Faculté de Médecine, Paris, France
| | - Romain Coriat
- Université Paris Cité, Faculté de Médecine, Paris, France
- Department of Gastroenterology and Digestive Oncology, Hôpital Cochin, Assistance Publique-Hopitaux de Paris, Paris, France
| | - Elliot K Fishman
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Steven P Rowe
- Department of Radiology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Linda Chu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Philippe Soyer
- Department of Radiology, Hôpital Cochin, Assistance Publique-Hopitaux de Paris, Paris, France
- Université Paris Cité, Faculté de Médecine, Paris, France
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30
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Greffier J, Yagil Y, Erhard K, Douek PC, Si-Mohamed SA. Reply to the Letter to the Editor: Quantitative accuracy of virtual monoenergetic images from multi-energy CT. Eur Radiol 2024; 34:2960-2962. [PMID: 37934244 PMCID: PMC11126428 DOI: 10.1007/s00330-023-10286-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 07/23/2023] [Accepted: 08/09/2023] [Indexed: 11/08/2023]
Affiliation(s)
- Joel Greffier
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France
| | | | | | - Philippe C Douek
- University Lyon, INSA-Lyon, University Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621, 7 Avenue Jean Capelle O, 69100, Villeurbanne, France
- Department of Cardiothoracic Radiology, CHU Cardiologique Louis Pradel, 59 Boulevard Pinel, 69500, Bron, France
| | - Salim A Si-Mohamed
- University Lyon, INSA-Lyon, University Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621, 7 Avenue Jean Capelle O, 69100, Villeurbanne, France.
- Department of Cardiothoracic Radiology, CHU Cardiologique Louis Pradel, 59 Boulevard Pinel, 69500, Bron, France.
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31
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Meloni A, Maffei E, Clemente A, De Gori C, Occhipinti M, Positano V, Berti S, La Grutta L, Saba L, Cau R, Bossone E, Mantini C, Cavaliere C, Punzo B, Celi S, Cademartiri F. Spectral Photon-Counting Computed Tomography: Technical Principles and Applications in the Assessment of Cardiovascular Diseases. J Clin Med 2024; 13:2359. [PMID: 38673632 PMCID: PMC11051476 DOI: 10.3390/jcm13082359] [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: 03/16/2024] [Revised: 04/15/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
Spectral Photon-Counting Computed Tomography (SPCCT) represents a groundbreaking advancement in X-ray imaging technology. The core innovation of SPCCT lies in its photon-counting detectors, which can count the exact number of incoming x-ray photons and individually measure their energy. The first part of this review summarizes the key elements of SPCCT technology, such as energy binning, energy weighting, and material decomposition. Its energy-discriminating ability represents the key to the increase in the contrast between different tissues, the elimination of the electronic noise, and the correction of beam-hardening artifacts. Material decomposition provides valuable insights into specific elements' composition, concentration, and distribution. The capability of SPCCT to operate in three or more energy regimes allows for the differentiation of several contrast agents, facilitating quantitative assessments of elements with specific energy thresholds within the diagnostic energy range. The second part of this review provides a brief overview of the applications of SPCCT in the assessment of various cardiovascular disease processes. SPCCT can support the study of myocardial blood perfusion and enable enhanced tissue characterization and the identification of contrast agents, in a manner that was previously unattainable.
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Affiliation(s)
- Antonella Meloni
- Bioengineering Unit, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.M.); (V.P.)
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Erica Maffei
- Department of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico SYNLAB SDN, 80131 Naples, Italy; (E.M.); (C.C.); (B.P.)
| | - Alberto Clemente
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Carmelo De Gori
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Mariaelena Occhipinti
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Vicenzo Positano
- Bioengineering Unit, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.M.); (V.P.)
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Sergio Berti
- Diagnostic and Interventional Cardiology Department, Fondazione G. Monasterio CNR-Regione Toscana, 54100 Massa, Italy;
| | - Ludovico La Grutta
- Department of Radiology, University Hospital “P. Giaccone”, 90127 Palermo, Italy;
| | - Luca Saba
- Department of Radiology, University Hospital of Cagliari, 09042 Monserrato (CA), Italy; (L.S.); (R.C.)
| | - Riccardo Cau
- Department of Radiology, University Hospital of Cagliari, 09042 Monserrato (CA), Italy; (L.S.); (R.C.)
| | - Eduardo Bossone
- Department of Cardiology, Ospedale Cardarelli, 80131 Naples, Italy;
| | - Cesare Mantini
- Department of Radiology, “G. D’Annunzio” University, 66100 Chieti, Italy;
| | - Carlo Cavaliere
- Department of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico SYNLAB SDN, 80131 Naples, Italy; (E.M.); (C.C.); (B.P.)
| | - Bruna Punzo
- Department of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico SYNLAB SDN, 80131 Naples, Italy; (E.M.); (C.C.); (B.P.)
| | - Simona Celi
- BioCardioLab, Fondazione G. Monasterio CNR-Regione Toscana, 54100 Massa, Italy;
| | - Filippo Cademartiri
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
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Liu F, Yao Y, Zhu B, Yu Y, Ren R, Hu Y. The novel imaging methods in diagnosis and assessment of cerebrovascular diseases: an overview. Front Med (Lausanne) 2024; 11:1269742. [PMID: 38660416 PMCID: PMC11039813 DOI: 10.3389/fmed.2024.1269742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Accepted: 03/27/2024] [Indexed: 04/26/2024] Open
Abstract
Cerebrovascular diseases, including ischemic strokes, hemorrhagic strokes, and vascular malformations, are major causes of morbidity and mortality worldwide. The advancements in neuroimaging techniques have revolutionized the field of cerebrovascular disease diagnosis and assessment. This comprehensive review aims to provide a detailed analysis of the novel imaging methods used in the diagnosis and assessment of cerebrovascular diseases. We discuss the applications of various imaging modalities, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and angiography, highlighting their strengths and limitations. Furthermore, we delve into the emerging imaging techniques, including perfusion imaging, diffusion tensor imaging (DTI), and molecular imaging, exploring their potential contributions to the field. Understanding these novel imaging methods is necessary for accurate diagnosis, effective treatment planning, and monitoring the progression of cerebrovascular diseases.
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Affiliation(s)
- Fei Liu
- Neuroscience Intensive Care Unit, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Ying Yao
- Neuroscience Intensive Care Unit, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Bingcheng Zhu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yue Yu
- Neuroscience Intensive Care Unit, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Reng Ren
- Neuroscience Intensive Care Unit, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yinghong Hu
- Neuroscience Intensive Care Unit, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
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Pezel T, Habert P. Can coronary CT angiography be used as the new gold-standard for quantifying coronary artery disease burden? Diagn Interv Imaging 2024; 105:127-128. [PMID: 38212228 DOI: 10.1016/j.diii.2024.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Accepted: 01/01/2024] [Indexed: 01/13/2024]
Affiliation(s)
- Théo Pezel
- Université Paris Cité, Service de Radiologie, Hôpital Lariboisière, Assistance Publique des Hôpitaux de Paris, AP-HP, 75010, Paris, France; Université Paris Cité, Service de Cardiologie, Hôpital Lariboisière, Assistance Publique des Hôpitaux de Paris, AP-HP, 75010, Paris, France; Inserm MASCOT - UMRS 942, Hôpital Lariboisière, 75010, Paris, France
| | - Paul Habert
- Department of Radiology, Hôpital Nord, APHM, Aix Marseille Université, 13015 Marseille, France; Aix Marseille Univ, LIIE, 13005 Marseille, France.
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Eibschutz LS, Matcuk G, Chiu MKJ, Lu MY, Gholamrezanezhad A. Updates on the Applications of Spectral Computed Tomography for Musculoskeletal Imaging. Diagnostics (Basel) 2024; 14:732. [PMID: 38611645 PMCID: PMC11011285 DOI: 10.3390/diagnostics14070732] [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: 02/27/2024] [Revised: 03/20/2024] [Accepted: 03/26/2024] [Indexed: 04/14/2024] Open
Abstract
Spectral CT represents a novel imaging approach that can noninvasively visualize, quantify, and characterize many musculoskeletal pathologies. This modality has revolutionized the field of radiology by capturing CT attenuation data across multiple energy levels and offering superior tissue characterization while potentially minimizing radiation exposure compared to traditional enhanced CT scans. Despite MRI being the preferred imaging method for many musculoskeletal conditions, it is not viable for some patients. Moreover, this technique is time-consuming, costly, and has limited availability in many healthcare settings. Thus, spectral CT has a considerable role in improving the diagnosis, characterization, and treatment of gout, inflammatory arthropathies, degenerative disc disease, osteoporosis, occult fractures, malignancies, ligamentous injuries, and other bone-marrow pathologies. This comprehensive review will delve into the diverse capabilities of dual-energy CT, a subset of spectral CT, in addressing these musculoskeletal conditions and explore potential future avenues for its integration into clinical practice.
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Affiliation(s)
- Liesl S. Eibschutz
- Department of Radiology, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA 90007, USA (M.K.-J.C.); (M.Y.L.)
| | - George Matcuk
- Department of Radiology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Michael Kuo-Jiun Chiu
- Department of Radiology, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA 90007, USA (M.K.-J.C.); (M.Y.L.)
| | - Max Yang Lu
- Department of Radiology, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA 90007, USA (M.K.-J.C.); (M.Y.L.)
| | - Ali Gholamrezanezhad
- Department of Radiology, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA 90007, USA (M.K.-J.C.); (M.Y.L.)
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Grange R, Si-Mohamed S, Kepenekian V, Boccalini S, Glehen O, Rousset P. Spectral photon-counting CT: Hype or hope for colorectal peritoneal metastases imaging? Diagn Interv Imaging 2024; 105:118-120. [PMID: 38262873 DOI: 10.1016/j.diii.2024.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Revised: 01/03/2024] [Accepted: 01/05/2024] [Indexed: 01/25/2024]
Affiliation(s)
- Rémi Grange
- Department of Radiology, University Hospital of Saint-Etienne, 42270 Saint-Priest-en-Jarez, France
| | - Salim Si-Mohamed
- University of Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, 69100 Villeurbanne, France; Department of Radiology, Hôpital Louis Pradel, Hospices Civils de Lyon, 69500 Bron, France.
| | - Vahan Kepenekian
- Department of General Surgery & Surgical Oncology, CHU Lyon-Sud, Hospices Civils de Lyon, EMR 3738, Lyon 1 University, 69495 Pierre Bénite, Lyon, France
| | - Sara Boccalini
- University of Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, 69100 Villeurbanne, France; Department of Radiology, Hôpital Louis Pradel, Hospices Civils de Lyon, 69500 Bron, France
| | - Olivier Glehen
- Department of General Surgery & Surgical Oncology, CHU Lyon-Sud, Hospices Civils de Lyon, EMR 3738, Lyon 1 University, 69495 Pierre Bénite, Lyon, France
| | - Pascal Rousset
- Department of Radiology, CHU Lyon Sud, Hospices Civils de Lyon, EMR 3738, Lyon 1 University, 69495 Pierre Bénite, France
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Barat M, Pellat A, Hoeffel C, Dohan A, Coriat R, Fishman EK, Nougaret S, Chu L, Soyer P. CT and MRI of abdominal cancers: current trends and perspectives in the era of radiomics and artificial intelligence. Jpn J Radiol 2024; 42:246-260. [PMID: 37926780 DOI: 10.1007/s11604-023-01504-0] [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: 09/13/2023] [Accepted: 10/12/2023] [Indexed: 11/07/2023]
Abstract
Abdominal cancers continue to pose daily challenges to clinicians, radiologists and researchers. These challenges are faced at each stage of abdominal cancer management, including early detection, accurate characterization, precise assessment of tumor spread, preoperative planning when surgery is anticipated, prediction of tumor aggressiveness, response to therapy, and detection of recurrence. Technical advances in medical imaging, often in combination with imaging biomarkers, show great promise in addressing such challenges. Information extracted from imaging datasets owing to the application of radiomics can be used to further improve the diagnostic capabilities of imaging. However, the analysis of the huge amount of data provided by these advances is a difficult task in daily practice. Artificial intelligence has the potential to help radiologists in all these challenges. Notably, the applications of AI in the field of abdominal cancers are expanding and now include diverse approaches for cancer detection, diagnosis and classification, genomics and detection of genetic alterations, analysis of tumor microenvironment, identification of predictive biomarkers and follow-up. However, AI currently has some limitations that need further refinement for implementation in the clinical setting. This review article sums up recent advances in imaging of abdominal cancers in the field of image/data acquisition, tumor detection, tumor characterization, prognosis, and treatment response evaluation.
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Affiliation(s)
- Maxime Barat
- Department of Radiology, Hôpital Cochin, Assistance Publique-Hopitaux de Paris, 75014, Paris, France
- Faculté de Médecine, Université Paris Cité, 75006, Paris, France
| | - Anna Pellat
- Faculté de Médecine, Université Paris Cité, 75006, Paris, France
- Department of Gastroenterology and Digestive Oncology, Hôpital Cochin, Assistance Publique-Hopitaux de Paris, 75014, Paris, France
| | - Christine Hoeffel
- Department of Radiology, Hopital Robert Debré, CHU Reims, Université Champagne-Ardennes, 51092, Reims, France
| | - Anthony Dohan
- Department of Radiology, Hôpital Cochin, Assistance Publique-Hopitaux de Paris, 75014, Paris, France
- Faculté de Médecine, Université Paris Cité, 75006, Paris, France
| | - Romain Coriat
- Faculté de Médecine, Université Paris Cité, 75006, Paris, France
- Department of Gastroenterology and Digestive Oncology, Hôpital Cochin, Assistance Publique-Hopitaux de Paris, 75014, Paris, France
| | - Elliot K Fishman
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Stéphanie Nougaret
- Department of Radiology, Montpellier Cancer Institute, 34000, Montpellier, France
- PINKCC Lab, IRCM, U1194, 34000, Montpellier, France
| | - Linda Chu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Philippe Soyer
- Department of Radiology, Hôpital Cochin, Assistance Publique-Hopitaux de Paris, 75014, Paris, France.
- Faculté de Médecine, Université Paris Cité, 75006, Paris, France.
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Sartoretti T, Mergen V, Dzaferi A, Allmendinger T, Manka R, Alkadhi H, Eberhard M. Effect of temporal resolution on calcium scoring: insights from photon-counting detector CT. THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING 2024:10.1007/s10554-024-03070-6. [PMID: 38389028 DOI: 10.1007/s10554-024-03070-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 02/13/2024] [Indexed: 02/24/2024]
Abstract
To intra-individually investigate the variation of coronary artery calcium (CAC), aortic valve calcium (AVC), and mitral annular calcium (MAC) scores and the presence of blur artifacts as a function of temporal resolution in patients undergoing non-contrast cardiac CT on a dual-source photon counting detector (PCD) CT. This retrospective, IRB-approved study included 70 patients (30 women, 40 men, mean age 78 ± 9 years) who underwent ECG-gated cardiac non-contrast CT with PCD-CT (gantry rotation time 0.25 s) prior to transcatheter aortic valve replacement. Each scan was reconstructed at a temporal resolution of 66 ms using the dual-source information and at 125 ms using the single-source information. Average heart rate and heart rate variability were calculated from the recorded ECG. CAC, AVC, and MAC were quantified according to the Agatston method on images with both temporal resolutions. Two readers assessed blur artifacts using a 4-point visual grading scale. The influence of average heart rate and heart rate variability on calcium quantification and blur artifacts of the respective structures were analyzed by linear regression analysis. Mean heart rate and heart rate variability during data acquisition were 76 ± 17 beats per minute (bpm) and 4 ± 6 bpm, respectively. CAC scores were smaller on 66 ms (median, 511; interquartile range, 220-978) than on 125 ms reconstructions (538; 203-1050, p < 0.001). Median AVC scores [2809 (2009-3952) versus 3177 (2158-4273)] and median MAC scores [226 (0-1284) versus 251 (0-1574)] were also significantly smaller on 66ms than on 125ms reconstructions (p < 0.001). Reclassification of CAC and AVC risk categories occurred in 4% and 11% of cases, respectively, whereby the risk category was always overestimated on 125ms reconstructions. Image blur artifacts were significantly less on 66ms as opposed to 125 ms reconstructions (p < 0.001). Intra-individual analyses indicate that temporal resolution significantly impacts on calcium scoring with cardiac CT, with CAC, MAC, and AVC being overestimated at lower temporal resolution because of increased motion artifacts eventually leading to an overestimation of patient risk.
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Affiliation(s)
- Thomas Sartoretti
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
| | - Victor Mergen
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
| | - Amina Dzaferi
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
| | | | - Robert Manka
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
- Department of Cardiology, University Heart Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Hatem Alkadhi
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
| | - Matthias Eberhard
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091, Zurich, Switzerland.
- Radiology, Spital Interlaken, Spitäler fmi AG, Unterseen, Switzerland.
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Cuau L, Akl P, Gautheron A, Houmeau A, Chaput F, Yaromina A, Dubois L, Lambin P, Karpati S, Parola S, Rezaeifar B, Langlois JB, Si-Mohamed SA, Montcel B, Douek P, Lerouge F. Surface modification effect on contrast agent efficiency for X-ray based spectral photon-counting scanner/luminescence imaging: from fundamental study to in vivo proof of concept. NANOSCALE 2024; 16:2931-2944. [PMID: 38230699 DOI: 10.1039/d3nr03710j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
X-Ray imaging techniques are among the most widely used modalities in medical imaging and their constant evolution has led to the emergence of new technologies. The new generation of computed tomography (CT) systems - spectral photonic counting CT (SPCCT) and X-ray luminescence optical imaging - are examples of such powerful techniques. With these new technologies the rising demand for new contrast agents has led to extensive research in the field of nanoparticles and the possibility to merge the modalities appears to be highly attractive. In this work, we propose the design of lanthanide-based nanocrystals as a multimodal contrast agent with the two aforementioned technologies, allowing SPCCT and optical imaging at the same time. We present a systematic study on the effect of the Tb3+ doping level and surface modification on the generation of contrast with SPCCT and the luminescence properties of GdF3:Tb3+ nanocrystals (NCs), comparing different surface grafting with organic ligands and coatings with silica to make these NCs bio-compatible. A comparison of the luminescence properties of these NCs with UV revealed that the best results were obtained for the Gd0.9Tb0.1F3 composition. This property was confirmed under X-ray excitation in microCT and with SPCCT. Moreover, we could demonstrate that the intensity of the luminescence and the excited state lifetime are strongly affected by the surface modification. Furthermore, whatever the chemical nature of the ligand, the contrast with SPCCT did not change. Finally, the successful proof of concept of multimodal imaging was performed in vivo with nude mice in the SPCCT taking advantage of the so-called color K-edge imaging method.
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Affiliation(s)
- Loic Cuau
- Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS UMR 5182, Université Claude Bernard Lyon 1, Laboratoire de Chimie, 46 allée d'Italie, F69364 Lyon, France.
| | - Pia Akl
- Université de Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69621, Lyon, France
- Department of Radiology, Hospices Civils de Lyon, 69500 Bron, France
| | - A Gautheron
- Université de Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69621, Lyon, France
- Université Jean Monnet Saint-Etienne, CNRS, Institut d'Optique Graduate School, Laboratoire Hubert Curien UMR 5516, F-42023, Saint-Etienne, France
| | - Angèle Houmeau
- Université de Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69621, Lyon, France
| | - Frédéric Chaput
- Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS UMR 5182, Université Claude Bernard Lyon 1, Laboratoire de Chimie, 46 allée d'Italie, F69364 Lyon, France.
| | - Ala Yaromina
- Department of Precision Medicine, The M-Lab, GROW - School of Oncology, Maastricht University, Maastricht, 6200, MD, The Netherlands
| | - Ludwig Dubois
- Department of Precision Medicine, The M-Lab, GROW - School of Oncology, Maastricht University, Maastricht, 6200, MD, The Netherlands
| | - Philippe Lambin
- Department of Precision Medicine, The M-Lab, GROW - School of Oncology, Maastricht University, Maastricht, 6200, MD, The Netherlands
| | - Szilvia Karpati
- Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS UMR 5182, Université Claude Bernard Lyon 1, Laboratoire de Chimie, 46 allée d'Italie, F69364 Lyon, France.
| | - Stephane Parola
- Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS UMR 5182, Université Claude Bernard Lyon 1, Laboratoire de Chimie, 46 allée d'Italie, F69364 Lyon, France.
| | - B Rezaeifar
- Department of Precision Medicine, The M-Lab, GROW - School of Oncology, Maastricht University, Maastricht, 6200, MD, The Netherlands
- Research group NuTeC, Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
| | | | - Salim A Si-Mohamed
- Université de Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69621, Lyon, France
- Department of Radiology, Hospices Civils de Lyon, 69500 Bron, France
| | - Bruno Montcel
- Université de Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69621, Lyon, France
| | - Philippe Douek
- Université de Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69621, Lyon, France
- Department of Radiology, Hospices Civils de Lyon, 69500 Bron, France
| | - Frederic Lerouge
- Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS UMR 5182, Université Claude Bernard Lyon 1, Laboratoire de Chimie, 46 allée d'Italie, F69364 Lyon, France.
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Zhang W, Liu J, Jin W, Li R, Xie X, Zhao W, Xia S, Han D. Radiomics from dual-energy CT-derived iodine maps predict lymph node metastasis in head and neck squamous cell carcinoma. LA RADIOLOGIA MEDICA 2024; 129:252-267. [PMID: 38015363 DOI: 10.1007/s11547-023-01750-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Accepted: 10/27/2023] [Indexed: 11/29/2023]
Abstract
OBJECTIVE To develop and validate an iodine maps-based radiomics nomogram for preoperatively predicting cervical lymph node metastasis (LNM) in head and neck squamous cell carcinoma (HNSCC). MATERIALS AND METHODS A total of 278 patients who pathologically confirmed as HNSCC were retrospectively recruited from two medical centers between June 2012 and July 2022. The training set (n = 152) and internal set (n = 67) were randomly selected from medical center A, and the patients from medical center B were enrolled as the external set (n = 69). The minority group in the training set was balanced by the adaptive synthetic sampling (ADASYN) approach. Radiomics features were extracted from dual-energy CT-derived iodine maps at arterial phase (AP) and venous phase (VP), respectively. Three radiomics signatures were constructed to predict the LNM by using a random forest algorithm. The independent clinical predictors for LNM were identified by multivariate analysis and combined with radiomics signatures to establish a radiomic-clinical nomogram. The performance of radiomic-clinical nomogram was evaluated with respect to its discrimination and clinical usefulness. RESULTS The AP-VP-incorporated radiomics model exhibited a great predictive performance for LNM prediction with an area under curve (AUC) of 0.885 (95% CI, 0.836-0.933) in ADASYN-training set and confirmed in all validation sets. The nomogram that incorporated AP-VP radiomics signatures, CT-reported LN status, and histological grades yielded AUCs of 0.920 (95% CI, 0.881-0.959) in ADASYN-training set, 0.858 (95% CI, 0.771-0.944) in internal validation, and 0.849 (95% CI, 0.752-0.946) in external validation, with good calibration in all cohorts (p > 0.05). Decision curve analyses indicated the nomogram was clinically useful. In addition, the predictive performance of clinical-radiomics nomogram was also validation in combing cohorts. Stratified analysis confirmed the stability of nomogram, particularly in group negative for CT-reported LNM. CONCLUSION Clinical-radiomics nomogram based on iodine maps exhibited promising performance in predicting LNM and providing valuable information for making individualized therapy decisions.
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Affiliation(s)
- Weiyuan Zhang
- Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Jin Liu
- Center of PET/CT, 920th Hospital of Joint Logistics Support Force, PLA, Kunming, 650032, China
| | - Wenfeng Jin
- Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Ruihong Li
- Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Xiaojie Xie
- Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Wen Zhao
- Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Shuang Xia
- Department of Radiology, The First Central Clinical School, Tianjin Medical University, Tianjin, 300192, China
| | - Dan Han
- Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China.
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40
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Bousse A, Kandarpa VSS, Rit S, Perelli A, Li M, Wang G, Zhou J, Wang G. Systematic Review on Learning-based Spectral CT. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2024; 8:113-137. [PMID: 38476981 PMCID: PMC10927029 DOI: 10.1109/trpms.2023.3314131] [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: 03/14/2024]
Abstract
Spectral computed tomography (CT) has recently emerged as an advanced version of medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two main forms: dual-energy computed tomography (DECT) and photon-counting computed tomography (PCCT), which offer image improvement, material decomposition, and feature quantification relative to conventional CT. However, the inherent challenges of spectral CT, evidenced by data and image artifacts, remain a bottleneck for clinical applications. To address these problems, machine learning techniques have been widely applied to spectral CT. In this review, we present the state-of-the-art data-driven techniques for spectral CT.
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Affiliation(s)
- Alexandre Bousse
- LaTIM, Inserm UMR 1101, Université de Bretagne Occidentale, 29238 Brest, France
| | | | - Simon Rit
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Étienne, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69373, Lyon, France
| | - Alessandro Perelli
- Department of Biomedical Engineering, School of Science and Engineering, University of Dundee, DD1 4HN, UK
| | - Mengzhou Li
- Biomedical Imaging Center, Rensselaer Polytechnic Institute, Troy, New York, USA
| | - Guobao Wang
- Department of Radiology, University of California Davis Health, Sacramento, USA
| | - Jian Zhou
- CTIQ, Canon Medical Research USA, Inc., Vernon Hills, 60061, USA
| | - Ge Wang
- Biomedical Imaging Center, Rensselaer Polytechnic Institute, Troy, New York, USA
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41
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Barat M, Pellat A, Dohan A, Hoeffel C, Coriat R, Soyer P. CT and MRI of Gastrointestinal Stromal Tumors: New Trends and Perspectives. Can Assoc Radiol J 2024; 75:107-117. [PMID: 37386745 DOI: 10.1177/08465371231180510] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2023] Open
Abstract
Gastrointestinal stromal tumors (GISTs) are defined as mesenchymal tumors of the gastrointestinal tract that express positivity for CD117, which is a c-KIT proto-oncogene antigen. Expression of the c-KIT protein, a tyrosine kinase growth factor receptor, allows the distinction between GISTs and other mesenchymal tumors such as leiomyoma, leiomyosarcoma, schwannoma and neurofibroma. GISTs can develop anywhere in the gastrointestinal tract, as well as in the mesentery and omentum. Over the years, the management of GISTs has improved due to a better knowledge of their behaviors and risk or recurrence, the identification of specific mutations and the use of targeted therapies. This has resulted in a better prognosis for patients with GISTs. In parallel, imaging of GISTs has been revolutionized by tremendous progress in the field of detection, characterization, survival prediction and monitoring during therapy. Recently, a particular attention has been given to radiomics for the characterization of GISTs using analysis of quantitative imaging features. In addition, radiomics has currently many applications that are developed in conjunction with artificial intelligence with the aim of better characterizing GISTs and providing a more precise assessment of tumor burden. This article sums up recent advances in computed tomography and magnetic resonance imaging of GISTs in the field of image/data acquisition, tumor detection, tumor characterization, treatment response evaluation, and preoperative planning.
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Affiliation(s)
- Maxime Barat
- Department of Radiology, Hopital Cochin, Paris, France
- Université Paris Cité, Faculté de Médecine, Paris, France
| | - Anna Pellat
- Université Paris Cité, Faculté de Médecine, Paris, France
- Department of Gastroenterology and Digestive Oncology, Hôpital Cochin, Paris, France
| | - Anthony Dohan
- Department of Radiology, Hopital Cochin, Paris, France
- Université Paris Cité, Faculté de Médecine, Paris, France
| | - Christine Hoeffel
- Reims Medical School, Department of Radiology, Hopital Robert Debré, CHU Reims, Université Champagne-Ardennes, Reims, France
| | - Romain Coriat
- Université Paris Cité, Faculté de Médecine, Paris, France
- Department of Gastroenterology and Digestive Oncology, Hôpital Cochin, Paris, France
| | - Philippe Soyer
- Department of Radiology, Hopital Cochin, Paris, France
- Université Paris Cité, Faculté de Médecine, Paris, France
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Fontana F, Piacentino F, Gnesutta A, Macchi E, Coppola A, Saccomanno A, Gatta T, Recaldini C, Minenna M, Tamborini C, Dossi F, Ascenti V, Barbera S, Cicero G, Carcano G, Ascenti G, Castiglioni B, Venturini M. Transcatheter Aortic Valve Implantation (TAVI) Planning with Dual-Layer Spectral CT Using Virtual Monoenergetic Image (VMI) Reconstructions and 20 mL of Contrast Media. J Clin Med 2024; 13:524. [PMID: 38256659 PMCID: PMC10816911 DOI: 10.3390/jcm13020524] [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: 12/01/2023] [Revised: 01/13/2024] [Accepted: 01/15/2024] [Indexed: 01/24/2024] Open
Abstract
Transcatheter aortic valve implantation (TAVI) is a less invasive alternative to surgical implantation and its implementation is progressively increasing worldwide. We routinely perform pre-procedural aortic angiography CT to assess aortic dimensions and vascular anatomy. This study aims to evaluate the image quality of CTA for TAVI planning using dual-layer spectral CT, with virtual monoenergetic image reconstructions at 40 keV. Thirty-one patients underwent a CTA protocol with the injection of 20 mL of contrast media. Image quality was assessed by measuring the mean density in Hounsfield Units (HU), the signal-to-noise ratio, and the contrast-to-noise ratio in VMI reconstructions. Additionally, a blinded subjective analysis was conducted by two observers. The results showed significant enhancement at all sampled vascular levels with a gradual decrease in HU from proximal to distal regions. Favourable subjective ratings were given for all parameters, with greater variability in the evaluation of iliac axes. A significant negative correlation (p < 0.05) was observed between BMI and CA at all vascular levels, indicating reduced contrast enhancement with increasing BMI. Spectral CT, along with reducing iodine load, allows for obtaining high-quality images without a significant increase in noise. The reduction in iodine load can have positive implications in clinical practice, improving patient safety and resource efficiency.
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Affiliation(s)
- Federico Fontana
- Diagnostic and Interventional Radiology Unit, Circolo Hospital, ASST Sette Laghi, 21100 Varese, Italy; (F.F.); (A.G.); (E.M.); (A.S.); (T.G.); (C.R.); (M.V.)
- Postgraduate School of Radiology Technician, Insubria University, 21100 Varese, Italy;
| | - Filippo Piacentino
- Diagnostic and Interventional Radiology Unit, Circolo Hospital, ASST Sette Laghi, 21100 Varese, Italy; (F.F.); (A.G.); (E.M.); (A.S.); (T.G.); (C.R.); (M.V.)
| | - Aroa Gnesutta
- Diagnostic and Interventional Radiology Unit, Circolo Hospital, ASST Sette Laghi, 21100 Varese, Italy; (F.F.); (A.G.); (E.M.); (A.S.); (T.G.); (C.R.); (M.V.)
| | - Edoardo Macchi
- Diagnostic and Interventional Radiology Unit, Circolo Hospital, ASST Sette Laghi, 21100 Varese, Italy; (F.F.); (A.G.); (E.M.); (A.S.); (T.G.); (C.R.); (M.V.)
| | - Andrea Coppola
- Diagnostic and Interventional Radiology Unit, Circolo Hospital, ASST Sette Laghi, 21100 Varese, Italy; (F.F.); (A.G.); (E.M.); (A.S.); (T.G.); (C.R.); (M.V.)
| | - Angiola Saccomanno
- Diagnostic and Interventional Radiology Unit, Circolo Hospital, ASST Sette Laghi, 21100 Varese, Italy; (F.F.); (A.G.); (E.M.); (A.S.); (T.G.); (C.R.); (M.V.)
| | - Tonia Gatta
- Diagnostic and Interventional Radiology Unit, Circolo Hospital, ASST Sette Laghi, 21100 Varese, Italy; (F.F.); (A.G.); (E.M.); (A.S.); (T.G.); (C.R.); (M.V.)
| | - Chiara Recaldini
- Diagnostic and Interventional Radiology Unit, Circolo Hospital, ASST Sette Laghi, 21100 Varese, Italy; (F.F.); (A.G.); (E.M.); (A.S.); (T.G.); (C.R.); (M.V.)
| | - Manuela Minenna
- Postgraduate School of Radiology Technician, Insubria University, 21100 Varese, Italy;
| | - Claudio Tamborini
- Department of Cardiovascular Diseases, ASST Settelaghi, 21100 Varese, Italy; (C.T.); (F.D.); (B.C.)
| | - Filippo Dossi
- Department of Cardiovascular Diseases, ASST Settelaghi, 21100 Varese, Italy; (C.T.); (F.D.); (B.C.)
| | - Velio Ascenti
- Postgraduate School of Radiodiagnostics, Policlinico Universitario, University of Milan, 20133 Milano, Italy;
| | - Simone Barbera
- Diagnostic and Interventional Radiology Unit, Biomorf Department, University Hospital Messina, 98124 Messina, Italy; (S.B.); (G.C.); (G.A.)
| | - Giuseppe Cicero
- Diagnostic and Interventional Radiology Unit, Biomorf Department, University Hospital Messina, 98124 Messina, Italy; (S.B.); (G.C.); (G.A.)
| | - Giulio Carcano
- Department of Medicine and Technological Innovation, Insubria University, 21100 Varese, Italy;
| | - Giorgio Ascenti
- Diagnostic and Interventional Radiology Unit, Biomorf Department, University Hospital Messina, 98124 Messina, Italy; (S.B.); (G.C.); (G.A.)
| | - Battistina Castiglioni
- Department of Cardiovascular Diseases, ASST Settelaghi, 21100 Varese, Italy; (C.T.); (F.D.); (B.C.)
| | - Massimo Venturini
- Diagnostic and Interventional Radiology Unit, Circolo Hospital, ASST Sette Laghi, 21100 Varese, Italy; (F.F.); (A.G.); (E.M.); (A.S.); (T.G.); (C.R.); (M.V.)
- Department of Medicine and Technological Innovation, Insubria University, 21100 Varese, Italy;
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Fu C, Zhang B, Guo T, Li J. Imaging Evaluation of Peritoneal Metastasis: Current and Promising Techniques. Korean J Radiol 2024; 25:86-102. [PMID: 38184772 PMCID: PMC10788608 DOI: 10.3348/kjr.2023.0840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 09/28/2023] [Accepted: 10/08/2023] [Indexed: 01/08/2024] Open
Abstract
Early diagnosis, accurate assessment, and localization of peritoneal metastasis (PM) are essential for the selection of appropriate treatments and surgical guidance. However, available imaging modalities (computed tomography [CT], conventional magnetic resonance imaging [MRI], and 18fluorodeoxyglucose positron emission tomography [PET]/CT) have limitations. The advent of new imaging techniques and novel molecular imaging agents have revealed molecular processes in the tumor microenvironment as an application for the early diagnosis and assessment of PM as well as real-time guided surgical resection, which has changed clinical management. In contrast to clinical imaging, which is purely qualitative and subjective for interpreting macroscopic structures, radiomics and artificial intelligence (AI) capitalize on high-dimensional numerical data from images that may reflect tumor pathophysiology. A predictive model can be used to predict the occurrence, recurrence, and prognosis of PM, thereby avoiding unnecessary exploratory surgeries. This review summarizes the role and status of different imaging techniques, especially new imaging strategies such as spectral photon-counting CT, fibroblast activation protein inhibitor (FAPI) PET/CT, near-infrared fluorescence imaging, and PET/MRI, for early diagnosis, assessment of surgical indications, and recurrence monitoring in patients with PM. The clinical applications, limitations, and solutions for fluorescence imaging, radiomics, and AI are also discussed.
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Affiliation(s)
- Chen Fu
- The First School of Clinical Medical, Gansu University of Chinese Medicine, Lanzhou, Gansu, China
| | - Bangxing Zhang
- School of Clinical Medicine, Ningxia Medical University, Yinchuan, Ningxia, China
| | - Tiankang Guo
- Department of General Surgery, Gansu Provincial Hospital, Lanzhou, Gansu, China
- Key Laboratory of Molecular Diagnostics and Precision Medicine for Surgical Oncology in Gansu Province, Gansu Provincial Hospital, Gansu, China
- NHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, Lanzhou, Gansu, China
| | - Junliang Li
- The First School of Clinical Medical, Gansu University of Chinese Medicine, Lanzhou, Gansu, China
- Department of General Surgery, Gansu Provincial Hospital, Lanzhou, Gansu, China
- Key Laboratory of Molecular Diagnostics and Precision Medicine for Surgical Oncology in Gansu Province, Gansu Provincial Hospital, Gansu, China
- NHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, Lanzhou, Gansu, China.
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Boubaker F, Teixeira PAG, Hossu G, Douis N, Gillet P, Blum A, Gillet R. In vivo depiction of cortical bone vascularization with ultra-high resolution-CT and deep learning algorithm reconstruction using osteoid osteoma as a model. Diagn Interv Imaging 2024; 105:26-32. [PMID: 37482455 DOI: 10.1016/j.diii.2023.07.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 06/24/2023] [Accepted: 07/12/2023] [Indexed: 07/25/2023]
Abstract
PURPOSE The purpose of this study was to evaluate the ability to depict in vivo bone vascularization using ultra-high-resolution (UHR) computed tomography (CT) with deep learning reconstruction (DLR) and hybrid iterative reconstruction algorithm, compared to simulated conventional CT, using osteoid osteoma as a model. MATERIALS AND METHODS Patients with histopathologically proven cortical osteoid osteoma who underwent UHR-CT between October 2019 and October 2022 were retrospectively included. Images were acquired with a 1024 × 1024 matrix and reconstructed with DLR and hybrid iterative reconstruction algorithm. To simulate conventional CT, images with a 512 × 512 matrix were also reconstructed. Two radiologists (R1, R2) independently evaluated the number of blood vessels entering the nidus and crossing the bone cortex, as well as vessel identification and image quality with a 5-point scale. Standard deviation (SD) of attenuation in the adjacent muscle and that of air were used as image noise and recorded. RESULTS Thirteen patients with 13 osteoid osteomas were included. There were 11 men and two women with a mean age of 21.8 ± 9.1 (SD) years. For both readers, UHR-CT with DLR depicted more nidus vessels (11.5 ± 4.3 [SD] (R1) and 11.9 ± 4.6 [SD] (R2)) and cortical vessels (4 ± 3.8 [SD] and 4.3 ± 4.1 [SD], respectively) than UHR-CT with hybrid iterative reconstruction (10.5 ± 4.3 [SD] and 10.4 ± 4.6 [SD], and 4.1 ± 3.8 [SD] and 4.3 ± 3.8 [SD], respectively) and simulated conventional CT (5.3 ± 2.2 [SD] and 6.4 ± 2.5 [SD], 2 ± 1.2 [SD] and 2.4 ± 1.6 [SD], respectively) (P < 0.05). UHR-CT with DLR provided less image noise than simulated conventional CT and UHR-CT with hybrid iterative reconstruction (P < 0.05). UHR-CT with DLR received the greatest score and simulated conventional CT the lowest score for vessel identification and image quality. CONCLUSION UHR-CT with DLR shows less noise than UHR-CT with hybrid iterative reconstruction and significantly improves cortical bone vascularization depiction compared to simulated conventional CT.
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Affiliation(s)
- Fatma Boubaker
- Guilloz Imaging Department, Central Hospital, University Hospital Center of Nancy, 54000, Nancy, France
| | - Pedro Augusto Gondim Teixeira
- Guilloz Imaging Department, Central Hospital, University Hospital Center of Nancy, 54000, Nancy, France; Université de Lorraine, INSERM, IADI, 54000, Nancy, France; Université de Lorraine, CIC, Innovation Technologique, University Hospital Center of Nancy, 54000, Nancy, France
| | - Gabriela Hossu
- Université de Lorraine, INSERM, IADI, 54000, Nancy, France; Université de Lorraine, CIC, Innovation Technologique, University Hospital Center of Nancy, 54000, Nancy, France
| | - Nicolas Douis
- Guilloz Imaging Department, Central Hospital, University Hospital Center of Nancy, 54000, Nancy, France
| | - Pierre Gillet
- Université de Lorraine, CNRS, IMoPA, 54000, Nancy, France
| | - Alain Blum
- Guilloz Imaging Department, Central Hospital, University Hospital Center of Nancy, 54000, Nancy, France; Université de Lorraine, INSERM, IADI, 54000, Nancy, France; Université de Lorraine, CIC, Innovation Technologique, University Hospital Center of Nancy, 54000, Nancy, France
| | - Romain Gillet
- Guilloz Imaging Department, Central Hospital, University Hospital Center of Nancy, 54000, Nancy, France; Université de Lorraine, INSERM, IADI, 54000, Nancy, France; Université de Lorraine, CIC, Innovation Technologique, University Hospital Center of Nancy, 54000, Nancy, France.
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45
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Patzer TS, Grunz JP, Huflage H, Hennes JL, Pannenbecker P, Gruschwitz P, Afat S, Herrmann J, Bley TA, Kunz AS. Ultra-high resolution photon-counting CT with tin prefiltration for bone-metal interface visualization. Eur J Radiol 2024; 170:111209. [PMID: 37992609 DOI: 10.1016/j.ejrad.2023.111209] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 11/08/2023] [Accepted: 11/16/2023] [Indexed: 11/24/2023]
Abstract
PURPOSE To investigate the metal artifact suppression potential of combining tin prefiltration and virtual monoenergetic imaging (VMI) for osseous microarchitecture depiction in ultra-high-resolution (UHR) photon-counting CT (PCCT) of the lower extremity. METHOD Derived from tin-filtered UHR scans at 140 kVp, polychromatic datasets (T3D) and VMI reconstructions at 70, 110, 150, and 190 keV were compared in 117 patients with lower extremity metal implants (53 female; 62.1 ± 18.0 years). Three implant groups were investigated (total arthroplasty [n = 48], osteosynthetic material [n = 43], and external fixation [n = 26]). Image quality was assessed with regions of interest placed in the most pronounced artifacts and adjacent soft tissue, measuring the respective attenuation. Additionally, artifact extent, bone-metal interface interpretability and overall image quality were independently evaluated by three radiologists. RESULTS Artifact reduction was superior with increasing keV level of VMI. While T3D was superior to VMI70keV (p ≥ 0.117), artifacts were more severe in T3D than in VMI ≥ 110 keV (all p ≤ 0.036). Image noise was highest for VMI70keV (all p < 0.001) and lowest for VMI110keV with comparable results for VMI110keV - VMI190keV. Subjective image quality regarding artifacts was superior for VMI ≥ 110 keV (all p ≤ 0.042) and comparable for VMI110keV - VMI190keV. Bone-metal interface interpretability was superior for VMI110keV (all p ≤ 0.001), while T3D, VMI150keV and VMI190keV were comparable. Overall image quality was deemed best for VMI110keV and VMI150keV. Interreader reliability was good in all cases (ICC ≥ 0.833). CONCLUSIONS Tin-filtered UHR-PCCT scans of the lower extremity combined with VMI reconstructions allow for efficient artifact reduction in the vicinity of bone-metal interfaces.
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Affiliation(s)
- Theresa Sophie Patzer
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany.
| | - Jan-Peter Grunz
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany
| | - Henner Huflage
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany
| | - Jan-Lucca Hennes
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany
| | - Pauline Pannenbecker
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany
| | - Philipp Gruschwitz
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany
| | - Saif Afat
- Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Hoppe-Seyler-Str 3, 72076 Tübingen, Germany
| | - Judith Herrmann
- Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Hoppe-Seyler-Str 3, 72076 Tübingen, Germany
| | - Thorsten Alexander Bley
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany
| | - Andreas Steven Kunz
- Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Hoppe-Seyler-Str 3, 72076 Tübingen, Germany
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Gogoshin G, Rodin AS. Graph Neural Networks in Cancer and Oncology Research: Emerging and Future Trends. Cancers (Basel) 2023; 15:5858. [PMID: 38136405 PMCID: PMC10742144 DOI: 10.3390/cancers15245858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 12/09/2023] [Accepted: 12/14/2023] [Indexed: 12/24/2023] Open
Abstract
Next-generation cancer and oncology research needs to take full advantage of the multimodal structured, or graph, information, with the graph data types ranging from molecular structures to spatially resolved imaging and digital pathology, biological networks, and knowledge graphs. Graph Neural Networks (GNNs) efficiently combine the graph structure representations with the high predictive performance of deep learning, especially on large multimodal datasets. In this review article, we survey the landscape of recent (2020-present) GNN applications in the context of cancer and oncology research, and delineate six currently predominant research areas. We then identify the most promising directions for future research. We compare GNNs with graphical models and "non-structured" deep learning, and devise guidelines for cancer and oncology researchers or physician-scientists, asking the question of whether they should adopt the GNN methodology in their research pipelines.
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Affiliation(s)
- Grigoriy Gogoshin
- Department of Computational and Quantitative Medicine, Beckman Research Institute, and Diabetes and Metabolism Research Institute, City of Hope National Medical Center, 1500 East Duarte Road, Duarte, CA 91010, USA
| | - Andrei S. Rodin
- Department of Computational and Quantitative Medicine, Beckman Research Institute, and Diabetes and Metabolism Research Institute, City of Hope National Medical Center, 1500 East Duarte Road, Duarte, CA 91010, USA
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Flohr T, Schmidt B, Ulzheimer S, Alkadhi H. Cardiac imaging with photon counting CT. Br J Radiol 2023; 96:20230407. [PMID: 37750856 PMCID: PMC10646663 DOI: 10.1259/bjr.20230407] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 08/17/2023] [Accepted: 08/24/2023] [Indexed: 09/27/2023] Open
Abstract
CT of the heart, in particular ECG-controlled coronary CT angiography (cCTA), has become clinical routine due to rapid technical progress with ever new generations of CT equipment. Recently, CT scanners with photon-counting detectors (PCD) have been introduced which have the potential to address some of the remaining challenges for cardiac CT, such as limited spatial resolution and lack of high-quality spectral data. In this review article, we briefly discuss the technical principles of photon-counting detector CT, and we give an overview on how the improved spatial resolution of photon-counting detector CT and the routine availability of spectral data can benefit cardiac applications. We focus on coronary artery calcium scoring, cCTA, and on the evaluation of the myocardium.
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Affiliation(s)
- Thomas Flohr
- Siemens Healthcare GmbH, Computed Tomography, Forchheim, Germany
| | - Bernhard Schmidt
- Siemens Healthcare GmbH, Computed Tomography, Forchheim, Germany
| | - Stefan Ulzheimer
- Siemens Healthcare GmbH, Computed Tomography, Forchheim, Germany
| | - Hatem Alkadhi
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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48
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Su Y, Ran P, Hui J, Yang YM. Quantitative Dual-Energy X-ray Imaging Based on K-Edge Absorption Difference. J Phys Chem Lett 2023; 14:10074-10079. [PMID: 37916648 DOI: 10.1021/acs.jpclett.3c02827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2023]
Abstract
Conventional flat panel X-ray imaging (FPXI) employs a single scintillator for X-ray conversion, which lacks energy spectrum information. The recent innovation of employing multilayer scintillators offers a route for multispectral X-ray imaging. However, the principles guiding optimal multilayer scintillator configuration selection and quantitative analysis models remain largely unexplored. Here, we propose to adopt the K-edge absorption coefficient as a key parameter for selecting tandem scintillator combinations and to utilize the coefficient matrix to calculate the absorption efficiency spectrum of the sample. Through a dual scintillator example comprising C4H12NMnCl3 and Cs3Cu2I5, we establish a streamlined quantitative framework for deducing X-ray spectra from scintillation spectra, with an average relative error of 6.28% between the calculated and measured sample absorption spectrum. This insight forms the foundation for our quantitative method to distinguish the material densities. Leveraging this tandem scintillator configuration, in conjunction with our analytical tools, we successfully demonstrate the inherent merits of dual-energy X-ray imaging for discerning materials with varied densities and thicknesses.
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Affiliation(s)
- Yirong Su
- State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China
| | - Peng Ran
- State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China
| | - Juan Hui
- State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China
| | - Yang Michael Yang
- State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China
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Martineau L, Branchu A, Boccalini S, Boussel L, Douek P, Si-Mohamed SA. Spectral dual-energy CT: A new tool to monitor lung perfusion recovery in acute pulmonary embolism after mechanical thrombectomy. Diagn Interv Imaging 2023; 104:560-561. [PMID: 37537022 DOI: 10.1016/j.diii.2023.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 07/25/2023] [Accepted: 07/26/2023] [Indexed: 08/05/2023]
Affiliation(s)
- Lorraine Martineau
- Department of Radiology, Hôpital Louis Pradel, Hospices Civils de Lyon, 69500 Bron, France
| | - Arthur Branchu
- Department of Radiology, Hôpital Louis Pradel, Hospices Civils de Lyon, 69500 Bron, France
| | - Sara Boccalini
- Department of Radiology, Hôpital Louis Pradel, Hospices Civils de Lyon, 69500 Bron, France; University Lyon, INSA-Lyon, University Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, INSERM, CREATIS UMR 5220, U1206, 69100 Villeurbanne, France
| | - Loic Boussel
- Department of Radiology, Hôpital Louis Pradel, Hospices Civils de Lyon, 69500 Bron, France; Department of Radiology, Hôpital Croix Rousse, Hospices Civils de Lyon, 69004 Lyon, France
| | - Philippe Douek
- Department of Radiology, Hôpital Louis Pradel, Hospices Civils de Lyon, 69500 Bron, France; University Lyon, INSA-Lyon, University Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, INSERM, CREATIS UMR 5220, U1206, 69100 Villeurbanne, France
| | - Salim A Si-Mohamed
- Department of Radiology, Hôpital Louis Pradel, Hospices Civils de Lyon, 69500 Bron, France; University Lyon, INSA-Lyon, University Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, INSERM, CREATIS UMR 5220, U1206, 69100 Villeurbanne, France.
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50
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Greffier J, Van Ngoc Ty C, Fitton I, Frandon J, Beregi JP, Dabli D. Spectral performance of two split-filter dual-energy CT systems: A phantom study. Med Phys 2023; 50:6828-6835. [PMID: 37672341 DOI: 10.1002/mp.16701] [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: 04/09/2023] [Revised: 07/31/2023] [Accepted: 07/31/2023] [Indexed: 09/08/2023] Open
Abstract
BACKGROUND Recently, a second generation of split filter dual-energy CT (SFCT) platform has been developed. The thicknesses of the gold and tin filters used to obtain both low- and high-energy spectra have been changed. These differences in filter thickness may affect the spectral separation between the two spectra and thus the quality of spectral images. PURPOSE To compare the spectral performance of two Split-Filter Dual-Energy CT systems (SFCT-1st and SFCT-2nd ) on virtual monoenergetic images (VMIs) and iodine map. METHODS A Multi-Energy CT phantom was scanned on two SFCT with a tube voltage of 120 kVp for both systems (SFCT-1st -120 and SFCT-2nd -120) and 140 kVp only for the second generation (SFCT-2nd -140). Acquisitions were performed on the phantom with a CTDIvol close to 11 mGy. Noise power spectrum (NPS) and task-based transfer function (TTF) were evaluated on VMIs from 40 to 70 keV. A detectability index (d') was computed to assess the detection of two contrast-enhanced lesions on VMIs. Hounsfield Unit (HU) accuracy was assessed on VMIs and the accuracy of iodine concentration was assessed on iodine maps. RESULTS For all keV, noise magnitude values were lower with the SFCT-2nd -120 than with the SFCT-1st -120 (on average: -22.5 ± 2.9%) and higher with the SFCT-2nd -140 than with the SFCT-2nd -120 (on average: 25.0 ± 6.2%). Average NPS spatial frequencies (fav ) were lower with the SFCT-1st -120 than with the SFCT-2nd -120 (-6.0 ± 0.5%) and the SFCT-2nd -140 (-3.6 ± 1.6%). Similar TTF50% values were found for both systems and both kVp for blood and iodine inserts at 2 mg/mL (0.29 ± 0.01 mm-1 ) and at 4 mg/mL (0.31 ± 0.01 mm-1 ). d' values peaked at 40 keV for the SFCT-2nd and at 70 keV for the SFCT-1st . Highest d' values were found for the SFCT-2nd -120 for both simulated lesions. Accuracy of HU values and iodine concentration was higher with the SFCT-2nd than with the SFCT 1st . CONCLUSION Compared to the SFCT-1st , with similar spatial resolution and noise texture values, the SFCT-2nd -120 exhibited the lowest values for noise magnitude, the highest detectability index values, and more accurate HU values and iodine concentrations.
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Affiliation(s)
- Joël Greffier
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France
| | - Claire Van Ngoc Ty
- Université de Paris, Assistance Publique Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Department of Radiology, Paris, France
| | - Isabelle Fitton
- Université de Paris, Assistance Publique Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Department of Radiology, Paris, France
| | - Julien Frandon
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France
| | - Jean-Paul Beregi
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France
| | - Djamel Dabli
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France
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