Liquid Calibration Phantoms in Ultra-Low-Dose QCT for the Assessment of Bone Mineral Density

Does the deep learning-based iterative reconstruction affect the measuring accuracy of bone mineral density in low-dose chest CT?

OBJECTIVES

To investigate the impacts of a deep learning-based iterative reconstruction algorithm on image quality and measuring accuracy of bone mineral density (BMD) in low-dose chest CT.

METHODS

Phantom and patient studies were separately conducted in this study. The same low-dose protocol was used for phantoms and patients. All images were reconstructed with filtered back projection, hybrid iterative reconstruction (HIR) (KARL®, level of 3,5,7), and deep learning-based iterative reconstruction (artificial intelligence iterative reconstruction [AIIR], low, medium, and high strength). The noise power spectrum (NPS) and the task-based transfer function (TTF) were evaluated using phantom. The accuracy and the relative error (RE) of BMD were evaluated using a European spine phantom. The subjective evaluation was performed by 2 experienced radiologists. BMD was measured using quantitative CT (QCT). Image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), BMD values, and subjective scores were compared with Wilcoxon signed-rank test. The Cohen's kappa test was used to evaluate the inter-reader and inter-group agreement.

RESULTS

AIIR reduced noise and improved resolution on phantom images significantly. There were no significant differences among BMD values in all groups of images (all P > 0.05). RE of BMD measured using AIIR images was smaller. In objective evaluation, all strengths of AIIR achieved less image noise and higher SNR and CNR (all P < 0.05). AIIR-H showed the lowest noise and highest SNR and CNR (P < 0.05). The increase in AIIR algorithm strengths did not affect BMD values significantly (all P > 0.05).

CONCLUSION

The deep learning-based iterative reconstruction did not affect the accuracy of BMD measurement in low-dose chest CT while reducing image noise and improving spatial resolution.

ADVANCES IN KNOWLEDGE

The BMD values could be measured accurately in low-dose chest CT with deep learning-based iterative reconstruction while reducing image noise and improving spatial resolution.

Diagnosis of Osteoporosis by Quantifying Volumetric Bone Mineral Density of Lumbar Vertebrae Using Abdominal CT Images and Two-Compartment Model

With the aging population, osteoporosis has become an important public health issue. The purpose of this study was to establish a two-compartment model (TCM) to quantify the volumetric bone mineral density (vBMD) of the lumbar spine using abdominal computed tomography (CT) images. The TCM approach uses water as the bone marrow equivalent and K₂HPO₄ solution as the cortical bone equivalent. A phantom study was performed to evaluate the accuracy of vBMD estimation at 100 kVp and 120 kVp. The data of 180 patients who underwent abdominal CT imaging and dual-energy X-ray absorptiometry (DXA) within one month were retrospectively collected. vBMD of L1-L4 vertebrae were calculated, and the receiver-operating characteristic curve analysis was performed to establish the diagnostic thresholds for osteoporosis and osteopenia in terms of vBMD. The average difference between the measured vBMD following TCM and the theoretical vBMD of the self-made phantom was 0.2%, and the maximum difference was 0.5%. vBMD of lumbar vertebrae obtained from TCM and aBMD obtained by DXA had a significant positive correlation (r = 0.655 to 0.723). The average diagnostic threshold for osteoporosis was 0.116 g/cm³. The sensitivity, specificity, and accuracy were 95.7%, 75.6.5%, and 80.0%, respectively. The average diagnostic threshold for osteopenia was 0.126 g/cm³. The sensitivity, specificity, and accuracy were 81.3%, 82.5%, and 82.7%, respectively. The aforementioned threshold values were used to perform the diagnostics on a test cohort, and the performance was equivalent to that in the experimental cohort. From the perspective of preventive medicine, opportunistic screening of bone mineral density using abdominal CT images and the TCM approach can facilitate early detection of osteoporosis and osteopenia and, with in-time treatment, slow down their progression.

Quantifying cortical bone free water using short echo time (STE-MRI) at 1.5 T

PURPOSE

The purpose of our study was to use Dual-TR STE-MR protocol as a clinical tool for cortical bone free water quantification at 1.5 T and validate it by comparing the obtained results (MR-derived results) with dehydration results.

METHODS

Human studies were compliant with HIPPA and were approved by the institutional review board. Short Echo Time (STE) MR imaging with different Repetition Times (TRs) was used for quantification of cortical bone free water T₁ (T₁free) and concentration (ρ_free). The proposed strategy was compared with the dehydration technique in seven bovine cortical bone samples. The agreement between the two methods was quantified by using Bland and Altman analysis. Then we applied the technique on a cross-sectional population of thirty healthy volunteers (18F/12M) and examined the association of the biomarkers with age.

RESULTS

The mean values of ρ_free for bovine cortical bone specimens were quantified as 4.37% and 5.34% by using STE-MR and dehydration techniques, respectively. The Bland and Altman analysis showed good agreement between the two methods along with the suggestion of 0.99% bias between them. Strong correlations were also reported between ρ_free (r² = 0.62) and T_1free and age (r² = 0.8). The reproducibility of the method, evaluated in eight subjects, yielded an intra-class correlation of 0.95.

CONCLUSION

STE-MR imaging with dual-TR strategy is a clinical solution for quantifying cortical bone ρ_free and T_1free.

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.