On the sensitivity of quantitative susceptibility mapping for measuring trabecular bone density

Abstract

Purpose To develop a methodological framework to simultaneously measure and magnetic susceptibility in trabecularized yellow bone marrow and to investigate the sensitivity of Quantitative Susceptibility Mapping (QSM) for measuring trabecular bone density using a non‐UTE multi‐gradient echo sequence. Methods The ankle of 16 healthy volunteers and two patients was scanned using a time‐interleaved multi‐gradient‐echo (TIMGRE) sequence. After field mapping based on water–fat separation methods and background field removal based on the Laplacian boundary value method, three different QSM dipole inversion schemes were implemented. Mean susceptibility values in regions of different trabecular bone density in the calcaneus were compared to the corresponding values in the maps, bone volume to total volume ratios (BV/TV) estimated from high resolution imaging (in 14 subjects), and CT attenuation (in two subjects). In addition, numerical simulations were performed in a simplified trabecular bone model of randomly positioned spherical bone inclusions to verify and compare the scaling of and susceptibility with BV/TV. Results Differences in calcaneus trabecularization were well depicted in susceptibility maps, in good agreement with high‐resolution MR and CT images. Simulations and in vivo scans showed a linear relationship of measured susceptibility with BV/TV and . The ankle in vivo results showed a strong linear correlation between susceptibility and ( R 2 = 0.88, p < 0.001) with a slope and intercept of −0.004 and 0.2 ppm, respectively. Conclusions A method for multi‐paramteric mapping, including ‐mapping and QSM was developed for measuring trabecularized yellow bone marrow, showing good sensitivity of QSM for measuring trabecular bone density.

Bone quantitative susceptibility mapping using a chemical species–specific signal model with ultrashort and conventional echo data

“…Above all, these attempts do not properly account for the underlying fat–water biophysics in the MRI signal generation, nor do they acquire signal within bone using UTE, as illustrated in this work. For trabecular bones with densities much lower than those of cortical bones, QSM may be straightforwardly applied using conventional TEs .…”

Quantitative Magnetic Resonance Imaging of Cortical and Trabecular Bone

“…109,110 Strong correlations between QSM and BMD in trabecular bone of spine or ankle were reported with the use of clinical MRI sequences. 111,112 Dimov et al 113 developed the UTE-MRI QSM technique for potential detection of BMD variation in porcine hoof and human distal femur. They reported significant correlations between radial 3D UTE-MRI QSM values and CT HU in a combined set of ROIs covering tendon, trabecular bone, and cortical bone.…”

“…Most low-resolution MRI-based analyses of trabecular bone have focused on marrow relaxometry or magnetic susceptibility measurements. 38,111,112,[123][124][125][126] These techniques can provide indirect quantifications of trabecular bone density and structure. 123,124,131,132 The strong susceptibility between trabeculae and marrow interface leads to greatly reduced relaxation times for bone marrow.…”

“…Strong correlations between QSM and BMD in trabecular bone of spine or ankle were reported in different studies with the use of clinical MRI sequences. 111,112 Alternatively, several research groups have focused on bone marrow composition analysis providing fat and water proton fractions through MR spectroscopy [133][134][135][136][137][138] or iterative decomposition of water and fat with echo asymmetry and least-squares estimation. [139][140][141][142] Fat fraction in bone marrow was found to be negatively correlated with BMD and bone-volume fraction (BVF) in trabecular bone.…”

Improved body quantitative susceptibility mapping by using a variable‐layer single‐min‐cut graph‐cut for field‐mapping

“…5 The first QSM step, the magnetic field-mapping, therefore connects QSM to the sub-domain of chemical shift encoding-based water-fat separation, which also can be reformulated as a field-map estimation problem. 5,11,15 Field-mapping in the body can be challenging for mainly two reasons: (a) the presence of large background fields possibly due to concave geometry of the anatomy or air inclusions in the field of view (FOV), 16 and (b) the presence of signal voids in regions of low signal-to-noise ratio (SNR) due to MR invisible or short-T 2 tissues, for example, bone. 17 Field-mapping in water-fat regions relies on optimizing a least-squares optimization problem due to the nonlinearity of the field-map term.…”