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Pullen LCE, Noortman WA, Triemstra L, de Jongh C, Rademaker FJ, Spijkerman R, Kalisvaart GM, Gertsen EC, de Geus-Oei LF, Tolboom N, de Steur WO, Dantuma M, Slart RHJA, van Hillegersberg R, Siersema PD, Ruurda JP, van Velden FHP, Vegt E. Prognostic Value of [ 18F]FDG PET Radiomics to Detect Peritoneal and Distant Metastases in Locally Advanced Gastric Cancer-A Side Study of the Prospective Multicentre PLASTIC Study. Cancers (Basel) 2023; 15:cancers15112874. [PMID: 37296837 DOI: 10.3390/cancers15112874] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 05/13/2023] [Accepted: 05/14/2023] [Indexed: 06/12/2023] Open
Abstract
AIM To improve identification of peritoneal and distant metastases in locally advanced gastric cancer using [18F]FDG-PET radiomics. METHODS [18F]FDG-PET scans of 206 patients acquired in 16 different Dutch hospitals in the prospective multicentre PLASTIC-study were analysed. Tumours were delineated and 105 radiomic features were extracted. Three classification models were developed to identify peritoneal and distant metastases (incidence: 21%): a model with clinical variables, a model with radiomic features, and a clinicoradiomic model, combining clinical variables and radiomic features. A least absolute shrinkage and selection operator (LASSO) regression classifier was trained and evaluated in a 100-times repeated random split, stratified for the presence of peritoneal and distant metastases. To exclude features with high mutual correlations, redundancy filtering of the Pearson correlation matrix was performed (r = 0.9). Model performances were expressed by the area under the receiver operating characteristic curve (AUC). In addition, subgroup analyses based on Lauren classification were performed. RESULTS None of the models could identify metastases with low AUCs of 0.59, 0.51, and 0.56, for the clinical, radiomic, and clinicoradiomic model, respectively. Subgroup analysis of intestinal and mixed-type tumours resulted in low AUCs of 0.67 and 0.60 for the clinical and radiomic models, and a moderate AUC of 0.71 in the clinicoradiomic model. Subgroup analysis of diffuse-type tumours did not improve the classification performance. CONCLUSION Overall, [18F]FDG-PET-based radiomics did not contribute to the preoperative identification of peritoneal and distant metastases in patients with locally advanced gastric carcinoma. In intestinal and mixed-type tumours, the classification performance of the clinical model slightly improved with the addition of radiomic features, but this slight improvement does not outweigh the laborious radiomic analysis.
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Affiliation(s)
- Lieke C E Pullen
- Biomedical Photonic Imaging Group, University of Twente, 7522 NB Enschede, The Netherlands
| | - Wyanne A Noortman
- Biomedical Photonic Imaging Group, University of Twente, 7522 NB Enschede, The Netherlands
- Department of Radiology, Leiden University Medical Center, 2333 ZD Leiden, The Netherlands
| | - Lianne Triemstra
- Department of Surgery, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Cas de Jongh
- Department of Surgery, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Fenna J Rademaker
- TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands
| | - Romy Spijkerman
- TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands
| | - Gijsbert M Kalisvaart
- Department of Radiology, Leiden University Medical Center, 2333 ZD Leiden, The Netherlands
| | - Emma C Gertsen
- Department of Surgery, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Lioe-Fee de Geus-Oei
- Biomedical Photonic Imaging Group, University of Twente, 7522 NB Enschede, The Netherlands
- Department of Radiology, Leiden University Medical Center, 2333 ZD Leiden, The Netherlands
| | - Nelleke Tolboom
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Wobbe O de Steur
- Department of Surgery, Leiden University Medical Center, 2333 ZD Leiden, The Netherlands
| | - Maura Dantuma
- Multi-Modality Medical Imaging Group, TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands
| | - Riemer H J A Slart
- Biomedical Photonic Imaging Group, University of Twente, 7522 NB Enschede, The Netherlands
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands
| | | | - Peter D Siersema
- Department of Gastroenterology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Jelle P Ruurda
- Department of Surgery, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Floris H P van Velden
- Department of Radiology, Leiden University Medical Center, 2333 ZD Leiden, The Netherlands
| | - Erik Vegt
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, 3015 GD Rotterdam, The Netherlands
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Vaz SC, Graff SL, Ferreira AR, Debiasi M, de Geus-Oei LF. PET/CT in Patients with Breast Cancer Treated with Immunotherapy. Cancers (Basel) 2023; 15:cancers15092620. [PMID: 37174086 PMCID: PMC10177398 DOI: 10.3390/cancers15092620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 04/27/2023] [Accepted: 05/02/2023] [Indexed: 05/15/2023] Open
Abstract
Significant advances in breast cancer (BC) treatment have been made in the last decade, including the use of immunotherapy and, in particular, immune checkpoint inhibitors that have been shown to improve the survival of patients with triple negative BC. This narrative review summarizes the studies supporting the use of immunotherapy in BC. Furthermore, the usefulness of 2-deoxy-2-[18F]fluoro-D-glucose (2-[18F]FDG) positron emission/computerized tomography (PET/CT) to image the tumor heterogeneity and to assess treatment response is explored, including the different criteria to interpret 2-[18F]FDG PET/CT imaging. The concept of immuno-PET is also described, by explaining the advantages of mapping treatment targets with a non-invasive and whole-body tool. Several radiopharmaceuticals in the preclinical phase are referred too, and, considering their promising results, translation to human studies is needed to support their use in clinical practice. Overall, this is an evolving field in BC treatment, despite PET imaging developments, the future trends also include expanding immunotherapy to early-stage BC and using other biomarkers.
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Affiliation(s)
- Sofia C Vaz
- Nuclear Medicine-Radiopharmacology, Champalimaud Center for the Unkown, Champalimaud Foundation, 1400-038 Lisbon, Portugal
- Department of Radiology, Leiden University Medical Center, P.O. Box 9600-2300 RC Leiden, The Netherlands
| | - Stephanie L Graff
- Division of Hematology/Oncology, Lifespan Cancer Institute, Providence, RI 02903, USA
- Legorreta Cancer Center, The Warren Alpert Medical School, Brown University, Providence, RI 02903, USA
| | - Arlindo R Ferreira
- Católica Medical School, Universidade Católica Portuguesa, 2635-631 Lisbon, Portugal
| | - Márcio Debiasi
- Breast Cancer Unit, Champalimaud Center for the Unkown, Champalimaud Foundation, 1400-038 Lisbon, Portugal
| | - Lioe-Fee de Geus-Oei
- Department of Radiology, Leiden University Medical Center, P.O. Box 9600-2300 RC Leiden, The Netherlands
- Biomedical Photonic Imaging Group, University of Twente, P.O. Box 217-7500 AE Enschede, The Netherlands
- Department of radiation Science & Technology, Delft University of Technology, P.O. Postbus 5 2600 AA Delft, The Netherlands
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Measures of Corticalization. J Clin Med 2022; 11:jcm11185463. [PMID: 36143109 PMCID: PMC9500652 DOI: 10.3390/jcm11185463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 09/14/2022] [Accepted: 09/15/2022] [Indexed: 11/16/2022] Open
Abstract
After the insertion of dental implants into living bone, the condition of the peri-implant bone changes with time. Implant-loading phenomena can induce bone remodeling in the form of the corticalization of the trabecular bone. The aim of this study was to see how bone index (BI) values behave in areas of bone loss (radiographically translucent non-trabecular areas) and to propose other indices specifically dedicated to detecting corticalization in living bone. Eight measures of corticalization in clinical standardized intraoral radiographs were studied: mean optical density, entropy, differential entropy, long-run emphasis moment, BI, corticalization index ver. 1 and ver. 2 (CI v.1, CI v.2) and corticalization factor (CF). The analysis was conducted on 40 cortical bone image samples, 40 cancellous bone samples and 40 soft tissue samples. It was found that each measure distinguishes corticalization significantly (p < 0.001), but only CI v.1 and CI v.2 do so selectively. CF or the inverse of BI can serve as a measure of peri-implant bone corticalization. However, better measures are CIs as they are dedicated to detecting this phenomenon and allowing clear clinical deduction.
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Editorial on Special Issue “Quantitative PET and SPECT”. Diagnostics (Basel) 2022; 12:diagnostics12081989. [PMID: 36010339 PMCID: PMC9407256 DOI: 10.3390/diagnostics12081989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 08/09/2022] [Accepted: 08/15/2022] [Indexed: 11/26/2022] Open
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Slart RHJA, de Geus-Oei LF. A new colleague in nuclear medicine, the clinical technologist: quo vadis? Eur J Nucl Med Mol Imaging 2022; 49:3012-3015. [PMID: 35384463 DOI: 10.1007/s00259-022-05789-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- Riemer H J A Slart
- Medical Imaging Centre, Department of Nuclear Medicine and Molecular Imaging (EB50), University Medical Center Groningen, University of Groningen, P.O. Box 30.001, 9700 RB, Groningen, The Netherlands. .,Biomedical Photonic Imaging Group, Faculty of Science and Technology, University of Twente, Enschede, The Netherlands.
| | - Lioe-Fee de Geus-Oei
- Biomedical Photonic Imaging Group, Faculty of Science and Technology, University of Twente, Enschede, The Netherlands.,Department of Radiology, Section of Nuclear Medicine, Leiden University Medical Center, Leiden, The Netherlands
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The Influence of the Exclusion of Central Necrosis on [ 18F]FDG PET Radiomic Analysis. Diagnostics (Basel) 2021; 11:diagnostics11071296. [PMID: 34359379 PMCID: PMC8304274 DOI: 10.3390/diagnostics11071296] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 07/14/2021] [Accepted: 07/15/2021] [Indexed: 11/17/2022] Open
Abstract
Background: Central necrosis can be detected on [18F]FDG PET/CT as a region with little to no tracer uptake. Currently, there is no consensus regarding the inclusion of regions of central necrosis during volume of interest (VOI) delineation for radiomic analysis. The aim of this study was to assess how central necrosis affects radiomic analysis in PET. Methods: Forty-three patients, either with non-small cell lung carcinomas (NSCLC, n = 12) or with pheochromocytomas or paragangliomas (PPGL, n = 31), were included retrospectively. VOIs were delineated with and without central necrosis. From all VOIs, 105 radiomic features were extracted. Differences in radiomic features between delineation methods were assessed using a paired t-test with Benjamini–Hochberg multiple testing correction. In the PPGL cohort, performances of the radiomic models to predict the noradrenergic biochemical profile were assessed by comparing the areas under the receiver operating characteristic curve (AUC) for both delineation methods. Results: At least 65% of the features showed significant differences between VOIvital-tumour and VOIgross-tumour (65%, 79% and 82% for the NSCLC, PPGL and combined cohort, respectively). The AUCs of the radiomic models were not significantly different between delineation methods. Conclusion: In both tumour types, almost two-third of the features were affected, demonstrating that the impact of whether or not to include central necrosis in the VOI on the radiomic feature values is significant. Nevertheless, predictive performances of both delineation methods were comparable. We recommend that radiomic studies should report whether or not central necrosis was included during delineation.
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Noortman WA, Vriens D, Mooij CDY, Slump CH, Aarntzen EH, van Berkel A, Timmers HJLM, Bussink J, Meijer TWH, de Geus-Oei LF, van Velden FHP. The Influence of the Exclusion of Central Necrosis on [ 18F]FDG PET Radiomic Analysis. DIAGNOSTICS (BASEL, SWITZERLAND) 2021. [PMID: 34359379 DOI: 10.3390/diagnostics] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Central necrosis can be detected on [18F]FDG PET/CT as a region with little to no tracer uptake. Currently, there is no consensus regarding the inclusion of regions of central necrosis during volume of interest (VOI) delineation for radiomic analysis. The aim of this study was to assess how central necrosis affects radiomic analysis in PET. METHODS Forty-three patients, either with non-small cell lung carcinomas (NSCLC, n = 12) or with pheochromocytomas or paragangliomas (PPGL, n = 31), were included retrospectively. VOIs were delineated with and without central necrosis. From all VOIs, 105 radiomic features were extracted. Differences in radiomic features between delineation methods were assessed using a paired t-test with Benjamini-Hochberg multiple testing correction. In the PPGL cohort, performances of the radiomic models to predict the noradrenergic biochemical profile were assessed by comparing the areas under the receiver operating characteristic curve (AUC) for both delineation methods. RESULTS At least 65% of the features showed significant differences between VOIvital-tumour and VOIgross-tumour (65%, 79% and 82% for the NSCLC, PPGL and combined cohort, respectively). The AUCs of the radiomic models were not significantly different between delineation methods. CONCLUSION In both tumour types, almost two-third of the features were affected, demonstrating that the impact of whether or not to include central necrosis in the VOI on the radiomic feature values is significant. Nevertheless, predictive performances of both delineation methods were comparable. We recommend that radiomic studies should report whether or not central necrosis was included during delineation.
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Affiliation(s)
- Wyanne A Noortman
- Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
- TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands
| | - Dennis Vriens
- Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
| | - Charlotte D Y Mooij
- Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
- Technical Medicine, Delft University of Technology, 2628 CD Delft, The Netherlands
| | - Cornelis H Slump
- TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands
| | - Erik H Aarntzen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Anouk van Berkel
- Division of Endocrinology, Department of Internal Medicine, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Henri J L M Timmers
- Division of Endocrinology, Department of Internal Medicine, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Johan Bussink
- Radiotherapy and OncoImmunology Laboratory, Department of Radiation Oncology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Tineke W H Meijer
- Department of Radiation Oncology, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands
| | - Lioe-Fee de Geus-Oei
- Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
- TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands
| | - Floris H P van Velden
- Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
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Arabi H, AkhavanAllaf A, Sanaat A, Shiri I, Zaidi H. The promise of artificial intelligence and deep learning in PET and SPECT imaging. Phys Med 2021; 83:122-137. [DOI: 10.1016/j.ejmp.2021.03.008] [Citation(s) in RCA: 84] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Revised: 02/18/2021] [Accepted: 03/03/2021] [Indexed: 02/06/2023] Open
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de Geus-Oei LF, Deroose CM. Nuclear medicine in precision oncology: a foreword. THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING : OFFICIAL PUBLICATION OF THE ITALIAN ASSOCIATION OF NUCLEAR MEDICINE (AIMN) [AND] THE INTERNATIONAL ASSOCIATION OF RADIOPHARMACOLOGY (IAR), [AND] SECTION OF THE SOCIETY OF RADIOPHARMACEUTICAL CHEMISTRY AND BIOLOGY 2020; 64:231-233. [PMID: 32343513 DOI: 10.23736/s1824-4785.20.03262-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Lioe-Fee de Geus-Oei
- Department of Radiology, Leiden University Medical Center (LUMC), Leiden, the Netherlands.,Biomedical Photonic Imaging Group, University of Twente, Enschede, the Netherlands
| | - Christophe M Deroose
- Nuclear Medicine, University Hospitals Leuven, Leuven, Belgium - .,Unit of Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
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