Portable, low-field magnetic resonance imaging for evaluation of Alzheimer's disease

Abstract

Portable, low-field magnetic resonance imaging (LF-MRI) of the brain may facilitate point-of-care assessment of patients with Alzheimer's disease (AD) in settings where conventional MRI cannot. However, image quality is limited by a lower signal-to-noise ratio. Here, we optimize LF-MRI acquisition and develop a freely available machine learning pipeline to quantify brain morphometry and white matter hyperintensities (WMH). We validate the pipeline and apply it to outpatients presenting with mild cognitive impairment or dementia due to AD. We find hippocampal volumes from ≤ 3 mm isotropic LF-MRI scans have agreement with conventional MRI and are more accurate than anisotropic counterparts. We also show WMH volume has agreement between manual segmentation and the automated pipeline. The increased availability and reduced cost of LF-MRI, in combination with our machine learning pipeline, has the potential to increase access to neuroimaging for dementia.

Fig. 1. Fine-tuning of LF-SynthSR and overall imaging analysis pipeline and performance.

a The architecture of the convolutional neural network LF-SynthSR (v2). b The overall imaging analysis pipeline includes acquisition of LF-MRI images at different contrasts and resolutions, super-resolving the raw images with LF-SynthSR followed by segmentation using SynthSeg. c–h LF-MRI images were prepared with the original (v1, T1 + T2 AXI) or fine-tuned (v2, T1 and T2 AXI) LF-SynthSR followed by automated segmentation with SynthSeg. LF-MRI segmentation volumes for the hippocampus (c and f), lateral ventricles (d and g) and whole brain (e and h) were compared with volumes derived from 1 mm MP-RAGE images acquired at high-field using the absolute symmetrized percentage difference (ASPD) and Dice coefficient. The ASPD for hippocampus (T1w p = 0.027; T2w p = 0.014) and lateral ventricle volumes (p < 0.001 for T1w and T2w) relative to high-field was less for T1w or T2w LF-MRI inputs when LF-SynthSR v2 was used. The ASPD for whole brain was improved for T1w (p < 0.001) but not for T2w (p = 0.040) when using LF-SynthSR v2. The Dice coefficient for the hippocampus was more accurate when v2 was used for both T1w (p = 0.022) and T2w inputs (p < 0.001), similar for lateral ventricles, and lower for the whole brain (p < 0.001). For each subpanel, the box plots show the median, the interquartile range, and the Tukey whiskers. Each box plot corresponds to n = 20 biological replicates. Source data is available via the following link: 10.7910/DVN/9PANMC. AXI, axial; LF, low-field; T1w, T1 weighted; T2w, T2 weighted. * p < 0.05, ** p < 0.01 using the Wilcoxon signed rank test compared to v1.

Fig. 2. Axial, sagittal, and coronal views of original and processed images at different resolutions from one healthy volunteer subject.

a Isotropic 1 mm MP-RAGE images acquired at 3 T are shown, including ground truth SynthSeg segmentation. b T1w and c T2w images acquired at anisotropic (AXI) and varying isotropic voxel sizes at LF were super-resolved with LF-SynthSR (v2) and automatically segmented by SynthSeg. MP-RAGE, Magnetization Prepared-RApid Gradient Echo; AXI, axial.

Fig. 3. Accuracy of brain volumes varies as a function of the initial image acquisition resolution at LF.

a The Dice similarity coefficient of the hippocampus derived from LF T1w images of anisotropic (T1 AXI) or varying isotropic resolutions was compared to 1 mm MP-RAGE images acquired at 3 T. Dice scores were higher when isotropic voxels ≤ 3 mm were used (p < 0.001) and (b) similar accuracy was obtained from T2w images (p < 0.001 for voxels ≤ 3 mm). c Re-scanning demonstrates higher test-retest agreement in 3.0 mm isotropic relative to anisotropic counterparts (T1w, p = 0.0059; T2w, p = 0.014). Similar improvements in the Dice coefficient were observed for voxel sizes ≤ 3.0 mm for the lateral ventricle volume and whole brain using (d) and (g) T1w images, e and h T2w images and (f) and (i) test-retest analysis, respectively. For each subpanel, the box plots show the median, the interquartile range, and the Tukey whiskers and the individual data points are shown adjacent to the box plots. The Wilcoxon signed rank test was used for analysis for n = 20 biological replicates, except for the test-retest analysis where n = 10. Source data is available via the following link: 10.7910/DVN/9PANMC. T1w, T1 weighted; T2w, T2 weighted; AXI, axial. * p < 0.05, ** p < 0.01 for all panels.

Fig. 4. WMH-SynthSeg can automatically segment WMH on LF-MRI FLAIR sequences in patients presenting without neurologic complaints yet concomitant vascular risk factors.

a An example of a subject with WMH at HF- and LF-MRI, with automatically segmented lesions outlined (blue) in the axial plane and with 3D rendering. b) WMH volume scatterplot and linear fit of WMH volumes derived at LF- compared to HF-MRI using WMH-SynthSeg (r = 0.91, p < 0.001). c Scatterplot of WMH volumes derived from automatic segmentation versus manual outlining at HF, and similarly at LF in (d). WMH volume (n = 23) was associated with the periventricular Fazekas score (e), the deep Fazekas score in (f), and the composite Fazekas score in (g). For each subpanel, the box plots shows the median, the interquartile range, and the Tukey whiskers. Source data is available via the following link: 10.7910/DVN/9PANMC. WMH, white matter hyperintensity volume; LF, low-field; HF, high-field.

Fig. 5. Application of LF-SynthSR v2 and WMH-SynthSeg to a cohort of MCI/AD subjects imaged in the clinic at LF.

a Representative T1 weighted (T1w) and FLAIR images at low field (LF) and high field (HF) in a patient with Alzheimer’s disease (AD). T1w images are processed through LF-SynthSR v2 (LF) and SynthSeg and FLAIR images are processed through WMH-SynthSeg. b Hippocampal (orange), lateral ventricle (red) and whole brain (light gray) volumes derived from SynthSeg and WMH (blue) derived from WMH-SynthSeg are shown in the 3D rendering for LF and HF counterparts. c Scatter plots comparing the hippocampus, lateral ventricle, whole brain, and WMH volume derived from HF-MRI and LF-MRI scans are shown. d Using LF-MRI scans, the hippocampus and whole brain volumes were smaller among Alzheimer’s disease (AD, n = 24) and mild cognitive impairment (MCI; n = 30) patients compared to the vascular cohort (VC; n = 23) presenting without memory complaints, and patients with AD had larger ventricles. Patients with AD also had greater WMH burden compared with the VC. Segmentation volumes are adjusted for total intracranial volume in mm³. For each subpanel, the box plots show the median, the interquartile range, and the Tukey whiskers. The individual data points are shown adjacent to the box plots. Source data is available via the following link: 10.7910/DVN/9PANMC. WMH, white matter hyperintensity. *** p < 0.001, compared to the VC.