Vertebral bone attenuation in Hounsfield Units and prevalent vertebral fractures are associated with the short-term risk of vertebral fractures in current and ex-smokers with and without COPD: a 3-year chest CT follow-up study

Dort, M.J. van; Driessen, Johanna H M; Geusens, Piet; Romme, Elisabeth A. P. M.; Smeenk, Frank W.J.M.; Wouters, Emiel F.M.; Bergh, Joop van den

doi:10.1007/s00198-019-04977-w

Cited by 13 publications

(4 citation statements)

References 47 publications

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“…Ohara et al showed that in COPD patients, the extent of pulmonary emphysema was significantly correlated with decreased bone density [ 65 ]. In addition, van Dort and associates evaluated bone attenuation in vertebrae T 4 –T 12 and prevalent and incident vertebra fractures in 1239 individuals included in the ECLIPSE study, with baseline and 1-year and 3-year follow-up CT scans [ 66 ]. The results demonstrated that in former smokers with and without COPD, the combination of bone attenuation and prevalent vertebra fractures was strongly associated with the short-term risk of incident vertebra fractures.…”

Section: Assessment Of Smoking-related Diseases (Comorbidities)mentioning

confidence: 99%

The Potential Role of Artificial Intelligence in Lung Cancer Screening Using Low-Dose Computed Tomography

2022

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Two large randomized controlled trials of low-dose CT (LDCT)-based lung cancer screening (LCS) in high-risk smoker populations have shown a reduction in the number of lung cancer deaths in the screening group compared to a control group. Even if various countries are currently considering the implementation of LCS programs, recurring doubts and fears persist about the potentially high false positive rates, cost-effectiveness, and the availability of radiologists for scan interpretation. Artificial intelligence (AI) can potentially increase the efficiency of LCS. The objective of this article is to review the performances of AI algorithms developed for different tasks that make up the interpretation of LCS CT scans, and to estimate how these AI algorithms may be used as a second reader. Despite the reduction in lung cancer mortality due to LCS with LDCT, many smokers die of comorbid smoking-related diseases. The identification of CT features associated with these comorbidities could increase the value of screening with minimal impact on LCS programs. Because these smoking-related conditions are not systematically assessed in current LCS programs, AI can identify individuals with evidence of previously undiagnosed cardiovascular disease, emphysema or osteoporosis and offer an opportunity for treatment and prevention.

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Section: Assessment Of Smoking-related Diseases (Comorbidities)mentioning

confidence: 99%

The Potential Role of Artificial Intelligence in Lung Cancer Screening Using Low-Dose Computed Tomography

2022

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“…Chest computed tomography (CT) scans are used for lung cancer screening in heavy smokers and to assess COPD [17,[22][23][24]. Quantitative CT can be used to characterize reduced BMD and bone architecture [23,25,26]. In addition, DEXA measures of whole body lean mass correlates with PMA derived from chest CT has and have been validated as a useful tool, which can be used to derive measurements of fat free muscle mass index (FFMI) to diagnose and monitor sarcopenia in COPD [22,24,27,28].…”

Section: Introductionmentioning

confidence: 99%

Increased chest CT derived bone and muscle measures capture markers of improved morbidity and mortality in COPD

et al. 2022

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Background Chronic obstructive pulmonary disease (COPD) is a disease of accelerated aging and is associated with comorbid conditions including osteoporosis and sarcopenia. These extrapulmonary conditions are highly prevalent yet frequently underdiagnosed and overlooked by pulmonologists in COPD treatment and management. There is evidence supporting a role for bone-muscle crosstalk which may compound osteoporosis and sarcopenia risk in COPD. Chest CT is commonly utilized in COPD management, and we evaluated its utility to identify low bone mineral density (BMD) and reduced pectoralis muscle area (PMA) as surrogates for osteoporosis and sarcopenia. We then tested whether BMD and PMA were associated with morbidity and mortality in COPD. Methods BMD and PMA were analyzed from chest CT scans of 8468 COPDGene participants with COPD and controls (smoking and non-smoking). Multivariable regression models tested the relationship of BMD and PMA with measures of function (6-min walk distance (6MWD), handgrip strength) and disease severity (percent emphysema and lung function). Multivariable Cox proportional hazards models were used to evaluate the relationship between sex-specific quartiles of BMD and/or PMA derived from non-smoking controls with all-cause mortality. Results COPD subjects had significantly lower BMD and PMA compared with controls. Higher BMD and PMA were associated with increased physical function and less disease severity. Participants with the highest BMD and PMA quartiles had a significantly reduced mortality risk (36% and 46%) compared to the lowest quartiles. Conclusions These findings highlight the potential for CT-derived BMD and PMA to characterize osteoporosis and sarcopenia using equipment available in the pulmonary setting.

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“…It has previously been shown that reduced bone quality, as measured with CT-derived HU, correlates with an increased rate of cage subsidence and loss of reduction [5,14]. Further, CT-based evaluation has a sensitivity comparable to DEXA for the detection of osteoporosis and can be used to predict osteoporotic fractures [15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Reliability of Hounsfield Units as a Measure of Bone Density: Applications in the Treatment of Thoracolumbar Fractures

Ullrich

McLean

Mendel

et al. 2021

Preprint

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PurposeThe aim of this study was to evaluate the reliability of Hounsfield units (HU) for bone density measurement in spinal trauma. HU have already been demonstrated to be reliable for this purpose in degenerative spine disease.Methods This study is a retrospective cross-sectional analysis considering CT scanner model, slice thickness and HU in native and contrast CT scans. Linear regression, bivariate correlation and ROC analyses were performed to analyze the relationship between qCT values and HU. The inter-rater reliability of HU measurements was assessed using the intra-class correlation coefficient.Results344 patient datasets were analyzed. CT scanner model and slice thickness were found to have no significant impact on HU. The inter-rater reliability for HU measurements from native CT scans was ICC(3, 1)=0.932 (CI95: 0.919 – 0.943, p<0.001). The formula qCT=0.8·HUwithout CM+5 can be used to predict qCT values from native CT scan HU. ROC analysis revealed maximum sensitivity and specificity of 0.91 and 0.93, respectively, with a cut-off value of 93 HU to predict osteoporosis.For contrast CT scans we determined an ICC(3,1) of 0.889 (CI95: 0.801 – 0.948, p<0.001) and a formula of qCT=0.6·HUwith CM-4. The maximum sensitivity and specificity calculated using HU in the presence of contrast medium were 0.83 and 0.89 with cut-off of values of 122 and 125 HU, respectively, depending on the observer.ConclusionsHU are reliable for measurement of bone quality in spinal trauma, especially in native CT scans. HU measurements from contrast CT scans should be used more cautiously for bone quality estimation.

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Vertebral bone attenuation in Hounsfield Units and prevalent vertebral fractures are associated with the short-term risk of vertebral fractures in current and ex-smokers with and without COPD: a 3-year chest CT follow-up study

Cited by 13 publications

References 47 publications

The Potential Role of Artificial Intelligence in Lung Cancer Screening Using Low-Dose Computed Tomography

The Potential Role of Artificial Intelligence in Lung Cancer Screening Using Low-Dose Computed Tomography

Increased chest CT derived bone and muscle measures capture markers of improved morbidity and mortality in COPD

Reliability of Hounsfield Units as a Measure of Bone Density: Applications in the Treatment of Thoracolumbar Fractures

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