title: Reporting of quantitative oxygen mapping in EPR imaging.
abstract: Oxygen maps derived from electron paramagnetic resonance spectral-spatial imaging (EPRI) are based upon the relaxivity of molecular oxygen with paramagnetic spin probes. This technique can be combined with MRI to facilitate mapping of pO(2) values in specific anatomic locations with high precision. The co-registration procedure, which matches the physical and digital dimensions of EPR and MR images, may present the pO(2) map at the higher MRI resolution, exaggerating the spatial resolution of oxygen, making it difficult to precisely distinguish hypoxic regions from normoxic regions. The latter distinction is critical in monitoring the treatment of cancer by radiation and chemotherapy, since it is well-established that hypoxic regions are three or four times more resistant to treatment compared to normoxic regions. The aim of this article is to describe pO(2) maps based on the intrinsic resolution of EPRI. A spectral parameter that affects the intrinsic spatial resolution of EPRI is the full width at half maximum (FWHM) height of the gradient-free EPR absorption line in frequency-encoded imaging. In single point imaging too, the transverse relaxation times (T(2)(∗)) limit the resolution since the signal decays by exp(-t(p)/T(2)(∗)) where the delay time after excitation pulse, t(p), is related to the resolution. Although the spin densities of two point objects may be resolved at this separation, it is inadequate to evaluate quantitative changes of pO(2) levels since the linewidths are proportionately affected by pO(2). A spatial separation of at least twice this resolution is necessary to correctly identify a change in pO(2) level. In addition, the pO(2) values are blurred by uncertainties arising from spectral dimensions. Blurring due to noise and low resolution modulates the pO(2) levels at the boundaries of hypoxic and normoxic regions resulting in higher apparent pO(2) levels in hypoxic regions. Therefore, specification of intrinsic resolution and pO(2) uncertainties are necessary to interpret digitally processed pO(2) illustrations.
authors.affiliation: Radiation Biology Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA.
authors.forename: Sankaran
authors.initials: S
authors.lastname: Subramanian
authors.forename: Nallathamby
authors.initials: N
authors.lastname: Devasahayam
authors.forename: Alan
authors.initials: A
authors.lastname: McMillan
authors.forename: Shingo
authors.initials: S
authors.lastname: Matsumoto
authors.forename: Jeeva P
authors.initials: JP
authors.lastname: Munasinghe
authors.forename: Keita
authors.initials: K
authors.lastname: Saito
authors.forename: James B
authors.initials: JB
authors.lastname: Mitchell
authors.forename: Gadisetti V R
authors.initials: GV
authors.lastname: Chandramouli
authors.forename: Murali C
authors.initials: MC
authors.lastname: Krishna
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D004578:Electron Spin Resonance Spectroscopy / Q000379:methods*; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008956:Models, Chemical; D008958:Models, Molecular; D010092:Oximetry / Q000379:methods*; D010100:Oxygen / Q000032:analysis*
chemical_list: D010100:Oxygen