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Fassia MK, Balasubramanian A, Woo S, Vargas HA, Hricak H, Konukoglu E, Becker AS. Deep Learning Prostate MRI Segmentation Accuracy and Robustness: A Systematic Review. Radiol Artif Intell 2024:e230138. [PMID: 38568094 DOI: 10.1148/ryai.230138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2024]
Abstract
"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To investigate the accuracy and robustness of prostate segmentation using deep learning across various training data sizes, MRI vendors, prostate zones, and testing methods relative to fellowship-trained diagnostic radiologists. Materials and methods In this systematic review, EMBASE, PubMed, Scopus and Web of Science databases were queried for English-language articles using keywords and related terms for prostate MRI segmentation and deep learning algorithms dated to July 31, 2022. A total of 691 articles from the search query were collected, and subsequently filtered to 48 based on predefined inclusion and exclusion criteria. Multiple characteristics were extracted from selected studies, such as deep learning algorithm performance, MRI vendor, and training dataset features. The primary outcome was comparison of mean Dice similarity coefficient (DSC) for prostate segmentation for deep learning algorithms versus diagnostic radiologists. Results Forty-eight studies were included. The vast majority of published deep learning algorithms for whole prostate gland segmentation (39/42 or 93%) had a DSC at or above expert level (DSC ≥ 0.86). The mean DSC was 0.79 ± 0.06 for peripheral zone, 0.87 ± 0.05 for transition zone, and 0.90 ± 0.04 for whole prostate gland segmentation. For selected studies using one major MRI vendor, the mean DSCs of each were as follows: GE (3/48 studies) 0.92 ± 0.03, Philips (4/48 studies) 0.92 ± 0.02, and Siemens (6/48 studies) 0.91 ± 0.03. Conclusion Deep learning algorithms for prostate MRI segmentation demonstrated comparable accuracy to expert radiologists despite varying parameters, therefore future research should shift toward evaluating segmentation robustness and patient outcomes across diverse clinical settings. ©RSNA, 2024.
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Affiliation(s)
- Mohammad-Kasim Fassia
- From the Departments of Radiology (M.K.F.) and Urology (A.B.), NewYork-Presbyterian Weill Cornell Medical Center, 525 E 68th St, New York, NY 10065-4870; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (S.W., H.A.V., H.H., A.S.B.); and Department of Biomedical Imaging, ETH-Zurich, Zurich Switzerland (E.K.)
| | - Adithiya Balasubramanian
- From the Departments of Radiology (M.K.F.) and Urology (A.B.), NewYork-Presbyterian Weill Cornell Medical Center, 525 E 68th St, New York, NY 10065-4870; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (S.W., H.A.V., H.H., A.S.B.); and Department of Biomedical Imaging, ETH-Zurich, Zurich Switzerland (E.K.)
| | - Sungmin Woo
- From the Departments of Radiology (M.K.F.) and Urology (A.B.), NewYork-Presbyterian Weill Cornell Medical Center, 525 E 68th St, New York, NY 10065-4870; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (S.W., H.A.V., H.H., A.S.B.); and Department of Biomedical Imaging, ETH-Zurich, Zurich Switzerland (E.K.)
| | - Hebert Alberto Vargas
- From the Departments of Radiology (M.K.F.) and Urology (A.B.), NewYork-Presbyterian Weill Cornell Medical Center, 525 E 68th St, New York, NY 10065-4870; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (S.W., H.A.V., H.H., A.S.B.); and Department of Biomedical Imaging, ETH-Zurich, Zurich Switzerland (E.K.)
| | - Hedvig Hricak
- From the Departments of Radiology (M.K.F.) and Urology (A.B.), NewYork-Presbyterian Weill Cornell Medical Center, 525 E 68th St, New York, NY 10065-4870; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (S.W., H.A.V., H.H., A.S.B.); and Department of Biomedical Imaging, ETH-Zurich, Zurich Switzerland (E.K.)
| | - Ender Konukoglu
- From the Departments of Radiology (M.K.F.) and Urology (A.B.), NewYork-Presbyterian Weill Cornell Medical Center, 525 E 68th St, New York, NY 10065-4870; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (S.W., H.A.V., H.H., A.S.B.); and Department of Biomedical Imaging, ETH-Zurich, Zurich Switzerland (E.K.)
| | - Anton S Becker
- From the Departments of Radiology (M.K.F.) and Urology (A.B.), NewYork-Presbyterian Weill Cornell Medical Center, 525 E 68th St, New York, NY 10065-4870; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (S.W., H.A.V., H.H., A.S.B.); and Department of Biomedical Imaging, ETH-Zurich, Zurich Switzerland (E.K.)
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Becker AS, Das JP, Woo S, Vilela de Oliveira C, Charbel C, Perez-Johnston R, Vargas HA. Body oncologic imaging subspecialty training a curriculum based on the experience in a tertiary cancer center. Eur J Radiol 2024; 173:111396. [PMID: 38428254 PMCID: PMC10989997 DOI: 10.1016/j.ejrad.2024.111396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 02/19/2024] [Accepted: 02/25/2024] [Indexed: 03/03/2024]
Abstract
PURPOSE To describe the structure of a dedicated body oncologic imaging fellowship program. To summarize the numbers and types of cross-sectional imaging examinations reported by fellows. METHODS The curriculum, training methods, and assessment measures utilized in the program were reviewed and described. An educational retrospective analysis was conducted. Data on the number of examinations interpreted by fellows, breakdown of modalities, and examinations by disease management team (DMT) were collected. RESULTS A total of 38 fellows completed the fellowship program during the study period. The median number of examinations reported per fellow was 2296 [interquartile range: 2148 - 2534], encompassing all oncology-relevant imaging modalities: CT 721 [646-786], MRI 1158 [1016-1309], ultrasound 256 [209-320] and PET/CT 176 [130-202]. The breakdown of examinations by DMT revealed variations in imaging patterns, with MRIs most frequently interpreted for genitourinary, musculoskeletal, and hepatobiliary cancers, and CTs most commonly for general staging or assessment of nonspecific symptoms. CONCLUSION This descriptive analysis may serve as a foundation for the development of similar fellowship programs and the advancement of body oncologic imaging. The volume and diversity of examinations reported by fellows highlights the comprehensive nature of body oncologic imaging.
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Affiliation(s)
- Anton S Becker
- Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY; Department of Radiology, Oncologic Imaging Service, NYU Langone, New York, NY. https://twitter.com/@becker_rad
| | - Jeeban P Das
- Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY.
| | - Sungmin Woo
- Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY; Department of Radiology, Oncologic Imaging Service, NYU Langone, New York, NY.
| | - Camila Vilela de Oliveira
- Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY.
| | - Charlotte Charbel
- Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY; Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA.
| | - Rocio Perez-Johnston
- Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY; Department of Radiology, Anschutz Medical Center, University of Colorado, Denver CO.
| | - Hebert Alberto Vargas
- Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY; Department of Radiology, Oncologic Imaging Service, NYU Langone, New York, NY.
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Becker AS, Chaim J, Vargas HA. Streamlining Radiology Workflows Through the Development and Deployment of Automated Microservices. J Imaging Inform Med 2024:10.1007/s10278-024-01034-9. [PMID: 38351225 DOI: 10.1007/s10278-024-01034-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 01/17/2024] [Accepted: 01/31/2024] [Indexed: 04/28/2024]
Abstract
Microservices are a software development approach where an application is structured as a collection of loosely coupled, independently deployable services, each focusing on executing a specific purpose. The development of microservices could have a significant impact on radiology workflows, allowing routine tasks to be automated and improving the efficiency and accuracy of radiologic tasks. This technical report describes the development of several microservices that have been successfully deployed in a tertiary cancer center, resulting in substantial time savings for radiologists and other staff involved in radiology workflows. These microservices include the automatic generation of shift emails, notifying administrative staff and faculty about fellows on rotation, notifying referring physicians about outside examinations, and populating report templates with information from PACS and RIS. The report outlines the common thought process behind developing these microservices, including identifying a problem, connecting various APIs, collecting data in a database, writing a prototype and deploying it, gathering feedback and refining the service, putting it in production, and identifying staff who are in charge of maintaining the service. The report concludes by discussing the benefits and challenges of microservices in radiology workflows, highlighting the importance of multidisciplinary collaboration, interoperability, security, and privacy.
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Affiliation(s)
- Anton S Becker
- Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
- Department of Radiology, Oncologic Imaging Service, NYU Langone, New York, NY, USA.
| | - Joshua Chaim
- Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Hebert Alberto Vargas
- Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
- Department of Radiology, Oncologic Imaging Service, NYU Langone, New York, NY, USA
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Law W, Terzic A, Chaim J, Erinjeri JP, Hricak H, Vargas HA, Becker AS. Integrated Automatic Examination Assignment Reduces Radiologist Interruptions: A 2-Year Cohort Study of 232,022 Examinations. J Imaging Inform Med 2024; 37:25-30. [PMID: 38343207 PMCID: PMC10976913 DOI: 10.1007/s10278-023-00917-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 10/07/2023] [Accepted: 10/09/2023] [Indexed: 03/02/2024]
Abstract
Radiology departments face challenges in delivering timely and accurate imaging reports, especially in high-volume, subspecialized settings. In this retrospective cohort study at a tertiary cancer center, we assessed the efficacy of an Automatic Assignment System (AAS) in improving radiology workflow efficiency by analyzing 232,022 CT examinations over a 12-month period post-implementation and compared it to a historical control period. The AAS was integrated with the hospital-wide scheduling system and set up to automatically prioritize and distribute unreported CT examinations to available radiologists based on upcoming patient appointments, coupled with an email notification system. Following this AAS implementation, despite a 9% rise in CT volume, coupled with a concurrent 8% increase in the number of available radiologists, the mean daily urgent radiology report requests (URR) significantly decreased by 60% (25 ± 12 to 10 ± 5, t = -17.6, p < 0.001), and URR during peak days (95th quantile) was reduced by 52.2% from 46 to 22 requests. Additionally, the mean turnaround time (TAT) for reporting was significantly reduced by 440 min for patients without immediate appointments and by 86 min for those with same-day appointments. Lastly, patient waiting time sampled in one of the outpatient clinics was not negatively affected. These results demonstrate that AAS can substantially decrease workflow interruptions and improve reporting efficiency.
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Affiliation(s)
- Wyanne Law
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Admir Terzic
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Joshua Chaim
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Joseph P Erinjeri
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Hedvig Hricak
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Hebert Alberto Vargas
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Radiology, Oncologic Imaging Division, NYU Langone, New York, NY, USA
| | - Anton S Becker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- Department of Radiology, Oncologic Imaging Division, NYU Langone, New York, NY, USA.
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Woo S, Becker AS, Das JP, Ghafoor S, Arita Y, Benfante N, Gangai N, Teo MY, Goh AC, Vargas HA. Evaluating residual tumor after neoadjuvant chemotherapy for muscle-invasive urothelial bladder cancer: diagnostic performance and outcomes using biparametric vs. multiparametric MRI. Cancer Imaging 2023; 23:110. [PMID: 37964386 PMCID: PMC10644594 DOI: 10.1186/s40644-023-00632-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 11/03/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND Neoadjuvant chemotherapy (NAC) before radical cystectomy is standard of care in patients with muscle-invasive bladder cancer (MIBC). Response assessment after NAC is important but suboptimal using CT. We assessed MRI without vs. with intravenous contrast (biparametric [BP] vs. multiparametric [MP]) for identifying residual disease on cystectomy and explored its prognostic role. METHODS Consecutive MIBC patients that underwent NAC, MRI, and cystectomy between January 2000-November 2022 were identified. Two radiologists reviewed BP-MRI (T2 + DWI) and MP-MRI (T2 + DWI + DCE) for residual tumor. Diagnostic performances were compared using receiver operating characteristic curve analysis. Kaplan-Meier curves and Cox proportional-hazards models were used to evaluate association with disease-free survival (DFS). RESULTS 61 patients (36 men and 25 women; median age 65 years, interquartile range 59-72) were included. After NAC, no residual disease was detected on pathology in 19 (31.1%) patients. BP-MRI was more accurate than MP-MRI for detecting residual disease after NAC: area under the curve = 0.75 (95% confidence interval (CI), 0.62-0.85) vs. 0.58 (95% CI, 0.45-0.70; p = 0.043). Sensitivity were identical (65.1%; 95% CI, 49.1-79.0) but specificity was higher in BP-MRI compared with MP-MRI for determining residual disease: 77.8% (95% CI, 52.4-93.6) vs. 38.9% (95% CI, 17.3-64.3), respectively. Positive BP-MRI and residual disease on pathology were both associated with worse DFS: hazard ratio (HR) = 4.01 (95% CI, 1.70-9.46; p = 0.002) and HR = 5.13 (95% CI, 2.66-17.13; p = 0.008), respectively. Concordance between MRI and pathology results was significantly associated with DFS. Concordant positive (MRI+/pathology+) patients showed worse DFS than concordant negative (MRI-/pathology-) patients (HR = 8.75, 95% CI, 2.02-37.82; p = 0.004) and compared to the discordant group (MRI+/pathology- or MRI-/pathology+) with HR = 3.48 (95% CI, 1.39-8.71; p = 0.014). CONCLUSION BP-MRI was more accurate than MP-MRI for identifying residual disease after NAC. A negative BP-MRI was associated with better outcomes, providing complementary information to pathological assessment of cystectomy specimens.
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Affiliation(s)
- Sungmin Woo
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
- Department of Radiology, NYU Langone Health, 660 1st Avenue, New York, NY, 10016, USA.
| | - Anton S Becker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
- Department of Radiology, NYU Langone Health, 660 1st Avenue, New York, NY, 10016, USA
| | - Jeeban P Das
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Soleen Ghafoor
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, Zürich, CH-8091, Switzerland
| | - Yuki Arita
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Nicole Benfante
- Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Natalie Gangai
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Min Yuen Teo
- Genitourinary Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Alvin C Goh
- Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Hebert A Vargas
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
- Department of Radiology, NYU Langone Health, 660 1st Avenue, New York, NY, 10016, USA
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Becker AS, Das JP, Woo S, Perez-Johnston R, Vargas HA. Improving Radiology Oncologic Imaging Trainee Case Diversity through Automatic Examination Assignment: Retrospective Study from a Tertiary Cancer Center. Radiol Imaging Cancer 2023; 5:e230035. [PMID: 37889137 DOI: 10.1148/rycan.230035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
In a retrospective single-center study, the authors assessed the efficacy of an automated imaging examination assignment system for enhancing the diversity of subspecialty examinations reported by oncologic imaging fellows. The study aimed to mitigate traditional biases of manual case selection and ensure equitable exposure to various case types. Methods included evaluating the proportion of "uncommon" to "common" cases reported by fellows before and after system implementation and measuring the weekly Shannon Diversity Index to determine case distribution equity. The proportion of reported uncommon cases more than doubled from 8.6% to 17.7% in total, at the cost of a concurrent 9.0% decrease in common cases from 91.3% to 82.3%. The weekly Shannon Diversity Index per fellow increased significantly from 0.66 (95% CI: 0.65, 0.67) to 0.74 (95% CI: 0.72, 0.75; P < .001), confirming a more balanced case distribution among fellows after introduction of the automatic assignment. © RSNA, 2023 Keywords: Computer Applications, Education, Fellows, Informatics, MRI, Oncologic Imaging.
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Affiliation(s)
- Anton S Becker
- From the Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065 (A.S.B., J.P.D., S.W., R.P.J., H.A.V.); and Department of Radiology, NYU Langone Medical Center, New York, NY (A.S.B., S.W., H.A.V.)
| | - Jeeban P Das
- From the Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065 (A.S.B., J.P.D., S.W., R.P.J., H.A.V.); and Department of Radiology, NYU Langone Medical Center, New York, NY (A.S.B., S.W., H.A.V.)
| | - Sungmin Woo
- From the Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065 (A.S.B., J.P.D., S.W., R.P.J., H.A.V.); and Department of Radiology, NYU Langone Medical Center, New York, NY (A.S.B., S.W., H.A.V.)
| | - Rocio Perez-Johnston
- From the Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065 (A.S.B., J.P.D., S.W., R.P.J., H.A.V.); and Department of Radiology, NYU Langone Medical Center, New York, NY (A.S.B., S.W., H.A.V.)
| | - Hebert Alberto Vargas
- From the Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065 (A.S.B., J.P.D., S.W., R.P.J., H.A.V.); and Department of Radiology, NYU Langone Medical Center, New York, NY (A.S.B., S.W., H.A.V.)
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Becker AS, Giganti F, Purysko AS, Fainberg J, Vargas HA, Woo S. Taking PI-QUAL beyond the prostate: Towards a standardized radiological image quality score (RI-QUAL). Eur J Radiol 2023; 165:110955. [PMID: 37421773 PMCID: PMC10404469 DOI: 10.1016/j.ejrad.2023.110955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 06/25/2023] [Accepted: 06/29/2023] [Indexed: 07/10/2023]
Abstract
PURPOSE To compare the interreader agreement of a novel quality score, called the Radiological Image Quality Score (RI-QUAL), to a slighly modified version of the existing Prostate Imaging Quality (mPI-QUAL) score for magnetic resonance imaging (MRI) of the prostate. METHODS A total of 43 consecutive scans were evaluated by two subspecialized radiologists who assigned scores using both the RI-QUAL and mPI-QUAL methods. The interreader agreement was analyzed using three statistical methods: concordance correlation coefficient (CCC), intraclass correlation coefficient (ICC), and Cohen's kappa. Time needed to arrive at a quality judgment was measured and compared using the Wilcoxon signed rank test. RESULTS The interreader agreement for RI-QUAL and mPI-QUAL scores was comparable, as evidenced by the high CCC (0.76 vs. 0.77, p = 0.93), ICC (0.86 vs. 0.87, p = 0.93), and moderate Cohen's kappa (0.61 vs. 0.64, p = 0.85) values. Moreover, RI-QUAL assessment was faster than mPI-QUAL (19 vs. 40 s, p = 0.001). CONCLUSION RI-QUAL is a new quality score that has comparable interreader agreement to the mPI-QUAL score, but with the potential to be applied to different MRI protocols and even different modalities. Like PI-QUAL, RI-QUAL may also facilitate communication about quality to referring physicians, as it provides a standardized and easily interpretable score. Further studies are warranted to validate the usefulness of RI-QUAL in larger patient cohorts and for other imaging modalities.
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Affiliation(s)
- Anton S Becker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States; Department of Radiology, NYU Langone, New York, NY, United States.
| | - Francesco Giganti
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK; Division of Surgery & Interventional Science, University College London, London, UK
| | - Andrei S Purysko
- Department of Radiology, Abdominal Imaging Section, Cleveland Clinic, Cleveland, OH, United States
| | - Jonathan Fainberg
- Department of Urology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Hebert Alberto Vargas
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States; Department of Radiology, NYU Langone, New York, NY, United States
| | - Sungmin Woo
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
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Cheng M, Duzgol C, Kim TH, Ghafoor S, Becker AS, Causa Andrieu PI, Gangai N, Jiang H, Hakimi AA, Vargas HA, Woo S. Sarcomatoid renal cell carcinoma: MRI features and their association with survival. Cancer Imaging 2023; 23:16. [PMID: 36793052 PMCID: PMC9930281 DOI: 10.1186/s40644-023-00535-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 02/13/2023] [Indexed: 02/17/2023] Open
Abstract
OBJECTIVE To evaluate MRI features of sarcomatoid renal cell carcinoma (RCC) and their association with survival. METHODS This retrospective single-center study included 59 patients with sarcomatoid RCC who underwent MRI before nephrectomy during July 2003-December 2019. Three radiologists reviewed MRI findings of tumor size, non-enhancing areas, lymphadenopathy, and volume (and percentage) of T2 low signal intensity areas (T2LIA). Clinicopathological factors of age, gender, ethnicity, baseline metastatic status, pathological details (subtype and extent of sarcomatoid differentiation), treatment type, and follow-up were extracted. Survival was estimated using Kaplan-Meier method and Cox proportional-hazards regression model was used to identify factors associated with survival. RESULTS Forty-one males and eighteen females (median age 62 years; interquartile range 51-68) were included. T2LIAs were present in 43 (72.9%) patients. At univariate analysis, clinicopathological factors associated with shorter survival were: greater tumor size (> 10 cm; HR [hazard ratio] = 2.44, 95% CI 1.15-5.21; p = 0.02), metastatic lymph nodes (present; HR = 2.10, 95% CI 1.01-4.37; p = 0.04), extent of sarcomatoid differentiation (non-focal; HR = 3.30, 95% CI 1.55-7.01; p < 0.01), subtypes other than clear cell, papillary, or chromophobe (HR = 3.25, 95% CI 1.28-8.20; p = 0.01), and metastasis at baseline (HR = 5.04, 95% CI 2.40-10.59; p < 0.01). MRI features associated with shorter survival were: lymphadenopathy (HR = 2.24, 95% CI 1.16-4.71; p = 0.01) and volume of T2LIA (> 3.2 mL, HR = 4.22, 95% CI 1.92-9.29); p < 0.01). At multivariate analysis, metastatic disease (HR = 6.89, 95% CI 2.79-16.97; p < 0.01), other subtypes (HR = 9.50, 95% CI 2.81-32.13; p < 0.01), and greater volume of T2LIA (HR = 2.51, 95% CI 1.04-6.05; p = 0.04) remained independently associated with worse survival. CONCLUSION T2LIAs were present in approximately two thirds of sarcomatoid RCCs. Volume of T2LIA along with clinicopathological factors were associated with survival.
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Affiliation(s)
- Monica Cheng
- grid.51462.340000 0001 2171 9952Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065 USA ,grid.38142.3c000000041936754XDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA
| | - Cihan Duzgol
- grid.51462.340000 0001 2171 9952Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065 USA ,grid.461527.30000 0004 0383 4123Department of Radiology, Lowell General Hospital, 295 Varnum Avenue, Lowell, MA 01854, USA
| | - Tae-Hyung Kim
- grid.51462.340000 0001 2171 9952Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065 USA
| | - Soleen Ghafoor
- grid.412004.30000 0004 0478 9977Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Anton S. Becker
- grid.51462.340000 0001 2171 9952Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065 USA
| | - Pamela I. Causa Andrieu
- grid.51462.340000 0001 2171 9952Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065 USA
| | - Natalie Gangai
- grid.51462.340000 0001 2171 9952Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065 USA
| | - Hui Jiang
- grid.51462.340000 0001 2171 9952Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - Abraham A. Hakimi
- grid.51462.340000 0001 2171 9952Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - Hebert A. Vargas
- grid.51462.340000 0001 2171 9952Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065 USA
| | - Sungmin Woo
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, 10065, USA.
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Ferraro DA, Hötker AM, Becker AS, Mebert I, Laudicella R, Baltensperger A, Rupp NJ, Rueschoff JH, Müller J, Mortezavi A, Sapienza MT, Eberli D, Donati OF, Burger IA. 68Ga-PSMA-11 PET/MRI versus multiparametric MRI in men referred for prostate biopsy: primary tumour localization and interreader agreement. Eur J Hybrid Imaging 2022; 6:14. [PMID: 35843966 PMCID: PMC9288941 DOI: 10.1186/s41824-022-00135-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 04/03/2022] [Indexed: 11/20/2022] Open
Abstract
Background Magnetic resonance imaging (MRI) is recommended by the European Urology Association guidelines as the standard modality for imaging-guided biopsy. Recently positron emission tomography with prostate-specific membrane antigen (PSMA PET) has shown promising results as a tool for this purpose. The aim of this study was to compare the accuracy of positron emission tomography with prostate-specific membrane antigen/magnetic resonance imaging (PET/MRI) using the gallium-labeled prostate-specific membrane antigen (68Ga-PSMA-11) and multiparametric MRI (mpMRI) for pre-biopsy tumour localization and interreader agreement for visual and semiquantitative analysis. Semiquantitative parameters included apparent diffusion coefficient (ADC) and maximum lesion diameter for mpMRI and standardized uptake value (SUVmax) and PSMA-positive volume (PSMAvol) for PSMA PET/MRI. Results Sensitivity and specificity were 61.4% and 92.9% for mpMRI and 66.7% and 92.9% for PSMA PET/MRI for reader one, respectively. RPE was available in 23 patients and 41 of 47 quadrants with discrepant findings. Based on RPE results, the specificity for both imaging modalities increased to 98% and 99%, and the sensitivity improved to 63.9% and 72.1% for mpMRI and PSMA PET/MRI, respectively. Both modalities yielded a substantial interreader agreement for primary tumour localization (mpMRI kappa = 0.65 (0.52–0.79), PSMA PET/MRI kappa = 0.73 (0.61–0.84)). ICC for SUVmax, PSMAvol and lesion diameter were almost perfect (≥ 0.90) while for ADC it was only moderate (ICC = 0.54 (0.04–0.78)). ADC and lesion diameter did not correlate significantly with Gleason score (ρ = 0.26 and ρ = 0.16) while SUVmax and PSMAvol did (ρ = − 0.474 and ρ = − 0.468). Conclusions PSMA PET/MRI has similar accuracy and reliability to mpMRI regarding primary prostate cancer (PCa) localization. In our cohort, semiquantitative parameters from PSMA PET/MRI correlated with tumour grade and were more reliable than the ones from mpMRI. Supplementary Information The online version contains supplementary material available at 10.1186/s41824-022-00135-4.
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Chen MM, Terzic A, Becker AS, Johnson JM, Wu CC, Wintermark M, Wald C, Wu J. Artificial intelligence in oncologic imaging. Eur J Radiol Open 2022; 9:100441. [PMID: 36193451 PMCID: PMC9525817 DOI: 10.1016/j.ejro.2022.100441] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/25/2022] [Accepted: 09/26/2022] [Indexed: 01/07/2023] Open
Abstract
Radiology is integral to cancer care. Compared to molecular assays, imaging has its advantages. Imaging as a noninvasive tool can assess the entirety of tumor unbiased by sampling error and is routinely acquired at multiple time points in oncological practice. Imaging data can be digitally post-processed for quantitative assessment. The ever-increasing application of Artificial intelligence (AI) to clinical imaging is challenging radiology to become a discipline with competence in data science, which plays an important role in modern oncology. Beyond streamlining certain clinical tasks, the power of AI lies in its ability to reveal previously undetected or even imperceptible radiographic patterns that may be difficult to ascertain by the human sensory system. Here, we provide a narrative review of the emerging AI applications relevant to the oncological imaging spectrum and elaborate on emerging paradigms and opportunities. We envision that these technical advances will change radiology in the coming years, leading to the optimization of imaging acquisition and discovery of clinically relevant biomarkers for cancer diagnosis, staging, and treatment monitoring. Together, they pave the road for future clinical translation in precision oncology.
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Affiliation(s)
- Melissa M. Chen
- Department of Neuroradiology, MD Anderson Cancer Center, Houston, TX, USA
| | - Admir Terzic
- Department of Radiology, Dom Zdravlja Odzak, Odzak, Bosnia and Herzegovina
| | - Anton S. Becker
- Department Radiology, Memorial Sloan Kettering, New York, NY, USA
| | - Jason M. Johnson
- Department of Neuroradiology, MD Anderson Cancer Center, Houston, TX, USA
| | - Carol C. Wu
- Department of Thoracic Imaging, MD Anderson Cancer Center, Houston, TX, USA
| | - Max Wintermark
- Department of Neuroradiology, MD Anderson Cancer Center, Houston, TX, USA
| | - Christoph Wald
- Department of Radiology, Lahey Hospital and Medical Center, Burlington, MA, USA
| | - Jia Wu
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA
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11
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Becker AS, Das JP, Woo S, Elnajjar P, Chaim J, Erinjeri JP, Hricak H, Vargas HA. Programmatic Implementation of a Custom Subspecialized Oncologic Imaging Workflow Manager at a Tertiary Cancer Center. JCO Clin Cancer Inform 2022; 6:e2200066. [PMID: 36084275 PMCID: PMC9848557 DOI: 10.1200/cci.22.00066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 07/27/2022] [Accepted: 08/09/2022] [Indexed: 01/26/2023] Open
Abstract
PURPOSE To evaluate whether a custom programmatic workflow manager reduces reporting turnaround times (TATs) from a body oncologic imaging workflow at a tertiary cancer center. METHODS A custom software program was developed and implemented in the programming language R. Other aspects of the workflow were left unchanged. TATs were measured over a 12-month period (June-May). The same prior 12-month period served as a historical control. Median TATs of magnetic resonance imaging (MRI) and computed tomography (CT) examinations were compared with a Wilcoxon test. A chi-square test was used to compare the numbers of examinations reported within 24 hours and after 72 hours as well as the proportions of examinations assigned according to individual radiologist preferences. RESULTS For all MRI and CT examinations (124,507 in 2019/2020 and 138,601 in 2020/2021), the median TAT decreased from 4 (interquartile range: 1-22 hours) to 3 hours (1-17 hours). Reports completed within 24 hours increased from 78% (124,127) to 89% (138,601). For MRI, TAT decreased from 22 (5-49 hours) to 8 hours (2-21 hours), and reports completed within 24 hours increased from 55% (14,211) to 80% (23,744). For CT, TAT decreased from 3 (1-19 hours) to 2 hours (1-13 hours), and reports completed within 24 hours increased from 84% (82,342) to 92% (99,922). Delayed reports (with a TAT > 72 hours) decreased from 17.0% (4,176) to 2.2% (649) for MRI and from 2.5% (2,500) to 0.7% (745) for CT. All differences were statistically significant (P < .001). CONCLUSION The custom workflow management software program significantly decreased MRI and CT report TATs.
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Affiliation(s)
- Anton S. Becker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Jeeban P. Das
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Sungmin Woo
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Pierre Elnajjar
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Joshua Chaim
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Joseph P. Erinjeri
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Hedvig Hricak
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
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12
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Becker AS. Evolution of deep learning trends between 2012 and 2020: A perspective from the EJR editorial board. Eur J Radiol 2022; 155:110462. [PMID: 35964507 DOI: 10.1016/j.ejrad.2022.110462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 08/03/2022] [Indexed: 11/03/2022]
Affiliation(s)
- Anton S Becker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York 10065, United States.
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Laumer F, Di Vece D, Cammann VL, Würdinger M, Petkova V, Schönberger M, Schönberger A, Mercier JC, Niederseer D, Seifert B, Schwyzer M, Burkholz R, Corinzia L, Becker AS, Scherff F, Brouwers S, Pazhenkottil AP, Dougoud S, Messerli M, Tanner FC, Fischer T, Delgado V, Schulze PC, Hauck C, Maier LS, Nguyen H, Surikow SY, Horowitz J, Liu K, Citro R, Bax J, Ruschitzka F, Ghadri JR, Buhmann JM, Templin C. Assessment of Artificial Intelligence in Echocardiography Diagnostics in Differentiating Takotsubo Syndrome From Myocardial Infarction. JAMA Cardiol 2022; 7:494-503. [PMID: 35353118 PMCID: PMC8968683 DOI: 10.1001/jamacardio.2022.0183] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Importance Machine learning algorithms enable the automatic classification of cardiovascular diseases based on raw cardiac ultrasound imaging data. However, the utility of machine learning in distinguishing between takotsubo syndrome (TTS) and acute myocardial infarction (AMI) has not been studied. Objectives To assess the utility of machine learning systems for automatic discrimination of TTS and AMI. Design, Settings, and Participants This cohort study included clinical data and transthoracic echocardiogram results of patients with AMI from the Zurich Acute Coronary Syndrome Registry and patients with TTS obtained from 7 cardiovascular centers in the International Takotsubo Registry. Data from the validation cohort were obtained from April 2011 to February 2017. Data from the training cohort were obtained from March 2017 to May 2019. Data were analyzed from September 2019 to June 2021. Exposure Transthoracic echocardiograms of 224 patients with TTS and 224 patients with AMI were analyzed. Main Outcomes and Measures Area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of the machine learning system evaluated on an independent data set and 4 practicing cardiologists for comparison. Echocardiography videos of 228 patients were used in the development and training of a deep learning model. The performance of the automated echocardiogram video analysis method was evaluated on an independent data set consisting of 220 patients. Data were matched according to age, sex, and ST-segment elevation/non-ST-segment elevation (1 patient with AMI for each patient with TTS). Predictions were compared with echocardiographic-based interpretations from 4 practicing cardiologists in terms of sensitivity, specificity, and AUC calculated from confidence scores concerning their binary diagnosis. Results In this cohort study, apical 2-chamber and 4-chamber echocardiographic views of 110 patients with TTS (mean [SD] age, 68.4 [12.1] years; 103 [90.4%] were female) and 110 patients with AMI (mean [SD] age, 69.1 [12.2] years; 103 [90.4%] were female) from an independent data set were evaluated. This approach achieved a mean (SD) AUC of 0.79 (0.01) with an overall accuracy of 74.8 (0.7%). In comparison, cardiologists achieved a mean (SD) AUC of 0.71 (0.03) and accuracy of 64.4 (3.5%) on the same data set. In a subanalysis based on 61 patients with apical TTS and 56 patients with AMI due to occlusion of the left anterior descending coronary artery, the model achieved a mean (SD) AUC score of 0.84 (0.01) and an accuracy of 78.6 (1.6%), outperforming the 4 practicing cardiologists (mean [SD] AUC, 0.72 [0.02]) and accuracy of 66.9 (2.8%). Conclusions and Relevance In this cohort study, a real-time system for fully automated interpretation of echocardiogram videos was established and trained to differentiate TTS from AMI. While this system was more accurate than cardiologists in echocardiography-based disease classification, further studies are warranted for clinical application.
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Affiliation(s)
- Fabian Laumer
- Department of Computer Science, ETH Zurich, Zurich, Switzerland
| | - Davide Di Vece
- Department of Cardiology, University Hospital Zurich, Zurich, Switzerland
| | - Victoria L Cammann
- Department of Cardiology, University Hospital Zurich, Zurich, Switzerland
| | - Michael Würdinger
- Department of Cardiology, University Hospital Zurich, Zurich, Switzerland
| | - Vanya Petkova
- Department of Cardiology, University Hospital Zurich, Zurich, Switzerland
| | | | | | - Julien C Mercier
- Department of Cardiology, University Hospital Zurich, Zurich, Switzerland
| | - David Niederseer
- Department of Cardiology, University Hospital Zurich, Zurich, Switzerland
| | - Burkhardt Seifert
- Division of Biostatistics, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Moritz Schwyzer
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | | | - Luca Corinzia
- Department of Computer Science, ETH Zurich, Zurich, Switzerland
| | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Frank Scherff
- Department of Cardiology, University Hospital Zurich, Zurich, Switzerland
| | - Sofie Brouwers
- Department of Cardiology, University Hospital Zurich, Zurich, Switzerland
| | - Aju P Pazhenkottil
- Department of Cardiology, University Hospital Zurich, Zurich, Switzerland.,Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Svetlana Dougoud
- Department of Cardiology, University Hospital Zurich, Zurich, Switzerland
| | - Michael Messerli
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Felix C Tanner
- Department of Cardiology, University Hospital Zurich, Zurich, Switzerland
| | - Thomas Fischer
- Department of Cardiology, Kantonsspital Winterthur, Winterthur, Switzerland
| | - Victoria Delgado
- Department of Cardiology, Leiden University Medical Centre, Leiden, the Netherlands
| | - P Christian Schulze
- Department of Internal Medicine I, University Hospital Jena, Friedrich-Schiller-University Jena, Jena, Germany
| | - Christian Hauck
- Klinik und Poliklinik für Innere Medizin II, Universitätsklinikum Regensburg, Regensburg, Germany
| | - Lars S Maier
- Klinik und Poliklinik für Innere Medizin II, Universitätsklinikum Regensburg, Regensburg, Germany
| | - Ha Nguyen
- Department of Cardiology, Basil Hetzel Institute, Queen Elizabeth Hospital, University of Adelaide, Adelaide, Australia
| | - Sven Y Surikow
- Department of Cardiology, Basil Hetzel Institute, Queen Elizabeth Hospital, University of Adelaide, Adelaide, Australia
| | - John Horowitz
- Department of Cardiology, Basil Hetzel Institute, Queen Elizabeth Hospital, University of Adelaide, Adelaide, Australia
| | - Kan Liu
- Division of Cardiology, Heart and Vascular Center, University of Iowa, Iowa City
| | - Rodolfo Citro
- Heart Department, University Hospital "San Giovanni di Dio e Ruggi d'Aragona", Salerno, Italy.,IRCCS Neuromed, Pozzilli, (Isernia) Italy
| | - Jeroen Bax
- Department of Cardiology, Leiden University Medical Centre, Leiden, the Netherlands
| | - Frank Ruschitzka
- Department of Cardiology, University Hospital Zurich, Zurich, Switzerland
| | - Jelena-Rima Ghadri
- Department of Cardiology, University Hospital Zurich, Zurich, Switzerland
| | | | - Christian Templin
- Division of Biostatistics, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
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14
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Horvat JV, Sevilimedu V, Becker AS, Perez-Johnston R, Yeh R, Feigin KN. Frequency and outcomes of MRI-detected axillary adenopathy following COVID-19 vaccination. Eur Radiol 2022; 32:5752-5758. [PMID: 35247087 PMCID: PMC8897548 DOI: 10.1007/s00330-022-08655-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 01/18/2022] [Accepted: 02/13/2022] [Indexed: 12/14/2022]
Abstract
Objectives To assess the frequency of ipsilateral axillary adenopathy on breast MRI after COVID-19 vaccination. To investigate the duration, outcomes, and associated variables of vaccine-related adenopathy. Methods In this retrospective cohort study, our database was queried for patients who underwent breast MRI following COVID-19 vaccination from January 22, 2021, to March 21, 2021. The frequency of ipsilateral axillary adenopathy and possible associated variables were evaluated, including age, personal history of ipsilateral breast cancer, clinical indication for breast MRI, type of vaccine, side of vaccination, number of doses, and number of days between the vaccine and the MRI exam. The outcomes of the adenopathy were investigated, including the duration of adenopathy and biopsy results. Results A total of 357 patients were included. The frequency of adenopathy on breast MRI was 29% (104/357 patients). Younger patients and shorter time intervals from the second dose of the vaccine were significantly associated with the development of adenopathy (p = 0.002 for both). Most adenopathy resolved or decreased on follow-up, with 11% of patients presenting persistence of adenopathy up to 64 days after the second dose of the vaccine. Metastatic axillary carcinoma was diagnosed in three patients; all three had a current ipsilateral breast cancer diagnosis. Conclusions Vaccine-related adenopathy is a frequent event after COVID-19 vaccination; short-term follow-up is an appropriate clinical approach, except in patients with current ipsilateral breast cancer. Adenopathy may often persist 4–8 weeks after the second dose of the vaccine, thus favoring longer follow-up periods. Key Points • MRI-detected ipsilateral axillary adenopathy is a frequent benign finding after mRNA COVID-19 vaccination. • Axillary adenopathy following COVID-19 vaccination often persists > 4 weeks after vaccination, favoring longer follow-up periods. • In patients with concurrent ipsilateral breast cancer, axillary adenopathy can represent metastatic carcinoma and follow-up is not appropriate.
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Affiliation(s)
- Joao V Horvat
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 300 E 66th St, New York, NY, 10065, USA.
| | - Varadan Sevilimedu
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Anton S Becker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 300 E 66th St, New York, NY, 10065, USA
| | - Rocio Perez-Johnston
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 300 E 66th St, New York, NY, 10065, USA
| | - Randy Yeh
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 300 E 66th St, New York, NY, 10065, USA
| | - Kimberly N Feigin
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 300 E 66th St, New York, NY, 10065, USA
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15
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Leithner D, Schoder H, Haug AR, Vargas HA, Gibbs P, Häggström I, Rausch I, Weber M, Becker AS, Schwartz J, Mayerhoefer ME. Impact of ComBat harmonization on PET radiomics-based tissue classification: a dual-center PET/MR and PET/CT study. J Nucl Med 2022; 63:1611-1616. [PMID: 35210300 PMCID: PMC9536705 DOI: 10.2967/jnumed.121.263102] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 01/26/2022] [Indexed: 11/16/2022] Open
Abstract
Rationale: To determine whether ComBat harmonization improves 18F-FDG-PET radiomics-based tissue classification in pooled PET/MR and PET/CT datasets. Methods: Two-hundred patients who had undergone 18F-FDG-PET/MR (two scanners/vendors; 50 patients each) or -PET/CT (two scanners/vendors; 50 patients each) were retrospectively included. Grey-level histogram (GLH), co-occurrence matrix (GLCM), run-length matrix (GLRLM), size-zone matrix (GLSZM), and neighborhood grey-tone difference matrix (NGTDM) radiomic features were calculated for volumes of interest in the disease-free liver, spleen, and bone marrow. For individual feature classes and a multi-class radiomic signature, tissue classification was performed on ComBat-harmonized and unharmonized pooled data, using a multi-layer perceptron neural network. Results: Median accuracies in training/validation datasets were: GLH, 69.5/68.3% (harmonized) vs. 59.5/58.9% (unharmonized); GLCM, 92.1/86.1% vs. 53.6/50.0%; GLRLM, 84.8/82.8% vs. 62.4/58.3%; GLSZM, 87.6/85.6% vs. 56.2/52.8%; NGTDM, 79.5/77.2% vs. 54.8/53.9%, and radiomic signature, 86.9/84.4% vs. 62.9/58.3%. Conclusion: ComBat harmonization may be useful for multi-center 18F-FDG-PET radiomics studies using pooled PET/MR and PET/CT data.
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Affiliation(s)
| | - Heiko Schoder
- Memorial Sloan Kettering Cancer Center, United States
| | | | | | - Peter Gibbs
- Memorial Sloan Kettering Cancer Center, United States
| | - Ida Häggström
- Memorial Sloan Kettering Cancer Center, United States
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16
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Schindler V, Hente J, Murray FR, Hüllner M, Becker AS, Giezendanner S, Schnurre L, Bordier V, Pohl D. Adding a liquid test meal to a standardized lactulose hydrogen breath test significantly influences abdominal symptom generation and hydrogen values. Eur J Gastroenterol Hepatol 2021; 33:1485-1494. [PMID: 34609811 DOI: 10.1097/meg.0000000000002042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
OBJECTIVE While single sugar tests are controversially discussed, combination tests with meals are gaining more attention. The aim of this study was to analyze the impact of adding a test meal to lactulose hydrogen breath tests (LHBT) on hydrogen values and abdominal symptoms in patients with functional gastrointestinal disorders (FGIDs). METHODS Data of 81 FGID patients between 2014-2018 were analyzed. Patients underwent LHBT with 30 g lactulose + 300 mL water and a nutrient challenge test (NCT) including 400 mL liquid test meal + 30 g lactulose. To statistically assess the effect of a test meal on abdominal symptoms and H2, mixed-effect models were used. RESULTS Adding a test meal to LHBT showed a significant increase in nausea [odds ratio (OR) 1.4; 95% confidence interval (CI), 1.1-1.7], decrease in abdominal pain (OR 0.7; 95% CI, 0.6-0.9), borborygmi (OR 0.5; 95% CI, 0.4-0.6), diarrhea (OR 0.4; 95% CI, 0.3-0.6), and H2 production (estimate -5.3, SE 0.7, P < 0.001). The effect on bloating was only significant in functional dyspepsia, irritable bowel syndrome-functional dyspepsia mixed type and functional abdominal pain/bloating (OR 0.1; 95% CI, 0.0-0.2; OR 1.7; 95% CI, 1.2-2.3 resp OR 4.4; 95% CI, 1.8-10.6). CONCLUSIONS Significant effects on abdominal symptoms and H2 production by adding a test meal to LHBT in FGID patients are shown. Increased occurrence of nausea may be caused by gastric/duodenal hypersensitivity; decreased H2, diarrhea and borborygmi by slower and more physiologic gastric emptying resulting in later arrival of the test substance in the bowel. We recommend NCTs instead of LHBT to more physiologically represent FGID patients' meal-induced burden.
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Affiliation(s)
| | | | | | | | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich
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17
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Becker AS, Erinjeri JP, Chaim J, Kastango N, Elnajjar P, Hricak H, Vargas HA. Automatic Forecasting of Radiology Examination Volume Trends for Optimal Resource Planning and Allocation. J Digit Imaging 2021; 35:1-8. [PMID: 34755249 PMCID: PMC8577854 DOI: 10.1007/s10278-021-00532-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 09/12/2021] [Accepted: 10/30/2021] [Indexed: 11/11/2022] Open
Abstract
The aim of the study was to evaluate the performance of the Prophet forecasting procedure, part of the Facebook open-source Artificial Intelligence portfolio, for forecasting variations in radiological examination volumes. Daily CT and MRI examination volumes from our institution were extracted from the radiology information system (RIS) database. Data from January 1, 2015, to December 31, 2019, was used for training the Prophet algorithm, and data from January 2020 was used for validation. Algorithm performance was then evaluated prospectively in February and August 2020. Total error and mean error per day were evaluated, and computational time was logged using different Markov chain Monte Carlo (MCMC) samples. Data from 610,570 examinations were used for training; the majority were CTs (82.3%). During retrospective testing, prediction error was reduced from 19 to < 1 per day in CT (total 589 to 17) and from 5 to < 1 per day (total 144 to 27) in MRI by fine-tuning the Prophet procedure. Prospective prediction error in February was 11 per day in CT (9934 predicted, 9667 actual) and 1 per day in MRI (2484 predicted, 2457 actual) and was significantly better than manual weekly predictions (p = 0.001). Inference with MCMC added no substantial improvements while vastly increasing computational time. Prophet accurately models weekly, seasonal, and overall trends paving the way for optimal resource allocation for radiology exam acquisition and interpretation.
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Affiliation(s)
- Anton S Becker
- Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| | - Joseph P Erinjeri
- Department of Radiology, Interventional Radiology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Joshua Chaim
- Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Nicholas Kastango
- Department of Strategy and Innovation, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Pierre Elnajjar
- Department of Radiology, Informatics Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Hedvig Hricak
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - H Alberto Vargas
- Department of Radiology, Body Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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18
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Ghafoor S, Becker AS, Woo S, Causa Andrieu PI, Stocker D, Gangai N, Hricak H, Vargas HA. Comparison of PI-RADS Versions 2.0 and 2.1 for MRI-based Calculation of the Prostate Volume. Acad Radiol 2021; 28:1548-1556. [PMID: 32814644 DOI: 10.1016/j.acra.2020.07.027] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 07/20/2020] [Accepted: 07/21/2020] [Indexed: 01/25/2023]
Abstract
RATIONALE AND OBJECTIVES Prostate gland volume (PGV) should be routinely included in MRI reports of the prostate. The recently updated Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 includes a change in the recommended measurement method for PGV compared to version 2.0. The purpose of this study was to evaluate the agreement of MRI-based PGV calculations with the volumetric manual slice-by-slice prostate segmentation as a reference standard using the linear measurements per PI-RADS versions 2.0 and 2.1. Furthermore, to assess inter-reader agreement for the different measurement approaches, determine the influence of an enlarged transition zone on measurement accuracy and to assess the value of the bullet formula for PGV calculation. MATERIALS AND METHODS Ninety-five consecutive treatment-naive patients undergoing prostate MRI were retrospectively analyzed. Prostates were manually contoured and segmented on axial T2-weighted images. Four different radiologists independently measured the prostate in three dimensions according to PI-RADS v2.0 and v2.1, respectively. MRI-based PGV was calculated using the ellipsoid and bullet formulas. Calculated volumes were compared to the reference manual segmentations using Wilcoxon signed-rank test. Inter-reader agreement was calculated using intraclass correlation coefficient (ICC). RESULTS Inter-reader agreement was excellent for the ellipsoid and bullet formulas using PI-RADS v2.0 (ICC 0.985 and 0.987) and v2.1 (ICC 0.990 and 0.994), respectively. The median difference from the reference standard using the ellipsoid formula derived PGV was 0.4 mL (interquartile range, -3.9 to 5.1 mL) for PI-RADS v2.0 (p = 0.393) and 2.6 mL (interquartile range, -1.6 to 7.3 mL) for v2.1 (p < 0.001) with a median difference of 2.2 mL. The bullet formula overestimated PGV by a median of 13.3 mL using PI-RADS v2.0 (p < 0.001) and 16.0 mL using v2.1 (p < 0.001). In the presence of an enlarged transition zone the PGV tended to be higher than the reference standard for PI-RADS v2.0 (median difference of 4.7 mL; p = 0.018) and for v2.1 (median difference of 5.7 mL, p < 0.001) using the ellipsoid formula. CONCLUSION Inter-reader agreement was excellent for the calculated PGV for both methods. PI-RADS v2.0 measurements with the ellipsoid formula yielded the most accurate volume estimates. The differences between PI-RADS v2.0 and v2.1 were statistically significant although small in absolute numbers but may be of relevance in specific clinical scenarios like prostate-specific antigen density calculation. These findings validate the use of the ellipsoid formula and highlight that the bullet formula should not be used for prostate volume estimation due to systematic overestimation.
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Affiliation(s)
- Soleen Ghafoor
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.
| | - Anton S Becker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Sungmin Woo
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Pamela I Causa Andrieu
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Daniel Stocker
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Natalie Gangai
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Hedvig Hricak
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Hebert Alberto Vargas
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
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Braga Silva J, Busnello CV, Becker AS, Moriguchi CA, de Melo RO, Waichel VB. End-to-side neurorrhaphy in peripheral nerves: Does it work? Hand Surg Rehabil 2021; 41:2-6. [PMID: 34464758 DOI: 10.1016/j.hansur.2021.08.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 08/05/2021] [Accepted: 08/21/2021] [Indexed: 11/15/2022]
Abstract
Acute peripheral nerve injuries are common and can cause physical disabilities with sensory and functional sequelae; they therefore require surgery. The aim of this study was to conduct a systematic review to assess the clinical applicability of end-to-side neurorrhaphy in peripheral nerve reconstruction, based on available evidence. We carried out a systematic review of the literature using MEDLINE/PubMed, EMBASE, Cochrane Library, Web of Science, Scielo and Scopus through March 16, 2021. Most of the selected studies were qualitative and employed nonrandomized groups of patients, without standardized scales for assessing outcomes, which made statistical analysis difficult. Efficacy varied from 24% to 81%. Factors for better outcome included the type of injury, type of injured nerve (sensory, motor or mixed), presence of an epineural window, topography, injury extension <1.3 cm, and intervention within 2 weeks of injury. Clinical studies so far lack scientific evidence on end-to-side neurorrhaphy in peripheral nerve lesions.
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Affiliation(s)
- J Braga Silva
- Service of Hand Surgery and Reconstructive Microsurgery, São Lucas Hospital, Centro Clinico PUCRS, Av. Ipiranga 6690, Suite 216, 90610-000 Porto Alegre, Rio Grande do Sul, Brazil.
| | - C V Busnello
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, Av. Ipiranga 6690, 90610-000 Porto Alegre, Rio Grande do Sul, Brazil.
| | - A S Becker
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, Av. Ipiranga 6690, 90610-000 Porto Alegre, Rio Grande do Sul, Brazil.
| | - C A Moriguchi
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, Av. Ipiranga 6690, 90610-000 Porto Alegre, Rio Grande do Sul, Brazil.
| | - R O de Melo
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, Av. Ipiranga 6690, 90610-000 Porto Alegre, Rio Grande do Sul, Brazil.
| | - V B Waichel
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, Av. Ipiranga 6690, 90610-000 Porto Alegre, Rio Grande do Sul, Brazil.
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Hack RI, Becker AS, Bode-Lesniewska B, Exner GU, Müller DA, Ferraro DA, Warnock GI, Burger IA, Britschgi C. When SUV Matters: FDG PET/CT at Baseline Correlates with Survival in Soft Tissue and Ewing Sarcoma. Life (Basel) 2021; 11:life11090869. [PMID: 34575018 PMCID: PMC8468558 DOI: 10.3390/life11090869] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 08/20/2021] [Accepted: 08/20/2021] [Indexed: 01/19/2023] Open
Abstract
Introduction: The role of positron-emission tomography/computed-tomography (PET/CT) in the management of sarcomas and as a prognostic tool has been studied. However, it remains unclear which metric is the most useful. We aimed to investigate if volume-based PET metrics (Tumor volume (TV) and total lesions glycolysis (TLG)) are superior to maximal standardized uptake value (SUVmax) and other metrics in predicting survival of patients with soft tissue and bone sarcomas. Materials and Methods: In this retrospective cohort study, we screened over 52′000 PET/CT scans to identify patients diagnosed with either soft tissue, bone or Ewing sarcoma and had a staging scan at our institution before initial therapy. We used a Wilcoxon signed-rank to assess which PET/CT metric was associated with survival in different patient subgroups. Receiver-Operating-Characteristic curve analysis was used to calculate cutoff values. Results: We identified a total of 88 patients with soft tissue (51), bone (26) or Ewing (11) sarcoma. Median age at presentation was 40 years (Range: 9–86 years). High SUVmax was most significantly associated with short survival (defined as <24 months) in soft tissue sarcoma (with a median and range of SUVmax 12.5 (8.8–16.0) in short (n = 18) and 5.5 (3.3–7.2) in long survival (≥24 months) (n = 31), with (p = 0.001). Similar results were seen in Ewing sarcoma (with a median and range of SUVmax 12.1 (7.6–14.7) in short (n = 6) and 3.7 (3.5–5.5) in long survival (n = 5), with (p = 0.017). However, no PET-specific metric but tumor-volume was significantly associated (p = 0.035) with survival in primary bone sarcomas (with a median and range of 217 cm3 (186–349) in short survival (n = 4) and 60 cm3 (22–104) in long survival (n = 19), with (p = 0.035). TLG was significantly inversely associated with long survival only in Ewing sarcoma (p = 0.03). Discussion: Our analysis shows that the outcome of soft tissue, bone and Ewing sarcomas is associated with different PET/CT metrics. We could not confirm the previously suggested superiority of volume-based metrics in soft tissue sarcomas, for which we found SUVmax to remain the best prognostic factor. However, bone sarcomas should probably be evaluated with tumor volume rather than FDG PET activity.
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Affiliation(s)
- Ruben I. Hack
- Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, 8091 Zürich, Switzerland; (R.I.H.); (D.A.F.)
| | - Anton S. Becker
- Department of Interventional and Diagnostic Radiology, University Hospital Zürich, University of Zürich, 8091 Zürich, Switzerland;
| | - Beata Bode-Lesniewska
- Institute of Pathology and Molecular Pathology, University Hospital Zürich, University of Zürich, 8091 Zürich, Switzerland;
| | | | - Daniel A. Müller
- Balgrist University Hospital Zürich, Forchstrasse 340, 8008 Zürich, Switzerland;
| | - Daniela A. Ferraro
- Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, 8091 Zürich, Switzerland; (R.I.H.); (D.A.F.)
| | | | - Irene A. Burger
- Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, 8091 Zürich, Switzerland; (R.I.H.); (D.A.F.)
- Department of Nuclear Medicine, Kantonsspital Baden, 5404 Baden, Switzerland
- Correspondence:
| | - Christian Britschgi
- Department of Medical Oncology and Hematology, University Hospital Zürich, University of Zürich, 8091 Zürich, Switzerland;
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21
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Becker AS, Perez-Johnston R, Chikarmane SA, Chen MM, El Homsi M, Feigin KN, Gallagher KM, Hanna EY, Hicks M, Ilica AT, Mayer EL, Shinagare AB, Yeh R, Mayerhoefer ME, Hricak H, Vargas HA. Multidisciplinary Recommendations Regarding Post-Vaccine Adenopathy and Radiologic Imaging: Radiology Scientific Expert Panel. Radiology 2021; 300:E323-E327. [PMID: 33625298 PMCID: PMC7909071 DOI: 10.1148/radiol.2021210436] [Citation(s) in RCA: 81] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Vaccination-associated adenopathy is a frequent imaging finding after administration of COVID-19 vaccines that may lead to a diagnostic conundrum in patients with manifest or suspected cancer, in whom it may be indistinguishable from malignant nodal involvement. To help the medical community address this concern in the absence of studies and evidence-based guidelines, this special report offers recommendations developed by a multidisciplinary panel of experts from three of the leading tertiary care cancer centers in the United States. According to these recommendations, some routine imaging examinations, such as those for screening, should be scheduled before or at least 6 weeks after the final vaccination dose to allow for any reactive adenopathy to resolve. However, there should be no delay of other clinically indicated imaging (eg, for acute symptoms, short-interval treatment monitoring, urgent treatment planning or complications) due to prior vaccination. The vaccine should be administered on the side contralateral to the primary or suspected cancer, and both doses should be administered in the same arm. Vaccination information-date(s) administered, injection site(s), laterality, and type of vaccine-should be included in every preimaging patient questionnaire, and this information should be made readily available to interpreting radiologists. Clear and effective communication between patients, radiologists, referring physician teams, and the general public should be considered of the highest priority when managing adenopathy in the setting of COVID-19 vaccination.
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Affiliation(s)
- Anton S Becker
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - Rocio Perez-Johnston
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - Sona A Chikarmane
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - Melissa M Chen
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - Maria El Homsi
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - Kimberly N Feigin
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - Katherine M Gallagher
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - Ehab Y Hanna
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - Marshall Hicks
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - Ahmet T Ilica
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - Erica L Mayer
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - Atul B Shinagare
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - Randy Yeh
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - Marius E Mayerhoefer
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - Hedvig Hricak
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
| | - H Alberto Vargas
- From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room H-704, New York, NY 10065 (A.S.B., R.P.J., M.E.H., K.N.F., K.M.G., A.T.I., R.Y., M.E.M., H.H., H.A.V.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (S.A.C., A.B.S.); Departments of Imaging (S.A.C., A.B.S.) and Medical Oncology (E.L.M.), Dana-Farber Cancer Institute, Boston, Mass; and Division of Diagnostic Imaging (M.M.C., M.H.) and Department of Head and Neck Surgery (E.Y.H.), MD Anderson Cancer Center, Houston, Tex
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Stocker D, Manoliu A, Becker AS, Barth BK, Nanz D, Klarhöfer M, Donati OF. Impact of different phased-array coils on the quality of prostate magnetic resonance images. Eur J Radiol Open 2021; 8:100327. [PMID: 33644263 PMCID: PMC7889823 DOI: 10.1016/j.ejro.2021.100327] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 01/21/2021] [Accepted: 01/21/2021] [Indexed: 11/19/2022] Open
Abstract
Image quality is similar for different body phased-array receive coil setups. An 18-channel body phased-array receive coil setup achieved good image quality. 60-channel body phased-array receive coil setup slightly improves SNR in T2W images.
Purpose To evaluate the influence of body phased-array (BPA) receive coil setups on signal-to-noise ratio (SNR) and image quality (IQ) in prostate MRI. Methods This prospective study evaluated axial T2-weighted images (T2W-TSE) and DWI of the prostate in ten healthy volunteers with 18-channel (18CH), 30-channel and 60-channel (60CH) BPA receive coil setups. SNR and ADC values were assessed in the peripheral and transition zones (TZ). Two radiologists rated IQ features. Differences in qualitative and quantitative image features between BPA receive coil setups were compared. After correction for multiple comparisons, p-values <0.004 for quantitative and p-values <0.017 for qualitative image analysis were considered statistically significant. Results Significantly higher SNR was found in T2W-TSE images in the TZ using 60CH BPA compared to 18CH BPA coil setups (15.20 ± 4.22 vs. 7.68 ± 2.37; p = 0.001). There were no significant differences between all other quantitative (T2W-TSE, p = 0.007−0.308; DWI, p = 0.024−0.574) and qualitative image features (T2W-TSE, p = 0.083–1.0; DWI, p = 0.046–1.0). Conclusion 60CH BPA receive coil setup showed marginal SNR improvement in T2W-TSE images. Good IQ could be achieved with 18CH BPA coil setups.
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Key Words
- 18CH, BPA 18-channel body array coil
- 30CH, BPA 30-channel body array coil
- 60CH, BPA 60-channel body array coil
- ANOVA, Analysis of variances
- BPA, Body phased-array
- ERC, Endorectal coil
- ICC, Intra-class correlation coefficient
- IQR, Interquartile range
- Magnetic resonance imaging
- PSTT, Post-hoc paired-sample t-tests
- Prostate imaging
- ROIs, Region of interests
- SD, Standard deviation
- SNR, Signal to noise ratio
- Signal-to-noise ratio
- T2W-TSE, T2-weighted turbo spin echo
- mpMRI, Multi-parametric magnetic resonance imaging
- ss-DWI-EPI, Single-shot diffusion-weighting spin-echo echo-planar imaging
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Affiliation(s)
- Daniel Stocker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, Switzerland
| | - Andrei Manoliu
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, Switzerland
- Max-Planck UCL Centre for Computational Psychiatry and Ageing Research, London, UK
- Wellcome Trust Centre for Human Neuroimaging, UCL, London, UK
- Psychiatric University Hospital, University of Zurich, Switzerland
| | - Anton S. Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, Switzerland
| | - Borna K. Barth
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, Switzerland
| | - Daniel Nanz
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, Switzerland
- Swiss Center for Musculoskeletal Imaging, SCMI, Balgrist Campus AG, Switzerland and Medical Faculty, University of Zurich, Zurich, Switzerland
| | | | - Olivio F. Donati
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, Switzerland
- Corresponding author at: Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, CH-8091, Zurich, Switzerland.
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Kirchner J, O'Donoghue JA, Becker AS, Ulaner GA. Improved image reconstruction of 89Zr-immunoPET studies using a Bayesian penalized likelihood reconstruction algorithm. EJNMMI Phys 2021; 8:6. [PMID: 33469848 PMCID: PMC7815860 DOI: 10.1186/s40658-021-00352-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 01/05/2021] [Indexed: 12/04/2022] Open
Abstract
Purpose The aim of this study was to evaluate the use of a Bayesian penalized likelihood reconstruction algorithm (Q.Clear) for 89Zr-immunoPET image reconstruction and its potential to improve image quality and reduce the administered activity of 89Zr-immunoPET tracers. Methods Eight 89Zr-immunoPET whole-body PET/CT scans from three 89Zr-immunoPET clinical trials were selected for analysis. On average, patients were imaged 6.3 days (range 5.0–8.0 days) after administration of 69 MBq (range 65–76 MBq) of [89Zr]Zr-DFO-daratumumab, [89Zr]Zr-DFO-pertuzumab, or [89Zr]Zr-DFO-trastuzumab. List-mode PET data was retrospectively reconstructed using Q.Clear with incremental β-values from 150 to 7200, as well as standard ordered-subset expectation maximization (OSEM) reconstruction (2-iterations, 16-subsets, a 6.4-mm Gaussian transaxial filter, “heavy” z-axis filtering and all manufacturers’ corrections active). Reduced activities were simulated by discarding 50% and 75% of original counts in each list mode stream. All reconstructed PET images were scored for image quality and lesion detectability using a 5-point scale. SUVmax for normal liver and sites of disease and liver signal-to-noise ratio were measured. Results Q.Clear reconstructions with β = 3600 provided the highest scores for image quality. Images reconstructed with β-values of 3600 or 5200 using only 50% or 25% of the original counts provided comparable or better image quality scores than standard OSEM reconstruction images using 100% of counts. Conclusion The Bayesian penalized likelihood reconstruction algorithm Q.Clear improved the quality of 89Zr-immunoPET images. This could be used in future studies to improve image quality and/or decrease the administered activity of 89Zr-immunoPET tracers. Supplementary Information The online version contains supplementary material available at 10.1186/s40658-021-00352-z.
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Affiliation(s)
- Julian Kirchner
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, Dusseldorf, Germany
| | - Joseph A O'Donoghue
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Anton S Becker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Gary A Ulaner
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA. .,Department of Radiology, Weill Cornell Medical College, New York, NY, USA. .,Molecular Imaging and Therapy, Hoag Family Cancer Institute, Newport Beach, CA, USA.
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Loeliger RC, Maushart CI, Gashi G, Senn JR, Felder M, Becker AS, Müller J, Balaz M, Wolfrum C, Burger IA, Betz MJ. Relation of diet-induced thermogenesis to brown adipose tissue activity in healthy men. Am J Physiol Endocrinol Metab 2021; 320:E93-E101. [PMID: 33225717 DOI: 10.1152/ajpendo.00237.2020] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Human brown adipose tissue (BAT) is a thermogenic tissue activated by the sympathetic nervous system in response to cold exposure. It contributes to energy expenditure (EE) and takes up glucose and lipids from the circulation. Studies in rodents suggest that BAT contributes to the transient rise in EE after food intake, so-called diet-induced thermogenesis (DIT). We investigated the relationship between human BAT activity and DIT in response to glucose intake in 17 healthy volunteers. We assessed DIT, cold-induced thermogenesis (CIT), and maximum BAT activity at three separate study visits within 2 wk. DIT was measured by indirect calorimetry during an oral glucose tolerance test. CIT was assessed as the difference in EE after cold exposure of 2-h duration as compared with warm conditions. Maximal activity of BAT was assessed by 18-F-fluoro-deoxyglucose (18F-FDG) 18F-FDG-PET/MRI after cold exposure and concomitant pharmacological stimulation with mirabegron. Seventeen healthy men (mean age = 23.4 yr, mean body mass index = 23.2 kg/m2) participated in the study. EE increased from 1,908 (±181) kcal/24 h to 2,128 (±277) kcal/24 h (P < 0.0001, +11.5%) after mild cold exposure. An oral glucose load increased EE from 1,911 (±165) kcal/24 h to 2,096 (±167) kcal/24 h at 60 min (P < 0.0001, +9.7%). The increase in EE in response to cold was significantly associated with BAT activity (R2 = 0.43, P = 0.004). However, DIT was not associated with BAT activity (R2 = 0.015, P = 0.64). DIT after an oral glucose load was not associated with stimulated 18F-FDG uptake into BAT, suggesting that DIT is independent from BAT activity in humans (Clinicaltrials.gov Registration No. NCT03189511).NEW & NOTEWORTHY Cold-induced thermogenesis (CIT) was related to BAT activity as determined by FDG-PET/MRI after stimulation of BAT. Diet-induced thermogenesis (DIT) was not related to stimulated BAT activity. Supraclavicular skin temperature was related to CIT but not to DIT. DIT in humans is probably not a function of BAT.
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Affiliation(s)
- Rahel Catherina Loeliger
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Claudia Irene Maushart
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Gani Gashi
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jaël Rut Senn
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Martina Felder
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich/University of Zurich, Zurich, Switzerland
| | - Julian Müller
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich/University of Zurich, Zurich, Switzerland
| | - Miroslav Balaz
- Institute of Food, Nutrition, and Health, ETH Zurich, Schwerzenbach, Switzerland
| | - Christian Wolfrum
- Institute of Food, Nutrition, and Health, ETH Zurich, Schwerzenbach, Switzerland
| | - Irene A Burger
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich/University of Zurich, Zurich, Switzerland
| | - Matthias Johannes Betz
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel and University of Basel, Basel, Switzerland
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Felder M, Maushart CI, Gashi G, Senn JR, Becker AS, Müller J, Balaz M, Wolfrum C, Burger IA, Betz MJ. Fluvastatin Reduces Glucose Tolerance in Healthy Young Individuals Independently of Cold Induced BAT Activity. Front Endocrinol (Lausanne) 2021; 12:765807. [PMID: 34858338 PMCID: PMC8631514 DOI: 10.3389/fendo.2021.765807] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 10/14/2021] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Statins are commonly prescribed for primary and secondary prevention of atherosclerotic disease. They reduce cholesterol biosynthesis by inhibiting hydroxymethylglutaryl-coenzyme A-reductase (HMG-CoA-reductase) and therefore mevalonate synthesis. Several studies reported a small, but significant increase in the diagnosis of diabetes mellitus with statin treatment. The molecular mechanisms behind this adverse effect are not yet fully understood. Brown adipose tissue (BAT), which plays a role in thermogenesis, has been associated with a reduced risk of insulin resistance. Statins inhibit adipose tissue browning and have been negatively linked to the presence of BAT in humans. We therefore speculated that inhibition of BAT by statins contributes to increased insulin resistance in humans. METHODS A prospective study was conducted in 17 young, healthy men. After screening whether significant cold-induced thermogenesis (CIT) was present, participants underwent glucose tolerance testing (oGTT) and assessment of BAT activity by FDG-PET/MRI after cold-exposure and treatment with a β3-agonist. Fluvastatin 2x40mg per day was then administered for two weeks and oGTT and FDG-PET/MRI were repeated. RESULTS Two weeks of fluvastatin treatment led to a significant increase in glucose area under the curve (AUC) during oGTT (p=0.02), reduction in total cholesterol and LDL cholesterol (both p<0.0001). Insulin AUC (p=0.26), resting energy expenditure (REE) (p=0.44) and diet induced thermogenesis (DIT) (p=0.27) did not change significantly. The Matsuda index, as an indicator of insulin sensitivity, was lower after fluvastatin intake, but the difference was not statistically significant (p=0.09). As parameters of BAT activity, mean standard uptake value (SUVmean) (p=0.12), volume (p=0.49) and total glycolysis (p=0.74) did not change significantly during the intervention. Matsuda index, was inversely related to SUVmean and the respiratory exchange ratio (RER) (both R2 = 0.44, p=0.005) at baseline, but not after administration of fluvastatin (R2 = 0.08, p=0.29, and R2 = 0.14, p=0.16, respectively). CONCLUSIONS Treatment with fluvastatin for two weeks reduced serum lipid levels but increased glucose AUC in young, healthy men, indicating reduced glucose tolerance. This was not associated with changes in cold-induced BAT activity.
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Affiliation(s)
- Martina Felder
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Claudia Irene Maushart
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Gani Gashi
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jaël Rut Senn
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Anton S. Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich/University of Zurich, Zurich, Switzerland
| | - Julian Müller
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich/University of Zurich, Zurich, Switzerland
| | - Miroslav Balaz
- Institute of Food, Nutrition and Health, ETH Zurich, Zurich, Switzerland
| | - Christian Wolfrum
- Institute of Food, Nutrition and Health, ETH Zurich, Zurich, Switzerland
| | - Irene A. Burger
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich/University of Zurich, Zurich, Switzerland
| | - Matthias Johannes Betz
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel and University of Basel, Basel, Switzerland
- *Correspondence: Matthias Johannes Betz,
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Maushart CI, Senn JR, Loeliger RC, Kraenzlin ME, Müller J, Becker AS, Balaz M, Wolfrum C, Burger IA, Betz MJ. Free Thyroxine Levels are Associated with Cold Induced Thermogenesis in Healthy Euthyroid Individuals. Front Endocrinol (Lausanne) 2021; 12:666595. [PMID: 34194392 PMCID: PMC8236885 DOI: 10.3389/fendo.2021.666595] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 04/20/2021] [Indexed: 01/06/2023] Open
Abstract
Thyroid hormone (TH) is an important regulator of mammalian metabolism and facilitates cold induced thermogenesis (CIT) in brown adipose tissue (BAT). Profound hypothyroidism or hyperthyroidism lead to alterations in BAT function and CIT. In euthyroid humans the inter-individual variation of thyroid hormones is relatively large. Therefore, we investigated whether levels of free thyroxine (T4) or free triiodothyronine (T3) are positively associated with CIT in euthyroid individuals. We performed an observational study in 79 healthy, euthyroid volunteers (mean age 25.6 years, mean BMI 23.0 kg · m-2). Resting energy expenditure (REE) was measured by indirect calorimetry during warm conditions (EEwarm) and after a mild cold stimulus of two hours (EEcold). CIT was calculated as the difference between EEcold and EEwarm. BAT activity was assessed by 18F-FDG-PET after a mild cold stimulus in a subset of 26 participants. EEcold and CIT were significantly related to levels of free T4 (R2 = 0.11, p=0.0025 and R2 = 0.13, p=0.0011, respectively) but not to free T3 and TSH. Cold induced BAT activity was also associated with levels of free T4 (R2 = 0.21, p=0.018). CIT was approximately fourfold higher in participants in the highest tertile of free T4 as compared to the lowest tertile. Additionally, free T4 was weakly, albeit significantly associated with outdoor temperature seven days prior to the respective study visit (R2 = 0.06, p=0.037). These finding suggests that variations in thyroid hormone levels within the euthyroid range are related to the capability to adapt to cool temperatures and affect energy balance.
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Affiliation(s)
- Claudia Irene Maushart
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Jaël Rut Senn
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Rahel Catherina Loeliger
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Marius E. Kraenzlin
- SpezialLABOR Hormone - Knochenstoffwechsel, University of Basel, Basel, Switzerland
| | - Julian Müller
- Department of Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Anton S. Becker
- Department of Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Miroslav Balaz
- Health Sciences and Technology, Institute of Food, Nutrition and Health, ETH Zurich, Schwerzenbach, Switzerland
| | - Christian Wolfrum
- Health Sciences and Technology, Institute of Food, Nutrition and Health, ETH Zurich, Schwerzenbach, Switzerland
| | - Irene A. Burger
- Department of Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Matthias Johannes Betz
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel, University of Basel, Basel, Switzerland
- *Correspondence: Matthias Johannes Betz,
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Ferraro DA, Lehner F, Becker AS, Kranzbühler B, Kudura K, Mebert I, Messerli M, Hermanns T, Eberli D, Burger IA. Improved oncological outcome after radical prostatectomy in patients staged with 68Ga-PSMA-11 PET: a single-center retrospective cohort comparison. Eur J Nucl Med Mol Imaging 2020; 48:1219-1228. [PMID: 33074376 PMCID: PMC8041683 DOI: 10.1007/s00259-020-05058-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 09/27/2020] [Indexed: 11/26/2022]
Abstract
BACKGROUND Positron emission tomography (PET) targeting the prostate-specific membrane antigen (PSMA) has superior sensitivity over conventional imaging (CI) to stage prostate cancer (PCa) and therefore is increasingly used in staging to stratify patients before radical therapy. Whether this improved diagnostic accuracy translates into improved outcome after radical prostatectomy (RPE) has not yet been shown. Therefore, the aim of this study was to compare the oncological outcome after RPE between patients that underwent preoperative staging with CI or PSMA-PET for intermediate and high-risk PCa. METHODS We retrospectively selected all patients that underwent RPE for intermediate- or high-risk PCa at our institution before PSMA-PET introduction (between March 2014 and September 2016) and compared the oncologic outcome of patients staged with PSMA-PET (between October 2016 and October 2018). Oncological pre-surgical risk parameters (age, PSA, D'Amico score, biopsy-ISUP, and cT stage) were compared between the groups. Oncological outcome was determined as PSA persistence, nerve-sparing rate, and surgical margin status. Wilcoxon rank-sum, Fisher's, and chi-square tests where used for statistical testing. RESULTS One hundred five patients were included, 53 in the CI group and 52 in the PSMA-group. Patients in the PSMA group had higher ISUP grade (p < 0.001) and D'Amico score (p < 0.05). The rate of free surgical margins and PSA persistence after RPE was 64% and 17% for the CI and 77% and 6% for the PSMA group (p = 0.15 and 0.13, respectively). Subgroup analysis with high-risk patients revealed PSA persistence in 7% (3/44) in the PSMA group and 25% (7/28) in the CI group (p = 0.04). Limitations include the retrospective design and choline-PET for some patients in the CI group. CONCLUSION Immediate outcome after RPE was not worse in the PSMA group compared with the CI group, despite a higher-risk cohort. In a comparison of only high-risk patients, PSMA-PET staging was associated with a significantly lower rate of postsurgical PSA persistence.
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Affiliation(s)
- Daniela A Ferraro
- Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Rämistrasse 100, 8091, Zürich, Switzerland
| | - Fabienne Lehner
- Department of Urology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | - Benedikt Kranzbühler
- Department of Urology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Ken Kudura
- Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Rämistrasse 100, 8091, Zürich, Switzerland
| | - Iliana Mebert
- Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Rämistrasse 100, 8091, Zürich, Switzerland
- Department of Urology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Michael Messerli
- Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Rämistrasse 100, 8091, Zürich, Switzerland
| | - Thomas Hermanns
- Department of Urology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Daniel Eberli
- Department of Urology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Irene A Burger
- Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Rämistrasse 100, 8091, Zürich, Switzerland.
- Department of Nuclear Medicine, Kantonsspital Baden, Baden, Switzerland.
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Becker AS, Zellweger C, Bacanovic S, Franckenberg S, Nagel HW, Frick L, Schawkat K, Eberhard M, Blüthgen C, Volbracht J, Moos R, Wolfrum C, Burger IA. Brown fat does not cause cachexia in cancer patients: A large retrospective longitudinal FDG-PET/CT cohort study. PLoS One 2020; 15:e0239990. [PMID: 33031379 PMCID: PMC7544086 DOI: 10.1371/journal.pone.0239990] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Accepted: 09/16/2020] [Indexed: 12/21/2022] Open
Abstract
Background Brown adipose tissue (BAT) is a specialized form of adipose tissue, able to increase energy expenditure by heat generation in response to various stimuli. Recently, its pathological activation has been implicated in the pathogenesis of cancer cachexia. To establish a causal relationship, we retrospectively investigated the longitudinal changes in BAT and cancer in a large FDG-PET/CT cohort. Methods We retrospectively analyzed 13 461 FDG-PET/CT examinations of n = 8 409 patients at our institution from the winter months of 2007–2015. We graded the activation strength of BAT based on the anatomical location of the most caudally activated BAT depot into three tiers, and the stage of the cancer into five general grades. We validated the cancer grading by an interreader analysis and correlation with histopathological stage. Ambient temperature data (seven-day average before the examination) was obtained from a meteorological station close to the hospital. Changes of BAT, cancer, body mass index (BMI) and temperature between the different examinations were examined with Spearman’s test and a mixed linear model for correlation, and with a causal inference algorithm for causality. Results We found n = 283 patients with at least two examinations and active BAT in at least one of them. There was no significant interaction between the changes in BAT activation, cancer burden or BMI. Temperature changes exhibited a strong negative correlation with BAT activity (ϱ = -0.57, p<0.00001). These results were confirmed with the mixed linear model. Causal inference revealed a link of Temperature ➜ BAT in all subjects and also of BMI ➜ BAT in subjects who had lost weight and increased cancer burden, but no role of cancer and no causal links of BAT ➜ BMI. Conclusions Our data did not confirm the hypothesis that BAT plays a major role in cancer-mediated weight loss. Temperature changes are the main driver of incidental BAT activity on FDG-PET scans.
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Affiliation(s)
- Anton S. Becker
- Department of Health Sciences and Technology; Institute of Food, Nutrition and Health, ETH Zurich, Schwerzenbach, Switzerland
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
- * E-mail:
| | - Caroline Zellweger
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Sara Bacanovic
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Sabine Franckenberg
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Hannes W. Nagel
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Lukas Frick
- Department of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland
| | - Khoschy Schawkat
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Matthias Eberhard
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Christian Blüthgen
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Jörk Volbracht
- Division of Controlling and Data Management, University Hospital Zurich, Zurich, Switzerland
| | - Rudolf Moos
- Division of Controlling and Data Management, University Hospital Zurich, Zurich, Switzerland
| | - Christian Wolfrum
- Department of Health Sciences and Technology; Institute of Food, Nutrition and Health, ETH Zurich, Schwerzenbach, Switzerland
| | - Irene A. Burger
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
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Schindler V, Huellner M, Murray F, Schnurre L, Becker AS, Bordier V, Pohl D. Nutrient Challenge Testing Is Not Equivalent to Scintigraphy-Lactulose Hydrogen Breath Testing in Diagnosing Small Intestinal Bacterial Overgrowth. J Neurogastroenterol Motil 2020; 26:514-520. [PMID: 32989187 PMCID: PMC7547189 DOI: 10.5056/jnm19162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2019] [Revised: 06/07/2020] [Accepted: 07/03/2020] [Indexed: 11/20/2022] Open
Abstract
Background/Aims Small intestinal bacterial overgrowth (SIBO) is a common condition in disorders of gut-brain interaction (DGBI). Recently, a combined scintigraphy–lactulose hydrogen breath test (ScLHBT) was described as an accurate tool diagnosing SIBO. We aim to analyze whether a lactulose nutrient challenge test (NCT), previously shown to separate DGBI from healthy volunteers, is equivalent to ScLHBT in diagnosing SIBO. Methods We studied data of 81 DGBI patients undergoing ScLHBT with 30 g lactulose and 300 mL water as well as NCT with 30 g lactulose and a 400 mL liquid test meal. Differences in proportion of positive SIBO diagnoses according to specified cecal load and time criteria for NCT and ScLHBT, respectively, were tested in an equivalence trial. An odds ratio (OR) range of 0.80-1.25 was considered equivalent. Results Diagnosis of SIBO during NCT was not equivalent to SIBO diagnosis in ScLHBT, considering a hydrogen increase before cecal load of 5.0%, 7.5%, or 10.0%, respectively ([OR, 3.76; 90% CI, 1.99-7.09], [OR, 1.87; 90% CI, 1.06-3.27], and [OR, 1.11; 90% CI, 0.65-1.89]). Considering only time to hydrogen increase as criterion, the odds of a positive SIBO diagnosis in the NCT (0.65) was lower than in ScLHBT (1.70) (OR, 0.38; 90% CI, 0.23-0.65). Conclusions This study could not show an equivalence of NCT and ScLHBT in diagnosing SIBO. A possible explanation might be the different transit times owing to unequal testing substances. The effect of this deviation in relation to consecutive therapy regimens should be tested in further prospective studies.
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Affiliation(s)
- Valeria Schindler
- Division of Gastroenterology and Hepatology, University Hospital Zurich, Zurich, Switzerland
| | - Martin Huellner
- Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Fritz Murray
- Division of Gastroenterology and Hepatology, University Hospital Zurich, Zurich, Switzerland
| | - Larissa Schnurre
- Division of Gastroenterology and Hepatology, University Hospital Zurich, Zurich, Switzerland
| | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Valentine Bordier
- Division of Gastroenterology and Hepatology, University Hospital Zurich, Zurich, Switzerland
| | - Daniel Pohl
- Division of Gastroenterology and Hepatology, University Hospital Zurich, Zurich, Switzerland
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Woo S, Ghafoor S, Becker AS, Han S, Wibmer AG, Hricak H, Burger IA, Schöder H, Vargas HA. Prostate-specific membrane antigen positron emission tomography (PSMA-PET) for local staging of prostate cancer: a systematic review and meta-analysis. Eur J Hybrid Imaging 2020; 4:16. [PMID: 34191215 PMCID: PMC8218057 DOI: 10.1186/s41824-020-00085-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 08/05/2020] [Indexed: 12/21/2022] Open
Abstract
Purpose Prostate-specific membrane antigen positron emission tomography (PSMA-PET) has shown promise for detecting nodal and distant prostate cancer (PCa) metastases. However, its performance for local tumor staging is not as well established. The purpose of this study was to review the diagnostic performance of PSMA-PET for determining seminal vesical invasion (SVI) and extraprostatic extension (EPE). Methods Pubmed and Embase databases were searched until January 12, 2020. Studies assessing accuracy of PSMA-PET in determining SVI and EPE were included. Study quality was evaluated with the revised Quality Assessment of Diagnostic Accuracy Studies-2 tool. Pooled sensitivity and specificity were calculated using hierarchical summary receiver operating characteristics modeling. Heterogeneity was explored using meta-regression analyses for anatomical imaging component (MRI vs CT) and by testing for a threshold effect. Results Twelve studies (615 patients) were included. Pooled sensitivity and specificity were 0.68 (95% CI 0.53-0.81) and 0.94 (95% CI 0.90-0.96) for SVI and 0.72 (95% CI 0.56-0.84) and 0.87 (95% CI 0.72-0.94) for EPE. Meta-regression analyses showed that for SVI, PET/MRI demonstrated greater sensitivity than PET/CT (0.87 [95% CI 0.75-0.98] vs 0.60 [95% CI 0.47-0.74]; p = 0.02 for joint model) while specificity was comparable (0.91 [95% CI 0.84-0.97] vs. 0.96 [95% CI 0.93-0.99]) but not for EPE (p = 0.08). A threshold effect was present for studies assessing EPE (correlation coefficient = 0.563 [95% CI, −0.234-0.908] between sensitivity and false-positive rate). Conclusion PSMA-PET has moderate sensitivity and excellent specificity for assessing local tumor extent in patients with PCa. PET/MRI showed potential for greater sensitivity than PET/CT in assessing SVI.
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Affiliation(s)
- Sungmin Woo
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
| | - Soleen Ghafoor
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Anton S Becker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Sangwon Han
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Korea
| | - Andreas G Wibmer
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Hedvig Hricak
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Irene A Burger
- Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, Zürich, Switzerland.,Department of Nuclear Medicine, Kantonsspital Baden, Baden, Switzerland
| | - Heiko Schöder
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Hebert Alberto Vargas
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
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Fischer JGW, Maushart CI, Becker AS, Müller J, Madoerin P, Chirindel A, Wild D, Ter Voert EEGW, Bieri O, Burger I, Betz MJ. Comparison of [ 18F]FDG PET/CT with magnetic resonance imaging for the assessment of human brown adipose tissue activity. EJNMMI Res 2020; 10:85. [PMID: 32699996 PMCID: PMC7376767 DOI: 10.1186/s13550-020-00665-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Accepted: 06/25/2020] [Indexed: 12/26/2022] Open
Abstract
Background Brown adipose tissue (BAT) is a thermogenic tissue which can generate heat in response to mild cold exposure. As it constitutes a promising target in the fight against obesity, we need reliable techniques to quantify its activity in response to therapeutic interventions. The current standard for the quantification of BAT activity is [18F]FDG PET/CT. Various sequences in magnetic resonance imaging (MRI), including those measuring its relative fat content (fat fraction), have been proposed and evaluated in small proof-of-principle studies, showing diverging results. Here, we systematically compare the predictive value of adipose tissue fat fraction measured by MRI to the results of [18F]FDG PET/CT. Methods We analyzed the diagnostic reliability of MRI measured fat fraction (FF) for the estimation of human BAT activity in two cohorts of healthy volunteers participating in two prospective clinical trials (NCT03189511, NCT03269747). In both cohorts, BAT activity was stimulated by mild cold exposure. In cohort 1, we performed [18F]FDG PET/MRI; in cohort 2, we used [18F]FDG PET/CT followed by MRI. Fat fraction was determined by 2-point Dixon and 6-point Dixon measurement, respectively. Fat fraction values were compared to SUVmean in the corresponding tissue depot by simple linear regression. Results In total, 33 male participants with a mean age of 23.9 years and a mean BMI of 22.8 kg/m2 were recruited. In 32 participants, active BAT was visible. On an intra-individual level, FF was significantly lower in high-SUV areas compared to low-SUV areas (cohort 1: p < 0.0001 and cohort 2: p = 0.0002). The FF of the supraclavicular adipose tissue depot was inversely related to its metabolic activity (SUVmean) in both cohorts (cohort 1: R2 = 0.18, p = 0.09 and cohort 2: R2 = 0.42, p = 0.009). Conclusion MRI FF explains only about 40% of the variation in BAT glucose uptake. Thus, it can currently not be used to substitute [18F] FDG PET-based imaging for quantification of BAT activity. Trial registration ClinicalTrials.gov. NCT03189511, registered on June 17, 2017, actual study start date was on May 31, 2017, retrospectively registered. NCT03269747, registered on September 01, 2017.
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Affiliation(s)
- Jonas Gabriel William Fischer
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland, and University of Basel, Basel, Switzerland
| | - Claudia Irene Maushart
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland, and University of Basel, Basel, Switzerland
| | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zürich, Rämistrasse 100, 8091, Zürich, Switzerland
| | - Julian Müller
- Department of Nuclear Medicine, University Hospital Zürich, Rämistrasse 100, Zürich, 8091, Switzerland
| | - Philipp Madoerin
- Department of Radiology, Division of Radiological Physics, University Hospital Basel, Basel, Switzerland
| | - Alin Chirindel
- Division of Nuclear Medicine, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland
| | - Damian Wild
- Division of Nuclear Medicine, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland
| | - Edwin E G W Ter Voert
- Department of Nuclear Medicine, University Hospital Zürich, Rämistrasse 100, Zürich, 8091, Switzerland
| | - Oliver Bieri
- Department of Radiology, University Hospital of Basel and University of Basel, Basel, Switzerland
| | - Irene Burger
- Department of Nuclear Medicine, University Hospital Zürich, Rämistrasse 100, Zürich, 8091, Switzerland
| | - Matthias Johannes Betz
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland, and University of Basel, Basel, Switzerland.
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Sartoretti T, Sartoretti E, Schwenk Á, van Smoorenburg L, Mannil M, Euler A, Becker AS, Alfieri A, Najafi A, Binkert CA, Wyss M, Sartoretti-Schefer S. Clinical feasibility of ultrafast intracranial vessel imaging with non-Cartesian spiral 3D time-of-flight MR angiography at 1.5T: An intra-individual comparison study. PLoS One 2020; 15:e0232372. [PMID: 32348366 PMCID: PMC7190165 DOI: 10.1371/journal.pone.0232372] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 04/13/2020] [Indexed: 02/06/2023] Open
Abstract
Objectives Non-Cartesian Spiral readout can be implemented in 3D Time-of-flight (TOF) MR angiography (MRA) with short acquisition times. In this intra-individual comparison study we evaluated the clinical feasibility of Spiral TOF MRA in comparison with compressed sensing accelerated TOF MRA at 1.5T for intracranial vessel imaging as it has yet to be determined. Materials and methods Forty-four consecutive patients with suspected intracranial vascular disease were imaged with two Spiral 3D TOFs (Spiral, 0.82x0.82x1.2 mm3, 01:32 min; Spiral 0.8, 0.8x0.8x0.8 mm3, 02:12 min) and a Compressed SENSE accelerated 3D TOF (CS 3.5, 0.82x0.82x1.2 mm3, 03:06 min) at 1.5T. Two neuroradiologists assessed qualitative (visualization of central and peripheral vessels) and quantitative image quality (Contrast Ratio, CR) and performed lesion and variation assessment for all three TOFs in each patient. After the rating process, the readers were questioned and representative cases were reinspected in a non-blinded fashion. For statistical analysis, the Friedman and Nemenyi post-hoc test, Kendall W tests, repeated measure ANOVA and weighted Cohen's Kappa tests were used. Results The Spiral and Spiral 0.8 outperformed the CS 3.5 in terms of peripheral image quality (p<0.001) and performed equally well in terms of central image quality (p>0.05). The readers noted slight differences in the appearance of maximum intensity projection images. A good to high degree of interstudy agreement between the three TOFs was observed for lesion and variation assessment (W = 0.638, p<0.001 –W = 1, p<0.001). CR values did not differ significantly between the three TOFs (p = 0.534). Interreader agreement ranged from good (K = 0.638) to excellent (K = 1). Conclusions Compared to the CS 3.5, both the Spiral and Spiral 0.8 exhibited comparable or better image quality and comparable diagnostic performance at much shorter acquisition times.
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Affiliation(s)
- Thomas Sartoretti
- Institute of Radiology, Winterthur Cantonal Hospital, Winterthur, Switzerland
| | | | - Árpád Schwenk
- Institute of Radiology, Winterthur Cantonal Hospital, Winterthur, Switzerland
| | | | - Manoj Mannil
- Institute of Diagnostic and Interventional Radiology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - André Euler
- Institute of Diagnostic and Interventional Radiology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Anton S. Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Alex Alfieri
- Department of Neurosurgery, Winterthur Cantonal Hospital, Winterthur, Switzerland
| | - Arash Najafi
- Institute of Radiology, Winterthur Cantonal Hospital, Winterthur, Switzerland
| | | | - Michael Wyss
- Institute of Radiology, Winterthur Cantonal Hospital, Winterthur, Switzerland
- Philips Healthsystems, Zürich, Switzerland
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Liechti MR, Muehlematter UJ, Schneider AF, Eberli D, Rupp NJ, Hötker AM, Donati OF, Becker AS. Manual prostate cancer segmentation in MRI: interreader agreement and volumetric correlation with transperineal template core needle biopsy. Eur Radiol 2020; 30:4806-4815. [PMID: 32306078 DOI: 10.1007/s00330-020-06786-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 02/16/2020] [Accepted: 03/02/2020] [Indexed: 11/26/2022]
Abstract
OBJECTIVES To assess interreader agreement of manual prostate cancer lesion segmentation on multiparametric MR images (mpMRI). The secondary aim was to compare tumor volume estimates between MRI segmentation and transperineal template saturation core needle biopsy (TTSB). METHODS We retrospectively reviewed patients who had undergone mpMRI of the prostate at our institution and who had received TTSB within 190 days of the examination. Seventy-eight cancer lesions with Gleason score of at least 3 + 4 = 7 were manually segmented in T2-weighted images by 3 radiologists and 1 medical student. Twenty lesions were also segmented in apparent diffusion coefficient (ADC) and dynamic contrast enhanced (DCE) series. First, 20 volumetric similarity scores were computed to quantify interreader agreement. Second, manually segmented cancer lesion volumes were compared with TTSB-derived estimates by Bland-Altman analysis and Wilcoxon testing. RESULTS Interreader agreement across all readers was only moderate with mean T2 Dice score of 0.57 (95%CI 0.39-0.70), volumetric similarity coefficient of 0.74 (0.48-0.89), and Hausdorff distance of 5.23 mm (3.17-9.32 mm). Discrepancy of volume estimate between MRI and TTSB was increasing with tumor size. Discrepancy was significantly different between tumors with a Gleason score 3 + 4 vs. higher grade tumors (0.66 ml vs. 0.78 ml; p = 0.007). There were no significant differences between T2, ADC, and DCE segmentations. CONCLUSIONS We found at best moderate interreader agreement of manual prostate cancer segmentation in mpMRI. Additionally, our study suggests a systematic discrepancy between the tumor volume estimate by MRI segmentation and TTSB core length, especially for large and high-grade tumors. KEY POINTS • Manual prostate cancer segmentation in mpMRI shows moderate interreader agreement. • There are no significant differences between T2, ADC, and DCE segmentation agreements. • There is a systematic difference between volume estimates derived from biopsy and MRI.
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Affiliation(s)
- Marc R Liechti
- Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich, Switzerland
| | - Urs J Muehlematter
- Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich, Switzerland
| | - Aurelia F Schneider
- Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich, Switzerland
| | - Daniel Eberli
- Department of Urology, University Hospital of Zurich, Zurich, Switzerland
| | - Niels J Rupp
- Department of Pathology and Molecular Pathology, University Hospital of Zurich, Zurich, Switzerland
| | - Andreas M Hötker
- Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich, Switzerland
| | - Olivio F Donati
- Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich, Switzerland
| | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich, Switzerland.
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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Fankhauser CD, Waisbrod S, Fierz C, Becker AS, Kranzbühler B, Eberli D, Sulser T, Mostafid H, Hermanns T. Diagnostic accuracy of ultrasonography, computed tomography, cystoscopy and cytology to detect urinary tract malignancies in patients with asymptomatic hematuria. World J Urol 2020; 39:97-103. [PMID: 32240349 DOI: 10.1007/s00345-020-03171-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Accepted: 03/16/2020] [Indexed: 10/24/2022] Open
Abstract
PURPOSE To report the incidence of urinary tract malignancies (UTM) and to compare the diagnostic accuracy of cytology with cystoscopy, renal ultrasound (US) and computed tomography (CT) in patients with hematuria. METHODS A retrospective analysis was conducted of patients who underwent cystoscopy, cytology, US and CT for hematuria between 2011 and 2017. Age, gender, BMI, smoking status, and results of further diagnostic interventions including transurethral resection of the bladder (TURB), ureterorenoscopy (URS), renal biopsy and imaging were extracted from medical charts. Logistic regression to identify risk factors for UTM was performed. Discriminatory accuracy of US, CT and cytology was assessed by 2 × 2 tables. RESULTS Of 847 patients, 432 (51%) presented with non-visible hematuria (NVH) and 415 (49%) with visible hematuria (VH). Of all patients with NVH, seven (1.6%) had bladder cancer (BCA), three (< 1%) had renal cell cancer (RCC) and no single patient had upper tract urothelial cancer (UTUC). Of the patients with VH, 62 (14.9%) were diagnosed with BCA, 7 (1.6%) with RCC and 4 (< 1%) with UTUC. In multivariable analysis VH, higher age, smoking and lower BMI were associated with an increased risk for UTM. The specificity/negative predictive value of US for the detection of RCC or UTUC in patients with NVH and VH were 96%/100% and 95%/99%, respectively. CONCLUSION Due to the low incidence of UTM, the necessity of further diagnostics should be questioned in patients with NVH. In contrast, patients with VH are at considerable risk for BCA, and cystoscopy and upper tract imaging is justified.
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Affiliation(s)
- Christian Daniel Fankhauser
- Department of Urology, University Hospital Zurich, University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.
| | - Sharon Waisbrod
- Department of Urology, University Hospital Zurich, University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland
| | - Cindy Fierz
- Department of Urology, University Hospital Zurich, University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland
| | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Benedikt Kranzbühler
- Department of Urology, University Hospital Zurich, University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland
| | - Daniel Eberli
- Department of Urology, University Hospital Zurich, University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland
| | - Tullio Sulser
- Department of Urology, University Hospital Zurich, University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland
| | - Hugh Mostafid
- Department of Urology, Royal Surrey County Hospital, Egerton Road, Guildford, Surrey, UK
| | - Thomas Hermanns
- Department of Urology, University Hospital Zurich, University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland
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Blüthgen C, Becker AS, Vittoria de Martini I, Meier A, Martini K, Frauenfelder T. Detection and localization of distal radius fractures: Deep learning system versus radiologists. Eur J Radiol 2020; 126:108925. [PMID: 32193036 DOI: 10.1016/j.ejrad.2020.108925] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Revised: 02/21/2020] [Accepted: 02/27/2020] [Indexed: 12/29/2022]
Abstract
PURPOSE To evaluate a deep learning based image analysis software for the detection and localization of distal radius fractures. METHOD A deep learning system (DLS) was trained on 524 wrist radiographs (166 showing fractures). Performance was tested on internal (100 radiographs, 42 showing fractures) and external test sets (200 radiographs, 100 showing fractures). Single and combined views of the radiographs were shown to DLS and three readers. Readers were asked to indicate fracture location with regions of interest (ROI). The DLS yielded scores (range 0-1) and a heatmap. Detection performance was expressed as AUC, sensitivity and specificity at the optimal threshold and compared to radiologists' performance. Heatmaps were compared to radiologists' ROIs. RESULTS The DLS showed excellent performance on the internal test set (AUC 0.93 (95% confidence interval (CI) 0.82-0.98) - 0.96 (0.87-1.00), sensitivity 0.81 (0.58-0.95) - 0.90 (0.70-0.99), specificity 0.86 (0.68-0.96) - 1.0 (0.88-1.0)). DLS performance decreased on the external test set (AUC 0.80 (0.71-0.88) - 0.89 (0.81-0.94), sensitivity 0.64 (0.49-0.77) - 0.92 (0.81-0.98), specificity 0.60 (0.45-0.74) - 0.90 (0.78-0.97)). Radiologists' performance was comparable on internal data (sensitivity 0.71 (0.48-0.89) - 0.95 (0.76-1.0), specificity 0.52 (0.32-0.71) - 0.97 (0.82-1.0)) and better on external data (sensitivity 0.88 (0.76-0.96) - 0.98 (0.89-1.0), specificities 0.66 (0.51-0.79) - 1.0 (0.93-1.0), p < 0.05). In over 90%, the areas of peak activation aligned with radiologists' annotations. CONCLUSIONS The DLS was able to detect and localize wrist fractures with a performance comparable to radiologists, using only a small dataset for training.
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Affiliation(s)
- Christian Blüthgen
- Institute for Diagnostic and Interventional Radiology, University Hospital of Zurich, Switzerland.
| | - Anton S Becker
- Institute for Diagnostic and Interventional Radiology, University Hospital of Zurich, Switzerland
| | | | - Andreas Meier
- Institute for Diagnostic and Interventional Radiology, University Hospital of Zurich, Switzerland
| | - Katharina Martini
- Institute for Diagnostic and Interventional Radiology, University Hospital of Zurich, Switzerland
| | - Thomas Frauenfelder
- Institute for Diagnostic and Interventional Radiology, University Hospital of Zurich, Switzerland
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Ter Voert EEGW, Svirydenka H, Müller J, Becker AS, Balaz M, Efthymiou V, Maushart CI, Gashi G, Wolfrum C, Betz MJ, Burger IA. Low-dose 18F-FDG TOF-PET/MR for accurate quantification of brown adipose tissue in healthy volunteers. EJNMMI Res 2020; 10:5. [PMID: 31974702 PMCID: PMC6977803 DOI: 10.1186/s13550-020-0592-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 01/12/2020] [Indexed: 12/12/2022] Open
Abstract
Background Positron emission tomography (PET) is increasingly applied for in vivo brown adipose tissue (BAT) research in healthy volunteers. To limit the radiation exposure, the injected 18F-FDG tracer dose should be as low as possible. With simultaneous PET/MR imaging, the radiation exposure due to computed tomography (CT) can be avoided, but more importantly, the PET acquisition time can often be increased to match the more extensive magnetic resonance (MR) imaging protocol. The potential gain in detected coincidence counts, due to the longer acquisition time, can then be applied to decrease the injected tracer dose. The aim of this study was to investigate the minimal 18F-FDG dose for a 10-min time-of-flight (TOF) PET/MR acquisition that would still allow accurate quantification of supraclavicular BAT volume and activity. Methods Twenty datasets from 13 volunteers were retrospectively included from a prospective clinical study. PET emission datasets were modified to simulate step-wise reductions of the original 75 MBq injected dose. The resulting PET images were visually and quantitatively assessed and compared to a 4-min reference scan. For the visual assessment, the image quality and artifacts were scored using a 5-point and a 3-point Likert scale. For the quantitative analysis, image noise and artifacts, BAT metabolic activity, BAT metabolic volume (BMV), and total BAT glycolysis (TBG) were investigated. Results The visual assessment showed still good image quality for the 35%, 30%, and 25% activity reconstructions with no artifacts. Quantitatively, the background noise was similar to the reference for the 35% and 30% activity reconstructions and the artifacts started to increase significantly in the 25% and lower activity reconstructions. There was no significant difference in supraclavicular BAT metabolic activity, BMV, and TBG between the reference and the 35% to 20% activity reconstructions. Conclusions This study indicates that when the PET acquisition time is matched to the 10-min MRI protocol, the injected 18F-FDG tracer dose can be reduced to approximately 19 MBq (25%) while maintaining image quality and accurate supraclavicular BAT quantification. This could decrease the effective dose from 1.4 mSv to 0.36 mSv.
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Affiliation(s)
- Edwin E G W Ter Voert
- Department of Nuclear Medicine, University Hospital Zürich, Rämistrasse 100, 8091, Zürich, Switzerland. .,University of Zurich, Rämistrasse 71, 8006, Zürich, Switzerland.
| | - Hanna Svirydenka
- Department of Nuclear Medicine, University Hospital Zürich, Rämistrasse 100, 8091, Zürich, Switzerland.,Department of Nuclear Medicine, Medical University Innsbruck, Anichstrasse 35, 6020, Innsbruck, Austria
| | - Julian Müller
- Department of Nuclear Medicine, University Hospital Zürich, Rämistrasse 100, 8091, Zürich, Switzerland
| | - Anton S Becker
- Department of Health Sciences and Technology, Institute of Food, Nutrition and Health, ETH Zürich, Schorenstrasse 16, 8603, Schwerzenbach, Switzerland.,Institute of Diagnostic and Interventional Radiology, University Hospital Zürich, Rämistrasse 100, 8091, Zürich, Switzerland
| | - Miroslav Balaz
- Department of Health Sciences and Technology, Institute of Food, Nutrition and Health, ETH Zürich, Schorenstrasse 16, 8603, Schwerzenbach, Switzerland
| | - Vissarion Efthymiou
- Department of Health Sciences and Technology, Institute of Food, Nutrition and Health, ETH Zürich, Schorenstrasse 16, 8603, Schwerzenbach, Switzerland
| | - Claudia Irene Maushart
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland.,University of Basel, Petersplatz 1, 4001, Basel, Switzerland
| | - Gani Gashi
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland.,University of Basel, Petersplatz 1, 4001, Basel, Switzerland
| | - Christian Wolfrum
- Department of Health Sciences and Technology, Institute of Food, Nutrition and Health, ETH Zürich, Schorenstrasse 16, 8603, Schwerzenbach, Switzerland
| | - Matthias J Betz
- Department of Endocrinology, Diabetes and Metabolism, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland.,University of Basel, Petersplatz 1, 4001, Basel, Switzerland
| | - Irene A Burger
- Department of Nuclear Medicine, University Hospital Zürich, Rämistrasse 100, 8091, Zürich, Switzerland.,Department of Nuclear Medicine, Kantonsspital Baden, Im Ergel 1, 5404, Baden, Switzerland
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Sartoretti E, Sartoretti T, Wyss M, Becker AS, Schwenk Á, van Smoorenburg L, Najafi A, Binkert C, Thoeny HC, Zhou J, Jiang S, Graf N, Czell D, Sartoretti-Schefer S, Reischauer C. Amide Proton Transfer Weighted Imaging Shows Differences in Multiple Sclerosis Lesions and White Matter Hyperintensities of Presumed Vascular Origin. Front Neurol 2019; 10:1307. [PMID: 31920930 PMCID: PMC6914856 DOI: 10.3389/fneur.2019.01307] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2019] [Accepted: 11/26/2019] [Indexed: 01/14/2023] Open
Abstract
Objectives: To assess the ability of 3D amide proton transfer weighted (APTw) imaging based on magnetization transfer analysis to discriminate between multiple sclerosis lesions (MSL) and white matter hyperintensities of presumed vascular origin (WMH) and to compare APTw signal intensity of healthy white matter (healthy WM) with APTw signal intensity of MSL and WHM. Materials and Methods: A total of 27 patients (16 female, 11 males, mean age 39.6 years) with multiple sclerosis, 35 patients (17 females, 18 males, mean age 66.6 years) with small vessel disease (SVD) and 20 healthy young volunteers (9 females, 11 males, mean age 29 years) were included in the MSL, the WMH, and the healthy WM group. MSL and WMH were segmented on fluid attenuated inversion recovery (FLAIR) images underlaid onto APTw images. Histogram parameters (mean, median, 10th, 25th, 75th, 90th percentile) were calculated. Mean APTw signal intensity values in healthy WM were defined by "Region of interest" (ROI) measurements. Wilcoxon rank sum tests and receiver operating characteristics (ROC) curve analyses of clustered data were applied. Results: All histogram parameters except the 75 and 90th percentile were significantly different between MSL and WMH (p = 0.018-p = 0.034). MSL presented with higher median values in all parameters. The histogram parameters offered only low diagnostic performance in discriminating between MSL and WMH. The 10th percentile yielded the highest diagnostic performance with an AUC of 0.6245 (95% CI: [0.532, 0.717]). Mean APTw signal intensity values of MSL were significantly higher than mean values of healthy WM (p = 0.005). The mean values of WMH did not differ significantly from the values of healthy WM (p = 0.345). Conclusions: We found significant differences in APTw signal intensity, based on straightforward magnetization transfer analysis, between MSL and WMH and between MSL and healthy WM. Low AUC values from ROC analyses, however, suggest that it may be challenging to determine type of lesion with APTw imaging. More advanced analysis of the APT CEST signal may be helpful for further differentiation of MSL and WMH.
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Affiliation(s)
| | - Thomas Sartoretti
- Laboratory of Translational Nutrition Biology, Department of Health Sciences and Technology, ETH Zurich, Schwerzenbach, Switzerland
| | - Michael Wyss
- Institute of Radiology, Kantonsspital Winterthur, Winterthur, Switzerland.,Philips Healthsystems, Zurich, Switzerland
| | - Anton S Becker
- Laboratory of Translational Nutrition Biology, Department of Health Sciences and Technology, ETH Zurich, Schwerzenbach, Switzerland.,Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Árpád Schwenk
- Institute of Radiology, Kantonsspital Winterthur, Winterthur, Switzerland
| | | | - Arash Najafi
- Institute of Radiology, Kantonsspital Winterthur, Winterthur, Switzerland
| | - Christoph Binkert
- Institute of Radiology, Kantonsspital Winterthur, Winterthur, Switzerland
| | - Harriet C Thoeny
- Department of Medicine, University of Fribourg, Fribourg, Switzerland.,Department of Radiology, HFR Fribourg-Hôpital Cantonal, Fribourg, Switzerland
| | - Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, United States
| | - Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, United States
| | | | - David Czell
- Department of Neurology, Spital Linth, Uznach, Switzerland
| | | | - Carolin Reischauer
- Department of Medicine, University of Fribourg, Fribourg, Switzerland.,Department of Radiology, HFR Fribourg-Hôpital Cantonal, Fribourg, Switzerland
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Marcon M, Ciritsis A, Rossi C, Becker AS, Berger N, Wurnig MC, Wagner MW, Frauenfelder T, Boss A. Diagnostic performance of machine learning applied to texture analysis-derived features for breast lesion characterisation at automated breast ultrasound: a pilot study. Eur Radiol Exp 2019; 3:44. [PMID: 31676937 PMCID: PMC6825080 DOI: 10.1186/s41747-019-0121-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Accepted: 08/28/2019] [Indexed: 12/31/2022] Open
Abstract
Background Our aims were to determine if features derived from texture analysis (TA) can distinguish normal, benign, and malignant tissue on automated breast ultrasound (ABUS); to evaluate whether machine learning (ML) applied to TA can categorise ABUS findings; and to compare ML to the analysis of single texture features for lesion classification. Methods This ethically approved retrospective pilot study included 54 women with benign (n = 38) and malignant (n = 32) solid breast lesions who underwent ABUS. After manual region of interest placement along the lesions’ margin as well as the surrounding fat and glandular breast tissue, 47 texture features (TFs) were calculated for each category. Statistical analysis (ANOVA) and a support vector machine (SVM) algorithm were applied to the texture feature to evaluate the accuracy in distinguishing (i) lesions versus normal tissue and (ii) benign versus malignant lesions. Results Skewness and kurtosis were the only TF significantly different among all the four categories (p < 0.000001). In subsets (i) and (ii), a maximum area under the curve of 0.86 (95% confidence interval [CI] 0.82–0.88) for energy and 0.86 (95% CI 0.82–0.89) for entropy were obtained. Using the SVM algorithm, a maximum area under the curve of 0.98 for both subsets was obtained with a maximum accuracy of 94.4% in subset (i) and 90.7% in subset (ii). Conclusions TA in combination with ML might represent a useful diagnostic tool in the evaluation of breast imaging findings in ABUS. Applying ML techniques to TFs might be superior compared to the analysis of single TF. Electronic supplementary material The online version of this article (10.1186/s41747-019-0121-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Magda Marcon
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland.
| | - Alexander Ciritsis
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
| | - Cristina Rossi
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
| | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
| | - Nicole Berger
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
| | - Moritz C Wurnig
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
| | - Matthias W Wagner
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
| | - Thomas Frauenfelder
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
| | - Andreas Boss
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
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Stieb S, Klarhoefer M, Finkenstaedt T, Wurnig MC, Becker AS, Ciritsis A, Rossi C. Correction for fast pseudo-diffusive fluid motion contaminations in diffusion tensor imaging. Magn Reson Imaging 2019; 66:50-56. [PMID: 31655141 DOI: 10.1016/j.mri.2019.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 07/18/2019] [Accepted: 09/15/2019] [Indexed: 11/26/2022]
Abstract
In this prospective study, we quantified the fast pseudo-diffusion contamination by blood perfusion or cerebrospinal fluid (CSF) intravoxel incoherent movements on the measurement of the diffusion tensor metrics in healthy brain tissue. Diffusion-weighted imaging (TR/TE = 4100 ms/90 ms; b-values: 0, 5, 10, 20, 35, 55, 80, 110, 150, 200, 300, 500, 750, 1000, 1300 s/mm2, 20 diffusion-encoding directions) was performed on a cohort of five healthy volunteers at 3 Tesla. The projections of the diffusion tensor along each diffusion-encoding direction were computed using a two b-value approach (2b), by fitting the signal to a monoexponential curve (mono), and by correcting for fast pseudo-diffusion compartments using the biexponential intravoxel incoherent motion model (IVIM) (bi). Fractional anisotropy (FA) and mean diffusivity (MD) of the diffusion tensor were quantified in regions of interest drawn over white matter areas, gray matter areas, and the ventricles. A significant dependence of the MD from the evaluation method was found in all selected regions. A lower MD was computed when accounting for the fast-diffusion compartments. A larger dependence was found in the nucleus caudatus (bi: median 0.86 10-3 mm2/s, Δ2b: -11.2%, Δmono: -14.4%; p = 0.007), in the anterior horn (bi: median 2.04 10-3 mm2/s, Δ2b: -9.4%, Δmono: -11.5%, p = 0.007) and in the posterior horn of the lateral ventricles (bi: median 2.47 10-3 mm2/s, Δ2b: -5.5%, Δmono: -11.7%; p = 0.007). Also for the FA, the signal modeling affected the computation of the anisotropy metrics. The deviation depended on the evaluated region with significant differences mainly in the nucleus caudatus (bi: median 0.15, Δ2b: +39.3%, Δmono: +14.7%; p = 0.022) and putamen (bi: median 0.19, Δ2b: +3.1%, Δmono: +17.3%; p = 0.015). Fast pseudo-diffusive regimes locally affect diffusion tensor imaging (DTI) metrics in the brain. Here, we propose the use of an IVIM-based method for correction of signal contaminations through CSF or perfusion.
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Affiliation(s)
- Sonja Stieb
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland.
| | | | - Tim Finkenstaedt
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Moritz C Wurnig
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Alexander Ciritsis
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Cristina Rossi
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
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Patzelt J, Zhang W, Sauter R, Mezger M, Nording H, Becker AS, Rudolph V, Saad M, Eitel I, Schlensak C, Gawaz M, Boekstegers P, Schreieck J, Seizer P, Langer HF. P4724Elevated mitral valve pressure gradient is predictive for long-term outcome after percutaneous edge-to-edge mitral valve repair (PMVR) in patients with degenerative MR, but not in functional MR. Eur Heart J 2019. [DOI: 10.1093/eurheartj/ehz745.1101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
To analyze the effects of residual mitral regurgitation (MR) and mean mitral valve pressure gradient (MVPG) after percutaneous edge-to-edge mitral valve repair (PMVR) using the MitraClip-system on long term outcome.
Methods and results
Two hundred fifty-five patients who underwent PMVR were analyzed. Kaplan-Meier and Cox regression analyses were performed to evaluate the impact of residual MR and MVPG on clinical outcome. A combined clinical endpoint (all-cause mortality, MV surgery, redo procedure, implantation of a left ventricular assist device) was used.
After PMVR, mean MVPG increased from 1.6±1.0 mmHg to 3.1±1.5 mmHg (p<0.001). Reduction of MR severity to ≤2+ postintervention was achieved in 98.4% of all patients. In the overall patient cohort, residual MR was predictive for the combined endpoint while elevated MVPG >4.4 mmHg was not according to Kaplan-Meier and Cox regression analyses. We then analyzed the cohort with degenerative and that with functional MR separately to account for these different entities.In the cohort with degenerative MR, elevated MVPG was associated with increased occurrence of the primary endpoint, whereas this was not observed in the cohort with functional MR.
Conclusions
MVPG >4.4 mmHg after MitraClip-implantation was predictive for clinical outcome in the patient cohort with degenerative MR. In the patient cohort with functional MR, MVPG >4.4 mmHg was not associated with increased clinical events.
Acknowledgement/Funding
This study was supported by grants from the German Research Foundation (KFO 274), the Volkswagen Foundation (Lichtenberg Program) and the German Heart
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Affiliation(s)
- J Patzelt
- UKSH, Department of Cardiology, Angiology, and Intensive Care Medicine, Luebeck, Germany
| | - W Zhang
- The Affiliated Hospital of Medical College Qingdao University, Department of Cardiology, Angiology, and Intensive Care Medicine, Qingdao, China
| | - R Sauter
- UKSH, Department of Cardiology, Angiology, and Intensive Care Medicine, Luebeck, Germany
| | - M Mezger
- UKSH, Department of Cardiology, Angiology, and Intensive Care Medicine, Luebeck, Germany
| | - H Nording
- UKSH, Department of Cardiology, Angiology, and Intensive Care Medicine, Luebeck, Germany
| | - A S Becker
- University Hospital, Department of Cardiology and Cardiovascular Medicine, Tuebingen, Germany
| | - V Rudolph
- Cologne University Hospital - Heart Center, Cologne, Germany
| | - M Saad
- UKSH, Department of Cardiology, Angiology, and Intensive Care Medicine, Luebeck, Germany
| | - I Eitel
- UKSH, Department of Cardiology, Angiology, and Intensive Care Medicine, Luebeck, Germany
| | - C Schlensak
- University Hospital, Department of Cardiovascular Surgery, Tuebingen, Germany
| | - M Gawaz
- University Hospital, Department of Cardiology and Cardiovascular Medicine, Tuebingen, Germany
| | | | - J Schreieck
- University Hospital, Department of Cardiology and Cardiovascular Medicine, Tuebingen, Germany
| | - P Seizer
- University Hospital, Department of Cardiology and Cardiovascular Medicine, Tuebingen, Germany
| | - H F Langer
- UKSH, Department of Cardiology, Angiology, and Intensive Care Medicine, Luebeck, Germany
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Fiechter M, Roggo A, Haider A, Bengs S, Burger IA, Marędziak M, Portmann A, Treyer V, Becker AS, Messerli M, Mühlematter UJ, Kudura K, von Felten E, Benz DC, Fuchs TA, Gräni C, Pazhenkottil AP, Buechel RR, Kaufmann PA, Gebhard C. Metabolic Activity in Central Neural Structures of Patients With Myocardial Injury. J Am Heart Assoc 2019; 8:e013070. [PMID: 31566462 PMCID: PMC6806042 DOI: 10.1161/jaha.119.013070] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Background Increasing evidence suggests a psychosomatic link between neural systems and the heart. In light of the growing burden of ischemic cardiovascular disease across the globe, a better understanding of heart‐brain interactions and their implications for cardiovascular treatment strategies is needed. Thus, we sought to investigate the interaction between myocardial injury and metabolic alterations in central neural areas in patients with suspected or known coronary artery disease. Methods and Results The association between resting metabolic activity in distinct neural structures and cardiac function was analyzed in 302 patients (aged 66.8±10.2 years; 70.9% men) undergoing fluor‐18‐deoxyglucose positron emission tomography and 99mTc‐tetrofosmin single‐photon emission computed tomography myocardial perfusion imaging. There was evidence for reduction of callosal, caudate, and brainstem fluor‐18‐deoxyglucose uptake in patients with impaired left ventricular ejection fraction (<55% versus ≥55%: P=0.047, P=0.022, and P=0.013, respectively) and/or in the presence of myocardial ischemia (versus normal perfusion: P=0.010, P=0.013, and P=0.016, respectively). In a sex‐stratified analysis, these differences were observed in men, but not in women. A first‐order interaction term consisting of sex and impaired left ventricular ejection fraction or myocardial ischemia was identified as predictor of metabolic activity in these neural regions (left ventricular ejection fraction: P=0.015 for brainstem; myocardial ischemia: P=0.004, P=0.018, and P=0.003 for callosal, caudate, or brainstem metabolism, respectively). Conclusions Myocardial dysfunction and injury are associated with reduced resting metabolic activity of central neural structures, including the corpus callosum, the caudate nucleus, and the brainstem. These associations differ in women and men, suggesting sex differences in the pathophysiological interplay of the nervous and cardiovascular systems.
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Affiliation(s)
- Michael Fiechter
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland.,Center for Molecular Cardiology University of Zurich Switzerland.,Swiss Paraplegic Center Nottwil Switzerland
| | - Andrea Roggo
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland
| | - Ahmed Haider
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland.,Center for Molecular Cardiology University of Zurich Switzerland
| | - Susan Bengs
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland.,Center for Molecular Cardiology University of Zurich Switzerland
| | - Irene A Burger
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland
| | - Monika Marędziak
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland.,Center for Molecular Cardiology University of Zurich Switzerland
| | - Angela Portmann
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland
| | - Valerie Treyer
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland
| | - Anton S Becker
- Department of Diagnostic and Interventional Radiology University Hospital Zurich Zurich Switzerland
| | - Michael Messerli
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland
| | - Urs J Mühlematter
- Department of Diagnostic and Interventional Radiology University Hospital Zurich Zurich Switzerland
| | - Ken Kudura
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland
| | - Elia von Felten
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland
| | - Dominik C Benz
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland
| | - Tobias A Fuchs
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland
| | - Christoph Gräni
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland
| | - Aju P Pazhenkottil
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland
| | - Ronny R Buechel
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland
| | - Philipp A Kaufmann
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland
| | - Catherine Gebhard
- Department of Nuclear Medicine University Hospital Zurich Zurich Switzerland.,Center for Molecular Cardiology University of Zurich Switzerland
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Sartoretti T, Sartoretti E, Wyss M, Schwenk Á, van Smoorenburg L, Eichenberger B, Najafi A, Binkert C, Becker AS, Sartoretti-Schefer S. Compressed SENSE accelerated 3D T1w black blood turbo spin echo versus 2D T1w turbo spin echo sequence in pituitary magnetic resonance imaging. Eur J Radiol 2019; 120:108667. [PMID: 31550639 DOI: 10.1016/j.ejrad.2019.108667] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Revised: 08/23/2019] [Accepted: 09/08/2019] [Indexed: 12/21/2022]
Abstract
PURPOSE To compare image quality between a 2D T1w turbo spin echo (TSE) sequence and a Compressed SENSE accelerated 3D T1w black blood TSE sequence (equipped with a black blood prepulse for blood signal suppression) in pre- and postcontrast imaging of the pituitary and to assess scan time reductions. METHODS AND MATERIALS For this retrospective study, 56 patients underwent pituitary MR imaging at 3T. 28 patients were scanned with the 2D- and 28 patients with the accelerated 3D sequence. Two board certified neuroradiologists independently evaluated 13 qualitative image features (12 features on postcontrast- and 1 feature on precontrast images).SNR and CNR measurements were obtained. Interreader agreement was assessed with the intraclass correlation coefficient while differences in scores were assessed with exact Wilcoxon rank sum tests. RESULTS The interreader agreement ranged from fair (visibility of the ophthalmic nerve, ICC = 0.57) to excellent (presence and severity of pulsation artefacts, ICC = 0.97). The Compressed SENSE accelerated 3D sequence outperformed the 2D sequence in terms of "overall image quality" (median: 4 versus 3, p = 0.04) and "presence and severity of pulsation artefacts" (median: 0 versus 1, p < 0.001). There were no significant differences in any other qualitative and quantitative (SNR, CNR) image quality features. Scan time was reduced by 03:53 min (33.1%) by replacing the 2D with the 3D sequence. CONCLUSION The Compressed SENSE accelerated 3D T1w black blood TSE sequence is a reliable alternative for the standard 2D sequence in pituitary imaging. The black blood prepulse may aid in suppression of pulsation artefacts.
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Affiliation(s)
- Thomas Sartoretti
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
| | - Elisabeth Sartoretti
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
| | - Michael Wyss
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland; Philips Healthsystems, Zürich, Switzerland.
| | - Árpád Schwenk
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
| | - Luuk van Smoorenburg
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
| | - Barbara Eichenberger
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
| | - Arash Najafi
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
| | - Christoph Binkert
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
| | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zürich, University of Zürich, Raemistrasse 100, CH-8091, Zürich, Switzerland; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
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Muehlematter UJ, Burger IA, Becker AS, Schawkat K, Hötker AM, Reiner CS, Müller J, Rupp NJ, Rüschoff JH, Eberli D, Donati OF. Diagnostic Accuracy of Multiparametric MRI versus 68Ga-PSMA-11 PET/MRI for Extracapsular Extension and Seminal Vesicle Invasion in Patients with Prostate Cancer. Radiology 2019; 293:350-358. [PMID: 31502937 DOI: 10.1148/radiol.2019190687] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Background Recent studies have reported the additive value of combined gallium 68 (68Ga)-labeled Glu-urea-Lys (Ahx)-HBED-CC ligand targeting the prostate-specific membrane antigen (PSMA) (hereafter called 68Ga-PSMA-11) PET/MRI for the detection and localization of primary prostate cancer compared with multiparametric MRI. Purpose To compare the diagnostic accuracy and interrater agreement of multiparametric MRI and 68Ga-PSMA-11 PET/MRI for the detection of extracapsular extension (ECE) and seminal vesicle infiltration (SVI) in patients with prostate cancer. Materials and Methods Retrospective analysis of 40 consecutive men who underwent multiparametric MRI and 68Ga-PSMA-11 PET/MRI within 6 months for suspected prostate cancer followed by radical prostatectomy between April 2016 and July 2018. Four readers blinded to clinical and histopathologic findings rated the probability of ECE and SVI at multiparametric MRI and PET/MRI by using a five-point Likert-type scale. The prostatectomy specimen served as the reference standard. Accuracy was assessed with a multireader multicase analysis and by calculating reader-average areas under the receiver operating characteristics curve (AUCs), sensitivity, and specificity for ordinal and dichotomized data in a region-specific and patient-specific approach. Interrater agreement was assessed with the Fleiss multirater κ. Results For multiparametric MRI versus PET/MRI in ECE detection, respectively, AUC, sensitivity, and specificity in the region-specific analysis were 0.67 and 0.75 (P = .07), 28% (21 of 76) and 47% (36 of 76) (P = .09), and 94% (529 of 564) and 90% (509 of 564) (P = .007). For the patient-specific analysis, AUC, sensitivity, and specificity were 0.66 and 0.73 (P = .19), 46% (22 of 48) and 69% (33 of 48) (P = .04), and 75% (84 of 112) and 67% (75 of 112) (P = .19), respectively. For multiparametric MRI versus PET/MRI in SVI detection, respectively, AUC, sensitivity, and specificity of the region-specific analysis were 0.66 and 0.74 (P = .21), 35% (seven of 20) and 50% (10 of 20) (P = .25), and 98% (295 of 300) and 94% (282 of 300) (P < .001). For the patient-specific analysis, AUC, sensitivity, and specificity were 0.65 and 0.79 (P = .25), 35% (seven of 20) and 55% (11 of 20) (P = .20), and 98% (137 of 140) and 94% (131 of 140) (P = .07), respectively. Interrater reliability for multiparametric MRI versus PET/MRI did not differ for ECE (κ, 0.46 vs 0.40; P = .24) and SVI (κ, 0.23 vs 0.33; P = .39). Conclusion Our results suggest that gallium 68 (68Ga)-labeled Glu-urea-Lys (Ahx)-HBED-CC ligand targeting the prostate-specific membrane antigen (PSMA) (68Ga-PSMA-11) PET/MRI and multiparametric MRI perform similarly for local staging of prostate cancer in patients with intermediate-to-high-risk prostate cancer. The increased sensitivity of 68Ga-PSMA-11 PET/MRI for the detection of extracapsular disease comes at the cost of a slightly reduced specificity. © RSNA, 2019.
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Affiliation(s)
- Urs J Muehlematter
- From the Institute of Diagnostic and Interventional Radiology (U.J.M., A.S.B., K.S., A.M.H., C.S.R., O.F.D.), Department of Nuclear Medicine (U.J.M., I.A.B., J.M.), Department of Pathology and Molecular Pathology (N.J.R., J.H.R.), and Department of Urology (D.E.), University Hospital Zurich, University of Zurich, Rämistrasse 100, Zurich 8091, Switzerland; and Department of Nuclear Medicine, Kantonsspital Baden, Baden, Switzerland (I.A.B.)
| | - Irene A Burger
- From the Institute of Diagnostic and Interventional Radiology (U.J.M., A.S.B., K.S., A.M.H., C.S.R., O.F.D.), Department of Nuclear Medicine (U.J.M., I.A.B., J.M.), Department of Pathology and Molecular Pathology (N.J.R., J.H.R.), and Department of Urology (D.E.), University Hospital Zurich, University of Zurich, Rämistrasse 100, Zurich 8091, Switzerland; and Department of Nuclear Medicine, Kantonsspital Baden, Baden, Switzerland (I.A.B.)
| | - Anton S Becker
- From the Institute of Diagnostic and Interventional Radiology (U.J.M., A.S.B., K.S., A.M.H., C.S.R., O.F.D.), Department of Nuclear Medicine (U.J.M., I.A.B., J.M.), Department of Pathology and Molecular Pathology (N.J.R., J.H.R.), and Department of Urology (D.E.), University Hospital Zurich, University of Zurich, Rämistrasse 100, Zurich 8091, Switzerland; and Department of Nuclear Medicine, Kantonsspital Baden, Baden, Switzerland (I.A.B.)
| | - Khoschy Schawkat
- From the Institute of Diagnostic and Interventional Radiology (U.J.M., A.S.B., K.S., A.M.H., C.S.R., O.F.D.), Department of Nuclear Medicine (U.J.M., I.A.B., J.M.), Department of Pathology and Molecular Pathology (N.J.R., J.H.R.), and Department of Urology (D.E.), University Hospital Zurich, University of Zurich, Rämistrasse 100, Zurich 8091, Switzerland; and Department of Nuclear Medicine, Kantonsspital Baden, Baden, Switzerland (I.A.B.)
| | - Andreas M Hötker
- From the Institute of Diagnostic and Interventional Radiology (U.J.M., A.S.B., K.S., A.M.H., C.S.R., O.F.D.), Department of Nuclear Medicine (U.J.M., I.A.B., J.M.), Department of Pathology and Molecular Pathology (N.J.R., J.H.R.), and Department of Urology (D.E.), University Hospital Zurich, University of Zurich, Rämistrasse 100, Zurich 8091, Switzerland; and Department of Nuclear Medicine, Kantonsspital Baden, Baden, Switzerland (I.A.B.)
| | - Cäcilia S Reiner
- From the Institute of Diagnostic and Interventional Radiology (U.J.M., A.S.B., K.S., A.M.H., C.S.R., O.F.D.), Department of Nuclear Medicine (U.J.M., I.A.B., J.M.), Department of Pathology and Molecular Pathology (N.J.R., J.H.R.), and Department of Urology (D.E.), University Hospital Zurich, University of Zurich, Rämistrasse 100, Zurich 8091, Switzerland; and Department of Nuclear Medicine, Kantonsspital Baden, Baden, Switzerland (I.A.B.)
| | - Julian Müller
- From the Institute of Diagnostic and Interventional Radiology (U.J.M., A.S.B., K.S., A.M.H., C.S.R., O.F.D.), Department of Nuclear Medicine (U.J.M., I.A.B., J.M.), Department of Pathology and Molecular Pathology (N.J.R., J.H.R.), and Department of Urology (D.E.), University Hospital Zurich, University of Zurich, Rämistrasse 100, Zurich 8091, Switzerland; and Department of Nuclear Medicine, Kantonsspital Baden, Baden, Switzerland (I.A.B.)
| | - Niels J Rupp
- From the Institute of Diagnostic and Interventional Radiology (U.J.M., A.S.B., K.S., A.M.H., C.S.R., O.F.D.), Department of Nuclear Medicine (U.J.M., I.A.B., J.M.), Department of Pathology and Molecular Pathology (N.J.R., J.H.R.), and Department of Urology (D.E.), University Hospital Zurich, University of Zurich, Rämistrasse 100, Zurich 8091, Switzerland; and Department of Nuclear Medicine, Kantonsspital Baden, Baden, Switzerland (I.A.B.)
| | - Jan H Rüschoff
- From the Institute of Diagnostic and Interventional Radiology (U.J.M., A.S.B., K.S., A.M.H., C.S.R., O.F.D.), Department of Nuclear Medicine (U.J.M., I.A.B., J.M.), Department of Pathology and Molecular Pathology (N.J.R., J.H.R.), and Department of Urology (D.E.), University Hospital Zurich, University of Zurich, Rämistrasse 100, Zurich 8091, Switzerland; and Department of Nuclear Medicine, Kantonsspital Baden, Baden, Switzerland (I.A.B.)
| | - Daniel Eberli
- From the Institute of Diagnostic and Interventional Radiology (U.J.M., A.S.B., K.S., A.M.H., C.S.R., O.F.D.), Department of Nuclear Medicine (U.J.M., I.A.B., J.M.), Department of Pathology and Molecular Pathology (N.J.R., J.H.R.), and Department of Urology (D.E.), University Hospital Zurich, University of Zurich, Rämistrasse 100, Zurich 8091, Switzerland; and Department of Nuclear Medicine, Kantonsspital Baden, Baden, Switzerland (I.A.B.)
| | - Olivio F Donati
- From the Institute of Diagnostic and Interventional Radiology (U.J.M., A.S.B., K.S., A.M.H., C.S.R., O.F.D.), Department of Nuclear Medicine (U.J.M., I.A.B., J.M.), Department of Pathology and Molecular Pathology (N.J.R., J.H.R.), and Department of Urology (D.E.), University Hospital Zurich, University of Zurich, Rämistrasse 100, Zurich 8091, Switzerland; and Department of Nuclear Medicine, Kantonsspital Baden, Baden, Switzerland (I.A.B.)
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Schawkat K, Sah BR, Ter Voert EE, Delso G, Wurnig M, Becker AS, Leibl S, Schneider PM, Reiner CS, Huellner MW, Veit-Haibach P. Role of intravoxel incoherent motion parameters in gastroesophageal cancer: relationship with 18F-FDG-positron emission tomography, computed tomography perfusion and magnetic resonance perfusion imaging parameters. Q J Nucl Med Mol Imaging 2019; 65:178-186. [PMID: 31496202 DOI: 10.23736/s1824-4785.19.03153-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
BACKGROUND Identification of pretherapeutic predictive markers in gastro-esophageal cancer is essential for individual-oriented treatment. This study evaluated the relationship of multimodality parameters derived from intravoxel incoherent motion method (IVIM), 18F-FDG-positron emission tomography (PET), computed tomography (CT) perfusion and dynamic contrast enhanced magnetic resonance imaging (MRI) in patients with gastro-esophageal cancer and investigated their histopathological correlation. METHODS Thirty-one consecutive patients (28 males; median age 63.9 years; range 37-84 years) with gastro-esophageal adenocarcinoma (N.=22) and esophageal squamous cell carcinoma (N.=9) were analyzed. IVIM parameters: pseudodiffusion (D*), perfusion fraction (fp), true diffusion (D) and the threshold b-value (bval); PET-parameters: SUV<inf>max</inf>, metabolic tumor volume (MTV) and total lesion glycolysis (TLG); CT perfusion parameters: blood flow (BF), blood volume (BV) and mean transit time (MTT); and MR perfusion parameters: time to enhance, positive enhancement integral, time-to-peak (TTP), maximum-slope-of-increase, and maximum-slope-of-decrease were determined, and correlated to each other and to histopathology. RESULTS IVIM and PET parameters showed significant negative correlations: MTV and bval (r<inf>s</inf> =-0.643, P=0.002), TLG and bval (r<inf>s</inf>=-0.699, P<0.01) and TLG and fp (r<inf>s</inf>=-0.577, P=0.006). Positive correlation was found for TLG and D (r<inf>s</inf>=0.705, P=0.000). Negative correlation was found for bval and staging (r<inf>s</inf>=0.590, P=0.005). Positive correlation was found for positive enhancement interval and BV (r<inf>s</inf>=0.547, P=0.007), BF and regression index (r<inf>s</inf>=0.753, P=0.005) and for time-to-peak and staging (r<inf>s</inf>=0.557, P=0.005). CONCLUSIONS IVIM parameters (bval, fp, D) provide quantitative information and correlate with PET parameters (MTV, TLG) and staging. IVIM might be a useful tool for additional characterization of gastro-esophageal cancer.
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Affiliation(s)
- Khoschy Schawkat
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland - .,University of Zurich, Zurich, Switzerland -
| | - Bert-Ram Sah
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.,University of Zurich, Zurich, Switzerland.,Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Edwin E Ter Voert
- University of Zurich, Zurich, Switzerland.,Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Gaspar Delso
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Moritz Wurnig
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.,University of Zurich, Zurich, Switzerland
| | - Anton S Becker
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.,University of Zurich, Zurich, Switzerland
| | - Sebastian Leibl
- Department of Pathology, University Hospital Zurich, Zurich, Switzerland
| | - Paul M Schneider
- Center for Visceral, Thoracic and Specialized Tumor Surgery, Hirslanden Medical Center, Zurich, Switzerland
| | - Cäcilia S Reiner
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.,University of Zurich, Zurich, Switzerland
| | - Martin W Huellner
- University of Zurich, Zurich, Switzerland.,Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Patrick Veit-Haibach
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.,University of Zurich, Zurich, Switzerland.,Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland.,University of Toronto, Toronto, ON, Canada.,Toronto Joint Department of Medical Imaging, University Hospital of Zurich, Toronto General Hospital, Zurich, Switzerland
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Kranzbühler B, Müller J, Becker AS, Garcia Schüler HI, Muehlematter U, Fankhauser CD, Kedzia S, Guckenberger M, Kaufmann PA, Eberli D, Burger IA. Detection Rate and Localization of Prostate Cancer Recurrence Using 68Ga-PSMA-11 PET/MRI in Patients with Low PSA Values ≤ 0.5 ng/mL. J Nucl Med 2019; 61:194-201. [PMID: 31375566 DOI: 10.2967/jnumed.118.225276] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Accepted: 07/22/2019] [Indexed: 11/16/2022] Open
Abstract
A first analysis of simultaneous 68Ga-prostate-specific membrane antigen (PSMA)-11 PET/MRI showed some improvement in the detection of recurrent disease at low serum prostate specific antigen (PSA) values below 0.5 ng/mL compared with the already high detection rate of 68Ga-PSMA-11 PET/CT. We therefore focused on all patients with biochemical recurrence and PSA values no higher than 0.5 ng/mL to assess the detection rate for 68Ga-PSMA-11 PET/MRI. Methods: We retrospectively analyzed a cohort of 66 consecutive patients who underwent 68Ga-PSMA-11 PET/MRI for biochemical recurrence with a PSA value no higher than 0.5 ng/mL at our institution. Median PSA level was 0.23 ng/mL (range, 0.03-0.5 ng/mL). Detection of PSMA-positive lesions within the prostate fossa, local and distant lymph nodes, bones, or visceral organs was recorded. In addition, all scans with 68Ga-PSMA-11 PET/MRI-positive lesions were retrospectively assessed to analyze if lesions were detected inside or outside a standard salvage radiotherapy volume. Results: Overall, in 36 of 66 patients (54.5%) PSMA-positive lesions were detected; in 26 of 40 (65%) patients with a PSA level between 0.2 and 0.5 ng/mL and in 10 of 26 (38.5%) patients with a PSA level less than 0.2 ng/mL. Even at those low PSA values, only 8 of 66 (12.1%) patients had exclusive local recurrence. Lymph nodes were detected in 23 patients and bone metastases in 5 on 68Ga-PSMA-11 PET/MRI. In 26 of 66 patients (39.4%), PSMA-positive lesions were located outside a standard salvage radiotherapy volume. Conclusion: Our data confirm that 68Ga-PSMA-11 PET/MRI has a high detection rate for recurrent prostate cancer, even at low PSA levels no higher than 0.5 ng/mL. In addition, we show that 68Ga-PSMA-11 PET/MRI detected PSMA-positive lesions outside a standard salvage radiotherapy volume in 39.4% of all patients.
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Affiliation(s)
- Benedikt Kranzbühler
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Julian Müller
- Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Anton S Becker
- Department of Interventional and Diagnostic Radiology, University Hospital Zürich, University of Zürich, Zürich, Switzerland; and
| | - Helena I Garcia Schüler
- Department of Radiation Oncology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Urs Muehlematter
- Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Christian D Fankhauser
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Sarah Kedzia
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland.,Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Matthias Guckenberger
- Department of Radiation Oncology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Philipp A Kaufmann
- Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Daniel Eberli
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Irene A Burger
- Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, Zürich, Switzerland
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Fiechter M, Haider A, Bengs S, Marȩdziak M, Burger IA, Roggo A, Portmann A, Warnock GI, Schade K, Treyer V, Becker AS, Messerli M, Felten EV, Benz DC, Fuchs TA, Gräni C, Pazhenkottil AP, Buechel RR, Kaufmann PA, Gebhard C. Sex Differences in the Association between Inflammation and Ischemic Heart Disease. Thromb Haemost 2019; 119:1471-1480. [PMID: 31226718 DOI: 10.1055/s-0039-1692442] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
BACKGROUND Inflammation plays a fundamental role in mediating all stages of atherosclerosis. Given the higher prevalence of inflammatory rheumatologic conditions in women and the female propensity towards worse cardiovascular outcomes, refined strategies are needed to better identify the high-risk female cardiovascular phenotype. OBJECTIVES This article aims to assess sex-specific links between inflammatory processes and the development and progression of ischemic heart disease. PATIENTS AND METHODS The relationship between vertebral bone marrow metabolism-a marker of inflammation-and myocardial injury was retrospectively assessed in 294 patients (28.6% women, mean age: 66.9 ± 10.0 years) who underwent 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) and 99mTc-tetrofosmin single-photon emission computed tomography myocardial perfusion imaging (SPECT-MPI). RESULTS A significant increase in 18F-FDG bone marrow uptake was observed in women with impaired myocardial perfusion (SPECT-MPI) as compared to women with normal myocardial perfusion (standardized uptake value [SUV]: 2.2 ± 1.2 vs. 1.7 ± 0.5, p = 0.013), while no such difference was observed in men (SUV: 1.6 ± 0.8 vs. 1.6 ± 0.4, p = 0.372). Furthermore, a significant inverse correlation between left ventricular ejection fraction (LVEF) and bone marrow metabolism was seen in women (r = -0.229, p = 0.037), but not in men (r = -0.075, p = 0.289). Accordingly, in women, but not in men, bone marrow activity was identified as an independent predictor of both, reduced LVEF (β-coefficient, -4.537; p = 0.040) and impaired myocardial perfusion (β-coefficient, 0.138; p = 0.014). CONCLUSION A strong link between bone marrow metabolism and impaired myocardial function and perfusion was observed in women, but not in men. Our data suggest that novel biomarkers of inflammation might help to identify women at risk for ischemic cardiomyopathy and to tailor disease management to the female cardiovascular phenotype.
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Affiliation(s)
- Michael Fiechter
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland.,Center for Molecular Cardiology, University of Zurich, Zurich, Switzerland.,Swiss Paraplegic Center, Nottwil, Switzerland
| | - Ahmed Haider
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland.,Center for Molecular Cardiology, University of Zurich, Zurich, Switzerland
| | - Susan Bengs
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland.,Center for Molecular Cardiology, University of Zurich, Zurich, Switzerland
| | - Monika Marȩdziak
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland.,Center for Molecular Cardiology, University of Zurich, Zurich, Switzerland
| | - Irene A Burger
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Andrea Roggo
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Angela Portmann
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland.,Center for Molecular Cardiology, University of Zurich, Zurich, Switzerland
| | - Geoffrey I Warnock
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland.,Center for Molecular Cardiology, University of Zurich, Zurich, Switzerland
| | - Katharina Schade
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Valerie Treyer
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Anton S Becker
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Michael Messerli
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Elia von Felten
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Dominik C Benz
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Tobias A Fuchs
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Christoph Gräni
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Aju P Pazhenkottil
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Ronny R Buechel
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Philipp A Kaufmann
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Catherine Gebhard
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland.,Center for Molecular Cardiology, University of Zurich, Zurich, Switzerland
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Woo S, Suh CH, Eastham JA, Zelefsky MJ, Morris MJ, Abida W, Scher HI, Sidlow R, Becker AS, Wibmer AG, Hricak H, Vargas HA. Comparison of Magnetic Resonance Imaging-stratified Clinical Pathways and Systematic Transrectal Ultrasound-guided Biopsy Pathway for the Detection of Clinically Significant Prostate Cancer: A Systematic Review and Meta-analysis of Randomized Controlled Trials. Eur Urol Oncol 2019; 2:605-616. [PMID: 31204311 DOI: 10.1016/j.euo.2019.05.004] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 05/14/2019] [Accepted: 05/23/2019] [Indexed: 02/02/2023]
Abstract
CONTEXT Recent studies suggested that magnetic resonance imaging (MRI) followed by targeted biopsy ("MRI-stratified pathway") detects more clinically significant prostate cancers (csPCa) than the systematic transrectal ultrasound-guided prostate biopsy (TRUS-Bx) pathway, but controversy persists. Several randomized clinical trials (RCTs) were recently published, enabling generation of higher-level evidence to evaluate this hypothesis. OBJECTIVE To perform a systematic review and meta-analysis of RCTs comparing the detection rates of csPCa in the MRI-stratified pathway and the systematic TRUS-Bx pathway in patients with a suspicion of prostate cancer (PCa). EVIDENCE ACQUISITION PubMed, EMBASE, and Cochrane databases were searched up to March 18, 2019. RCTs reporting csPCa detection rates of both pathways in patients with a clinical suspicion of prostate cancer were included. Relative csPCa detection rates of the MRI-stratified pathway were pooled using random-effect model. Study quality was assessed using the Cochrane risk of bias tool for randomized trials. A comparison of detection rates of clinically insignificant PCa (cisPCa) and any PCa was also performed. EVIDENCE SYNTHESIS Nine RCTs (2908 patients) were included. The MRI-stratified pathway detected more csPCa than the TRUS-Bx pathway (relative detection rate 1.45 [95% confidence interval {CI} 1.09-1.92] for all patients, and 1.42 [95% CI 1.02-1.97] and 1.60 [95% CI 1.01-2.54] for biopsy-naïve and prior negative biopsy patients, respectively). Detection rates were not significantly different between pathways for cisPCa (0.89 [95% CI 0.49-1.62]), but higher in the MRI-stratified pathway for the detection of any PCa (1.39 [95% CI 1.05-1.84]). CONCLUSIONS The MRI-stratified pathway detected more csPCa than the systematic TRUS-guided biopsy pathway in men with a clinical suspicion of PCa, for both biopsy-naïve patients and those with prior negative biopsy. The detection rate of any PCa was higher in the MRI-stratified pathway, but not significantly different from that of cisPCa. PATIENT SUMMARY Our meta-analysis of clinical trials shows that the magnetic resonance imaging-stratified pathway detects more clinically significant prostate cancers than the transrectal ultrasound-guided prostate biopsy pathway in men with a suspicion of prostate cancer.
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Affiliation(s)
- Sungmin Woo
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.
| | - Chong Hyun Suh
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - James A Eastham
- Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Michael J Zelefsky
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Michael J Morris
- Genitourinary Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Wassim Abida
- Genitourinary Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Howard I Scher
- Genitourinary Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Robert Sidlow
- Integrative Medicine Service, Division of Survivorship and Supportive Care, Bendheim Center for Integrative Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Anton S Becker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Andreas G Wibmer
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Hedvig Hricak
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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Becker AS, Blüthgen C, Phi van VD, Sekaggya-Wiltshire C, Castelnuovo B, Kambugu A, Fehr J, Frauenfelder T. Detection of tuberculosis patterns in digital photographs of chest X-ray images using Deep Learning: feasibility study. Int J Tuberc Lung Dis 2019; 22:328-335. [PMID: 29471912 DOI: 10.5588/ijtld.17.0520] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
OBJECTIVE To evaluate the feasibility of Deep Learning-based detection and classification of pathological patterns in a set of digital photographs of chest X-ray (CXR) images of tuberculosis (TB) patients. MATERIALS AND METHODS In this prospective, observational study, patients with previously diagnosed TB were enrolled. Photographs of their CXRs were taken using a consumer-grade digital still camera. The images were stratified by pathological patterns into classes: cavity, consolidation, effusion, interstitial changes, miliary pattern or normal examination. Image analysis was performed with commercially available Deep Learning software in two steps. Pathological areas were first localised; detected areas were then classified. Detection was assessed using receiver operating characteristics (ROC) analysis, and classification using a confusion matrix. RESULTS The study cohort was 138 patients with human immunodeficiency virus (HIV) and TB co-infection (median age 34 years, IQR 28-40); 54 patients were female. Localisation of pathological areas was excellent (area under the ROC curve 0.82). The software could perfectly distinguish pleural effusions from intraparenchymal changes. The most frequent misclassifications were consolidations as cavitations, and miliary patterns as interstitial patterns (and vice versa). CONCLUSION Deep Learning analysis of CXR photographs is a promising tool. Further efforts are needed to build larger, high-quality data sets to achieve better diagnostic performance.
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Affiliation(s)
- A S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich, Switzerland
| | - C Blüthgen
- Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich, Switzerland
| | - V D Phi van
- Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich, Switzerland
| | - C Sekaggya-Wiltshire
- Infectious Disease Institute, College of Health Sciences, Makerere University, Kampala, Uganda
| | - B Castelnuovo
- Infectious Disease Institute, College of Health Sciences, Makerere University, Kampala, Uganda
| | - A Kambugu
- Infectious Disease Institute, College of Health Sciences, Makerere University, Kampala, Uganda
| | - J Fehr
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - T Frauenfelder
- Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich, Switzerland
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Sartoretti T, Sartoretti E, Wyss M, Schwenk Á, Najafi A, Binkert C, Reischauer C, Zhou J, Jiang S, Becker AS, Sartoretti-Schefer S. Amide Proton Transfer Contrast Distribution in Different Brain Regions in Young Healthy Subjects. Front Neurosci 2019; 13:520. [PMID: 31178687 PMCID: PMC6538817 DOI: 10.3389/fnins.2019.00520] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 05/06/2019] [Indexed: 12/11/2022] Open
Abstract
Objectives To define normal signal intensity values of amide proton transfer-weighted (APTw) magnetic resonance (MR) imaging in different brain regions. Materials and Methods Twenty healthy subjects (9 females, mean age 29 years, range 19 - 37 years) underwent MR imaging at 3 Tesla. 3D APTw (RF saturation B1,rms = 2 μT, duration 2 s, 100% duty cycle) and 2D T2-weighted turbo spin echo (TSE) images were acquired. Postprocessing (image fusion, ROI measurements of APTw intensity values in 22 different brain regions) was performed and controlled by two independent neuroradiologists. Values were measured separately for each brain hemisphere. A subject was scanned both in prone and supine position to investigate differences between hemispheres. A mixed model on a 5% significance level was used to assess the effect of gender, brain region and side on APTw intensity values. Results Mean APTw intensity values in the hippocampus and amygdala varied between 1.13 and 1.57%, in the deep subcortical nuclei (putamen, globus pallidus, head of caudate nucleus, thalamus, red nucleus, substantia nigra) between 0.73 and 1.84%, in the frontal, occipital and parietal cortex between 0.56 and 1.03%; in the insular cortex between 1.11 and 1.15%, in the temporal cortex between 1.22 and 1.37%, in the frontal, occipital and parietal white matter between 0.32 and 0.54% and in the temporal white matter between 0.83 and 0.89%. APTw intensity values were significantly impacted both by brain region (p < 0.001) and by side (p < 0.001), whereby overall values on the left side were higher than on the right side (1.13 vs. 0.9%). Gender did not significantly impact APTw intensity values (p = 0.24). APTw intensity values between the left and the right side were partially reversed after changing the position of one subject from supine to prone. Conclusion We determined normal baseline APTw intensity values in different anatomical localizations in healthy subjects. APTw intensity values differed both between anatomical regions and between left and right brain hemisphere.
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Affiliation(s)
- Thomas Sartoretti
- Institute of Radiology, Cantonal Hospital Winterthur, Winterthur, Switzerland.,Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Elisabeth Sartoretti
- Institute of Radiology, Cantonal Hospital Winterthur, Winterthur, Switzerland.,Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Michael Wyss
- Institute of Radiology, Cantonal Hospital Winterthur, Winterthur, Switzerland.,Philips Health Systems, Zurich, Switzerland
| | - Árpád Schwenk
- Institute of Radiology, Cantonal Hospital Winterthur, Winterthur, Switzerland
| | - Arash Najafi
- Institute of Radiology, Cantonal Hospital Winterthur, Winterthur, Switzerland
| | - Christoph Binkert
- Institute of Radiology, Cantonal Hospital Winterthur, Winterthur, Switzerland.,Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Carolin Reischauer
- Institute of Radiology, Cantonal Hospital Winterthur, Winterthur, Switzerland
| | - Jinyuan Zhou
- Department of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, United States
| | - Shanshan Jiang
- Department of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, United States
| | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Sabine Sartoretti-Schefer
- Institute of Radiology, Cantonal Hospital Winterthur, Winterthur, Switzerland.,Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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50
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Schindler V, Runggaldier D, Bianca A, Becker AS, Murray F, Savarino E, Pohl D. Opioid Treatment and Excessive Alcohol Consumption Are Associated With Esophagogastric Junction Disorders. J Neurogastroenterol Motil 2019; 25:205-211. [PMID: 30982239 PMCID: PMC6474705 DOI: 10.5056/jnm18150] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 12/06/2018] [Accepted: 01/08/2019] [Indexed: 12/23/2022] Open
Abstract
Background/Aims The influence of external factors such as opioids and alcohol has been extensively investigated for various segments of the gastrointestinal tract. However, the association between their use and the development of esophagogastric junction outflow obstruction disorders (EGJOODs) is unknown. Therefore, the aim of this study is to analyze prevalence and clinical relevance of opioids and alcohol intake in patients with EGJOODs. Methods In this single-center, retrospective study, we reviewed clinical and pharmacological data of 375 consecutive patients who had undergone high resolution impedance manometry for EGJOODs. EGJOODs were classified according to the Chicago classification version 3.0 and to recently published normal values for test meals. Demographics, manometric data, and symptoms were compared between different groups using Pearson’s chi-squared test, Fisher’s exact test, and multivariate analysis. A P < 0.05 was considered significant. Results EGJOOD was found in 30.7% (115/375) of all analyzed patients. The prevalence of opioids (14.8% vs 4.2%, P = 0.026) was significantly higher in patients with EGJOODs compared to patients without EGJOODs. Additionally, excessive alcohol consumption (12.2% vs 3.5%, P = 0.011) was associated with EGJOODs. Excessive alcohol consumption was especially frequent in the non-achalasia esophagogastric junction outflow obstruction subgroup (16.2%) and opioid use in the achalasia type III subgroup (20.0%). Conclusions We found a significant association between EGJOODs and opioid as well as excessive alcohol consumption. This underlines the importance of detailed history taking regarding medication and ethanol consumption in patients with dysphagia. Further prospective studies on mechanisms undelaying esophagogastric junction dysfunction due to opioids or alcohol are warranted.
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Affiliation(s)
- Valeria Schindler
- Division of Gastroenterology and Hepatology, University Hospital Zurich, Switzerland
| | - Daniel Runggaldier
- Division of Gastroenterology and Hepatology, University Hospital Zurich, Switzerland.,Department of Otorhinolaryngology, University Hospital of Zurich, Switzerland
| | - Amanda Bianca
- Division of Gastroenterology and Hepatology, University Hospital Zurich, Switzerland
| | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Switzerland
| | - Fritz Murray
- Division of Gastroenterology and Hepatology, University Hospital Zurich, Switzerland
| | - Edoardo Savarino
- Department of Surgery, Oncology and Gastroenterology, University of Padua, Italy
| | - Daniel Pohl
- Division of Gastroenterology and Hepatology, University Hospital Zurich, Switzerland
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