ArticleBiomedical engineering online2026
Desargues cloud TPS: a cloud-based automatic radiation treatment planning system for IMRT.
Article in Biomedical engineering online, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Artificial intelligence in radiation treatment planning: a narrative review from automation to clinical decision support.Translational cancer research · 2026Review
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Authors and funding
20 authors.
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Abstract
purposeTo develop a cloud-based automated treatment planning system for intensity-modulated radiation therapy and evaluate its efficacy and safety for tumors in various anatomical sites under general clinical scenarios.
resultsAll the plans from both groups satisfy the PTV prescription dose coverage requirement of at least 95% of the PTV volume. The mean HI of plan A group and plan B group is 0.084 and 0.081, respectively, with no statistically significant difference from those of plan C group. The mean CI, PQM, OOT and POT are 0.806, 77.55. 410 s and 185 s for plan A group, and 0.841, 76.87, 515.1 s and 271.1 s for plan B group, which were significantly superior than those of plan C group except for the CI of plan A group. There is no statistically significant difference between the dose accuracies of plan B and plan C groups.
conclusionsIt is concluded that the overall efficacy and safety of the Desargues Cloud TPS are not significantly different to those of Varian Eclipse, while some efficacy indicators of plans generated from automatic planning without or with manual adjustments are even significantly superior to those of fully manual plans from Eclipse. The cloud-based automatic treatment planning additionally increase the efficiency of treatment planning process and facilitate the sharing of planning knowledge. MATERIALS AND
methodsThe cloud-based automatic radiation treatment planning system, Desargues Cloud TPS, was designed and developed based on browser/server mode, where all the computing intensive functions were deployed on the server and user interfaces were implemented on the web. The communication between the browser and the server was through the local area network (LAN) of a radiotherapy institution. The automatic treatment planning module adopted a hybrid of both knowledge-based planning (KBP) and protocol-based automatic iterative optimization (PB-AIO), consisting of three steps: beam angle optimization (BAO), beam fluence optimization (BFO) and machine parameter optimization (MPO). 53 patients from two institutions have been enrolled in a multi-center self-controlled clinical validation. For each patient, three IMRT plans were designed. The plan A and B were designed on Desargues Cloud TPS using automatic planning without and with manual adjustments, respectively. The plan C was designed on Varian Eclipse TPS using fully manual planning. The efficacy indicators were heterogeneous index, conformity index, plan quality metric, overall operation time and plan optimization time. The safety indicators were gamma indices of dose verification.
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