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Concurrent functional and metabolic assessment of brain tumors using hybrid PET/MR imaging

  • Clinical Study
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Abstract

To evaluate diagnostic accuracy of perfusion weighted imaging (PWI) and positron emission tomography (PET) using an integrated PET/MR system in tumor grading as well as in differentiating recurrent tumor from treatment-induced effects (TIE) in brain tumor patients. Twenty patients (Group A: treatment naïve, 9 patients with 16 lesions; Group B: post-therapy, 11 patients with 18 lesions) underwent fluorine 18 (18F) fluorodeoxyglucose (FDG) brain PET/MR with PWI. Two blinded readers predicted low versus high-grade tumor (for Group A) and tumor recurrence versus TIE (for Group B) based solely on tumor rCBV (regional cerebral blood volume) and SUV (standardized uptake values). Tumor histopathology at resection was the reference standard. Using rCBVmean ≤ 1.74 as a cut-off, 100 % sensitivity and 74 % specificity were observed, whereas 75 % sensitivity and 89.7 % specificity were observed with SUVmean ≤ 4.0 as a cut-off to classify patients as test positive for low-grade tumors (Group A) and TIE (Group B). Diagnostic accuracy for detection of low-grade tumors was 90 % using PWI and 40 % using PET in Group A (p = 0.056); for detection of TIE in Group B, diagnostic accuracy was 94.1 % using PWI and 55.6 % using PET (p = 0.033). No significant correlation was demonstrated between rCBV parameters and SUV in Group A (mean values: p > 0.403), Group B (p > 0.06) and in the entire population (p > 0.07). Best overall sensitivity and specificity were obtained using rCBVmean ≤ 1.74 and SUVmean ≤ 4.0 cut-off values. PWI demonstrated better diagnostic accuracy in both groups. Poor correlation was observed between FDG and rCBV parameters.

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Acknowledgments

Work principally supported by CAI2R and/or performed by CAI2R personnel. The Center for Advanced Imaging Innovation and Research (CAI2R, www.cai2r.net) at New York University School of Medicine is supported by NIH/NIBIB Grant number P41 EB017183.

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Authors and Affiliations

  1. Department of Radiology, NYU School of Medicine, 660 First Avenue, 2nd Floor, New York, NY, 10016, USA

    B. Sacconi, R. A. Raad, J. Lee, J. S. Babb & R. Jain

  2. Department of Medicine, Weill Cornell Medical College, New York-Presbyterian Hospital, New York, NY, USA

    H. Fine

  3. Department of Neurosurgery, NYU School of Medicine, New York, NY, USA

    D. Kondziolka, J. G. Golfinos & R. Jain

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  1. B. Sacconi
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  2. R. A. Raad
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  3. J. Lee
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  4. H. Fine
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  5. D. Kondziolka
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  6. J. G. Golfinos
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  7. J. S. Babb
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  8. R. Jain
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Correspondence to R. Jain.

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Sacconi, B., Raad, R.A., Lee, J. et al. Concurrent functional and metabolic assessment of brain tumors using hybrid PET/MR imaging. J Neurooncol 127, 287–293 (2016). https://doi.org/10.1007/s11060-015-2032-6

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  • DOI: https://doi.org/10.1007/s11060-015-2032-6

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