Baseline 18F-FDG PET/CT Radiomics in Classical Hodgkin's Lymphoma: The Predictive Role of the Largest and the Hottest Lesions

被引:4
作者
Triumbari, Elizabeth Katherine Anna [1 ,2 ]
Gatta, Roberto [3 ,4 ,5 ]
Maiolo, Elena [6 ]
De Summa, Marco [7 ]
Boldrini, Luca [5 ]
Mayerhoefer, Marius E. [8 ,9 ]
Hohaus, Stefan [6 ,10 ]
Nardo, Lorenzo [2 ]
Morland, David [11 ,12 ,13 ,14 ]
Annunziata, Salvatore [11 ]
机构
[1] Univ Cattolica Sacro Cuore, Dept Radiol Sci & Hematol, Sect Nucl Med, I-00168 Rome, Italy
[2] Univ Calif Davis, Dept Radiol, Sacramento, CA 95817 USA
[3] Univ Brescia, Dept Clin & Expt Sci, I-25121 Brescia, Italy
[4] Lausanne Univ Hosp, Dept Oncol, CH-1011 Lausanne, Switzerland
[5] Fdn Policlin Univ A Gemelli, IRCCS, Radiom, Dipartimento Radiol Radioterapia Ematol, I-00168 Rome, Italy
[6] Fdn Policlin Univ A Gemelli, IRCCS, Ematol, Dipartimento Radiol Radioterapia Ematol, I-00168 Rome, Italy
[7] Fdn Policlin Univ A Gemelli, Medipass Spa, IRCCS, Integrat Serv PET CT Radiofarmacy TracerGLab, I-00168 Rome, Italy
[8] Med Univ Vienna, Dept Biomed Imaging & Image Guided Therapy, Div Gen & Pediat Radiol, A-1090 Vienna, Austria
[9] Mem Sloan Kettering Canc Ctr, Dept Radiol, New York, NY 10065 USA
[10] Univ Cattolica Sacro Cuore, Dept Radiol Sci & Hematol, Hematol Sect, I-00168 Rome, Italy
[11] Fdn Policlin Univ A Gemelli, Dipartimento Radiol, Unita Med Nucl GSTeP Radiofarm,TracerGLa, I-00168 Rome, Italy
[12] Inst Godinot, Med Nucl, F-51100 Reims, France
[13] Univ Reims, CReST EA 3804, F-51100 Reims, France
[14] Lab Biophys, Univ Reims Champagne Ardenne, F-51100 Reims, France
关键词
classical Hodgkin's lymphoma; F-18-FDG PET; CT; radiomics; METABOLIC TUMOR VOLUME; FDG-PET/CT; RESPONSE ASSESSMENT; CT;
D O I
10.3390/diagnostics13081391
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
This study investigated the predictive role of baseline F-18-FDG PET/CT (bPET/CT) radiomics from two distinct target lesions in patients with classical Hodgkin's lymphoma (cHL). cHL patients examined with bPET/CT and interim PET/CT between 2010 and 2019 were retrospectively included. Two bPET/CT target lesions were selected for radiomic feature extraction: Lesion_A, with the largest axial diameter, and Lesion_B, with the highest SUVmax. Deauville score at interim PET/CT (DS) and 24-month progression-free-survival (PFS) were recorded. Mann-Whitney test identified the most promising image features (p < 0.05) from both lesions with regards to DS and PFS; all possible radiomic bivariate models were then built through a logistic regression analysis and trained/tested with a cross-fold validation test. The best bivariate models were selected based on their mean area under curve (mAUC). A total of 227 cHL patients were included. The best models for DS prediction had 0.78 +/- 0.05 maximum mAUC, with a predominant contribution of Lesion_A features to the combinations. The best models for 24-month PFS prediction reached 0.74 +/- 0.12 mAUC and mainly depended on Lesion_B features. bFDG-PET/CT radiomic features from the largest and hottest lesions in patients with cHL may provide relevant information in terms of early response-to-treatment and prognosis, thus representing an earlier and stronger decision-making support for therapeutic strategies. External validations of the proposed model are planned.
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页数:14
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