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Relationship of computed tomography perfusion and positron emission tomography to tumour progression in malignant glioma

IntroductionThis study aimed to explore the potential for computed tomography (CT) perfusion and 18-Fluorodeoxyglucose positron emission tomography (FDG-PET) in predicting sites of future progressive tumour on a voxel-by-voxel basis after radiotherapy and chemotherapy. MethodsTen patients underwent...

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Detalles Bibliográficos
Autores principales: Yeung, Timothy P C, Yartsev, Slav, Lee, Ting-Yim, Wong, Eugene, He, Wenqing, Fisher, Barbara, VanderSpek, Lauren L, Macdonald, David, Bauman, Glenn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: WILEY-VCH Verlag 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4175825/
https://www.ncbi.nlm.nih.gov/pubmed/26229630
http://dx.doi.org/10.1002/jmrs.37
Descripción
Sumario:IntroductionThis study aimed to explore the potential for computed tomography (CT) perfusion and 18-Fluorodeoxyglucose positron emission tomography (FDG-PET) in predicting sites of future progressive tumour on a voxel-by-voxel basis after radiotherapy and chemotherapy. MethodsTen patients underwent pre-radiotherapy magnetic resonance (MR), FDG-PET and CT perfusion near the end of radiotherapy and repeated post-radiotherapy follow-up MR scans. The relationships between these images and tumour progression were assessed using logistic regression. Cross-validation with receiver operating characteristic (ROC) analysis was used to assess the value of these images in predicting sites of tumour progression. ResultsPre-radiotherapy MR-defined gross tumour; near-end-of-radiotherapy CT-defined enhancing lesion; CT perfusion blood flow (BF), blood volume (BV) and permeability-surface area (PS) product; FDG-PET standard uptake value (SUV); and SUV:BF showed significant associations with tumour progression on follow-up MR imaging (P < 0.0001). The mean sensitivity (±standard deviation), specificity and area under the ROC curve (AUC) of PS were 0.64 ± 0.15, 0.74 ± 0.07 and 0.72 ± 0.12 respectively. This mean AUC was higher than that of the pre-radiotherapy MR-defined gross tumour and near-end-of-radiotherapy CT-defined enhancing lesion (both AUCs = 0.6 ± 0.1, P ≤ 0.03). The multivariate model using BF, BV, PS and SUV had a mean AUC of 0.8 ± 0.1, but this was not significantly higher than the PS only model. ConclusionPS is the single best predictor of tumour progression when compared to other parameters, but voxel-based prediction based on logistic regression had modest sensitivity and specificity.