Dataset Information

Comparison of FDG PET/CT and Bone Marrow Biopsy Results in Patients with Diffuse Large B Cell Lymphoma with Subgroup Analysis of PET Radiomics.

ABSTRACT: Whether FDG PET/CT can replace bone marrow biopsy (BMBx) is undecided in patients with diffuse large B cell lymphoma (DLBCL). We compared the visual PET findings and PET radiomic features, with BMBx results. A total of 328 patients were included; 269 (82%) were PET-negative and 59 (18%) were PET-positive for bone lesions on visual assessment. A fair degree of agreement was present between PET and BMBx findings (ĸ = 0.362, p < 0.001). Bone involvement on PET/CT lead to stage IV in 12 patients, despite no other evidence of extranodal lesion. Of 35 discordant PET-positive and BMBx-negative cases, 22 (63%) had discrete bone uptake on PET/CT. A total of 144 patients were eligible for radiomic analysis, and two grey-level zone-length matrix derived parameters obtained from the iliac crests showed a trend for higher values in the BMBx-positive group compared to the BMBx-negative group (mean 436.6 ± 449.0 versus 227.2 ± 137.8, unadjusted p = 0.037 for high grey-level zone emphasis; mean 308.8 ± 394.4 versus 135.7 ± 97.2, unadjusted p = 0.048 for short-zone high grey-level emphasis), but statistical significance was not found after multiple comparison correction. Visual FDG PET/CT assessment and BMBx results were discordant in 17% of patients with newly diagnosed DLBCL, and the two tests are complementary in the evaluation of bone involvement.

SUBMITTER: Han EJ

PROVIDER: S-EPMC8774933 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Comparison of FDG PET/CT and Bone Marrow Biopsy Results in Patients with Diffuse Large B Cell Lymphoma with Subgroup Analysis of PET Radiomics.

Han Eun Ji EJ O Joo Hyun JH Yoon Hyukjin H Ha Seunggyun S Yoo Ie Ryung IR Min Jae Won JW Choi Joon-Il JI Choi Byung-Ock BO Park Gyeongsin G Lee Han Hee HH Jeon Young-Woo YW Min Gi-June GJ Cho Seok-Goo SG

Diagnostics (Basel, Switzerland) 20220117 1

Whether FDG PET/CT can replace bone marrow biopsy (BMBx) is undecided in patients with diffuse large B cell lymphoma (DLBCL). We compared the visual PET findings and PET radiomic features, with BMBx results. A total of 328 patients were included; 269 (82%) were PET-negative and 59 (18%) were PET-positive for bone lesions on visual assessment. A fair degree of agreement was present between PET and BMBx findings (ĸ = 0.362, <i>p</i> < 0.001). Bone involvement on PET/CT lead to stage IV in 12 patie ...[more]

PMID: 35054389

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Project description:BackgroundDiffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma in adults. Standard treatment includes chemoimmunotherapy with R-CHOP or similar regimens. Despite treatment advancements, many patients with DLBCL experience refractory disease or relapse. While baseline 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) parameters have shown promise in predicting survival, they may not fully capture lesion heterogeneity. This study aimed to assess the prognostic value of baseline 18F-FDG PET radiomics features in comparison with clinical factors and metabolic parameters for assessing 2-year progression-free survival (PFS) and 5-year overall survival (OS) in patients with DLBCL.ResultsA total of 201 patients with DLBCL were enrolled in this study, and 1328 radiomics features were extracted. The radiomics signatures, clinical factors, and metabolic parameters showed significant prognostic value for individualized prognosis prediction in patients with DLBCL. Radiomics signatures showed the lowest Akaike information criterion (AIC) value and highest Harrell's concordance index (C-index) value in comparison with clinical factors and metabolic parameters for both PFS (AIC: 571.688 vs. 596.040 vs. 576.481; C-index: 0.732 vs. 0.658 vs. 0.702, respectively) and OS (AIC: 339.843 vs. 363.671 vs. 358.412; C-index: 0.759 vs. 0.667 vs. 0.659, respectively). Statistically significant differences were observed in the area under the curve (AUC) values between the radiomics signatures and clinical factors for both PFS (AUC: 0.768 vs. 0.681, P = 0.017) and OS (AUC: 0.767 vs. 0.667, P = 0.023). For OS, the AUC of the radiomics signatures were significantly higher than those of metabolic parameters (AUC: 0.767 vs. 0.688, P = 0.007). However, for PFS, no significant difference was observed between the radiomics signatures and metabolic parameters (AUC: 0.768 vs. 0.756, P = 0.654). The combined model and the best-performing individual model (radiomics signatures) alone showed no significant difference for both PFS (AUC: 0.784 vs. 0.768, P = 0.163) or OS (AUC: 0.772 vs. 0.767, P = 0.403).ConclusionsRadiomics signatures derived from PET images showed the high predictive power for progression in patients with DLBCL. The combination of radiomics signatures, clinical factors, and metabolic parameters may not significantly improve predictive value beyond that of radiomics signatures alone.

Project description:The combination of visual assessment of whole body [18F]FDG PET images and evaluation of bone marrow samples by Multiparameter Flow Cytometry (MFC) or Next-Generation Sequencing (NGS) is currently the most common clinical practice for the detection of Measurable Residual Disease (MRD) in Multiple Myeloma (MM) patients. In this study, radiomic features extracted from the bone marrow biopsy locations are analyzed and compared to those extracted from the whole bone marrow in order to study the representativeness of these biopsy locations in the image-based MRD assessment. Whole body [18F]FDG PET of 39 patients with newly diagnosed MM were included in the database, and visually evaluated by experts in nuclear medicine. A methodology for the segmentation of biopsy sites from PET images, including sternum and posterior iliac crest, and their subsequent quantification is proposed. First, starting from the bone marrow segmentation, a segmentation of the biopsy sites is performed. Then, segmentations are quantified extracting SUV metrics and radiomic features from the [18F]FDG PET images and are evaluated by Mann-Whitney U-tests as valuable features differentiating PET+/PET- and MFC+ /MFC- groups. Moreover, correlation between whole bone marrow and biopsy sites is studied by Spearman ρ rank. Classification performance of the radiomics features is evaluated applying seven machine learning algorithms. Statistical analyses reveal that some images features are significant in PET+/PET- differentiation, such as SUVmax, Gray Level Non-Uniformity or Entropy, especially with a balanced database where 16 of the features show a p value < 0.001. Correlation analyses between whole bone marrow and biopsy sites results in significant and acceptable coefficients, with 11 of the variables reaching a correlation coefficient greater than 0.7, with a maximum of 0.853. Machine learning algorithms demonstrate high performances in PET+/PET- classification reaching a maximum AUC of 0.974, but not for MFC+/MFC- classification. The results demonstrate the representativeness of sample sites as well as the effectiveness of extracted features (SUV metrics and radiomic features) from the [18F]FDG PET images in MRD assessment in MM patients.

Dataset Information

Comparison of FDG PET/CT and Bone Marrow Biopsy Results in Patients with Diffuse Large B Cell Lymphoma with Subgroup Analysis of PET Radiomics.

Publications

Comparison of FDG PET/CT and Bone Marrow Biopsy Results in Patients with Diffuse Large B Cell Lymphoma with Subgroup Analysis of PET Radiomics.

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