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Kifjak D, Hochmair M, Sobotka D, Haug AR, Ambros R, Prayer F, Heidinger BH, Roehrich S, Milos RI, Wadsak W, Fuereder T, Krenbek D, Fazekas A, Meilinger M, Mayerhoefer ME, Langs G, Herold C, Prosch H, Beer L. Metabolic tumor volume and sites of organ involvement predict outcome in NSCLC immune-checkpoint inhibitor therapy. Eur J Radiol 2024; 170:111198. [PMID: 37992608 DOI: 10.1016/j.ejrad.2023.111198] [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: 08/20/2023] [Revised: 10/13/2023] [Accepted: 11/13/2023] [Indexed: 11/24/2023]
Abstract
PURPOSE The purpose of this study was to assess the ability of pretreatment PET parameters and peripheral blood biomarkers to predict progression-free survival (PFS) and overall survival (OS) in NSCLC patients treated with ICIT. METHODS We prospectively included 87 patients in this study who underwent pre-treatment [18F]-FDG PET/CT. Organ-specific and total metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured using a semiautomatic software. Sites of organ involvement (SOI) were assessed by PET/CT. The log-rank test and Cox-regression analysis were used to assess associations between clinical, laboratory, and imaging parameters with PFS and OS. Time dependent ROC were calculated and model performance was evaluated in terms of its clinical utility. RESULTS MTV increased with the number of SOI and was correlated with neutrophil and lymphocyte cell count (Spearman's rho = 0.27 or 0.32; p =.02 or 0.003; respectively). Even after adjustment for known risk factors, such as PD-1 expression and neutrophil cell count, the MTV and the number of SOI were independent risk factors for progression (per 100 cm3; adjusted hazard ratio [aHR]: 1.13; 95% confidence interval [95%CI]: 1.01-1.28; p =.04; single SOI vs. ≥ 4 SOI: aHR: 2.26, 95%CI: 1.04-4.94; p =.04). MTV and the number of SOI were independent risk factors for overall survival (per 100 cm3 aHR: 1.11, 95%CI: 1.01-1.23; p =.03; single SOI vs. ≥ 4 SOI: aHR: 4.54, 95%CI: 1.64-12.58; p =.04). The combination of MTV and the number of SOI improved the risk stratification for PFS and OS (log-rank test p <.001; C-index: 0.64 and 0.67). CONCLUSION The MTV and the number of SOI are simple imaging markers that provide complementary information to facilitate risk stratification in NSCLC patients scheduled for ICIT.
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Affiliation(s)
- Daria Kifjak
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Department of Radiology, UMass Memorial Medical Center and University of Massachusetts Chan Medical School, Worcester, MA, USA; Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria
| | - Maximilian Hochmair
- Department of Respiratory and Critical Care Medicine, Karl Landsteiner Institute of Lung Research and Pulmonary Oncology, Klinik Floridsdorf, Vienna, Austria
| | - Daniel Sobotka
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Alexander R Haug
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Raphael Ambros
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Florian Prayer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Benedikt H Heidinger
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Sebastian Roehrich
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Ruxandra-Iulia Milos
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Wadsak
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Center for Biomarker Research in Medicine, CBmed, Graz, Austria
| | - Thorsten Fuereder
- Department of Internal Medicine I & Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Dagmar Krenbek
- Department of Pathology and Bacteriology, Klinik Floridsdorf, Brünner Strasse 68, 1210 Vienna, Austria
| | - Andreas Fazekas
- Department of Respiratory and Critical Care Medicine, Karl Landsteiner Institute of Lung Research and Pulmonary Oncology, Klinik Floridsdorf, Vienna, Austria
| | - Michael Meilinger
- Department of Respiratory and Critical Care Medicine, Karl Landsteiner Institute of Lung Research and Pulmonary Oncology, Klinik Floridsdorf, Vienna, Austria
| | - Marius E Mayerhoefer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Georg Langs
- Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria; Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Christian Herold
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Helmut Prosch
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria.
| | - Lucian Beer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria
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Relationship of FDG Uptake of the Reticuloendothelial System with Tumor Immune Microenvironment and Prognosis in Patients with Gastric Cancer. Life (Basel) 2023; 13:life13030771. [PMID: 36983926 PMCID: PMC10053773 DOI: 10.3390/life13030771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 02/11/2023] [Accepted: 03/10/2023] [Indexed: 03/15/2023] Open
Abstract
2-deoxy-2-[18F]fluoro-D-glucose (FDG) uptake of the reticuloendothelial system, including the bone marrow (BM) and spleen, on positron emission tomography/computed tomography (PET/CT) has been shown to be a significant prognostic factor in diverse malignancies. However, the relationship between FDG uptake of the BM and spleen and histopathological findings, including the tumor immune microenvironment, has not been fully evaluated. This study aimed to investigate the relationship of FDG uptake in the BM and spleen with histopathological findings and recurrence-free survival (RFS) in patients with gastric cancer. Seventy patients with gastric cancer who underwent pre-operative FDG PET/CT and subsequent curative surgery were retrospectively enrolled. On image analysis, the BM-to-liver uptake ratio (BLR) and spleen-to-liver uptake ratio (SLR) were measured from PET/CT images, and on immunohistochemical analysis, the densities of immune cell infiltration in the tumor tissue were graded. The BLR and SLR showed significant positive correlations with the grades of CD163 cell and CD8 cell infiltration in the tumor tissue, respectively (p < 0.05). In multivariate survival analysis, both BLR and SLR were significant predictors of RFS (p < 0.05). FDG uptake in the BM and spleen might be potential imaging biomarkers for evaluating tumor immune microenvironment conditions and predicting RFS in patients with gastric cancer.
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Zhang L, Xu C, Zhang X, Wang J, Jiang H, Chen J, Zhang H. A novel analytical approach for outcome prediction in newly diagnosed NSCLC based on [ 18F]FDG PET/CT metabolic parameters, inflammatory markers, and clinical variables. Eur Radiol 2023; 33:1757-1768. [PMID: 36222865 DOI: 10.1007/s00330-022-09150-2] [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: 05/07/2022] [Revised: 08/24/2022] [Accepted: 09/06/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVES To develop a novel analytical approach based on 18F-fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) metabolic parameters, serum inflammatory markers, and clinical variables to improve the outcome prediction in NSCLC. METHODS A total of 190 newly diagnosed NSCLC patients who underwent pretreatment [18F]FDG PET/CT were retrospectively enrolled and divided into a training cohort (n = 127) and a test cohort (n = 63). Cox regression analysis was used to investigate the predictive values of PET metabolic parameters, inflammation markers, and clinical variables for progression-free survival (PFS) and overall survival (OS). Based on the results of multivariate analysis, PET-based, clinical, and combined models were constructed. The predictive performance of different models was evaluated using time-dependent ROC curve analysis, Harrell concordance index (C-index), calibration curve, and decision curve analysis. RESULTS The combined models incorporating SULmax, MTV, NLR, and ECOG PS demonstrated significant prognostic superiority over PET-based models, clinical models, and TNM stage in terms of both PFS (C-index: 0.813 vs. 0.786 vs. 0.776 vs. 0.678, respectively) and OS (C-index: 0.856 vs. 0.792 vs. 0.781 vs. 0.674, respectively) in the training cohort. Similar results were observed in the test cohort for PFS (C-index: 0.808 vs. 0.764 vs. 0.748 vs. 0.679, respectively) and OS (C-index: 0.836 vs. 0.785 vs. 0.726 vs. 0.660, respectively) prediction. The combined model calibrated well in two cohorts. Decision curve analysis supported the clinical utility of the combined model. CONCLUSIONS We reported a novel analytical approach combining PET metabolic information with inflammatory biomarker and clinical characteristics, which could significantly improve outcome prediction in newly diagnosed NSCLC. KEY POINTS • The nomogram incorporating SULmax, MTV, NLR, and ECOG PS outperformed the TNM stage for outcome prediction in patients with newly diagnosed NSCLC. • The established nomogram could provide refined prognostic stratification.
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Affiliation(s)
- Lixia Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310006, Zhejiang, China
| | - Caiyun Xu
- Department of Nuclear Medicine, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310006, Zhejiang, China
| | - Xiaohui Zhang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China. .,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009, Zhejiang, China. .,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, Zhejiang, China.
| | - Jing Wang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China. .,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009, Zhejiang, China. .,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, Zhejiang, China.
| | - Han Jiang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009, Zhejiang, China.,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, Zhejiang, China
| | - Jinyan Chen
- Department of Nuclear Medicine, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310006, Zhejiang, China
| | - Hong Zhang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China. .,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009, Zhejiang, China. .,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, Zhejiang, China.
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Ling T, Zhang L, Peng R, Yue C, Huang L. Prognostic value of 18F-FDG PET/CT in patients with advanced or metastatic non-small-cell lung cancer treated with immune checkpoint inhibitors: A systematic review and meta-analysis. Front Immunol 2022; 13:1014063. [PMID: 36466905 PMCID: PMC9713836 DOI: 10.3389/fimmu.2022.1014063] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 10/20/2022] [Indexed: 08/30/2023] Open
Abstract
PURPOSE This study aimed to investigate the value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in predicting early immunotherapy response of immune checkpoint inhibitors (ICIs) in patients with advanced or metastatic non-small-cell lung cancer (NSCLC). METHODS A comprehensive search of PubMed, Web of science, Embase and the Cochrane library was performed to examine the prognostic value of 18F-FDG PET/CT in predicting early immunotherapy response of ICIs in patients with NSCLC. The main outcomes for evaluation were overall survival (OS) and progression-free survival (PFS). Detailed data from each study were extracted and analyzed using STATA 14.0 software. RESULTS 13 eligible articles were included in this systematic review. Compared to baseline 18F-FDG PET/CT imaging, the pooled hazard ratios (HR) of maximum and mean standardized uptake values SUVmax, SUVmean, MTV and TLG for OS were 0.88 (95% CI: 0.69-1.12), 0.79 (95% CI: 0.50-1.27), 2.10 (95% CI: 1.57-2.82) and 1.58 (95% CI: 1.03-2.44), respectively. The pooled HR of SUVmax, SUVmean, MTV and TLG for PFS were 1.06 (95% CI: 0.68-1.65), 0.66 (95% CI: 0.48-0.90), 1.50 (95% CI: 1.26-1.79), 1.27 (95% CI: 0.92-1.77), respectively. Subgroup analysis showed that high MTV group had shorter OS than low MTV group in both first line group (HR: 1.97, 95% CI: 1.39-2.79) and undefined line group (HR: 2.11, 95% CI: 1.61-2.77). High MTV group also showed a shorter PFS in first line group (HR: 1.85, 95% CI: 1.28-2.68), and low TLG group had a longer OS in undefined group (HR: 1.37, 95% CI: 1.00-1.86). No significant differences were in other subgroup analysis. CONCLUSION Baseline MTV and TLG may have predictive value and should be prospectively studied in clinical trials. Baseline SUVmax and SUVmean may not be appropriate prognostic markers in advanced or metastatic NSCLC patients treated with ICIs. SYSTEMATIC REVIEW REGISTRATION https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=323906, identifier CRD42022323906.
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Affiliation(s)
- Tao Ling
- Department of Pharmacy, Suqian First Hospital, Suqian, China
| | - Lianghui Zhang
- Department of Oncology, Changzhou Traditional Chinese Medicine Hospital, Changzhou, China
| | - Rui Peng
- Department of General Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Chao Yue
- Department of General Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Lingli Huang
- Department of Pharmacy, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
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Prognostic Potential of Metabolic Activity on 18F-FDG Accumulation in Advanced NSCLC Receiving Combining Chemotherapy Plus PD-1 Blockade. J Immunother 2022; 45:349-357. [PMID: 35980360 DOI: 10.1097/cji.0000000000000434] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 07/06/2022] [Indexed: 11/25/2022]
Abstract
Combined chemotherapy plus programmed death-1 (PD-1) blockade is an established treatment against patients with advanced non-small cell lung cancer (NSCLC). However, a promising predictor besides programmed death ligand-1 expression remains uncertain. We examined the prognostic significance of baseline 18F-FDG-positron emission tomography for predicting first-line combined chemotherapy plus PD-1 blockade in NSCLC patients. Forty-five patients with advanced NSCLC who received 18F-FDG-positron emission tomography immediately before combined platinum-based chemotherapy with PD-1 blockade as first-line setting were eligible for this study, and assessment of maximum of standard uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) on 18F-FDG uptake was performed. The objective response rate, median progression-free survival, and overall survival were 51.2%, 206 days, and 681 days, respectively. High SUVmax, TLG, and MTV significantly correlated with age and performance status (PS), C-reactive protein (CRP), and PS, CRP, albumin, and baseline tumor size, respectively. Univariate analysis identified albumin, TLG and MTV as significant predictors of progression-free survival, and CRP, albumin, TLG and MTV as significant factors for predicting overall survival. High TLG was confirmed as an independent factor associated with poor prognosis in multivariate analysis. In particular, TLG is identified as the most powerful predictor in patients with good PS, adenocarcinoma, programmed death ligand-1≥1%, and low baseline tumor size. The tumor metabolic volume by MTV and TLG at pretreatment was clarified as a significant predictor for combined chemotherapy with PD-1 blockade, but not maximal glycolytic level by SUVmax.
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Xu W, Li H, Guo Z, Zhang L, Zhang R, Zhang L. Combined SUVmax and localized colonic wall thickening parameters to identify high-risk lesions from incidental focal colorectal 18F-FDG uptake foci. Front Oncol 2022; 12:972096. [PMID: 36033516 PMCID: PMC9416927 DOI: 10.3389/fonc.2022.972096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 07/25/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveTo evaluate the detection ability of 18F-FDG PET/CT for identifying high-risk lesions (high-risk adenomas and adenocarcinoma) from incidental focal colorectal 18F-FDG uptake foci combining maximum standard uptake value (SUVmax) and localized colonic wall thickening (CWT). The secondary objective was to investigate the factors of missed detection of high-risk adenomas by 18F-FDG PET/CT.Patients and methodsA total of 6394 patients who underwent 18F-FDG PET/CT in our hospital from August 2019 to December 2021 were retrospectively analysed, and 145 patients with incidental focal colorectal 18F-FDG uptake foci were identified. The optimal cut-off value of SUVmax for 18F-FDG PET/CT diagnosis of high-risk lesions was determined by receiver operating characteristic (ROC) curves. SUVmax and localized CWT were combined to identify high-risk lesions from incidental focal colorectal 18F-FDG uptake foci. The characteristics of incidental adenomas detected and high-risk adenomas missed by 18F-FDG PET/CT were compared.ResultsOf the 6394 patients, 145 patients were found to have incidental focal colorectal FDG uptake foci (2.3%), and 44 patients underwent colonoscopy and pathological examination at the same time. In fact, 45 lesions, including 12 low-risk lesions and 33 high-risk lesions (22 high-risk adenomas, 11 adenocarcinoma), were found by colonoscopy. The area under the ROC curve of SUVmax for low-risk lesions and high-risk lesions was 0.737, and the optimal cut-off value was 6.45 (with a sensitivity of 87.9% and specificity of 58.3%). When SUVmax ≥6.45, the combination of localized CWT parameters has little influence on the sensitivity and specificity of detection; when SUVmax <6.45, the combination of localized CWT parameters can improve the specificity of detection of high-risk lesions, but the sensitivity has little change. In addition, the size of high-risk adenomas discovered incidentally by 18F-FDG PET/CT was larger than that of high-risk adenomas missed, but there was no significant difference in lesion location, pathological type or intraepithelial neoplasia between the two groups.ConclusionsThe combination of SUVmax and localized CWT parameters of 18F-FDG PET/CT helped identify high-risk lesions from incidental focal colorectal 18F-FDG uptake foci, especially for lesions with SUVmax <6.45. Lesion size may be the only factor in 18F-FDG PET/CT missing high-risk adenomas.
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Affiliation(s)
- Wenmin Xu
- Department of Endoscopy, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Hansen Li
- Department of Endoscopy, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Ziqian Guo
- Department of Endoscopy, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Linqi Zhang
- Department of Nuclear Medicine, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Rusen Zhang
- Department of Nuclear Medicine, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Long Zhang
- Department of Endoscopy, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
- *Correspondence: Long Zhang,
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