Vertebral fracture risk (VFR) score for fracture prediction in postmenopausal women.

SUMMARY: Early prognosis of osteoporosis risk is not only important to individual patients but is also a key factor when screening for osteoporosis drug trial populations. We present an osteoporosis fracture risk score based on vertebral heights. The score separated individuals who sustained fractures (by follow-up after 6.3 years) from healthy controls at baseline. INTRODUCTION: This case-control study was designed to assess the ability of three novel fracture risk scoring methods to predict first incident lumbar vertebral fractures in postmenopausal women matched for classical risk factors such as BMD, BMI, and age. METHODS: This was a case-control study of 126 postmenopausal women, 25 of whom sustained at least one incident lumbar fracture and 101 controls that maintained skeletal integrity over a 6.3-year period. Three methods for fracture risk assessment were developed and tested. They are based on anterior, middle, and posterior vertebral heights measured from vertebrae T12-L5 in lumbar radiographs at baseline. Each score's fracture prediction potential was investigated in two variants using (1) measurements from the single most deformed vertebra or (2) average measurements across vertebrae T12-L5. Emphasis was given to the vertebral fracture risk (VFR) score. RESULTS: All scoring methods demonstrated significant separation of cases from controls at baseline. Specifically, for the VFR score, cases and controls were significantly different (0.67 ± 0.04 vs. 0.35 ± 0.03, p < 10 (-6)) with an AUC of 0.82. Dividing the VFR scores into tertiles, the fracture odds ratio for the highest versus lowest tertile was 35 (p < 0.001). Sorting the combined case-control group according to VFR score resulted in 90% of cases in the top half. CONCLUSION: At baseline, the three scores separated cases from controls and, especially, the VFR score appears to be predictive of fractures. Control experiments, however also, indicate that VFR-based fracture prediction is operator/annotator dependent and high-quality annotations are needed for good fracture prediction.

Parallel assessment of the impact of different hormone replacement therapies on breast density by radiologist- and computer-based analyses of mammograms.

OBJECTIVES: First, to compare the impact of nasally and orally dosed estradiol on breast density; second, to investigate the utility of computer-based automated approaches to the assessment of breast density with reference to traditional methods. METHODS: Digitized images from two 2-year, randomized, placebo-controlled trials formed the basis of the present post hoc analysis. Active treatments were 1 mg estradiol continuously combined with 0.125 mg trimegestone (oral hormone replacement therapy, HRT) or low-dose (150 or 300 microg estradiol) nasal estradiol cyclically combined with 200 mg micronized progesterone (nasal HRT). The effects on breast density were assessed by a radiologist, providing the BI-RADS score and the interactive threshold, and by a computer-based approach, providing the measure of stripiness and the HRT-effect specific measure of breast density. RESULTS: In the oral HRT trial, active treatment induced a significant increase in breast density, which was consistent in all methods used (all p < 0.05). In contrast, none of the methods detected significant changes in women receiving nasal HRT. The sensitivity of automated methods to discriminate HRT- from placebo-treated women was equal or better than the sensitivity of methods performed by the radiologist. CONCLUSIONS: The markedly different pharmacokinetic profile of nasal estrogen seems to be associated with better breast safety. Automated computer-based analysis of digitized mammograms provides a sensitive measure of changes in breast density induced by hormones and could serve as a useful tool in future clinical trials.

Separation of healthy and early osteoarthritis by automatic quantification of cartilage homogeneity.

OBJECTIVE: Cartilage loss as determined either by magnetic resonance imaging (MRI) or by joint space narrowing in X-rays is the result of cartilage erosion. However, metabolic processes within the cartilage that later result in cartilage loss may be a more accurate assessment method for early changes. Early biological processes of cartilage destruction are among other things, a combination of proteoglycan turnover, as a result of altered charge distributions, and local alterations in water content (edema). As water distribution is detectable by MRI, the aim of this study was to investigate cartilage homogeneity visualized by MRI related to water distribution, as a potential very early marker for early detection of knee osteoarthritis (OA). DESIGN: One hundred and fourteen right and left knees from 71 subjects aged 22-79 years were scanned using a Turbo 3D T(1) sequence on a 0.18T MRI Esaote scanner. The medial compartment of the tibial cartilage sheet was segmented using a fully automatic voxel classification scheme based on supervised learning. From the segmented cartilage sheet, homogeneity was quantified by measuring entropy from the distribution of signal intensities inside the compartment. For each knee an X-ray was acquired and the knees were categorized by the Kellgren and Lawrence (KL) index and the joint space width (JSW) was measured. The P-values for separating the groups by each of JSW, cartilage volume, cartilage mean intensity, and cartilage homogeneity were calculated using the unpaired t-test. RESULTS: The P-value for separating the group diagnosed as KL 0 from the group being KL 1 based on JSW, volume and mean signal intensity the values were P=0.9, P=0.4 and P=0.0009, respectively. In contrast, the P-value for homogeneity was P=0.0004. The precision of the measures assessed, as a test-retest root mean square coefficient of variation (RMS-CV%) was 3.9% for JSW, 7.4% for volume, 3.9% for mean signal intensity and 3.0% for homogeneity quantification. CONCLUSION: These data demonstrate that the distribution of components of the articular matrix precedes erosion, as measured by cartilage homogeneity related to water concentration. We show that homogeneity was able to separate early OA from healthy individuals in contrast to traditional volume and JSW quantifications. These data suggest that cartilage homogeneity quantification may be able to quantify early biochemical changes in articular cartilage prior to cartilage loss and thereby provide better identification of patients for OA trials who may respond better to medicinal intervention of some treatments. In addition, this study supports the feasibility of using low-field MRI in clinical studies.

A computer-based measure of irregularity in vertebral alignment is a BMD-independent predictor of fracture risk in postmenopausal women.

UNLABELLED: Prevalent fracture and BMD are core elements of fracture prediction. In this control study case, we demonstrate that a simple computer-based estimation of local irregularities in the alignment of the lumbar vertebrae independently contributes to the fracture risk, thus supplementing current diagnostic tools. INTRODUCTION: We tested the hypothesis that degree of lordosis and/or irregularity in the alignment of lumbar vertebrae could be contributors to the risk of fragility fractures. METHODS: This was a case-control analysis including 144 elderly women; 108 maintaining skeletal integrity, whereas 36 sustaining a lumbar vertebral fracture during a 7.5-year observation period. The two groups of women were carefully matched for age, BMI, spine BMD and numerous classic risk factors. Lateral X-rays of the lumbar spine were digitized and the four corner points of endplates on each vertebra from Th12 to L5 were annotated. The degree of lordosis and irregularity of vertebral alignment was assessed by image analysis software. RESULTS: Degree of lordosis was not predictive for fractures. In contrast, irregularity was significantly higher in those who later sustained a fracture (1.6 x 10(-2)vs. 2.0 x 10(-3) cm(-1), p < 0.001), and further increased upon a sustained fracture (2.8 x 10(-2) cm(-1), p < 0.001), but was unchanged in controls (1.6 x 10(-2) cm(-1)). The predictive value of irregularity was independent of classic risk factors of fractures, including BMD (p < 0.01). CONCLUSION: Our results suggest that the herein introduced simple measure of irregularities in vertebral alignment could provide useful supplement to the currently used diagnostic tools of fracture prediction in elderly women.

Automatic morphometric cartilage quantification in the medial tibial plateau from MRI for osteoarthritis grading.

OBJECTIVE: To evaluate whether a novel, fully automatic, morphometric cartilage quantification framework is suitable for assessing level of knee osteoarthritis (OA) in clinical trials. METHOD: The population was designed with a normal population and groups with varying degree of OA of both sexes and at ages from 21 to 78. Posterior-anterior X-rays were acquired in semi-flexed, load-bearing position. The radiographic signs of OA were evaluated based on the Kellgren and Lawrence score (KL) and the joint space width (JSW) was measured. Turbo 3D T1 magnetic resonance imaging (MRI) scans were acquired with resolution 0.7x0.7x0.8mm(3) from a 0.18T scanner. The morphometric cartilage quantification from MRI resulted in volume, surface area, thickness and surface curvature for the medial tibial cartilage compartment. These quantifications were evaluated against JSW with respect to precision and ability to separate healthy subjects from OA subjects. RESULTS: The automatic, morphometric cartilage quantifications allowed fairly precise measurements with scan-rescan coefficient of variations (CVs) in the range from 3.4% to 6.3%. All quantifications, including JSW, allowed separation of the groups of healthy and OA subjects. However, for separation of the healthy from the borderline cases (KL 0 vs KL 1), only the Cartilage Curvature quantification allowed statistically significant separation (P<0.01). CONCLUSION: The novel morphometric framework shows promise for use in clinical trials. The ability of the Cartilage Curvature quantification to detect the early stages of OA and the effectiveness of the focal thickness Q10 measure are particularly noteworthy. Furthermore, these results may indirectly support that low-field MRI may be a low-cost option for clinical trials.

Effects of thoracotomy on respiratory system, lung, and chest wall mechanics.

Nineteen rats were sedated, anesthetized, paralyzed, and mechanically ventilated. The respiratory, lung, and chest wall elastances (Est-rs, Est-L, Est-w); respiratory system, pulmonary, and chest wall total resistances (Rtot-rs, Rtot-L, Rtot-w); respiratory system, pulmonary, and chest wall initial resistances (Rinit-rs, Rinit-L, Rinit-w); and respiratory system, pulmonary, and chest wall difference resistances (Rdiff-rs, Rdiff-L, Rdiff-w) were determined before and after thoracotomy using the end-inflation occlusion method. Rinit reflects the Newtonian resistances and Rdiff represents the viscoelastic/inhomogeneous pressure dissipations in the system. Rtot = Rinit+Rdiff, ie, total resistance. The animals were submitted to either anterolateral thoracotomy (group A, n = 7), median sternotomy (group B, n = 6), or median sternotomy under PEEP while the lungs were exposed (group C, n = 6). In groups A and B, statistically significant increases in Rdiff-rs significantly augmented Rtot-rs. The former results were entirely secondary to significant increases in Rdiff-L, which naturally raised Rtot, L. Resistance was not altered in group C rats. Thus, anterolateral thoracotomy and median sternotomy increases Rtot-rs as a consequence of augmented Rdiff-L, but this finding could be prevented by the use of PEEP. Est-rs and Est-L increased in the three groups after surgery. Groups D and E were comprised of four animals each. Both underwent median sternotomy and in group E, PEEP was applied. Histopathologic examination of the lungs demonstrated a higher degree of lung collapse in group D.