دورية أكاديمية
أعرض في EDS

Multiblock Discriminant Analysis of Integrative 18 F-FDG-PET/CT Radiomics for Predicting Circulating Tumor Cells in Early-Stage Non-small Cell Lung Cancer Treated With Stereotactic Body Radiation Therapy.

التفاصيل البيبلوغرافية
العنوان: Multiblock Discriminant Analysis of Integrative 18 F-FDG-PET/CT Radiomics for Predicting Circulating Tumor Cells in Early-Stage Non-small Cell Lung Cancer Treated With Stereotactic Body Radiation Therapy.
المؤلفون: Lee SH; Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania. Electronic address: SangHo.Lee@pennmedicine.upenn.edu., Kao GD; Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania., Feigenberg SJ; Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania., Dorsey JF; Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania., Frick MA; Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania., Jean-Baptiste S; Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania., Uche CZ; Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania., Cengel KA; Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania., Levin WP; Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania., Berman AT; Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania., Aggarwal C; Division of Hematology/Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania., Fan Y; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania., Xiao Y; Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania.
المصدر: International journal of radiation oncology, biology, physics [Int J Radiat Oncol Biol Phys] 2021 Aug 01; Vol. 110 (5), pp. 1451-1465. Date of Electronic Publication: 2021 Mar 01.
نوع المنشور: Journal Article; Research Support, N.I.H., Extramural
اللغة: English
بيانات الدورية: Publisher: Elsevier, Inc Country of Publication: United States NLM ID: 7603616 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-355X (Electronic) Linking ISSN: 03603016 NLM ISO Abbreviation: Int J Radiat Oncol Biol Phys Subsets: MEDLINE
أسماء مطبوعة: Publication: New York, NY : Elsevier, Inc
Original Publication: Elmsford, N. Y., Pergamon Press.
مواضيع طبية MeSH: Neoplastic Cells, Circulating* , Positron Emission Tomography Computed Tomography*, Carcinoma, Non-Small-Cell Lung/*blood , Carcinoma, Non-Small-Cell Lung/*radiotherapy , Lung Neoplasms/*blood , Lung Neoplasms/*radiotherapy, Aged ; Aged, 80 and over ; Area Under Curve ; Biomarkers, Tumor ; Carcinoma, Non-Small-Cell Lung/pathology ; Discriminant Analysis ; Female ; Fluorodeoxyglucose F18 ; Humans ; Lung Neoplasms/pathology ; Male ; Middle Aged ; Prospective Studies ; Radiopharmaceuticals ; Statistics, Nonparametric ; Tumor Burden
مستخلص: Purpose: The main objective of the present study was to integrate 18 F-FDG-PET/CT radiomics with multiblock discriminant analysis for predicting circulating tumor cells (CTCs) in early-stage non-small cell lung cancer (ES-NSCLC) treated with stereotactic body radiation therapy (SBRT).
Methods: Fifty-six patients with stage I NSCLC treated with SBRT underwent 18 F-FDG-PET/CT imaging pre-SBRT and post-SBRT (median, 5 months; range, 3-10 months). CTCs were assessed via a telomerase-based assay before and within 3 months after SBRT and dichotomized at 5 and 1.3 CTCs/mL. Pre-SBRT, post-SBRT, and delta PET/CT radiomics features (n = 1548 × 3/1562 × 3) were extracted from gross tumor volume. Seven feature blocks were constructed including clinical parameters (n = 12). Multiblock data integration was performed using block sparse partial least squares-discriminant analysis (sPLS-DA) referred to as Data Integration Analysis for Biomarker Discovery Using Latent Components (DIABLO) for identifying key signatures by maximizing common information between different feature blocks while discriminating CTC levels. Optimal input blocks were identified using a pairwise combination method. DIABLO performance for predicting pre-SBRT and post-SBRT CTCs was evaluated using combined AUC (area under the curve, averaged across different blocks) analysis with 20 × 5-fold cross-validation (CV) and compared with that of concatenation-based sPLS-DA that consisted of combining all features into 1 block. CV prediction scores between 1 class versus the other were compared using the Wilcoxon rank sum test.
Results: For predicting pre-SBRT CTCs, DIABLO achieved the best performance with combined pre-SBRT PET radiomics and clinical feature blocks, showing CV AUC of 0.875 (P = .009). For predicting post-SBRT CTCs, DIABLO achieved the best performance with combined post-SBRT CT and delta CT radiomics feature blocks, showing CV AUCs of 0.883 (P = .001). In contrast, all single-block sPLS-DA models could not attain CV AUCs higher than 0.7.
Conclusions: Multiblock integration with discriminant analysis of 18 F-FDG-PET/CT radiomics has the potential for predicting pre-SBRT and post-SBRT CTCs. Radiomics and CTC analysis may complement and together help guide the subsequent management of patients with ES-NSCLC.
(Copyright © 2021 Elsevier Inc. All rights reserved.)
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معلومات مُعتمدة: R01 CA201071 United States CA NCI NIH HHS; S10 OD023495 United States OD NIH HHS; U10 CA180868 United States CA NCI NIH HHS; U24 CA180803 United States CA NCI NIH HHS
المشرفين على المادة: 0 (Biomarkers, Tumor)
0 (Radiopharmaceuticals)
0Z5B2CJX4D (Fluorodeoxyglucose F18)
تواريخ الأحداث: Date Created: 20210304 Date Completed: 20210923 Latest Revision: 20240402
رمز التحديث: 20240402
مُعرف محوري في PubMed: PMC8286285
DOI: 10.1016/j.ijrobp.2021.02.030
PMID: 33662459
قاعدة البيانات: MEDLINE
الوصف
تدمد:1879-355X
DOI:10.1016/j.ijrobp.2021.02.030