Improvement of Online Treatment Planning with the MR-Linac Using Fat-Suppressed MRI
T Salzillo1*, A Dresner2, A Way1, K Wahid1, S Mulder1, A Yoder1, S Ahmed1, K Corrigan1, G Manzar1, L Andring1, C Pinnix1, R Stafford3, A Mohamed1, J Wang4, C Fuller1, (1) Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX (2) Philips Healthcare (3) Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX (4) Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX
Presentations
SU-H330-IePD-F6-1 (Sunday, 7/10/2022) 3:30 PM - 4:00 PM [Eastern Time (GMT-4)]
Exhibit Hall | Forum 6
Purpose: With the combination of superior soft tissue contrast and online treatment adaptation, the MR-Linac has the potential for extremely precise treatment delivery. To take advantage of this, we sought to develop a clinically feasible fat-suppressed T2 sequence to improve the visibility of target and surrounding structures in the head and neck. A novel analytic platform was also developed to comprehensively assess the quality of potential sequences and identify the optimal sequence parameters.
Methods: Five iterations of a 3D Spectral Attenuated Inversion Recovery (SPAIR) T2-weighted sequence were developed by adjusting relevant sequence parameters. Images were acquired on five head and neck cases on the MR-Linac. The tumor, parotid glands, and pterygoid muscles were contoured by five radiation oncologists. SNR and CNR (relative to muscle and fat) were calculated for these segmentations. The visibility of these structures was quantified through conspicuity measurements. Contour precision was assessed by calculating pairwise Dice similarity coefficient and Hausdorff distance between each observer for a given image and averaged. Lastly, qualitative rankings for each image were provided by each of the observers and two separate imaging physicists, which encompassed presence of artifacts, level of fat suppression, and clarity of structures.
Results: With regards to visibility and segmentation precision, three of the SPAIR iterations consistently outperformed the non-fat-suppressed sequence for the tumor and parotid glands. Conversely, each of the SPAIR iterations were consistently worse compared with the non-fat-suppressed sequence for the pterygoid muscles.
Conclusion: An optimized 3D T2-weighted SPAIR sequence has been developed and validated for acquisition on MR-Linac devices. Furthermore, a robust and comprehensive analysis platform for sequence optimization has been developed. The combination of qualitative and quantitative metrics of image quality and segmentation precision have been incorporated into an image grade and can be applied to any type of imaging technique for optimization.
Keywords
MRI, Treatment Planning, Segmentation
Taxonomy
IM/TH- MRI in Radiation Therapy: MRI for treatment planning
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