Brain Volume Perfusion CT Performed with 128-detector Row CT System in Patients with Cerebral Gliomas: a Feasibility Study

Overview

Journal Eur Radiol

Specialty Radiology

Date 2011 May 17

PMID 21573969

Citations 7

Authors

Argyro Xyda

Ulrike Haberland

Ernst Klotz

Hans Christoph Bock

Klaus Jung

Michael Knauth

Ramona Schramm

Marios Nikos Psychogios

Gunter Erb

Peter Schramm

Affiliations

Soon will be listed here.

Abstract

Objectives: Validation of the feasibility and efficacy of volume perfusion computed tomography (VPCT) in the preoperative assessment of cerebral gliomas by applying a 128-slice CT covering the entire tumour.

Methods: Forty-six patients (25 men, 21 women; mean age 52.8 years) with cerebral gliomas were evaluated with VPCT. Two readers independently evaluated VPCT data, drawing volumes of interest (VOIs) around the tumour according to maximum intensity projection volumes, which were mapped automatically onto the cerebral blood volume (CBV), flow (CBF) and permeability (Ktrans) perfusion datasets. As control, a second VOI was placed in the contralateral healthy cortex. Correlation among perfusion parameters, tumour grade, hemisphere and VOIs was assessed. The diagnostic power of perfusion parameters was analysed by receiver operating characteristics curve analyses.

Results: VPCT was feasible in the assessment of the entire tumour extent. Mean values of Ktrans, CBV, CBF in high-grade gliomas were significantly higher compared with low-grade (p < 0.01). Ktrans demonstrated the highest diagnostic (97% sensitivity), positive (100%) and negative (94%) prognostic values.

Conclusions: VPCT was feasible in all subjects. All areas of different perfusion characteristics are depicted and quantified in colour-coded 3D maps. The derived parameters correlate well with tumour histopathology, differentiating low- from high-grade gliomas.

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References

Law M, Yang S, Babb J, Knopp E, Golfinos J, Zagzag D . Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade. AJNR Am J Neuroradiol. 2004; 25(5):746-55. PMC: 7974484. View

Abels B, Klotz E, Tomandl B, Kloska S, Lell M . Perfusion CT in acute ischemic stroke: a qualitative and quantitative comparison of deconvolution and maximum slope approach. AJNR Am J Neuroradiol. 2010; 31(9):1690-8. PMC: 7964979. DOI: 10.3174/ajnr.A2151. View

Weidner N . Intratumor microvessel density as a prognostic factor in cancer. Am J Pathol. 1995; 147(1):9-19. PMC: 1869874. View

Cao Y, Shen Z, Chenevert T, Ewing J . Estimate of vascular permeability and cerebral blood volume using Gd-DTPA contrast enhancement and dynamic T2*-weighted MRI. J Magn Reson Imaging. 2006; 24(2):288-96. DOI: 10.1002/jmri.20634. View

Wittkamp G, Buerke B, Dziewas R, Ditt H, Seidensticker P, Heindel W . Whole brain perfused blood volume CT: visualization of infarcted tissue compared to quantitative perfusion CT. Acad Radiol. 2010; 17(4):427-32. DOI: 10.1016/j.acra.2009.11.005. View

Louis D, Ohgaki H, Wiestler O, Cavenee W, Burger P, Jouvet A . The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol. 2007; 114(2):97-109. PMC: 1929165. DOI: 10.1007/s00401-007-0243-4. View

Miles K, Charnsangavej C, Lee F, Fishman E, Horton K, Lee T . Application of CT in the investigation of angiogenesis in oncology. Acad Radiol. 2000; 7(10):840-50. DOI: 10.1016/s1076-6332(00)80632-7. View

Miles K . Functional computed tomography in oncology. Eur J Cancer. 2002; 38(16):2079-84. DOI: 10.1016/s0959-8049(02)00386-6. View

van Dijke C, Brasch R, Roberts T, Weidner N, Mathur A, Shames D . Mammary carcinoma model: correlation of macromolecular contrast-enhanced MR imaging characterizations of tumor microvasculature and histologic capillary density. Radiology. 1996; 198(3):813-8. DOI: 10.1148/radiology.198.3.8628876. View

10.

Rother J, Jonetz-Mentzel L, Fiala A, Reichenbach J, Herzau M, Kaiser W . Hemodynamic assessment of acute stroke using dynamic single-slice computed tomographic perfusion imaging. Arch Neurol. 2000; 57(8):1161-6. DOI: 10.1001/archneur.57.8.1161. View

11.

Jain R, Ellika S, Scarpace L, Schultz L, Rock J, Gutierrez J . Quantitative estimation of permeability surface-area product in astroglial brain tumors using perfusion CT and correlation with histopathologic grade. AJNR Am J Neuroradiol. 2008; 29(4):694-700. PMC: 7978188. DOI: 10.3174/ajnr.A0899. View

12.

Jain R, Scarpace L, Ellika S, Schultz L, Rock J, Rosenblum M . First-pass perfusion computed tomography: initial experience in differentiating recurrent brain tumors from radiation effects and radiation necrosis. Neurosurgery. 2007; 61(4):778-86. DOI: 10.1227/01.NEU.0000298906.48388.26. View

13.

Mnyusiwalla A, Aviv R, Symons S . Radiation dose from multidetector row CT imaging for acute stroke. Neuroradiology. 2009; 51(10):635-40. DOI: 10.1007/s00234-009-0543-6. View

14.

Murayama K, Katada K, Nakane M, Toyama H, Anno H, Hayakawa M . Whole-brain perfusion CT performed with a prototype 256-detector row CT system: initial experience. Radiology. 2008; 250(1):202-11. DOI: 10.1148/radiol.2501071809. View

15.

Burger P, Vogel F, Green S, Strike T . Glioblastoma multiforme and anaplastic astrocytoma. Pathologic criteria and prognostic implications. Cancer. 1985; 56(5):1106-11. DOI: 10.1002/1097-0142(19850901)56:5<1106::aid-cncr2820560525>3.0.co;2-2. View

16.

Gossmann A, Helbich T, Kuriyama N, Ostrowitzki S, Roberts T, Shames D . Dynamic contrast-enhanced magnetic resonance imaging as a surrogate marker of tumor response to anti-angiogenic therapy in a xenograft model of glioblastoma multiforme. J Magn Reson Imaging. 2002; 15(3):233-40. DOI: 10.1002/jmri.10072. View

17.

Ding B, Ling H, Chen K, Jiang H, Zhu Y . Comparison of cerebral blood volume and permeability in preoperative grading of intracranial glioma using CT perfusion imaging. Neuroradiology. 2006; 48(10):773-81. DOI: 10.1007/s00234-006-0120-1. View

18.

Cenic A, Nabavi D, Craen R, Gelb A, Lee T . A CT method to measure hemodynamics in brain tumors: validation and application of cerebral blood flow maps. AJNR Am J Neuroradiol. 2000; 21(3):462-70. PMC: 8174983. View

19.

Schramm P, Xyda A, Klotz E, Tronnier V, Knauth M, Hartmann M . Dynamic CT perfusion imaging of intra-axial brain tumours: differentiation of high-grade gliomas from primary CNS lymphomas. Eur Radiol. 2010; 20(10):2482-90. PMC: 2940017. DOI: 10.1007/s00330-010-1817-4. View

20.

Daldrup H, Shames D, Wendland M, Okuhata Y, Link T, Rosenau W . Correlation of dynamic contrast-enhanced MR imaging with histologic tumor grade: comparison of macromolecular and small-molecular contrast media. AJR Am J Roentgenol. 1998; 171(4):941-9. DOI: 10.2214/ajr.171.4.9762973. View