Corrado Santarosa1, Antonella Castellano1, Gian Marco Conte1, Marcello Cadioli2, Antonella Iadanza1, Maria Rosa Terreni3, Alberto Franzin4, Lorenzo Bello5, Massimo Caulo6, Andrea Falini1, Nicoletta Anzalone7. 1. Neuroradiology Unit and CERMAC, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy. 2. Neuroradiology Unit and CERMAC, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy; Philips Healthcare, Monza, Italy. 3. Pathology Department, San Raffaele Scientific Institute, Milan, Italy. 4. Department of Neurosurgery, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy. 5. Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, Italy; Unit of Surgical Neurooncology, Humanitas Research Hospital, Rozzano, MI, Italy. 6. Department of Neuroscience and Imaging and ITAB-Institute of Advanced Biomedical Technologies, University "G. d'Annunzio", Chieti, Italy. 7. Neuroradiology Unit and CERMAC, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy. Electronic address: anzalone.nicoletta@hsr.it.
Abstract
INTRODUCTION: Dynamic susceptibility contrast (DSC)-MRI is a perfusion technique with high diagnostic accuracy for glioma grading, despite limitations due to inherent susceptibility effects. Dynamic contrast-enhanced (DCE)-MRI has been proposed as an alternative technique able to overcome the DSC-MRI shortcomings. This pilot study aimed at comparing the diagnostic accuracy of DSC and DCE-MRI for glioma grading by evaluating two estimates of blood volume, the DCE-derived plasma volume (Vp) and the DSC-derived relative cerebral blood volume (rCBV), and a measure of vessel permeability, the DCE-derived volume transfer constant K(trans). METHODS: Twenty-six newly diagnosed glioma patients underwent 3T-MR DCE and DSC imaging. Parametric maps of CBV, Vp and K(trans) were calculated and the region of highest value (hotspot) was measured on each map. Histograms of rCBV, Vp and K(trans) values were calculated for the tumor volume. Statistical differences according to WHO grade were assessed. The diagnostic accuracy for tumor grading of the two techniques was determined by ROC analysis. RESULTS: rCBV, Vp and K(trans) measures differed significantly between high and low-grade gliomas. Hotspot analysis showed the highest correlation with grading. K(trans) hotspots co-localized with Vp hotspots only in 56% of enhancing gliomas. For differentiating high from low-grade gliomas the AUC was 0.987 for rCBVmax, and 1.000 for Vpmax and K(trans)max. Combination of DCE-derived Vp and K(trans) parameters improved the diagnostic performance of the histogram method. CONCLUSION: This initial experience of DCE-derived Vp evaluation shows that this parameter is as accurate as the well-established DSC-derived rCBV for glioma grading. DCE-derived K(trans) is equally useful for grading, providing different informations with respect to Vp.
INTRODUCTION: Dynamic susceptibility contrast (DSC)-MRI is a perfusion technique with high diagnostic accuracy for glioma grading, despite limitations due to inherent susceptibility effects. Dynamic contrast-enhanced (DCE)-MRI has been proposed as an alternative technique able to overcome the DSC-MRI shortcomings. This pilot study aimed at comparing the diagnostic accuracy of DSC and DCE-MRI for glioma grading by evaluating two estimates of blood volume, the DCE-derived plasma volume (Vp) and the DSC-derived relative cerebral blood volume (rCBV), and a measure of vessel permeability, the DCE-derived volume transfer constant K(trans). METHODS: Twenty-six newly diagnosed gliomapatients underwent 3T-MR DCE and DSC imaging. Parametric maps of CBV, Vp and K(trans) were calculated and the region of highest value (hotspot) was measured on each map. Histograms of rCBV, Vp and K(trans) values were calculated for the tumor volume. Statistical differences according to WHO grade were assessed. The diagnostic accuracy for tumor grading of the two techniques was determined by ROC analysis. RESULTS:rCBV, Vp and K(trans) measures differed significantly between high and low-grade gliomas. Hotspot analysis showed the highest correlation with grading. K(trans) hotspots co-localized with Vp hotspots only in 56% of enhancing gliomas. For differentiating high from low-grade gliomas the AUC was 0.987 for rCBVmax, and 1.000 for Vpmax and K(trans)max. Combination of DCE-derived Vp and K(trans) parameters improved the diagnostic performance of the histogram method. CONCLUSION: This initial experience of DCE-derived Vp evaluation shows that this parameter is as accurate as the well-established DSC-derived rCBV for glioma grading. DCE-derived K(trans) is equally useful for grading, providing different informations with respect to Vp.
Authors: Jann N Sarkaria; Leland S Hu; Ian F Parney; Deanna H Pafundi; Debra H Brinkmann; Nadia N Laack; Caterina Giannini; Terence C Burns; Sani H Kizilbash; Janice K Laramy; Kristin R Swanson; Timothy J Kaufmann; Paul D Brown; Nathalie Y R Agar; Evanthia Galanis; Jan C Buckner; William F Elmquist Journal: Neuro Oncol Date: 2018-01-22 Impact factor: 12.300
Authors: Gayle R Salama; Linda A Heier; Praneil Patel; Rohan Ramakrishna; Rajiv Magge; Apostolos John Tsiouris Journal: Front Neurol Date: 2018-01-22 Impact factor: 4.003