The Experts below are selected from a list of 984429 Experts worldwide ranked by ideXlab platform
Martin Fungisai Gerche - One of the best experts on this subject based on the ideXlab platform.
-
just a very expensive breathing training risk of respiratory artefacts in functional connectivity based real time fmri neurofeedback
NeuroImage, 2020Co-Authors: Franziska Weiss, Vera Zamoscik, Stephanie N L Schmid, Patrick Halli, Pete Kirsch, Martin Fungisai GercheAbstract:Abstract Real-time functional magnetic resonance imaging neurofeedback (rtfMRI NFB) is a promising method for Targeted regulation of pathological brain processes in mental disorders. But most NFB approaches so far have used relatively restricted regional activation as a Target, which might not address the complexity of the underlying network changes. Aiming towards advancing novel treatment tools for disorders like schizophrenia, we developed a large-scale network functional connectivity-based rtfMRI NFB approach Targeting dorsolateral prefrontal cortex and anterior cingulate cortex connectivity with the striatum. In a double-blind randomized yoke-controlled single-session feasibility study with N = 38 healthy controls, we identified strong associations between our connectivity estimates and physiological parameters reflecting the rate and regularity of breathing. These undesired artefacts are especially detrimental in rtfMRI NFB, where the same data serves as an online feedback signal and offline Analysis Target. To evaluate ways to control for the identified respiratory artefacts, we compared model-based physiological nuisance regression and global signal regression (GSR) and found that GSR was the most effective method in our data. Our results strongly emphasize the need to control for physiological artefacts in connectivity-based rtfMRI NFB approaches and suggest that GSR might be a useful method for online data correction for respiratory artefacts.
Stephanie N L Schmid - One of the best experts on this subject based on the ideXlab platform.
-
just a very expensive breathing training risk of respiratory artefacts in functional connectivity based real time fmri neurofeedback
NeuroImage, 2020Co-Authors: Franziska Weiss, Vera Zamoscik, Stephanie N L Schmid, Patrick Halli, Pete Kirsch, Martin Fungisai GercheAbstract:Abstract Real-time functional magnetic resonance imaging neurofeedback (rtfMRI NFB) is a promising method for Targeted regulation of pathological brain processes in mental disorders. But most NFB approaches so far have used relatively restricted regional activation as a Target, which might not address the complexity of the underlying network changes. Aiming towards advancing novel treatment tools for disorders like schizophrenia, we developed a large-scale network functional connectivity-based rtfMRI NFB approach Targeting dorsolateral prefrontal cortex and anterior cingulate cortex connectivity with the striatum. In a double-blind randomized yoke-controlled single-session feasibility study with N = 38 healthy controls, we identified strong associations between our connectivity estimates and physiological parameters reflecting the rate and regularity of breathing. These undesired artefacts are especially detrimental in rtfMRI NFB, where the same data serves as an online feedback signal and offline Analysis Target. To evaluate ways to control for the identified respiratory artefacts, we compared model-based physiological nuisance regression and global signal regression (GSR) and found that GSR was the most effective method in our data. Our results strongly emphasize the need to control for physiological artefacts in connectivity-based rtfMRI NFB approaches and suggest that GSR might be a useful method for online data correction for respiratory artefacts.
Vera Zamoscik - One of the best experts on this subject based on the ideXlab platform.
-
just a very expensive breathing training risk of respiratory artefacts in functional connectivity based real time fmri neurofeedback
NeuroImage, 2020Co-Authors: Franziska Weiss, Vera Zamoscik, Stephanie N L Schmid, Patrick Halli, Pete Kirsch, Martin Fungisai GercheAbstract:Abstract Real-time functional magnetic resonance imaging neurofeedback (rtfMRI NFB) is a promising method for Targeted regulation of pathological brain processes in mental disorders. But most NFB approaches so far have used relatively restricted regional activation as a Target, which might not address the complexity of the underlying network changes. Aiming towards advancing novel treatment tools for disorders like schizophrenia, we developed a large-scale network functional connectivity-based rtfMRI NFB approach Targeting dorsolateral prefrontal cortex and anterior cingulate cortex connectivity with the striatum. In a double-blind randomized yoke-controlled single-session feasibility study with N = 38 healthy controls, we identified strong associations between our connectivity estimates and physiological parameters reflecting the rate and regularity of breathing. These undesired artefacts are especially detrimental in rtfMRI NFB, where the same data serves as an online feedback signal and offline Analysis Target. To evaluate ways to control for the identified respiratory artefacts, we compared model-based physiological nuisance regression and global signal regression (GSR) and found that GSR was the most effective method in our data. Our results strongly emphasize the need to control for physiological artefacts in connectivity-based rtfMRI NFB approaches and suggest that GSR might be a useful method for online data correction for respiratory artefacts.
Franziska Weiss - One of the best experts on this subject based on the ideXlab platform.
-
just a very expensive breathing training risk of respiratory artefacts in functional connectivity based real time fmri neurofeedback
NeuroImage, 2020Co-Authors: Franziska Weiss, Vera Zamoscik, Stephanie N L Schmid, Patrick Halli, Pete Kirsch, Martin Fungisai GercheAbstract:Abstract Real-time functional magnetic resonance imaging neurofeedback (rtfMRI NFB) is a promising method for Targeted regulation of pathological brain processes in mental disorders. But most NFB approaches so far have used relatively restricted regional activation as a Target, which might not address the complexity of the underlying network changes. Aiming towards advancing novel treatment tools for disorders like schizophrenia, we developed a large-scale network functional connectivity-based rtfMRI NFB approach Targeting dorsolateral prefrontal cortex and anterior cingulate cortex connectivity with the striatum. In a double-blind randomized yoke-controlled single-session feasibility study with N = 38 healthy controls, we identified strong associations between our connectivity estimates and physiological parameters reflecting the rate and regularity of breathing. These undesired artefacts are especially detrimental in rtfMRI NFB, where the same data serves as an online feedback signal and offline Analysis Target. To evaluate ways to control for the identified respiratory artefacts, we compared model-based physiological nuisance regression and global signal regression (GSR) and found that GSR was the most effective method in our data. Our results strongly emphasize the need to control for physiological artefacts in connectivity-based rtfMRI NFB approaches and suggest that GSR might be a useful method for online data correction for respiratory artefacts.
Glaudemans, Andor W J M - One of the best experts on this subject based on the ideXlab platform.
-
99mTc-HYNIC-IL-2 scintigraphy to detect acute rejection in lung transplantation patients: a proof-of-concept study
2019Co-Authors: Telenga, Eef D, Van Der Bij Wim, De Vries, Erik F J, Verschuuren, Erik A M, Timens Wim, Luurtsema Gert, Slart, Riemer H J A, Signore Alberto, Glaudemans, Andor W J MAbstract:RATIONALE: Acute allograft rejection is one of the major complications after lung transplantation, and adequate and early recognition is important. Till now, the reference standard to detect acute rejection is the histopathological grading of transbronchial biopsies (TBBs). Acute rejection is characterised by high levels of activated T lymphocytes. Interleukin-2 (IL-2) binds specifically to high-affinity IL-2 receptors expressed on the cell membrane of activated T lymphocytes. The aim of this proof-of-concept study was to evaluate if non-invasive imaging with 99mTc-HYNIC-IL-2 is able to detect acute rejection after lung transplantation. METHODS: 99mTc-HYNIC-IL-2 scintigraphy (static, SPECT/CT of the lungs) was performed shortly before routine transbronchial biopsy (pathology as reference standard). Scans were scored as likely or unlikely for rejection, and semiquantitative Analysis (Target-to-background ratio) was performed. RESULTS: Thirteen patients were included of which 3 showed acute rejection at transbronchial biopsy; in 2 of these patients (scored as graded 2-3 at pathology), the scan was scored likely for rejection, and in 1 patient (scored grade 1 at pathology), the scan was scored unlikely. No correlation was found between biopsy results and semiquantitative Analysis. CONCLUSION: 99mTc-HYNIC-IL-2 scintigraphy proved to be a good technique to detect grade 2 and 3 acute rejection in a small sample population of patients after lung transplantation. Larger studies are necessary to really show the added value of this non-invasive specific imaging technique over transbronchial biopsy. Alternatively, imaging with the PET tracer 18F-IL-2 may be useful for this purpose
-
Tc-99m-HYNIC-IL-2 scintigraphy to detect acute rejection in lung transplantation patients: a proof-of-concept study
'Springer Science and Business Media LLC', 2019Co-Authors: Telenga, Eef D, Van Der Bij Wim, De Vries, Erik F J, Verschuuren, Erik A M, Timens Wim, Luurtsema Gert, Slart, Riemer H J A, Signore Alberto, Glaudemans, Andor W J MAbstract:RATIONALE: Acute allograft rejection is one of the major complications after lung transplantation, and adequate and early recognition is important. Till now, the reference standard to detect acute rejection is the histopathological grading of transbronchial biopsies (TBBs). Acute rejection is characterised by high levels of activated T lymphocytes. Interleukin-2 (IL-2) binds specifically to high-affinity IL-2 receptors expressed on the cell membrane of activated T lymphocytes. The aim of this proof-of-concept study was to evaluate if non-invasive imaging with 99mTc-HYNIC-IL-2 is able to detect acute rejection after lung transplantation. METHODS: 99mTc-HYNIC-IL-2 scintigraphy (static, SPECT/CT of the lungs) was performed shortly before routine transbronchial biopsy (pathology as reference standard). Scans were scored as likely or unlikely for rejection, and semiquantitative Analysis (Target-to-background ratio) was performed. RESULTS: Thirteen patients were included of which 3 showed acute rejection at transbronchial biopsy; in 2 of these patients (scored as graded 2-3 at pathology), the scan was scored likely for rejection, and in 1 patient (scored grade 1 at pathology), the scan was scored unlikely. No correlation was found between biopsy results and semiquantitative Analysis. CONCLUSION: 99mTc-HYNIC-IL-2 scintigraphy proved to be a good technique to detect grade 2 and 3 acute rejection in a small sample population of patients after lung transplantation. Larger studies are necessary to really show the added value of this non-invasive specific imaging technique over transbronchial biopsy. Alternatively, imaging with the PET tracer 18F-IL-2 may be useful for this purpose