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Keyl J, Bucher A, Jungmann F, Hosch R, Ziller A, Armbruster R, Malkomes P, Reissig TM, Koitka S, Tzianopoulos I, Keyl P, Kostbade K, Albers D, Markus P, Treckmann J, Nassenstein K, Haubold J, Makowski M, Forsting M, Baba HA, Kasper S, Siveke JT, Nensa F, Schuler M, Kaissis G, Kleesiek J, Braren R. Prognostic value of deep learning-derived body composition in advanced pancreatic cancer-a retrospective multicenter study. ESMO Open 2024; 9:102219. [PMID: 38194881 PMCID: PMC10837775 DOI: 10.1016/j.esmoop.2023.102219] [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] [Received: 09/03/2023] [Revised: 12/11/2023] [Accepted: 12/13/2023] [Indexed: 01/11/2024] Open
Abstract
BACKGROUND Despite the prognostic relevance of cachexia in pancreatic cancer, individual body composition has not been routinely integrated into treatment planning. In this multicenter study, we investigated the prognostic value of sarcopenia and myosteatosis automatically extracted from routine computed tomography (CT) scans of patients with advanced pancreatic ductal adenocarcinoma (PDAC). PATIENTS AND METHODS We retrospectively analyzed clinical imaging data of 601 patients from three German cancer centers. We applied a deep learning approach to assess sarcopenia by the abdominal muscle-to-bone ratio (MBR) and myosteatosis by the ratio of abdominal inter- and intramuscular fat to muscle volume. In the pooled cohort, univariable and multivariable analyses were carried out to analyze the association between body composition markers and overall survival (OS). We analyzed the relationship between body composition markers and laboratory values during the first year of therapy in a subgroup using linear regression analysis adjusted for age, sex, and American Joint Committee on Cancer (AJCC) stage. RESULTS Deep learning-derived MBR [hazard ratio (HR) 0.60, 95% confidence interval (CI) 0.47-0.77, P < 0.005] and myosteatosis (HR 3.73, 95% CI 1.66-8.39, P < 0.005) were significantly associated with OS in univariable analysis. In multivariable analysis, MBR (P = 0.019) and myosteatosis (P = 0.02) were associated with OS independent of age, sex, and AJCC stage. In a subgroup, MBR and myosteatosis were associated with albumin and C-reactive protein levels after initiation of therapy. Additionally, MBR was also associated with hemoglobin and total protein levels. CONCLUSIONS Our work demonstrates that deep learning can be applied across cancer centers to automatically assess sarcopenia and myosteatosis from routine CT scans. We highlight the prognostic role of our proposed markers and show a strong relationship with protein levels, inflammation, and anemia. In clinical practice, automated body composition analysis holds the potential to further personalize cancer treatment.
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Affiliation(s)
- J Keyl
- Institute for Artificial Intelligence in Medicine, University Hospital Essen (AöR), Essen, Germany; Institute of Pathology, University Hospital Essen (AöR), Essen, Germany.
| | - A Bucher
- Institute for Diagnostic and Interventional Radiology, Goethe University Frankfurt, Frankfurt am Main, Germany; German Cancer Consortium (DKTK), Frankfurt partner site, Heidelberg, Germany
| | - F Jungmann
- Institute of Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany; Artificial Intelligence in Healthcare and Medicine, School of Computation, Information and Technology, Technical University of Munich, Munich, Germany
| | - R Hosch
- Institute for Artificial Intelligence in Medicine, University Hospital Essen (AöR), Essen, Germany
| | - A Ziller
- Institute of Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany; Artificial Intelligence in Healthcare and Medicine, School of Computation, Information and Technology, Technical University of Munich, Munich, Germany
| | - R Armbruster
- Institute for Diagnostic and Interventional Radiology, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - P Malkomes
- Department of General, Visceral and Transplant Surgery, Goethe University Hospital Frankfurt, Frankfurt am Main, Germany
| | - T M Reissig
- Department of Medical Oncology, University Hospital Essen (AöR), Essen, Germany; West German Cancer Center, University Hospital Essen (AöR), Essen, Germany; German Cancer Consortium (DKTK), Partner site University Hospital Essen (AöR), Essen, Germany; Bridge Institute of Experimental Tumor Therapy, West German Cancer Center, University Hospital Essen, University of Duisburg-Essen, Essen, Germany; Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK Partner Site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany
| | - S Koitka
- Institute for Artificial Intelligence in Medicine, University Hospital Essen (AöR), Essen, Germany; Institute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen (AöR), Essen, Germany
| | - I Tzianopoulos
- Department of Medical Oncology, University Hospital Essen (AöR), Essen, Germany; West German Cancer Center, University Hospital Essen (AöR), Essen, Germany; Bridge Institute of Experimental Tumor Therapy, West German Cancer Center, University Hospital Essen, University of Duisburg-Essen, Essen, Germany; Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK Partner Site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany
| | - P Keyl
- Institute of Pathology, Ludwig-Maximilians-University Munich, Munich, Germany
| | - K Kostbade
- Department of Medical Oncology, University Hospital Essen (AöR), Essen, Germany; West German Cancer Center, University Hospital Essen (AöR), Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - D Albers
- Department of Gastroenterology, Elisabeth Hospital Essen, Essen, Germany
| | - P Markus
- Department of General Surgery and Traumatology, Elisabeth Hospital Essen, Essen, Germany
| | - J Treckmann
- West German Cancer Center, University Hospital Essen (AöR), Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany; Department of General, Visceral and Transplant Surgery, University Hospital Essen, Essen, Germany
| | - K Nassenstein
- Institute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen (AöR), Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - J Haubold
- Institute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen (AöR), Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - M Makowski
- Institute of Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany
| | - M Forsting
- German Cancer Consortium (DKTK), Partner site University Hospital Essen (AöR), Essen, Germany; Institute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen (AöR), Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - H A Baba
- Institute of Pathology, University Hospital Essen (AöR), Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - S Kasper
- Department of Medical Oncology, University Hospital Essen (AöR), Essen, Germany; West German Cancer Center, University Hospital Essen (AöR), Essen, Germany; German Cancer Consortium (DKTK), Partner site University Hospital Essen (AöR), Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - J T Siveke
- Department of Medical Oncology, University Hospital Essen (AöR), Essen, Germany; West German Cancer Center, University Hospital Essen (AöR), Essen, Germany; German Cancer Consortium (DKTK), Partner site University Hospital Essen (AöR), Essen, Germany; Bridge Institute of Experimental Tumor Therapy, West German Cancer Center, University Hospital Essen, University of Duisburg-Essen, Essen, Germany; Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK Partner Site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - F Nensa
- Institute for Artificial Intelligence in Medicine, University Hospital Essen (AöR), Essen, Germany; German Cancer Consortium (DKTK), Partner site University Hospital Essen (AöR), Essen, Germany; Institute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen (AöR), Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - M Schuler
- Department of Medical Oncology, University Hospital Essen (AöR), Essen, Germany; West German Cancer Center, University Hospital Essen (AöR), Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany; National Center for Tumor Diseases (NCT), NCT West, Essen, Germany
| | - G Kaissis
- Institute of Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany; Artificial Intelligence in Healthcare and Medicine, School of Computation, Information and Technology, Technical University of Munich, Munich, Germany
| | - J Kleesiek
- Institute for Artificial Intelligence in Medicine, University Hospital Essen (AöR), Essen, Germany; West German Cancer Center, University Hospital Essen (AöR), Essen, Germany; German Cancer Consortium (DKTK), Partner site University Hospital Essen (AöR), Essen, Germany; Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - R Braren
- Institute of Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany; German Cancer Consortium (DKTK), Munich partner site, Heidelberg, Germany
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Summer T, Bota O, Armbruster R, Münchow S, Dragu A. [Soft tissue defects following tumor resection in the limbs and trunk : Plastic reconstructive soft tissue and revision concepts]. Orthopade 2020; 49:169-176. [PMID: 31974632 DOI: 10.1007/s00132-020-03871-2] [Citation(s) in RCA: 2] [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] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
BACKGROUND Tissue defects of the trunk and limbs after oncologic surgery and radiation require plastic reconstructive tissue coverage. Depending on the location and size of the wound as well as the interdisciplinary treatment concept, different reconstructive procedures are performed. These range from skin transplantation to local and pedicle flaps, to perforator flaps and free microsurgical tissue transfer. METHODS The modern "reconstructive ladder" can be regarded as an orientation for the sequence of the reconstructive options. Considering the patient's wishes and risk profile, an individual reconstructive concept must be devised. The best functional and simultaneously safest procedure with the smallest secondary defect is to be chosen. Wound preconditioning via vacuum-assisted closure can precede definitive tissue coverage in order to optimize local conditions. CONCLUSION Safe tissue coverage can be achieved even in advanced stages of oncologic disease and after extensive surgery by performing wound preconditioning and arteriovenous loop grafting to induce safe de novo recipient vessels for two-stage free tissue transfer. The choice between maximum plastic reconstructive options for a curative approach or limited palliative surgery is to be harmonized and balanced with therapeutic goals and the patient's biologic resources. Preservation and restoration of quality of life and functionality is the plastic surgeon's dictum.
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Affiliation(s)
- T Summer
- Abteilung für Plastische und Handchirurgie, UniversitätsCentrum für Orthopädie und Unfallchirurgie, Universitätsklinikum Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307, Dresden, Deutschland.
| | - O Bota
- Abteilung für Plastische und Handchirurgie, UniversitätsCentrum für Orthopädie und Unfallchirurgie, Universitätsklinikum Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307, Dresden, Deutschland
| | - R Armbruster
- Abteilung für Plastische und Handchirurgie, UniversitätsCentrum für Orthopädie und Unfallchirurgie, Universitätsklinikum Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307, Dresden, Deutschland
| | - S Münchow
- Abteilung für Plastische und Handchirurgie, UniversitätsCentrum für Orthopädie und Unfallchirurgie, Universitätsklinikum Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307, Dresden, Deutschland
| | - A Dragu
- Abteilung für Plastische und Handchirurgie, UniversitätsCentrum für Orthopädie und Unfallchirurgie, Universitätsklinikum Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307, Dresden, Deutschland
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