This study received significant support and modeling assistance from the R&#38;D department of Beijing Intelligent Entropy Science &#38; Technology Co Ltd., Beijing, China.

This study was approved by the Institutional Review Board of Beijing Dongzhimen Hospital, Beijing, China. An MRI scanner was used with pulsed ASL (PASL) sequence based on turbo gradient spin echo (TGSE) for 3D arterial spin labeling (3D-ASL) with the following parameters: TR 4000 ms, TE 25 ms, bolus duration 700 ms, inversion time 1990 ms. The software tools used in this research are listed in the Table of Materials.
1. Data collection and preparation
NOTE: The variance in parameters remains unaffected by the research approach. Both DICOM and NIFTI formats are used for storing digital medical imaging data, with DICOM being the usual output from clinical imaging devices. However, the NIFTI format is often preferred for computational convenience in research activities. Converting from DICOM to NIFTI is a straightforward and common practice17. In this study, authentic DICOM data were acquired and converted into NIFTI format. The data was acquired using a 1.5 Tesla MRI scanner. In the cross-image registration process of this study, the fluid-attenuated inversion recovery (FLAIR) sequence was mainly used and fused with CBF images. The CBF Atlas tool (Table of Materials) used in this study is commercial software.
<ol>
	<li>Copy data to the designated working directory.
	<ol>
		<li>Copy all NIFTI data to a customized working directory. 
		NOTE: The working directory is the same in the operating system and MATLAB. The research follows the Right Anterior Superior (RAS) orientation standard.</li>
		<li>Go to the directory housing the data within MATLAB&#39;s current working directory, and use the niftiread function to load FLAIR data into the workspace. Use the size function to check the dimensions of the FLAIR sequence. Call the Flair_Slice command to view the FLAIR sequence (as shown in Figure 1). Use the specific commands as follows: 
		FLAIR_XLF = niftiread(&#39;FLAIR_XFL.nii&#39;); 
		size(FLAIR_XLF) 
		&#8203;Flair_Slice(FLAIR_XLF);</li>
		<li>Refer to Figure 1 for an image of the interactive graphic user interface (GUI) for the FLAIR sequence. Use the bottom scroll bar to quickly browse the different sequences.</li>
	</ol>
	</li>
	<li>Quickly check images of CBF.
	<ol>
		<li>Use the niftiread function to load CBF data into the workspace. Use the size function to check the dimensions of the CBF sequence. Call the CBF_Slice command to view the CBF sequence (as shown in Figure 2). Use the specific commands as follows: 
		CBF_XLF = niftiread(&#39;CBF_XFL.nii&#39;); 
		size(CBF_XLF) 
		CBF_Slice(CBF_XLF);</li>
		<li>Refer to Figure 2 for an interactive GUI screenshot of the CBF sequence. Use the bottom scroll bar to quickly browse the different sequences. 
		NOTE: In Figure 2, the CBF value range is usually 0-120 mL/100 g/min. Figure 2 uses a color map to represent different CBF levels in different colors.</li>
	</ol>
	</li>
</ol>
2. Segmentation of cerebral functional regions from FLAIR sequence
NOTE: The FLAIR sequence serves as both structural imaging and provides excellent pathological diagnostic capabilities. Therefore, fusing FLAIR with CBF holds important diagnostic value in clinics. This study segments major cerebral functional regions from the FLAIR sequence.
<ol>
	<li>In the workspace, call the FLAIR_Segment function and run the pretrained 3-D U-Net-based image segmentation program to automatically generate triplanar views of cerebral functional regions segmentation, as shown in Figure 3. Each color in Figure 3 represents a distinct functional region.</li>
	<li>For real-time inspection of different cerebral functional regions, use the crosshair interaction (Figure 3). Click and drag the center of the crosshair for an arbitrary 3D examination of the reconstructed brain anatomy. 
	NOTE: The GUI in Figure 3 also enables adjustment of the grayscale intensity range, contrast, and brightness of the triplanar views.</li>
	<li>Press and drag the left mouse button over any region of the images for real-time modification of brightness and contrast levels. Release the mouse button to confirm and finalize the adjustments.</li>
</ol>
3. Triplanar views of CBF distribution across cerebral functional regions
NOTE: Examining CBF distribution across different cerebral functional regions facilitates precise clinical judgments of patient conditions. Under the functional region framework from Figure 3, incorporating the exact CBF values from the CBF sequence and presenting them in triplanar views allows comprehensive physician inspection.
<ol>
	<li>Call the CBF_triplanar function to generate the triplanar GUI view shown in Figure 4, displaying CBF spatial distribution across functional regions. Move the crosshair to allow examination of CBF distribution in regions of interest.</li>
	<li>Click the Data Tips button on the top right corner of the GUI to display the CBF values at any position.</li>
	<li>Press and drag the left mouse button over any region of the images for real-time modification of brightness and contrast levels. Release the mouse button to confirm and finalize the adjustments.</li>
</ol>
4. CBF atlas across major cerebral functional regions
NOTE: Normalizing the CBF probability distributions across different functional regions generates the Cerebral Functional Regions CBF Atlas, expressing the CBF levels across cerebral functional regions of the subject.
<ol>
	<li>Call the CBF_Atlas function to convert the CBF spatial distribution shown in Figure 4 into a CBF Atlas (as shown in Figure 5). 
	NOTE: In Figure 5, the x-axis represents different cerebral functional regions, and the y-axis represents different CBF levels; the different colors denote different probability levels (the redder the color, the more voxels present).</li>
	<li>Click the Zoom In/Out button on the top right of the GUI shown in Figure 5 to scale partial images. 
	NOTE: The curve in Figure 5 connects the average CBF across regions.</li>
</ol>
5. Significant differences in CBF_Atlas between healthy subjects and CCI patients
NOTE: Using the same process described in sections 1-4, the average CBF values across different cerebral functional regions can be obtained for CCI patients.
<ol>
	<li>Utilize the CBF_Compare function to generate a comparative plot of the CBF curve from a healthy subject versus a CCI patient (Figure 6).</li>
	<li>Observe the significant differences between the patient&#39;s CBF curve (colored in black) and the healthy curve (colored in red) (Figure 6). Identify the functional regions with more pronounced CBF drops in the patient. Integrating step 3.3, re-examine the regions where the patient performed worse compared to the other regions. 
	NOTE: Step 3.3 allows for the viewing of the patient&#39;s CBF levels in three-dimensional space, meaning doctors can utilize the triplanar GUI view shown in Figure 4 to examine the CBF at any position of the patient. Here, the degree of CBF decline varies in different locations for CCI patients. Doctors can revisit Figure 4 to focus on brain regions with significant CBF decline.</li>
	<li>Use the icons in the GUI&#39;s upper right corner (Figure 5) to access functions such as zooming out, zooming in, returning to the global view, and marking the coordinates of the selected pixel. 
	NOTE: Using the same principle, pre-treatment and post-treatment results from the same patient can also be compared using the approach in Figure 6 to evaluate clinical efficacy over time.</li>
</ol>

MRI-Arterial Spin Labeling Integration to Detect and Monitor Cerebral Blood Flow 

<ol><li>Rodriguez, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Regional+cerebral+blood+flow+in+chronic+stroke+patients%5BTitle%5D)+AND+%22Stroke%22%5BJournal%5D)">Regional cerebral blood flow in chronic stroke patients.</a> Stroke. 24 (1), 94-99 (1993).</li>
<li>Kwok, C. H. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Cognition+and+cerebral+blood+flow+after+extracranial+carotid+revascularization+for+carotid+atherosclerosis%3A+A+systematic+review%5BTitle%5D)+AND+%22Clin+Ther%22%5BJournal%5D)">Cognition and cerebral blood flow after extracranial carotid revascularization for carotid atherosclerosis: A systematic review.</a> Clin Ther. 45 (11), 1069-1076 (2023).</li>
<li>Togao, O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Arterial+spin+labeling-based+MR+angiography+for+cerebrovascular+diseases%3A+Principles+and+clinical+applications%5BTitle%5D)+AND+%22J+Magn+Reson+Imaging%22%5BJournal%5D)">Arterial spin labeling-based MR angiography for cerebrovascular diseases: Principles and clinical applications.</a> J Magn Reson Imaging. , (2023).</li>
<li>Haidar, H., Majzoub, R. E., Hajeer, S., Abbas, L. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Arterial+spin+labeling+%28ASL-MRI%29+versus+fluorodeoxyglucose-PET+%28FDG-PET%29+in+diagnosing+dementia%3A+a+systematic+review+and+meta-analysis%5BTitle%5D)+AND+%22BMC+Neurol%22%5BJournal%5D)">Arterial spin labeling (ASL-MRI) versus fluorodeoxyglucose-PET (FDG-PET) in diagnosing dementia: a systematic review and meta-analysis.</a> BMC Neurol. 23 (1), 385(2023).</li>
<li>Xu, Y., Tan, G., Chen, D., Liu, J., Zhou, Z., Liu, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Arterial+spin+labeling+perfusion+MRI+applications+in+drug-resistant+epilepsy+and+epileptic+emergency%5BTitle%5D)+AND+%22Acta+Epileptol%22%5BJournal%5D)">Arterial spin labeling perfusion MRI applications in drug-resistant epilepsy and epileptic emergency.</a> Acta Epileptol. 5, 23(2023).</li>
<li>Xie, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Abnormalities+of+cerebral+blood+flow+and+the+regional+brain+function+in+Parkinson%27s+disease%3A+a+systematic+review+and+multimodal+neuroimaging+meta-analysis%5BTitle%5D)+AND+%22Front+Neurol%22%5BJournal%5D)">Abnormalities of cerebral blood flow and the regional brain function in Parkinson's disease: a systematic review and multimodal neuroimaging meta-analysis.</a> Front Neurol. 14, 1289934(2023).</li>
<li>Tenberg, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Dysautonomia+and+activity+in+the+early+stroke+recovery+period%5BTitle%5D)+AND+%22Neurol+Sci%22%5BJournal%5D)">Dysautonomia and activity in the early stroke recovery period.</a> Neurol Sci. 45 (6), 2505-2521 (2024).</li>
<li>Joshi, D., Prasad, S., Saini, J., Ingalhalikar, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Role+of+arterial+spin+labeling+%28ASL%29+images+in+Parkinson%27s+disease+%28PD%29%3A+A+systematic+review%5BTitle%5D)+AND+%22Acad+Radiol%22%5BJournal%5D)">Role of arterial spin labeling (ASL) images in Parkinson's disease (PD): A systematic review.</a> Acad Radiol. 30 (8), 1695-1708 (2023).</li>
<li>Mohamed, A. Z., Kwiatek, R., Fante, P. D., Calhoun, V. D., Lagopoulos, J., Shan, Z. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Functional+MRI+of+the+brainstem+for+assessing+its+autonomic+functions%3A+From+imaging+parameters+and+analysis+to+functional+atlas%5BTitle%5D)+AND+%22J+Magn+Reson+Imaging%22%5BJournal%5D)">Functional MRI of the brainstem for assessing its autonomic functions: From imaging parameters and analysis to functional atlas.</a> J Magn Reson Imaging. , (2024).</li>
<li>Vanherle, L., Matuskova, H., Don-Doncow, N., Uhl, F. E., Meissner, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Improving+cerebrovascular+function+to+increase+neuronal+recovery+in+neurodegeneration+associated+to+cardiovascular+disease%5BTitle%5D)+AND+%22Front+Cell+Dev+Biol%22%5BJournal%5D)">Improving cerebrovascular function to increase neuronal recovery in neurodegeneration associated to cardiovascular disease.</a> Front Cell Dev Biol. 8, 53(2020).</li>
<li>Fujimura, M., Tominaga, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Significance+of+cerebral+blood+flow+analysis+in+the+acute+stage+after+revascularization+surgery+for+Moyamoya+disease%5BTitle%5D)+AND+%22Neurol+Med+Chir+%28Tokyo%29%22%5BJournal%5D)">Significance of cerebral blood flow analysis in the acute stage after revascularization surgery for Moyamoya disease.</a> Neurol Med Chir (Tokyo). 55 (10), 775-781 (2015).</li>
<li>Østergaard, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+role+of+the+microcirculation+in+delayed+cerebral+ischemia+and+chronic+degenerative+changes+after+subarachnoid+hemorrhage%5BTitle%5D)+AND+%22J+Cereb+Blood+Flow+Metab%22%5BJournal%5D)">The role of the microcirculation in delayed cerebral ischemia and chronic degenerative changes after subarachnoid hemorrhage.</a> J Cereb Blood Flow Metab. 33 (12), 1825-1837 (2013).</li>
<li>Mankoo, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+role+of+the+autonomic+nervous+system+in+cerebral+blood+flow+regulation+in+stroke%3A+A+review%5BTitle%5D)+AND+%22Auton+Neurosci%22%5BJournal%5D)">The role of the autonomic nervous system in cerebral blood flow regulation in stroke: A review.</a> Auton Neurosci. 246, 103082(2023).</li>
<li>Yang, X., Qiang, Q., Li, N., Feng, P., Wei, W., Hölscher, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Neuroprotective+mechanisms+of+glucagon-like+peptide-1-based+therapies+in+ischemic+stroke%3A+An+update+based+on+preclinical+research%5BTitle%5D)+AND+%22Front+Neurol%22%5BJournal%5D)">Neuroprotective mechanisms of glucagon-like peptide-1-based therapies in ischemic stroke: An update based on preclinical research.</a> Front Neurol. 13, 844697(2022).</li>
<li>Ho, M. -L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Arterial+spin+labeling%3A+Clinical+applications%5BTitle%5D)+AND+%22J+Neuroradiol%22%5BJournal%5D)">Arterial spin labeling: Clinical applications.</a> J Neuroradiol. 45 (5), 276-289 (2018).</li>
<li>Sforza, M., Bianchini, E., Alivernini, D., Salvetti, M., Pontieri, F. E., Sette, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+impact+of+cerebral+vasomotor+reactivity+on+cerebrovascular+diseases+and+cognitive+impairment%5BTitle%5D)+AND+%22J+Neural+Transm+%28Vienna%29%22%5BJournal%5D)">The impact of cerebral vasomotor reactivity on cerebrovascular diseases and cognitive impairment.</a> J Neural Transm (Vienna). 129 (11), 1321-1330 (2022).</li>
<li>Elhadad, A., Jamjoom, M., Abulkasim, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Reduction+of+NIFTI+files+storage+and+compression+to+facilitate+telemedicine+services+based+on+quantization+hiding+of+downsampling+approach%5BTitle%5D)+AND+%22Sci+Rep%22%5BJournal%5D)">Reduction of NIFTI files storage and compression to facilitate telemedicine services based on quantization hiding of downsampling approach.</a> Sci Rep. 14 (1), 5168(2024).</li>
<li>Gonzalez-Ortiz, F., Kac, P. R., Brum, W. S., Zetterberg, H., Blennow, K., Karikari, T. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Plasma+phospho-tau+in+Alzheimer%27s+disease%3A+towards+diagnostic+and+therapeutic+trial+applications%5BTitle%5D)+AND+%22Mol+Neurodegener%22%5BJournal%5D)">Plasma phospho-tau in Alzheimer's disease: towards diagnostic and therapeutic trial applications.</a> Mol Neurodegener. 18 (1), 18(2023).</li>
<li>Magliozzi, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((CSF+parvalbumin+levels+reflect+interneuron+loss+linked+with+cortical+pathology+in+multiple+sclerosis%5BTitle%5D)+AND+%22Ann+Clin+Transl+Neurol%22%5BJournal%5D)">CSF parvalbumin levels reflect interneuron loss linked with cortical pathology in multiple sclerosis.</a> Ann Clin Transl Neurol. 8 (5), 534-547 (2021).</li>
<li>Kawano, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Aging+and+sex+differences+in+brain+volume+and+cerebral+blood+flow%5BTitle%5D)+AND+%22Aging+Dis%22%5BJournal%5D)">Aging and sex differences in brain volume and cerebral blood flow.</a> Aging Dis. , (2023).</li>
<li>Jia, R., Solé-Guardia, G., Kiliaan, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Blood-brain+barrier+pathology+in+cerebral+small+vessel+disease%5BTitle%5D)+AND+%22Neural+Regen+Res%22%5BJournal%5D)">Blood-brain barrier pathology in cerebral small vessel disease.</a> Neural Regen Res. 19 (6), 1233-1240 (2023).</li>
</ol>

The software tool CBF Atlas V1.0 is a product of Beijing Intelligent Entropy Science &amp; Technology Co., Ltd. The intellectual property rights of this software tool belong to the company. The authors have no conflicts of interest to declare.

The key steps (sections 3 and 4) constitute the basis for constructing the CBF Atlas, quantifying CBF distribution across cerebral functional regions. Step 4.2 explicitly delineates CBF levels for each brain area, pioneering a new technique. This not only provides physicians with a global view of patient CBF but also quantitative measurements of individual functional regions. Step 5.1&#160;demonstrates that the CBF Atlas holds substantial clinical diagnostic utility distinguishing CCI from healthy controls.
<p class=...

In the realm of neuroimaging, the quest for precise, noninvasive tools to assess cerebral function and pathology remains paramount. Among these, cerebral blood flow (CBF) stands as a vital indicator, reflecting the metabolic demands and health status of brain tissue1. Traditional approaches often entail empirical assessments, relying heavily on the expertise of clinicians to interpret images and discern pathological changes2. However, advancements in magnetic resonance imaging (MRI) techniques, particularly arterial spin labeling (ASL)3, offer a promising avenue for quantifying CBF with greater accuracy and objectivity4,5.
This study presents a pioneering methodology that integrates three-dimensional ASL (3D-ASL) with structural MRI to construct a comprehensive CBF atlas across cerebral functional regions6. By leveraging this novel approach, clinicians can not only obtain a global perspective of CBF but also delve into specific functional areas, allowing for a nuanced understanding of cerebral perfusion patterns7,8. This improvement in resolution is a direct result of technological progress in imaging equipment rather than the use of interpolated voxels. It is worth noting that the majority of mainstream MRI devices available on the market today typically offer imaging precision better than 1.5 mm9. These advancements in imaging technology have paved the way for more detailed and accurate CBF assessments. This represents a paradigm shift from conventional imaging, which often lacks the resolution to detect subtle changes in CBF associated with early-stage pathologies10.
The genesis of this methodology lies in the imperative to address the diagnostic challenges posed by cerebral conditions, including chronic cerebral ischemia (CCI) and other neurological disorders11,12. These conditions necessitate precise and timely assessments to guide therapeutic interventions effectively13,14. By comparing CBF atlases between healthy individuals and patients with CCI, this study unveils significant disparities in regional CBF distributions, offering insights into disease pathology and potential treatment avenues.
The utility of this MRI-ASL approach extends beyond diagnosis, encompassing therapeutic evaluation and monitoring of disease progression15. Longitudinal CBF atlases hold promise in tracking treatment responses and rehabilitation outcomes, providing clinicians with invaluable tools for personalized patient management. Moreover, the ability to discern subtle CBF changes may serve as an early biomarker for impending tissue abnormalities, enabling proactive interventions to mitigate neurological damage before it becomes irreversible16.
While this methodology represents an advanced tool, several avenues for refinement and expansion merit consideration. Standardizing scanning protocols, CBF normalization techniques, and constructing multi-subject healthy CBF atlases are crucial steps toward enhancing diagnostic accuracy and clinical utility. Collaborative efforts across diverse cerebral pathologies are essential to validate and refine this approach for widespread clinical adoption.
This study introduces a novel approach whereby MRI-derived CBF atlases offer clinicians deep insights into cerebral function and pathology. By bridging the gap between imaging group and clinical interpretation, this methodology has the potential to revolutionize the diagnosis and management of a myriad of neurological conditions, ushering in a future of precision medicine tailored to the unique needs of each patient.

<table><tbody><tr><td>CBF Atlas</td><td>Intelligent Entropy</td><td>CBF Atlas V1.0</td><td>Beijing Intelligent Entropy Science &amp;amp; Technology Co Ltd.&lt;br/&gt; Modeling for Thyroid Disease</td></tr><tr><td>MATLAB</td><td>MathWorks</td><td>2023B</td><td>Computing and visualization</td></tr><tr><td>MRI Device</td><td>Siemens</td><td>Amria 1.5 T</td><td>MRI scanner</td></tr></tbody></table>

construction and application of cerebral functional region-based cerebral blood flow atlas using magnetic resonance imaging-arterial spin labeling

Cerebral conditions often require precise diagnosis and monitoring, necessitating advanced imaging techniques. Current modalities may not adequately detect early signs of reversible tissue damage, underlining the need for innovative diagnostic tools that can quantify changes in cerebral blood flow (CBF) with high specificity and sensitivity.&#160;This study integrates three-dimensional arterial spin labeling (3D-ASL) with structural MRI to develop comprehensive CBF atlases that cover all main functional regions of the brain. This innovative magnetic resonance imaging- arterial spin labeling (MRI-ASL) methodology provides a rapid and noninvasive means of quantifying region-specific CBF, offering a detailed view of CBF levels across different functional regions.The comparison between chronic cerebral ischemia (CCI) patients and healthy subjects revealed significantly diminished CBF across the cerebral functional regions in the constructed CBF atlases for the former. This approach not only allows for the efficient identification of CCI by analyzing concurrent decreases in CBF across critical areas relative to healthy distributions but also enables the tracking of treatment responses and rehabilitation progress through longitudinal CBF atlases.The CBF atlas developed using the MRI-ASL technique represents a novel advancement in the field of cerebral diagnostics and patient care. By comparing regional CBF levels against normative standards, this method enhances diagnostic capabilities, enabling clinicians to provide personalized care to patients with cerebral conditions.

This investigation utilizes actual patient data acquired using a 1.5 T MRI scanner to validate the cerebral blood flow (CBF) quantification and atlas construction methodology. The preprocessing steps included FLAIR structural images (Figure 1), CBF images (Figure 2), and triplanar fused images (Figure 3 and Figure 4).
Cerebral functional regions were segmented from FLAIR scan...

Author Spotlight: Noninvasive Cerebral Blood Flow Determination in Human Functional Brain Region for Diagnosis of Neurological Disorders

This study integrated magnetic resonance imaging- arterial spin labeling images to derive cerebral blood flow (CBF) atlas for cerebral functional regions. Comparing typical healthy and chronic cerebral ischemia CBF atlases revealed significant differences in regional CBF distributions, enabling rapid, noninvasive assessments of functional CBF to assist in diagnosis and evaluate therapeutics.

Construction and Application of Cerebral Functional Region-Based Cerebral Blood Flow Atlas Using Magnetic Resonance Imaging-Arterial Spin Labeling

Cerebral conditions often require precise diagnosis and monitoring, necessitating advanced imaging techniques. Current modalities may not adequately ...

construction-application-cerebral-functional-region-based-cerebral

Research

JoVE Journal

Medicine

535 Views.  Beijing University of Chinese Medicine. This study integrated magnetic resonance imaging- arterial spin labeling images to derive cerebral blood flow (CBF) atlas for cerebral functional regions. Comparing typical healthy and chronic cerebral ischemia CBF atlases revealed significant differences in regional CBF distributions, enabling rapid, noninvasive assessments of functional CBF to assist in diagnosis and evaluate therapeutics.

Video: Author Spotlight: Noninvasive Cerebral Blood Flow Determination in Human Functional Brain Region for Diagnosis of Neurological Disorders

Magnetic Resonance Imaging Quantification of Pulmonary Perfusion using Calibrated Arterial Spin Labeling

This demonstrates a MR imaging method to measure the spatial distribution of pulmonary blood flow in healthy subjects 
during normoxia (inspired O2, fraction (FIO2) = 0.21) hypoxia (FIO2 = 0.125), and hyperoxia 
(FIO2 = 1.00). In addition, the physiological responses of the subject are monitored in the MR scan environment. MR images 
were obtained on a 1.5 T GE MRI scanner during a breath hold from a sagittal slice in the right lung at functional residual capacity. An arterial 
spin labeling sequence (ASL-FAIRER) was used to measure the spatial distribution of pulmonary blood flow 1,2 and a multi-echo fast 
gradient echo (mGRE) sequence 3 was used to quantify the regional proton (i.e. H2O) density, allowing the quantification 
of density-normalized perfusion for each voxel (milliliters blood per minute per gram lung tissue). 
With a pneumatic switching valve and facemask equipped with a 2-way non-rebreathing valve, different oxygen concentrations 
were introduced to the subject in the MR scanner through the inspired gas tubing. A metabolic cart collected expiratory gas via expiratory tubing. Mixed expiratory O2 and CO2 concentrations, oxygen consumption, carbon dioxide production, respiratory exchange ratio, 
respiratory frequency and tidal volume were measured. Heart rate and oxygen saturation were monitored using pulse-oximetry. 
Data obtained from a normal subject showed that, as expected, heart rate was higher in hypoxia (60 bpm) than during normoxia (51) or hyperoxia (50) and the arterial oxygen saturation (SpO2) was reduced during hypoxia to 86%. Mean ventilation was 8.31 L/min BTPS during hypoxia, 7.04 L/min during normoxia, and 6.64 L/min during hyperoxia. Tidal volume was 0.76 L during hypoxia, 0.69 L during normoxia, and 0.67 L during hyperoxia. 
Representative quantified ASL data showed that the mean density normalized perfusion was 8.86 ml/min/g during hypoxia, 8.26 ml/min/g during normoxia and 8.46 ml/min/g during hyperoxia, respectively. In this subject, the relative dispersion4, an index of global heterogeneity, was increased in hypoxia (1.07 during hypoxia, 0.85 during normoxia, and 0.87 during hyperoxia) while the fractal dimension (Ds), another index of heterogeneity reflecting vascular branching structure, was unchanged (1.24 during hypoxia, 1.26 during normoxia, and 1.26 during hyperoxia). 
Overview. This protocol will demonstrate the acquisition of data to measure the distribution of pulmonary perfusion noninvasively under conditions of normoxia, hypoxia, and hyperoxia using a magnetic resonance imaging technique known as arterial spin labeling (ASL). 
Rationale: Measurement of pulmonary blood flow and lung proton density using MR technique offers high spatial resolution images which can be quantified and the ability to perform repeated measurements under several different physiological conditions. In human studies, PET, SPECT, and CT are commonly used as the alternative techniques. However, these techniques involve exposure to ionizing radiation, and thus are not suitable for repeated measurements in human subjects.

A MR imaging method to study the distribution of pulmonary blood flow under a variety of physiological conditions, in this case exposure to three different inspired oxygen concentrations: hypoxia, normoxia, and hyperoxia, is described. This technique utilizes human pulmonary physiology research techniques in an MR scanning environment.

This demonstrates a MR imaging method to measure the spatial distribution of pulmonary blood flow in healthy subjects 
during normoxia (inspired O2, ...

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Functional MRI (fMRI) is a widely used tool for non-invasively measuring correlates of human brain activity. However, its use has mostly been focused upon measuring activity on the surface of cerebral cortex rather than in subcortical regions such as midbrain and brainstem. Subcortical fMRI must overcome two challenges: spatial resolution and physiological noise. Here we describe an optimized set of techniques developed to perform high-resolution fMRI in human SC, a structure on the dorsal surface of the midbrain; the methods can also be used to image other brainstem and subcortical structures.
High-resolution (1.2 mm voxels) fMRI of the SC requires a non-conventional approach. The desired spatial sampling is obtained using a multi-shot (interleaved) spiral acquisition1. Since, T2* of SC tissue is longer than in cortex, a correspondingly longer echo time (TE ~ 40 msec) is used to maximize functional contrast. To cover the full extent of the SC, 8-10 slices are obtained. For each session a structural anatomy with the same slice prescription as the fMRI is also obtained, which is used to align the functional data to a high-resolution reference volume.
In a separate session, for each subject, we create a high-resolution (0.7 mm sampling) reference volume using a T1-weighted sequence that gives good tissue contrast. In the reference volume, the midbrain region is segmented using the ITK-SNAP software application2. This segmentation is used to create a 3D surface representation of the midbrain that is both smooth and accurate3. The surface vertices and normals are used to create a map of depth from the midbrain surface within the tissue4.
Functional data is transformed into the coordinate system of the segmented reference volume. Depth associations of the voxels enable the averaging of fMRI time series data within specified depth ranges to improve signal quality. Data is rendered on the 3D surface for visualization.
In our lab we use this technique for measuring topographic maps of visual stimulation and covert and overt visual attention within the SC1. As an example, we demonstrate the topographic representation of polar angle to visual stimulation in SC.

This article describes techniques to perform high-resolution functional magnetic resonance imaging with 1.2 mm sampling in human midbrain and subcortical structures using a 3T scanner. Use of these techniques to resolve topographic maps of visual stimulation in the human superior colliculus (SC) is given as an example.

Functional MRI (fMRI) is a widely used tool for non-invasively measuring correlates of human brain activity. However, its use has mostly been focused upon ...

Neuroscience

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when studying the brain, as the functional role that a brain area fulfills may be largely defined by its connections to other brain areas. In this report, we describe a novel, non-invasive approach for relating brain structure and function using magnetic resonance imaging (MRI). This approach, a combination of structural imaging of long-range fiber connections and functional imaging data, is illustrated in two distinct cognitive domains, visual attention and face perception. Structural imaging is performed with diffusion-weighted imaging (DWI) and fiber tractography, which track the diffusion of water molecules along white-matter fiber tracts in the brain (Figure 1). By visualizing these fiber tracts, we are able to investigate the long-range connective architecture of the brain. The results compare favorably with one of the most widely-used techniques in DWI, diffusion tensor imaging (DTI). DTI is unable to resolve complex configurations of fiber tracts, limiting its utility for constructing detailed, anatomically-informed models of brain function. In contrast, our analyses reproduce known neuroanatomy with precision and accuracy. This advantage is partly due to data acquisition procedures: while many DTI protocols measure diffusion in a small number of directions (e.g., 6 or 12), we employ a diffusion spectrum imaging (DSI)1, 2 protocol which assesses diffusion in 257 directions and at a range of magnetic gradient strengths. Moreover, DSI data allow us to use more sophisticated methods for reconstructing acquired data. In two experiments (visual attention and face perception), tractography reveals that co-active areas of the human brain are anatomically connected, supporting extant hypotheses that they form functional networks. DWI allows us to create a "circuit diagram" and reproduce it on an individual-subject basis, for the purpose of monitoring task-relevant brain activity in networks of interest.

We describe a novel approach for simultaneous analysis of brain function and structure using magnetic resonance imaging (MRI). We assess brain structure with high-resolution diffusion-weighted imaging and white-matter fiber tractography. Unlike standard structural MRI, these techniques allow us to directly relate anatomical connectivity to functional properties of brain networks.

The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when ...

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.

Multivariate techniques including principal component analysis (PCA) have been used to identify signature patterns of regional change in functional brain images. We have developed an algorithm to identify reproducible network biomarkers for the diagnosis of neurodegenerative disorders, assessment of disease progression, and objective evaluation of treatment effects in patient populations.

The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain ...

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

In lesion-symptom mapping (LSM), brain function is inferred by relating the location of acquired brain lesions to behavioral or cognitive symptoms in a group of patients. With recent advances in brain imaging and image processing, LSM has become a popular tool in cognitive neuroscience. LSM can provide fundamental insights into the functional architecture of the human brain for a variety of cognitive and non-cognitive functions. A crucial step in performing LSM studies is the segmentation of lesions on brains scans of a large group of patients and registration of each scan to a common stereotaxic space (also called standard space or a standardized brain template). Described here is an open-access, standardized method for infarct segmentation and registration for the purpose of LSM, as well as a detailed and hands-on walkthrough based on exemplary cases. A comprehensive tutorial for the manual segmentation of brain infarcts on CT scans and DWI or FLAIR MRI sequences is provided, including criteria for infarct identification and pitfalls for different scan types. The registration software provides multiple registration schemes that can be used for processing of CT and MRI data with heterogeneous acquisition parameters. A tutorial on using this registration software and performing visual quality checks and manual corrections (which are needed in some cases) is provided. This approach provides researchers with a framework for the entire process of brain image processing required to perform an LSM study, from gathering of the data to final quality checks of the results.

Provided here is a practical tutorial for an open-access, standardized image processing pipeline for the purpose of lesion-symptom mapping. A step-by-step walkthrough is provided for each processing step, from manual infarct segmentation on CT/MRI to subsequent registration to standard space, along with practical recommendations and illustrations with exemplary cases.

In lesion-symptom mapping (LSM), brain function is inferred by relating the location of acquired brain lesions to behavioral or cognitive symptoms in a ...

Behavior

Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy

To obtain a comprehensive understanding of the human brain, utilization of cerebral blood flow (CBF) as a source of contrast is desired because it is a key hemodynamic parameter related to cerebral oxygen supply. Resting state low frequency fluctuations based on oxygenation contrast have been shown to provide correlations between functionally connected regions. The presented protocol uses optical diffuse correlation spectroscopy (DCS) to assess blood flow-based resting state functional connectivity (RSFC) in the human brain. Results of CBF-based RSFC in human frontal cortex indicate that intra-regional RSFC is significantly higher in the left and right cortices compared to inter-regional RSFC in both cortices. This protocol should be of interest to researchers who employ multi-modal imaging techniques to study human brain function, especially in the pediatric population.

This protocol demonstrates how to measure resting state functional connectivity in the human prefrontal cortex using a custom-made diffuse correlation spectroscopy instrument. The report also discuss practical aspects of the experiment as well as detailed steps for analyzing the data.

To obtain a comprehensive understanding of the human brain, utilization of cerebral blood flow (CBF) as a source of contrast is desired because it is a ...

Bioengineering

Mapping Regional Homogeneity and Functional Connectivity of the Visual Cortex in Resting-State fMRI

A combined regional homogeneity (ReHo) and functional connectivity (FC) method, a type of noninvasive functional magnetic resonance imaging (fMRI) method, has been used to evaluate synchronous neuronal activity changes in retinitis pigmentosa (RP). The purpose of this study is to describe our method for analysis of intra- and interregional synchronizations of changes in neuronal activity in RP patients. The advantages of the combined ReHo and FC method are that it is both noninvasive and sufficiently sensitive to investigate changes in cerebral synchronous neuronal activity changes in vivo. Here, 16 RP patients and 14 healthy controls closely matched in age, sex, and education underwent resting-state fMRI scans. Two sample t-tests were conducted to compare ReHo and FC across groups. Our results showed that visual network disconnection and reorganization of the retino-thalamocortical pathway and dorsal visual stream occurred in the RP patients. Here, we describe the details of this method, its use, and the impact of its key parameters in a step-by-step manner.

We present a protocol for analyzing functional magnetic resonance imaging data to investigate spontaneous neural activity alterations in retinitis pigmentosa patient using a combined regional homogeneity and functional connectivity method.

A combined regional homogeneity (ReHo) and functional connectivity (FC) method, a type of noninvasive functional magnetic resonance imaging (fMRI) method, ...

Quantification of Cerebral Perfusion using Laser Speckle Imaging and Infarct Volume using MRI in a Pre-clinical Model of Posterior Circulation Stroke

Background: Basilar artery occlusion (BAO) is a subset of posterior circulation stroke that carries a mortality as high as 90%.&#160; The current clinical standard to diagnose ischemic stroke include computerized tomography (CT), CT angiography and perfusion and magnetic resonance imaging (MRI). Large animal pre-clinical models to accurately reflect the clinical disease as well as methods to assess stroke burden and evaluate treatments are lacking.
Methods: We describe a canine model of large vessel occlusion (LVO) stroke in the posterior circulation, and developed a laser speckle imaging (LSI) protocol to monitor perfusion changes in real time.&#160; We then utilized high b-value DWI (b=1800s/mm2) MRI to increase detection sensitivity. We also evaluated the ability of magnetic resonance angiography (MRA) to assess arterial occlusion and correlate with DSA. Finally, we verified infarct size from apparent diffusion coefficient (ADC) mapping with histology.&#160;
Results:&#160; Administration of thromboembolism occluded the basilar artery as tracked by DSA (n=7).&#160; &#160;LSI correlated with DSA, demonstrating a reduction in perfusion after stroke onset that persisted throughout the experiment, allowing us to monitor perfusion in real time.&#160; DWI with an optimized b-value for dogs illustrated the stroke volume and allowed us to derive ADC and magnetic resonance angiography (MRA) images. The MRA performed at the end of the experiment correlated with DSA performed after occlusion. Finally, stroke burden on MRI correlated with histology.
Conclusions: Our studies demonstrate real time perfusion imaging using LSI of a canine thromboembolic LVO model of posterior circulation stroke, which utilizes multimodal imaging important in the diagnosis and treatment of ischemic stroke.

A canine model of LVO stroke was utilized to develop laser speckle imaging to monitor cerebral perfusion in real-time.&#160; Diffusion-weighted MRI was optimized to image infarct volume utilizing a high b-value, enabling ADC and MRA, correlated with DSA at the time of stroke.&#160; Finally, ADC reconstructions correlated with histological findings.

Background: Basilar artery occlusion (BAO) is a subset of posterior circulation stroke that carries a mortality as high as 90%.&#160; The current clinical ...

fMRI: Functional Magnetic Resonance Imaging

Functional magnetic resonance imaging (fMRI) is a non-invasive neuroimaging technique used to investigate human brain function and cognition in both healthy individuals and populations with abnormal brain states. Functional MRI utilizes a magnetic resonance signal to detect changes in blood flow that are coupled to neuronal activation when a specific task is performed. This is possible because hemoglobin within the blood has different magnetic properties depending on whether or not it is bound to oxygen. When a certain task is performed, there is an influx of oxygenated blood to brain regions responsible for that function, and this influx can then be detected with specific MRI scan&#160;parameters. This phenomenon is termed the blood oxygen level ependent (BOLD) effect, and can be used to create maps of brain activity.
This video begins with a brief overview of how MRI and fMRI signal is obtained. Then, basic experimental design is reviewed, which involves first setting up a stimulus presentation that is specifically designed to test the function that will be mapped. Next, key steps involved in performing the fMRI scan are introduced, including subject safety and setting up at the scanner. Commonly used steps for data processing are then presented, including pre-processing and statistical analysis with the general linear model. Finally, some specific applications of fMRI are reviewed, such as investigations into abnormal function in psychological disorders, and combining fMRI with complimentary imaging modalities, such as diffusion tensor imaging (DTI).

Functional magnetic resonance imaging (fMRI) is a non-invasive neuroimaging technique used to investigate human brain function and cognition in both ...

Education

JoVE Science Education

Advanced Biology

Developing a Cerebral Blood Flow Atlas for Blood Flow Mapping

Source:&#160;Tan, Z.,&#160;et al., Construction and Application of Cerebral Functional Region-Based Cerebral Blood Flow Atlas Using Magnetic Resonance ...