TY - JOUR

T1 - Feasibility of multi-parametric PET and MRI for prediction of tumour recurrence in patients with glioblastoma

AU - Lundemann, Michael

AU - af Rosenschold, Per Munck

AU - Muhic, Aida

AU - Larsen, Vibeke A.

AU - Poulsen, Hans S.

AU - Engelholm, Svend-Aage

AU - Andersen, Flemming L.

AU - Kjaer, Andreas

AU - Larsson, Henrik B. W.

AU - Law, Ian

AU - Hansen, Adam E.

PY - 2019

Y1 - 2019

N2 - BackgroundRecurrence in glioblastoma patients often occur close to the original tumour and indicates that the current treatment is inadequate for local tumour control. In this study, we explored the feasibility of using multi-modality imaging at the time of radiotherapy planning. Specifically, we aimed to identify parameters from pre-treatment PET and MRI with potential to predict tumour recurrence.Materials and methodsSixteen patients were prospectively recruited and treated according to established guidelines. Multi-parametric imaging with F-18-FET PET/CT and F-18-FDG PET/MR including diffusion and dynamic contrast enhanced perfusion MRI were performed before radiotherapy. Correlations between imaging parameters were calculated. Imaging was related to the voxel-wise outcome at the time of tumour recurrence. Within the radiotherapy target, median differences of imaging parameters in recurring and non-recurring voxels were calculated for contrast-enhancing lesion (CEL), non-enhancing lesion (NEL), and normal appearing grey and white matter. Logistic regression models were created to predict the patient-specific probability of recurrence. The most important parameters were identified using standardized model coefficients.ResultsSignificant median differences between recurring and non-recurring voxels were observed for FDG, FET, fractional anisotropy, mean diffusivity, mean transit time, extra-vascular, extra-cellular blood volume and permeability derived from scans prior to chemo-radiotherapy. Tissue-specific patterns of voxel-wise correlations were observed. The most pronounced correlations were observed for F-18-FDG- and F-18-FET-uptake in CEL and NEL. Voxel-wise modelling of recurrence probability resulted in area under the receiver operating characteristic curve of 0.77 from scans prior to therapy. Overall, FET proved to be the most important parameter for recurrence prediction.ConclusionMulti-parametric imaging before radiotherapy is feasible and significant differences in imaging parameters between recurring and non-recurring voxels were observed. Combining parameters in a logistic regression model enabled patient-specific maps of recurrence probability, where F-18-FET proved to be most important. This strategy could enable risk-adapted radiotherapy planning.

AB - BackgroundRecurrence in glioblastoma patients often occur close to the original tumour and indicates that the current treatment is inadequate for local tumour control. In this study, we explored the feasibility of using multi-modality imaging at the time of radiotherapy planning. Specifically, we aimed to identify parameters from pre-treatment PET and MRI with potential to predict tumour recurrence.Materials and methodsSixteen patients were prospectively recruited and treated according to established guidelines. Multi-parametric imaging with F-18-FET PET/CT and F-18-FDG PET/MR including diffusion and dynamic contrast enhanced perfusion MRI were performed before radiotherapy. Correlations between imaging parameters were calculated. Imaging was related to the voxel-wise outcome at the time of tumour recurrence. Within the radiotherapy target, median differences of imaging parameters in recurring and non-recurring voxels were calculated for contrast-enhancing lesion (CEL), non-enhancing lesion (NEL), and normal appearing grey and white matter. Logistic regression models were created to predict the patient-specific probability of recurrence. The most important parameters were identified using standardized model coefficients.ResultsSignificant median differences between recurring and non-recurring voxels were observed for FDG, FET, fractional anisotropy, mean diffusivity, mean transit time, extra-vascular, extra-cellular blood volume and permeability derived from scans prior to chemo-radiotherapy. Tissue-specific patterns of voxel-wise correlations were observed. The most pronounced correlations were observed for F-18-FDG- and F-18-FET-uptake in CEL and NEL. Voxel-wise modelling of recurrence probability resulted in area under the receiver operating characteristic curve of 0.77 from scans prior to therapy. Overall, FET proved to be the most important parameter for recurrence prediction.ConclusionMulti-parametric imaging before radiotherapy is feasible and significant differences in imaging parameters between recurring and non-recurring voxels were observed. Combining parameters in a logistic regression model enabled patient-specific maps of recurrence probability, where F-18-FET proved to be most important. This strategy could enable risk-adapted radiotherapy planning.

KW - Radiotherapy

KW - Glioblastoma

KW - Response prediction

KW - FET

KW - PET

KW - MRI

U2 - 10.1007/s00259-018-4180-3

DO - 10.1007/s00259-018-4180-3

M3 - Journal article

C2 - 30276440

VL - 46

SP - 603

EP - 613

JO - European Journal of Nuclear Medicine and Molecular Imaging

JF - European Journal of Nuclear Medicine and Molecular Imaging

SN - 1619-7070

IS - 3

ER -