ArticlePhysics and imaging in radiation oncology2025
Knowledge-based model for automated multi-isocenter total marrow and lymphoid irradiation planning across standard and large patient anatomies.
Article in Physics and imaging in radiation oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Automated contouring, treatment planning, and quality assurance for total marrow lymphoid irradiation.Frontiers in oncology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and purpose: Total marrow and lymphoid irradiation (TMLI) planning is challenging. This study evaluates whether a knowledge-based (KB) model for TMLI delivered using volumetric modulated arc therapy (VMAT) can achieve clinically acceptable dose distributions through fully or semi-automated optimization and whether a single model is effective across varying patient anatomies. Materials and methods: Fifty-one consecutive VMAT-TMLI patients were selected. A KB model was trained using 30 patients treated with standard configurations (5 body isocenters). Validation included two cohorts: 10 standard patients and 11 patients with a larger anatomy treated using separate isocenters for the arms (4 body and 2 arms isocenters). Two planning approaches were explored: fully automated (AutoKB), and KB with manual adjustments (HybridKB) by a planner with no prior experience in TMLI. KB plans were evaluated against clinical plans (CPs) using paired t-tests. Results: The KB model reduced mean doses to major organs-at-risk (OARs). For standard configurations, mean OAR doses were 71% ± 2%, 66% ± 2%, and 66% ± 2% for CP, AutoKB, and HybridKB (both p < 0.01). For larger patients, the corresponding values were 75% ± 3%, 69% ± 2%, and 68% ± 2% (both p < 0.01). D2% of the planning target volume increased in AutoKB, reaching 122% ± 2% (p < 0.001) vs. 117% ± 3% in CP for standard configurations, and 126% ± 2% (p < 0.001) vs. 117% ± 3% in CP for arms configurations. HybridKB was on par with CPs. Conclusions: A single KB model enabled effective planning for multi-isocenter TMLI, including anatomies requiring separate isocenters for the arms. Fully automated KB provided suboptimal dose distributions. KB with manual refinements reduced planner dependence and improved plan quality.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.