Pub Date : 2024-09-01DOI: 10.1016/j.diii.2024.07.007
{"title":"Impact factor, first quartile, CiteScore and other metrics","authors":"","doi":"10.1016/j.diii.2024.07.007","DOIUrl":"10.1016/j.diii.2024.07.007","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141914292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01DOI: 10.1016/j.diii.2024.07.003
Anatomic imaging with contrast-enhanced computed tomography (CT) and magnetic resonance imaging (MRI) has long been the mainstay of renal mass characterization. However, those modalities are often unable to adequately characterize indeterminate, solid, enhancing renal masses – with some exceptions, such as the development of the clear-cell likelihood score on multi-parametric MRI. As such, molecular imaging approaches have gained traction as an alternative to anatomic imaging. Mitochondrial imaging with 99mTc-sestamibi single-photon emission computed tomography/CT is a cost-effective means of non-invasively identifying oncocytomas and other indolent renal masses. On the other end of the spectrum, carbonic anhydrase IX agents, most notably the monoclonal antibody girentuximab – which can be labeled with positron emission tomography radionuclides such as zirconium-89 – are effective at identifying renal masses that are likely to be aggressive clear cell renal cell carcinomas. Renal mass biopsy, which has a relatively high non-diagnostic rate and does not definitively characterize many oncocytic neoplasms, nonetheless may play an important role in any algorithm targeted to renal mass risk stratification. The combination of molecular imaging and biopsy in selected patients with other advanced imaging methods, such as artificial intelligence/machine learning and the abstraction of radiomics features, offers the optimal way forward for maximization of the information to be gained from risk stratification of indeterminate renal masses. With the proper application of those methods, inappropriately aggressive therapy for benign and indolent renal masses may be curtailed.
长期以来,造影剂增强计算机断层扫描(CT)和磁共振成像(MRI)的解剖成像一直是肾脏肿块定性的主要方法。然而,这些方法往往无法充分描述不确定、实性、增强型肾肿块的特征--除了一些例外情况,如在多参数核磁共振成像上发展出透明细胞可能性评分。因此,分子成像方法作为解剖成像的替代方法受到了越来越多的关注。使用 99mTc-sestamibi 单光子发射计算机断层扫描/CT 进行线粒体成像是一种经济有效的非侵入性方法,可用于识别肿瘤细胞瘤和其他不显性肾肿块。另一方面,碳酸酐酶 IX 药剂,尤其是单克隆抗体吉伦妥昔单抗(可标记正电子发射断层扫描放射性核素,如锆-89),可有效识别可能是侵袭性透明细胞肾细胞癌的肾肿块。肾肿块活检的非诊断率相对较高,而且不能确定许多肿瘤细胞瘤的特征,但在任何针对肾肿块风险分层的算法中都可能发挥重要作用。在选定的患者中将分子成像和活检与其他先进的成像方法(如人工智能/机器学习和放射组学特征抽象)相结合,为最大限度地从不确定性肾肿块风险分层中获取信息提供了最佳途径。通过正确应用这些方法,可以减少对良性和隐匿性肾肿块不适当的积极治疗。
{"title":"Molecular imaging for non-invasive risk stratification of renal masses","authors":"","doi":"10.1016/j.diii.2024.07.003","DOIUrl":"10.1016/j.diii.2024.07.003","url":null,"abstract":"<div><p>Anatomic imaging with contrast-enhanced computed tomography (CT) and magnetic resonance imaging (MRI) has long been the mainstay of renal mass characterization. However, those modalities are often unable to adequately characterize indeterminate, solid, enhancing renal masses – with some exceptions, such as the development of the clear-cell likelihood score on multi-parametric MRI. As such, molecular imaging approaches have gained traction as an alternative to anatomic imaging. Mitochondrial imaging with <sup>99m</sup>Tc-sestamibi single-photon emission computed tomography/CT is a cost-effective means of non-invasively identifying oncocytomas and other indolent renal masses. On the other end of the spectrum, carbonic anhydrase IX agents, most notably the monoclonal antibody girentuximab – which can be labeled with positron emission tomography radionuclides such as zirconium-89 – are effective at identifying renal masses that are likely to be aggressive clear cell renal cell carcinomas. Renal mass biopsy, which has a relatively high non-diagnostic rate and does not definitively characterize many oncocytic neoplasms, nonetheless may play an important role in any algorithm targeted to renal mass risk stratification. The combination of molecular imaging and biopsy in selected patients with other advanced imaging methods, such as artificial intelligence/machine learning and the abstraction of radiomics features, offers the optimal way forward for maximization of the information to be gained from risk stratification of indeterminate renal masses. With the proper application of those methods, inappropriately aggressive therapy for benign and indolent renal masses may be curtailed.</p></div>","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141761824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1016/j.diii.2024.07.006
{"title":"CT, MRI and PET/CT of adrenal schwannoma","authors":"","doi":"10.1016/j.diii.2024.07.006","DOIUrl":"10.1016/j.diii.2024.07.006","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141876372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.1016/j.diii.2024.07.002
Purpose
The purpose of the 2023 SFR data challenge was to invite researchers to develop artificial intelligence (AI) models to identify the presence of a pancreatic mass and distinguish between benign and malignant pancreatic masses on abdominal computed tomography (CT) examinations.
Materials and methods
Anonymized abdominal CT examinations acquired during the portal venous phase were collected from 18 French centers. Abdominal CT examinations were divided into three groups including CT examinations with no lesion, CT examinations with benign pancreatic mass, or CT examinations with malignant pancreatic mass. Each team included at least one radiologist, one data scientist, and one engineer. Pancreatic lesions were annotated by expert radiologists. CT examinations were distributed in balanced batches via a Health Data Hosting certified platform. Data were distributed into four batches, two for training, one for internal evaluation, and one for the external evaluation. Training used 83 % of the data from 14 centers and external evaluation used data from the other four centers. The metric (i.e., final score) used to rank the participants was a weighted average of mean sensitivity, mean precision and mean area under the curve.
Results
A total of 1037 abdominal CT examinations were divided into two training sets (including 500 and 232 CT examinations), an internal evaluation set (including 139 CT examinations), and an external evaluation set (including 166 CT examinations). The training sets were distributed on September 7 and October 13, 2023, and evaluation sets on October 15, 2023. Ten teams with a total of 93 members participated to the data challenge, with the best final score being 0.72.
Conclusion
This SFR 2023 data challenge based on multicenter CT data suggests that the use of AI for pancreatic lesions detection is possible on real data, but the distinction between benign and malignant pancreatic lesions remains challenging.
{"title":"Detection and characterization of pancreatic lesion with artificial intelligence: The SFR 2023 artificial intelligence data challenge","authors":"","doi":"10.1016/j.diii.2024.07.002","DOIUrl":"10.1016/j.diii.2024.07.002","url":null,"abstract":"<div><h3>Purpose</h3><div>The purpose of the 2023 SFR data challenge was to invite researchers to develop artificial intelligence (AI) models to identify the presence of a pancreatic mass and distinguish between benign and malignant pancreatic masses on abdominal computed tomography (CT) examinations.</div></div><div><h3>Materials and methods</h3><div><span>Anonymized abdominal CT examinations acquired during the portal venous phase were collected from 18 French centers. Abdominal CT examinations were divided into three groups including CT examinations with no lesion, CT examinations with benign pancreatic mass, or CT examinations with malignant pancreatic mass. Each team included at least one radiologist, one data scientist, and one engineer. Pancreatic lesions were annotated by expert radiologists. CT examinations were distributed in balanced batches via a Health Data Hosting certified platform. Data were distributed into four batches, two for training, one for internal evaluation, and one for the external evaluation. Training used 83 % of the data from 14 centers and external evaluation used data from the other four centers. The metric (</span><em>i.e.</em>, final score) used to rank the participants was a weighted average of mean sensitivity, mean precision and mean area under the curve.</div></div><div><h3>Results</h3><div>A total of 1037 abdominal CT examinations were divided into two training sets (including 500 and 232 CT examinations), an internal evaluation set (including 139 CT examinations), and an external evaluation set (including 166 CT examinations). The training sets were distributed on September 7 and October 13, 2023, and evaluation sets on October 15, 2023. Ten teams with a total of 93 members participated to the data challenge, with the best final score being 0.72.</div></div><div><h3>Conclusion</h3><div>This SFR 2023 data challenge based on multicenter CT data suggests that the use of AI for pancreatic lesions detection is possible on real data, but the distinction between benign and malignant pancreatic lesions remains challenging.</div></div>","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141761823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-22DOI: 10.1016/j.diii.2024.07.001
{"title":"The role of MR imaging in ovarian tumor risk stratification","authors":"","doi":"10.1016/j.diii.2024.07.001","DOIUrl":"10.1016/j.diii.2024.07.001","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141753064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.diii.2024.02.007
Farah Cadour, Jean-Nicolas Dacher
{"title":"When artificial intelligence meets photon-counting coronary CT angiography to reduce the need for invasive coronary angiography in TAVR candidates","authors":"Farah Cadour, Jean-Nicolas Dacher","doi":"10.1016/j.diii.2024.02.007","DOIUrl":"10.1016/j.diii.2024.02.007","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139984180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.diii.2024.01.009
Estibaliz Valdeolmillos , Hichem Sakhi , Marine Tortigue , Marion Audié , Marc-Antoine Isorni , Florence Lecerf , Olivier Sitbon , David Montani , Xavier Jais , Laurent Savale , Marc Humbert , Arshid Azarine , Sébastien Hascoët
Purpose
The purpose of this study was to evaluate the accuracy of four-dimensional flow cardiac magnetic resonance imaging (4D flow MRI) compared to right heart catheterization in measuring pulmonary flow (Qp), systemic flow (Qs) and pulmonary-to-systemic flow ratio (Qp/Qs) in patients with pulmonary arterial hypertension associated with congenital heart disease (PAH-CHD).
Materials and methods
The study was registered on Clinical-trial.gov (NCT03928002). Sixty-four patients with PAH-CHD who underwent 4D flow MRI were included. There were 16 men and 48 women with a mean age of 45.3 ± 13.7 (standard deviation [SD]) years (age range: 21–77 years). Fifty patients (50/64; 78%) presented with pre-tricuspid shunt. Qp (L/min), Qs (L/min) and Qp/Qs were measured invasively using direct Fick method during right heart catheterization and compared with measurements assessed by 4D flow MRI within a 24–48-hour window.
Results
The average mean pulmonary artery pressure was 51 ± 17 (SD) mm Hg with median pulmonary vascular resistance of 8.8 Wood units (Q1, Q3: 5.3, 11.7). A strong linear correlation was found between Qp measurements obtained with 4D flow MRI and those obtained with the Fick method (r = 0.96; P < 0.001). Bland Altman analysis indicated a mean difference of 0.15 ± 0.48 (SD) L/min between Qp estimated by 4D flow MRI and by right heart catheterization. A strong correlation was found between Qs and Qp/Qs measured by 4D flow MRI and those obtained with the direct Fick method (r = 0.85 and r = 0.92; P < 0.001 for both).
Conclusion
Qp as measured by 4D flow MRI shows a strong correlation with measurements derived from the direct Fick method. Further investigation is needed to develop less complex and standardized methods for measuring essential PAH parameters, such as pulmonary arterial pressures and pulmonary vascular resistance.
{"title":"4D flow cardiac MRI to assess pulmonary blood flow in patients with pulmonary arterial hypertension associated with congenital heart disease","authors":"Estibaliz Valdeolmillos , Hichem Sakhi , Marine Tortigue , Marion Audié , Marc-Antoine Isorni , Florence Lecerf , Olivier Sitbon , David Montani , Xavier Jais , Laurent Savale , Marc Humbert , Arshid Azarine , Sébastien Hascoët","doi":"10.1016/j.diii.2024.01.009","DOIUrl":"10.1016/j.diii.2024.01.009","url":null,"abstract":"<div><h3>Purpose</h3><p>The purpose of this study was to evaluate the accuracy of four-dimensional flow cardiac magnetic resonance imaging (4D flow MRI) compared to right heart catheterization in measuring pulmonary flow (Qp), systemic flow (Qs) and pulmonary-to-systemic flow ratio (Qp/Qs) in patients with pulmonary arterial hypertension associated with congenital heart disease (PAH-CHD).</p></div><div><h3>Materials and methods</h3><p>The study was registered on Clinical-trial.gov (NCT03928002). Sixty-four patients with PAH-CHD who underwent 4D flow MRI were included. There were 16 men and 48 women with a mean age of 45.3 ± 13.7 (standard deviation [SD]) years (age range: 21–77 years). Fifty patients (50/64; 78%) presented with pre-tricuspid shunt. Qp (L/min), Qs (L/min) and Qp/Qs were measured invasively using direct Fick method during right heart catheterization and compared with measurements assessed by 4D flow MRI within a 24–48-hour window.</p></div><div><h3>Results</h3><p>The average mean pulmonary artery pressure was 51 ± 17 (SD) mm Hg with median pulmonary vascular resistance of 8.8 Wood units (Q1, Q3: 5.3, 11.7). A strong linear correlation was found between Qp measurements obtained with 4D flow MRI and those obtained with the Fick method (<em>r</em> = 0.96; <em>P</em> < 0.001). Bland Altman analysis indicated a mean difference of 0.15 ± 0.48 (SD) L/min between Qp estimated by 4D flow MRI and by right heart catheterization. A strong correlation was found between Qs and Qp/Qs measured by 4D flow MRI and those obtained with the direct Fick method (<em>r</em> = 0.85 and <em>r</em> = 0.92; <em>P</em> < 0.001 for both).</p></div><div><h3>Conclusion</h3><p>Qp as measured by 4D flow MRI shows a strong correlation with measurements derived from the direct Fick method. Further investigation is needed to develop less complex and standardized methods for measuring essential PAH parameters, such as pulmonary arterial pressures and pulmonary vascular resistance.</p></div>","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139898306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.diii.2024.02.014
David A Bluemke , Nadine Kawel-Boehm
{"title":"More evidence to support greater use of 4D flow cardiac MRI","authors":"David A Bluemke , Nadine Kawel-Boehm","doi":"10.1016/j.diii.2024.02.014","DOIUrl":"10.1016/j.diii.2024.02.014","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140066020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.diii.2024.06.008
{"title":"Improved image quality and abdominal lesion detection with photon-counting CT compared to dual-source CT: New evidence from a phantom study","authors":"","doi":"10.1016/j.diii.2024.06.008","DOIUrl":"10.1016/j.diii.2024.06.008","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141493942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.diii.2024.02.011
Paul Calame , Sébastien Mulé
{"title":"Dual-energy CT: Bridging the gap between innovation and clinical practice","authors":"Paul Calame , Sébastien Mulé","doi":"10.1016/j.diii.2024.02.011","DOIUrl":"10.1016/j.diii.2024.02.011","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140068822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}