Validation of asynchronous quantitative bone densitometry of the spine: Accuracy, short-term reproducibility, and a comparison with conventional quantitative computed tomography

Reproducibility of CT-based opportunistic vertebral volumetric bone mineral density measurements from an automated segmentation framework

BACKGROUND

To investigate the reproducibility of automated volumetric bone mineral density (vBMD) measurements from routine thoracoabdominal computed tomography (CT) assessed with segmentations by a convolutional neural network and automated correction of contrast phases, on diverse scanners, with scanner-specific asynchronous or scanner-agnostic calibrations.

METHODS

We obtained 679 observations from 278 CT scans in 121 patients (77 males, 63.6%) studied from 04/2019 to 06/2020. Observations consisted of two vBMD measurements from Δdifferent reconstruction kernels (n = 169), Δcontrast phases (n = 133), scan Δsessions (n = 123), Δscanners (n = 63), or Δall of the aforementioned (n = 20), and observations lacking scanner-specific calibration (n = 171). Precision was assessed using root-mean-square error (RMSE) and root-mean-square coefficient of variation (RMSCV). Cross-measurement agreement was assessed using Bland-Altman plots; outliers within 95% confidence interval of the limits of agreement were reviewed.

RESULTS

Repeated measurements from Δdifferent reconstruction kernels were highly precise (RMSE 3.0 mg/cm3; RMSCV 1.3%), even for consecutive scans with different Δcontrast phases (RMSCV 2.9%). Measurements from different Δscan sessions or Δscanners showed decreased precision (RMSCV 4.7% and 4.9%, respectively). Plot-review identified 12 outliers from different scan Δsessions, with signs of hydropic decompensation. Observations with Δall differences showed decreased precision compared to those lacking scanner-specific calibration (RMSCV 5.9 and 3.7, respectively).

CONCLUSION

Automatic vBMD assessment from routine CT is precise across varying setups, when calibrated appropriately. Low precision was found in patients with signs of new or worsening hydropic decompensation, what should be considered an exclusion criterion for both opportunistic and dedicated quantitative CT.

RELEVANCE STATEMENT

Automated CT-based vBMD measurements are precise in various scenarios, including cross-session and cross-scanner settings, and may therefore facilitate opportunistic screening for osteoporosis and surveillance of BMD in patients undergoing routine clinical CT scans.

KEY POINTS

Artificial intelligence-based tools facilitate BMD measurements in routine clinical CT datasets. Automated BMD measurements are highly reproducible in various settings. Reliable, automated opportunistic osteoporosis diagnostics allow for large-scale application.

Role of effective atomic number of paraspinal muscles in the prediction of acute vertebral fracture risk assessment: a cross-sectional case-control study

OBJECTIVES

We aim to investigate the relations among effective atomic number (Zeff), density, and area of paraspinal muscles, volumetric bone mineral density (vBMD), and acute vertebral fractures (VF) by using spectral base images (SBIs) and routine CT images.

METHODS

A total of 223 patients (52 men and 171 women) with acute lumber VF and 776 subjects (286 men and 390 women) without VF of at least 60 years were enrolled and underwent dual-layer detector CT scans. We quantified the cross-sectional area, density (paraSMD), and Zeff of paraspinal muscles by CT images and SBIs and measured vBMD of the lumbar spine by quantitative CT.

RESULTS

Higher vBMD was associated with lower VF risk in both sexes (adjusted OR, 0.33 and 0.43). After adjusting for age and body mass index, the associations of paraSMD with VF were not significant in men, and in women the association was borderline significant (OR, 0.80; 95% CI, 0.64-1.00). However, higher Zeff of paraspinal muscles was associated with lower VF risk in men (adjusted OR, 0.59; 0.36-0.96) but not in women. The associations of all muscle indexes with VF were not significant after further adjusting for vBMD.

CONCLUSIONS

A higher Zeff of paraspinal muscles is associated with lower VF risk in older men but not in older women. The density, area, and Zeff of paraspinal muscles were not vBMD independent risk factors for acute VF.

ADVANCES IN KNOWLEDGE

The effective atomic number of paraspinal muscles might be a potential marker for VF risk prediction.

Optimizing twin-beam dual-energy CT reconstruction: Quantitative consistency and stability assessment in reference to 120 kV: An observational study

The split filter CT can filter X-ray beam. Theoretically, the split filter CT not only provides a good low-energy beam, but also provides a more robust CT value. The aim of this study was to compare conventional single-energy computed tomography (SECT) and twin-beam dual-energy (TBDE) CT regarding the quantitative consistency and stabilities of HU measurements at different abdominal organs. Forty-four patients were prospectively enrolled to randomly receive SECT and TBDE protocols at either body part of a thorax-abdominal examination. Their overlapping scan coverage was subjected to further image analysis. For TBDE scans, composed images(c-images) and virtual monoenergetic images (VMIs) at 60, 70, 80, and 90 kiloelectron volt (keV) were reconstructed. The attenuations were measured at 5 abdominal organs and compared between SECT and TBDE to characterize quantitative consistency by intraclass correlation coefficients (ICCs), whereas their standard deviations were used to assess the Hounsfield Unit (HU) stability. The c-images, 70 keV and 80 keV VMIs from TBDE provided consistent HU values (all ICCs > 0.8) with the SECT measurements; moreover, these TBDE images had superior HU stability over SECT images in all abdominal measurements except for fat tissue. The best HU stability can be achieved in 80 keV VMIs with the lowest noise level. The c-images and VMIs derived from TBDE can produce consistent values as SECT. The 80 keV images displayed better HU stability and a lower noise level across various abdominal organs.

Semi-automatic proximal humeral trabecular bone density assessment tool: technique application and clinical validation

PURPOSE

This study aimed to apply a newly developed semi-automatic phantom-less QCT (PL-QCT) to measure proximal humerus trabecular bone density based on chest CT and verify its accuracy and precision.

METHODS

Subcutaneous fat of the shoulder joint and trapezius muscle were used as calibration references for PL-QCT BMD measurement. A self-developed algorithm based on a convolution map was utilized in PL-QCT for semi-automatic BMD measurements. CT values of ROIs used in PL-QCT measurements were directly used for phantom-based quantitative computed tomography (PB-QCT) BMD assessment. The study included 376 proximal humerus for comparison between PB-QCT and PL-QCT. Two sports medicine doctors measured the proximal humerus with PB-QCT and PL-QCT without knowing each other's results. Among them, 100 proximal humerus were included in the inter-operative and intra-operative BMD measurements for evaluating the repeatability and reproducibility of PL-QCT and PB-QCT.

RESULTS

A total of 188 patients with 376 shoulders were involved in this study. The consistency analysis indicated that the average bias between proximal humerus BMDs measured by PB-QCT and PL-QCT was 1.0 mg/cc (agreement range - 9.4 to 11.4; P > 0.05, no significant difference). Regression analysis between PB-QCT and PL-QCT indicated a good correlation (R-square is 0.9723). Short-term repeatability and reproducibility of proximal humerus BMDs measured by PB-QCT (CV: 5.10% and 3.41%) were slightly better than those of PL-QCT (CV: 6.17% and 5.64%).

CONCLUSIONS

We evaluated the bone quality of the proximal humeral using chest CT through the semi-automatic PL-QCT system for the first time. Comparison between it and PB-QCT indicated that it could be a reliable shoulder BMD assessment tool with acceptable accuracy and precision. This study developed and verify a semi-automatic PL-QCT for assessment of proximal humeral bone density based on CT to assist in the assessment of proximal humeral osteoporosis and development of individualized treatment plans for shoulders.

Correlation between vertebral bone mineral density and multi-level virtual non-calcium imaging parameters from dual-layer spectral detector computed tomography

Background

Virtual non-calcium (VNCa) imaging based on dual-energy computed tomography (CT) plays an increasingly important role in diagnosing spinal diseases. However, the utility of VNCa technology in the measurement of vertebral bone mineral density (BMD) is limited, especially the VNCa CT value at multiple calcium suppression levels and the slope of VNCa curve. This retrospective cross-sectional study aimed to explore the correlation between vertebral BMD and new VNCa parameters from dual-layer spectral detector CT.

Methods

The dual-layer spectral detector CT and quantitative CT (QCT) data of 4 hydroxyapatite (HAP) inserts and 667 vertebrae of 234 patients (132 male and 102 female) who visited a university teaching hospital between April and May 2023 were retrospectively analyzed. The BMD values of 3 vertebrae (T12, L1, and L2) and inserts were measured using QCT, defined as QCT-BMD. The VNCa CT values and the slope λ of the VNCa attenuation curve of vertebrae and inserts were recorded. The correlations between VNCa parameters (VNCa CT value, slope λ) and QCT-BMD were analyzed.

Results

For the vertebrae, the correlation coefficient ranged from -0.904 to 0.712 (all P<0.05). As the calcium suppression index (CaSI) increased, the correlation degree exhibited a decrease first and then increased, with the best correlation (r=-0.904, P<0.001) observed at the index of 25%. In contrast, the correlation coefficient for the inserts remained relatively stable (r=-0.899 to -1, all P<0.05). For the vertebrae, the values of 3 slopes λ (λ1, λ2, and λ3) derived from the VNCa attenuation curve were 6.50±1.99, 3.75±1.15, and 2.04±0.62, respectively. Regarding the inserts, the λ1, λ2, and λ3 values were 11.56 [interquartile range (IQR): 2.40-22.62], 6.68 (IQR: 1.39-13.49), and 3.63 (IQR: 0.75-7.8), respectively. For the vertebrae, all 3 correlation coefficients between 3 slopes λ and QCT-BMD were 0.956 (all P<0.05). For the inserts, the 3 correlation coefficients were 0.996, 0.998, and 1 (all P<0.05), respectively.

Conclusions

A promising correlation was detected between VNCa CT parameters and QCT-BMD in vertebrae, warranting further investigation to explore the possibility of VNCa imaging to assess BMD.

Medial Calcar Density Measured via Opportunistic Computed Tomography Is Well Represented by the Dorr C Classification

Introduction The canal-to-calcar isthmus (CC) ratio has been previously correlated with proximal femur osteology, but its relationship with bone density is not well established. Our purpose was to assess the relationship between femoral bone density, measured on opportunistic quantitative CT in Hounsfield units (HU), and CC ratio. Methods A total of 148 THA patients were included. The CC ratio was measured on anteroposterior hip radiographs. Using perioperative CT scans, a 1 cm diameter area was identified on a single mid-coronal slice in the medial calcar just proximal to the intertrochanteric ridge. The mean HU was calculated in this region to represent calcar bone density. Results Twenty-four percent (n = 35) of patients were classified as Dorr A (average CC ratio 0.47 [0.45; 0.48]), 67% (n = 96) as Dorr B (0.62 [0.55; 0.68]), and 11% (n = 17) as Dorr C (0.78 [0.77; 0.80]). There was a significant difference between Dorr A and Dorr C femurs (769 (144) vs. 588 (154) HU) as well as between B and C femurs (718 (166) vs. 588 (154) HU). The CC ratio was correlated with calcar bone density on CT (-0.370). Conclusion CC ratio is correlated with bone density determined by HU measurements on an opportunistic quantitative computed tomography scan, and bone density HU values were able to accurately differentiate bone density in Dorr A and B from Dorr C femurs. These findings suggest that the CC ratio is a reliable measurement to predict bone density in Dorr C femurs. Therefore, arthroplasty surgeons can confidently use the Dorr classification for patients with Dorr C femurs when preoperatively planning for THA.

Imaging in osteogenesis imperfecta: Where we are and where we are going

Osteogenesis imperfecta (OI) is a rare phenotypically and genetically heterogeneous group of inherited skeletal dysplasias. The hallmark features of OI include bone fragility and susceptibility to fractures, bone deformity, and diminished growth, along with a plethora of associated secondary features (both skeletal and extraskeletal). The diagnosis of OI is currently made on clinical grounds and may be confirmed by genetic testing. However, imaging remains pivotal in the evaluation of this disease. The aim of this article is to review the current role played by the various radiologic techniques in the diagnosis and monitoring of OI in the postnatal setting as well as to discuss recent advances and future perspectives in OI imaging. Conventional Radiography and Dual-energy X-ray Absorptiometry (DXA) are currently the two most used imaging modalities in OI. The cardinal radiographic features of OI include generalized osteopenia/osteoporosis, bone deformities, and fractures. DXA is currently the most available technique to assess Bone Mineral Density (BMD), specifically areal BMD (aBMD). However, DXA has important limitations and cannot fully characterize bone fragility in OI based on aBMD. Novel DXA-derived parameters, such as Trabecular Bone Score (TBS), may provide further insight into skeletal changes induced by OI, but evidence is still limited. Techniques like Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) can be useful as problem-solvers or in specific settings, including the evaluation of cranio-cervical abnormalities. Recent evidence supports the use of High-Resolution peripheral Quantitative Computed Tomography (HR-pQCT) as a promising tool to improve the characterization of bone fragility in OI. However, HR-pQCT remains a primarily research technique at present. Quantitative Computed Tomography (QCT) is an alternative to DXA for the determination of BMD at central sites, with distinct advantages but considerably higher radiation exposure. Quantitative Ultrasound (QUS) is a portable, inexpensive, and radiation-free modality that may complement DXA evaluation, providing information on bone quality. However, evidence of usefulness of QUS in OI is poor. Radiofrequency Echographic Multi Spectrometry (REMS) is an emerging non-ionizing imaging method that holds promise for the diagnosis of low BMD and for the prediction of fracture risk, but so far only one published study has investigated its role in OI. To conclude, several different radiologic techniques have proven to be effective in the diagnosis and monitoring of OI, each with their own specificities and peculiarities. Clinicians should be aware of the strategic role of the various modalities in the different phases of the patient care process. In this scenario, the development of international guidelines including recommendations on the role of imaging in the diagnosis and monitoring of OI, accompanied by continuous active research in the field, could significantly improve the standardization of patient care.

DeepmdQCT: A multitask network with domain invariant features and comprehensive attention mechanism for quantitative computer tomography diagnosis of osteoporosis

In the medical field, the application of machine learning technology in the automatic diagnosis and monitoring of osteoporosis often faces challenges related to domain adaptation in drug therapy research. The existing neural networks used for the diagnosis of osteoporosis may experience a decrease in model performance when applied to new data domains due to changes in radiation dose and equipment. To address this issue, in this study, we propose a new method for multi domain diagnostic and quantitative computed tomography (QCT) images, called DeepmdQCT. This method adopts a domain invariant feature strategy and integrates a comprehensive attention mechanism to guide the fusion of global and local features, effectively improving the diagnostic performance of multi domain CT images. We conducted experimental evaluations on a self-created OQCT dataset, and the results showed that for dose domain images, the average accuracy reached 91%, while for device domain images, the accuracy reached 90.5%. our method successfully estimated bone density values, with a fit of 0.95 to the gold standard. Our method not only achieved high accuracy in CT images in the dose and equipment fields, but also successfully estimated key bone density values, which is crucial for evaluating the effectiveness of osteoporosis drug treatment. In addition, we validated the effectiveness of our architecture in feature extraction using three publicly available datasets. We also encourage the application of the DeepmdQCT method to a wider range of medical image analysis fields to improve the performance of multi-domain images.

Artificial Intelligence Applications for Osteoporosis Classification Using Computed Tomography

Osteoporosis, marked by low bone mineral density (BMD) and a high fracture risk, is a major health issue. Recent progress in medical imaging, especially CT scans, offers new ways of diagnosing and assessing osteoporosis. This review examines the use of AI analysis of CT scans to stratify BMD and diagnose osteoporosis. By summarizing the relevant studies, we aimed to assess the effectiveness, constraints, and potential impact of AI-based osteoporosis classification (severity) via CT. A systematic search of electronic databases (PubMed, MEDLINE, Web of Science, ClinicalTrials.gov) was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 39 articles were retrieved from the databases, and the key findings were compiled and summarized, including the regions analyzed, the type of CT imaging, and their efficacy in predicting BMD compared with conventional DXA studies. Important considerations and limitations are also discussed. The overall reported accuracy, sensitivity, and specificity of AI in classifying osteoporosis using CT images ranged from 61.8% to 99.4%, 41.0% to 100.0%, and 31.0% to 100.0% respectively, with areas under the curve (AUCs) ranging from 0.582 to 0.994. While additional research is necessary to validate the clinical efficacy and reproducibility of these AI tools before incorporating them into routine clinical practice, these studies demonstrate the promising potential of using CT to opportunistically predict and classify osteoporosis without the need for DEXA.

MRI-based Endplate Bone Quality score independently predicts cage subsidence following transforaminal lumbar interbody fusion

BACKGROUND CONTEXT

Cage subsidence following transforaminal lumbar interbody fusion (TLIF) has closely correlated with poor vertebral bone quality. Studies have shown better predictive value for cage subsidence by measuring bone density at specific site. However, few studies have been performed to examine the relationship between site-specific MRI bone assessment and cage subsidence in patients who have undergone lumbar interbody fusion. The association between MRI-based assessment of endplate bone quality and cage subsidence after TLIF remains unclear.

PURPOSE

To study the predictive value of MRI-based endplate bone quality (EBQ) score for cage subsidence following TLIF, using QCT bone densitometry as a reference standard.

STUDY DESIGN/SETTING

A retrospective study.

PATIENT SAMPLE

A total of 280 adult patients undergoing single-segment TLIF for degenerative lumbar spine disease from 2010 to 2020 at our institution who had preoperative T1-weighted MRIs.

OUTCOME MEASURES

Cage subsidence, disc height, endplate bone quality (EBQ) score, bone mineral density, fusion rate.

METHODS

The retrospective study reviewed patients who underwent TLIF at one institution between March 2010 and October 2020. Cage subsidence was measured with postoperative lumbar X-rays based on the cage protrusion through into the superior or inferior end plate or both by more than 2 mm. The EBQ score was measured from preoperative T1-weighted MRI in accordance with the previously reported method.

RESULTS

Cage subsidence was observed in 42 of the 280 patients. Bone densitometry with quantitative computed tomography was visibly reduced in the subsidence group. The mean EBQ scores of the lumbar endplate bone was 4.3±0.9 in nonsubsidence and 5.0±0.6 in subsidence. On multivariate logistic regression, the difference between the two groups was remarkable. Risk of cage subsidence increases significantly with higher EBQ scores (odds ratio [OR]=2.063, 95% confidence interval [CI] 1.365-3.120, p=.001) and was an independent factor in predicting subsidence after TLIF. On receiver operating characteristic curve, the AUC for the EBQ score was 0.820 (95% confidence interval [CI]: 0.755-0.844) and the most suitable threshold for the EBQ score was 4.730 (sensitivity: 76.2%, specificity: 83.2%).

CONCLUSIONS

Higher EBQ scores measured on preoperative MRI correlated significantly with cage subsidence following TLIF. Performing EBQ assessment prior to TLIF may be a valid method of predicting the risk of postoperative subsidence.

MRI-based vertebral bone quality score for predicting cage subsidence by assessing bone mineral density following transforaminal lumbar interbody fusion: a retrospective analysis

PURPOSE

This is the first study to evaluate the predictive value of the vertebral bone quality (VBQ) score on cage subsidence after transforaminal lumbar interbody fusion (TLIF) in a Chinese population using the spinal quantitative computed tomography (QCT) as the clinical standard. Meanwhile, the accuracy of the MRI-based VBQ score in bone mineral density (BMD) measurement was verified.

METHODS

We performed a retrospective study of patients who underwent single-level TLIF from 2015 to 2020 with at least 1 year of follow-up. Cage subsidence was measured using postoperative radiographic images based on cage protrusion through the endplates more than 2 mm. The VBQ score was measured on T1-weighted MRI. The results were subjected to statistical analysis.

RESULTS

A total of 283 patients (61.1% of female) were included in the study. The subsidence rate was with 14.1% (n = 40), and the average cage subsidence was 2.3 mm. There was a significant difference in age, sex, VBQ score and spinal QCT between the subsidence group and the no-subsidence group. The multivariable analysis demonstrated that only an increased VBQ score (OR = 2.690, 95% CI 1.312-5.515, p = 0.007) and decreased L1/2 QCT-vBMD (OR = 0.955, 95% CI 0.933-0.977, p < 0.001) were associated with an increased rate of cage subsidence. The VBQ score was found to be moderately correlated with the spinal QCT (r = -0.426, p < 0.001). The VBQ score was shown to significantly predict cage subsidence, with an accuracy of 82.5%.

CONCLUSION

Our findings indicate that the MRI-based VBQ score is a significant predictor of cage subsidence and could be used to assess BMD.

Addressing Challenges of Opportunistic Computed Tomography Bone Mineral Density Analysis

Computed tomography (CT) offers advanced biomedical imaging of the body and is broadly utilized for clinical diagnosis. Traditionally, clinical CT scans have not been used for volumetric bone mineral density (vBMD) assessment; however, computational advances can now leverage clinically obtained CT data for the secondary analysis of bone, known as opportunistic CT analysis. Initial applications focused on using clinically acquired CT scans for secondary osteoporosis screening, but opportunistic CT analysis can also be applied to answer research questions related to vBMD changes in response to various disease states. There are several considerations for opportunistic CT analysis, including scan acquisition, contrast enhancement, the internal calibration technique, and bone segmentation, but there remains no consensus on applying these methods. These factors may influence vBMD measures and therefore the robustness of the opportunistic CT analysis. Further research and standardization efforts are needed to establish a consensus and optimize the application of opportunistic CT analysis for accurate and reliable assessment of vBMD in clinical and research settings. This review summarizes the current state of opportunistic CT analysis, highlighting its potential and addressing the associated challenges.

Osteosarcopenia in the Spine Beyond Bone Mineral Density: Association Between Paraspinal Muscle Impairment and Advanced Glycation Endproducts

STUDY DESIGN

Prospective cross-sectional study.

OBJECTIVE

To determine if an accumulation of advanced glycation endproducts (AGEs) is associated with impaired paraspinal muscle composition.

BACKGROUND

Impaired bone integrity and muscle function are described as osteosarcopenia. Osteosarcopenia is associated with falls, fragility fractures, and reduced quality of life. Bone integrity is influenced by bone quantity (bone mineral density) and quality (microarchitecture and collagen). The accumulation of AGEs stiffens collagen fibers and increases bone fragility. The relationship between paraspinal muscle composition and bone collagen properties has not been evaluated.

METHODS

Intraoperative bone biopsies from the posterior superior iliac spine were obtained and evaluated with multiphoton microscopy for fluorescent AGE cross-link density (fAGEs). Preoperative magnetic resonance imaging measurements at level L4 included the musculus (m.) psoas and combined m. multifidus and m. erector spinae (posterior paraspinal musculature, PPM). Muscle segmentation on axial images (cross-sectional area, CSA) and calculation of a pixel intensity threshold method to differentiate muscle (functional cross-sectional area, fCSA) and intramuscular fat (FAT). Quantitative computed tomography was performed at the lumbar spine. Univariate and multivariable regression models were used to investigate associations between fAGEs and paraspinal musculature.

RESULTS

One hundred seven prospectively enrolled patients (50.5% female, age 60.7 y, BMI 28.9 kg/m 2 ) were analyzed. In all, 41.1% and 15.0% of the patients demonstrated osteopenia and osteoporosis, respectively. Univariate linear regression analysis demonstrated a significant association between cortical fAGEs and CSA in the psoas (ρ=0.220, P =0.039) but not in the PPM. Trabecular fAGEs revealed no significant associations to PPM or psoas musculature. In the multivariable analysis, higher cortical fAGEs were associated with increased FAT (β=1.556; P =0.002) and CSA (β=1.305; P =0.005) in the PPM after adjusting for covariates.

CONCLUSION

This is the first investigation demonstrating that an accumulation of nonenzymatic collagen cross-linking product fAGEs in cortical bone is associated with increased intramuscular fat in the lumbar paraspinal musculature.

Bone microstructure and volumetric bone mineral density in patients with global sagittal malalignment

PURPOSE

Sagittal spinal malalignment often leads to surgical realignment, which is associated with major complications. Low bone mineral density (BMD) and impaired bone microstructure are risk factors for instrumentation failure. This study aims to demonstrate differences in volumetric BMD and bone microstructure between normal and pathological sagittal alignment and to determine the relationships among vBMD, microstructure, sagittal spinal and spinopelvic alignment.

METHODS

A retrospective, cross-sectional study of patients who underwent lumbar fusion for degeneration was conducted. The vBMD of the lumbar spine was assessed by quantitative computed tomography. Bone biopsies were evaluated using microcomputed tomography (μCT). C7-S1 sagittal vertical axis (SVA; ≥ 50 mm malalignment) and spinopelvic alignment were measured. Univariate and multivariable linear regression analysis evaluated associations among the alignment, vBMD and μCT parameters.

RESULTS

A total of 172 patients (55.8% female, 63.3 years, BMI 29.7 kg/m2, 43.0% with malalignment) including N = 106 bone biopsies were analyzed. The vBMD at levels L1, L2, L3 and L4 and the trabecular bone (BV) and total volume (TV) were significantly lower in the malalignment group. SVA was significantly correlated with vBMD at L1-L4 (ρ = -0.300, p < 0.001), BV (ρ = - 0.319, p = 0.006) and TV (ρ = - 0.276, p = 0.018). Significant associations were found between PT and L1-L4 vBMD (ρ = - 0.171, p = 0.029), PT and trabecular number (ρ = - 0.249, p = 0.032), PT and trabecular separation (ρ = 0.291, p = 0.012), and LL and trabecular thickness (ρ = 0.240, p = 0.017). In the multivariable analysis, a higher SVA was associated with lower vBMD (β = - 0.269; p = 0.002).

CONCLUSION

Sagittal malalignment is associated with lower lumbar vBMD and trabecular microstructure. Lumbar vBMD was significantly lower in patients with malalignment. These findings warrant attention, as malalignment patients may be at a higher risk of surgery-related complications due to impaired bone. Standardized preoperative assessment of vBMD may be advisable.

MRI-based vertebral bone quality score compared to quantitative computed tomography bone mineral density in patients undergoing cervical spinal surgery

PURPOSE

The vertebral bone quality (VBQ) score based on magnetic resonance imaging (MRI) was introduced as a bone quality marker in the lumbar spine. Prior studies showed that it could be utilized as a predictor of osteoporotic fracture or complications after instrumented spine surgery. The objective of this study was to evaluate the correlation between VBQ scores and bone mineral density (BMD) measured by quantitative computer tomography (QCT) in the cervical spine.

METHODS

Preoperative cervical CT and sagittal T1-weighted MRIs from patients undergoing ACDF were retrospectively reviewed and included. The VBQ score in each cervical level was calculated by dividing the signal intensity of the vertebral body by the signal intensity of the cerebrospinal fluid on midsagittal T1-weighted MRI images and correlated with QCT measurements of the C2-T1 vertebral bodies. A total of 102 patients (37.3% female) were included.

RESULTS

VBQ values of C2-T1 vertebrae strongly correlated with each other. C2 showed the highest VBQ value [Median (range) 2.33 (1.33, 4.23)] and T1 showed the lowest VBQ value [Median (range) 1.64 (0.81, 3.88)]. There was significant weak to moderate negative correlations between and VBQ Scores for all levels [C2: p < 0.001; C3: p < 0.001; C4: p < 0.001; C5: p < 0.004; C6: p < 0.001; C7: p < 0.025; T1: p < 0.001].

CONCLUSION

Our results indicate that cervical VBQ scores may be insufficient in the estimation of BMDs, which might limit their clinical application. Additional studies are recommended to determine the utility of VBQ and QCT BMD to evaluate their potential use as bone status markers.

Bone collagen quality in lumbar fusion patients: the association between volumetric bone mineral density and advanced glycation endproducts

PURPOSE

The sole determination of volumetric bone mineral density (vBMD) is insufficient to evaluate overall bone integrity. The accumulation of advanced glycation endproducts (AGEs) stiffens and embrittles collagen fibers. Despite the important role of AGEs in bone aging, the relationship between AGEs and vBMD is poorly understood. We hypothesized that an accumulation of AGEs, a marker of impaired bone quality, is related to decreased vBMD.

METHODS

Prospectively collected data of 127 patients undergoing lumbar fusion were analyzed. Quantitative computed tomography (QCT) measurements were performed at the lumbar spine. Intraoperative bone biopsies were obtained and analyzed with confocal fluorescence microscopy for fluorescent AGEs, both trabecular and cortical. Spearman's correlation coefficients were calculated to examine relationships between vBMD and fAGEs, stratified by sex. Multivariable linear regression analysis with adjustments for age, sex, body mass index (BMI), race, diabetes mellitus and HbA1c was used to investigate associations between vBMD and fAGEs.

RESULTS

One-hundred and twenty-seven patients (51.2% female, 61.2 years, BMI of 28.7 kg/m2) with 107 bone biopsies were included in the final analysis, excluding patients on anti-osteoporotic drug therapy. In the univariate analysis, cortical fAGEs increased with decreasing vBMD at (r = -0.301; p = 0.030), but only in men. In the multivariable analysis, trabecular fAGEs increased with decreasing vBMD after adjusting for age, sex, BMI, race, diabetes mellitus and HbA1c (β = 0.99;95%CI=(0.994,1.000); p = 0.04).

CONCLUSION

QCT-derived vBMD measurements were found to be inversely associated with trabecular fAGEs. Our results enhance the understanding of bone integrity by suggesting that spine surgery patients with decreased bone quantity may also have poorer bone quality.

Combination of vertebral bone quality scores from different magnetic resonance imaging sequences improves prognostic value for the estimation of osteoporosis

BACKGROUND CONTEXT

Recent findings revealed a correlation between vertebral bone quality based on T1-weighted (VBQ_T1) magnetic resonance imaging (MRI) and volumetric bone mass density (vBMD) measured using quantitative computerized tomography. The coherence of VBQ for other MRI sequences, such as T2 or short tau inversion recovery (STIR), has not been examined. The combination of different VBQs has not been studied.

PURPOSE

The aims of the study were to confirm the correlation between VBQ_T1 and vBMD and to examine VBQs from other MRI sequences and their combination with vBMD.

STUDY DESIGN/SETTING

This was a retrospective cross-sectional study.

PATIENT SAMPLE

The sample consisted of patients older than 18 years, who received treatment at a level-one university spine center of the German Spine Society for degenerative or traumatic reasons in 2017-2021.

OUTCOME MEASURES

The outcome measures were the correlation of VBQs from different MRI sequences with vBMD and the association of VBQs with osteopenia/osteoporosis.

METHODS

Patients' VBQ was calculated based on the signal intensities of the vertebral bodies L1-4 in T1-, T2-, and STIR-weighted MRI. The VBQ was standardized according to the signal intensity of the cerebrospinal fluid. The vBMD was determined using data from a calibrated scanner (SOMATOM Definition AS+) and processed with CliniQCT (Mindways Software, Inc., USA). Groups were divided according to vBMD into the following groups: (I) osteoporosis/osteopenia (< 120 mg/m³) and (II) healthy (≥120 mg/m³). An analysis of the correlation between various VBQs and vBMD as well as receiver operating characteristic (ROC) and binary regression analyses were performed for the prediction of osteoporosis/osteopenia.

RESULTS

We included 136 patients (women: 56.6%) in the study (69.7 ± 15.0 years). According to vBMD, 108 patients (79.4%) had osteoporosis/osteopenia. Women were affected significantly more often than men (p = .045) and had significantly higher VBQ_T1 and VBQ_T2 values than men (VBQ_T1: p = .048; VBQ_T2: p = .013). VBQ_T1 and VBQ_T2 values were significantly higher in patients with osteoporosis/osteopenia than in healthy persons (VBQ_T1: p<.001; VBQ_T2: p = .025). VBQ_T1 and VBQ_T2 were significantly negatively correlated with vBMD with a moderate effect size (p<.001), while VBQ_STIR was not significantly correlated with vBMD, although it showed a positive coherence. The combination of different VBQs in terms of VBQ_T1 × VBQ_T2 / VBQ_STIR distinctly increased the effect size of the negative correlation with vBMD compared to VBQ alone. A cutoff value for VBQ_T1 × VBQ_T2 / VBQ_STIR of 2.9179 achieved a sensitivity of 80.0%, a specificity of 75.0%, and an area under the curve (AUC) of 0.775 for the determination of osteoporosis. The mathematical model derived from the binary logistic regression showed an excellent AUC of 0.846.

CONCLUSIONS

This study confirms a significant correlation between VBQ_T1 and vBMD. The combination of VBQs from different MRI sequences enhances the prognostic value of VBQ for the determination of osteoporosis. While safe clinical application of VBQ for the determination of osteoporosis requires further validation, VBQ might offer opportunistic estimation for further diagnostics.

Risk Factors Associated with Bone Marrow Adiposity Deposition in Postmenopausal Women in the CASH China Study

Purpose

To investigated the factors that influence BMAC.

Patients and Methods

Quantitative computed tomography (QCT) and magnetic resonance imaging (MRI) were applied to measure abdominal fat areas, liver fat content, erector muscle fat content, and BMAC of the L2-4 vertebrae. Sex hormone, adipokine, and inflammatory factor levels were measured on the same day.

Results

Although age, erector muscle fat content, estradiol, testosterone, and adiponectin/leptin levels showed correlations with BMAC in the correlation analysis, the equations obtained from the whole population by multivariate analysis were unclear. Patients were stratified according to BMAC quartiles, and differences were found in vBMD, age, estradiol, testosterone, and erector muscle fat content among the four quartiles. Logistic analyses confirmed that age, estradiol/testosterone ratio, and TNF-α had independent effects on BMAC in all quartiles. In addition, height was related to higher BMAC quartiles, and glucose was related to lower BMAC quartiles.

Conclusion

Compared to other body fats, BMAC is a unique fat depot. Age, estradiol/testosterone ratio, and TNF-α are all key influencing factors related to BMAC in postmenopausal women. Furthermore, height and glucose levels were related to BMAC in the higher and lower BMAC quartiles, respectively.

Bone quality in patients with osteoporosis undergoing lumbar fusion surgery: analysis of the MRI-based vertebral bone quality score and the bone microstructure derived from microcomputed tomography

BACKGROUND CONTEXT

Osteoporosis is a risk factor for instrumentation failure in spine surgery. Bone strength is commonly assessed by bone mineral density (BMD) as a surrogate marker. However, BMD represents only a portion of bone strength and does not capture the qualitative dimensions of bone. Recently, the magnetic resonance imaging (MRI)-based vertebral bone quality (VBQ) score was introduced as a novel marker of bone quality. However, it is still unclear if the VBQ score correlates with in-vivo bone microstructure.

PURPOSE

The aims of the study were (1) to demonstrate differences in MRI-based (VBQ) and in-vivo (microcomputed tomography; μCT) bone quality between osteopenic/osteoporotic and normal bone, (2) to show the correlation between VBQ, bone microstructure and volumetric BMD (vBMD), and (3) to determine the predictive value of the VBQ score for the prevalence of osteopenia/osteoporosis.

STUDY DESIGN/SETTING

Retrospective cross-sectional study.

PATIENT SAMPLE

267 patients who underwent posterior lumbar fusion surgery from 2014 to 2021 at a single academic institution. Bone biopsies were harvested intraoperatively in 118 patients.

OUTCOME MEASURES

VBMD, VBQ score, and bone microstructure parameters derived from μCT.

METHODS

Quantitative computed tomography (QCT) measurements were performed at the lumbar spine and the L1/L2 average was used to categorize patients with a vBMD ≤120mg/cm³ as osteopenic/osteoporotic. The VBQ score was determined by dividing the median signal intensity of the L1-L4 vertebrae by the signal intensity of the cerebrospinal fluid using sagittal T1-weighted MRI scans. Intraoperative bone biopsies from the posterior superior iliac spine were obtained and evaluated with μCT. VBQ scores and μCT parameters were compared between the normal and the osteopenic/osteoporotic group. Correlations between VBQ score, μCT parameters and vBMD were assessed with Spearman's correlation (ρ). Receiver operating characteristic (ROC) analysis was performed to determine the VBQ score as a predictor for osteopenia/osteoporosis. Multiple linear regression analysis with vBMD L1/L2 as outcome was used to identify independent predictors from VBQ, μCT parameters and demographics.

RESULTS

267 patients (55.8% female, age 63.3 years, BMI 29.7 kg/m²; n=118 with bone biopsy) with a prevalence of osteopenia/osteoporosis of 65.2% were analyzed. In the osteopenic/osteoporotic group the VBQ score, structured model index (SMI), and trabecular separation (Tb.Sp) were significantly higher, whereas bone volume fraction (BV/TV), connectivity density (Conn.D) and trabecular number (Tb.N) were significantly lower. There were significant correlations between VBQ and μCT parameters ranging from ρ=-.387 to ρ=0.314 as well as between vBMD and μCT parameters ranging from ρ=-.425 to ρ=.421, and vBMD and VBQ (ρ=-.300, p<.001). ROC analysis discriminated osteopenia/osteoporosis with a sensitivity of 84.7% and a specificity of 40.6% at a VBQ score threshold value of 2.18. Age, BV/TV and trabecular thickness (Tb.Th), but not VBQ, were significant independent predictors for vBMD (corrected R²=0.434).

CONCLUSIONS

This study demonstrated for the first time that the VBQ score is associated with trabecular microstructure determined by μCT. The bone microstructure and VBQ score were significantly different in patients with impaired vBMD. However, the ability to predict osteopenia/osteoporosis with the VBQ score was moderate. The VBQ score appears to reflect additional bone quality characteristics and might have a complementary role to vBMD. This enhances our understanding of the biological background of the radiographic VBQ score and might be a take-off point to evaluate the clinical utility of it as non-invasive screening tool for bone quality.

Trabecular volumetric bone mineral density of the occipital bone at preferred screw placement sites measured by quantitative computed tomography

This study aimed at quantifying trabecular volumetric bone mineral density (vBMD) at the external occipital protuberance (EOP) and the upper cervical spine. A retrospective review of patients who underwent non-contrast enhanced computed tomography of the cervical spine that included the occipital bone up to the EOP between 2007 and 2020 was conducted. Measurements of trabecular vBMD were performed in the occipital midline area, with the region of interest extending 4.5 mm above and below the center of the EOP, as well as the C1 lateral masses and the C2 vertebral body using asynchronous quantitative computed tomography. Eighty-six patients (female, 37.2%) were included for analysis. The patient population was 81.4% Caucasian with a mean ± SD age of 62.3 ± 13.1 years. Total bone thickness at the EOP was 16.7 ± 3.4 mm, with a ratio of trabecular to total bone thickness of 0.44. Trabecular vBMD (mean ± SD) was significantly higher at the EOP than at C1 and C2 (EOP = 612.3 ± 145.8 mg/cm³ , C1 average = 290.3 ± 66.5 mg/cm³ , C2 = 305.8 ± 78.8 mg/cm³ ; p < 0.001). A significant strong correlation between trabecular vBMD of C1 and C2 was observed (r = 0.744; p < 0.001), but only low correlations between the EOP and C1 (r = 0.295; p = 0.008) and C2 (r = 0.413; p < 0.001). In individuals > 65 years of age, cervical vBMD was significantly lower, but remained high at the EOP. Clinical significance: Trabecular vBMD at the EOP is significantly higher than at the upper cervical vertebrae and remains high in older populations. Together with morphological information about the occipital bone, these results might be helpful for occipitocervical fixation when deciding about uni- or bicortical screw placement at the EOP.

One Novel Phantom-Less Quantitative Computed Tomography System for Auto-Diagnosis of Osteoporosis Utilizes Low-Dose Chest Computed Tomography Obtained for COVID-19 Screening

Background: The diagnosis of osteoporosis is still one of the most critical topics for orthopedic surgeons worldwide. One research direction is to use existing clinical imaging data for accurate measurements of bone mineral density (BMD) without additional radiation.

Methods: A novel phantom-less quantitative computed tomography (PL-QCT) system was developed to measure BMD and diagnose osteoporosis, as our previous study reported. Compared with traditional phantom-less QCT, this tool can conduct an automatic selection of body tissues and complete the BMD calibration with high efficacy and precision. The function has great advantages in big data screening and thus expands the scope of use of this novel PL-QCT. In this study, we utilized lung cancer or COVID-19 screening low-dose computed tomography (LDCT) of 649 patients for BMD calibration by the novel PL-QCT, and we made the BMD changes with age based on this PL-QCT.

Results: The results show that the novel PL-QCT can predict osteoporosis with relatively high accuracy and precision using LDCT, and the AUC values range from 0.68 to 0.88 with DXA results as diagnosis reference. The relationship between PL-QCT BMD with age is close to the real trend population (from ∼160 mg/cc in less than 30 years old to ∼70 mg/cc in greater than 80 years old for both female and male groups). Additionally, the calculation results of Pearson’s r-values for correlation between CT values with BMD in different CT devices were 0.85–0.99.

Conclusion: To our knowledge, it is the first time for automatic PL-QCT to evaluate the performance against dual-energy X-ray absorptiometry (DXA) in LDCT images. The results indicate that it may be a promising tool for individuals screened for low-dose chest computed tomography.

Automatic phantom-less QCT system with high precision of BMD measurement for osteoporosis screening: Technique optimisation and clinical validation

Background

Objective

Methods

Results

Conclusion

Translational potential statement

Focal osteoporosis defect is associated with vertebral compression fracture prevalence in a bone mineral density-independent manner

Introduction

Focal osteoporosis defect has shown a high association with the bone fragility and osteoporotic fracture prevalence. However, no routine computed tomography (CT)-based vertebral focal osteoporosis defect measurement and its association with vertebral compression fracture (VCF) were discussed yet. This study aimed to develop a routine CT-based measurement method for focal osteoporosis defect quantification, and to assess its association with the VCF prevalence.

Materials and Methods

A total of 205 cases who underwent routine CT scanning, were retrospectively reviewed and enrolled into either the VCF or the control group. The focal bone mineral content loss (focal BMC loss), measured as the cumulated demineralization within bone void space, was proposed for focal osteoporosis defect quantification. Its scan-rescan reproducibility and its correlation with trabecular bone mineral density (BMD) and apparent microarchitecture parameters were evaluated. The association between focal BMC loss and the prevalence of VCF was studied by logistic regression.

Results

The measurement of focal BMC loss showed high reproducibility (RMSSD = 0.011 mm, LSC = 0.030 mm, ICC = 0.97), and good correlation with focal bone volume fraction (r = 0.79, P < 0.001), trabecular bone separation (r = 0.76, P < 0.001), but poor correlation with trabecular BMD (r = 0.37, P < 0.001). The focal BMC loss was significantly higher in the fracture group than the control (1.03 ± 0.13 vs. 0.93 ± 0.11 mm; P < 0.001), and was associated with prevalent VCF (1.87, 95% CI = 1.31-2.65, P < 0.001) independent of trabecular BMD level.

Discussion

As a surrogate measure of focal osteoporosis defect, focal BMC Loss independently associated with the VCF prevalence. It suggests that focal osteoporosis defect is a common manifestation that positively contributed to compression fracture risk and can be quantified with routine CT using focal BMC Loss.

Fully automated radiomic screening pipeline for osteoporosis and abnormal bone density with a deep learning-based segmentation using a short lumbar mDixon sequence

BACKGROUND

Although lumbar bone marrow fat fraction (BMFF) has been demonstrated to be predictive of osteoporosis, its utility is limited by the requirement of manual segmentation. Additionally, quantitative features beyond simple BMFF average remain to be explored. In this study, we developed a fully automated radiomic pipeline using deep learning-based segmentation to detect osteoporosis and abnormal bone density (ABD) using a <20 s modified Dixon (mDixon) sequence.

METHODS

In total, 222 subjects underwent quantitative computed tomography (QCT) and lower back magnetic resonance imaging (MRI). Bone mineral density (BMD) were extracted from L1-L3 using QCT as the reference standard; 206 subjects (48.8±14.9 years old, 140 females) were included in the final analysis, and were divided temporally into the training/validation set (142/64 subjects). A deep-learning network was developed to perform automated segmentation. Radiomic models were built using the same training set to predict ABD and osteoporosis using the mDixon maps. The performance was evaluated using the temporal validation set comprised of 64 subjects, along with the automated segmentation. Additional 25 subjects (56.1±8.8 years, 14 females) from another site and a different scanner vendor was included as independent validation to evaluate the performance of the pipeline.

RESULTS

The automated segmentation achieved an outstanding mean dice coefficient of 0.912±0.062 compared to manual in the temporal validation. Task-based evaluation was performed in the temporal validation set, for predicting ABD and osteoporosis, the area under the curve, sensitivity, specificity, and accuracy were 0.925/0.899, 0.923/0.667, 0.789/0.873, 0.844/0.844, respectively. These values were comparable to that of manual segmentation. External validation (cross-vendor) was also performed; the area under the curve, sensitivity, specificity, and accuracy were 0.688/0.913, 0.786/0.857, 0.545/0.944, 0.680/0.920 for ABD and osteoporosis prediction, respectively.

CONCLUSIONS

Our work is the first attempt using radiomics to predict osteoporosis with BMFF map, and the deep-learning based segmentation will further facilitate the clinical utility of the pipeline as a screening tool for early detection of ABD.

Level-Specific Volumetric BMD Threshold Values for the Prediction of Incident Vertebral Fractures Using Opportunistic QCT: A Case-Control Study

PURPOSE

To establish and evaluate the diagnostic accuracy of volumetric bone mineral density (vBMD) threshold values at different spinal levels, derived from opportunistic quantitative computed tomography (QCT), for the prediction of incident vertebral fractures (VF).

MATERIALS AND METHODS

In this case-control study, 35 incident VF cases (23 women, 12 men; mean age: 67 years) and 70 sex- and age-matched controls were included, based on routine multi detector CT (MDCT) scans of the thoracolumbar spine. Trabecular vBMD was measured from routine baseline CT scans of the thoracolumbar spine using an automated pipeline including vertebral segmentation, asynchronous calibration for HU-to-vBMD conversion, and correction of intravenous contrast medium (https://anduin.bonescreen.de). Threshold values at T1-L5 were calculated for the optimal operating point according to the Youden index and for fixed sensitivities (60 - 85%) in receiver operating characteristic (ROC) curves.

RESULTS

vBMD at each single level of the thoracolumbar spine was significantly associated with incident VFs (odds ratio per SD decrease [OR], 95% confidence interval [CI] at T1-T4: 3.28, 1.66-6.49; at T5-T8: 3.28, 1.72-6.26; at T9-T12: 3.37, 1.78-6.36; and at L1-L4: 3.98, 1.97-8.06), independent of adjustment for age, sex, and prevalent VF. AUC showed no significant difference between vertebral levels and was highest at the thoracolumbar junction (AUC = 0.75, 95%-CI = 0.63 - 0.85 for T11-L2). Optimal threshold values increased from lumbar (L1-L4: 52.0 mg/cm³) to upper thoracic spine (T1-T4: 69.3 mg/cm³). At T11-L2, T12-L3 and L1-L4, a threshold of 80.0 mg/cm³ showed sensitivities of 85 - 88%, and specificities of 41 - 49%. To achieve comparable sensitivity (85%) at more superior spinal levels, resulting thresholds were higher: 114.1 mg/cm³ (T1-T4), 92.0 mg/cm³ (T5-T8), 88.2 mg/cm³ (T9-T12).

CONCLUSIONS

At all levels of the thoracolumbar spine, lower vBMD was associated with incident VFs in an elderly, predominantly oncologic patient population. Automated opportunistic osteoporosis screening of vBMD along the entire thoracolumbar spine allows for risk assessment of imminent VFs. We propose level-specific vBMD threshold at the thoracolumbar spine to identify individuals at high fracture risk.

Screening of osteoporosis and sarcopenia in individuals aged 50 years and older at different altitudes in Yunnan province: Protocol of a longitudinal cohort study

INTRODUCTION

Musculoskeletal system gradually degenerates with aging, and a hypoxia environment at a high altitude may accelerate this process. However, the comprehensive effects of high-altitude environments on bones and muscles remain unclear. This study aims to compare the differences in bones and muscles at different altitudes, and to explore the mechanism and influencing factors of the high-altitude environment on the skeletal muscle system.

METHODS

This is a prospective, multicenter, cohort study, which will recruit a total of 4000 participants over 50 years from 12 research centers with different altitudes (50m~3500m). The study will consist of a baseline assessment and a 5-year follow-up. Participants will undergo assessments of demographic information, anthropomorphic measures, self-reported questionnaires, handgrip muscle strength assessment (HGS), short physical performance battery (SPPB), blood sample analysis, and imaging assessments (QCT and/or DXA, US) within a time frame of 3 days after inclusion. A 5-year follow-up will be conducted to evaluate the changes in muscle size, density, and fat infiltration in different muscles; the muscle function impairment; the decrease in BMD; and the osteoporotic fracture incidence. Statistical analyses will be used to compare the research results between different altitudes. Multiple linear, logistic regression and classification tree analyses will be conducted to calculate the effects of various factors (e.g., altitude, age, and physical activity) on the skeletal muscle system in a high-altitude environment. Finally, a provisional cut-off point for the diagnosis of sarcopenia in adults at different altitudes will be calculated.

ETHICS AND DISSEMINATION

The study has been approved by the institutional research ethics committee of each study center (main center number: KHLL2021-KY056). Results will be disseminated through scientific conferences and peer-reviewed publications, as well as meetings with stakeholders.

CLINICAL TRIAL REGISTRATION NUMBER

http://www.chictr.org.cn/index.aspx, identifier ChiCTR2100052153.

Deep-learning image reconstruction for image quality evaluation and accurate bone mineral density measurement on quantitative CT: A phantom-patient study

BACKGROUND AND PURPOSE

To investigate the image quality and accurate bone mineral density (BMD) on quantitative CT (QCT) for osteoporosis screening by deep-learning image reconstruction (DLIR) based on a multi-phantom and patient study.

MATERIALS AND METHODS

High-contrast spatial resolution, low-contrast detectability, modulation function test (MTF), noise power spectrum (NPS), and image noise were evaluated for physical image quality on Caphan 500 phantom. Three calcium hydroxyapatite (HA) inserts were used for accurate BMD measurement on European Spine Phantom (ESP). CT images were reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction-veo 50% (ASiR-V50%), and three levels of DLIR(L/M/H). Subjective evaluation of the image high-contrast spatial resolution and low-contrast detectability were compared visually by qualified radiologists, whilst the statistical difference in the objective evaluation of the image high-contrast spatial resolution and low-contrast detectability, image noise, and relative measurement error were compared using one-way analysis of variance (ANOVA). Cohen's kappa coefficient (k) was performed to determine the interobserver agreement in qualitative evaluation between two radiologists.

RESULTS

Overall, for three levels of DLIR, 50% MTF was about 4.50 (lp/cm), better than FBP (4.12 lp/cm) and ASiR-V50% (4.00 lp/cm); the 2 mm low-contrast object was clearly resolved at a 0.5% contrast level, while 3mm at FBP and ASiR-V50%. As the strength level decreased and radiation dose increased, DLIR at three levels showed a higher NPS peak frequency and lower noise level, leading to leftward and rightward shifts, respectively. Measured L1, L2, and L3 were slightly lower than that of nominal HA inserts (44.8, 95.9, 194.9 versus 50.2, 100.6, 199.2mg/cm³) with a relative measurement error of 9.84%, 4.08%, and 2.60%. Coefficients of variance for the L1, L2, and L3 HA inserts were 1.51%, 1.41%, and 1.18%. DLIR-M and DLIR-H scored significantly better than ASiR-V50% in image noise (4.83 ± 0.34, 4.50 ± 0.50 versus 4.17 ± 0.37), image contrast (4.67 ± 0.73, 4.50 ± 0.70 versus 3.80 ± 0.99), small structure visibility (4.83 ± 0.70, 4.17 ± 0.73 versus 3.83 ± 1.05), image sharpness (3.83 ± 1.12, 3.53 ± 0.90 versus 3.27 ± 1.16), and artifacts (3.83 ± 0.90, 3.42 ± 0.37 versus 3.10 ± 0.83). The CT value, image noise, contrast noise ratio, and image artifacts in DLIR-M and DLIR-H outperformed ASiR-V50% and FBP (P<0.001), whilst it showed no statistically significant between DLIR-L and ASiR-V50% (P>0.05). The prevalence of osteoporosis was 74 (24.67%) in women and 49 (11.79%) in men, whilst the osteoporotic vertebral fracture rate was 26 (8.67%) in women and (5.29%) in men.

CONCLUSION

Image quality with DLIR was high-qualified without affecting the accuracy of BMD measurement. It has a potential clinical utility in osteoporosis screening.

Sources of error in bone mineral density estimates from quantitative CT

Bone mineral density (BMD) estimates from quantitative computed tomography (QCT) have proven useful for opportunistic screening of osteoporosis, treatment monitoring, and bone strength measurement. These estimates are subject to bias and variance from a variety of sources related to the imaging equipment, methods applied in the estimation procedure, and the patients themselves. In this article, we review the literature to describe the sources and sizes of error in spine and hip BMD estimates from single-energy QCT that can result from factors related to the scanner, imaging techniques, imaging subject, calibration phantom, and calibration approach. We also describe the baseline variance that can be expected based on repeatability and reproducibility studies. Though reproducible BMD estimates may be achievable with QCT, a thorough understanding of the potential sources of error and their size relative to the diagnostic task is essential to their appropriate and meaningful interpretation.

Advancements in Osteoporosis Imaging, Screening, and Study of Disease Etiology

PURPOSE OF REVIEW

The purpose of this review is to inform researchers and clinicians with the most recent imaging techniques that are employed (1) to opportunistically screen for osteoporosis and (2) to provide a better understanding into the disease etiology of osteoporosis.

RECENT FINDINGS

Phantomless calibration techniques for computed tomography (CT) may pave the way for better opportunistic osteoporosis screening and the retroactive analysis of imaging data. Additionally, hardware advances are enabling new applications of dual-energy CT and cone-beam CT to the study of bone. Advances in MRI sequences are also improving imaging evaluation of bone properties. Finally, the application of image registration techniques is enabling new uses of imaging to investigate soft tissue-bone interactions as well as bone turnover. While DXA remains the most prominent imaging tool for osteoporosis diagnosis, new imaging techniques are becoming more widely available and providing additional information to inform clinical decision-making.

Opportunistic diagnosis of osteoporosis, fragile bone strength and vertebral fractures from routine CT scans; a review of approved technology systems and pathways to implementation

Osteoporosis causes bones to become weak, porous and fracture more easily. While a vertebral fracture is the archetypal fracture of osteoporosis, it is also the most difficult to diagnose clinically. Patients often suffer further spine or other fractures, deformity, height loss and pain before diagnosis. There were an estimated 520,000 fragility fractures in the United Kingdom (UK) in 2017 (costing £4.5 billion), a figure set to increase 30% by 2030. One way to improve both vertebral fracture identification and the diagnosis of osteoporosis is to assess a patient's spine or hips during routine computed tomography (CT) scans. Patients attend routine CT for diagnosis and monitoring of various medical conditions, but the skeleton can be overlooked as radiologists concentrate on the primary reason for scanning. More than half a million CT scans done each year in the National Health Service (NHS) could potentially be screened for osteoporosis (increasing 5% annually). If CT-based screening became embedded in practice, then the technique could have a positive clinical impact in the identification of fragility fracture and/or low bone density. Several companies have developed software methods to diagnose osteoporosis/fragile bone strength and/or identify vertebral fractures in CT datasets, using various methods that include image processing, computational modelling, artificial intelligence and biomechanical engineering concepts. Technology to evaluate Hounsfield units is used to calculate bone density, but not necessarily bone strength. In this rapid evidence review, we summarise the current literature underpinning approved technologies for opportunistic screening of routine CT images to identify fractures, bone density or strength information. We highlight how other new software technologies have become embedded in NHS clinical practice (having overcome barriers to implementation) and highlight how the novel osteoporosis technologies could follow suit. We define the key unanswered questions where further research is needed to enable the adoption of these technologies for maximal patient benefit.

The Association of Lumbar Disc Herniation with Lumbar Volumetric Bone Mineral Density in a Cross-Sectional Chinese Study

Little is known about the effect of lumbar intervertebral disc herniation (LDH) on lumbar bone mineral density (BMD), and few previous studies have used quantitative computed tomography (QCT) to assess whether the staging of LDH correlates with lumbar vertebral trabecular volumetric bone mineral density (Trab.vBMD). To explore the relationship between lumbar Trab.vBMD and LDH, seven hundred and fifty-four healthy participants aged 20–60 years were enrolled in the study from an ongoing study on the degeneration of the spine and knee between June 2014 and 2017. QCT was used to measure L2–4 Trab.vBMD and lumbar spine magnetic resonance images (MRI) were performed to assess the incidence of disc herniation. After 9 exclusions, a total of 322 men and 423 women remained. The men and women were divided into younger (age 20–39 years) and older (age 40–60 years) groups and further into those without LDH, with a single LDH segment, and with ≥2 segments. Covariance analysis was used to adjust for the effects of age, BMI, waistline, and hipline on the relationship between Trab.vBMD and LDH. Forty-one younger men (25.0%) and 59 older men (37.3%) had at least one LDH segment. Amongst the women, the numbers were 46 (22.5%) and 80 (36.4%), respectively. Although there were differences in the characteristics data between men and women, the difference in Trab.vBMD between those without LDH and those with single and ≥2 segments was not statistically significant (p > 0.05). These results remained not statistically significant after further adjusting for covariates (p > 0.05). No associations between lumbar disc herniation and vertebral trabecular volumetric bone mineral density were observed in either men or women.

Cross-sectional associations of adipokines and abdominal fat distribution with aging in men

OBJECTIVE

To investigate the relationship of adipokines and abdominal fat distribution with aging in men.

METHODS

In a cross-sectional study, a total of 218 participants aged 40-79 years were recruited as a subset of the Prospective Urban Rural Epidemiology (PURE) China Action on Spine and Hip status (CASH) study population. Analysis of variance (ANOVA) and multivariable regression were used to estimate the associations of interest.

RESULTS

With the increasing of age, waist circumference, waist-to-hip ratio, waist-to-height ratio, total adipose tissue (TAT), visceral adipose tissue (VAT), VAT/subcutaneous adipose tissue (SAT), leptin, adiponectin-to-leptin ratio, and human monocyte chemo-attractant protein-1 (MCP-1) increased significantly (p < 0.05), while adiponectin decreased significantly (p < 0.05). Adiponectin, adiponectin/leptin, and adiponectin/resistin varied inversely with the VAT quartiles (p < 0.05). There was a significant negative correlation among adiponectin, adiponectin-to-leptin ratio, adiponectin-to-resistin ratio, and all the body fat distribution parameters. VAT was inversely and significantly associated with adiponectin, adiponectin-to-leptin ratio, and adiponectin-to-resistin ratio (p < 0.05).

CONCLUSIONS

It showed that aging, abdominal fat distribution, and adipokines were related with each other, which support the hypothesis that regulation of VAT and adipokines is closely linked to aging.

Opportunistic osteoporosis screening: contrast-enhanced dual-layer spectral CT provides accurate measurements of vertebral bone mineral density

Objectives

Osteoporosis remains under-diagnosed, which may be improved by opportunistic bone mineral density (BMD) measurements on CT. However, correcting for the influence of intravenous iodine-based contrast agent is challenging. The purpose of this study was to assess the diagnostic accuracy of iodine-corrected vertebral BMD measurements derived from non-dedicated contrast-enhanced phantomless dual-layer spectral CT (DLCT) examinations.

Methods

Vertebral volumetric DLCT-BMD was measured in native, arterial, and portal-venous scans of 132 patients (63 ± 16 years; 32% women) using virtual monoenergetic images (50 and 200 keV). For comparison, conventional BMD was determined using an asynchronous QCT calibration. Additionally, iodine densities were measured in the abdominal aorta (AA), inferior vena cava, and vena portae (VP) on each CT phase to adjust for iodine-related measurement errors in multivariable linear regressions and a generalized estimated equation, and conversion equations were calculated.

Results

BMD values derived from contrast-enhanced phases using conversion equations adjusted for individual vessel iodine concentrations of VP and/or AA showed a high agreement with those from non-enhanced scans in Bland-Altman plots. Mean absolute errors (MAE) of DLCT-BMD were 3.57 mg/ml for the arterial (R² = 0.989) and 3.69 mg/ml for the portal-venous phase (R² = 0.987) (conventional BMD: 4.70 [R² = 0.983] and 5.15 mg/ml [R² = 0.981]). In the phase-independent analysis, MAE was 4.49 mg/ml for DLCT (R² = 0.989) (conventional BMD: 4.82 mg/ml [R² = 0.981]).

Conclusions

Converted BMD derived from contrast-enhanced DLCT examinations and adjusted for individual vessel iodine concentrations showed a high agreement with non-enhanced DLCT-BMD, suggesting that opportunistic BMD measurements are feasible even in non-dedicated contrast-enhanced DLCT examinations.

Key Points

• Accurate BMD values can be converted from contrast-enhanced DLCT scans, independent from the used scan phase.

• DLCT-BMD measurements from contrast-enhanced scans should be adjusted with iodine concentrations of portal vein and/or abdominal aorta, which significantly improves the goodness-of-fit of conversion models.

Multi-energy computed tomography and material quantification: Current barriers and opportunities for advancement

Computed tomography (CT) technology has rapidly evolved since its introduction in the 1970s. It is a highly important diagnostic tool for clinicians as demonstrated by the significant increase in utilization over several decades. However, much of the effort to develop and advance CT applications has been focused on improving visual sensitivity and reducing radiation dose. In comparison to these areas, improvements in quantitative CT have lagged behind. While this could be a consequence of the technological limitations of conventional CT, advanced dual-energy CT (DECT) and photon-counting detector CT (PCD-CT) offer new opportunities for quantitation. Routine use of DECT is becoming more widely available and PCD-CT is rapidly developing. This review covers efforts to address an unmet need for improved quantitative imaging to better characterize disease, identify biomarkers, and evaluate therapeutic response, with an emphasis on multi-energy CT applications. The review will primarily discuss applications that have utilized quantitative metrics using both conventional and DECT, such as bone mineral density measurement, evaluation of renal lesions, and diagnosis of fatty liver disease. Other topics that will be discussed include efforts to improve quantitative CT volumetry and radiomics. Finally, we will address the use of quantitative CT to enhance image-guided techniques for surgery, radiotherapy and interventions and provide unique opportunities for development of new contrast agents.

CT Phantom Evaluation of 67,392 American College of Radiology Accreditation Examinations: Implications for Opportunistic Screening of Osteoporosis Using CT

OBJECTIVE. The purpose of this study was to investigate whether systematic bias in attenuation measurements occurs among CT scanners made by four major manufacturers and the relevance of this bias regarding opportunistic screening for osteoporosis. MATERIALS AND METHODS. Data on attenuation measurement accuracy were acquired using the American College of Radiology (ACR) accreditation phantom and were evaluated in a blinded fashion for four CT manufacturers (8500 accreditation submissions for manufacturer A; 18,575 for manufacturer B; 8278 for manufacturer C; and 32,039 for manufacturer D). The attenuation value for water, acrylic (surrogate for trabecular bone), and Teflon (surrogate for cortical bone; Chemours) materials for an adult abdominal CT technique (120 kV, 240 mA, standard reconstruction algorithm) was used in the analysis. Differences in attenuation value across all manufacturers were assessed using the Kruskal-Wallis test followed by a post hoc test for pairwise comparisons. RESULTS. The mean attenuation value for water ranged from -0.3 to 2.7 HU, with highly significant differences among all manufacturers (p < 0.001). For the trabecular bone surrogate, differences in attenuation values across all manufacturers were also highly significant (p < 0.001), with mean values of 120.9 (SD, 3.5), 124.6 (3.3), 126.9 (4.4), and 123.9 (3.4) HU for manufacturers A, B, C, and D, respectively. For the cortical bone surrogate, differences in attenuation values across all manufacturers were also highly significant (p < 0.001), with mean values of 939.0 (14.2), 874.3 (13.3), 897.6 (11.3), and 912.7 (13.4) HU for manufacturers A, B, C, and D, respectively. CONCLUSION. CT scanners made by different manufacturers show systematic offsets in attenuation measurement when compared with each other. Knowledge of these off-sets is useful for optimizing the accuracy of opportunistic diagnosis of osteoporosis.

Concurrent losses of skeletal muscle mass, adipose tissue and bone mineral density during bevacizumab / cytotoxic chemotherapy treatment for metastatic colorectal cancer

BACKGROUND

Changes in skeletal muscle mass (SMM), total adipose tissue mass (TAT) or bone mineral density (BMD) have been described in patients with cancer undergoing various treatments; simultaneous variations of all 3 tissues has not been reported.

METHODS

Data were prospectively collected in a clinical study (NCT00489697) including patients with liver metastases of colorectal cancer who received 4 cycles of bevacizumab in combination with cytotoxic chemotherapy. Computerized tomography (CT) at baseline and after chemotherapy was used to quantify skeletal muscle and adipose tissue cross-sectional areas, and mean lumbar spine BMD using validated approaches.

RESULTS

After exclusion of patients lacking adequate CT images or missing data, 72 subjects were included. Patients were 63% male, aged 63.2 ± 10.3 years, 100% had liver metastases and 54%, 24% and 22% respectively has 0, 1 and ≥2 extrahepatic metastases. 100% tolerated 4 cycles of treatment and none showed progressive disease at the end of treatment. The scan interval was 70 days (95% CI, 62.3 to 80.5). Thresholds for loss of tissue were defined as loss ≥ measurement error. 10% of patients showed no loss of any tissue and a further 43% lost one tissue (SMM, TAT or BMD); 47% of patients lost 2 tissues (16.5% lost SMM + TAT, 8% lost SMM + BMD, 10% lost TAT + BMD) or all 3 tissues (12.5%). Catabolic behavior (2 or 3 tissue loss vs 0 or 1 tissue loss) associated with disease burden, including unresectable primary tumor (p = 0.010), presence of extrahepatic (EH) metastases (p = 0.039) and number of EH metastases (p = 0.004). No association was found between the number of tissues lost and treatment response, which was uniformly high, or treatment toxicity, which was uniformly low.

CONCLUSION

Multiple tissues can be measured in routine CT images and these show considerable inter-individual variation. Substantial losses in some individuals appear to associate with disease burden.

Automatic opportunistic osteoporosis screening using low-dose chest computed tomography scans obtained for lung cancer screening

Objective

Osteoporosis is a prevalent and treatable condition, but it remains underdiagnosed. In this study, a deep learning-based system was developed to automatically measure bone mineral density (BMD) for opportunistic osteoporosis screening using low-dose chest computed tomography (LDCT) scans obtained for lung cancer screening.

Methods

First, a deep learning model was trained and tested with 200 annotated LDCT scans to segment and label all vertebral bodies (VBs). Then, the mean CT numbers of the trabecular area of target VBs were obtained based on the segmentation mask through geometric operations. Finally, a linear function was built to map the trabecular CT numbers of target VBs to their BMDs collected from approved software used for osteoporosis diagnosis. The diagnostic performance of the developed system was evaluated using an independent dataset of 374 LDCT scans with standard BMDs and osteoporosis diagnosis.

Results

Our deep learning model achieved a mean Dice coefficient of 86.6% for VB segmentation and 97.5% accuracy for VB labeling. Line regression and Bland-Altman analyses showed good agreement between the predicted BMD and the ground truth, with correlation coefficients of 0.964–0.968 and mean errors of 2.2–4.0 mg/cm³. The area under the curve (AUC) was 0.927 for detecting osteoporosis and 0.942 for distinguishing low BMD.

Conclusion

The proposed deep learning-based system demonstrated the potential to automatically perform opportunistic osteoporosis screening using LDCT scans obtained for lung cancer screening.

Key Points

• Osteoporosis is a prevalent but underdiagnosed condition that can increase the risk of fracture.

• A deep learning-based system was developed to fully automate bone mineral density measurement in low-dose chest computed tomography scans.

• The developed system achieved high accuracy for automatic opportunistic osteoporosis screening using low-dose chest computed tomography scans obtained for lung cancer screening.

X-ray-based quantitative osteoporosis imaging at the spine

Osteoporosis is a metabolic bone disease with a high prevalence that affects the population worldwide, particularly the elderly. It is often due to fractures associated with bone fragility that the diagnosis of osteoporosis becomes clinically evident. However, early diagnosis would be necessary to initiate therapy and to prevent occurrence of further fractures, thus reducing morbidity and mortality. X-ray-based imaging plays a key role for fracture risk assessment and monitoring of osteoporosis. Whereas over decades dual-energy X-ray absorptiometry (DXA) has been the main method used and still reflects the reference standard, another modality reemerges with quantitative computed tomography (QCT) because of its three-dimensional advantages and the opportunistic exploitation of routine CT scans. Against this background, this article intends to review and evaluate recent advances in the field of X-ray-based quantitative imaging of osteoporosis at the spine. First, standard DXA with the recent addition of trabecular bone score (TBS) is presented. Secondly, standard QCT, dual-energy BMD quantification, and opportunistic BMD screening in non-dedicated CT exams are discussed. Lastly, finite element analysis and microstructural parameter analysis are reviewed.

Improved prediction of incident vertebral fractures using opportunistic QCT compared to DXA

OBJECTIVES

To compare opportunistic quantitative CT (QCT) with dual energy X-ray absorptiometry (DXA) in their ability to predict incident vertebral fractures.

METHODS

We included 84 patients aged 50 years and older, who had routine CT including the lumbar spine and DXA within a 12-month period (baseline) as well as follow-up imaging after at least 12 months or who sustained an incident vertebral fracture documented earlier. Patients with bone disorders aside from osteoporosis were excluded. Fracture status and trabecular bone mineral density (BMD) were retrospectively evaluated in baseline CT and fracture status was reassessed at follow-up. BMDQCT was assessed by opportunistic QCT with asynchronous calibration of multiple MDCT scanners.

RESULTS

Sixteen patients had incident vertebral fractures showing lower mean BMDQCT than patients without fracture (p = 0.001). For the risk of incident vertebral fractures, the hazard ratio increased per SD in BMDQCT (4.07; 95% CI, 1.98-8.38), as well as after adjusting for age, sex, and prevalent fractures (2.54; 95% CI, 1.09-5.90). For DXA, a statistically significant increase in relative hazard per SD decrease in T-score was only observed after age and sex adjustment (1.57; 95% CI, 1.04-2.38). The predictability of incident vertebral fractures was good by BMDQCT (AUC = 0.76; 95% CI, 0.64-0.89) and non-significant by T-scores. Asynchronously calibrated CT scanners showed good long-term stability (linear drift ranging from - 0.55 to - 2.29 HU per year).

CONCLUSIONS

Opportunistic screening of mainly neurosurgical and oncologic patients in CT performed for indications other than densitometry allows for better risk assessment of imminent vertebral fractures than dedicated DXA.

KEY POINTS

• Opportunistic QCT predicts osteoporotic vertebral fractures better than DXA reference standard in mainly neurosurgical and oncologic patients. • More than every second patient (56%) with an incident vertebral fracture was misdiagnosed not having osteoporosis according to DXA. • Standard ACR QCT-cutoff values for osteoporosis (< 80 mg/cm 3 ) and osteopenia (≤ 120 mg/cm 3 ) can also be applied scanner independently in calibrated opportunistic QCT.

Translation of Quantitative Imaging Biomarkers into Clinical Chest CT

Quantitative imaging has been proposed as the next frontier in radiology as part of an effort to improve patient care through precision medicine. In 2007, the Radiological Society of North America launched the Quantitative Imaging Biomarkers Alliance (QIBA), an initiative aimed at improving the value and practicality of quantitative imaging biomarkers by reducing variability across devices, sites, patients, and time. Chest CT occupies a strategic position in this initiative because it is one of the most frequently used imaging modalities, anatomically encompassing the leading causes of mortality worldwide. To date, QIBA has worked on profiles focused on the accurate, reproducible, and meaningful use of volumetric measurements of lung lesions in chest CT. However, other quantitative methods are on the verge of translation from research grounds into clinical practice, including (a) assessment of parenchymal and airway changes in patients with chronic obstructive pulmonary disease, (b) analysis of perfusion with dual-energy CT biomarkers, and (c) opportunistic screening for coronary atherosclerosis and low bone mass by using chest CT examinations performed for other indications. The rationale for and the key facts related to the application of these quantitative imaging biomarkers in cardiothoracic chest CT are presented. ^©RSNA, 2019 See discussion on this article by Buckler (pp 977-980).

The influence of CT and dual-energy X-ray absorptiometry (DXA) bone density on quantitative [18F] sodium fluoride PET

Background

[¹⁸F] sodium fluoride PET/CT provides quantitative measures of bone metabolic activity expressed by the parameters standardised uptake value (SUV) and bone plasma clearance (K _i) that correlate with measurements of bone formation rate obtained by bone biopsy with double tetracycline labelling. Both SUV and K _i relate to the tracer uptake in each millilitre of tissue. In general, the bone region of interest (ROI) includes both mineralised bone {generally with a high concentration of [¹⁸F]NaF} and bone marrow (with a much lower concentration), suggesting that correcting SUV and K _i for volumetric bone mineral density (vBMD) and measuring them with respect to the tracer uptake in each gram of bone mineral might improve the correlation with the findings of bone biopsy. As a first test of this hypothesis, we looked for positive correlations between SUV and K _i values with CT and DXA bone mineral density (BMD) parameters measured in the same ROI.

Methods

A retrospective reanalysis was performed of 63 lumbar spine [¹⁸F]NaF PET/CT scans acquired in four earlier studies. The quantitative PET parameters SUV and K _i were measured in L1-L4 and Hounsfield units (HU) measured on the CT scans in the same ROI. Spine BMD data was also obtained from DXA scans in the form of areal BMD and used to derive the bone mineral apparent density (BMAD, an estimate of vBMD). Scatter plots were drawn of SUV and K _i against HU, BMAD and areal BMD and the Spearman rank correlation coefficients derived for each plot.

Results

All correlations were positive and statistically significant. Correlations were highest for HU (SUV: R_S =0.513, P<0.0001; K _i: R_S =0.429, P=0.0005) and lowest for areal BMD (SUV: R_S =0.353, P=0.005; K _i: R_S =0.274, P=0.03).

Conclusions

The results demonstrate significant positive correlations between SUV and K _i and vBMD measurements in the form of HU from CT or BMAD and areal BMD from DXA. These findings justify further exploration of the relationship between SUV and K _i [¹⁸F]NaF PET/CT measurements and CT or DXA measurements of vBMD to examine whether normalization for bone density might improve their correlation with bone metabolic activity as measured by bone biopsy.

Patient-Specific Phantomless Estimation of Bone Mineral Density and Its Effects on Finite Element Analysis Results: A Feasibility Study

Objectives

This study proposes a regression model for the phantomless Hounsfield units (HU) to bone mineral density (BMD) conversion including patient physical factors and analyzes the accuracy of the estimated BMD values.

Methods

The HU values, BMDs, circumferences of the body, and cross-sectional areas of bone were measured from 39 quantitative computed tomography images of L2 vertebrae and hips. Then, the phantomless HU-to-BMD conversion was derived using a multiple linear regression model. For the statistical analysis, the correlation between the estimated BMD values and the reference BMD values was evaluated using Pearson's correlation test. Voxelwise BMD and finite element analysis (FEA) results were analyzed in terms of root-mean-square error (RMSE) and strain energy density, respectively.

Results

The HU values and circumferences were statistically significant (p < 0.05) for the lumbar spine, whereas only the HU values were statistically significant (p < 0.05) for the proximal femur. The BMD values estimated using the proposed HU-to-BMD conversion were significantly correlated with those measured using the reference phantom: Pearson's correlation coefficients of 0.998 and 0.984 for the lumbar spine and proximal femur, respectively. The RMSEs of the estimated BMD values for the lumbar spine and hip were 4.26 ± 0.60 (mg/cc) and 8.35 ± 0.57 (mg/cc), respectively. The errors of total strain energy were 1.06% and 0.91%, respectively.

Conclusions

The proposed phantomless HU-to-BMD conversion demonstrates the potential of precisely estimating BMD values from CT images without the reference phantom and being utilized as a viable tool for FEA-based quantitative assessment using routine CT images.

Highlights of the annual scientific meeting of the 24th congress of the European Society of Musculoskeletal Radiology (ESSR) 2017

This paper summarizes the main aspects of the 24th Annual Scientific Meeting of the European Society of Musculoskeletal Radiology (ESSR), which was hosted in Bari (Italy) in June 2017.