FES PET changed nodal staging, field design and boost dose in ER-positive breast cancer
In a diagnostically difficult breast cancer case, FES PET identified occult ER-positive nodal disease and materially changed radiotherapy volume and dose.
Tag
treatment-planning
Beam-deflection compensation restored proton dose delivery inside an in-beam MR scanner
Energy-layer-wise compensation restored millimetre-level proton targeting despite magnetic-field beam shifts approaching 30 mm in an MR-integrated prototype.
Reducing tomotherapy modulation beyond the gantry plateau saved almost no treatment time
The pre-plateau modulation factor preserved plan quality while further reduction created idle delivery time without meaningful efficiency gain.
Action-priority FMEA narrowed radiation therapy QA risks from 30 to seven
A severity-weighted action-priority framework identified the same seven highest RT workflow risks while avoiding 23 additional traditional FMEA flags.
AI is moving across particle therapy planning but clinical validation remains the bottleneck
AI can automate particle planning, dose prediction, adaptation and quality assurance, but limited data and validation still constrain clinical adoption.
uTPS produced deliverable Halcyon VMAT plans comparable with Eclipse
uTPS generated Halcyon VMAT plans with generally comparable dosimetry to Eclipse and greater than 97% gamma passing rates.
PTV coverage prescriptions poorly represented delivered tumor dose in lung SBRT
D95% and D98% PTV prescriptions produced substantial interpatient variability, while GTV- and ITV-based median or mean doses were more accurate.
Brainlab reference beam model enabled one-day SRS commissioning with accurate Monte Carlo calculations
Brainlab Elements commissioning was completed in one day, while Monte Carlo generally agreed with end-to-end measurements within 3%.
Automated proton planning reproduced clinical head and neck NTCP estimates within minutes
Automated proton plans reproduced clinical dysphagia and xerostomia estimates closely while reducing optimization time from days to about one hour.
Individual target optimization reduced brain dose in single-isocenter multi-metastasis radiosurgery
Individual target optimization lowered normal-brain V12 and improved dose gradients while maintaining over 99% coverage, at the cost of higher monitor units.
Deep learning generated deliverable lymphoma intensity-modulated plans but remained dosimetrically inferior
Deep learning produced machine-deliverable lymphoma plans across heterogeneous anatomy, but target coverage and hot spots remained inferior to reference planning.
Photon minibeams enable denser LATTICE patterns in small tumors
Mini-LATTICE created more compact high-dose vertices and greater peak-to-valley separation than conventional LATTICE across six planning cases.
Radiotherapy 3D printing needs standardized quality assurance across institutions
Inter-centre material variability supports shared QA datasets and standardized acceptance criteria for clinical radiotherapy 3D printing.
CT–MRI fusion improved contrast-free lung perfusion mapping for radiotherapy planning
Multimodal CT–MRI perfusion maps matched SPECT better than single-modality methods and reduced high-function lung dose in exploratory planning.
AI-assisted VMAT planning shortened workflow but required manual hotspot correction
AI-assisted planning cut average planning time from about two hours to 30 minutes, but three of 12 plans required manual hotspot correction.