CKD Stages, Bone Metabolism Markers, and Cortical Porosity Index: Associations and Mediation Effects Analysis

A comprehensive set of ultrashort echo time magnetic resonance imaging biomarkers to assess cortical bone health: A feasibility study at clinical field strength

INTRODUCTION

Conventional bone imaging methods primarily use X-ray techniques to assess bone mineral density (BMD), focusing exclusively on the mineral phase. This approach lacks information about the organic phase and bone water content, resulting in an incomplete evaluation of bone health. Recent research highlights the potential of ultrashort echo time magnetic resonance imaging (UTE MRI) to measure cortical porosity and estimate BMD based on signal intensity. UTE MRI also provides insights into bone water distribution and matrix organization, enabling a comprehensive bone assessment with a single imaging technique. Our study aimed to establish quantifiable UTE MRI-based biomarkers at clinical field strength to estimate BMD and microarchitecture while quantifying bound water content and matrix organization.

METHODS

Femoral bones from 11 cadaveric specimens (n = 4 males 67-92 yrs of age, n = 7 females 70-95 yrs of age) underwent dual-echo UTE MRI (3.0 T, 0.45 mm resolution) with different echo times and high resolution peripheral quantitative computed tomography (HR-pQCT) imaging (60.7 μm voxel size). Following registration, a 4.5 mm HR-pQCT region of interest was divided into four quadrants and used across the multi-modal images. Statistical analysis involved Pearson correlation between UTE MRI porosity index and a signal-intensity technique used to estimate BMD with corresponding HR-pQCT measures. UTE MRI was used to calculate T1 relaxation time and a novel bound water index (BWI), compared across subregions using repeated measures ANOVA.

RESULTS

The UTE MRI-derived porosity index and signal-intensity-based estimated BMD correlated with the HR-pQCT variables (porosity: r = 0.73, p = 0.006; BMD: r = 0.79, p = 0.002). However, these correlations varied in strength when we examined each of the four quadrants (subregions, r = 0.11-0.71). T1 relaxometry and the BWI exhibited variations across the four subregions, though these differences were not statistically significant. Notably, we observed a strong negative correlation between T1 relaxation time and the BWI (r = -0.87, p = 0.0006).

CONCLUSION

UTE MRI shows promise for being an innocuous method for estimating cortical porosity and BMD parameters while also giving insight into bone hydration and matrix organization. This method offers the potential to equip clinicians with a more comprehensive array of imaging biomarkers to assess bone health without the need for invasive or ionizing procedures.

In Vivo Assessment of Bone Quality Without X-rays

PURPOSE OF REVIEW

This review summarizes recent advances in the assessment of bone quality using non-X-ray techniques.

RECENT FINDINGS

Quantitative ultrasound (QUS) provides multiple measurements of bone characteristics based on the propagation of sound through bone, the attenuation of that sound, and different processing techniques. QUS parameters and model predictions based on backscattered signals can discriminate non-fracture from fracture cases with accuracy comparable to standard bone mineral density (BMD). With advances in magnetic resonance imaging (MRI), bound water and pore water, or a porosity index, can be quantified in several long bones in vivo. Since such imaging-derived measurements correlate with the fracture resistance of bone, they potentially provide new BMD-independent predictors of fracture risk. While numerous measurements of mineral, organic matrix, and bound water by Raman spectroscopy correlate with the strength and toughness of cortical bone, the clinical assessment of person's bone quality using spatially offset Raman spectroscopy (SORS) requires advanced spectral processing techniques that minimize contaminating signals from fat, skin, and blood. Limiting exposure of patients to ionizing radiation, QUS, MRI, and SORS has the potential to improve the assessment of fracture risk and track changes of new therapies that target bone matrix and micro-structure.

Assessing cortical bone porosity with MRI in an animal model of chronic kidney disease

Chronic kidney disease (CKD) is characterized by secondary hyperparathyroidism and an increased risk of hip fractures predominantly related to cortical porosity. Unfortunately, bone mineral density measurements and high-resolution peripheral computed tomography (HR-pQCT) imaging have shortcomings that limit their utility in these patients. Ultrashort echo time magnetic resonance imaging (UTE-MRI) has the potential to overcome these limitations by providing an alternative assessment of cortical porosity. The goal of the current study was to determine if UTE-MRI could detect changes in porosity in an established rat model of CKD. Cy/+ rats (n = 11), an established animal model of CKD-MBD, and their normal littermates (n = 12) were imaged using microcomputed tomography (microCT) and UTE-MRI at 30 and 35 weeks of age (which approximates late-stage kidney disease in humans). Images were obtained at the distal tibia and the proximal femur. Cortical porosity was assessed using the percent porosity (Pore%) calculated from microCT imaging and the porosity index (PI) calculated from UTE-MRI. Correlations between Pore% and PI were also calculated. Cy/+ rats had higher Pore% than normal rats at both skeletal sites at 35 weeks (tibia = 7.13 % +/- 5.59 % vs. 0.51 % +/- 0.09 %, femur = 19.99 % +/- 7.72 % vs. 2.72 % +/- 0.32 %). They also had greater PI at the distal tibia at 30 weeks of age (0.47 +/- 0.06 vs. 0.40 +/- 0.08). However, Pore% and PI were only correlated in the proximal femur at 35 weeks of age (ρ = 0.929, Spearman). These microCT results are consistent with prior studies in this animal model utilizing microCT imaging. The UTE-MRI results were inconsistent, resulting in variable correlations with microCT imaging, which may be related to suboptimal bound and pore water discrimination at higher magnetic field strengths. Nevertheless, UTE-MRI may still provide an additional clinical tool to assess fracture risk without using ionizing radiation in CKD patients.

Automated, calibration-free quantification of cortical bone porosity and geometry in postmenopausal osteoporosis from ultrashort echo time MRI and deep learning

BACKGROUND

Assessment of cortical bone porosity and geometry by imaging in vivo can provide useful information about bone quality that is independent of bone mineral density (BMD). Ultrashort echo time (UTE) MRI techniques of measuring cortical bone porosity and geometry have been extensively validated in preclinical studies and have recently been shown to detect impaired bone quality in vivo in patients with osteoporosis. However, these techniques rely on laborious image segmentation, which is clinically impractical. Additionally, UTE MRI porosity techniques typically require long scan times or external calibration samples and elaborate physics processing, which limit their translatability. To this end, the UTE MRI-derived Suppression Ratio has been proposed as a simple-to-calculate, reference-free biomarker of porosity which can be acquired in clinically feasible acquisition times.

PURPOSE

To explore whether a deep learning method can automate cortical bone segmentation and the corresponding analysis of cortical bone imaging biomarkers, and to investigate the Suppression Ratio as a fast, simple, and reference-free biomarker of cortical bone porosity.

METHODS

In this retrospective study, a deep learning 2D U-Net was trained to segment the tibial cortex from 48 individual image sets comprised of 46 slices each, corresponding to 2208 training slices. Network performance was validated through an external test dataset comprised of 28 scans from 3 groups: (1) 10 healthy, young participants, (2) 9 postmenopausal, non-osteoporotic women, and (3) 9 postmenopausal, osteoporotic women. The accuracy of automated porosity and geometry quantifications were assessed with the coefficient of determination and the intraclass correlation coefficient (ICC). Furthermore, automated MRI biomarkers were compared between groups and to dual energy X-ray absorptiometry (DXA)- and peripheral quantitative CT (pQCT)-derived BMD. Additionally, the Suppression Ratio was compared to UTE porosity techniques based on calibration samples.

RESULTS

The deep learning model provided accurate labeling (Dice score 0.93, intersection-over-union 0.88) and similar results to manual segmentation in quantifying cortical porosity (R2 ≥ 0.97, ICC ≥ 0.98) and geometry (R2 ≥ 0.82, ICC ≥ 0.75) parameters in vivo. Furthermore, the Suppression Ratio was validated compared to established porosity protocols (R2 ≥ 0.78). Automated parameters detected age- and osteoporosis-related impairments in cortical bone porosity (P ≤ .002) and geometry (P values ranging from <0.001 to 0.08). Finally, automated porosity markers showed strong, inverse Pearson's correlations with BMD measured by pQCT (|R| ≥ 0.88) and DXA (|R| ≥ 0.76) in postmenopausal women, confirming that lower mineral density corresponds to greater porosity.

CONCLUSION

This study demonstrated feasibility of a simple, automated, and ionizing-radiation-free protocol for quantifying cortical bone porosity and geometry in vivo from UTE MRI and deep learning.

MRI Quantification of Cortical Bone Porosity, Mineralization, and Morphologic Structure in Postmenopausal Osteoporosis

Background Preclinical studies have suggested that solid-state MRI markers of cortical bone porosity, morphologic structure, mineralization, and osteoid density are useful measures of bone health. Purpose To explore whether MRI markers of cortical bone porosity, morphologic structure, mineralization, and osteoid density are affected in postmenopausal osteoporosis (OP) and to examine associations between MRI markers and bone mineral density (BMD) in postmenopausal women. Materials and Methods In this single-center study, postmenopausal women were prospectively recruited from January 2019 to October 2020 into two groups: participants with OP who had not undergone treatment, defined as having any dual-energy x-ray absorptiometry (DXA) T-score of -2.5 or less, and age-matched control participants without OP (hereafter, non-OP). Participants underwent MRI in the midtibia, along with DXA in the hip and spine, and peripheral quantitative CT in the midtibia. Specifically, MRI measures of cortical bone porosity (pore water and total water), osteoid density (bound water [BW]), morphologic structure (cortical bone thickness), and mineralization (phosphorous [P] density [31P] and 31P-to-BW concentration ratio) were quantified at 3.0 T. MRI measures were compared between OP and non-OP groups and correlations with BMD were assessed. Results Fifteen participants with OP (mean age, 63 years ± 5 [SD]) and 19 participants without OP (mean age, 65 years ± 6) were evaluated. The OP group had elevated pore water (11.6 mol/L vs 9.5 mol/L; P = .007) and total water densities (21.2 mol/L vs 19.7 mol/L; P = .03), and had lower cortical bone thickness (4.8 mm vs 5.6 mm; P < .001) and 31P density (6.4 mol/L vs 7.5 mol/L; P = .01) than the non-OP group, respectively, although there was no evidence of a difference in BW or 31P-to-BW concentration ratio. Pore and total water densities were inversely associated with DXA and peripheral quantitative CT BMD (P < .001), whereas cortical bone thickness and 31P density were positively associated with DXA and peripheral quantitative CT BMD (P = .01). BW, 31P density, and 31P-to-BW concentration ratio were positively associated with DXA (P < .05), but not with peripheral quantitative CT. Conclusion Solid-state MRI of cortical bone was able to help detect potential impairments in parameters reflecting porosity, morphologic structure, and mineralization in postmenopausal osteoporosis. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Bae in this issue.

MRI-based porosity index (PI) and suppression ratio (SR) in the tibial cortex show significant differences between normal, osteopenic, and osteoporotic female subjects

Introduction

Ultrashort echo time (UTE) MRI enables quantitative assessment of cortical bone. The signal ratio in dual-echo UTE imaging, known as porosity index (PI), as well as the signal ratio between UTE and inversion recovery UTE (IR-UTE) imaging, known as the suppression ratio (SR), are two rapid UTE-based bone evaluation techniques developed to reduce the time demand and cost in future clinical studies. The goal of this study was to investigate the performance of PI and SR in detecting bone quality differences between subjects with osteoporosis (OPo), osteopenia (OPe), and normal bone (Normal).

Methods

Tibial midshaft of fourteen OPe (72 ± 6 years old), thirty-one OPo (72 ± 6 years old), and thirty-seven Normal (36 ± 19 years old) subjects were scanned using dual-echo UTE and IR-UTE sequences on a clinical 3T scanner. Measured PI, SR, and bone thickness were compared between OPo, OPe, and normal bone (Normal) subjects using the Kruskal-Wallis test by ranks. Spearman's rank correlation coefficients were calculated between dual-energy x-ray absorptiometry (DEXA) T-score and UTE-MRI results.

Results

PI was significantly higher in the OPo group compared with the Normal (24.1%) and OPe (16.3%) groups. SR was significantly higher in the OPo group compared with the Normal (41.5%) and OPe (21.8%) groups. SR differences between the OPe and Normal groups were also statistically significant (16.2%). Cortical bone was significantly thinner in the OPo group compared with the Normal (22.0%) and OPe (13.0%) groups. DEXA T-scores in subjects were significantly correlated with PI (R=-0.32), SR (R=-0.50), and bone thickness (R=0.51).

Discussion

PI and SR, as rapid UTE-MRI-based techniques, may be useful tools to detect and monitor bone quality changes, in addition to bone morphology, in individuals affected by osteoporosis.

Quantitative assessment of lumbar spine bone marrow in patients with different severity of CKD by IDEAL-IQ magnetic resonance sequence

BACKGROUND

Chronic kidney disease (CKD) has a significant negative impact on bone health. Bone marrow is an essential component of bone, mainly composed of trabecular bone and fat. The IDEAL-IQ sequence of MRI allows indirect quantification of trabecular bone mass by R2* and direct quantification of bone marrow fat content by FF map, respectively.

OBJECTIVE

Our objective was to explore the association of CKD severity with bone marrow using IDEAL-IQ and whether mineral and bone metabolism markers alter this association.

METHOD

We recruited 68 CKD patients in this cross-sectional research (15 with CKD stages 3-4, 26 with stage 5, and 27 with stage 5d). All patients underwent lumbar spine IDEAL-IQ, BMD, and several bone metabolism markers (iPTH, 25-(OH)-VitD, calcium and phosphorus). Multiple linear regression analysis was used to examine the association of CKD severity with MRI measurements (R2* and FF).

RESULTS

More severe CKD was associated with a higher R2* value [CKD 5d versus 3-4: 30.077 s^-1 (95% CI: 12.937, 47.217), P for trend < 0.001], and this association was attenuated when iPTH was introduced [CKD 5d versus 3-4: 19.660 s^-1 (95% CI: 0.205, 39.114), P for trend = 0.042]. Furthermore, iPTH had an association with R2* value [iPTH (pg/mL): 0.033 s^-1 (95% CI: 0.001, 0.064), P = 0.041]. Besides, FF was mainly affected by age and BMI, but not CKD.

CONCLUSIONS

The bone marrow R2* value measured by IDEAL-IQ sequence is associated with CKD severity and iPTH. The R2* of IDEAL-IQ has the potential to reflect lumbar bone changes in patients with CKD.