This is the Boney toolbox, an extension to SPM12 and its CAT12 toolbox, supporting the extraction of measurements related to the bone and head structure. It is developed by Polona Kalc and Robert Dahnke and is a free but copyright software, distributed under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
If you find any bugs, please report them to polona.kalc@med.uni-jena.de or robert.dahnke@uni-jena.de.
The increasing interest in the bone-brain crosstalk suggests the implication of bone metabolism in mood, cognition, energy homeostasis, etc. (Khrimian et al. 2017; Nakamura, Imaoka, and Takeda 2021 ; Obri et al. 2018; Rousseaud et al. 2016). Furthermore, low bone mineral density (BMD) and osteoporosis have been associated with an increased risk of Alzheimer's disease (Kostev, Hadji, and Jacob 2018; Zhang et al. 2022; Xiao et al. 2023). However, the BMD measures are typically not available in open-source brain imaging databases, such as IXI, ADNI, AIBL, OASIS, etc. We therefore decided to extract a proxy measure for head BMD from the skull.
To extract bone parameters from MRI data, we use a refined SPM tissue segmentation procedure and derive different cranial intensity and thickness measures that can be used to approximate the head BMD measure. An estimation of the head's skin-fold (subcutaneous fat thickness) is also available and can be used as an additional information to the typically available BMI measure.
Install Matlab/Octave, SPM12 and its CAT12 toolbox. Download the zip-file and unpack it into your SPM12 toolbox directory.
Run SPM and open the toolbox:
spm fmri; spm_boney;
Open the bone processing batch:
and select the structural images that should be processed. Adapt relevant parameters (see paragraph Parameters and SPM batch help) and start the processing. Voilà!
After the processing has finished, you can use the XML2CSV batch to extract the estimated (bone) values for further analyses.
You can select different predefined SPM and CAT segmentation routines with various predefined settings. SPM's routine is faster but may fail in some cases, often because of the inital affine registration problems.
In addition, you can select between different advanced processing routines for the bone measures (e.g., SPMmat, volume, surface).
SPMmat focuses on the tissue values estimated within the unified segmenation process and is therefore pretty fast (+5 seconds).
The volume option further refines the bone tissue segment (high bone marrow intensities within the diploë were often misclassified as head tissue) and estimates (regional) intensity and thickness of the bone class (+50 seconds).
The surface pipeline creates a central bone surface that is used to extract intensity- and thickness values for (i) the bone cortex by mapping the minimum intensity along the surface normals, and (ii) the bone marrow by using the weighted average intensity (+10 seconds).
(We would advise the use of the refined measure, which is robust to the exclusion of the parts within the diploë.)
Furthermore, you can specify which output files to write, e.g., the short bone-report (as a JPG), or the processed NIFTI volumes or GIFTI surfaces that are also shown in the bone-report.
Boney writes a report file and a mat file that include all processed values for each individual. The most important measures are prompted on the command line while processing. The parameters are grouped by processing aspects listed in table #. The T* parameters are derived from SPM/CAT preprocessing and provide important information about the given MRI input. We estimate thickness (th) or intensity parameters, which can be volume- or surface-based (v/s) in the masked occipital region of the head (H), bone cortex (Bcor), bone marrow (Bmar), or full structure (see table). Intensity-based measures were normalized for CSF intensity but depend strongly on the protocol.
Table: Command-line and report abbreviations:
| nr | parameter | content |
|---|---|---|
| 1 | Tw | MRI image weighting (T1w, T2w, PDw, MTw, IRw) |
| 2 | Tbg | Backgound intensity (e.g. low in MPRage, high in many MP2Rage, MT, R1 protocols |
| 3 | Tfat | Use of fat suppression protocol that reduces the bone (marrow) intensity |
| 4 | Tres | RMS resolution quality measure, i.e. weighted-average resolution in mm (lower=better) |
| 5 | Tcnr | Contrast-to-noise ratio to roughly quantify image quality and the presence of motion artifacts (lower=better) |
| 6 | v/sBmar | Volume/surface-based bone marrow measure |
| 7 | v/sBcor | Volume/surface-based bone cortex measure (~bone mineral density) |
| 8 | v/sBth | Volume/surface-based bone thickness (diploë and cortex) |
| 9 | v/sHth | Volume/surface-based head thickness (fat and muscles) |
| 10 | v/sHmed | Volume/surface-based head intensity (median of all voxel-values, protocol dependent!) |
| 11 | Tbcor | SPM-based bone cortex intensity - the minimum of the typically 3 Gaussians of the unified segmentation (basic measure only for debugging/tests/comparison) |
| 12 | Tbmar | SPM-based bone cortex intensity - the maximum of the typically 3 Gaussians of the unified segmentation (basic measure only for debugging/tests/comparison) |
| 13 | Tbdns | SPM-based bone density - volume-ratio between SPM minimum and median Gaussian (expert, only for comparison) |
| 14 | Tmed(c) | Volume-based (classic) median bone intensity of the corrected bone (expert, only for comparison) |
In addition, a csv-table of the most relevant measures (including brain tissue volumes) is created at the end of the processing. The csv-export batch can be used to create independent table of previously processed data by selecting the XML-reports of interest.
Table: Major XML report fields:
| struct | group | function | content |
|---|---|---|---|
| set8t | SPM | boney_segment_get_segmat | The main field "seg8t" includes single values from the SPM preprocessing used by SPM12, CAT12, or CTseg. |
| tis | SPM | boney_segment_get_segmat | The main "tis" structure inlcudes SPM-based measures (seg8*,WMth) image resolution (res_*) and major image class values (WM,GM,CSF,bone[cortex |
| tismri | vol | boney_segment_evalSPMseg |
Table: Detailed XML report fields:
| struct | group | parameter | content |
|---|---|---|---|
| set8t | SPM | Affine | Affine transformation matrix from individual to (MNI) template space. |
| set8t | SPM | lkp | Gaussians for each TPM class. |
| set8t | SPM | wp | - |
| set8t | SPM | mg | Weighting within each TPM class defined by lkp. |
| set8t | SPM | mn | Gaussian peak value of each TPM class define by lkp. |
| set8t | SPM | vr | Variance of each Gaussian peak value of each TPM class define by lkp. |
| set8t | SPM | ll | Final total log-likelyhood of the SPM preprocessing. |
| tis | SPM | seg8o | SPM seg8 main tissue intensity (mn of max mg in lkp). |
| tis | SPM | seg8ov | SPM seg8 main tissue variance (vr of max mg in lkp). |
| tis | SPM | seg8n | SPM main tissue intensity (mn of max mg in lkp) normalized by the WM. |
| tis | SPM | seg8nv | SPM main tissue variance (vr of max mg in lkp) normalized by the WM. |
| tis | SPM | seg8con | Minimum brain tissue contrast in SPM seg8t. |
| tis | SPM | seg8conn | Minimum brain tissue contrast in SPM seg8t normalized by the WM. |
| tis | SPM | seg8CNR | Noise estimate as minimum of the WM and CSF variance in percent (similar to BWP). |
| tis | SPM | WMth | SPM WM tissue intensity. |
| tis | SPM | res_vx_vol | Image voxel resolution in mm. |
| tis | SPM | res_RES | RMS voxel resolution. |
| tis | SPM | weighting(n) | MRI image weighting (T1w, T2w, PDw, MTw, IRw). |
| tis | SPM | highBG | RMS voxel resolution. |
| tis | SPM | headFatType | Protocol intensity type of the head based on SPM seg8t values (0-low[<CSV], 1-mid[<WM], 2-[>WM]). |
| tis | SPM | boneIntType | Protocol intensity type of the bone based on SPM seg8t values (0-low[<CSF], 1-mid[<WM], 2-[>WM]). |
| tis | SPM | WM | Averaged SPM WM intensity. |
| tis | SPM | GM | Averaged SPM GM intensity. |
| tis | SPM | CSF | Averaged SPM CSF intensity. |
| tis | SPM | bonecortex | Cortical bone intensity, i.e. "min( seg8.mn( seg8t.lkp==4) )". |
| tis | SPM | bonemarrow | Cortical bone intensity, i.e. "min( seg8.mn( seg8t.lkp==4) )". |
| tis | SPM | bonestruct | Ratio between cortical and spongy bone. |
| tis | SPM | bone | Average bone intensity, i.e. "mean( seg8.mn( seg8t.lkp==4 ) )". |
| tis | SPM | head | Average head intensity, i.e. "mean( seg8.mn( seg8t.lkp==5 ) )". |
| tis | SPM | background | Averaged SPM background intensity. |
| tismri | vol | TIV | Total intracranial volume (GM + WM + CSF). |
| tismri | vol | vol | Volume of the SPM tissues classes in mm (probability >.5). |
| tismri | vol | volr | Relative volume of the SPM tissues classes (probability >.5) normalized by TIV. |
| tismri | vol | TIV | Total intracranial volume (GM + WM + CSF). |
| tismri | vol | vol | Volume of the SPM tissues classes in mm (probability >.5). |
| tismri | vol | volr | Relative volume of the SPM tissues classes (probability >.5) normalized by TIV. |
| tismri | vol | volfat | Volume of fat tissue in the masked upper head (simple threshold to separate the head tissues, in mm). |
| tismri | vol | volmus | Volume of muscle-like tissue in the masked upper head (simple threshold to separate the head tissues, in mm). |
| tismri | vol | volmusr | Relative volume of muscle-like tissue in the masked upper head (simple threshold to separate the head tissues). |
| tismri | vol | clsQC | Relation of voxel with high vs. low density within 30 mm distance. |
| tismri | vol | int | Intensity based evaluated tissue classes: (1) GM: median (=tismri.Tth(1)); (2) WM: median (=tismir.Tth(2)); (3) CSF: median (=tismri.Th(3)); (4) bone: kmeans with 3 classes for bone (1) and bone marrow (3); (5) head: kmeans with 3 classes head (1), muscle (2), and fat (3); (6) bg: median (=tismri.Th(6)). |
Figure: Bonereport with (1) Table 1 with the tissue intensities and absolute/relative volumes, (2) Table 2 with specific bone and head values (see abbreviations for details, (3) a histogram with the major values, (4) two volumes (i) the orignal image with bone and fat overlay and (ii) the normalized bone intensities with GM, WM and head (HD) segment for orientation, and (5) two surface sets (i) with bone thickness (and atlas boundaries) and (ii) the bone marrow intensity.
Abbreviations:
Table 1: GM = grey matter, WM = white matter, CSF = cerebrospinal fluid, BG = background, TPM = tissue probability map, Norm. Med. Int. = normalized median intensity.
Table 2: Tw = image weighting, Tres = root mean square resolution rating, Tbg = background type, Tfat = heat fat suppression type, Tbone = bone fat intensity, sBcor = surface-based bone-cortex intensity, sBmar = surface-based bone-marrow intensity, sBth = surface-based bone thickness, sHth = surface-based head thickness.
RD: Show only the main measures for BMD and FAT linked with the processing routines
The figure shows the results for the selected bone measures estimated on a UKB subsample created by the evaluation scripts. The most relevant regional bone measures are (i) the occipital surface-based bone cortex estimate sROI_bonecortex3, (ii) the occipital volume-based bone marrow estimate vROI_bonemarrow3, and the bone mineral density estimate (BMD) that show a high correlation to the UKB BMD measures.
In addition, the estimated head fat measure is supported by high correlations with visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT), body fat percentage, BMI, and waist measurements of the UKB.
You can find out more about the bone and skin-fold thickness measures in our preprint.
Concept and overview with main functions and data-flow chart.
Table of Boney functions with important subfunctions and variables vars (see table #) stored in the boney XML output.
| order | (sub)function / directories | content |
|---|---|---|
| 1 | boney_segment | Main processing function of the Bone segmentation batch that uses the following subroutines to extract bone and head specific measures. |
| 1.1 | boney_segment_preprocessing | Call of SPM or CAT to prepare the MRI images and tissue segments. |
| 1.2 | boney_segment_filenames | Setup of filenames depending on the selected input files. |
| 1.3 | boney_segment_prepare_print | Prepare command-line output. |
| 1.4 | boney_segment_get_segmat | Get SPM and CAT presprocessing structures (seg8t and tis values) |
| 1.5.A1 | boney_segment_loadMRI | Load the images and limit the resolution. |
| 1.5.A2 | boney_segment_simpleBone | Original prototype processing function with "classic" bone measures. |
| 1.5.A3 | boney_segment_evalSPMseg | Estimate refined tissue peaks on the given images (tismri values). |
| 1.5.A4 | boney_segment_refineSPM | Refined SPM/CAT bone and head classes (high intensity bone tissue is often misslabed as head). |
| 1.5.A5 | boney_segment_extractbone | Estimate the bone/head intensity and thickness maps and parameters (vROI values and boney_*.nii volumes files). |
| 1.5.A6 | boney_segment_create_bone_surface | Create median bone surface and map meassures (sROI values and boney_*.gii surface files). |
| 1.5.B | boney_segment_fst | Fast processing without refinements, just using SPM/CAT parameters. |
| 1.6 | . | Prepare and write XML output (boney_.xml*). |
| 1.7 | boney_segment_print_figure | A lot of code to print a result figure with images and surfaces (boney_report_*.jpg) |
| 1.8 | boney_segment_cmdline | Print results on the command-line. |
| 1.9 | boney_segment_cleanup | Remove temporary data. |
| 2 | boney_xml2csv | cat_io_xml2csv |
| 3 | tbx_cfg_boney, spm_boney | SPM toolbox and batch configuration files. |
| D1 | docs [dir] | Publication connected with Boney. |
| D2 | evaluation [dir] | Directory with functions for evaluation (in progress). |
| D2.1 | boney_run_boneseg | . |
| D2.2 | boney_eval_main | . |
| D2.2.1 | boney_eval_readCSV | . |
| D2.2.2 | boney_eval_prepareMeasures | . |
| D2.2.3 | boney_eval_printCrossCorrelation | . |
| D2.2.4 | boney_eval_printDetails | . |
| D2.3 | boney_getBoneMeasures | Old function. |
| D3 | images [dir] | Images and result figures used in this document. |
