Optimal PET-based radiomic signature construction based on the cross-combination method for predicting the survival of patients with diffuse large B-cell lymphoma

Jiang, Chunhe; Li, Ang; Teng, Yue; Huang, XiangJun; Chen, Jianxin; Xu, Jingyan; Zhou, Zhengyang

doi:10.1007/s00259-022-05717-9

Cited by 25 publications

(19 citation statements)

References 49 publications

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“…Through rigorous multivariate analysis, we have determined that patients with a TMTV greater than 230.9 cm 3 are at greater risk for decreased overall survival and that TMTV is an independent predictor of survival. These ndings are in line with similar studies that have investigated TMTV in patients with DLBCL 15,16 . For example, Jiang et al analyzed the baseline [ 18 F]FDG PET/CT images of 383 patients with DLBCL and concluded that TMTV (HR = 1.789, P = 0.036) was a reliable predictor of overall survival in patients 15 .…”

Section: Discussionsupporting

confidence: 91%

“…These ndings are in line with similar studies that have investigated TMTV in patients with DLBCL 15,16 . For example, Jiang et al analyzed the baseline [ 18 F]FDG PET/CT images of 383 patients with DLBCL and concluded that TMTV (HR = 1.789, P = 0.036) was a reliable predictor of overall survival in patients 15 . Cottereau et al also studied TMTV in elderly DLBCL patients and discovered that TMTV (HR = 2.9, P = 0.0021) was an independent predictor of survival 16 .…”

Section: Discussionsupporting

confidence: 91%

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Prognostic value of metabolic parameters of baseline PET/CT in patients with double expression types of diffuse large B-cell lymphoma

Zhao

Teng

Jiang

et al. 2023

Preprint

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Objectives To explore the value of baseline PET/CT parameters for predicting prognosis in patients with double expression lymphoma (DEL). Methods We retrospectively analyzed the clinical and [18F]FDG PET/CT imaging data of 118 patients diagnosed with DLBCL by pathological examination at two independent medical centers from October 2015 to September 2022. We used receiver operating characteristic (ROC) curve analysis to determine the optimal threshold for the maximum standardized uptake value (SUVmax), the total metabolic tumor volume (TMTV), and the total lesion glycolysis (TLG) in predicting overall survival (OS) rate. Kaplan-Meier survival analysis, univariate and multivariate analyses were performed to predict OS rate, construct a survival prediction model, plot a calibration curve for the model, a time-dependent area under the ROC curve (tdAUC), and a decision curve analysis (DCA) curve, and calculate the C-index of the model. Results The area under the curve (AUC) of the ROC curve for TMTV was 0.705, with corresponding cutoff values of 230.9 cm3. In multivariate analysis, Eastern Cooperative Oncology Group performance status (ECOG PS) (HR=3.989, P=0.002) and TMTV (HR=4.042, P<0.008) were identified as independent predictors of OS. A combined model of ECOG PS and TMTV was found to be superior to IPI in predicting OS. Conclusions TMTV, a metabolic index, and ECOG PS, a clinical risk factor, are independent predictors of OS in patients with DEL, and their combination can provide more accurate prognostic predictions.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 91%

Prognostic value of metabolic parameters of baseline PET/CT in patients with double expression types of diffuse large B-cell lymphoma

Zhao

Teng

Jiang

et al. 2023

Preprint

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“…A total of 24 articles on lymphomas were included in this review [ 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 ], 13 of which studying diffuse large B-cell lymphoma (including 2 studies on gastro-intestinal lymphoma), 3 on follicular lymphoma, 3 on Hodgkin’s lymphoma, 2 on mantle cell lymphoma and 3 on other sub-types of lymphoma. 18F-FDG was the only tracer employed and all studies built radiomic models on baseline, pre-treatment PET images, often including clinical parameters and international prognostic indices.…”

Section: Resultsmentioning

confidence: 99%

“…Several studies evaluated the role of PET radiomics and AI analysis in blood malignancies [ 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 ]. Lymphoma radiomics on 18F-FDG PET/CT was more often assessed on patients with DLBCL, in retrospective cohorts and for prognostic purposes.…”

Section: Discussionmentioning

confidence: 99%

Radiomics in Oncological PET Imaging: A Systematic Review—Part 2, Infradiaphragmatic Cancers, Blood Malignancies, Melanoma and Musculoskeletal Cancers

et al. 2022

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The objective of this review was to summarize published radiomics studies dealing with infradiaphragmatic cancers, blood malignancies, melanoma, and musculoskeletal cancers, and assess their quality. PubMed database was searched from January 1990 to February 2022 for articles performing radiomics on PET imaging of at least 1 specified tumor type. Exclusion criteria includd: non-oncological studies; supradiaphragmatic tumors; reviews, comments, cases reports; phantom or animal studies; technical articles without a clinically oriented question; studies including <30 patients in the training cohort. The review database contained PMID, first author, year of publication, cancer type, number of patients, study design, independent validation cohort and objective. This database was completed twice by the same person; discrepant results were resolved by a third reading of the articles. A total of 162 studies met inclusion criteria; 61 (37.7%) studies included >100 patients, 13 (8.0%) were prospective and 61 (37.7%) used an independent validation set. The most represented cancers were esophagus, lymphoma, and cervical cancer (n = 24, n = 24 and n = 19 articles, respectively). Most studies focused on 18F-FDG, and prognostic and response to treatment objectives. Although radiomics and artificial intelligence are technically challenging, new contributions and guidelines help improving research quality over the years and pave the way toward personalized medicine.

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“…Model evaluation by Harrell's C-index is recommended for survival analysis 24,25 and is commonly used for radiomic survival studies. [26][27][28] Statistical analysis was performed with R software, version 4.1.0.…”

Section: Image Analysis and Radiomic Features Extractionmentioning

confidence: 99%

[¹⁸F]‐FDG PET radiomic model as prognostic biomarker in diffuse large B‐cell lymphoma

Travaini

Botta

Derenzini

et al. 2023

Hematological Oncology

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To evaluate the association between radiomic features (RFs) extracted from 18F‐FDG PET/CT (18F‐FDG‐PET) with progression‐free survival (PFS) and overall survival (OS) in diffuse large‐B‐cell lymphoma (DLBCL) patients eligible to first‐line chemotherapy. DLBCL patients who underwent 18F‐FDG‐PET prior to first‐line chemotherapy were retrospectively analyzed. RFs were extracted from the lesion showing the highest uptake. A radiomic score to predict PFS and OS was obtained by multivariable Elastic Net Cox model. Radiomic univariate model, clinical and combined clinical‐radiomic multivariable models to predict PFS and OS were obtained. 112 patients were analyzed. Median follow‐up was 34.7 months (Inter‐Quartile Range (IQR) 11.3–66.3 months) for PFS and 41.1 (IQR 18.4–68.9) for OS. Radiomic score resulted associated with PFS and OS (p < 0.001), outperforming conventional PET parameters. C‐index (95% CI) for PFS prediction were 0.67 (0.58–0.76), 0.81 (0.75–0.88) and 0.84 (0.77–0.91) for clinical, radiomic and combined clinical‐radiomic model, respectively. C‐index for OS were 0.77 (0.66–0.89), 0.84 (0.76–0.91) and 0.90 (0.81–0.98). In the Kaplan‐Meier analysis (low‐IPI vs. high‐IPI), the radiomic score was significant predictor of PFS (p < 0.001). The radiomic score was an independent prognostic biomarker of survival in DLBCL patients. The extraction of RFs from baseline 18F‐FDG‐PET might be proposed in DLBCL to stratify high‐risk versus low‐risk patients of relapse after first‐line therapy, especially in low‐IPI patients.

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Optimal PET-based radiomic signature construction based on the cross-combination method for predicting the survival of patients with diffuse large B-cell lymphoma

Cited by 25 publications

References 49 publications

Prognostic value of metabolic parameters of baseline PET/CT in patients with double expression types of diffuse large B-cell lymphoma

Prognostic value of metabolic parameters of baseline PET/CT in patients with double expression types of diffuse large B-cell lymphoma

Radiomics in Oncological PET Imaging: A Systematic Review—Part 2, Infradiaphragmatic Cancers, Blood Malignancies, Melanoma and Musculoskeletal Cancers

[¹⁸F]‐FDG PET radiomic model as prognostic biomarker in diffuse large B‐cell lymphoma

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Optimal PET-based radiomic signature construction based on the cross-combination method for predicting the survival of patients with diffuse large B-cell lymphoma

Cited by 25 publications

References 49 publications

Prognostic value of metabolic parameters of baseline PET/CT in patients with double expression types of diffuse large B-cell lymphoma

Prognostic value of metabolic parameters of baseline PET/CT in patients with double expression types of diffuse large B-cell lymphoma

Radiomics in Oncological PET Imaging: A Systematic Review—Part 2, Infradiaphragmatic Cancers, Blood Malignancies, Melanoma and Musculoskeletal Cancers

[18F]‐FDG PET radiomic model as prognostic biomarker in diffuse large B‐cell lymphoma

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[¹⁸F]‐FDG PET radiomic model as prognostic biomarker in diffuse large B‐cell lymphoma