Bone mineral density measurements derived from dual-layer spectral CT enable opportunistic screening for osteoporosis

Utilizing artificial intelligence to determine bone mineral density using spectral CT

BACKGROUND

Dual-energy computed tomography (DECT) has demonstrated the feasibility of using HAP-water to respond to BMD changes without requiring dedicated software or calibration. Artificial intelligence (AI) has been utilized for diagnosising osteoporosis in routine CT scans but has rarely been used in DECT. This study investigated the diagnostic performance of an AI system for osteoporosis screening using DECT images with reference quantitative CT (QCT).

METHODS

This prospective study included 120 patients who underwent DECT and QCT scans from August to December 2023. Two convolutional neural networks, 3D RetinaNet and U-Net, were employed for automated vertebral body segmentation. The accuracy of the bone mineral density (BMD) measurement was assessed with relative measurement error (RME%). Linear regression and Bland-Altman analyses were performed to compare the BMD values between the AI and manual systems with those of the QCT. The diagnostic performance of the AI and manual systems for osteoporosis and low BMD was evaluated using receiver operating characteristic curve analysis.

RESULTS

The overall mean RME% for the AI and manual systems were - 15.93 ± 12.05 % and - 25.47 ± 14.83 %, respectively. BMD measurements using the AI system achieved greater agreement with the QCT results than those using the manual system (R2 = 0.973, 0.948, p < 0.001; mean errors, 23.27, 35.71 mg/cm3; 95 % LoA, -9.72 to 56.26, -11.45 to 82.87 mg/cm3). The areas under the curve for the AI and manual systems were 0.979 and 0.933 for detecting osteoporosis and 0.980 and 0.991 for low BMD.

CONCLUSION

This AI system could achieve relatively high accuracy for automated BMD measurement on DECT scans, providing great potential for the follow-up of BMD in osteoporosis screening.

In Vivo Bone Mineral Density Assessment With Spectral Localizer Radiographs From Photon-Counting Detector CT: Prospective Comparison With DXA

PURPOSE

The aim of this study was to determine in a prospective patient study the accuracy of areal bone mineral density (aBMD) measurements with spectral localizer radiographs obtained with a clinical photon-counting detector computed tomography (PCD-CT) scanner in comparison with dual-energy x-ray absorptiometry (DXA).

METHODS

In this institutional review board-approved, prospective study, 41 patients (15 females, 26 males; mean age 61.3 years, age range 35-78 years) underwent PCD-CT of the abdomen with a spectral localizer radiograph (tube voltage 140 kVp, tube current 30 mA) and DXA within a median of 45 days. aBMD values were derived for lumbar vertebrae L1-L4 from both methods and were compared with linear regression, Pearson correlation, intraclass correlation coefficients (ICCs), and Bland-Altman plots. T-scores were calculated on a patient level and were compared between methods.

RESULTS

DXA and spectral localizer radiographs showed strong correlation in aBMD measurements (R = 0.97, P < 0.001) and patient level T-scores (R = 0.99, P < 0.001). There was a strong agreement between aBMD from both methods (ICC, 0.96; 95% CI, 0.94-0.97). Bland-Altman analysis revealed a very small mean difference in aBMD between methods (mean absolute error 0.019 g/cm2) with narrow limits of agreement (-0.083 g/cm2 to 0.121 g/cm2). Similarly, there were small differences in regard to the T-score (mean absolute error 0.156) with narrow limits of agreement (-0.422 to 0.734) between methods. ICCs indicated an excellent agreement between T-scores from DXA and spectral localizer radiographs (ICC, 0.98; 95% confidence interval, 0.95-0.99).

CONCLUSIONS

Our prospective patient study indicates that spectral localizer radiographs obtained with a clinical PCD-CT system enable accurate quantification of the lumbar bone areal mineral density. This opens up the opportunity for opportunistic screening of osteoporosis in patients who undergo CT for other indications.

Dark-field radiography for the detection of bone microstructure changes in osteoporotic human lumbar spine specimens

BACKGROUND

Dark-field radiography imaging exploits the wave character of x-rays to measure small-angle scattering on material interfaces, providing structural information with low radiation exposure. We explored the potential of dark-field imaging of bone microstructure to improve the assessment of bone strength in osteoporosis.

METHODS

We prospectively examined 14 osteoporotic/osteopenic and 21 non-osteoporotic/osteopenic human cadaveric vertebrae (L2-L4) with a clinical dark-field radiography system, micro-computed tomography (CT), and spectral CT. Dark-field images were obtained in both vertical and horizontal sample positions. Bone microstructural parameters (trabecular number, Tb.N; trabecular thickness, Tb.Th; bone volume fraction, BV/TV; degree of anisotropy, DA) were measured using standard ex vivo micro-CT, while hydroxyapatite density was measured using spectral CT. Correlations were assessed using Spearman rank correlation coefficients.

RESULTS

The measured dark-field signal was lower in osteoporotic/osteopenic vertebrae (vertical position, 0.23 ± 0.05 versus 0.29 ± 0.04, p < 0.001; horizontal position, 0.28 ± 0.06 versus 0.34 ± 0.04, p = 0.003). The dark-field signal from the vertical position correlated significantly with Tb.N (ρ = 0.46, p = 0.005), BV/TV (ρ = 0.45, p = 0.007), DA (ρ = -0.43, p = 0.010), and hydroxyapatite density (ρ = 0.53, p = 0.010). The calculated ratio of vertical/horizontal dark-field signal correlated significantly with Tb.N (ρ = 0.43, p = 0.011), BV/TV (ρ = 0.36, p = 0.032), DA (ρ = -0.51, p = 0.002), and hydroxyapatite density (ρ = 0.42, p = 0.049).

CONCLUSION

Dark-field radiography is a feasible modality for drawing conclusions on bone microarchitecture in human cadaveric vertebral bone.

RELEVANCE STATEMENT

Gaining knowledge of the microarchitecture of bone contributes crucially to predicting bone strength in osteoporosis. This novel radiographic approach based on dark-field x-rays provides insights into bone microstructure at a lower radiation exposure than that of CT modalities.

KEY POINTS

Dark-field radiography can give information on bone microstructure with low radiation exposure. The dark-field signal correlated positively with bone microstructure parameters. Dark-field signal correlated negatively with the degree of anisotropy. Dark-field radiography helps to determine the directionality of trabecular loss.

Automated deep learning-based bone mineral density assessment for opportunistic osteoporosis screening using various CT protocols with multi-vendor scanners

This retrospective study examined the diagnostic efficacy of automated deep learning-based bone mineral density (DL-BMD) measurements for osteoporosis screening using 422 CT datasets from four vendors in two medical centers, encompassing 159 chest, 156 abdominal, and 107 lumbar spine datasets. DL-BMD values on L1 and L2 vertebral bodies were compared with manual BMD (m-BMD) measurements using Pearson's correlation and intraclass correlation coefficients. Strong agreement was found between m-BMD and DL-BMD in total CT scans (r = 0.953, p < 0.001). The diagnostic performance of DL-BMD was assessed using receiver operating characteristic analysis for osteoporosis and low BMD by dual-energy x-ray absorptiometry (DXA) and m-BMD. Compared to DXA, DL-BMD demonstrated an AUC of 0.790 (95% CI 0.733-0.839) for low BMD and 0.769 (95% CI 0.710-0.820) for osteoporosis, with sensitivity, specificity, and accuracy of 80.8% (95% CI 74.2-86.3%), 56.3% (95% CI 43.4-68.6%), and 74.3% (95% CI 68.3-79.7%) for low BMD and 65.4% (95% CI 50.9-78.0%), 70.9% (95% CI 63.8-77.3%), and 69.7% (95% CI 63.5-75.4%) for osteoporosis, respectively. Compared to m-BMD, DL-BMD showed an AUC of 0.983 (95% CI 0.973-0.993) for low BMD and 0.972 (95% CI 0.958-0.987) for osteoporosis, with sensitivity, specificity, and accuracy of 97.3% (95% CI 94.5-98.9%), 85.2% (95% CI 78.8-90.3%), and 92.7% (95% CI 89.7-95.0%) for low BMD and 94.4% (95% CI 88.3-97.9%), 89.5% (95% CI 85.6-92.7%), and 90.8% (95% CI 87.6-93.4%) for osteoporosis, respectively. The DL-based method can provide accurate and reliable BMD assessments across diverse CT protocols and scanners.

The accuracy and clinical utility of spectral CT bone density measurement in the lumbar spine of unenhanced images: A narrative review

OBJECTIVES

To review and evaluate available literature on spectral computed tomography (SCT) bone mineral density (BMD) measurement in adult thoracolumbar vertebrae of unenhanced images compared to quantitative computed tomography (QCT), to understand its current clinical utility.

KEY FINDINGS

Keyword searches in four databases identified four cross-sectional studies which acquired an SCT BMD measurement in thoracolumbar vertebrae and compared this respectively to QCT, which were then critically appraised using the AXIS tool for cross-sectional studies. 862 vertebrae were measured between T10-S1 in 368 patients. Three studies demonstrated a statistically significant correlation between SCT and QCT for the measurement of Hydroxyapatite (HAP) and calcium (r = 0.86-0.96). One study demonstrated a diagnostic accuracy of 96% using a receiver operating curve.

CONCLUSIONS

SCT measurements of HAP and calcium in the lumbar vertebrae are comparable to QCT for patients with no additional pathology present. However, further research is required to evaluate diagnostic accuracy before clinical application.

IMPLICATIONS FOR PRACTICE

SCT BMD measurement has the potential to be developed as a screening tool for osteoporosis within the fracture liaison service (FLS). This could aid in the identification of patients with osteoporosis and address the current treatment gap. Nonetheless, many factors must be considered for this application including staff training, radiation protection and patient engagement with the screening programme.

Quantitative calcium-based assessment of osteoporosis in dual-layer spectral CT

OBJECTIVES

To evaluate a novel calcium-only imaging technique (VCa) with subtracted bone marrow in osteoporosis in dual-layer CT (DLCT) compared to conventional CT images (CI) and dual-energy X-ray absorptiometry (DXA).

MATERIAL AND METHODS

Images of a multi-energy CT phantom with calcium inserts, quantitative CT calibration phantom, and of 55 patients (mean age: 64.6 ± 11.5 years) were acquired on a DLCT to evaluate bone mineral density (BMD). CI, calcium-suppressed images, and VCa were calculated. For investigating the association of VCa and CI with DXA a subsample of 30 patients (<90 days between DXA and CT) was used. Multiple regression analysis was performed to identify further factors improving the prediction of DXA BMD.

RESULTS

The calcium concentrations of the CT phantom inserts were significantly associated with CT numbers from VCa (R2 = 0.94) and from CI (R2 = 0.89-0.92). VCa showed significantly higher CT numbers than CI in the phantom (p ≤ 0.001) and clinical setting (p < 0.001). CT numbers from VCa were significantly associated with CI (R2 = 0.95, p < 0.001) and with DXA (R2 = 0.31, p = 0.007), whereas no significant association between DXA and CI was found. Prediction of DXA BMD based on CT numbers derived from VCa yielded R2 = 0.76 in multiple regression analysis. ROC for the differentiation of normal from pathologic BMD in VCa yielded an AUC of 0.7, and a cut-off value of 126HU (sensitivity: 0.90; specificity: 0.47).

CONCLUSION

VCa images showed better agreement with DXA and known calcium concentrations than CI, and could be used to estimate BMD. A VCa cut-off of 126HU could be used to identify abnormal bone mineral density.

Value of Dual-Energy CT-Derived Metrics for the Prediction of Bone Non-union in Distal Radius Fractures

RATIONALE AND OBJECTIVES

Bone non-union is a serious complication of distal radius fractures (DRF) that can result in functional limitations and persistent pain. However, no accepted method has been established to identify patients at risk of developing bone non-union yet. This study aimed to compare various CT-derived metrics for bone mineral density (BMD) assessment to identify predictive values for the development of bone non-union.

MATERIALS AND METHODS

CT images of 192 patients with DRFs who underwent unenhanced dual-energy CT (DECT) of the distal radius between 03/2016 and 12/2020 were retrospectively identified. Available follow-up imaging and medical health records were evaluated to determine the occurrence of bone non-union. DECT-based BMD, trabecular Hounsfield unit (HU), cortical HU and cortical thickness ratio were measured in normalized non-fractured segments of the distal radius.

RESULTS

Patients who developed bone non-union were significantly older (median age 72 years vs. 54 years) and had a significantly lower DECT-based BMD (median 68.1 mg/cm3 vs. 94.6 mg/cm3, p < 0.001). Other metrics (cortical thickness ratio, cortical HU, trabecular HU) showed no significant differences. ROC and PR curve analyses confirmed the highest diagnostic accuracy for DECT-based BMD with an area under the curve (AUC) of 0.83 for the ROC curve and an AUC of 0.46 for the PR curve. In logistic regression models, DECT-based BMD was the sole metric significantly associated with bone non-union.

CONCLUSION

DECT-derived metrics can accurately predict bone non-union in patients who sustained DRF. The diagnostic performance of DECT-based BMD is superior to that of HU-based metrics and cortical thickness ratio.

Calcium-Based Imaging of the Spine at Dual-Layer CT and Evaluation of Vertebral Fractures in Multiple Myeloma

PURPOSE

To evaluate the prediction of vertebral fractures in plasma cell dyscrasias using dual-layer CT (DLCT) with quantitative assessment of conventional CT image data (CI), calcium suppressed image data (CaSupp), and calculation of virtual calcium-only (VCa) image data.

MATERIAL AND METHODS

Patients (n = 81) with the diagnosis of a plasma cell dyscrasia and whole-body DLCT at the time of diagnosis and follow-up were retrospectively enrolled. CI, CaSupp25, and CaSupp100 were quantitatively analyzed using regions of interest in the lumbar vertebral bodies and fractured vertebral bodies on baseline or follow-up imaging. VCa were calculated by subtraction (CaSupp100-CaSupp25), delineating bone only. Logistic regression analyses were performed to assess the possibility of imminent spine fractures.

RESULTS

In 24 patients, new vertebral fractures were observed in the follow-up imaging. The possibility of new vertebral fractures was significant for baseline assessment of CT numbers in CI, CaSupp25, and VCa (p = 0.01, respectively), with a higher risk for new fractures in the case of lower CT numbers in CI (Odds ratio = [0.969; 0.994]) and VCa (Odds ratio = [0.978; 0.995]) and in the case of higher CT numbers in CaSupp 25 (Odds ratio 1.015 [1.006; 1.026]). Direct model comparisons implied that CT numbers in CaSupp 25 and VCa might show better fracture prediction than those in CI (R2 = 0.18 both vs. 0.15; AICc = 91.95, 91.79 vs. 93.62), suggesting cut-off values for CI at 103 HU (sensitivity: 54.2%; specificity: 82.5; AUC: 0.69), for VCa at 129 HU (sensitivity: 41.7%; specificity: 94.7; AUC: 0.72).

CONCLUSIONS

Quantitative assessment with CaSupp and calculation of VCa is feasible to predict the vertebral fracture risk in MM patients. DLCT may prove useful in detecting imminent fractures.

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.

Longitudinal MR-based proton-density fat fraction (PDFF) and T2* for the assessment of associations between bone marrow changes and myelotoxic chemotherapy

OBJECTIVES

MR imaging-based proton density fat fraction (PDFF) and T2* imaging has shown to be useful for the evaluation of degenerative changes in the spine. Therefore, the aim of this study was to investigate the influence of myelotoxic chemotherapy on the PDFF and T2* of the thoracolumbar spine in comparison to changes in bone mineral density (BMD).

METHODS

In this study, 19 patients were included who had received myelotoxic chemotherapy (MC) and had received a MR imaging scan of the thoracolumbar vertebrates before and after the MC. Every patient was matched for age, sex, and time between the MRI scans to two controls without MC. All patients underwent 3-T MR imaging including the thoracolumbar spine comprising chemical shift encoding-based water-fat imaging to extract PDFF and T2* maps. Moreover, trabecular BMD values were determined before and after chemotherapy. Longitudinal changes in PDFF and T2* were evaluated and compared to changes in BMD.

RESULTS

Absolute mean differences of PDFF values between scans before and after MC were at 8.7% (p = 0.01) and at -0.5% (p = 0.57) in the control group, resulting in significantly higher changes in PDFF in patients with MC (p = 0.008). BMD and T2* values neither showed significant changes in patients with nor in those without myelotoxic chemotherapy (p = 0.15 and p = 0.47). There was an inverse, yet non-significant correlation between changes in PDFF and BMD found in patients with myelotoxic chemotherapy (r = -0.41, p = 0.12).

CONCLUSION

Therefore, PDFF could be a useful non-invasive biomarker in order to detect changes in the bone marrow in patients receiving myelotoxic therapy.

CLINICAL RELEVANCE STATEMENT

Using PDFF as a non-invasive biomarker for early bone marrow changes in oncologic patients undergoing myelotoxic treatment may help enable more targeted countermeasures at commencing states of bone marrow degradation and reduce risks of possible fragility fractures.

KEY POINTS

Quantifying changes in bone marrow fat fraction, as well as T2* caused by myelotoxic pharmaceuticals using proton density fat fraction, is feasible. Proton density fat fraction could potentially be established as a non-invasive biomarker for early bone marrow changes in oncologic patients undergoing myelotoxic treatment.

Functional Imaging in Musculoskeletal Disorders in Menopause

Menopause-related musculoskeletal (MSK) disorders include osteoporosis, osteoarthritis (OA), sarcopenia and sarco-obesity. This review focuses on the applications of nuclear medicine for the functional imaging of the aforementioned clinical conditions. Bone Scan (BS) with 99mTc-labeled phosphonates, alone or in combination with MRI, can identify "fresh" vertebral collapse due to age-associated osteoporosis and provides quantitative parameters characterized by a good correlation with radiological indices in patients with OA. 18F-NaF PET, particularly when performed by dynamic scan, has given encouraging results for measuring bone turnover in osteoporosis and allows the evaluation of subchondral bone metabolic activity in OA. FDG PET can help discriminate between pathological and nonpathological vertebral fractures, especially by applying appropriate SUV-based thresholds. In OA, it can effectively image inflamed joints and support appropriate clinical management. Preliminary evidences suggest a possible application of FDG in sarco-obesity for the detection and quantification of visceral adipose tissue (VAT). Further studies are needed to better define the role of nuclear medicine in menopause-related MSK disease, especially as regards the possible impact of new radiopharmaceuticals (ie, FAPI and RGD peptides) and recent technological advances (eg, total-body PET/CT scanners).

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.

Harnessing artificial intelligence in radiology to augment population health

This review article serves to highlight radiological services as a major cost driver for the healthcare sector, and the potential improvements in productivity and cost savings that can be generated by incorporating artificial intelligence (AI) into the radiology workflow, referencing Singapore healthcare as an example. More specifically, we will discuss the opportunities for AI in lowering healthcare costs and supporting transformational shifts in our care model in the following domains: predictive analytics for optimising throughput and appropriate referrals, computer vision for image enhancement (to increase scanner efficiency and decrease radiation exposure) and pattern recognition (to aid human interpretation and worklist prioritisation), natural language processing and large language models for optimising reports and text data-mining. In the context of preventive health, we will discuss how AI can support population level screening for major disease burdens through opportunistic screening and democratise expertise to increase access to radiological services in primary and community care.

Association of Phantomless Dual-Energy CT-based Volumetric Bone Mineral Density with the Prevalence of Acute Insufficiency Fractures of the Spine

RATIONALE AND OBJECTIVES

To evaluate the bone mineral density (BMD) of the lumbar spine derived from dual-energy CT (DECT)-based volumetric material decomposition and its association with acute insufficiency fractures of the thoracolumbar spine.

MATERIALS AND METHODS

L1 of 160 patients (77 men, 83 women; mean age 64.3 years, range, 22-94 years) who underwent third-generation dual-source DECT between January 2016 and December 2021 due to suspected insufficiency fractures was retrospectively analyzed. All depicted vertebrae were examined for signs of recent fractures. A dedicated DECT postprocessing software using material decomposition was applied for phantomless BMD assessment. Receiver-operating characteristic (ROC) analysis identified optimal BMD thresholds. Associations of BMD, sex, and age with the occurrence of insufficiency fractures were examined with logistic regression models.

RESULTS

A DECT-derived BMD threshold of 120.40 mg/cm³ yielded 90.1% specificity and 59.32% sensitivity to differentiate patients with at least one insufficiency fracture from patients without fracture. No patient without fracture had a DECT-derived BMD below 85 mg/cm3. Lower DECT-derived bone mineral density was associated with an increased risk of insufficiency fractures (Odds ratio of 0.93, 95% CI, 0.91-0.96, p < 0.001). Overall ROC-derived AUC was 0.82 (p < 0.0001) for the differentiation of patients that sustained an insufficiency fracture from the control group.

CONCLUSION

Dual-Energy CT-based BMD assessment can accurately differentiate patients with acute insufficiency fractures of the thoracolumbar spine from patients without fracture. This algorithm can be used for phantomless risk stratification of patients undergoing routine CT to sustain insufficiency fractures of the thoracolumbar spine The identified cut-off value of 120.4 mg/cm³ is in line with current American College of Radiology (ACR) recommendations to differentiate healthy individuals from those with reduced bone mineral density.

Quantification of bone quality and distribution of the proximal humerus with dual-energy computed tomography

Background

The proximal humerus is a common site of osteoporotic fractures, and bone quality is a predictor of surgical reduction quality. Dual-energy computed tomography (DECT) is assuming an increasingly important role in the quantification of bone mineral density (BMD) due it is ability to perform three-material decomposition. We aimed to analyze the bone quality and distribution of the proximal humerus with DECT quantitatively.

Methods

Sixty-five consecutive patients (average age 49.5±15.2 years; male: female ratio 32:33) without proximal humerus fractures who had undergone DECT were retrospectively selected. The humeral head was divided into 4 regions on a cross section in the medial plane between the greater tuberosity and the surgical neck. The quantitative parameters, including virtual noncalcium (VNCa) value, computed tomography value of calcium (CaCT), computed tomography value of mixed-energy images (regular CT value) (rCT), and relative calcium density (rCaD), were measured. The correlations between the quantitative parameters and age and body mass index (BMI) were analyzed, and the correlations of age, sex, BMI, region of the humeral head, and VNCa value on CaCT were evaluated.

Results

The differences in CaCT, rCT, and rCaD between the 4 regions of proximal humerus were statistically significant (P<0.001), while the difference in VNCa values was not (P=0.688). The calcium concentration (CaCT and rCaD) was the densest in the posteromedial zone. The differences of CaCT, rCT, and rCaD between males and females in the 4 regions of proximal humerus were statistically significant (P<0.05), while those of the posterolateral zone were not (rCT; P>0.05). The differences in VNCa values between males and females were also not significant (P>0.05). Multivariable linear regression analysis indicated that sex, age, BMI, regions, and VNCa were significant (P<0.05) predictors of the CaCT value.

Conclusions

The concentration of calcium was the densest in the posteromedial region of proximal humerus, and the VNCa value of DECT may be used for quantifying the BMD of the proximal humerus.

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.

Computed Tomography Bone Imaging: Pushing the Boundaries in Clinical Practice

Bone microarchitecture has several clinical implications over and above estimating bone strength. Computed tomography (CT) analysis mainly uses high-resolution peripheral quantitative CT and micro-CT, research imaging techniques, most often limited to peripheral skeleton assessment. Ultra-high-resolution (UHR) CT and photon-counting detector CT, two commercially available techniques, provide images that can approach the spatial resolution of the trabeculae, bringing bone microarchitecture analysis into clinical practice and improving depiction of bone vascularization, tumor matrix, and cortical and periosteal bone. This review presents bone microarchitecture anatomy, principles of analysis, reference measurements, and an update on the performance and potential clinical applications of these new CT techniques. We also share our clinical experience and technical considerations using an UHR-CT device.

Comparison of volumetric and areal bone mineral density in CT and scout scans using spectral detector technology

BACKGROUND

To determine whether denoised areal bone mineral density (BMD) measurements from scout scans in spectral detector computed tomography (CT) correlate with volumetric trabecular BMD for opportunistic osteoporosis screening.

METHODS

A 64-slice single-source dual-layer spectral CT scanner was used to acquire scout scan data of 228 lumbar vertebral bodies within 57 patients. Scout scans in anterior-posterior (AP) view were performed with a dose of < 0.06 mSv and spectrally decomposed into areal BMD (aBMD) values. A spectral dictionary denoising algorithm was applied to increase the signal-to-noise ratio (SNR). Volumetric trabecular bone mineral density (vBMD) was determined via material decomposition. A 3D convolutional network for image segmentation and labeling was applied for automated vBMD quantification. Projected maps were used to compare the classification accuracy of AP and lateral scout scans.

RESULTS

The denoising algorithm led to the minimization of anticorrelated noise in spectral maps and an SNR increase from 5.23 to 13.4 (p < 0.002). Correlation analysis between vBMD and measured AP aBMD, projected AP, and lateral aBMD showed a Pearson correlation coefficient of 0.68, 0.81, and 0.90, respectively. The sensitivity and specificity for the osteoporosis classification task were higher in lateral projection images than in AP crystallizing in an increased area under the curve value of 0.99 versus 0.90.

CONCLUSION

Denoised material-specific aBMD maps show a positive correlation to vBMD, enabling spectral scout scans as an opportunistic predictor for osteoporotic patients. This could be applied routinely as a screening tool in patients undergoing a CT examination.

RELEVANCE STATEMENT

Scout-based DEXA could be applied routinely as a screening tool in patients undergoing a CT examination.

KEY POINTS

• Spectral scout scans can be used as a dual-energy x-ray absorptiometry-like screening tool. • Spectral dictionary denoising on projection images increases the signal-to-noise ratio. • Positive correlation between volumetric and areal bone mineral density is observed. • Lateral projections increase osteoporosis classification accuracy compared to anterior-posterior projections.

Dark-field X-ray imaging for the assessment of osteoporosis in human lumbar spine specimens

Background: Dark-field imaging is a novel imaging modality that allows for the assessment of material interfaces by exploiting the wave character of x-ray. While it has been extensively studied in chest imaging, only little is known about the modality for imaging other tissues. Therefore, the purpose of this study was to evaluate whether a clinical X-ray dark-field scanner prototype allows for the assessment of osteoporosis. Materials and methods: In this prospective study we examined human cadaveric lumbar spine specimens (vertebral segments L2 to L4). We used a clinical prototype for dark-field radiography that yields both attenuation and dark-field images. All specimens were scanned in lateral orientation in vertical and horizontal position. All specimens were additionally imaged with CT as reference. Bone mineral density (BMD) values were derived from asynchronously calibrated quantitative CT measurements. Correlations between attenuation signal, dark-field signal and BMD were assessed using Spearman's rank correlation coefficients. The capability of the dark-field signal for the detection of osteoporosis/osteopenia was evaluated with receiver operating characteristics (ROC) curve analysis. Results: A total of 58 vertebrae from 20 human cadaveric spine specimens (mean age, 73 years ±13 [standard deviation]; 11 women) were studied. The dark-field signal was positively correlated with the BMD, both in vertical (r = 0.56, p < .001) and horizontal position (r = 0.43, p < .001). Also, the dark-field signal ratio was positively correlated with BMD (r = 0.30, p = .02). No correlation was found between the signal ratio of attenuation signal and BMD (r = 0.14, p = .29). For the differentiation between specimens with and without osteoporosis/osteopenia, the area under the ROC curve (AUC) was 0.80 for the dark-field signal in vertical position. Conclusion: Dark-field imaging allows for the differentiation between spine specimens with and without osteoporosis/osteopenia and may therefore be a potential biomarker for bone stability.

Automatic segmentation and radiomic texture analysis for osteoporosis screening using chest low-dose computed tomography

OBJECTIVE

This study developed a diagnostic tool combining machine learning (ML) segmentation and radiomic texture analysis (RTA) for bone density screening using chest low-dose computed tomography (LDCT).

METHODS

A total of 197 patients who underwent LDCT followed by dual-energy X-ray absorptiometry were analyzed. First, an autosegmentation model was trained using LDCT to delineate the thoracic vertebral body (VB). Second, a two-level classifier was developed using radiomic features extracted from VBs for the hierarchical pairwise classification of each patient's bone status. All the patients were initially classified as either normal or abnormal, and all patients with abnormal bone density were then subdivided into an osteopenia group and an osteoporosis group. The performance of the classifier was evaluated through fivefold cross-validation.

RESULTS

The model for automated VB segmentation achieved a Sorenson-Dice coefficient of 0.87 ± 0.01. Furthermore, the area under the receiver operating characteristic curve scores for the two-level classifier were 0.96 ± 0.01 for detecting abnormal bone density (accuracy = 0.91 ± 0.02; sensitivity = 0.93 ± 0.03; specificity = 0.89 ± 0.03) and 0.98 ± 0.01 for distinguishing osteoporosis (accuracy = 0.94 ± 0.02; sensitivity = 0.95 ± 0.03; specificity = 0.93 ± 0.03). The testing prediction accuracy levels for the first- and second-level classifiers were 0.92 ± 0.04 and 0.94 ± 0.05, respectively. The overall testing prediction accuracy of our method was 0.90 ± 0.05.

CONCLUSION

The combination of ML segmentation and RTA for automated bone density prediction based on LDCT scans is a feasible approach that could be valuable for osteoporosis screening during lung cancer screening.

KEY POINTS

• This study developed an automatic diagnostic tool combining machine learning-based segmentation and radiomic texture analysis for bone density screening using chest low-dose computed tomography. • The developed method enables opportunistic screening without quantitative computed tomography or a dedicated phantom. • The developed method could be integrated into the current clinical workflow and used as an adjunct for opportunistic screening or for patients who are ineligible for screening with dual-energy X-ray absorptiometry.

Opportunistic Screening Techniques for Analysis of CT Scans

PURPOSE OF REVIEW

Opportunistic screening is a combination of techniques to identify subjects of high risk for osteoporotic fracture using routine clinical CT scans prescribed for diagnoses unrelated to osteoporosis. The two main components are automated detection of vertebral fractures and measurement of bone mineral density (BMD) in CT scans, in which a phantom for calibration of CT to BMD values is not used. This review describes the particular challenges of opportunistic screening and provides an overview and comparison of current techniques used for opportunistic screening. The review further outlines the performance of opportunistic screening.

RECENT FINDINGS

A wide range of technologies for the automatic detection of vertebral fractures have been developed and successfully validated. Most of them are based on artificial intelligence algorithms. The automated differentiation of osteoporotic from traumatic fractures and vertebral deformities unrelated to osteoporosis, the grading of vertebral fracture severity, and the detection of mild vertebral fractures is still problematic. The accuracy of automated fracture detection compared to classical radiological semi-quantitative Genant scoring is about 80%. Accuracy errors of alternative BMD calibration methods compared to simultaneous phantom-based calibration used in standard quantitative CT (QCT) range from below 5% to about 10%. The impact of contrast agents, frequently administered in clinical CT on the determination of BMD and on fracture risk determination is still controversial. Opportunistic screening, the identification of vertebral fracture and the measurement of BMD using clinical routine CT scans, is feasible but corresponding techniques still need to be integrated into the clinical workflow and further validated with respect to the prediction of fracture risk.

The new fast kilovoltage-switching dual-energy computed tomography for measuring bone mineral density

Background

The update in technology may impact the accuracy in measuring bone mineral density (BMD). However, the application of the new fast kilovoltage (kV)-switching dual-energy computed tomography (DECT) for BMD measurement has not yet been reported. This study aimed to examine the accuracy and precision of the new fast kV-switching DECT in measuring BMD and to evaluate its applicability in clinical BMD measurement.

Methods

Forty sets of the new fast kV-switching DECT scans and one quantitative computed tomography (QCT) scan were performed on the European Spine Phantom. Their relative errors and relative standard deviations were compared. A retrospective analysis was performed on patients who underwent chest plain DECT and abdominal monoenergetic plain CT at the same time. The relationship between hydroxyapatite-water and hydroxyapatite-fat measured using DECT and BMD measured using QCT was analyzed by multivariate regression analysis.

Results

The relative errors of the new fast kV-switching DECT with low tube speeds (0.8 and 1.0 s/r) were all less than 6% and were less than those of QCT, except for those at 515 mA. The relative standard deviation values with high tube rotation speeds (0.5 and 0.6 s/r) were higher than those with low tube speeds (0.8 and 1.0 s/r) under most tube current conditions. The new fast kV-switching DECT-derived BMD values corrected by multiple linear regression (predicted hydroxyapatite) were significantly positively correlated with the QCT-based BMD values (R²=0.912; P<0.001). The results of the Bland-Altman analysis demonstrated high consistency between the 2 measurement methods.

Conclusions

Results of the phantom measurements indicated that the new fast kV-switching DECT could measure BMD with relatively high accuracy and precision. The results of a subsequent clinical in vivo experiment demonstrated that vertebral BMD measurements derived from DECT and QCT were mostly consistent and highly accurate. Therefore, patients who undergo DECT for other clinical indications can simultaneously have their BMD determined.

Diagnostic power of vertebral hydroxyapatite concentration measurements in spectral CT for osteoporosis-associated fractures and impact of intravenous contrast administration

OBJECTIVES

To evaluate the diagnostic power of using vertebral hydroxyapatite concentration measurements in unenhanced and contrast-enhanced spectral CT for detecting and predicting the risk of osteoporosis-associated fractures.

METHODS

L1 of 210 patients (105 men, 105 women; mean age, 64 years, range, 19-103 years) who had undergone spectral CT examinations from January 1, 2018, to March 1, 2019, were retrospectively analyzed. Patient data for 3 years after spectral CT were retrieved from electronic medical record information systems to obtain the incidence of osteoporotic fractures. Baseline vertebral cancellous hydroxyapatite concentration from unenhanced and contrast-enhanced late-arterial-phase images was measured. The receiver operating characteristic curves were used to evaluate the diagnostic power for detecting and predicting the 3-year risk of osteoporosis-associated fractures using hydroxyapatite concentrations in both phases.

RESULTS

The hydroxyapatite concentrations in both phases had good diagnostic power to detect fractures at baseline. The sensitivity and specificity for predicting one or more osteoporosis-associated fractures within 3 years after spectral CT were 76.80% and 93.10%, respectively, using the cutoff of 74.79 mg/cm³ in vertebral hydroxyapatite concentration in the unenhanced CT phase, and 82.87% and 82.76%, respectively, using the cutoff of 84.65 mg/cm³ in the late-arterial phase. Furthermore, there was no significant difference in the diagnosis between unenhanced and enhanced CT-derived hydroxyapatite concentrations (p = 0.360).

CONCLUSIONS

Both unenhanced and enhanced spectral CT-derived hydroxyapatite concentrations can accurately detect and predict future risk of osteoporosis-associated fractures. The hydroxyapatite concentration assessed in the late-arterial phase may have a similar diagnostic efficacy to that in the unenhanced phase.

KEY POINTS

• A cutoff of 74.79 mg/cm³ of vertebral hydroxyapatite concentration in the unenhanced CT scans had 76.80% sensitivity and 93.10% specificity to predict one or more osteoporosis-associated fractures within 3 years after spectral CT examinations. • A cutoff of 84.65 mg/cm³ of vertebral hydroxyapatite concentration in the late-arterial-enhanced CT scans had 82.87% sensitivity and 82.76% specificity to predict one or more osteoporosis-associated fractures within 3 years after spectral CT examinations. • The hydroxyapatite concentration assessed in the late-arterial phase may have a similar diagnostic efficacy to that in the unenhanced phase.

Study on the scanning protocols for measuring bone mineral density by gemstone CT spectral imaging based on European spine phantom

BACKGROUND

Gemstone spectral computed tomography (GSCT) has been used to measure bone mineral density (BMD) in human vertebrae and animal models gradually.

PURPOSE

To investigate the effect of scanning protocols for BMD measurements by GSCT using the European spine phantom (ESP) and its accuracy and precision.

MATERIAL AND METHODS

The ESP number 145 containing three hydroxyapatite (HAP) inserts with densities of 50, 100, and 200 mg/cm³ were labeled as L₁, L₂, and L₃, respectively. Quantitative CT (QCT) protocol and 14 groups of scanning protocols configured by GSCT were used to repeatedly scan the ESP 10 times. Their measurements were compared with the true values of ESP and their relative standard deviation and relative error were calculated.

RESULTS

The measured values of the three inserts at different exposure levels were statistically significant (P < 0.05). The measured values in the 0.8 s/r 260 mA group, 0.5 s/r 630 mA group, and 0.6 s/r 640 mA group were not significantly different from the actual ESP values for L₁ and L₂. However, the measured values at all the parameters were significantly different from the actual values for the L₃.

CONCLUSION

CT gemstone spectral imaging can accurately and quantitatively measure the HAP value of ESP, but the results of BMD will be affected by the scanning protocols. The best scanning parameter of ESP measured by GSCT was 0.8 s/r 260 mA, taking dose into consideration, and the measurement accuracy of vertebrae with low BMD was higher than that of QCT under this parameter.

Associations between Bone Mineral Density and Longitudinal Changes of Vertebral Bone Marrow and Paraspinal Muscle Composition Assessed Using MR-Based Proton Density Fat Fraction and T2* Maps in Patients with and without Osteoporosis

Background: Proton-density fat fraction (PDFF) and T2* of the vertebrae, as well as the cross-sectional area (CSA) of the paraspinal musculature (PSM), have been suggested as biomarkers for bone fragility. The aim of this study was to longitudinally assess changes in PDFF, T2* and CSA of the PSM over 6 months in patients with and without osteoporosis. Methods: Opportunistic bone mineral density (BMD) measurements (BMD < 120 mg/cm3) were obtained from a CT acquired during the clinical routine work up in osteoporotic/osteopenic patients (n = 29, mean age 72.37 ± 10.12 years, 16 women). These patients were frequency-matched for age and sex to subjects with normal BMD values (n = 29). All study patients underwent 3T MR imaging at baseline and 6-month follow up, including spoiled gradient echo sequences for chemical shift encoding-based water-fat separation, from which T2* and PDFF values of the lumbar spine and the PSM were obtained. Moreover, the CSA of the PSM was assessed longitudinally. Changes in T2*, PDFF and CSA over 6 months were calculated for the vertebrae and PSM and associations with baseline BMD values were assessed. Results: The change in CSA of the PSM over 6 months was significantly lower in the osteoporotic/osteopenic group (−91.5 ± 311.7 mm2), compared to the non-osteoporotic group, in which the CSA increased (29.9 ± 164.0 mm2, p = 0.03). In a further analysis, patients with higher vertebral PDFF at baseline showed a significantly stronger increase in vertebral T2*, compared to those patients with lower vertebral PDFF at baseline (0.9 ± 1.6 ms vs. 0.0 ± 1.8 ms, p = 0.04). Moreover, patients with higher PSM PDFF at baseline showed a significantly stronger increase in vertebral T2*, compared to those patients with lower PSM PDFF at baseline (0.9 ± 2.0 ms vs. 0.0 ± 1.3 ms, p = 0.03). Conclusion: The PSM CSA decreased significantly longitudinally in patients with osteoporosis/osteopenia, compared to those without. Additionally, higher vertebral and PSM PDFF at baseline were associated with stronger changes in vertebral bone marrow T2*. Therefore, longitudinal PDFF and T2* mapping may be useful quantitative radiation-free tools for the assessment and prediction of muscle and bone health in patients with suspected osteoporosis/osteopenia.

Effect of intravenous iodinated contrast administration on diagnostic ability for osteoporosis using CT attenuation measurement in patients with liver cirrhosis

OBJECTIVES

To evaluate the influence of intravenous contrast agent on the diagnostic ability for osteoporosis using CT attenuation measurement in patients with liver cirrhosis.

METHODS

This retrospective study was approved by our institutional review board and informed consent was waived. 208 patients with liver cirrhosis (mean age, 61.25 years ± 9.43 [standard deviation]; range, 30-82 years) who underwent both unenhanced and two contrast-enhanced (arterial and venous phase) abdominal dual-energy CT examinations from January 1 to September 1, 2020, were recruited. CT attenuation values were measured in the medullary compartment of vertebral body (L1-L3) and bone mass was determined by the hydroxyapatite concentration obtained in dual-energy spectral CT and used as the reference standard. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic ability of using CT attenuation number in unenhanced, arterial, and venous phases.

RESULTS

Area under ROC curve using unenhanced CT attenuation was different from using arterial CT attenuation (p= 0.038) and venous CT attenuation (p = 0.048) to diagnosing osteoporosis. However, there was no significant difference between unenhanced CT attenuation and arterial CT attenuation (p = 0.773) and between unenhanced CT attenuation and venous CT attenuation (p = 0.746) to distinguish low bone mass (osteoporosis or osteopenia).

CONCLUSIONS

The diagnostic ability for osteoporosis using CT attenuation measurement in contrast-enhanced scans is decreased due to intravenous contrast contamination, however, which had no influence on the diagnostic ability of CT attenuation for low bone mass (osteoporosis or osteopenia).

ADVANCES IN KNOWLEDGE

The diagnostic ability of using enhanced CT attenuation values for osteoporosis decreased compared to unenhanced CT attenuation values.

Patient-Specific Finite Element Modeling of the Whole Lumbar Spine Using Clinical Routine Multi-Detector Computed Tomography (MDCT) Data-A Pilot Study

(1) Background: To study the feasibility of developing finite element (FE) models of the whole lumbar spine using clinical routine multi-detector computed tomography (MDCT) scans to predict failure load (FL) and range of motion (ROM) parameters. (2) Methods: MDCT scans of 12 subjects (6 healthy controls (HC), mean age ± standard deviation (SD): 62.16 ± 10.24 years, and 6 osteoporotic patients (OP), mean age ± SD: 65.83 ± 11.19 years) were included in the current study. Comprehensive FE models of the lumbar spine (5 vertebrae + 4 intervertebral discs (IVDs) + ligaments) were generated (L1−L5) and simulated. The coefficients of correlation (ρ) were calculated to investigate the relationship between FE-based FL and ROM parameters and bone mineral density (BMD) values of L1−L3 derived from MDCT (BMDQCT-L1-3). Finally, Mann−Whitney U tests were performed to analyze differences in FL and ROM parameters between HC and OP cohorts. (3) Results: Mean FE-based FL value of the HC cohort was significantly higher than that of the OP cohort (1471.50 ± 275.69 N (HC) vs. 763.33 ± 166.70 N (OP), p < 0.01). A strong correlation of 0.8 (p < 0.01) was observed between FE-based FL and BMDQCT-L1-L3 values. However, no significant differences were observed between ROM parameters of HC and OP cohorts (p = 0.69 for flexion; p = 0.69 for extension; p = 0.47 for lateral bending; p = 0.13 for twisting). In addition, no statistically significant correlations were observed between ROM parameters and BMDQCT- L1-3. (4) Conclusions: Clinical routine MDCT data can be used for patient-specific FE modeling of the whole lumbar spine. ROM parameters do not seem to be significantly altered between HC and OP. In contrast, FE-derived FL may help identify patients with increased osteoporotic fracture risk in the future.

Imaging of the Osteoporotic Spine - Quantitative Approaches in Diagnostics and for the Prediction of the Individual Fracture Risk

Osteoporosis is a highly prevalent systemic skeletal disease that is characterized by low bone mass and microarchitectural bone deterioration. It predisposes to fragility fractures that can occur at various sites of the skeleton, but vertebral fractures (VFs) have been shown to be particularly common. Prevention strategies and timely intervention depend on reliable diagnosis and prediction of the individual fracture risk, and dual-energy X-ray absorptiometry (DXA) has been the reference standard for decades. Yet, DXA has its inherent limitations, and other techniques have shown potential as viable add-on or even stand-alone options. Specifically, three-dimensional (3 D) imaging modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI), are playing an increasing role. For CT, recent advances in medical image analysis now allow automatic vertebral segmentation and value extraction from single vertebral bodies using a deep-learning-based architecture that can be implemented in clinical practice. Regarding MRI, a variety of methods have been developed over recent years, including magnetic resonance spectroscopy (MRS) and chemical shift encoding-based water-fat MRI (CSE-MRI) that enable the extraction of a vertebral body's proton density fat fraction (PDFF) as a promising surrogate biomarker of bone health. Yet, imaging data from CT or MRI may be more efficiently used when combined with advanced analysis techniques such as texture analysis (TA; to provide spatially resolved assessments of vertebral body composition) or finite element analysis (FEA; to provide estimates of bone strength) to further improve fracture prediction. However, distinct and experimentally validated diagnostic criteria for osteoporosis based on CT- and MRI-derived measures have not yet been achieved, limiting broad transfer to clinical practice for these novel approaches. KEY POINTS::   · DXA is the reference standard for diagnosis and fracture prediction in osteoporosis, but it has important limitations.. · CT- and MRI-based methods are increasingly used as (opportunistic) approaches.. · For CT, particularly deep-learning-based automatic vertebral segmentation and value extraction seem promising.. · For MRI, multiple techniques including spectroscopy and chemical shift imaging are available to extract fat fractions.. · Texture and finite element analyses can provide additional measures for vertebral body composition and bone strength.. CITATION FORMAT: · Sollmann N, Kirschke JS, Kronthaler S et al. Imaging of the Osteoporotic Spine - Quantitative Approaches in Diagnostics and for the Prediction of the Individual Fracture Risk. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1770-4626.

Diagnostic accuracy of quantitative dual-energy CT-based volumetric bone mineral density assessment for the prediction of osteoporosis-associated fractures

OBJECTIVES

To evaluate the predictive value of volumetric bone mineral density (BMD) assessment of the lumbar spine derived from phantomless dual-energy CT (DECT)-based volumetric material decomposition as an indicator for the 2-year occurrence risk of osteoporosis-associated fractures.

METHODS

L1 of 92 patients (46 men, 46 women; mean age, 64 years, range, 19-103 years) who had undergone third-generation dual-source DECT between 01/2016 and 12/2018 was retrospectively analyzed. For phantomless BMD assessment, dedicated DECT postprocessing software using material decomposition was applied. Digital files of all patients were sighted for 2 years following DECT to obtain the incidence of osteoporotic fractures. Receiver operating characteristic (ROC) analysis was used to calculate cut-off values and logistic regression models were used to determine associations of BMD, sex, and age with the occurrence of osteoporotic fractures.

RESULTS

A DECT-derived BMD cut-off of 93.70 mg/cm3 yielded 85.45% sensitivity and 89.19% specificity for the prediction to sustain one or more osteoporosis-associated fractures within 2 years after BMD measurement. DECT-derived BMD was significantly associated with the occurrence of new fractures (odds ratio of 0.8710, 95% CI, 0.091-0.9375, p < .001), indicating a protective effect of increased DECT-derived BMD values. Overall AUC was 0.9373 (CI, 0.867-0.977, p < .001) for the differentiation of patients who sustained osteoporosis-associated fractures within 2 years of BMD assessment.

CONCLUSIONS

Retrospective DECT-based volumetric BMD assessment can accurately predict the 2-year risk to sustain an osteoporosis-associated fracture in at-risk patients without requiring a calibration phantom. Lower DECT-based BMD values are strongly associated with an increased risk to sustain fragility fractures.

KEY POINTS

•Dual-energy CT-derived assessment of bone mineral density can identify patients at risk to sustain osteoporosis-associated fractures with a sensitivity of 85.45% and a specificity of 89.19%. •The DECT-derived BMD threshold for identification of at-risk patients lies above the American College of Radiology (ACR) QCT guidelines for the identification of osteoporosis (93.70 mg/cm3 vs 80 mg/cm3).

BMD accuracy errors specific to phantomless calibration of CT scans of the lumbar spine

Opportunistic screening using existing CT images may be a new strategy to identify subjects at increased risk for osteoporotic fracture. Low bone mineral density (BMD) is a key parameter but routine clinical CT scans do not include a calibration phantom to calculate BMD from the measured CT values. An alternative is internal or phantomless calibration, which is based on the CT values of air and of internal tissues of the subject such as blood, muscle or adipose tissue. However, the composition and as a consequence the CT values of these so-called internal calibration materials vary among subjects, which introduces additional BMD accuracy errors compared to phantom based calibration. The objective of this study was to quantify these accuracy errors and to identify optimum combinations of internal calibration materials (IM) for BMD assessments in opportunistic screening. Based on the base material decomposition theory we demonstrate how BMD can be derived from the CT values of the internal calibration materials. 121 CT datasets of the lumbar spine form postmenopausal women were used to determine the population variance of blood assessed in the aorta or the inferior vena cava, skeletal muscle of the erector spinae or psoas, subcutaneous adipose tissue (SAT) and air. The corresponding standard deviations were used for error propagation to determine phantomless calibration related BMD accuracy errors. Using a CT value of 150 HU, a typical value of trabecular bone, simulated BMD accuracy errors for most IM combinations containing air as one of the two base materials were below 5% or 6 mg/cm³. The lowest errors were determined for the combination of blood and air (<2 mg/cm³). The combination of blood and skeletal muscle resulted in higher errors (>10.5% or >12 mg/cm³) and is not recommended. Due to possible age-related differences in tissue composition, the selection of IMs is suggested to be adapted according to the measured subject. In younger subjects without significant aortic calcifications, air and blood of the aorta may be the best combination whereas in elderly subjects, air and SAT (error of 4%) may be preferable. The use of skeletal muscle as one of the two IMs is discouraged, in particular in elderly subjects because of varying fatty infiltration. A practical implementation of the internal calibration with different IM pairs confirmed the theoretical results. In summary, compared to a phantom based calibration the phantomless approach used for opportunistic screening creates additional BMD accuracy errors of 2% or more, dependent on the used internal reference tissues. The impact on fracture prediction still must be evaluated.

MR-based proton density fat fraction (PDFF) of the vertebral bone marrow differentiates between patients with and without osteoporotic vertebral fractures

The bone marrow proton density fat fraction (PDFF) assessed with MRI enables the differentiation between osteoporotic/osteopenic patients with and without vertebral fractures. Therefore, PDFF may be a potentially useful biomarker for bone fragility assessment.

INTRODUCTION

To evaluate whether magnetic resonance imaging (MRI)-based proton density fat fraction (PDFF) of vertebral bone marrow can differentiate between osteoporotic/osteopenic patients with and without vertebral fractures.

METHODS

Of the 52 study patients, 32 presented with vertebral fractures of the lumbar spine (66.4 ± 14.4 years, 62.5% women; acute low-energy osteoporotic/osteopenic vertebral fractures, N = 25; acute high-energy traumatic vertebral fractures, N = 7). These patients were frequency matched for age and sex to patients without vertebral fractures (N = 20, 69.3 ± 10.1 years, 70.0% women). Trabecular bone mineral density (BMD) values were derived from quantitative computed tomography. Chemical shift encoding-based water-fat MRI of the lumbar spine was performed, and PDFF maps were calculated. Associations between fracture status and PDFF were assessed using multivariable linear regression models.

RESULTS

Over all patients, mean PDFF and trabecular BMD correlated significantly (r =  - 0.51, P < 0.001). In the osteoporotic/osteopenic group, those patients with osteoporotic/osteopenic fractures had a significantly higher PDFF than those without osteoporotic fractures after adjusting for age, sex, weight, height, and trabecular BMD (adjusted mean difference [95% confidence interval], 20.8% [10.4%, 30.7%]; P < 0.001), although trabecular BMD values showed no significant difference between the subgroups (P = 0.63). For the differentiation of patients with and without vertebral fractures in the osteoporotic/osteopenic subgroup using mean PDFF, an area under the receiver operating characteristic (ROC) curve (AUC) of 0.88 (P = 0.006) was assessed. When evaluating all patients with vertebral fractures, those with high-energy traumatic fractures had a significantly lower PDFF than those with low-energy osteoporotic/osteopenic vertebral fractures (P < 0.001).

CONCLUSION

MR-based PDFF enables the differentiation between osteoporotic/osteopenic patients with and without vertebral fractures, suggesting the use of PDFF as a potential biomarker for bone fragility.

Associations of incidental vertebral fractures and longitudinal changes of MR-based proton density fat fraction and T2* measurements of vertebral bone marrow

BACKGROUND

Quantitative magnetic resonance imaging (MRI) techniques such as chemical shift encoding-based water-fat separation techniques (CSE-MRI) are increasingly applied as noninvasive biomarkers to assess the biochemical composition of vertebrae. This study aims to investigate the longitudinal change of proton density fat fraction (PDFF) and T2* derived from CSE-MRI of the thoracolumbar vertebral bone marrow in patients that develop incidental vertebral compression fractures (VCFs), and whether PDFF and T2* enable the prediction of an incidental VCF.

METHODS

In this study we included 48 patients with CT-derived bone mineral density (BMD) measurements at baseline. Patients that presented an incidental VCF at follow up (N=12, mean age 70.5 ± 7.4 years, 5 female) were compared to controls without incidental VCF at follow up (N=36, mean age 71.1 ± 8.6 years, 15 females). All patients underwent 3T MRI, containing a significant part of the thoracolumbar spine (Th11-L4), at baseline, 6-month and 12 month follow up, including a gradient echo sequence for chemical shift encoding-based water-fat separation, from which PDFF and T2* maps were obtained. Associations between changes in PDFF, T2* and BMD measurements over 12 months and the group (incidental VCF vs. no VCF) were assessed using multivariable regression models. Mixed-effect regression models were used to test if there is a difference in the rate of change in PDFF, T2* and BMD between patients with and without incidental VCF.

RESULTS

Prior to the occurrence of an incidental VCF, PDFF in vertebrae increased in the VCF group (Δ_PDFF=6.3 ± 3.1%) and was significantly higher than the change of PDFF in the group without VCF (Δ_PDFF=2.1 ± 2.5%, P=0.03). There was no significant change in T2* (Δ_T2*=1.7 ± 1.1ms vs. Δ_T2*=1.1 ± 1.3ms, P=0.31) and BMD (Δ_BMD=-1.2 ± 11.3mg/cm³ vs. Δ_BMD=-11.4 ± 24.1mg/cm³, P= 0.37) between the two groups over 12 months. At baseline, no significant differences were detected in the average PDFF, T2* and BMD of all measured vertebrae (Th11-L4) between the VCF group and the group without VCF (P=0.66, P=0.35 and P= 0.21, respectively). When assessing the differences in rates of change, there was a significant change in slope for PDFF (2.32 per 6 months, 95% confidence interval (CI) 0.31-4.32; P=0.03) but not for T2* (0.02 per 6 months, CI -0.98-0.95; P=0.90) or BMD (-4.84 per 6 months, CI -23.4-13.7; P=0.60).

CONCLUSIONS

In our study population, the average change of PDFF over 12 months is significantly higher in patients that develop incidental fractures at 12-month follow up compared to patients without incidental VCF, while T2* and BMD show no significant changes prior to the occurrence of the incidental vertebral fractures. Therefore, a longitudinal increase in bone marrow PDFF may be predictive for vertebral compression fractures.

Accuracy and precision of volumetric bone mineral density assessment using dual-source dual-energy versus quantitative CT: a phantom study

BACKGROUND

Dual-source dual-energy computed tomography (DECT) offers the potential for opportunistic osteoporosis screening by enabling phantomless bone mineral density (BMD) quantification. This study sought to assess the accuracy and precision of volumetric BMD measurement using dual-source DECT in comparison to quantitative CT (QCT).

METHODS

A validated spine phantom consisting of three lumbar vertebra equivalents with 50 (L1), 100 (L2), and 200 mg/cm3 (L3) calcium hydroxyapatite (HA) concentrations was scanned employing third-generation dual-source DECT and QCT. While BMD assessment based on QCT required an additional standardised bone density calibration phantom, the DECT technique operated by using a dedicated postprocessing software based on material decomposition without requiring calibration phantoms. Accuracy and precision of both modalities were compared by calculating measurement errors. In addition, correlation and agreement analyses were performed using Pearson correlation, linear regression, and Bland-Altman plots.

RESULTS

DECT-derived BMD values differed significantly from those obtained by QCT (p < 0.001) and were found to be closer to true HA concentrations. Relative measurement errors were significantly smaller for DECT in comparison to QCT (L1, 0.94% versus 9.68%; L2, 0.28% versus 5.74%; L3, 0.24% versus 3.67%, respectively). DECT demonstrated better BMD measurement repeatability compared to QCT (coefficient of variance < 4.29% for DECT, < 6.74% for QCT). Both methods correlated well to each other (r = 0.9993; 95% confidence interval 0.9984-0.9997; p < 0.001) and revealed substantial agreement in Bland-Altman plots.

CONCLUSIONS

Phantomless dual-source DECT-based BMD assessment of lumbar vertebra equivalents using material decomposition showed higher diagnostic accuracy compared to QCT.

Assessment of Bone Mineral Density From a Computed Tomography Topogram of Photon-Counting Detector Computed Tomography-Effect of Phantom Size and Tube Voltage

PURPOSE

The aim of this study was to assess the accuracy and impact of different sizes and tube voltages on bone mineral density (BMD) assessment using a computed tomography (CT) topogram acquired with photon-counting detector CT in an osteopenic ex vivo animal spine.

MATERIALS AND METHODS

The lumbar back of a piglet was used to simulate osteopenia of the lumbar spine. Five fat layers (each with a thickness of 3 cm) were consecutively placed on top of the excised spine to emulate a total of 5 different sizes. Each size was repeatedly imaged on (A) a conventional dual-energy x-ray absorptiometry scanner as the reference standard, (B) a prototype photon-counting detector CT system at 120 kVp with energy thresholds at 20 and 70 keV, and (C) the same prototype system at 140 kVp with thresholds at 20 and 75 keV. Material-specific data were reconstructed from spectral topograms for B and C. Bone mineral density was measured for 3 lumbar vertebrae (L2-L4). A linear mixed-effects model was used to estimate the impact of vertebra, imaging setup, size, and their interaction term on BMD.

RESULTS

The BMD of the lumbar spine corresponded to a T score in humans between -4.2 and -4.8, which is seen in osteoporosis. Averaged across the 3 vertebrae and 5 sizes, mean BMD was 0.56 ± 0.03, 0.55 ± 0.02, and 0.55 ± 0.02 g/cm2 for setup A, B, and C, respectively. There was no significant influence of imaging setup (P = 0.7), simulated size (P = 0.67), and their interaction term (both P > 0.2) on BMD. Bone mineral density decreased significantly from L2 to L4 for all 3 setups (all P < 0.0001). Bone mineral density was 0.59 ± 0.01, 0.57 ± 0.01, and 0.52 ± 0.02 g/cm2 for L2, L3, and L4, respectively, for setup A; 0.57 ± 0.02, 0.55 ± 0.01, and 0.53 ± 0.01 g/cm2 for setup B; and 0.57 ± 0.01, 0.55 ± 0.01, and 0.53 ± 0.01 g/cm2 for setup C.

CONCLUSION

A single CT topogram acquired on photon-counting detector CT with 2 energy thresholds enabled BMD quantification with similar accuracy compared with dual-energy x-ray absorptiometry over a range of simulated sizes and tube voltages in an osteopenic ex vivo animal spine.

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.

Vertebral bone marrow T2* mapping using chemical shift encoding-based water-fat separation in the quantitative analysis of lumbar osteoporosis and osteoporotic fractures

BACKGROUND

Chemical shift encoding-based water-fat separation techniques have been used for fat quantification [proton density fat fraction (PDFF)], but they also enable the assessment of bone marrow T2*, which has previously been reported to be a potential biomarker for osteoporosis and may give insight into the cause of vertebral fractures (i.e., osteoporotic vs. traumatic) and the microstructure of the bone when applied to vertebral bone marrow.

METHODS

The 32 patients (78.1% with low-energy osteopenic/osteoporotic fractures, mean age 72.3±9.8 years, 76% women; 21.9% with high-energy traumatic fractures, 47.3±12.8 years, no women) were frequency-matched for age and sex to subjects without vertebral fractures (n=20). All study patients underwent 3T-MRI of the lumbar spine including sagittally acquired spoiled gradient echo sequences for chemical shift encoding-based water-fat separation, from which T2* values were obtained. Volumetric trabecular bone mineral density (BMD) and trabecular bone parameters describing the three-dimensional structural integrity of trabecular bone were derived from quantitative CT. Associations between T2* measurements, fracture status and trabecular bone parameters were assessed using multivariable linear regression models.

RESULTS

Mean T2* values of non fractured vertebrae in all patients showed a significant correlation with BMD (r=-0.65, P<0.001), trabecular number (TbN) (r=-0.56, P<0.001) and trabecular spacing (TbSp) (r=0.61, P<0.001); patients with low-energy osteoporotic vertebral fractures showed significantly higher mean T2* values than those with traumatic fractures (13.6±4.3 vs. 8.4±2.2 ms, P=0.01) as well as a significantly lower TbN (0.69±0.08 vs. 0.93±0.03 mm-1, P<0.01) and a significantly larger trabecular spacing (1.06±0.16 vs. 0.56±0.08 mm, P<0.01). Mean T2* values of osteoporotic patients with and without vertebral fracture showed no significant difference (13.5±3.4 vs. 15.6±3.5 ms, P=0.40). When comparing the mean T2* of the fractured vertebrae, no significant difference could be detected between low-energy osteoporotic fractures and high-energy traumatic fractures (12.6±5.4 vs. 8.1±2.4 ms, P=0.10).

CONCLUSIONS

T2* mapping of vertebral bone marrow using using chemical shift encoding-based water-fat separation allows for assessing osteoporosis as well as the trabecular microstructure and enables a radiation-free differentiation between patients with low-energy osteoporotic and high-energy traumatic vertebral fractures, suggesting its potential as a biomarker for bone fragility.

Dual-Energy Computed Tomography Virtual Noncalcium Technique in Diagnosing Osteoporosis: Correlation With Quantitative Computed Tomography

OBJECTIVE

The aim of this study was to evaluate dual-energy computed tomography (CT) virtual noncalcium (VNCa) technique as a means of quantifying osteoporosis.

METHODS

Dual-energy CT scans were obtained prospectively, targeting lumbar regions of 55 patients with chronic low back pain. A standard quantitative CT (QCT) phantom was positioned at the waist during each procedure, using proprietary software (QCT Pro; Mindways, Tex) to measure bone mineral density (BMD) in each vertebral body. Vendor dual-energy analytic software was altered with a specially modified configuration file to produce a "Virtual Non Calcium" or "VNCa" output, as such output variables were remapped to produce the following calcium values rather than iodine, yielding the following QCT parameters: CT value of calcium (originally "contrast media" [CM]), CT value of mixed energy imaging (regular CT value [rCT]), calcium density (originally "contrast agent density" [CaD]), and fat fraction (FF). Pearson test served to assess correlations between BMD and these parameters. Multiple linear regression analysis was applied to construct an equation for generating regressive BMD (rBMD) values. In gauging diagnostic accuracies, the criterion-standard BMD cutoff point (<80 mg/cm3) was adopted for QCT, whereas the rBMD threshold was defined by receiver operating characteristic curve.

RESULTS

Contrast media, rCT, CaD, and FF values (reflecting CT value of calcium, regular CT value, calcium density, and fat fraction, respectively) significantly correlated with BMD (r values: 0.885, 0.947, 0.877, and 0.492, respectively; all P < 0.01). Contrast media, CaD, and FF showed independent associations with BMD; the regressive equation was formulated as follows: rBMD = 54.82 - 0.19 × CM + 20.03 × CaD - 1.24 × FF. The area under the curve of rBMD in diagnosing osteoporosis was 0.966 ± 0.009 (P < 0.01). At an rBMD threshold of less than 81.94 mg/cm3, sensitivity and specificity were 90.0% and 92.0%, respectively.

CONCLUSIONS

Dual-energy CT VNCa technique may constitute a valid alternative method for quantifying the mineral content and marrow fat composition of bone in diagnostic assessments of osteoporosis.

Risk of vertebral fractures: evaluation on vertebral trabecular attenuation value and hydroxyapatite concentration in patients by chest spectral CT

OBJECTIVES

To analyze vertebral fractures risk in patients with chest scans by evaluating vertebral hydroxyapatite concentration measured on spectral CT compared to trabecular attenuation value measured on conventional CT.

METHODS

Our retrospective study reviewed CT of 216 patients. Analysis of vertebral (T11 - L1) hydroxyapatite concentration by spectral imaging and trabecular attenuation value by conventional CT imaging were performed in patients with chest CT examinations. Specificity, sensitivity, negative predictive value (NPV), and positive predictive value (PPV) were performed by using receiver operating characteristic (ROC) curves in patients with and without vertebral fractures.

RESULTS

In male patients, vertebral hydroxyapatite concentration had high area under the ROC curve (0.916), by using the optimal threshold of 72.27 mg/cm³, specificity, sensitivity, NPV, and PPV were 91.7, 80.2, 36.7, and 98.7%, respectively. In female patients, vertebral hydroxyapatite concentration also had high area under the ROC curve (0.870), by using the optimal threshold of 74.79 mg/cm³, specificity, sensitivity, NPV, and PPV were 100.0, 77.8, 47.4, and 100.0%, respectively. Area under the ROC curve was significantly different between spectral CT-measured bone hydroxyapatite concentration and conventional CT-measured attenuation value in distinguishing vertebral fractures (p = 0.007 for males; p = 0.005 for females).

CONCLUSIONS

Quantitative assessment with spectral CT may appear as higher accuracy than that of conventional CT imaging to analyze risk of vertebral fractures. Hydroxyapatite concentration measured with chest spectral CT may be used to evaluate risk of bone fractures.

ADVANCES IN KNOWLEDGE

Hydroxyapatite concentration measured with chest spectral CT may be used to evaluate risk of bone fractures.

Dual-Layer Detector CT With Virtual Noncalcium Imaging: Diagnostic Performance in Patients With Suspected Wrist Fractures

OBJECTIVE. The purpose of this study was to evaluate the diagnostic utility of dual-layer CT (DLCT) for evaluating wrist injuries and to compare it with MRI. MATERIALS AND METHODS. The cases of 62 patients with suspected wrist fractures who underwent imaging with both DLCT and MRI from January 2018 through February 2019 were retrospectively reviewed. By means of a calcium suppression algorithm, virtual noncalcium (VNCa) image reconstruction was performed, and the images were reviewed by two readers to identify fractures, bone contusions, and nontraumatic lesions in the radius, ulna, and carpal bones. Sensitivity, specificity, PPV, and NPV were calculated and compared between standard CT and VNCa images with a combination of standard CT and MRI as the reference standard. RESULTS. Use of DLCT with VNCa reconstruction increased the sensitivity of diagnosis of fractures in the radius and carpal bones over that of standard CT alone; occult fractures were detected that were not seen with standard CT. The sensitivity and specificity for detecting radius fracture were 98.1% and 93.8% for DLCT and 96.3% and 93.8% for standard CT. For detecting carpal bone fracture, sensitivity and specificity were 100% and 98.9% for DLCT and 93.8% and 100% for standard CT. VNCa reconstruction also had good diagnostic accuracy with regard to diagnosing nonfracture bone contusions in carpal bones. The accuracy was comparable to that of MRI with sensitivity of 92.9% and specificity of 94.5%. Interreader agreement in interpreting VNCa images was generally good to excellent. CONCLUSION. DLCT with VNCa reconstruction is a promising tool for identifying occult wrist fractures and nonfracture contusion injuries in patients with wrist trauma.

In vivo quantification of bone mineral density of lumbar vertebrae using fast kVp switching dual-energy CT: correlation with quantitative computed tomography

Background

Osteoporosis is a common, progressive disease related to low bone mineral density (BMD). If it can be diagnosed at an early stage, osteoporosis is treatable. Quantitative computed tomography (QCT) is one of the current reference standards of BMD measurement, but dual-energy computed tomography (DECT) is considered to be a potential alternative. This study aimed to evaluate the feasibility and accuracy of phantomless in vivo DECT-based BMD quantification in comparison with QCT.

Methods

A total of 128 consecutive participants who underwent DECT lumbar examinations between July 2018 and February 2019 were retrospectively analyzed. The density of calcium (water), hydroxyapatite (water), calcium (fat), and hydroxyapatite (fat) [D_Ca(Wa), D_HAP(Wa), D_Ca(Fat) and D_HAP(Fat), respectively] were measured along with BMD in the trabecular bone of lumbar level 1-2 by DECT and QCT. Linear regression analysis was performed to assess the relationship between DECT- and QCT-derived BMD at both the participant level and the vertebral level. Linear regression models were quantitatively evaluated with adjusted R-square, normalized mean squared error (NMSE) and relative error (RE). Bland-Altman analysis was conducted to assess agreement between measurements. P<0.05 was considered statistically significant.

Results

Strong correlations were observed between DECT- and QCT-derived BMD at both the participant level and the vertebral level (adjusted R² =0.983-0.987; NMSE = 1.6-2.1%; RE_linear =0.6-0.9%). Bland-Altman plots indicated high agreement between both measurements. D_Ca(Fat) and D_HAP(Fat) showed relatively similar and optimal predictive capability for QCT-derived BMD (both: adjusted R² =0.987, NMSE =1.6%, RE_linear =0.6%).

Conclusions

Fast kVp switching DECT enabled accurate phantomless in vivo BMD quantification of the lumbar spine. D_Ca(Fat) and D_HAP(Fat) had relatively similar and optimal predictive capability.

Bone Mineral Density Quantification from Localizer Radiographs: Accuracy and Precision of Energy-integrating Detector CT and Photon-counting Detector CT

Background Bone mineral density (BMD) could be derived from CT localizer radiographs and could potentially enable opportunistic osteoporosis screening. Purpose To assess the accuracy and precision of BMD measurement using two localizer radiographs obtained with energy-integrating detector CT and a single localizer radiograph obtained with photon-counting detector CT. Materials and Methods A calibration phantom and a porcine phantom with lumbar vertebrae were imaged with a dual-energy x-ray absorptiometry (DXA) scanner, a clinical energy-integrating detector CT scanner, and a prototype photon-counting detector CT scanner. Two localizer radiographs at different combinations of tube voltages were obtained with energy-integrating detector CT, and one localizer radiograph was obtained with photon-counting detector CT using different energy thresholds. BMD was calculated for all three approaches and compared with the known specifications in the calibration phantom. In the animal phantom, BMDs from both CT systems were compared with those from the DXA scanner (the reference standard). Accuracy was defined as the measurement error of BMD (ΔBMD), and precision was defined as the coefficient of variation (in percentage). Radiation doses were estimated. Nonparametric tests were applied. Results In the calibration phantom, ΔBMD was smaller with both CT systems compared with the DXA scanner (both P < .05). ΔBMD ranged from -5% to -1.8% for DXA, from -2.3% to -1.7% for energy-integrating detector CT, and from -1.6% to 1.6% for photon-counting detector CT. Precision (range, 0.3%-2.8%) was high for both CT systems. In the animal phantom, ΔBMD ranged from -0.6% to 0.1% for energy-integrating detector CT and from -0.1% to 0.6% for photon-counting detector CT, with no significant differences between CT systems (P = .65). The dose-area product in the animal phantom was 4.6 cGy ∙ cm² for DXA, 3.5-11.5 cGy ∙ cm² for energy-integrating detector CT, and 7.2-11.2 cGy ∙ cm² for photon-counting detector CT, depending on tube voltage and energy threshold combination. Conclusion Experimental evidence suggests that bone mineral density measurements are accurate and precise using two localizer radiographs at different tube voltages from energy-integrating detector CT and a single localizer radiograph with different energy thresholds from photon-counting detector CT. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Pourmorteza in this issue.

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.

Opportunistic osteoporosis screening in multi-detector CT images using deep convolutional neural networks

OBJECTIVE

To explore the application of deep learning in patients with primary osteoporosis, and to develop a fully automatic method based on deep convolutional neural network (DCNN) for vertebral body segmentation and bone mineral density (BMD) calculation in CT images.

MATERIALS AND METHODS

A total of 1449 patients were used for experiments and analysis in this retrospective study, who underwent spinal or abdominal CT scans for other indications between March 2018 and May 2020. All data was gathered from three different CT vendors. Among them, 586 cases were used for training, and other 863 cases were used for testing. A fully convolutional neural network, called U-Net, was employed for automated vertebral body segmentation. The manually sketched region of vertebral body was used as the ground truth for comparison. A convolutional neural network, called DenseNet-121, was applied for BMD calculation. The values post-processed by quantitative computed tomography (QCT) were identified as the standards for analysis.

RESULTS

Based on the diversity of CT vendors, all testing cases were split into three testing cohorts: Test set 1 (n = 463), test set 2 (n = 200), and test set 3 (n = 200). Automated segmentation correlated well with manual segmentation regarding four lumbar vertebral bodies (L1-L4): the minimum average dice coefficients for three testing sets were 0.823, 0.786, and 0.782, respectively. For testing sets from different vendors, the average BMDs calculated by automated regression showed high correlation (r > 0.98) and agreement with those derived from QCT.

CONCLUSIONS

A deep learning-based method could achieve fully automatic identification of osteoporosis, osteopenia, and normal bone mineral density in CT images.

KEY POINTS

• Deep learning can perform accurate fully automated segmentation of lumbar vertebral body in CT images. • The average BMDs obtained by deep learning highly correlates with ones derived from QCT. • The deep learning-based method could be helpful for clinicians in opportunistic osteoporosis screening in spinal or abdominal CT scans.

Advanced Quantitative Spine Imaging

Although advanced quantitative imaging may not be currently used to any degree in the routine reporting of spinal examinations, this situation will change in the not too distant future. Advanced quantitative imaging has already allowed us to understand a great deal more regarding spinal development, marrow physiology, and disease pathogenesis. Radiologists are ideally suited to drive this research forward. To speed up this process and optimize the impact of studies reporting spine quantitative data, we should work toward universal standards on the acquisition of spine data that will allow quantitative studies to be more easily compared, contrasted, and amalgamated.

Accuracy, agreement, and reliability of DECT-derived vBMD measurements: an initial ex vivo study

OBJECTIVES

To assess the agreement and reliability of DECT (dual-energy CT)-derived vBMD (volumetric bone mineral density) measurements from excised human femoral heads and to compare DECT-derived BMD with that measured by DXA (dual-energy X-ray absorptiometry) and QCT (quantitative CT) to determine its accuracy.

METHODS

Twenty patients that underwent total hip arthroplasty were enrolled to this study. Femoral heads were excised to rectangles without cortical bones for scanning. A dual-source DECT scanner generated images under 80/Sn140 kVp and 100/Sn140 kVp scanning conditions. Specimens were subsequently scanned by QCT and DXA to produce QCT-derived vBMD (mg/cm³) and DXA-derived BMM (bone mineral mass, g). DECT images were loaded to a post-processing workstation to calculate DECT-derived vBMD and BMM.

RESULTS

Higher DECT-derived vBMD and BMM were found under 80/Sn140 and 100/Sn140 kVp compared with those for QCT and DXA (p = 0.005). DECT-derived vBMD was highly correlated with QCT-derived vBMD (r = 0.961 ~ 0.993, p < 0.05). Similarly, DECT-derived BMM was strongly correlated with DXA-derived BMM (r = 0.927 ~ 0.943, p < 0.05). Agreement of the inter- and intra-observation of DECT-derived vBMD was excellent. Linear regression was carried out to calibrate DECT-derived vBMD of 80/Sn140 kVp (14 + 0.7 × DECT-derived vBMD) and 100/Sn140 kVp (74 + 0.4 × DECT-derived vBMD) with the reference of QCT-derived vBMD. After calibration, excellent agreement was found for vBMD and BMM within various imaging modalities.

CONCLUSIONS

Our study showed that DECT-derived vBMD exhibited high agreement and reliability features, and after calibration, it also displayed a high degree of accuracy. However, in vivo studies are needed to extend its potential utility in clinical settings.

KEY POINTS

• Measurements of DECT-derived vBMD had high intra- and inter-observer agreement and reliability. • Measurements of DECT-derived vBMD and BMM had a high correlation with those derived from QCT and DXA. • DECT-derived vBMD and BMM were accurate after calibration compared with QCT and DXA.

The accurate relationship between spine bone density and bone marrow in humans

CONTEXT

The accuracy of QCT measurements of lumbar spine trabecular volumetric bone mineral density (vBMD) is decreased due to differences in the amount of bone marrow adipose tissue (BMAT).

OBJECTIVE

To correct vBMD measurements for differences in marrow composition and investigate the true relationship between vBMD and BMAT.

DESIGN

Cross-sectional study.

SETTING

University teaching hospital.

PARTICIPANTS

Healthy Chinese subjects (233 women, 167 men) aged between 21 and 82 years.

MAIN OUTCOME MEASURES

vBMD and BMAT were measured using QCT (120 kV) and chemical shift-encoded MRI of the L2-L4 vertebrae. vBMD measurements were standardized to the European Spine Phantom (ESP) and corrected for differences in BMAT. Linear regression was used to analyze BMAT, ESP adjusted vBMD (vBMD_ESPcorr) and BMAT corrected vBMD (vBMD_BMATcorr) against age and corrected vBMD against BMAT.

RESULTS

BMAT in the L2-L4 vertebral bodies increased with age in both sexes, with a faster rate of change in women compared with men (0.54%/year vs. 0.27%/year, P < 0.0001). After vBMD measurements were corrected for BMAT there were statistically significant changes in the slope of the regression line with age in both sexes (women: -3.00 ± 0.13 vs. -2.57 ± 0.11 mg/cm³/year, P < 0.0001; men: -1.92 ± 0.15 vs. -1.70 ± 0.14 mg/cm³/year, P < 0.0001). When vBMD_BMATcorr was plotted against BMAT, vBMD decreased linearly with increasing BMAT in both sexes (women: -3.30 ± 0.18 mg/cm³/%; men: -2.69 ± 0.25 mg/cm³/%, P = 0.048).

CONCLUSION

Our approach reveals the true relationship between vBMD and BMAT and provides a new tool for studying the interaction between bone and marrow adipose tissue.

Phantomless assessment of volumetric bone mineral density using virtual non-contrast images from spectral detector computed tomography

OBJECTIVE

To evaluate phantomless assessment of volumetric bone mineral density (vBMD) based on virtual non-contrast images of arterial (VNC_a) and venous phase (VNC_v) derived from spectral detector CT in comparison to true non-contrast (TNC) images and adjusted venous phase conventional images (CI_V(adjusted)).

METHODS

104 consecutive patients who underwent triphasic spectral detector CT between January 2018 and April 2019 were retrospectively included. TNC, VNC_a, VNC_v and venous phase images (CI_V) were reconstructed. vBMD was obtained by two radiologists using an FDA/CE-cleared software. Average vBMD of the first three lumbar vertebrae was determined in each reconstruction; vBMD of CI_V was adjusted for contrast enhancement as suggested earlier.

RESULTS

vBMD values obtained from CI_V(adjusted) are comparable to vBMD values derived from TNC images (91.79 ± 36.52 vs 90.16 ± 41.71 mg/cm³, p = 1.00); however, vBMD values derived from VNC_a and VNC_v (42.20 ± 22.50 and 41.98 ± 23.3 mg/cm³ respectively) were significantly lower as compared to vBMD values from TNC and CI_V(adjusted) (all p ≤ 0.01).

CONCLUSION

Spectral detector CT-derived virtual non-contrast images systematically underestimate vBMD and therefore should not be used without appropriate adjustments. Adjusted venous phase images provide reliable results and may be utilized for an opportunistic BMD screening in CT examinations.

ADVANCES IN KNOWLEDGE

Adjustments of venous phase images facilitate opportunistic assessment of vBMD, while spectral detector CT-derived VNC images systematically underestimate vBMD.

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.

Opportunistic QCT Bone Mineral Density Measurements Predicting Osteoporotic Fractures: A Use Case in a Prospective Clinical Cohort

PURPOSE

To assess whether volumetric vertebral bone mineral density (BMD) measured with opportunistic quantitative computed tomography (QCT) (i.e., CT acquired for other reasons) can predict osteoporotic fracture occurrence in a prospective clinical cohort and how this performs in comparison to dual-energy X-ray absorptiometry (DXA) measurements.

METHODS

In the database of our fracture liaison service, 58 patients (73 ± 11 years, 72% women) were identified that had at least one prevalent low-energy fracture and had undergone CT of the spine. BMD was determined by converting HU using scanner-specific conversion equations. Baseline DXA was available for 31 patients. During a 3-year follow-up, new fractures were diagnosed either by (i) recent in-house imaging or (ii) clinical follow-up with validated external reports. Associations were assessed using logistic regression models, and cut-off values were determined with ROC/Youden analyses.

RESULTS

Within 3 years, 20 of 58 patients presented new low-energy fractures (34%). Mean QCT BMD of patients with fractures was significantly lower (56 ± 20 vs. 91 ± 38 mg/cm³; p = 0.003) and age was higher (77 ± 10 vs. 71 ± 11 years; p = 0.037). QCT BMD was significantly associated with the occurrence of new fractures, and the OR for developing a new fracture during follow-up was 1.034 (95% CI, 1.010-1.058, p = 0.005), suggesting 3% higher odds for every unit of BMD decrease (1 mg/cm³). Age and sex showed no association. For the differentiation between patients with and without new fractures, ROC showed an AUC of 0.76 and a Youden's Index of J = 0.48, suggesting an optimal cut-off value of 82 mg/cm³. DXA T-scores showed no significant association with fracture occurrence in analogous regression models.

CONCLUSION

In this use case, opportunistic BMD measurements attained through QCT predicted fractures during a 3-year follow-up. This suggests that opportunistic measurements are useful to reduce the diagnostic gap and evaluate the fracture risk in osteoporotic patients.