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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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Reissig TM, Tzianopoulos I, Liffers ST, Rosery VK, Guyot M, Ting S, Wiesweg M, Kasper S, Meister P, Herold T, Schmidt HH, Schumacher B, Albers D, Markus P, Treckmann J, Schuler M, Schildhaus HU, Siveke JT. Smaller panel, similar results: genomic profiling and molecularly informed therapy in pancreatic cancer. ESMO Open 2023; 8:101539. [PMID: 37148593 DOI: 10.1016/j.esmoop.2023.101539] [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: 02/04/2023] [Revised: 03/12/2023] [Accepted: 03/24/2023] [Indexed: 05/08/2023] Open
Abstract
BACKGROUND Pancreatic cancer has a dismal prognosis. One reason is resistance to cytotoxic drugs. Molecularly matched therapies might overcome this resistance but the best approach to identify those patients who may benefit is unknown. Therefore, we sought to evaluate a molecularly guided treatment approach. MATERIALS AND METHODS We retrospectively analyzed the clinical outcome and mutational status of patients with pancreatic cancer who received molecular profiling at the West German Cancer Center Essen from 2016 to 2021. We carried out a 47-gene DNA next-generation sequencing (NGS) panel. Furthermore, we assessed microsatellite instability-high/deficient mismatch repair (MSI-H/dMMR) status and, sequentially and only in case of KRAS wild-type, gene fusions via RNA-based NGS. Patient data and treatment were retrieved from the electronic medical records. RESULTS Of 190 included patients, 171 had pancreatic ductal adenocarcinoma (90%). One hundred and three patients had stage IV pancreatic cancer at diagnosis (54%). MMR analysis in 94 patients (94/190, 49.5%) identified 3 patients with dMMR (3/94, 3.2%). Notably, we identified 32 patients with KRAS wild-type status (16.8%). To identify driver alterations in these patients, we conducted an RNA-based fusion assay on 13 assessable samples and identified 5 potentially actionable fusions (5/13, 38.5%). Overall, we identified 34 patients with potentially actionable alterations (34/190, 17.9%). Of these 34 patients, 10 patients (10/34, 29.4%) finally received at least one molecularly targeted treatment and 4 patients had an exceptional response (>9 months on treatment). CONCLUSIONS Here, we show that a small-sized gene panel can suffice to identify relevant therapeutic options for pancreatic cancer patients. Informally comparing with previous large-scale studies, this approach yields a similar detection rate of actionable targets. We propose molecular sequencing of pancreatic cancer as standard of care to identify KRAS wild-type and rare molecular subsets for targeted treatment strategies.
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Affiliation(s)
- T M Reissig
- Bridge Institute of Experimental Tumor Therapy, West German Cancer Center, University Hospital Essen, Essen, Germany; Division of Solid Tumor Translational Oncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Partner Site University Hospital Essen, Heidelberg, Germany; Department of Medical Oncology, West German Cancer Center, University Hospital Essen, Essen, Germany; German Cancer Consortium (DKTK), Partner Site University Hospital Essen, Essen, Germany
| | - I Tzianopoulos
- Bridge Institute of Experimental Tumor Therapy, West German Cancer Center, University Hospital Essen, Essen, Germany; Division of Solid Tumor Translational Oncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Partner Site University Hospital Essen, Heidelberg, Germany; Department of Medical Oncology, West German Cancer Center, University Hospital Essen, Essen, Germany
| | - S-T Liffers
- Bridge Institute of Experimental Tumor Therapy, West German Cancer Center, University Hospital Essen, Essen, Germany; Division of Solid Tumor Translational Oncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Partner Site University Hospital Essen, Heidelberg, Germany; German Cancer Consortium (DKTK), Partner Site University Hospital Essen, Essen, Germany
| | - V K Rosery
- Bridge Institute of Experimental Tumor Therapy, West German Cancer Center, University Hospital Essen, Essen, Germany; Division of Solid Tumor Translational Oncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Partner Site University Hospital Essen, Heidelberg, Germany; Department of Medical Oncology, West German Cancer Center, University Hospital Essen, Essen, Germany; German Cancer Consortium (DKTK), Partner Site University Hospital Essen, Essen, Germany
| | - M Guyot
- Department of Medical Oncology, West German Cancer Center, University Hospital Essen, Essen, Germany; Department of Gastroenterology, Oncology und Hematology, Diabetology and Rheumatology, Marien-Hospital Wesel, Wesel, Germany
| | - S Ting
- Institute of Pathology, West German Cancer Center, University Hospital Essen, Essen, Germany
| | - M Wiesweg
- Department of Medical Oncology, West German Cancer Center, University Hospital Essen, Essen, Germany; German Cancer Consortium (DKTK), Partner Site University Hospital Essen, Essen, Germany
| | - S Kasper
- Department of Medical Oncology, West German Cancer Center, University Hospital Essen, Essen, Germany; German Cancer Consortium (DKTK), Partner Site University Hospital Essen, Essen, Germany
| | - P Meister
- Department of General, Visceral and Transplantation Surgery, Hepatology, and Transplant Medicine, University Hospital Essen, Essen, Germany
| | - T Herold
- Institute of Pathology, West German Cancer Center, University Hospital Essen, Essen, Germany
| | - H H Schmidt
- Department of Gastroenterology, Hepatology, and Transplant Medicine, University Hospital Essen, Essen, Germany
| | - B Schumacher
- Department of Gastroenterology, Visceral and Trauma Surgery, Elisabeth Hospital Essen, Essen, Germany
| | - D Albers
- Department of Gastroenterology, Visceral and Trauma Surgery, Elisabeth Hospital Essen, Essen, Germany
| | - P Markus
- Department of General, Visceral and Trauma Surgery, Elisabeth Hospital Essen, Essen, Germany
| | - J Treckmann
- Department of General, Visceral and Transplantation Surgery, Hepatology, and Transplant Medicine, University Hospital Essen, Essen, Germany
| | - M Schuler
- Department of Medical Oncology, West German Cancer Center, University Hospital Essen, Essen, Germany; German Cancer Consortium (DKTK), Partner Site University Hospital Essen, Essen, Germany
| | - H-U Schildhaus
- German Cancer Consortium (DKTK), Partner Site University Hospital Essen, Essen, Germany; Institute of Pathology, West German Cancer Center, University Hospital Essen, Essen, Germany
| | - J T Siveke
- Bridge Institute of Experimental Tumor Therapy, West German Cancer Center, University Hospital Essen, Essen, Germany; Division of Solid Tumor Translational Oncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Partner Site University Hospital Essen, Heidelberg, Germany; Department of Medical Oncology, West German Cancer Center, University Hospital Essen, Essen, Germany; German Cancer Consortium (DKTK), Partner Site University Hospital Essen, Essen, Germany.
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