MRI-only based treatment with a commercial deep-learning generation method for synthetic CT of brain

Forskningsoutput: KonferensbidragKonferensabstractPeer review


To show feasibility of synthetic computed tomography (sCT) images generated using a commercially
available software, enabling MRI-only treatment planning for the brain in a clinical setting.
Patients and Methods
20 and 16 patients with brain malignancies, including post-surgical cases, were included for validation
and treatment, respectively. Dixon MR images of the skull were exported to the MRI Planner software
(Spectronic Medical AB), which utilizes convolutional neural network algorithms for sCT generation.
In the validation study, sCT images were rigidly registered and resampled to CT geometry for each
patient. Treatment plans were optimized on CT and retrospectively recalculated on sCT images for
evaluation of dosimetric and geometric endpoints. Clinical robustness in patient setup verification was
assessed by rigidly registering cone beam CT (CBCT) to sCT and CT images, respectively.
The treatment study was performed on sCT images, using CT solely for QA purposes.
All sCT images were successfully generated in the validation study. Mean absolute error of the sCT
images within the body contour for all patients was 62.2 ± 4.1 HU. Average absorbed dose differences
were below 0.2%. Mean pass rate of global gamma (1%/1mm) for all patients was 100.0 ± 0.0 % within
PTV and 99.1 ± 0.6 % for the full dose distribution. No clinically relevant deviations were found in the
CBCT-sCT vs CBCT-CT image registrations. Areas of bone resection due to surgery were accurately
depicted in the sCT images. Finally, treatment success rate was 15/16. One patient was excluded due to
sCT artifacts from a haemostatic substance injected during surgery.
15 patients have successfully received MRI-only RT for brain tumours using the validated commercially
available sCT software. Validation showed comparable results between sCT and CT images for both
dosimetric and geometric endpoints
StatusPublished - 2020
EvenemangVirtual 8th MR in RT Symposium - Virtual
Varaktighet: 2021 apr. 192021 apr. 21


KonferensVirtual 8th MR in RT Symposium

Ämnesklassifikation (UKÄ)

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