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Brain MR-only workflow in clinical practice: A comparison among generators for quality assurance and patient
Mathilde Levardon1, Damien Autret2, Thomas Le Dorze2
1Department of Nuclear Medicine, Centre Hospitalier Universitaire d'Angers, Angers, France.
Background And Purpose:
Routine quality control procedures are still required for sCT based on artificial intelligence (AI) to verify the performance of the generators. The aim of this study was to evaluate three generators based on AI or bulk density (BD) assignment for the patient-specific quality assurance (PSQA) of another AI-based generator in clinical routine. A patient positioning study based on 2D/2D kV-image comparing the performances of four sCT generators was also performed.
Materials And Methods:
On the four generators available commercially at our institution, one was chosen as the clinical one, and the three others were used for PSQA. Several dose metrics were calculated like the mean error, dose-volume histogram metrics, and 1%/1 mm gamma analysis. A comparison against CT was considered as a reference. Translations and rotations found during patient positioning based on sCT were compared to those based on CT.
Results:
Some of the metrics calculated against CT revealed patients outside the tolerances chosen (1% for point metrics; 90% for gamma pass rate). None of the generators was able to identify these outliers for all metrics studied. Performing a PSQA with other sCT generators introduced several false positives and false negatives. None of the generators was able to clearly identify, for all metrics studied, a true sCT failure caused by a metal implant. The smallest positioning deviations were found for the BD assignment sCT, the largest for the only AI generator not based on a T1 Dixon MR sequence.
Conclusions:
PSQA of a sCT generator with another sCT generator should be performed with great care. Patient positioning is an important aspect to consider when evaluating a sCT generator. The results of this study should help medical physicists willing to set up a MR-only workflow for the brain based on a 2D/2D kV-image patient positioning.
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