ESTRO 2024 - Abstract Book

S5093

Physics - Radiomics, functional and biological imaging and outcome prediction

ESTRO 2024

Leveraging hybrid PET/MR imaging to distinguish progression from radionecrosis post-radiosurgery

Michael Maddalena 1 , Dr. Adam Farag 2 , Randy Jager 3 , Noha Sinno 3 , David B Schultz 4,3 , Catherine Coolens 1,4

1 University of Toronto, Medical Biophysics, Toronto, Canada. 2 University Health Network, Toronto General Hospital, Toronto, Canada. 3 University Health Network, Princess Margaret Hospital, Toronto, Canada. 4 University of Toronto, Radiation Oncology, Toronto, Canada

Purpose/Objective:

Despite excellent local control of brain metastasis patients treated with stereotactic radiosurgery (SRS), potential tumour progression (TP) is observed during follow-up in up to 20% of cases 1 . The lesion may also contain radionecrosis (RN), a by-product of SRS which appears indistinguishable from TP via MRI yet warrants a distinct treatment regimen 2 . Proper diagnostic protocols are key in prolonging patient survival post-SRS, as up to 20% of all cancer patients develop brain metastases, a condition currently associated with a dismal 24-month overall survival rate of 8.1% 3,4 . Currently, invasive post-surgical histopathology remains the only gold-standard confirmation of TP/RN 5 . Thus, non-invasive imaging techniques with strong diagnostic accuracy are urgently required to improve patient stratification while minimizing harm. However, the historic rate of image-based TP/RN differentiation accuracy lies at a modest 54%, impeding the widespread and complete adoption of image-based protocols in clinical practice due to suboptimal performance 6 . To bridge this gap, the objective of our study is the establishment of an image based PET/MR classification protocol to distinguish tumour progression from radionecrosis in patient lesions post SRS at a ≥80% diagnostic accuracy/sensitivity/specificity threshold across all implemented classification methods. To date eight adult patients with confirmed TP or RN via histopathology have been enrolled in the context of an ongoing ethics board-approved clinical trial. All patient images were co-acquired in a single session using a hybrid PET/MR platform. PET imaging utilizes 18-F-Fluorothymidine (FLT), a radiotracer which has been approved for experimental use. Acquired static and dynamic PET datasets were analyzed using two methods: (i) a conventional static PET maximum standard uptake value (SUV max ) estimation and, (ii) compartmental modelling of a 20-minute dynamic PET acquisition (dPET). dPET time-activity curves were fitted reversible and irreversible two-compartment models, with the best-fitting model selected using the Akaike Information Criterion. Additional kinetic parameters (net flux – Ki, distribution volume – Vd; phosphorylated fraction – Pf) were calculated from fitted compartment parameters (k1, k2, k3 and k4). The classification performance of SUV max values versus dPET kinetic parameters was assessed to distinguish which protocol differentiates TP from RN most accurately. MRI t1-weighted, t2-weighted and diffusion weighted imaging (DWI) sequences were co-acquired in the same frame of reference as PET acquisitions and co registered to a planning t1-weighted MRI reference. Region-of-interest and voxel-wise DWI MR analyses were performed to calculate apparent diffusion coefficients (ADC) at 16 unique b-values (0-3000); true diffusion (Dp), vascular fraction (Fp), and pseudo-perfusion (Dt) ADC values were inferred using a bi-exponential fit with uncertainty propagation weighting. Material/Methods:

Results:

The FLT-dPET derived kinetic parameters Ki and Pf suggest that dPET analysis can distinguish TP from RN in post-SRS lesions (0.063±0.043; 0.304±0.204 and 0.002±0.0; 0.004±0.001 respectively, p < 0.05), whereas RN cannot be