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Lue KH, Chen YH, Chu SC, Lin CB, Wang TF, Liu SH. Prognostic value of combining clinical factors, 18F-FDG PET-based intensity, volumetric features, and deep learning predictor in patients with EGFR-mutated lung adenocarcinoma undergoing targeted therapies: a cross-scanner and temporal validation study. Ann Nucl Med 2024; 38:647-658. [PMID: 38704786 DOI: 10.1007/s12149-024-01936-2] [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: 03/07/2024] [Accepted: 04/22/2024] [Indexed: 05/07/2024]
Abstract
OBJECTIVE To investigate the prognostic value of 18F-FDG PET-based intensity, volumetric features, and deep learning (DL) across different generations of PET scanners in patients with epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma receiving tyrosine kinase inhibitor (TKI) treatment. METHODS We retrospectively analyzed the pre-treatment 18F-FDG PET of 217 patients with advanced-stage lung adenocarcinoma and actionable EGFR mutations who received TKI as first-line treatment. Patients were separated into analog (n = 166) and digital (n = 51) PET cohorts. 18F-FDG PET-derived intensity, volumetric features, ResNet-50 DL of the primary tumor, and clinical variables were used to predict progression-free survival (PFS). Independent prognosticators were used to develop prediction model. Model was developed and validated in the analog and digital PET cohorts, respectively. RESULTS In the analog PET cohort, female sex, stage IVB status, exon 19 deletion, SUVmax, metabolic tumor volume, and positive DL prediction independently predicted PFS. The model devised from these six prognosticators significantly predicted PFS in the analog (HR = 1.319, p < 0.001) and digital PET cohorts (HR = 1.284, p = 0.001). Our model provided incremental prognostic value to staging status (c-indices = 0.738 vs. 0.558 and 0.662 vs. 0.598 in the analog and digital PET cohorts, respectively). Our model also demonstrated a significant prognostic value for overall survival (HR = 1.198, p < 0.001, c-index = 0.708 and HR = 1.256, p = 0.021, c-index = 0.664 in the analog and digital PET cohorts, respectively). CONCLUSIONS Combining 18F-FDG PET-based intensity, volumetric features, and DL with clinical variables may improve the survival stratification in patients with advanced EGFR-mutated lung adenocarcinoma receiving TKI treatment. Implementing the prediction model across different generations of PET scanners may be feasible and facilitate tailored therapeutic strategies for these patients.
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Affiliation(s)
- Kun-Han Lue
- Department of Medical Imaging and Radiological Sciences, Tzu Chi University of Science and Technology, No.880, Sec.2, Chien-kuo Rd., Hualien, 970302, Taiwan
| | - Yu-Hung Chen
- Department of Medical Imaging and Radiological Sciences, Tzu Chi University of Science and Technology, No.880, Sec.2, Chien-kuo Rd., Hualien, 970302, Taiwan.
- Department of Nuclear Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, No.707, Sec.3, Zhongyang Rd, Hualien, 970473, Taiwan.
- School of Medicine, College of Medicine, Tzu Chi University, No.701, Sec.3, Zhongyang Rd, Hualien, 970473, Taiwan.
| | - Sung-Chao Chu
- School of Medicine, College of Medicine, Tzu Chi University, No.701, Sec.3, Zhongyang Rd, Hualien, 970473, Taiwan
- Department of Hematology and Oncology, Buddhist Tzu Chi Medical Foundation, Hualien Tzu Chi Hospital, Hualien, Taiwan
| | - Chih-Bin Lin
- School of Medicine, College of Medicine, Tzu Chi University, No.701, Sec.3, Zhongyang Rd, Hualien, 970473, Taiwan
- Department of Internal Medicine, Buddhist Tzu Chi Medical Foundation, Hualien Tzu Chi Hospital, Hualien, Taiwan
| | - Tso-Fu Wang
- School of Medicine, College of Medicine, Tzu Chi University, No.701, Sec.3, Zhongyang Rd, Hualien, 970473, Taiwan
- Department of Hematology and Oncology, Buddhist Tzu Chi Medical Foundation, Hualien Tzu Chi Hospital, Hualien, Taiwan
| | - Shu-Hsin Liu
- Department of Medical Imaging and Radiological Sciences, Tzu Chi University of Science and Technology, No.880, Sec.2, Chien-kuo Rd., Hualien, 970302, Taiwan
- Department of Nuclear Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, No.707, Sec.3, Zhongyang Rd, Hualien, 970473, Taiwan
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Jiang M, Guo X, Chen P, Zhang X, Gao Q, Zhang J, Zheng J. Prognostic significance of integrating total metabolic tumor volume and EGFR mutation status in patients with lung adenocarcinoma. PeerJ 2024; 12:e16807. [PMID: 38250731 PMCID: PMC10799611 DOI: 10.7717/peerj.16807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 12/28/2023] [Indexed: 01/23/2024] Open
Abstract
Background The objective of this study was to investigate the prognostic significance of total metabolic tumor volume (TMTV) derived from baseline 18F-2-fluoro-2-deoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT), in conjunction with epidermal growth factor receptor (EGFR) mutation status, among patients with lung adenocarcinoma (LUAD). Methods We performed a retrospective analysis on 141 patients with LUAD (74 males, 67 females, median age 67 (range 34-86)) who underwent 18F-FDG PET/CT and had their EGFR mutation status determined. Optimal cutoff points for TMTV were determined using time-dependent receiver operating characteristic curve analysis. The survival difference was compared using Cox regression analysis and Kaplan‒Meier curves. Results The EGFR mutant patients (n = 79, 56.0%) exhibited significantly higher 2-year progression-free survival (PFS) and overall survival (OS) rates compared to those with EGFR wild-type (n = 62, 44.0%), with rates of 74.2% vs 69.2% (P = 0.029) and 86.1% vs 67.7% (P = 0.009), respectively. The optimal cutoff values of TMTV were 36.42 cm3 for PFS and 37.51 cm3 for OS. Patients with high TMTV exhibited significantly inferior 2-year PFS and OS, with rates of 22.4% and 38.1%, respectively, compared to those with low TMTV, who had rates of 85.8% and 95.0% (both P < 0.001). In both the EGFR mutant and wild-type groups, patients exhibiting high TMTV demonstrated significantly inferior 2-year PFS and OS compared to those with low TMTV. In multivariate analysis, EGFR mutation status (hazard ratio, HR, 0.41, 95% confidence interval, CI [0.18-0.94], P = 0.034) and TMTV (HR 8.08, 95% CI [2.34-28.0], P < 0.001) were independent prognostic factors of OS, whereas TMTV was also an independent prognosticator of PFS (HR 2.59, 95% CI [1.30-5.13], P = 0.007). Conclusion Our study demonstrates that the integration of TMTV on baseline 18F-FDG PET/CT with EGFR mutation status improves the accuracy of prognostic evaluation for patients with LUAD.
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Affiliation(s)
- Maoqing Jiang
- Department of Radiology, Ningbo No. 2 Hospital, Ningbo, Zhejiang, China
- Department of Nuclear Medicine, Ningbo No. 2 Hospital, Ningbo, Zhejiang, China
| | - Xiuyu Guo
- Department of Radiology, Ningbo No. 2 Hospital, Ningbo, Zhejiang, China
| | - Ping Chen
- Department of Nephrology, Ningbo No. 2 Hospital, Ningbo, Zhejiang, China
| | - Xiaohui Zhang
- Department of Radiology, Ningbo No. 2 Hospital, Ningbo, Zhejiang, China
| | - Qiaoling Gao
- Department of Radiology, Ningbo No. 2 Hospital, Ningbo, Zhejiang, China
| | - Jingfeng Zhang
- Department of Radiology, Ningbo No. 2 Hospital, Ningbo, Zhejiang, China
| | - Jianjun Zheng
- Department of Radiology, Ningbo No. 2 Hospital, Ningbo, Zhejiang, China
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Sun J, Sun ZY, Zhang LJ. Editorial: Opportunities for PET imaging for the identification, staging, and monitoring of cancers. Front Oncol 2023; 13:1135928. [PMID: 36761979 PMCID: PMC9904280 DOI: 10.3389/fonc.2023.1135928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Accepted: 01/16/2023] [Indexed: 01/25/2023] Open
Affiliation(s)
| | - Zhi Yuan Sun
- *Correspondence: Long Jiang Zhang, ; Zhi Yuan Sun,
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