Biomarkers of Cartilage Composition.

Magnetic resonance imaging (MRI) has significantly advanced the understanding of osteoarthritis (OA) because it enables visualization of noncalcified tissues. Cartilage is avascular and nurtured by diffusion, so it has a very low turnover and limited capabilities of repair. Consequently, prevention of structural and detection of premorphological damage is key in maintaining cartilage health. The integrity of cartilage composition and ultrastructure determines its mechanical properties but is not accessible to morphological imaging. Therefore, various techniques of compositional MRI with and without use of intravenous contrast medium have been developed. Spin-spin relaxation time (T2) and spin-lattice relaxation time constant in rotating frame (T1rho) mapping, the most studied cartilage biomarkers, were included in the recent standardization effort by the Quantitative Imaging Biomarkers Alliance (QIBA) that aims to make compositional MRI of cartilage clinically feasible and comparable. Additional techniques that are less frequently used include ultrashort echo time with T2*, delayed gadolinium-enhanced MRI of cartilage (dGEMRIC), glycosaminoglycan concentration by chemical exchange-dependent saturation transfer (gagCEST), sodium imaging, and diffusion-weighted MRI.

Effect of weight loss on knee joint synovitis over 48 months and mediation by subcutaneous fat around the knee: data from the Osteoarthritis Initiative.

BACKGROUND: Obesity influences the development of osteoarthritis via low-grade inflammation. Progression of local inflammation (= synovitis) increased with weight gain in overweight and obese women compared to stable weight. Synovitis could be associated with subcutaneous fat (SCF) around the knee. Purpose of the study was to investigate the effect of weight loss on synovitis progression and to assess whether SCF around the knee mediates the relationship between weight loss and synovitis progression. METHODS: We included 234 overweight and obese participants (body mass index [BMI] ≥ 25 kg/m2) from the Osteoarthritis Initiative (OAI) with > 10% weight loss (n = 117) or stable overweight (< ± 3% change, n = 117) over 48 months matched for age and sex. In magnetic resonance imaging (MRI) at baseline and 48 months, effusion-synovitis and Hoffa-synovitis using the MRI Osteoarthritis Knee Score (MOAKS) and average joint-adjacent SCF (ajSCF) were assessed. Odds-ratios (ORs) for synovitis progression over 48 months (≥ 1 score increase) were calculated in logistic regression models adjusting for age, sex, baseline BMI, Physical Activity Scale for the Elderly (PASE), and baseline SCF measurements. Mediation of the effect of weight loss on synovitis progression by local SCF change was assessed. RESULTS: Odds for effusion-synovitis progression decreased with weight loss and ajSCF decrease (odds ratio [OR] = 0.61 and 0.56 per standard deviation [SD] change, 95% confidence interval [CI] 0.44, 0.83 and 0.40, 0.79, p = 0.002 and 0.001, respectively), whereas odds for Hoffa-synovitis progression increased with weight loss and ajSCF decrease (OR = 1.47 and 1.48, CI 1.05, 2.04 and 1.02, 2.13, p = 0.024 and 0.038, respectively). AjSCF decrease mediated 39% of the effect of weight loss on effusion-synovitis progression. CONCLUSIONS: Effusion-synovitis progression was slowed by weight loss and decrease in local subcutaneous fat. Hoffa-synovitis characterized by fluid in the infrapatellar fat pad increased at the same time, suggesting a decreasing fat pad rather than active synovitis. Decrease in local subcutaneous fat partially mediated the systemic effect of weight loss on synovitis.

Association of lumbar vertebral bone marrow and paraspinal muscle fat composition with intervertebral disc degeneration: 3T quantitative MRI findings from the population-based KORA study.

OBJECTIVE: To assess the association of lumbar bone marrow adipose tissue fat fraction (BMAT-FF) and paraspinal muscle proton density fat fraction (PDFF) and their interplay with intervertebral disc degeneration (IVDD). METHODS: In this retrospective cross-sectional study based on a prospective population-based cohort, BMAT-FF and PDFF of asymptomatic individuals were calculated based on 3T-MRI dual-echo and multi-echo Dixon VIBE sequences. IVDD was assessed at motion segments L1 to L5 and dichotomized based on Pfirrmann grade ≥ 4 and/or presence of other severe degenerative changes or spinal abnormalities at least at one segment. Pearson's correlation coefficients were calculated for BMAT-FF and PDFF. Univariable and multivariable logistic regression models for IVDD were calculated. RESULTS: Among 335 participants (mean age: 56.2 ± 9.0 years, 43.3% female), the average BMI was 27.7 ± 4.5 kg/m2 and the prevalence of IVDD was high (69.9%). BMAT-FF and PDFF were significantly correlated (r = 0.31-0.34; p < 0.001). The risk for IVDD increased with higher PDFF (OR = 1.45; CI 1.03, 2.04) and BMAT-FF (OR = 1.56; CI 1.16, 2.11). Pairwise combinations of PDFF and BMAT-FF quartiles revealed a lower risk for IVDD in individuals in the lowest BMAT-FF and PDFF quartile (OR = 0.21; CI 0.1, 0.48). Individuals in the highest BMAT-FF and PDFF quartile showed an increased risk for IVDD (OR = 5.12; CI 1.17, 22.34) CONCLUSION: Lumbar BMAT-FF and paraspinal muscle PDFF are correlated and represent both independent and additive risk factors for IVDD. Quantitative MRI measurements of paraspinal myosteatosis and vertebral bone marrow fatty infiltration may serve as imaging biomarkers to assess the individual risk for IVDD. KEY POINTS: • Fat composition of the lumbar vertebral bone marrow is positively correlated with paraspinal skeletal muscle fat. • Higher fat-fractions of lumbar vertebral bone marrow and paraspinal muscle are both independent as well as additive risk factors for intervertebral disc degeneration. • Quantitative magnetic resonance imaging measurements of bone marrow and paraspinal muscle may serve as imaging biomarkers for intervertebral disc degeneration.

Proposed diagnostic volumetric bone mineral density thresholds for osteoporosis and osteopenia at the cervicothoracic spine in correlation to the lumbar spine.

OBJECTIVES: To determine the correlation between cervicothoracic and lumbar volumetric bone mineral density (vBMD) in an average cohort of adults and to identify specific diagnostic thresholds for the cervicothoracic spine on the individual subject level. METHODS: In this HIPPA-compliant study, we retrospectively included 260 patients (59.7 ± 18.3 years, 105 women), who received a contrast-enhanced or non-contrast-enhanced CT scan. vBMD was extracted using an automated pipeline ( https://anduin.bonescreen.de ). The association of vBMD between each vertebra spanning C2-T12 and the averaged values at the lumbar spine (L1-L3) was analyzed before and after semiquantitative assessment of fracture status and degeneration, and respective vertebra-specific cut-off values for osteoporosis were calculated using linear regression. RESULTS: In both women and men, trabecular vBMD decreased with age in the cervical, thoracic, and lumbar regions. vBMD values of cervicothoracic vertebrae showed strong correlations with lumbar vertebrae (L1-L3), with a median Pearson value of r = 0.87 (range: rC2 = 0.76 to rT12 = 0.96). The correlation coefficients were significantly lower (p < 0.0001) without excluding fractured and degenerated vertebrae, median r = 0.82 (range: rC2 = 0.69 to rT12 = 0.93). Respective cut-off values for osteoporosis peaked at C4 (209.2 mg/ml) and decreased to 83.8 mg/ml at T12. CONCLUSION: Our data show a high correlation between clinically used mean L1-L3 values and vBMD values elsewhere in the spine, independent of age. The proposed cut-off values for the cervicothoracic spine therefore may allow the determination of low bone mass even in clinical cases where only parts of the spine are imaged. KEY POINTS: vBMD of all cervicothoracic vertebrae showed strong correlation with lumbar vertebrae (L1-L3), with a median Pearson's correlation coefficient of r = 0.87 (range: rC2 = 0.76 to rT12 = 0.96). The correlation coefficients were significantly lower (p < 0.0001) without excluding fractured and moderate to severely degenerated vertebrae, median r = 0.82 (range: rC2 = 0.69 to rT12 = 0.93). We postulate that trabecular vBMD < 200 mg/ml for the cervical spine and < 100 mg/ml for the thoracic spine are strong indicators of osteoporosis, similar to < 80 mg/ml at the lumbar spine.

[Mediastinal lesions : The most common pathologies in chest X-rays and their correlations in computed tomography]. / Mediastinale Läsionen : Die häufigsten Pathologien in der Röntgenaufnahme des Thorax und deren Korrelation in der Computertomographie.

BACKGROUND: Many pathologies of the mediastinum can be diagnosed using standard radiographs. Correlation of radiographic findings with computed tomography (CT) is instructive for a better understanding and can help improve detection rates of mediastinal lesions. OBJECTIVES: To identify the most common mediastinal lesions and to correlate their features in chest radiographs and CT. METHODS: The International Thymic Malignancy Interest Group (ITMIG) classification in the anterior, middle, and posterior mediastinum is based on anatomic landmarks. Used as a tool to characterize mediastinal lesions this classification is applied in this article. RESULTS: The most common lesions include mediastinal goiter, germ cell and thymic neoplasms in the anterior mediastinum, lymphadenopathy in the middle mediastinum, and neurogenic neoplasms in the posterior mediastinum. Other lesions of neoplastic or non-neoplastic origin can be distinguished in the three compartments and should be considered in the differential diagnosis. CONCLUSIONS: Knowledge of the most common pathologies in the three mediastinal compartments can accelerate differential diagnosis. Understanding the normal mediastinal lines is key in anatomic localization and detection of many lesions in chest radiographs.

MRI-Based Quantitative Osteoporosis Imaging at the Spine and Femur.

Osteoporosis is a systemic skeletal disease with a high prevalence worldwide, characterized by low bone mass and microarchitectural deterioration, predisposing an individual to fragility fractures. Dual-energy X-ray absorptiometry (DXA) has been the clinical reference standard for diagnosing osteoporosis and for assessing fracture risk for decades. However, other imaging modalities are of increasing importance to investigate the etiology, treatment, and fracture risk. The purpose of this work is to review the available literature on quantitative magnetic resonance imaging (MRI) methods and related findings in osteoporosis at the spine and proximal femur as the clinically most important fracture sites. Trabecular bone microstructure analysis at the proximal femur based on high-resolution MRI allows for a better prediction of osteoporotic fracture risk than DXA-based bone mineral density (BMD) alone. In the 1990s, T2 * mapping was shown to correlate with the density and orientation of the trabecular bone. Recently, quantitative susceptibility mapping (QSM), which overcomes some of the limitations of T2 * mapping, has been applied for trabecular bone quantifications at the spine, whereas ultrashort echo time (UTE) imaging provides valuable surrogate markers of cortical bone quantity and quality. Magnetic resonance spectroscopy (MRS) and chemical shift encoding-based water-fat MRI (CSE-MRI) enable the quantitative assessment of the nonmineralized bone compartment through extraction of the bone marrow fat fraction (BMFF). Furthermore, CSE-MRI allows for the differentiation of osteoporotic vs. pathologic fractures, which is of high clinical relevance. Lastly, advanced postprocessing and image analysis tools, particularly considering statistical parametric mapping and region-specific BMFF distributions, have high potential to further improve MRI-based fracture risk assessments at the spine and hip. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 2.

Low-dose MDCT: evaluation of the impact of systematic tube current reduction and sparse sampling on the detection of degenerative spine diseases.

OBJECTIVES: To investigate potential radiation dose reduction for multi-detector computed tomography (MDCT) exams of the spine by using sparse sampling and virtually lowered tube currents combined with statistical iterative reconstruction (SIR). METHODS: MDCT data of 26 patients (68.9 ± 11.7 years, 42.3% males) were retrospectively simulated as if the scans were acquired at 50%, 10%, 5%, and 3% of the original X-ray tube current or number of projections, using SIR for image reconstructions. Two readers performed qualitative image evaluation considering overall image quality, artifacts, and contrast and determined the number and type of degenerative changes. Scoring was compared between readers and virtual low-dose and sparse-sampled MDCT, respectively. RESULTS: Image quality and contrast decreased with virtual lowering of tube current and sparse sampling, but all degenerative changes were correctly detected in MDCT with 50% of tube current as well as MDCT with 50% of projections. Sparse-sampled MDCT with only 10% of initial projections still enabled correct identification of all degenerative changes, in contrast to MDCT with virtual tube current reduction by 90% where non-calcified disc herniations were frequently missed (R1: 23.1%, R2: 21.2% non-diagnosed herniations). The average volumetric CT dose index (CTDIvol) was 1.4 mGy for MDCT with 10% of initial projections, compared with 13.8 mGy for standard-dose imaging. CONCLUSIONS: MDCT with 50% of original tube current or projections using SIR still allowed for accurate diagnosis of degenerative changes. Sparse sampling may be more promising for further radiation dose reductions since no degenerative changes were missed with 10% of initial projections. KEY POINTS: • Most common degenerative changes of the spine can be diagnosed in multi-detector CT with 50% of tube current or number of projections. • Sparse-sampled multi-detector CT with only 10% of initial projections still enables correct identification of degenerative changes, in contrast to imaging with 10% of original tube current. • Sparse sampling may be a promising option for distinct lowering of radiation dose, reducing the CTDIvol from 13.8 to 1.4 mGy in the study cohort.

Automatic opportunistic osteoporosis screening in routine CT: improved prediction of patients with prevalent vertebral fractures compared to DXA.

OBJECTIVES: To compare spinal bone measures derived from automatic and manual assessment in routine CT with dual energy X-ray absorptiometry (DXA) in their association with prevalent osteoporotic vertebral fractures using our fully automated framework ( https://anduin.bonescreen.de ) to assess various bone measures in clinical CT. METHODS: We included 192 patients (141 women, 51 men; age 70.2 ± 9.7 years) who had lumbar DXA and CT available (within 1 year). Automatic assessment of spinal bone measures in CT included segmentation of vertebrae using a convolutional neural network (CNN), reduction to the vertebral body, and extraction of bone mineral content (BMC), trabecular and integral volumetric bone mineral density (vBMD), and CT-based areal BMD (aBMD) using asynchronous calibration. Moreover, trabecular bone was manually sampled (manual vBMD). RESULTS: A total of 148 patients (77%) had vertebral fractures and significantly lower values in all bone measures compared to patients without fractures (p ≤ 0.001). Except for BMC, all CT-based measures performed significantly better as predictors for vertebral fractures compared to DXA (e.g., AUC = 0.885 for trabecular vBMD and AUC = 0.86 for integral vBMD vs. AUC = 0.668 for DXA aBMD, respectively; both p < 0.001). Age- and sex-adjusted associations with fracture status were strongest for manual vBMD (OR = 7.3, [95%] CI 3.8-14.3) followed by automatically assessed trabecular vBMD (OR = 6.9, CI 3.5-13.4) and integral vBMD (OR = 4.3, CI 2.5-7.6). Diagnostic cutoffs of integral vBMD for osteoporosis (< 160 mg/cm3) or low bone mass (160 ≤ BMD < 190 mg/cm3) had sensitivity (84%/41%) and specificity (78%/95%) similar to trabecular vBMD. CONCLUSIONS: Fully automatic osteoporosis screening in routine CT of the spine is feasible. CT-based measures can better identify individuals with reduced bone mass who suffered from vertebral fractures than DXA. KEY POINTS: • Opportunistic osteoporosis screening of spinal bone measures derived from clinical routine CT is feasible in a fully automatic fashion using a deep learning-driven framework ( https://anduin.bonescreen.de ). • Manually sampled volumetric BMD (vBMD) and automatically assessed trabecular and integral vBMD were the best predictors for prevalent vertebral fractures. • Except for bone mineral content, all CT-based bone measures performed significantly better than DXA-based measures. • We introduce diagnostic thresholds of integral vBMD for osteoporosis (< 160 mg/cm3) and low bone mass (160 ≤ BMD < 190 mg/cm3) with almost equal sensitivity and specificity compared to conventional thresholds of quantitative CT as proposed by the American College of Radiology (osteoporosis < 80 mg/cm3).

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

OBJECTIVES: To compare opportunistic quantitative CT (QCT) with dual energy X-ray absorptiometry (DXA) in their ability to predict incident vertebral fractures. METHODS: We included 84 patients aged 50 years and older, who had routine CT including the lumbar spine and DXA within a 12-month period (baseline) as well as follow-up imaging after at least 12 months or who sustained an incident vertebral fracture documented earlier. Patients with bone disorders aside from osteoporosis were excluded. Fracture status and trabecular bone mineral density (BMD) were retrospectively evaluated in baseline CT and fracture status was reassessed at follow-up. BMDQCT was assessed by opportunistic QCT with asynchronous calibration of multiple MDCT scanners. RESULTS: Sixteen patients had incident vertebral fractures showing lower mean BMDQCT than patients without fracture (p = 0.001). For the risk of incident vertebral fractures, the hazard ratio increased per SD in BMDQCT (4.07; 95% CI, 1.98-8.38), as well as after adjusting for age, sex, and prevalent fractures (2.54; 95% CI, 1.09-5.90). For DXA, a statistically significant increase in relative hazard per SD decrease in T-score was only observed after age and sex adjustment (1.57; 95% CI, 1.04-2.38). The predictability of incident vertebral fractures was good by BMDQCT (AUC = 0.76; 95% CI, 0.64-0.89) and non-significant by T-scores. Asynchronously calibrated CT scanners showed good long-term stability (linear drift ranging from - 0.55 to - 2.29 HU per year). CONCLUSIONS: Opportunistic screening of mainly neurosurgical and oncologic patients in CT performed for indications other than densitometry allows for better risk assessment of imminent vertebral fractures than dedicated DXA. KEY POINTS: • Opportunistic QCT predicts osteoporotic vertebral fractures better than DXA reference standard in mainly neurosurgical and oncologic patients. • More than every second patient (56%) with an incident vertebral fracture was misdiagnosed not having osteoporosis according to DXA. • Standard ACR QCT-cutoff values for osteoporosis (< 80 mg/cm 3 ) and osteopenia (≤ 120 mg/cm 3 ) can also be applied scanner independently in calibrated opportunistic QCT.

Multi-detector CT imaging: impact of virtual tube current reduction and sparse sampling on detection of vertebral fractures.

PURPOSE: To systematically evaluate the effects of virtual tube current reduction and sparse sampling on image quality and vertebral fracture diagnostics in multi-detector computed tomography (MDCT). MATERIALS AND METHODS: In routine MDCT scans of 35 patients (80.0% females, 70.6 ± 14.2 years, 65.7% showing vertebral fractures), reduced radiation doses were retrospectively simulated by virtually lowering tube currents and applying sparse sampling, considering 50%, 25%, and 10% of the original tube current and projections, respectively. Two readers evaluated items of image quality and presence of vertebral fractures. Readout between the evaluations in the original images and those with virtually lowered tube currents or sparse sampling were compared. RESULTS: A significant difference was revealed between the evaluations of image quality between MDCT with virtually lowered tube current and sparse-sampled MDCT (p < 0.001). Sparse-sampled data with only 25% of original projections still showed good to very good overall image quality and contrast of vertebrae as well as minimal artifacts. There were no missed fractures in sparse-sampled MDCT with 50% reduction of projections, and clinically acceptable determination of fracture age was possible in MDCT with 75% reduction of projections, in contrast to MDCT with 50% or 75% virtual tube current reduction, respectively. CONCLUSION: Sparse-sampled MDCT provides adequate image quality and diagnostic accuracy for vertebral fracture detection with 50% of original projections in contrast to corresponding MDCT with lowered tube current. Thus, sparse sampling is a promising technique for dose reductions in MDCT that could be introduced in future generations of scanners. KEY POINTS: • MDCT with a reduction of projection numbers of 50% still showed high diagnostic accuracy without any missed vertebral fractures. • Clinically acceptable determination of vertebral fracture age was possible in MDCT with a reduction of projection numbers of 75%. • With sparse sampling, higher reductions in radiation exposure can be achieved without compromised image or diagnostic quality in routine MDCT of the spine as compared to MDCT with reduced tube currents.

Tube Current Reduction in CT Angiography: How Low Can We Go in Imaging of Patients With Suspected Acute Stroke?

OBJECTIVE. The purpose of this study was to systematically evaluate image quality, detectability of large-vessel occlusion or dissection, and diagnostic confidence in CT angiography (CTA) with virtually lowered tube current and iterative reconstruction in patients with suspected acute stroke. MATERIALS AND METHODS. Thirty patients (15 with large-vessel occlusion or dissection) underwent CTA of the supraaortal up to the intracranial arterial vessels. CTA scans were simulated as if they were made at 50% (D50), 25% (D25), and 10% (D10) of the original tube current. Image reconstruction was achieved with two levels of iterative reconstruction (A, similar to clinical reconstructions; B, two times stronger regularization). Two readers performed qualitative image evaluation considering overall image quality, artifacts, vessel contrast, detection of vessel abnormalities, and diagnostic confidence. RESULTS. Level B of iterative reconstruction was favorable regarding overall image quality and artifacts for D10, whereas level A was favorable for D100 and D50. CTA scans at D25 and both levels of iterative reconstruction still showed good vessel contrast, with even peripheral arterial branches of the anterior, middle, and posterior cerebral arteries being clearly detectable. Furthermore, CTA scans at D25 and level A of iterative reconstruction showed an adequate level of diagnostic confidence without any missed large-vessel occlusion or dissection according to evaluations by both readers. CONCLUSION. CTA with iterative reconstruction and tube currents decreased to 25% of that for original imaging is feasible without limitations in vessel contrast or detection of vessel abnormalities in patients with suspected acute stroke. Thus, the approach evaluated enables substantial reductions in radiation exposure for patients undergoing head and neck CTA.

Sex differences and age-related changes in vertebral body volume and volumetric bone mineral density at the thoracolumbar spine using opportunistic QCT.

Objectives: To quantitatively investigate the age- and sex-related longitudinal changes in trabecular volumetric bone mineral density (vBMD) and vertebral body volume at the thoracolumbar spine in adults. Methods: We retrospectively included 168 adults (mean age 58.7 ± 9.8 years, 51 women) who received ≥7 MDCT scans over a period of ≥6.5 years (mean follow-up 9.0 ± 2.1 years) for clinical reasons. Level-wise vBMD and vertebral body volume were extracted from 22720 thoracolumbar vertebrae using a convolutional neural network (CNN)-based framework with asynchronous calibration and correction of the contrast media phase. Human readers conducted semiquantitative assessment of fracture status and bony degenerations. Results: In the 40-60 years age group, women had a significantly higher trabecular vBMD than men at all thoracolumbar levels (p<0.05 to p<0.001). Conversely, men, on average, had larger vertebrae with lower vBMD. This sex difference in vBMD did not persist in the 60-80 years age group. While the lumbar (T12-L5) vBMD slopes in women only showed a non-significant trend of accelerated decline with age, vertebrae T1-11 displayed a distinct pattern, with women demonstrating a significantly accelerated decline compared to men (p<0.01 to p<0.0001). Between baseline and last follow-up examinations, the vertebral body volume slightly increased in women (T1-12: 1.1 ± 1.0 cm3; L1-5: 1.0 ± 1.4 cm3) and men (T1-12: 1.2 ± 1.3 cm3; L1-5: 1.5 ± 1.6 cm3). After excluding vertebrae with bony degenerations, the residual increase was only small in women (T1-12: 0.6 ± 0.6 cm3; L1-5: 0.7 ± 0.7 cm3) and men (T1-12: 0.7 ± 0.6 cm3; L1-5: 1.2 ± 0.8 cm3). In non-degenerated vertebrae, the mean change in volume was <5% of the respective vertebral body volumes. Conclusion: Sex differences in thoracolumbar vBMD were apparent before menopause, and disappeared after menopause, likely attributable to an accelerated and more profound vBMD decline in women at the thoracic spine. In patients without advanced spine degeneration, the overall volumetric changes in the vertebral body appeared subtle.

Microvascular disease not type 2 diabetes is associated with increased cortical porosity: A study of cortical bone microstructure and intracortical vessel characteristics.

Introduction: Fracture risk is elevated in type 2 diabetes (T2D) despite normal or even high bone mineral density (BMD). Microvascular disease (MVD) is a diabetic complication, but also associated with other diseases, for example chronic kidney disease. We hypothesize that increased fracture risk in T2D could be due to increased cortical porosity (Ct.Po) driven by expansion of the vascular network in MVD. The purpose of this study was to investigate associations of T2D and MVD with cortical microstructure and intracortical vessel parameters. Methods: The study group consisted of 75 participants (38 with T2D and 37 without T2D). High-resolution peripheral quantitative CT (HR-pQCT) and dynamic contrast-enhanced MRI (DCE-MRI) of the ultra-distal tibia were performed to assess cortical bone and intracortical vessels (outcomes). MVD was defined as ≥1 manifestation including neuropathy, nephropathy, or retinopathy based on clinical exams in all participants. Adjusted means of outcomes were compared between groups with/without T2D or between participants with/without MVD in both groups using linear regression models adjusting for age, sex, BMI, and T2D as applicable. Results: MVD was found in 21 (55 %) participants with T2D and in 9 (24 %) participants without T2D. In T2D, cortical pore diameter (Ct.Po.Dm) and diameter distribution (Ct.Po.Dm.SD) were significantly higher by 14.6 µm (3.6 %, 95 % confidence interval [CI]: 2.70, 26.5 µm, p = 0.017) and by 8.73 µm (4.8 %, CI: 0.79, 16.7 µm, p = 0.032), respectively. In MVD, but not in T2D, cortical porosity was significantly higher by 2.25 % (relative increase = 12.9 %, CI: 0.53, 3.97 %, p = 0.011) and cortical BMD (Ct.BMD) was significantly lower by -43.6 mg/cm3 (2.6 %, CI: -77.4, -9.81 mg/cm3, p = 0.012). In T2D, vessel volume and vessel diameter were significantly higher by 0.02 mm3 (13.3 %, CI: 0.004, 0.04 mm3, p = 0.017) and 15.4 µm (2.9 %, CI: 0.42, 30.4 µm, p = 0.044), respectively. In MVD, vessel density was significantly higher by 0.11 mm-3 (17.8 %, CI: 0.01, 0.21 mm-3, p = 0.033) and vessel volume and diameter were significantly lower by -0.02 mm3 (13.7 %, CI: -0.04, -0.004 mm3, p = 0.015) and - 14.6 µm (2.8 %, CI: -29.1, -0.11 µm, p = 0.048), respectively. Conclusions: The presence of MVD, rather than T2D, was associated with increased cortical porosity. Increased porosity in MVD was coupled with a larger number of smaller vessels, which could indicate upregulation of neovascularization triggered by ischemia. It is unclear why higher variability and average diameters of pores in T2D were accompanied by larger vessels.

MR-based techniques for intracortical vessel visualization and characterization: understanding the impact of microvascular disease on skeletal health.

PURPOSE OF REVIEW: The relationships between bone vasculature and bone microstructure and strength remain incompletely understood. Addressing this gap will require in vivo imaging capabilities. We describe the relevant vascular anatomy of compact bone, review current magnetic resonance imaging (MRI)-based techniques that allow in vivo assessment of intracortical vasculature, and finally present preliminary studies that apply these techniques to investigate changes in intracortical vessels in aging and disease. RECENT FINDINGS: Ultra-short echo time MRI (UTE MRI), dynamic contrast-enhanced MRI (DCE-MRI), and susceptibility-weighted MRI techniques are able to probe intracortical vasculature. Applied to patients with type 2 diabetes, DCE-MRI was able to find significantly larger intracortical vessels compared to nondiabetic controls. Using the same technique, a significantly larger number of smaller vessels was observed in patients with microvascular disease compared to those without. Preliminary data on perfusion MRI showed decreased cortical perfusion with age. SUMMARY: Development of in vivo techniques for intracortical vessel visualization and characterization will enable the exploration of interactions between the vascular and skeletal systems, and further our understanding of drivers of cortical pore expansion. As we investigate potential pathways of cortical pore expansion, appropriate treatment and prevention strategies will be clarified.

Computed Tomography of the Spine : Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose.

The introduction of the first whole-body CT scanner in 1974 marked the beginning of cross-sectional spine imaging. In the last decades, the technological advancement, increasing availability and clinical success of CT led to a rapidly growing number of CT examinations, also of the spine. After initially being primarily used for trauma evaluation, new indications continued to emerge, such as assessment of vertebral fractures or degenerative spine disease, preoperative and postoperative evaluation, or CT-guided interventions at the spine; however, improvements in patient management and clinical outcomes come along with higher radiation exposure, which increases the risk for secondary malignancies. Therefore, technical developments in CT acquisition and reconstruction must always include efforts to reduce the radiation dose. But how exactly can the dose be reduced? What amount of dose reduction can be achieved without compromising the clinical value of spinal CT examinations and what can be expected from the rising stars in CT technology: artificial intelligence and photon counting CT? In this article, we try to answer these questions by systematically reviewing dose reduction techniques with respect to the major clinical indications of spinal CT. Furthermore, we take a concise look on the dose reduction potential of future developments in CT hardware and software.

Computed Tomography of the Head : A Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose.

In 1971, the first computed tomography (CT) scan was performed on a patient's brain. Clinical CT systems were introduced in 1974 and dedicated to head imaging only. New technological developments, broader availability, and the clinical success of CT led to a steady growth in examination numbers. Most frequent indications for non-contrast CT (NCCT) of the head include the assessment of ischemia and stroke, intracranial hemorrhage and trauma, while CT angiography (CTA) has become the standard for first-line cerebrovascular evaluation; however, resulting improvements in patient management and clinical outcomes come at the cost of radiation exposure, increasing the risk for secondary morbidity. Therefore, radiation dose optimization should always be part of technical advancements in CT imaging but how can the dose be optimized? What dose reduction can be achieved without compromising diagnostic value, and what is the potential of the upcoming technologies artificial intelligence and photon counting CT? In this article, we look for answers to these questions by reviewing dose reduction techniques with respect to the major clinical indications of NCCT and CTA of the head, including a brief perspective on what to expect from current and future developments in CT technology with respect to radiation dose optimization.

Long-term reproducibility of opportunistically assessed vertebral bone mineral density and texture features in routine clinical multi-detector computed tomography using an automated segmentation framework.

Background: To investigate reproducibility of texture features and volumetric bone mineral density (vBMD) extracted from trabecular bone in the thoracolumbar spine in routine clinical multi-detector computed tomography (MDCT) data in a single scanner environment. Methods: Patients who underwent two routine clinical thoraco-abdominal MDCT exams at a single scanner with a time interval of 6 to 26 months (n=203, 131 males; time interval mean, 13 months; median, 12 months) were included in this observational study. Exclusion criteria were metabolic and hematological disorders, bone metastases, use of bone-active medications, and history of osteoporotic vertebral fractures (VFs) or prior diagnosis of osteoporosis. A convolutional neural network (CNN)-based framework was used for automated spine labeling and segmentation (T5-L5), asynchronous Hounsfield unit (HU)-to-BMD calibration, and correction for the intravenous contrast medium phase. Vertebral vBMD and six texture features [varianceglobal, entropy, short-run emphasis (SRE), long-run emphasis (LRE), run-length non-uniformity (RLN), and run percentage (RP)] were extracted for mid- (T5-T8) and lower thoracic (T9-T12), and lumbar vertebrae (L1-L5), respectively. Relative annual changes were calculated in texture features and vBMD for each vertebral level and sorted by sex, and changes were checked for statistical significance (P<0.05) using paired t-tests. Root mean square coefficient of variation (RMSCV) and root mean square error (RMSE) were calculated as measures of variability. Results: SRE, LRE, RLN, and RP exhibited substantial reproducibility with RMSCV-values below 2%, for both sexes and at all spine levels, while vBMD was less reproducible (RMSCV =11.9-16.2%). Entropy showed highest variability (RMSCV =4.34-7.69%) due to statistically significant increases [range, mean ± standard deviation: (4.40±5.78)% to (8.36±8.66)%, P<0.001]. RMSCV of varianceglobal ranged from 1.60% to 3.03%. Conclusions: Opportunistic assessment of texture features in a single scanner environment using the presented CNN-based framework yields substantial reproducibility, outperforming vBMD reproducibility. Lowest scan-rescan variability was found for higher-order texture features. Further studies are warranted to determine, whether microarchitectural changes to the trabecular bone may be assessed through texture features.

Incidental vertebral fracture prediction using neuronal network-based automatic spine segmentation and volumetric bone mineral density extraction from routine clinical CT scans.

Objectives: To investigate vertebral osteoporotic fracture (VF) prediction by automatically extracted trabecular volumetric bone mineral density (vBMD) from routine CT, and to compare the model with fracture prevalence-based prediction models. Methods: This single-center retrospective study included patients who underwent two thoraco-abdominal CT scans during clinical routine with an average inter-scan interval of 21.7 ± 13.1 months (range 5-52 months). Automatic spine segmentation and vBMD extraction was performed by a convolutional neural network framework (anduin.bonescreen.de). Mean vBMD was calculated for levels T5-8, T9-12, and L1-5. VFs were identified by an expert in spine imaging. Odds ratios (ORs) for prevalent and incident VFs were calculated for vBMD (per standard deviation decrease) at each level, for baseline VF prevalence (yes/no), and for baseline VF count (n) using logistic regression models, adjusted for age and sex. Models were compared using Akaike's and Bayesian information criteria (AIC & BIC). Results: 420 patients (mean age, 63 years ± 9, 276 males) were included in this study. 40 (25 female) had prevalent and 24 (13 female) had incident VFs. Individuals with lower vBMD at any spine level had higher odds for VFs (L1-5, prevalent VF: OR,95%-CI,p: 2.2, 1.4-3.5,p=0.001; incident VF: 3.5, 1.8-6.9,p<0.001). In contrast, VF status (2.15, 0.72-6.43,p=0.170) and count (1.38, 0.89-2.12,p=0.147) performed worse in incident VF prediction. Information criteria revealed best fit for vBMD-based models (AIC vBMD=165.2; VF status=181.0; count=180.7). Conclusions: VF prediction based on automatically extracted vBMD from routine clinical MDCT outperforms prediction models based on VF status and count. These findings underline the importance of opportunistic quantitative osteoporosis screening in clinical routine MDCT data.

Cost-effectiveness of opportunistic QCT-based osteoporosis screening for the prediction of incident vertebral fractures.

Objectives: Opportunistic quantitative computed tomography (oQCT) derived from non-dedicated routine CT has demonstrated high accuracy in diagnosing osteoporosis and predicting incident vertebral fractures (VFs). We aimed to investigate the cost-effectiveness of oQCT screening compared to dual-energy X-ray absorptiometry (DXA) as the standard of care for osteoporosis screening. Methods: Three screening strategies ("no osteoporosis screening", "oQCT screening", and "DXA screening") after routine CT were simulated in a state-transition model for hypothetical cohorts of 1,000 patients (women and men aged 65 years) over a follow-up period of 5 years (base case). The primary outcomes were the cumulative costs and the quality-adjusted life years (QALYs) estimated from a U.S. health care perspective for the year 2022. Cost-effectiveness was assessed based on a willingness-to-pay (WTP) threshold of $70,249 per QALY. The secondary outcome was the number of prevented VFs. Deterministic and probabilistic sensitivity analyses were conducted to test the models' robustness. Results: Compared to DXA screening, oQCT screening increased QALYs in both sexes (additional 2.40 per 1,000 women and 1.44 per 1,000 men) and resulted in total costs of $3,199,016 and $950,359 vs. $3,262,934 and $933,077 for women and men, respectively. As a secondary outcome, oQCT screening prevented 2.6 and 2.0 additional VFs per 1,000 women and men, respectively. In the probabilistic sensitivity analysis, oQCT screening remained cost-effective in 88.3% (women) and 90.0% (men) of iterations. Conclusion: oQCT screening is a cost-effective ancillary approach for osteoporosis screening and has the potential to prevent a substantial number of VFs if considered in daily clinical practice.

Validation of a Patient-Specific Musculoskeletal Model for Lumbar Load Estimation Generated by an Automated Pipeline From Whole Body CT.

Background: Chronic back pain is a major health problem worldwide. Although its causes can be diverse, biomechanical factors leading to spinal degeneration are considered a central issue. Numerical biomechanical models can identify critical factors and, thus, help predict impending spinal degeneration. However, spinal biomechanics are subject to significant interindividual variations. Therefore, in order to achieve meaningful findings on potential pathologies, predictive models have to take into account individual characteristics. To make these highly individualized models suitable for systematic studies on spinal biomechanics and clinical practice, the automation of data processing and modeling itself is inevitable. The purpose of this study was to validate an automatically generated patient-specific musculoskeletal model of the spine simulating static loading tasks. Methods: CT imaging data from two patients with non-degenerative spines were processed using an automated deep learning-based segmentation pipeline. In a semi-automated process with minimal user interaction, we generated patient-specific musculoskeletal models and simulated various static loading tasks. To validate the model, calculated vertebral loadings of the lumbar spine and muscle forces were compared with in vivo data from the literature. Finally, results from both models were compared to assess the potential of our process for interindividual analysis. Results: Calculated vertebral loads and muscle activation overall stood in close correlation with data from the literature. Compression forces normalized to upright standing deviated by a maximum of 16% for flexion and 33% for lifting tasks. Interindividual comparison of compression, as well as lateral and anterior-posterior shear forces, could be linked plausibly to individual spinal alignment and bodyweight. Conclusion: We developed a method to generate patient-specific musculoskeletal models of the lumbar spine. The models were able to calculate loads of the lumbar spine for static activities with respect to individual biomechanical properties, such as spinal alignment, bodyweight distribution, and ligament and muscle insertion points. The process is automated to a large extent, which makes it suitable for systematic investigation of spinal biomechanics in large datasets.