The Visible Human Project male CAD based computational phantom and its use in bioelectromagnetic simulations

Abstract

Use of numerical simulation tools to provide qualitative estimates on electromagnetic safety, characterize antenna performance for WBAN applications and facilitate ground breaking research on diagnostic and therapeutic bioelectrical solutions has steadily grown over the past twenty years. However, the accuracy and applicability of such tools are directly proportional to the fidelity of the model used during the simulation. This paper describes the construction of a new CAD based male computational phantom, the Visible Human Project (VHP)-Male model, suitable for use in major commercial electromagnetics simulation packages.

Noninvasive Electrical Stimulation Neuromodulation and Digital Brain Technology: A Review

“…Through verification, in simple localization simulation, the model error is greater than 1 cm, and the practical significance of the model is not great [ 78 , 79 ]. An attempt to build a real human brain simulation model through a digital human model has been conducted, considering the problems with a simplified model dataset [ 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 ] ( Figure 7 ).…”

“…Moreover, the software application is mainly centralized on MRI coil design and electromagnetic simulation; these procedures cannot be used to achieve electrical stimulation simulation design. Japanese NII [ 93 ], Korean ETRI [ 94 , 95 , 96 , 97 ], British NRPB [ 98 ], German Munchen, CST AG [ 98 , 100 , 101 ], American Penn State [ 99 ], U Texas Austin, and others [ 82 , 83 , 84 , 85 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 ] have also developed a digital human model. However, because of incomplete public data and a rough data segmentation scheme, numerous singularities are generated after data segmentation; therefore, it is difficult to achieve the reverse modeling of human organs.…”

“…Only three electromagnetic theoretical models of electrical stimulation neuromodulation have been established using the above data. The first report is from 2014 when Alvaro Pascal-Leone’s research team at Worcester Polytechnic Institute in the USA built the FEM model of the head through a series of simplifications using the public data of the Visible Human Project ( Figure 9 ) [ 82 , 111 , 114 ]. This model, through simplification and division, has been used to construct 14 organs including skin, fat, white matter of the brain, and gray matter of the brain.…”

“…Only thin and uneven closed cerebrospinal fluid shells and ventricles were considered in the subarachnoid space, causing difficulties in locating and stimulating special target areas during electrical stimulation and the impact analysis of the correlation between tissues. Second, in 2016, the City University of New York and the Stefan Haufe research team of Columbia University used the Brain VISA software developed based on the US public database [ 82 , 111 , 114 ] to divide the head data into five parts: skin, skull, cerebrospinal fluid, gray matter, and white matter, and added a cavity through thickening to achieve head modeling ( Figure 10 ) [ 86 ]. The team could analyze the effect of electrical stimulation on the brain and the location of EEG source signals using this model.…”

“…However, because of the oversimplification of this model, its calculation results are not very accurate. The most recent report is from 2019 when Myles McLaughlin’s team at Katholieke Universiteit Leuven simplified the head data into five parts, namely the skin, skull, cerebrospinal fluid, gray matter, and white matter based on the US public database [ 82 , 111 , 114 ] referencing the Sim4Life data segmentation method developed by Swiss [ 88 , 89 ] to analyze the stimulation effect of AC stimulation on specific areas of the brain ( Figure 5 ) [ 65 ]. Effectively analyzing the mechanism of signal propagation in the brain was impossible because the model was too simple.…”

Noninvasive Electrical Stimulation Neuromodulation and Digital Brain Technology: A Review

“…Through verification, in simple localization simulation, the model error is greater than 1 cm, and the practical significance of the model is not great [ 78 , 79 ]. An attempt to build a real human brain simulation model through a digital human model has been conducted, considering the problems with a simplified model dataset [ 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 ] ( Figure 7 ).…”

“…Moreover, the software application is mainly centralized on MRI coil design and electromagnetic simulation; these procedures cannot be used to achieve electrical stimulation simulation design. Japanese NII [ 93 ], Korean ETRI [ 94 , 95 , 96 , 97 ], British NRPB [ 98 ], German Munchen, CST AG [ 98 , 100 , 101 ], American Penn State [ 99 ], U Texas Austin, and others [ 82 , 83 , 84 , 85 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 ] have also developed a digital human model. However, because of incomplete public data and a rough data segmentation scheme, numerous singularities are generated after data segmentation; therefore, it is difficult to achieve the reverse modeling of human organs.…”

“…Only three electromagnetic theoretical models of electrical stimulation neuromodulation have been established using the above data. The first report is from 2014 when Alvaro Pascal-Leone’s research team at Worcester Polytechnic Institute in the USA built the FEM model of the head through a series of simplifications using the public data of the Visible Human Project ( Figure 9 ) [ 82 , 111 , 114 ]. This model, through simplification and division, has been used to construct 14 organs including skin, fat, white matter of the brain, and gray matter of the brain.…”

“…Only thin and uneven closed cerebrospinal fluid shells and ventricles were considered in the subarachnoid space, causing difficulties in locating and stimulating special target areas during electrical stimulation and the impact analysis of the correlation between tissues. Second, in 2016, the City University of New York and the Stefan Haufe research team of Columbia University used the Brain VISA software developed based on the US public database [ 82 , 111 , 114 ] to divide the head data into five parts: skin, skull, cerebrospinal fluid, gray matter, and white matter, and added a cavity through thickening to achieve head modeling ( Figure 10 ) [ 86 ]. The team could analyze the effect of electrical stimulation on the brain and the location of EEG source signals using this model.…”

“…However, because of the oversimplification of this model, its calculation results are not very accurate. The most recent report is from 2019 when Myles McLaughlin’s team at Katholieke Universiteit Leuven simplified the head data into five parts, namely the skin, skull, cerebrospinal fluid, gray matter, and white matter based on the US public database [ 82 , 111 , 114 ] referencing the Sim4Life data segmentation method developed by Swiss [ 88 , 89 ] to analyze the stimulation effect of AC stimulation on specific areas of the brain ( Figure 5 ) [ 65 ]. Effectively analyzing the mechanism of signal propagation in the brain was impossible because the model was too simple.…”

Noninvasive Electrical Stimulation Neuromodulation and Digital Brain Technology: A Review

“…Through verification, in simple localization simulation, the model error is greater than 1 cm, and the practical significance of the model is not great [ 78 , 79 ]. An attempt to build a real human brain simulation model through a digital human model has been conducted, considering the problems with a simplified model dataset [ 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 ] ( Figure 7 ).…”

“…Moreover, the software application is mainly centralized on MRI coil design and electromagnetic simulation; these procedures cannot be used to achieve electrical stimulation simulation design. Japanese NII [ 93 ], Korean ETRI [ 94 , 95 , 96 , 97 ], British NRPB [ 98 ], German Munchen, CST AG [ 98 , 100 , 101 ], American Penn State [ 99 ], U Texas Austin, and others [ 82 , 83 , 84 , 85 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 ] have also developed a digital human model. However, because of incomplete public data and a rough data segmentation scheme, numerous singularities are generated after data segmentation; therefore, it is difficult to achieve the reverse modeling of human organs.…”

“…Only three electromagnetic theoretical models of electrical stimulation neuromodulation have been established using the above data. The first report is from 2014 when Alvaro Pascal-Leone’s research team at Worcester Polytechnic Institute in the USA built the FEM model of the head through a series of simplifications using the public data of the Visible Human Project ( Figure 9 ) [ 82 , 111 , 114 ]. This model, through simplification and division, has been used to construct 14 organs including skin, fat, white matter of the brain, and gray matter of the brain.…”

“…Only thin and uneven closed cerebrospinal fluid shells and ventricles were considered in the subarachnoid space, causing difficulties in locating and stimulating special target areas during electrical stimulation and the impact analysis of the correlation between tissues. Second, in 2016, the City University of New York and the Stefan Haufe research team of Columbia University used the Brain VISA software developed based on the US public database [ 82 , 111 , 114 ] to divide the head data into five parts: skin, skull, cerebrospinal fluid, gray matter, and white matter, and added a cavity through thickening to achieve head modeling ( Figure 10 ) [ 86 ]. The team could analyze the effect of electrical stimulation on the brain and the location of EEG source signals using this model.…”

“…However, because of the oversimplification of this model, its calculation results are not very accurate. The most recent report is from 2019 when Myles McLaughlin’s team at Katholieke Universiteit Leuven simplified the head data into five parts, namely the skin, skull, cerebrospinal fluid, gray matter, and white matter based on the US public database [ 82 , 111 , 114 ] referencing the Sim4Life data segmentation method developed by Swiss [ 88 , 89 ] to analyze the stimulation effect of AC stimulation on specific areas of the brain ( Figure 5 ) [ 65 ]. Effectively analyzing the mechanism of signal propagation in the brain was impossible because the model was too simple.…”

Noninvasive Electrical Stimulation Neuromodulation and Digital Brain Technology: A Review

“…Through verification, in simple localization simulation, the model error is greater than 1 cm, and the practical significance of the model is not great [ 78 , 79 ]. An attempt to build a real human brain simulation model through a digital human model has been conducted, considering the problems with a simplified model dataset [ 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 ] ( Figure 7 ).…”

“…Moreover, the software application is mainly centralized on MRI coil design and electromagnetic simulation; these procedures cannot be used to achieve electrical stimulation simulation design. Japanese NII [ 93 ], Korean ETRI [ 94 , 95 , 96 , 97 ], British NRPB [ 98 ], German Munchen, CST AG [ 98 , 100 , 101 ], American Penn State [ 99 ], U Texas Austin, and others [ 82 , 83 , 84 , 85 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 ] have also developed a digital human model. However, because of incomplete public data and a rough data segmentation scheme, numerous singularities are generated after data segmentation; therefore, it is difficult to achieve the reverse modeling of human organs.…”

“…Only three electromagnetic theoretical models of electrical stimulation neuromodulation have been established using the above data. The first report is from 2014 when Alvaro Pascal-Leone’s research team at Worcester Polytechnic Institute in the USA built the FEM model of the head through a series of simplifications using the public data of the Visible Human Project ( Figure 9 ) [ 82 , 111 , 114 ]. This model, through simplification and division, has been used to construct 14 organs including skin, fat, white matter of the brain, and gray matter of the brain.…”

“…Only thin and uneven closed cerebrospinal fluid shells and ventricles were considered in the subarachnoid space, causing difficulties in locating and stimulating special target areas during electrical stimulation and the impact analysis of the correlation between tissues. Second, in 2016, the City University of New York and the Stefan Haufe research team of Columbia University used the Brain VISA software developed based on the US public database [ 82 , 111 , 114 ] to divide the head data into five parts: skin, skull, cerebrospinal fluid, gray matter, and white matter, and added a cavity through thickening to achieve head modeling ( Figure 10 ) [ 86 ]. The team could analyze the effect of electrical stimulation on the brain and the location of EEG source signals using this model.…”

“…However, because of the oversimplification of this model, its calculation results are not very accurate. The most recent report is from 2019 when Myles McLaughlin’s team at Katholieke Universiteit Leuven simplified the head data into five parts, namely the skin, skull, cerebrospinal fluid, gray matter, and white matter based on the US public database [ 82 , 111 , 114 ] referencing the Sim4Life data segmentation method developed by Swiss [ 88 , 89 ] to analyze the stimulation effect of AC stimulation on specific areas of the brain ( Figure 5 ) [ 65 ]. Effectively analyzing the mechanism of signal propagation in the brain was impossible because the model was too simple.…”