Quantitative sodium magnetic resonance imaging (²³Na-MRI) enables the non-invasive measurement of in vivo total ²³Na concentration (TSC) in the human brain¹. This involves a complex process of reconstructing datasets acquired to calculate a TSC map². Quantitative TSC map calibration relies on external reference phantoms with known concentration for linear calibration³. This commonly involves manually segmenting the phantoms by a trained rater, hindering automatic analysis of the images, and presenting a bottleneck in the TSC map computation. Moreover, the manual segmentation of the sodium phantoms reduces reproducibility due to intra-rater and inter-rater variability.

Here we propose to substitute the manual segmentation with an automated method. Recently, it has been demonstrated that the Optimitzed PatchMatch Label fusion algorithm³ (OPAL) has an excellent performance in terms of segmentation accuracy and computation time when compared with recently published methods⁴. By introducing OPAL into our pipeline for phantom segmentation, we aim to make the processing of TSC maps more time efficient and reproducible.

Protocol: 10 healthy controls and 14 Multiple Sclerosis (MS) patients were scanned on a 3T Philips Achieva. They underwent two protocols in the same session using: 1) A proton scan using a 32-channel head coil, which included a PD/T2 (1x1x3 mm³) and a 3DT1-weighted (1x1x1 mm³) scans; 2) ²³Na scan using a fixed-tuned ²³Na transmit/receive coil (Rapid Biomedical), which included a 3D-Cones UTE sequence⁴ (3x3x3 mm³) and a 1H PD/T2w sequence. Two 4% agar phantoms with 40 and 80 mM NaCl were placed on either head side for calibration⁵.

Manual phantom segmentation: Three observers manually outlined both phantoms in all participants using JIM (Xinapse systems); the time needed to manually segment the phantoms was about 30 minutes per subject. Additionally, white matter (WM) lesions were marked by an experienced observer from the PD images.

Automatic phantom segmentation: OPAL³ was used to automatically detect the phantoms. The template library was composed of 24 sodium images and the associated manual phantom segmentations from the manual step. In order to increase the size of the library, all the scans were left-right flipped, increasing the template library to 48 samples. For each subject a leave-one-out technique was used, where the manual segmentation for that particular subject was omitted from the library. OPAL was used with the parameters suggested by Ta et al. The time needed for detecting both phantoms was <0.5 seconds.

Processing: Probabilistic brain tissue segmentation was performed over the 3DT1 images using GIF⁶. The segmentation masks were registered to the ²³Na TSC maps. A set of symmetric affine registrations⁷ were computed and concatenated. Masks were resampled to sodium space with linear interpolation using a point-spread function⁸ to preserve mask continuity. The registration steps were: the 3DT1 and pseudo-T1 images (PDw-T2w images⁹) were registered, the transformation between T2w and 1H PD/T2w was calculated, and finally 1H PD-T2w was registered to TSC map.

Partial volume correction: With the aim of removing the cerebrospinal fluid (CSF) sodium contribution in the tissues, we used a voxel-wise modified partition-based correction method¹⁰.

Statistics: The mean and standard deviation of grey matter (GM), cortical grey matter (CGM), deep grey matter (DGM) and WM ²³Na values were calculated using both manually segmented phantoms and their automatic segmentations. Two-tailed t-tests were used to look for differences between pipelines for each tissue class in controls and patients. In addition, for each method TSC differences between patients and controls were assessed.

The new fully-automatic pipeline obtains non-significantly different means in healthy controls, while significantly higher means in patients as well as a lower standard deviation (both groups), demonstrating it obtains more informative TSC maps (Table 1 and 2). The difference between patients and controls becomes more significant with the new fully automatic pipeline for each tissues class (Table 3). Finally, the new pipeline saves 30 minutes per subject comparing with manual computation time.We have introduced a novel fast, robust and reliable technique for segmenting sodium phantoms that allows fully-automatic reconstruction of TSC maps. The new automatic pipeline has shown less variability and hence higher sensitivity to changes in ²³Na concentration. This will enable less user-dependent variation on the results and faster processing of large batches of data.