Cortical Bone Mechanical Assessment via Free Water Relaxometry at 3 T.

BACKGROUND: Investigation of cortical bone using magnetic resonance imaging is a developing field, which uses short/ultrashort echo time (TE) pulse sequences to quantify bone water content and to obtain indirect information about bone microstructure. PURPOSE: To improve the accuracy of the previously proposed technique of free water T1 quantification and to seek the relationship between cortical bone free water T1 and its mechanical competence. STUDY TYPE: Prospective. SUBJECTS: Twenty samples of bovine tibia bone. FIELD STRENGTH/SEQUENCES: 3.0 T; ultra-fast two-dimensional gradient echo, Radio frequency-spoiled three-dimensional gradient echo. ASSESSMENT: Cortical bone free water T1 was quantified via three different methods: inversion recovery (IR), variable flip angle (VFA), and variable repetition time (VTR). Signal-to-noise ratio was measured by dividing the signal of each segmented sample to background noise. Segmentation was done manually. The effect of noise on T1 quantification was evaluated. Then, the samples were subjected to mechanical compression test to measure the toughness, yield stress, ultimate stress, and Young modulus. STATISTICAL TESTS: All the statistical analysis (Shapiro-Wilk, way analysis of variance, paired t test, Pearson correlation, and Bland-Altman plot) were done using SPSS. RESULTS: Significant difference was found between T1 quantification groups (P < 0.05). Average T1 of each quantification method differed significantly after adding noise (P < 0.05). VFA-T1 values significantly correlated with toughness (r = -0.68, P < 0.05), ultimate stress (r = -0.71, P < 0.05), and yield stress (r = -0.62, P < 0.05). No significant correlation was found between VTR-T1 values and toughness (P = 0.07), ultimate stress (P = 0.47), yield stress (P = 0.30), and Young modulus (P = 0.39). DATA CONCLUSION: Pore water T1 value is associated with bone mechanical competence, and VFA method employing short-TE pulse sequence seems a superior technique to VTR method for this quantification. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: 1.

MDCT-QCT, QUS, and DXA in healthy adults: An intermodality comparison.

Background: Cortical deceleration is the main reason for bone loss at peripheral sites. It was suggested that when peripheral bones were assessed for osteoporosis, management and therapy can be administered early. The main aim of this study was to assess the relationships between the central and peripheral measurements at different skeleton bone sites (spine, femur, forearm, tibia, and calcaneus) with available modalities: DXA, QUS, and MDCT-QCT. Methods: The volunteers recruited in this study did not have any history or evidence of metabolic bone disease. Blood test and DXA measurements were used as inclusion criteria to select 40 healthy participants. The selected volunteers underwent 3 imaging modalities: QCT, DXA, and QUS. DXA-based measurements were made on 3 sites, including spine, femur, and forearm. QCT and QUS measurements were done for distal of tibia and calcaneus bones, respectively. The extracted parameters from the 3 modalities were analyzed using a bivariate (Pearson) correlation (r) in statistical software. Results: The results showed moderate to good correlations between spongy bones in central and peripheral sites from all the modalities. However, there was no correlation between MDCT measures and central bone values. According to correlations between different peripheral sits, aBMD of 33% radius and trabecular vBMD in 38% distal tibia showed weak but significant relationship between peripheral bones (r=-0.342, p=0.044). Conclusion: The findings demonstrated how bones in central and peripheral sites were correlated. Multimodality imaging was used in this group of healthy volunteers. Also, it was found that QCT-based MDCT needs more optimization and requires further investigations.

Effective Connectivity Evaluation of Resting-State Brain Networks in Alzheimer's Disease, Amnestic Mild Cognitive Impairment, and Normal Aging: An Exploratory Study.

(1) Background: Alzheimer's disease (AD) is a neurodegenerative disease with a high prevalence. Despite the cognitive tests to diagnose AD, there are pitfalls in early diagnosis. Brain deposition of pathological markers of AD can affect the direction and intensity of the signaling. The study of effective connectivity allows the evaluation of intensity flow and signaling pathways in functional regions, even in the early stage, known as amnestic mild cognitive impairment (aMCI). (2) Methods: 16 aMCI, 13 AD, and 14 normal subjects were scanned using resting-state fMRI and T1-weighted protocols. After data pre-processing, the signal of the predefined nodes was extracted, and spectral dynamic causal modeling analysis (spDCM) was constructed. Afterward, the mean and standard deviation of the Jacobin matrix of each subject describing effective connectivity was calculated and compared. (3) Results: The maps of effective connectivity in the brain networks of the three groups were different, and the direction and strength of the causal effect with the progression of the disease showed substantial changes. (4) Conclusions: Impaired information flow in the resting-state networks of the aMCI and AD groups was found versus normal groups. Effective connectivity can serve as a potential marker of Alzheimer's pathophysiology, even in the early stages of the disease.