Publications by authors named "S F Barrington"
Tumour bulk is an established prognostic factor in Hodgkin lymphoma (HL) but most patients with limited-stage (LS) HL do not have 'bulk' by standard binary definitions. In the RAPID trial, maximum tumor diameter (MTD) was associated with risk of relapse for LS-HL patients achieving PET-negativity after ABVD chemotherapy. We aimed to externally validate these findings in the H10 trial.
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- The study aimed to validate a deep learning model for predicting treatment outcomes in diffuse large B-cell lymphoma patients across 5 clinical trials, comparing it to the international prognostic index (IPI) and radiomic models.
- The deep learning model, trained on PET/CT scans, demonstrated a higher predictive performance (AUC of 0.66) than IPI (AUC of 0.60) and performed well across all trials.
- While the deep learning and clinical PET models showed similar performance (AUC of 0.69), the PET model achieved the highest AUC (0.71), although the deep learning model provided outcomes without requiring tumor delineation.
Purpose: Hypoxia is a major cause of radioresistance in head and neck cancer (HNC), resulting in treatment failure and disease recurrence. F-fluoromisonidazole [F]FMISO PET has been proposed as a means of localising intratumoural hypoxia in HNC so that radiotherapy can be specifically escalated in hypoxic regions. This concept may not be deliverable in routine clinical practice, however, given that [F]FMISO PET is costly, time consuming and difficult to access.
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- The IELSG37 trial investigated whether patients with primary mediastinal B-cell lymphoma (PMBCL) who have a complete metabolic response (CMR) after treatment can safely skip consolidation radiotherapy.
- It was a randomized noninferiority study involving 545 patients, focusing on progression-free survival (PFS) over 30 months, with results showing high PFS rates of 96.2% for observation and 98.5% for radiotherapy.
- The study concluded that avoiding irradiation does not negatively impact survival, highlighting positive outcomes for patients with CMR.
Total 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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