Dynamic contrast enhancement in magnetic resonance imaging (DCE-MRI) is a promising tool for the clinical diagnosis of tumors, whose implementation may be improved through the use of suitable hemodynamic models. If one prefers to avoid assumptions about the tumor physiology, empirical fitting functions may be adopted. For this purpose, in this paper we discuss the exploitation of a recently proposed phenomenological universalities (PUN) formalism. In fact, we show that a novel PUN class may be used to describe the time-signal intensity curves in both healthy and tumoral tissues, discriminating between the two cases and thus potentially providing a convenient diagnostic tool. The proposed approach is applied to analysis of the DCE-MRI data relative to a study group composed of ten patients with spine tumors.

Phenomenological universalities: A novel tool for the analysis of dynamic contrast enhancement in magnetic resonance imaging

Mazzetti, S.;REGGE, Daniele;
2011-01-01

Abstract

Dynamic contrast enhancement in magnetic resonance imaging (DCE-MRI) is a promising tool for the clinical diagnosis of tumors, whose implementation may be improved through the use of suitable hemodynamic models. If one prefers to avoid assumptions about the tumor physiology, empirical fitting functions may be adopted. For this purpose, in this paper we discuss the exploitation of a recently proposed phenomenological universalities (PUN) formalism. In fact, we show that a novel PUN class may be used to describe the time-signal intensity curves in both healthy and tumoral tissues, discriminating between the two cases and thus potentially providing a convenient diagnostic tool. The proposed approach is applied to analysis of the DCE-MRI data relative to a study group composed of ten patients with spine tumors.
2011
56
3
573
586
http://iopscience.iop.org/0031-9155/56/3/004/pdf/0031-9155_56_3_004.pdf
Humans; Image Enhancement; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Spinal Cord Neoplasms; Time Factors; Contrast Media; Radiology, Nuclear Medicine and Imaging; Radiological and Ultrasound Technology
Gliozzi, A.S; Mazzetti, S.; Delsanto, P.P.; Regge, D.; Stasi, M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1548809
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