Publications by authors named "Romain Ricci"
Understanding the differences between prognostic and predictive indices is imperative for medical research advances. We have developed a new prognostic measure that will identify the strengths, limitations, and potential applications in clinical practice.
View Article and Find Full Text PDFTotal metabolic tumor volume (TMTV) is prognostic in lymphoma. However, cutoff values for risk stratification vary markedly, according to the tumor delineation method used. We aimed to create a standardized TMTV benchmark dataset allowing TMTV to be tested and applied as a reproducible biomarker.
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- * A 3D V-NET model, trained on 1218 baseline 18FDG-PET/CT scans, achieved strong segmentation performance with mean dice scores of 0.84 for training and validation sets, and a slightly lower score of 0.76 for the test set.
- * The deep learning model shows significant potential to reduce the time required for TMTV computation while maintaining high accuracy, with Spearman's correlations between manual and predicted TMTV ranging from 0.92
We tested baseline positron emission tomography (PET)/computed tomography (CT) as a measure of total tumor burden to better identify high-risk patients with early-stage Hodgkin lymphoma (HL). Patients with stage I-II HL enrolled in the standard arm (combined modality treatment) of the H10 trial (NCT00433433) with available baseline PET and interim PET (iPET2) after 2 cycles of doxorubicin, bleomycin, vinblastine, and dacarbazine were included. Total metabolic tumor volume (TMTV) was measured on baseline PET.
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