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Wei L, Aryal MP, Lee C, Shah JL, Mierzwa ML, Cao Y. Interpretable survival network for progression risk analysis of multimodality imaging biomarkers in poor-prognosis head and neck cancers. Sci Rep 2024; 14:30004. [PMID: 39622922 PMCID: PMC11612283 DOI: 10.1038/s41598-024-80815-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2024] [Accepted: 11/21/2024] [Indexed: 12/06/2024] Open
Abstract
This study explores the predictive utility of multi-time point, multi-modality quantitative imaging biomarkers (QIBs) and clinical factors in patients with poor-prognosis head and neck cancers (HNCs) using interpretable machine learning. We examined 93 patients with p16 + oropharyngeal squamous cell carcinoma or locally advanced p16- HNCs enrolled in a phase II adaptive radiation dose escalation trial. FDG-PET and multiparametric MRI scans were conducted before radiation therapy and at the 10th fraction (2 weeks). A survival network analyzed MRI and PET-derived biomarkers such as gross tumor volume (GTV), blood volume (BV), and metabolic tumor volume (MTV50), along with clinical factors to predict local (LF) and distant failures (DF). Feature attributions and interactions were assessed using Expected Gradients (EG) and Expected Hessian (EH). Through rigorous cross-validation, the model for predicting LF, incorporating biomarkers like p16 status and radiation boost, achieved a c-index of 0.758. Similarly, the DF prediction model showed a c-index of 0.695. The analysis of feature attributions and interactions enhanced understanding of important features and complex factor interplays, potentially guiding more personalized and intensified treatment approaches for HNC patients.
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Affiliation(s)
- Lise Wei
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
| | - Madhava P Aryal
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Choonik Lee
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Jennifer L Shah
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Michelle L Mierzwa
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Yue Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
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Liang H, Tan W, Wang J, Li M, Pang H, Wang X, Yang L, Jing X. Novel prediction model combining PET/CT metabolic parameters, inflammation markers, and TNM stage: prospects for personalizing prognosis in nasopharyngeal carcinoma. Ann Nucl Med 2024; 38:802-813. [PMID: 38874876 DOI: 10.1007/s12149-024-01949-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Accepted: 05/30/2024] [Indexed: 06/15/2024]
Abstract
PURPOSE This study aims to develop a novel prediction model and risk stratification system that could accurately predict progression-free survival (PFS) in patients with nasopharyngeal carcinoma (NPC). METHODS Herein, we included 106 individuals diagnosed with NPC, who underwent 18F-FDG PET/CT scanning before treatment. They were divided into training (n = 76) and validation (n = 30) sets. The prediction model was constructed based on multivariate Cox regression analysis results and its predictive performance was evaluated. Risk factor stratification was performed based on the nomogram scores of each case, and Kaplan-Meier curves were used to evaluate the model's discriminative ability for high- and low-risk groups. RESULTS Multivariate Cox regression analysis showed that N stage, M stage, SUVmax, MTV, HI, and SIRI were independent factors affecting the prognosis of patients with NPC. In the training set, the model considerably outperformed the TNM stage in predicting PFS (AUCs of 0.931 vs. 0.841, 0.892 vs. 0.785, and 0.892 vs. 0.804 at 1-3 years, respectively). The calibration plots showed good agreement between actual observations and model predictions. The DCA curves further justified the effectiveness of the model in clinical practice. Between high- and low-risk group, 3-year PFS rates were significantly different (high- vs. low-risk group: 62.8% vs. 9.8%, p < 0.001). Adjuvant chemotherapy was also effective for prolonging survival in high-risk patients (p = 0.009). CONCLUSION Herein, a novel prediction model was successfully developed and validated to improve the accuracy of prognostic prediction for patients with NPC, with the aim of facilitating personalized treatment.
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Affiliation(s)
- Huan Liang
- Department of Nuclear Medicine, The First Affiliated Hospital of Chongqing Medical University, Yuzhong District, No. 1 Youyi Road, YuanjiagangChongqing, 400016, China
| | - Weilin Tan
- Department of Neurosurgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Jie Wang
- Department of Nuclear Medicine, The First Affiliated Hospital of Chongqing Medical University, Yuzhong District, No. 1 Youyi Road, YuanjiagangChongqing, 400016, China
| | - Mengdan Li
- Department of Nuclear Medicine, The First Affiliated Hospital of Chongqing Medical University, Yuzhong District, No. 1 Youyi Road, YuanjiagangChongqing, 400016, China
| | - Hua Pang
- Department of Nuclear Medicine, The First Affiliated Hospital of Chongqing Medical University, Yuzhong District, No. 1 Youyi Road, YuanjiagangChongqing, 400016, China
| | - Xiaohui Wang
- Department of Nuclear Medicine, The First Affiliated Hospital of Chongqing Medical University, Yuzhong District, No. 1 Youyi Road, YuanjiagangChongqing, 400016, China
| | - Lu Yang
- Department of Nuclear Medicine, The First Affiliated Hospital of Chongqing Medical University, Yuzhong District, No. 1 Youyi Road, YuanjiagangChongqing, 400016, China
| | - Xingguo Jing
- Department of Nuclear Medicine, The First Affiliated Hospital of Chongqing Medical University, Yuzhong District, No. 1 Youyi Road, YuanjiagangChongqing, 400016, China.
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3
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Zschaeck S, Klinger B, van den Hoff J, Cegla P, Apostolova I, Kreissl MC, Cholewiński W, Kukuk E, Strobel H, Amthauer H, Blüthgen N, Zips D, Hofheinz F. Combination of tumor asphericity and an extracellular matrix-related prognostic gene signature in non-small cell lung cancer patients. Sci Rep 2023; 13:20840. [PMID: 38012155 PMCID: PMC10681996 DOI: 10.1038/s41598-023-46405-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 10/31/2023] [Indexed: 11/29/2023] Open
Abstract
One important aim of precision oncology is a personalized treatment of patients. This can be achieved by various biomarkers, especially imaging parameters and gene expression signatures are commonly used. So far, combination approaches are sparse. The aim of the study was to independently validate the prognostic value of the novel positron emission tomography (PET) parameter tumor asphericity (ASP) in non small cell lung cancer (NSCLC) patients and to investigate associations between published gene expression profiles and ASP. This was a retrospective evaluation of PET imaging and gene expression data from three public databases and two institutional datasets. The whole cohort comprised 253 NSCLC patients, all treated with curative intent surgery. Clinical parameters, standard PET parameters and ASP were evaluated in all patients. Additional gene expression data were available for 120 patients. Univariate Cox regression and Kaplan-Meier analysis was performed for the primary endpoint progression-free survival (PFS) and additional endpoints. Furthermore, multivariate cox regression testing was performed including clinically significant parameters, ASP, and the extracellular matrix-related prognostic gene signature (EPPI). In the whole cohort, a significant association with PFS was observed for ASP (p < 0.001) and EPPI (p = 0.012). Upon multivariate testing, EPPI remained significantly associated with PFS (p = 0.018) in the subgroup of patients with additional gene expression data, while ASP was significantly associated with PFS in the whole cohort (p = 0.012). In stage II patients, ASP was significantly associated with PFS (p = 0.009), and a previously published cutoff value for ASP (19.5%) was successfully validated (p = 0.008). In patients with additional gene expression data, EPPI showed a significant association with PFS, too (p = 0.033). The exploratory combination of ASP and EPPI showed that the combinatory approach has potential to further improve patient stratification compared to the use of only one parameter. We report the first successful validation of EPPI and ASP in stage II NSCLC patients. The combination of both parameters seems to be a very promising approach for improvement of risk stratification in a group of patients with urgent need for a more personalized treatment approach.
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Affiliation(s)
- Sebastian Zschaeck
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Berlin Institute of Health (BIH), 10178, Berlin, Germany
| | - Bertram Klinger
- Berlin Institute of Health (BIH), 10178, Berlin, Germany
- Computational Modelling in Medicine, Instiute of Pathology, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- German Cancer Consortium (DKTK), Partner Site Berlin, Berlin, Germany
| | - Jörg van den Hoff
- Helmholtz-Zentrum Dresden-Rossendorf, PET Center, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Paulina Cegla
- Department of Nuclear Medicine, Greater Poland Cancer Centre, Poznan, Poland
| | - Ivayla Apostolova
- Department for Diagnostic and Interventional Radiology and Nuclear Medicine, University Hospital Hamburg-Eppendorf, Hamburg, Germany
- Division of Nuclear Medicine, Department of Radiology and Nuclear Medicine, Otto Von Guericke University, Magdeburg, Germany
| | - Michael C Kreissl
- Division of Nuclear Medicine, Department of Radiology and Nuclear Medicine, Otto Von Guericke University, Magdeburg, Germany
| | - Witold Cholewiński
- Department of Nuclear Medicine, Greater Poland Cancer Centre, Poznan, Poland
| | - Emily Kukuk
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Helen Strobel
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Holger Amthauer
- Division of Nuclear Medicine, Department of Radiology and Nuclear Medicine, Otto Von Guericke University, Magdeburg, Germany
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Nils Blüthgen
- Berlin Institute of Health (BIH), 10178, Berlin, Germany
- Computational Modelling in Medicine, Instiute of Pathology, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- German Cancer Consortium (DKTK), Partner Site Berlin, Berlin, Germany
| | - Daniel Zips
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- German Cancer Consortium (DKTK), Partner Site Berlin, Berlin, Germany
| | - Frank Hofheinz
- Helmholtz-Zentrum Dresden-Rossendorf, PET Center, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany.
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Demirel BB, Gülbahar Ateş S, Atasever Akkaş E, Göksel F, Uçmak G. Prognostic value of primary tumor and lymph node volumetric metabolic parameters at pre-treatment F-18 FDG PET/CT in nasopharyngeal carcinoma. Rev Esp Med Nucl Imagen Mol 2023; 42:367-373. [PMID: 37391092 DOI: 10.1016/j.remnie.2023.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 05/26/2023] [Accepted: 05/28/2023] [Indexed: 07/02/2023]
Abstract
BACKGROUND The aim of this study was to evaluate the prognostic significance of volumetric metabolic parameters of pre-treatment PET/CT along with clinical characteristics in patients with non-metastatic nasopharyngeal carcinoma. MATERIAL AND METHODS Seventy-nine patients with nasopharyngeal carcinoma underwent F18- FDG PET/CT for pretreatment evaluation and included in this study. The patient features (patient age, tumor histopathology, T and N stage, size of primary tumor and the largest cervical lymph node) and PET parameters were analyzed: maximum, mean and peak standardized uptake values (SUVmax, SUVmean, SUVpeak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) for primary tumor and largest cervical lymph node. After treatment, patients were evaluated for disease progression and mortality. Survival analysis for progression-free survival (PFS) and over-all survival (OS) was performed with Kaplan-Meier method using PET findings and clinical characteristics. RESULTS The median follow-up duration was 29.7 months (range 3-125 months). Among clinical characteristics, no parameters had significance association for PFS. Primary tumor-MTV and cervical lymph node-MTV were independent prognostic factors for PFS (p = 0.025 and p = 0.004, respectively).Patients with primary tumor-MTV >19.4 and patients with lymph node-MTV>3.4 had shorter PFS. For OS, age and the size of the lymph node were independent prognostic factor (p = 0.031 and p = 0.029).Patients with age over 54 years and patients with lymph node size >1 cm were associated with decreased OS. CONCLUSION Primary tumor-MTV and lymph node-MTV on pre-treatment PET/CT are significant prognostic factors for long-term PFS in non-metastatic nasopharyngeal carcinoma. We consider that measuring MTV as volume-based metabolic parameter on pretreatment PET/CT may contribute decision of treatment intensity and individualized risk stratification and may improve long-term PFS. Additionally, age and the size of lymph node are independent prognostic factors for mortality.
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Affiliation(s)
- Bedriye Büşra Demirel
- Ankara Oncology Research and Training Hospital, Department of Nuclear Medicine, Ankara, Turkey.
| | - Seda Gülbahar Ateş
- Hitit University Erol Olçok Education and Research Hospital, Department of Nuclear Medicine, Ankara, Turkey
| | - Ebru Atasever Akkaş
- Ankara Oncology Research and Training Hospital, Department of Radiation Oncology, Ankara, Turkey
| | - Fatih Göksel
- Ankara Oncology Research and Training Hospital, Department of Radiation Oncology, Ankara, Turkey
| | - Gülin Uçmak
- Ankara Oncology Research and Training Hospital, Department of Nuclear Medicine, Ankara, Turkey
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Liu Q, Bode AM, Chen X, Luo X. Metabolic reprogramming in nasopharyngeal carcinoma: Mechanisms and therapeutic opportunities. Biochim Biophys Acta Rev Cancer 2023; 1878:189023. [PMID: 37979733 DOI: 10.1016/j.bbcan.2023.189023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 11/08/2023] [Accepted: 11/09/2023] [Indexed: 11/20/2023]
Abstract
The high prevalence of metabolic reprogramming in nasopharyngeal carcinoma (NPC) offers an abundance of potential therapeutic targets. This review delves into the distinct mechanisms underlying metabolic reprogramming in NPC, including enhanced glycolysis, nucleotide synthesis, and lipid metabolism. All of these changes are modulated by Epstein-Barr virus (EBV) infection, hypoxia, and tumor microenvironment. We highlight the role of metabolic reprogramming in the development of NPC resistance to standard therapies, which represents a challenging barrier in treating this malignancy. Furthermore, we dissect the state of the art in therapeutic strategies that target these metabolic changes, evaluating the successes and failures of clinical trials and the strategies to tackle resistance mechanisms. By providing a comprehensive overview of the current knowledge and future directions in this field, this review sets the stage for new therapeutic avenues in NPC.
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Affiliation(s)
- Qian Liu
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Oncotarget Gene, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan 410013, PR China; Key Laboratory of Carcinogenesis and Invasion, Chinese Ministry of Education, Cancer Research Institute, School of Basic Medicine, Central South University, Changsha, Hunan 410078, PR China
| | - Ann M Bode
- The Hormel Institute, University of Minnesota, Austin, MN 55912, USA
| | - Xue Chen
- Early Clinical Trial Center, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan 410013, PR China.
| | - Xiangjian Luo
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Oncotarget Gene, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan 410013, PR China; Key Laboratory of Carcinogenesis and Invasion, Chinese Ministry of Education, Cancer Research Institute, School of Basic Medicine, Central South University, Changsha, Hunan 410078, PR China; Key Laboratory of Biological Nanotechnology of National Health Commission, Central South University, Changsha, Hunan 410078, China.
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6
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Mokoala KMG, Lawal IO, Maserumule LC, Bida M, Maes A, Ndlovu H, Reed J, Mahapane J, Davis C, Van de Wiele C, Popoola G, Giesel FL, Vorster M, Sathekge MM. Correlation between [ 68Ga]Ga-FAPI-46 PET Imaging and HIF-1α Immunohistochemical Analysis in Cervical Cancer: Proof-of-Concept. Cancers (Basel) 2023; 15:3953. [PMID: 37568769 PMCID: PMC10417683 DOI: 10.3390/cancers15153953] [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: 06/02/2023] [Revised: 07/31/2023] [Accepted: 07/31/2023] [Indexed: 08/13/2023] Open
Abstract
Hypoxia leads to changes in tumor microenvironment (upregulated CAFs) with resultant aggressiveness. A key factor in the physiological response to hypoxia is hypoxia-inducible factor-1alpha (HIF-1α). [68Ga]Ga-FAPI PET imaging has been demonstrated in various cancer types. We hypothesized that [68Ga]Ga-FAPI PET may be used as an indirect tracer for mapping hypoxia by correlating the image findings to pathological analysis of HIF-1α expression. The [68Ga]Ga-FAPI PET/CT scans of women with cancer of the cervix were reviewed and the maximum and mean standardized uptake value (SUVmax and SUVmean) and FAPI tumor volume (FAPI-TV) were documented. Correlation analysis was performed between PET-derived parameters and immunohistochemical staining as well as between PET-derived parameters and the presence of metastasis. Ten women were included. All patients demonstrated tracer uptake in the primary site or region of the primary. All patients had lymph node metastases while only six patients had distant visceral or skeletal metastases. The mean SUVmax, SUVmean, and FAPI-TV was 18.89, 6.88, and 195.66 cm3, respectively. The average FAPI-TV for patients with additional sites of metastases was higher than those without. Immunohistochemistry revealed varying intensities of HIF-1α expression in all tested samples. There was a positive correlation between the presence of skeletal metastases and staining for HIF-1α (r=0.80;p=0.017). The presence of skeletal metastasis was correlated to the HIF-1⍺ staining (percentage distribution). Furthermore, the FAPI-TV was a better predictor of metastatic disease than the SUVmax.
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Affiliation(s)
- Kgomotso M. G. Mokoala
- Department of Nuclear Medicine, University of Pretoria, Pretoria 0028, South Africa; (K.M.G.M.); (I.O.L.); (L.C.M.); (A.M.); (H.N.); (J.R.); (C.D.); (C.V.d.W.)
| | - Ismaheel O. Lawal
- Department of Nuclear Medicine, University of Pretoria, Pretoria 0028, South Africa; (K.M.G.M.); (I.O.L.); (L.C.M.); (A.M.); (H.N.); (J.R.); (C.D.); (C.V.d.W.)
- Nuclear Medicine Research Infrastructure (NuMeRI), Steve Biko Academic Hospital, Pretoria 0001, South Africa
| | - Letjie C. Maserumule
- Department of Nuclear Medicine, University of Pretoria, Pretoria 0028, South Africa; (K.M.G.M.); (I.O.L.); (L.C.M.); (A.M.); (H.N.); (J.R.); (C.D.); (C.V.d.W.)
| | - Meshack Bida
- National Health Laboratory Services, Department of Anatomical Pathology, Pretoria 0001, South Africa;
| | - Alex Maes
- Department of Nuclear Medicine, University of Pretoria, Pretoria 0028, South Africa; (K.M.G.M.); (I.O.L.); (L.C.M.); (A.M.); (H.N.); (J.R.); (C.D.); (C.V.d.W.)
- Katholieke University Leuven, 3000 Kortrijk, Belgium
| | - Honest Ndlovu
- Department of Nuclear Medicine, University of Pretoria, Pretoria 0028, South Africa; (K.M.G.M.); (I.O.L.); (L.C.M.); (A.M.); (H.N.); (J.R.); (C.D.); (C.V.d.W.)
| | - Janet Reed
- Department of Nuclear Medicine, University of Pretoria, Pretoria 0028, South Africa; (K.M.G.M.); (I.O.L.); (L.C.M.); (A.M.); (H.N.); (J.R.); (C.D.); (C.V.d.W.)
| | - Johncy Mahapane
- Department of Radiography, University of Pretoria, Pretoria 0028, South Africa;
| | - Cindy Davis
- Department of Nuclear Medicine, University of Pretoria, Pretoria 0028, South Africa; (K.M.G.M.); (I.O.L.); (L.C.M.); (A.M.); (H.N.); (J.R.); (C.D.); (C.V.d.W.)
| | - Christophe Van de Wiele
- Department of Nuclear Medicine, University of Pretoria, Pretoria 0028, South Africa; (K.M.G.M.); (I.O.L.); (L.C.M.); (A.M.); (H.N.); (J.R.); (C.D.); (C.V.d.W.)
- Department of Diagnostic Sciences, University Ghent, 9000 Ghent, Belgium
| | - Gbenga Popoola
- Lincolnshire Partnership NHS Foundation Trust, St George’s, Lincoln, Lincolnshire LN1 1FS, UK;
| | - Frederik L. Giesel
- Department of Nuclear Medicine, Medical Faculty, University Hospital Dusseldorf, Heinrich-Heine-University, 40225 Düsseldorf, Germany;
| | - Mariza Vorster
- Department of Nuclear Medicine, University of Kwazulu Natal, Durban 4001, South Africa;
| | - Mike M. Sathekge
- Department of Nuclear Medicine, University of Pretoria, Pretoria 0028, South Africa; (K.M.G.M.); (I.O.L.); (L.C.M.); (A.M.); (H.N.); (J.R.); (C.D.); (C.V.d.W.)
- Nuclear Medicine Research Infrastructure (NuMeRI), Steve Biko Academic Hospital, Pretoria 0001, South Africa
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Elahmadawy MA, Ashraf A, Moustafa H, Kotb M, Abd El-Gaid S. Prognostic value of initial [ 18 F]FDG PET/computed tomography volumetric and texture analysis-based parameters in patients with head and neck squamous cell carcinoma. Nucl Med Commun 2023; 44:653-662. [PMID: 37038954 DOI: 10.1097/mnm.0000000000001695] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Abstract
AIM OF WORK To determine the predictive value of initial [ 18 F]FDG PET/computed tomography (CT) volumetric and radiomics-derived analyses in patients with head and neck squamous cell carcinoma (HNSCC). METHODS Forty-six adult patients had pathologically proven HNSCC and underwent pretherapy [ 18 F]FDG PET/CT were enrolled. Semi-quantitative PET-derived volumetric [(maximum standardized uptake value (SUVmax) and mean SUV (SUVmean), total lesion glycolysis (TLG) and metabolic tumor volume (MTV)] and radiomics analyses using LIFEx 6.73.3 software were performed. RESULTS In the current study group, the receiver operating characteristic curve marked a cutoff point of 21.105 for primary MTV with area under the curve (AUC) of 0.727, sensitivity of 62.5%, and specificity of 86.8% ( P value 0.041) to distinguish responders from non-responders, while no statistically significant primary SUVmean or max or primary TLG cut off points could be determined. It also marked the cutoff point for survival prediction of 10.845 for primary MTV with AUC 0.728, sensitivity of 80%, and specificity of 77.8% ( P value 0.026). A test of the synergistic performance of PET-derived volumetric and textural features significant parameters was conducted in an attempt to develop the most accurate and stable prediction model. Therefore, multivariate logistic regression analysis was performed to detect independent predictors of mortality. With a high specificity of 97.1% and an overall accuracy of 89.1%, the combination of primary tumor MTV and the textural feature gray-level co-occurrence matrix correlation provided the most accurate prediction of mortality ( P value < 0.001). CONCLUSION Textural feature indices are a noninvasive method for capturing intra-tumoral heterogeneity. In our study, a PET-derived prediction model was successfully generated with high specificity and accuracy.
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Affiliation(s)
| | - Aya Ashraf
- Nuclear Medicine Unit, National Cancer Institute
| | - Hosna Moustafa
- Nuclear Medicine Unit, Kasr Al-Ainy (NEMROCK Center), Cairo University, Cairo, Egypt
| | - Magdy Kotb
- Nuclear Medicine Unit, National Cancer Institute
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8
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Nikulin P, Zschaeck S, Maus J, Cegla P, Lombardo E, Furth C, Kaźmierska J, Rogasch JMM, Holzgreve A, Albert NL, Ferentinos K, Strouthos I, Hajiyianni M, Marschner SN, Belka C, Landry G, Cholewinski W, Kotzerke J, Hofheinz F, van den Hoff J. A convolutional neural network with self-attention for fully automated metabolic tumor volume delineation of head and neck cancer in [Formula: see text]F]FDG PET/CT. Eur J Nucl Med Mol Imaging 2023; 50:2751-2766. [PMID: 37079128 PMCID: PMC10317885 DOI: 10.1007/s00259-023-06197-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 03/14/2023] [Indexed: 04/21/2023]
Abstract
PURPOSE PET-derived metabolic tumor volume (MTV) and total lesion glycolysis of the primary tumor are known to be prognostic of clinical outcome in head and neck cancer (HNC). Including evaluation of lymph node metastases can further increase the prognostic value of PET but accurate manual delineation and classification of all lesions is time-consuming and prone to interobserver variability. Our goal, therefore, was development and evaluation of an automated tool for MTV delineation/classification of primary tumor and lymph node metastases in PET/CT investigations of HNC patients. METHODS Automated lesion delineation was performed with a residual 3D U-Net convolutional neural network (CNN) incorporating a multi-head self-attention block. 698 [Formula: see text]F]FDG PET/CT scans from 3 different sites and 5 public databases were used for network training and testing. An external dataset of 181 [Formula: see text]F]FDG PET/CT scans from 2 additional sites was employed to assess the generalizability of the network. In these data, primary tumor and lymph node (LN) metastases were interactively delineated and labeled by two experienced physicians. Performance of the trained network models was assessed by 5-fold cross-validation in the main dataset and by pooling results from the 5 developed models in the external dataset. The Dice similarity coefficient (DSC) for individual delineation tasks and the primary tumor/metastasis classification accuracy were used as evaluation metrics. Additionally, a survival analysis using univariate Cox regression was performed comparing achieved group separation for manual and automated delineation, respectively. RESULTS In the cross-validation experiment, delineation of all malignant lesions with the trained U-Net models achieves DSC of 0.885, 0.805, and 0.870 for primary tumor, LN metastases, and the union of both, respectively. In external testing, the DSC reaches 0.850, 0.724, and 0.823 for primary tumor, LN metastases, and the union of both, respectively. The voxel classification accuracy was 98.0% and 97.9% in cross-validation and external data, respectively. Univariate Cox analysis in the cross-validation and the external testing reveals that manually and automatically derived total MTVs are both highly prognostic with respect to overall survival, yielding essentially identical hazard ratios (HR) ([Formula: see text]; [Formula: see text] vs. [Formula: see text]; [Formula: see text] in cross-validation and [Formula: see text]; [Formula: see text] vs. [Formula: see text]; [Formula: see text] in external testing). CONCLUSION To the best of our knowledge, this work presents the first CNN model for successful MTV delineation and lesion classification in HNC. In the vast majority of patients, the network performs satisfactory delineation and classification of primary tumor and lymph node metastases and only rarely requires more than minimal manual correction. It is thus able to massively facilitate study data evaluation in large patient groups and also does have clear potential for supervised clinical application.
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Affiliation(s)
- Pavel Nikulin
- Helmholtz-Zentrum Dresden-Rossendorf, PET Center, Institute of Radiopharmaceutical Cancer Research, Bautzner Landstrasse 400, 01328, Dresden, Germany.
| | - Sebastian Zschaeck
- Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Jens Maus
- Helmholtz-Zentrum Dresden-Rossendorf, PET Center, Institute of Radiopharmaceutical Cancer Research, Bautzner Landstrasse 400, 01328, Dresden, Germany
| | - Paulina Cegla
- Department of Nuclear Medicine, Greater Poland Cancer Centre, Poznan, Poland
| | - Elia Lombardo
- Department of Radiation Oncology, University Hospital, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Christian Furth
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Joanna Kaźmierska
- Electroradiology Department, University of Medical Sciences, Poznan, Poland
- Radiotherapy Department II, Greater Poland Cancer Centre, Poznan, Poland
| | - Julian M M Rogasch
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Adrien Holzgreve
- Department of Nuclear Medicine, University Hospital, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Nathalie L Albert
- Department of Nuclear Medicine, University Hospital, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Konstantinos Ferentinos
- Department of Radiation Oncology, German Oncology Center, European University Cyprus, Limassol, Cyprus
| | - Iosif Strouthos
- Department of Radiation Oncology, German Oncology Center, European University Cyprus, Limassol, Cyprus
| | - Marina Hajiyianni
- Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Sebastian N Marschner
- Department of Radiation Oncology, University Hospital, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Guillaume Landry
- Department of Radiation Oncology, University Hospital, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Witold Cholewinski
- Department of Nuclear Medicine, Greater Poland Cancer Centre, Poznan, Poland
- Electroradiology Department, University of Medical Sciences, Poznan, Poland
| | - Jörg Kotzerke
- Department of Nuclear Medicine, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Frank Hofheinz
- Helmholtz-Zentrum Dresden-Rossendorf, PET Center, Institute of Radiopharmaceutical Cancer Research, Bautzner Landstrasse 400, 01328, Dresden, Germany
| | - Jörg van den Hoff
- Helmholtz-Zentrum Dresden-Rossendorf, PET Center, Institute of Radiopharmaceutical Cancer Research, Bautzner Landstrasse 400, 01328, Dresden, Germany
- Department of Nuclear Medicine, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
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9
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Lou Y, Chen D, Lin Z, Sun J, Song L, Chen W, Zhang M, Chen Y. The prognostic value of the ratio of standard uptake value of lymph node to primary tumor before treatment of locally advanced nasopharyngeal carcinoma. Eur Arch Otorhinolaryngol 2023; 280:347-356. [PMID: 35932312 PMCID: PMC9813001 DOI: 10.1007/s00405-022-07562-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 07/17/2022] [Indexed: 01/19/2023]
Abstract
BACKGROUND To evaluate the prognostic value of the ratio of the standard uptake value of the lymph node and primary tumor before the treatment of locally advanced nasopharyngeal carcinoma and examine the prognostic value of the tumor metabolic parameters (SUVmax, MTV, and TLG) of the lymph node and primary tumor of locally advanced nasopharyngeal carcinoma. METHODS A total of 180 patients with locally advanced nasopharyngeal carcinoma diagnosed pathologically from January 1, 2016 to December 31, 2018 were selected, and the MEDEX system was used to automatically delineate the SUVmax, MTV, and TLG of the lymph node metastases and nasopharyngeal carcinoma primary tumor. In addition, the ratio of LN-SUVmax (SUVmax of the lymph node metastases) to T-SUVmax (SUVmax of the nasopharyngeal carcinoma primary tumor) was calculated, and a ROC curve was drawn to obtain the best cut-off value. Kaplan-Meier and Cox regression models were used for survival and multivariate analyses, respectively. RESULTS The median follow-up period for participants was 32 (4-62) months. Univariate analysis showed that age (P = 0.013), LN-SUVmax (P = 0.001), LN-TLG (P = 0.007) and NTR (P = 0.001) were factors influencing the overall survival (OS). Factors affecting local progression-free survival (LPFS) were LN-SUVmax (P = 0.005), LN-TLG (P = 0.003) and NTR (P = 0.020), while clinical stage (P = 0.023), LN-SUVmax (P = 0.007), LN-TLG (P = 0.006), and NTR (P = 0.032) were factors affecting distant metastasis-free survival (DMFS). Multivariate analysis showed that NTR was an independent influencing factor of OS (HR 3.00, 95% CI 1.06-8.4, P = 0.038), LPFS (HR 3.08, 95% CI 1.27-7.50, P = 0.013), and DMFS (HR 1.84, 95% CI 0.99-3.42, P = 0.054). Taking OS as the main observation point, the best cut-off point of NTR was 0.95. Kaplan-Meier results showed that the 3-year OS (97.0% vs 85.4%, χ2 = 11.25, P = 0.001), 3-year LPFS (91.3% vs 82.1%, χ2 = 4.035, P = 0.045), and 3-year DMFS (92.3% vs 87.9%, χ2 = 4.576, P = 0.032) of patients with NTR < 0.95 were higher than those with NTR > 0.95. CONCLUSIONS High NTR before treatment indicates a poor prognosis for patients with nasopharyngeal carcinoma. This can serve as a reference value for the reasonable treatment and prognosis monitoring of such patients.
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Affiliation(s)
- Yunlong Lou
- Department of Nuclear Medicine, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences Meizhou, Meizhou, China
| | - Dandan Chen
- Department of Nuclear Medicine, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences Meizhou, Meizhou, China
| | - Zheng Lin
- Department of Nuclear Medicine, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences Meizhou, Meizhou, China
| | - Jianda Sun
- Department of Radiotherapy, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences Meizhou, Meizhou, China
| | - Li Song
- Department of Nuclear Medicine, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences Meizhou, Meizhou, China
| | - Wenzhong Chen
- Department of Nuclear Medicine, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences Meizhou, Meizhou, China
| | - Ming Zhang
- Department of Nuclear Medicine, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences Meizhou, Meizhou, China
| | - Yibiao Chen
- Department of Radiotherapy, Meizhou People's Hospital, Meizhou Academy of Medical Sciences Meizhou, Meizhou, China.
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10
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Wong WC. Focal Nasopharyngeal Activity Detected on [ 18F]FDG PET/CT: Clinical Implications and Comparison of Metabolic Parameters for Prediction of Malignancy. Nucl Med Mol Imaging 2022; 56:299-305. [PMID: 36425278 PMCID: PMC9679055 DOI: 10.1007/s13139-022-00771-5] [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: 05/16/2022] [Revised: 08/10/2022] [Accepted: 08/20/2022] [Indexed: 10/14/2022] Open
Abstract
Purpose We aimed to investigate the incidence and clinical significance of incidental focal nasopharyngeal uptake on [18F]FDG PET/CT and to evaluate the diagnostic performance of various metabolic parameters to differentiate between benign and malignant nasopharyngeal lesions. Methods A total of 63 consecutive patients with incidental focal nasopharyngeal uptake on [18F]FDG PET/CT and subsequent nasopharyngeal biopsy were retrospectively enrolled. In addition, baseline pretherapeutic [18F]FDG PET/CT images of 59 patients with newly diagnosed pathologically proven nasopharyngeal carcinoma (NPC) were reviewed. Maximum standardized uptake value (SUVmax), mean SUV (SUVmean), nasopharynx-to-palatine tonsil ratio (NPR), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the nasopharyngeal lesions were determined. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the metabolic parameters. Results Incidental focal nasopharyngeal uptake in two patients (3.2%, 2/63) was pathologically confirmed to be NPC. All the metabolic parameters (SUVmax, SUVmean, NPR, MTV, and TLG) demonstrated significantly greater values in patients with NPC compared with patients with benign or physiological nasopharyngeal uptake (p < 0.001). Among the metabolic parameters, NPR demonstrated the greatest area under the curve of 0.992 (p < 0.05), with a sensitivity of 96.7% and a specificity of 93.4% when a cut-off of 1.1 was used. Similar results were seen in nasopharyngeal lesions without morphological abnormality. Conclusion NPC is an infrequent but important cause of incidental focal nasopharyngeal uptake on [18F]FDG PET/CT. Metabolic parameters were shown to be useful to differentiate between benign and malignant nasopharyngeal lesions, and NPR showed the best diagnostic performance.
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Affiliation(s)
- Wai-Chung Wong
- Nuclear Medicine Unit, Department of Radiology and Imaging, Queen Elizabeth Hospital, 30 Gascoigne Road, Kowloon, Hong Kong
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11
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Zschaeck S, Weingärtner J, Lombardo E, Marschner S, Hajiyianni M, Beck M, Zips D, Li Y, Lin Q, Amthauer H, Troost EGC, van den Hoff J, Budach V, Kotzerke J, Ferentinos K, Karagiannis E, Kaul D, Gregoire V, Holzgreve A, Albert NL, Nikulin P, Bachmann M, Kopka K, Krause M, Baumann M, Kazmierska J, Cegla P, Cholewinski W, Strouthos I, Zöphel K, Majchrzak E, Landry G, Belka C, Stromberger C, Hofheinz F. 18F-Fluorodeoxyglucose Positron Emission Tomography of Head and Neck Cancer: Location and HPV Specific Parameters for Potential Treatment Individualization. Front Oncol 2022; 12:870319. [PMID: 35756665 PMCID: PMC9213669 DOI: 10.3389/fonc.2022.870319] [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: 02/06/2022] [Accepted: 04/29/2022] [Indexed: 11/17/2022] Open
Abstract
Purpose 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is utilized for staging and treatment planning of head and neck squamous cell carcinomas (HNSCC). Some older publications on the prognostic relevance showed inconclusive results, most probably due to small study sizes. This study evaluates the prognostic and potentially predictive value of FDG-PET in a large multi-center analysis. Methods Original analysis of individual FDG-PET and patient data from 16 international centers (8 institutional datasets, 8 public repositories) with 1104 patients. All patients received curative intent radiotherapy/chemoradiation (CRT) and pre-treatment FDG-PET imaging. Primary tumors were semi-automatically delineated for calculation of SUVmax, SUVmean, metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Cox regression analyses were performed for event-free survival (EFS), overall survival (OS), loco-regional control (LRC) and freedom from distant metastases (FFDM). Results FDG-PET parameters were associated with patient outcome in the whole cohort regarding clinical endpoints (EFS, OS, LRC, FFDM), in uni- and multivariate Cox regression analyses. Several previously published cut-off values were successfully validated. Subgroup analyses identified tumor- and human papillomavirus (HPV) specific parameters. In HPV positive oropharynx cancer (OPC) SUVmax was well suited to identify patients with excellent LRC for organ preservation. Patients with SUVmax of 14 or less were unlikely to develop loco-regional recurrence after definitive CRT. In contrast FDG PET parameters deliver only limited prognostic information in laryngeal cancer. Conclusion FDG-PET parameters bear considerable prognostic value in HNSCC and potential predictive value in subgroups of patients, especially regarding treatment de-intensification and organ-preservation. The potential predictive value needs further validation in appropriate control groups. Further research on advanced imaging approaches including radiomics or artificial intelligence methods should implement the identified cut-off values as benchmark routine imaging parameters.
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Affiliation(s)
- Sebastian Zschaeck
- Department of Radiation Oncology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.,Berlin Institute of Health (BIH), Berlin, Germany.,Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ) Heidelberg, Germany, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany
| | - Julian Weingärtner
- Department of Radiation Oncology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.,Berlin Institute of Health (BIH), Berlin, Germany
| | - Elia Lombardo
- Department of Radiation Oncology, University Hospital, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Sebastian Marschner
- Department of Radiation Oncology, University Hospital, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Marina Hajiyianni
- Department of Radiation Oncology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Marcus Beck
- Department of Radiation Oncology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Daniel Zips
- Department of Radiation Oncology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.,German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ) Heidelberg, Germany, Germany.,Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Yimin Li
- Department of Radiation Oncology, Xiamen Cancer Center, The First Affiliated Hospital of Xiamen University, Xiamen, China
| | - Qin Lin
- Department of Radiation Oncology, Xiamen Cancer Center, The First Affiliated Hospital of Xiamen University, Xiamen, China
| | - Holger Amthauer
- Department of Nuclear Medicine, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Esther G C Troost
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ) Heidelberg, Germany, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,Institute of Radiooncology - OncoRay, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,Helmholtz Association/Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Dresden, Germany
| | - Jörg van den Hoff
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Volker Budach
- Department of Radiation Oncology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Jörg Kotzerke
- German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ) Heidelberg, Germany, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,Department of Nuclear Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Dresden, Germany
| | - Konstantinos Ferentinos
- Department of Radiation Oncology, German Oncology Center, European University Cyprus, Limassol, Cyprus
| | - Efstratios Karagiannis
- Department of Radiation Oncology, German Oncology Center, European University Cyprus, Limassol, Cyprus
| | - David Kaul
- Department of Radiation Oncology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Vincent Gregoire
- Radiation Oncology Department, Leon Bérard Cancer Center, Lyon, France
| | - Adrien Holzgreve
- Department of Nuclear Medicine, University Hospital, Ludwig-Maximilians-University (LMU) Munich, Germany
| | - Nathalie L Albert
- Department of Nuclear Medicine, University Hospital, Ludwig-Maximilians-University (LMU) Munich, Germany
| | - Pavel Nikulin
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Michael Bachmann
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Klaus Kopka
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Mechthild Krause
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ) Heidelberg, Germany, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,Institute of Radiooncology - OncoRay, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,Helmholtz Association/Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Dresden, Germany
| | - Michael Baumann
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ) Heidelberg, Germany, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,Institute of Radiooncology - OncoRay, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Joanna Kazmierska
- Electroradiology Department, University of Medical Sciences, Poznan, Poland.,Radiotherapy Department II, Greater Poland Cancer Centre, Poznan, Poland
| | - Paulina Cegla
- Department of Nuclear Medicine, Greater Poland Cancer Centre, Poznan, Poland
| | - Witold Cholewinski
- Electroradiology Department, University of Medical Sciences, Poznan, Poland.,Department of Nuclear Medicine, Greater Poland Cancer Centre, Poznan, Poland
| | - Iosif Strouthos
- Department of Radiation Oncology, German Oncology Center, European University Cyprus, Limassol, Cyprus
| | - Klaus Zöphel
- German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ) Heidelberg, Germany, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,Department of Nuclear Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Dresden, Germany.,Department of Nuclear Medicine, Klinikum Chemnitz gGmbH, Chemnitz, Germany
| | - Ewa Majchrzak
- Department of Head and Neck Surgery, Poznan University of Medical Sciences, Greater Poland Cancer Centre, Poznan, Poland
| | - Guillaume Landry
- Department of Radiation Oncology, University Hospital, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Carmen Stromberger
- Department of Radiation Oncology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Frank Hofheinz
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
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12
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Zschaeck S, Andela SB, Amthauer H, Furth C, Rogasch JM, Beck M, Hofheinz F, Huang K. Correlation Between Quantitative PSMA PET Parameters and Clinical Risk Factors in Non-Metastatic Primary Prostate Cancer Patients. Front Oncol 2022; 12:879089. [PMID: 35530334 PMCID: PMC9074726 DOI: 10.3389/fonc.2022.879089] [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: 02/18/2022] [Accepted: 03/28/2022] [Indexed: 11/13/2022] Open
Abstract
Background PSMA PET is frequently used for staging of prostate cancer patients. Furthermore, there is increasing interest to use PET information for personalized local treatment approaches in surgery and radiotherapy, especially for focal treatment strategies. However, it is not well established which quantitative imaging parameters show highest correlation with clinical and histological tumor aggressiveness. Methods This is a retrospective analysis of 135 consecutive patients with non-metastatic prostate cancer and PSMA PET before any treatment. Clinical risk parameters (PSA values, Gleason score and D'Amico risk group) were correlated with quantitative PET parameters maximum standardized uptake value (SUVmax), mean SUV (SUVmean), tumor asphericity (ASP) and PSMA tumor volume (PSMA-TV). Results Most of the investigated imaging parameters were highly correlated with each other (correlation coefficients between 0.20 and 0.95). A low to moderate, however significant, correlation of imaging parameters with PSA values (0.19 to 0.45) and with Gleason scores (0.17 to 0.31) was observed for all parameters except ASP which did not show a significant correlation with Gleason score. Receiver operating characteristics for the detection of D'Amico high-risk patients showed poor to fair sensitivity and specificity for all investigated quantitative PSMA PET parameters (Areas under the curve (AUC) between 0.63 and 0.73). Comparison of AUC between quantitative PET parameters by DeLong test showed significant superiority of SUVmax compared to SUVmean for the detection of high-risk patients. None of the investigated imaging parameters significantly outperformed SUVmax. Conclusion Our data confirm prior publications with lower number of patients that reported moderate correlations of PSMA PET parameters with clinical risk factors. With the important limitation that Gleason scores were only biopsy-derived in this study, there is no indication that the investigated additional parameters deliver superior information compared to SUVmax.
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Affiliation(s)
- Sebastian Zschaeck
- Department of Radiation Oncology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- BIH Charité Clinician Scientist Program, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, Berlin, Germany
| | - Stephanie Bela Andela
- Department of Radiation Oncology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Holger Amthauer
- Department of Nuclear Medicine, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Christian Furth
- Department of Nuclear Medicine, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Julian M. Rogasch
- BIH Charité Clinician Scientist Program, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, Berlin, Germany
- Department of Nuclear Medicine, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Marcus Beck
- Department of Radiation Oncology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Frank Hofheinz
- PET Center, Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Kai Huang
- Department of Nuclear Medicine, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
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13
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Rogasch JMM, Hofheinz F, van Heek L, Voltin CA, Boellaard R, Kobe C. Influences on PET Quantification and Interpretation. Diagnostics (Basel) 2022; 12:451. [PMID: 35204542 PMCID: PMC8871060 DOI: 10.3390/diagnostics12020451] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 01/06/2022] [Accepted: 02/08/2022] [Indexed: 01/21/2023] Open
Abstract
Various factors have been identified that influence quantitative accuracy and image interpretation in positron emission tomography (PET). Through the continuous introduction of new PET technology-both imaging hardware and reconstruction software-into clinical care, we now find ourselves in a transition period in which traditional and new technologies coexist. The effects on the clinical value of PET imaging and its interpretation in routine clinical practice require careful reevaluation. In this review, we provide a comprehensive summary of important factors influencing quantification and interpretation with a focus on recent developments in PET technology. Finally, we discuss the relationship between quantitative accuracy and subjective image interpretation.
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Affiliation(s)
- Julian M. M. Rogasch
- Department of Nuclear Medicine, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 13353 Berlin, Germany;
- Berlin Institute of Health at Charité, Universitätsmedizin Berlin, 10178 Berlin, Germany
| | - Frank Hofheinz
- Institute of Radiopharmaceutical Cancer Research, Helmholtz Center Dresden-Rossendorf, 01328 Dresden, Germany;
| | - Lutz van Heek
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany; (L.v.H.); (C.-A.V.)
| | - Conrad-Amadeus Voltin
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany; (L.v.H.); (C.-A.V.)
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam (CCA), Amsterdam University Medical Center, Free University Amsterdam, 1081 HV Amsterdam, The Netherlands;
| | - Carsten Kobe
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany; (L.v.H.); (C.-A.V.)
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14
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Huang H, Li S, Tang Q, Zhu G. Metabolic Reprogramming and Immune Evasion in Nasopharyngeal Carcinoma. Front Immunol 2021; 12:680955. [PMID: 34566954 PMCID: PMC8458828 DOI: 10.3389/fimmu.2021.680955] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 08/25/2021] [Indexed: 01/31/2023] Open
Abstract
Nasopharyngeal carcinoma (NPC) is a malignant tumor of the nasopharynx mainly characterized by geographic distribution and EBV infection. Metabolic reprogramming, one of the cancer hallmarks, has been frequently reported in NPCs to adapt to internal energy demands and external environmental pressures. Inevitably, the metabolic reprogramming within the tumor cell will lead to a decreased pH value and diverse nutritional supplements in the tumor-infiltrating micro-environment incorporating immune cells, fibroblasts, and endothelial cells. Accumulated evidence indicates that metabolic reprogramming derived from NPC cells may facilitate cancer progression and immunosuppression by cell-cell communications with their surrounding immune cells. This review presents the dysregulated metabolism processes, including glucose, fatty acid, amino acid, nucleotide metabolism, and their mutual interactions in NPC. Moreover, the potential connections between reprogrammed metabolism, tumor immunity, and associated therapy would be discussed in this review. Accordingly, the development of targets on the interactions between metabolic reprogramming and immune cells may provide assistances to overcome the current treatment resistance in NPC patients.
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Affiliation(s)
- Huimei Huang
- Department of Otolaryngology-Head and Neck Surgery, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Shisheng Li
- Department of Otolaryngology-Head and Neck Surgery, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Qinglai Tang
- Department of Otolaryngology-Head and Neck Surgery, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Gangcai Zhu
- Department of Otolaryngology-Head and Neck Surgery, The Second Xiangya Hospital, Central South University, Changsha, China
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15
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Ben-Ami T, Kontny U, Surun A, Brecht IB, Almaraz RL, Dragomir M, Pourtsidis A, Casanova M, Fresneau B, Bisogno G, Schneider DT, Reguerre Y, Bien E, Stachowicz-Stencel T, Österlundh G, Wygoda M, Janssens GO, Zsiros J, Jehanno N, Brisse HJ, Gandola L, Christiansen H, Claude L, Ferrari A, Rodriguez-Galindo C, Orbach D. Nasopharyngeal carcinoma in children and adolescents: The EXPeRT/PARTNER diagnostic and therapeutic recommendations. Pediatr Blood Cancer 2021; 68 Suppl 4:e29018. [PMID: 33844410 DOI: 10.1002/pbc.29018] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 03/02/2021] [Accepted: 03/03/2021] [Indexed: 01/25/2023]
Abstract
Nasopharyngeal carcinoma (NPC) is a rare pediatric tumor. Collaborative studies performed over the last decades showed improved results compared to historical data, but standardized guidelines for diagnosis and management of pediatric NPC are still unavailable. This study presents a European consensus guideline for the diagnosis and treatment of pediatric NPC developed by the European Cooperative Study Group for Pediatric Rare Tumors (EXPeRT). Main recommendations include induction chemotherapy with cisplatin and 5-flurouracil, concomitant chemoradiotherapy in advanced disease, and to consider maintenance treatment with interferon beta (IFN-β) for selected high-risk patients. Dose adjustments of radiotherapy based on response to induction chemotherapy may decrease the rates of long-term treatment-related complications that affect most of the survivors.
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Affiliation(s)
- Tal Ben-Ami
- Pediatric Hematology-Oncology Unit, Kaplan Medical Center, Faculty of Medicine, Hebrew University of Jerusalem, Rehovot, Israel
| | - Udo Kontny
- Division of Pediatric Hematology Oncology and Stem Cell Transplantation, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Aurore Surun
- SIREDO Oncology Center (Care, Innovation and Research for Children and AYA with Cancer), PSL Research University, Institut Curie, Paris, France
| | - Ines B Brecht
- Pediatric Hematology and Oncology, University Children's Hospital, Eberhard-Karls-Universitaet, Tuebingen, Germany
| | - Ricardo López Almaraz
- Pediatric Hematology and Oncology Unit, Hospital Universitario de Cruces, Barakaldo-Bizkaia, Spain
| | - Monica Dragomir
- Department of Pediatric Oncology, Oncology Institute "Prof. Dr. Al. Trestioreanu,", Bucharest, Romania
| | - Apostolos Pourtsidis
- Pediatric and Adolescents Oncology Clinic Children's Hospital MITERA, Athens, Greece
| | - Michela Casanova
- Pediatric Oncology Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Brice Fresneau
- Gustave Roussy, Department of Pediatric Oncology, Université Paris-Saclay, Villejuif, France.,Paris-Saclay University, Paris-Sud University, Paris, France
| | - Gianni Bisogno
- Hematology Oncology Division, Department of Woman's and Child's Health, University of Padova, Padova, Italy
| | | | - Yves Reguerre
- Department of Pediatric Hematology and Oncology, Félix Guyon University Hospital, St. Denis, Réunion Island, France
| | - Ewa Bien
- Department of Pediatrics, Hematology and Oncology, Medical University of Gdansk, Gdansk, Poland
| | | | - Gustaf Österlundh
- Department of Pediatric Hematology and Oncology, The Queen Silvia Children's Hospital, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Marc Wygoda
- Department of Oncology, Hadassah Hebrew University Medical Center, Jerusalem, Israel
| | - Geert O Janssens
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.,Princess Maxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - József Zsiros
- Princess Maxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Nina Jehanno
- Department of Nuclear Medicine, Institut Curie, Paris, France
| | - Herve J Brisse
- Department of Radiology, Institut Curie, Paris University, Paris, France
| | - Lorenza Gandola
- Pediatric Radiotherapy Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Hans Christiansen
- Department of Radiation Oncology, Hannover Medical School, Hanover, Germany
| | - Line Claude
- Department of Radiation Oncology, Léon Bérard Center, Lyon, France
| | - Andrea Ferrari
- Pediatric Oncology Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | | | - Daniel Orbach
- SIREDO Oncology Center (Care, Innovation and Research for Children and AYA with Cancer), PSL Research University, Institut Curie, Paris, France
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16
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Rogasch JMM, Furth C, Bluemel S, Radojewski P, Amthauer H, Hofheinz F. Asphericity of tumor FDG uptake in non-small cell lung cancer: reproducibility and implications for harmonization in multicenter studies. EJNMMI Res 2020; 10:134. [PMID: 33140213 PMCID: PMC7606415 DOI: 10.1186/s13550-020-00725-y] [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: 09/16/2020] [Accepted: 10/21/2020] [Indexed: 11/15/2022] Open
Abstract
Background Asphericity (ASP) of the primary tumor’s metabolic tumor volume (MTV) in FDG-PET/CT is independently predictive for survival in patients with non-small cell lung cancer (NSCLC). However, comparability between PET systems may be limited. Therefore, reproducibility of ASP was evaluated at varying image reconstruction and acquisition times to assess feasibility of ASP assessment in multicenter studies.
Methods This is a retrospective study of 50 patients with NSCLC (female 20; median age 69 years) undergoing pretherapeutic FDG-PET/CT (median 3.7 MBq/kg; 180 s/bed position). Reconstruction used OSEM with TOF4/16 (iterations 4; subsets 16; in-plane filter 2.0, 6.4 or 9.5 mm), TOF4/8 (4 it; 8 ss; filter 2.0/6.0/9.5 mm), PSF + TOF2/17 (2 it; 17 ss; filter 2.0/7.0/10.0 mm) or Bayesian-penalized likelihood (Q.Clear; beta, 600/1750/4000). Resulting reconstructed spatial resolution (FWHM) was determined from hot sphere inserts of a NEMA IEC phantom. Data with approx. 5-mm FWHM were retrospectively smoothed to achieve 7-mm FWHM. List mode data were rebinned for acquisition times of 120/90/60 s. Threshold-based delineation of primary tumor MTV was followed by evaluation of relative ASP/SUVmax/MTV differences between datasets and resulting proportions of discordantly classified cases.
Results Reconstructed resolution for narrow/medium/wide in-plane filter (or low/medium/high beta) was approx. 5/7/9 mm FWHM. Comparing different pairs of reconstructed resolution between TOF4/8, PSF + TOF2/17, Q.Clear and the reference algorithm TOF4/16, ASP differences was lowest at FWHM of 7 versus 7 mm. Proportions of discordant cases (ASP > 19.5% vs. ≤ 19.5%) were also lowest at 7 mm (TOF4/8, 2%; PSF + TOF2/17, 4%; Q.Clear, 10%). Smoothing of 5-mm data to 7-mm FWHM significantly reduced discordant cases (TOF4/8, 38% reduced to 2%; PSF + TOF2/17, 12% to 4%; Q.Clear, 10% to 6%), resulting in proportions comparable to original 7-mm data. Shorter acquisition time only increased proportions of discordant cases at < 90 s. Conclusions ASP differences were mainly determined by reconstructed spatial resolution, and multicenter studies should aim at comparable FWHM (e.g., 7 mm; determined by in-plane filter width). This reduces discordant cases (high vs. low ASP) to an acceptable proportion for TOF and PSF + TOF of < 5% (Q.Clear: 10%). Data with better resolution (i.e., lower FWHM) could be retrospectively smoothed to the desired FWHM, resulting in a comparable number of discordant cases.
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Affiliation(s)
- Julian M M Rogasch
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353, Berlin, Germany.
| | - Christian Furth
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Stephanie Bluemel
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Piotr Radojewski
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Holger Amthauer
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Frank Hofheinz
- Institute for Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
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