Early visual ERPs show stable body-sensitive patterns over a 4-week test period

Event-related potential (ERP) studies feature among the most cited papers in the field of body representation, with recent research highlighting the potential of ERPs as neuropsychiatric biomarkers. Despite this, investigation into how reliable early visual ERPs and body-sensitive effects are over time has been overlooked. This study therefore aimed to assess the stability of early body-sensitive effects and visual P1, N1 and VPP responses. Participants were asked to identify pictures of their own bodies, other bodies and houses during an EEG test session that was completed at the same time, once a week, for four consecutive weeks. Results showed that amplitude and latency of early visual components and their associated body-sensitive effects were stable over the 4-week period. Furthermore, correlational analyses revealed that VPP component amplitude might be more reliable than VPP latency and specific electrode sites might be more robust indicators of body-sensitive cortical activity than others. These findings suggest that visual P1, N1 and VPP responses, alongside body-sensitive N1/VPP effects, are robust indications of neuronal activity. We conclude that these components are eligible to be considered as electrophysiological biomarkers relevant to body representation

Prostate cancer localization by novel magnetic resonance dispersion imaging

Diagnosis and focal treatment of prostate cancer, the most prevalent form of cancer in men, is hampered by the limits of current clinical imaging. Angiogenesis imaging is a promising option for detection and localization of prostate cancer. It can be imaged by dynamic contrast-enhanced (DCE) MRI, assessing microvascular permeability as an indicator for angiogenesis. However, information on microvascular architecture changes associated with angiogenesis is not available. This paper presents a new model enabling the combined assessment of microvascular permeability and architecture. After the intravenous injection of a gadolinium-chelate bolus, time-concentration curves (TCCs) are measured by DCE-MRI at each voxel. According to the convective dispersion equation, the microvascular architecture is reflected in the dispersion coefficient. A solution of this equation is therefore proposed to represent the intravascular blood plasma compartment in the Tofts model. Fitting the resulting model to TCCs measured at each voxel leads to the simultaneous generation of a dispersion and a permeability map. Measurement of an arterial input function is no longer required. Preliminary validation was performed by spatial comparison with the histological results in seven patients referred for radical prostatectomy. Cancer localization by the obtained dispersion maps provided an area under the receiver operating characteristic curve equal to 0.91. None of the standard DCE-MRI parametric maps could outperform this result, motivating towards an extended validation of the method, also aimed at investigating other forms of cancer with pronounced angiogenic developmen

DCE-MRI dispersion imaging for quantitative assessment of tumor angiogenesis

Based on the established link between cancer growth and angiogenesis [2], in this work we propose a new method for assessment of tumor angiogenesis by dynamic contrast-enhanced magnetic resonance dispersion imaging and we investigate the feasibility of the method for prostate cancer localization

Magnetic resonance dispersion imaging for localization of angiogenesis and cancer growth

Purpose: Cancer angiogenesis can be imaged by using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Pharmacokinetic modeling can be used to assess vascular perfusion and permeability, but the assessment of angiogenic changes in the microvascular architecture remains challenging. This article presents 2 models enabling the characterization of the microvascular architecture by DCE-MRI. Theory: The microvascular architecture is reflected in the dispersion coefficient according to the convective dispersion equation. A solution of this equation, combined with the Tofts model, permits defining a dispersion model for magnetic resonance imaging. A reduced dispersion model is also presented. Methods: The proposed models were evaluated for prostate cancer diagnosis. Dynamic contrast-enhanced magnetic resonance imaging was performed, and concentration-time curves were calculated in each voxel. The simultaneous generation of parametric maps related to permeability and dispersion was obtained through model fitting. A preliminary validation was carried out through comparison with the histology in 15 patients referred for radical prostatectomy. Results: Cancer localization was accurate with both dispersion models, with an area under the receiver operating characteristic curve greater than 0.8. None of the compared parameters, aimed at assessing vascular permeability and perfusion, showed better results. Conclusions: A new DCE-MRI method is proposed to characterize the microvascular architecture through the assessment of intravascular dispersion, without the need for separate arterial-input-function estimation. The results are promising and encourage further research

Magnetic resonance dispersion imaging for localization of angiogenesis and cancer growth

Purpose: Cancer angiogenesis can be imaged by using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Pharmacokinetic modeling can be used to assess vascular perfusion and permeability, but the assessment of angiogenic changes in the microvascular architecture remains challenging. This article presents 2 models enabling the characterization of the microvascular architecture by DCE-MRI. Theory: The microvascular architecture is reflected in the dispersion coefficient according to the convective dispersion equation. A solution of this equation, combined with the Tofts model, permits defining a dispersion model for magnetic resonance imaging. A reduced dispersion model is also presented. Methods: The proposed models were evaluated for prostate cancer diagnosis. Dynamic contrast-enhanced magnetic resonance imaging was performed, and concentration-time curves were calculated in each voxel. The simultaneous generation of parametric maps related to permeability and dispersion was obtained through model fitting. A preliminary validation was carried out through comparison with the histology in 15 patients referred for radical prostatectomy. Results: Cancer localization was accurate with both dispersion models, with an area under the receiver operating characteristic curve greater than 0.8. None of the compared parameters, aimed at assessing vascular permeability and perfusion, showed better results. Conclusions: A new DCE-MRI method is proposed to characterize the microvascular architecture through the assessment of intravascular dispersion, without the need for separate arterial-input-function estimation. The results are promising and encourage further research