The utilization of structural, functional, and biochemical data + from the human brain has grown in addressing inquiries related to + neurodegenerative and neuropsychiatric conditions. However, the normal + variability within these measures has not been systematically + reported. In this work, a database comprising these outcome measures + in a healthy population (n=51) was established to potentially serve as + a comparative reference. Healthy individuals underwent standardized + procedures to ensure consistent collection of magnetic resonance + imaging (MRI) and spectroscopy data. The MR data was acquired using a + 3T scanner with various sequences, including MPRAGE 3D T1w, + pseudo-continuous arterial spin labelling (pCASL), and single voxel + proton magnetic resonance spectroscopy (1H-MRS). Established and + custom software tools were employed to analyze outcome measures such + as tissue segmentation, cortical thickness, cerebral blood flow, + metabolite levels, and temperature estimated using MRS. This study + provides a comprehensive overview of the data analysis process, aiming + to facilitate future utilization of the collected data through an + interactive dashboard developed in R using the Shiny framework.
+The pursuit to understand the biological foundations of + neurodegenerative and neuropsychiatric conditions has led to an + extensive exploration of brain imaging and neurophysiological tools. + Integrating various magnetic resonance imaging (MRI) modalities has + emerged as an essential approach to obtain a comprehensive + understanding of these conditions. By combining morphological, + functional, and biochemical data, researchers gain valuable insights + into the intricate mechanisms underlying neurological diseases. These + insights extend to identifying potential biomarkers and therapeutic + targets, thereby paving the way for improved treatment strategies for + neurological disorders.
+A notable challenge in understanding the brain’s behaviour in + disease lies in the incomplete comprehension of its state within a + healthy population at rest. In the field of brain imaging, the + importance of considering variability between individuals and across + different brain regions is high. Therefore, creating a comprehensive + database that includes information from multiple brain regions, and + multiple modalities in a healthy population is invaluable for guiding + future research and clinical use. Such a database can be utilized as a + reference, allowing researchers to measure deviations, potentially + enabling early disease detection and monitoring progression across + different populations. Furthermore, it enables a focused analysis of + specific subsets of groups, for example, examining outcomes-based + factors like sex or age that allow for matched comparisons.
+Our study provides a description of the meticulous methodology that + ensures consistency of the data acquisition and analysis methods. + Standardized procedures have been followed to maximize the precision + of the data gathered. The outcomes available include morphological + measures such as brain tissue volume (gray matter, white matter, and + cerebral spinal fluid) and cortical thickness. Additionally, we have + included blood perfusion levels, biochemical profiles, and temperature + of different brain regions assessed through MR spectroscopy (MRS).
+The MRShiny Brain application has been developed as a normative + live database, designed to facilitate user-friendly access to a wide + spectrum of morphological, perfusion, biochemical, and temperature + brain data. Our core objective revolves around presenting a normative + representation of the healthy brain during rest with the intent of + empowering the scientific community to formulate a priori hypotheses. + Recognizing that the analysis of MRI/MRS data can be a time-consuming + and expertise-demanding task, we aim to provide these data and the + analysis scripts in an accessible format.
+As we examine brain function, it becomes evident that understanding + the brain in a healthy state is pivotal to understanding it in + pathological states. The challenge of understanding the brain’s + intricacies in various states, particularly during rest, underscores + the importance of our study. By building a comprehensive foundation of + knowledge through the integration of diverse brain outcome measures, + into a user-friendly database we aim to drive advancements in our + understanding of brain function.
+This is a live database that undergoes continuous updates,
+ resulting in changes to the following information. At the time of
+ this report, 51 healthy participants have been recruited for this
+ experiment (24M, mean age = 27.4 years, SD = 6.16 years, range = 19
+ - 47 years). Participants were asked to arrive at the laboratory in
+ a fasting state, and were given one muffin to eat about one hour
+ prior to the MRI scan to account for food intake effects
+ (
Study design. MR scans included an anatomical 3DT1, a + pseudo-continuous arterial spin labelling (pCASL) sequence, and an + MR Spectroscopy (MRS) sequence sLASER. MRS data were collected at + 4 different voxel locations (periungual anterior cingulate cortex + [pACC], anterior mid-cingulate cortex [aMCC], posterior + mid-cingulate cortex [pMCC], and the posterior cingulate cortex + [PCC]) The order of the MRS acquisition from each voxel was + randomized for each participant. Figure modified with text, + markings, and colour after adaptation of “Nervous System & + Medical Equipment” from Servier Medical Art by Servier, licensed + under a Creative Commons Attribution 3.0 Unported + License.
MRI data were collected using a
| Sequence | +Parameters | +
|---|---|
| 3D MPRAGE | +- TE/TR/TI = 4.3/9.3/950ms- Shot interval = 2400ms- + Resolution = 0.8mm³ isotropic- FOV (ap/rl/fh) = + 256/256/180mm³- Scan time = 5:49 min | +
| pCASL | +- TE/TR = 12/4174ms- Post-labelling duration = 2000ms- + Labelling duration = 1800ms- Total scan duration = 5.59 min- + Four pairs of perfusion-weighted and control scans | +
| 1H-MRS | +- TE/TR = 32/5000 ms- NSA = 64- Voxel size = 24/22/15 + mm³ (7.9mL)- Automated 2nd order shimming- 32-step phase + cycle- Water suppression using frequency selective + Excitation- Four cingulate cortex locations (pACC, aMCC, + pMCC, PCC) randomized | +
Image Segmentation was performed in FSL
+ (
Arterial spin-labeled MRI images were preprocessed using
+ ASLPrep
A total of 50 T1-weighted (T1w) images were found within the
+ input BIDS dataset. The T1-weighted (T1w) image was corrected for
+ intensity non-uniformity (INU) with
+
For the 1 ASL run obtained per subject, the following + preprocessing was performed:
+First, the second volume of the ASL timeseries was selected as
+ the reference volume and brain extracted using Nipype’s custom
+ brain extraction workflow. First, the middle M0 volume of the ASL
+ timeseries was selected as the reference volume and brain
+ extracted using Nipype’s custom brain extraction workflow.
+ Susceptibility distortion correction (SDC) was omitted.
+ Head-motion parameters were estimated for the ASL data using FSL’s
+
ASLPrep calculated cerebral blood flow (CBF) from the
+ single-delayPCASL using a single-compartment general kinetic model
+ (
ROI perfusion levels were extracted in native space using each
+ ROI’s mask. Firstly the images were co-registered using
+
The QEI was computed for each CBF map
+ (
MRS analysis was performed following the recent expert
+ guideline recommendations
+ (
MRS thermometry exploits the temperature dependence of the
+ location of the water peak on the frequency axis (-0.01 ppm/°C),
+ whereas that at the reference metabolite [e.g., N-acetylasparteate
+ (NAA)] is not temperature dependent
+ (
NAAppm and waterppm values were defined as the mid-point of the
+ full width half max (FWHM) for both the NAA and water peaks,
+ respectively. TB was estimated for each voxel separately (i.e.,
+ pACC, aMCC, pMCC, PCC -
+
To facilitate the reuse and exploration of the data, we have
+ developed an interactive web application using R Shiny. This
+ application provides an intuitive and user-friendly interface for
+ accessing and analyzing the dataset. The application allows users to
+ interact with the data in a dynamic manner, enabling exploration,
+ visualization, and integration with other datasets. The dataset is
+ composed of different types of data structural, perfusion, and
+ biochemical. These data can all be downloaded directly via the
+
-
+
GM: gray matter fraction in each region of interest.
+WM: white matter fraction in each region of interest.
+CSF: cerebrospinal fluid fraction in each region of + interest.
+CT: Cortical thickness in mm in each region of + interest.
+-
+
CBF: cerebral blood flow (
-
+
Metabolites available: N-Acetyl aspartic acid (NAA), total + creatine (tCr), total choline (tCho), myoinositol (mI), + glutamate (Glu), glutamine (Gln), and glutamate+glutamine + (Glx).
+Quality Measures signal-to-noise-ration (SNR), linewidth of + the water spectrum (LW), and Cramer-Rao Lower Bounds of each + metabolite (CRLB).
+-
+
Temperature: Temperature in Celcius
+ {math}
The quality metrics of the spectra can be seen in the application + directly, while Figure 2 illustrates the pre-processed and baseline + corrected spectra.
+MRS Average Spectra at each brain location. Averaged + participant spectra are illustrated in gray, and the group mean in + black. MRS data were collected at 4 different voxel locations + (periungual anterior cingulate cortex [pACC], anterior mid-cingulate + cortex [aMCC], posterior mid-cingulate cortex [pMCC], and the + posterior cingulate cortex [PCC]).
MRS and CBF data (1 M) were unable to be included since the + individual transients, and pCASL data were not properly saved, but CT + data was viable. For three participants we excluded metabolites from + one location (i.e., pACC (n=1), aMCC (n=1), and PCC (n=1)), due to + linewidth of the water being >10Hz. The MRS data quality from the + remaining participants are illustrated in app. The mean ± std.dev of + the quality evaluation index (QEI)25 for ASL CBF maps for the 50 + subjects is 0.794 ± 0.032.
+In summary, this work provides a database containing structural, + functional, and biochemical data from the brains of 51 healthy + participants. This resource serves as a valuable reference for + researchers exploring neurodegenerative and neuropsychiatric + conditions. The interplay of structural, functional, and biochemical + measures within a healthy population may provide an understanding of + normal variability, laying the groundwork for more nuanced + investigations into neurological conditions.
+The UBC MRI technologists are sincerely thanked for their valuable + assistance and support throughout the study. The following funding + sources are also acknowledged: J. Archibald’s research scholarship + from the National Council of Science and Technology (CONACYT), + GSD-NSERC, and the Friedman Foundation. P.S. Scheuren is supported by + the International Foundation for Research in Paraplegia (P 198 F), the + Swiss National Science Foundation (P500PB_214416), and Michael Smith + Health Research BC (RT-2023-3173). E.L. MacMillan’s salary support + from Philips Canada; and J. Kramer’s funding from an NSERC Discovery + Grant.
+An interactive NeuroLibre dashboard has been deployed at
+ https://shinybrain.db.neurolibre.org. The data is downloadable within
+ the application. The analysis scripts are available on github, with
+ the exception of the MRS preprocessing MRS MATLAB code, this can be
+ accessed by reaching out to ELM directly
+