Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Fractional anisotropy derived from the single-tensor model (FADTI) in diffusion MRI (dMRI) is the most widely used metric to characterize white matter (WM) micro-architecture in disease, despite known limitations in regions with extensive fiber crossing. Due to time constraints and interest in collecting multiple clinical samples and MRI scan types, complex HARDI acquisition protocols are rare in clinical population dMRI studies. Under such constraints, the tensor distribution function (TDF) can still be used to reconstruct multiple underlying fibers by representing the diffusion profile as a probabilistic mixture of tensors. Here  set out to better profile WM deficits in Alzheimer's disease (AD) by comparing the standard FADTI and TDF-derived FA (FATDF) in (1) WM network connectivity and voxel-based analyses of diagnostic differences, and (2) for picking up associations with clinical cognitive ratings and hippocampal volume. Ultimately, the TDF approach may be more sensitive and accurate than corresponding DTI-derived measures.
['Talia M. Nir', 'Artemis Zavaliangos-Petropulu', 'Neda Jahanshad', 'Julio E. Villalon-Reina', 'Liang Zhan', 'Alex D. Leow', 'Matt A. Bernstein', 'Clifford R. Jack', 'Michael W. Weiner', 'Paul M. Thompson']
I am writing a research paper on a idea Diffusion tensor distribution function metrics boost power to detect deficits in Alzheimer's disease
[{"from": "human", "value": "I am writing a research paper on a idea Diffusion tensor distribution function metrics boost power to detect deficits in Alzheimer's disease"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Fractional anisotropy derived from the single-tensor model (FADTI) in diffusion MRI (dMRI) is the most widely used metric to characterize white matter (WM) micro-architecture in disease, despite known limitations in regions with extensive fiber crossing. Due to time constraints and interest in collecting multiple clinical samples and MRI scan types, complex HARDI acquisition protocols are rare in clinical population dMRI studies. Under such constraints, the tensor distribution function (TDF) can still be used to reconstruct multiple underlying fibers by representing the diffusion profile as a probabilistic mixture of tensors. Here  set out to better profile WM deficits in Alzheimer's disease (AD) by comparing the standard FADTI and TDF-derived FA (FATDF) in (1) WM network connectivity and voxel-based analyses of diagnostic differences, and (2) for picking up associations with clinical cognitive ratings and hippocampal volume. Ultimately, the TDF approach may be more sensitive and accurate than corresponding DTI-derived measures."}]