E M Lochmüller

Paracelsus Medical University Salzburg, Salzburg, Salzburg, Austria

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Publications (41)90.18 Total impact

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    ABSTRACT: We investigate the use of different trabecular bone descriptors and advanced machine learning tech niques to complement standard bone mineral density (BMD) measures derived from dual-energy x-ray absorptiometry (DXA) for improving clinical assessment of osteoporotic fracture risk. For this purpose, volumes of interest were extracted from the head, neck, and trochanter of 146 ex vivo proximal femur specimens on multidetector computer tomography. The trabecular bone captured was characterized with (1) statistical moments of the BMD distribution, (2) geometrical features derived from the scaling index method (SIM), and (3) morphometric parameters, such as bone fraction, trabecular thickness, etc. Feature sets comprising DXA BMD and such supplemental features were used to predict the failure load (FL) of the specimens, previously determined through biomechanical testing, with multiregression and support vector regression. Prediction performance was measured by the root mean square error (RMSE); correlation with measured FL was evaluated using the coefficient of determination R (2). The best prediction performance was achieved by a combination of DXA BMD and SIM-derived geometric features derived from the femoral head (RMSE: 0.869 ± 0.121, R (2): 0.68 ± 0.079), which was significantly better than DXA BMD alone (RMSE: 0.948 ± 0.119, R (2): 0.61 ± 0.101) (p < 10(-4)). For multivariate feature sets, SVR outperformed multiregression (p < 0.05). These results suggest that supplementing standard DXA BMD measurements with sophisticated femoral trabecular bone characterization and supervised learning techniques can significantly improve biomechanical strength prediction in proximal femur specimens.
    Journal of Electronic Imaging 02/2014; 23(1):013013. DOI:10.1117/1.JEI.23.1.013013 · 0.85 Impact Factor
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    ABSTRACT: Estimating local trabecular bone quality for purposes of femoral bone strength prediction is important for improving the clinical assessment of osteoporotic hip fracture risk. In this study, we explore the ability of geometric features derived from the Scaling Index Method (SIM) in predicting the biomechanical strength of proximal femur specimens as visualized on multi-detector computed tomography (MDCT) images. MDCT scans were acquired for 50 proximal femur specimens harvested from human cadavers. An automated volume of interest (VOI)-fitting algorithm was used to define a consistent volume in the femoral head of each specimen. In these VOIs, the non-linear micro-structure of the trabecular bone was characterized by statistical moments of its BMD distribution and by local scaling properties derived from SIM. Linear multi-regression analysis and support vector regression with a linear kernel (SVRlin) were used to predict the failure load (FL) from the feature sets; the predicted FL was compared to the FL values determined through biomechanical testing. The prediction performance was measured by the root mean square error (RMSE) for each image feature on independent test set. The best prediction result was obtained from the SIM feature set with SVRlin, which had the lowest prediction error (RMSE = 0.842 ± 0.209) and which was significantly lower than the conventionally used mean BMD (RMSE = 1.103 ± 0.262, , p<0.005). Our results indicate that the biomechanical strength prediction can be significantly improved in proximal femur specimens on MDCT images by using high-dimensional geometric features derived from SIM with support vector regression.
    SPIE Medical Imaging; 03/2013
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    ABSTRACT: The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10-4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications.
    Proceedings of SPIE - The International Society for Optical Engineering 03/2013; DOI:10.1117/12.2007192 · 0.20 Impact Factor
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    ABSTRACT: To improve the clinical assessment of osteoporotic hip fracture risk, recent computer-aided diagnosis systems explore new approaches to estimate the local trabecular bone quality beyond bone density alone to predict femoral bone strength. In this context, statistical bone mineral density (BMD) features extracted from multi-detector computed tomography (MDCT) images of proximal femur specimens and different function approximations methods were compared in their ability to predict the biomechanical strength. MDCT scans were acquired in 146 proximal femur specimens harvested from human cadavers. The femurs' failure load (FL) was determined through biomechanical testing. An automated volume of interest (VOI)-fitting algorithm was used to define a consistent volume in the femoral head of each specimen. In these VOIs, the trabecular bone was represented by statistical moments of the BMD distribution and by pairwise spatial occurrence of BMD values using the gray-level co-occurrence (GLCM) approach. A linear multi-regression analysis (MultiReg) and a support vector regression algorithm with a linear kernel (SVRlin) were used to predict the FL from the image feature sets. The prediction performance was measured by the root mean square error (RMSE) for each image feature on independent test sets; in addition the coefficient of determination R2 was calculated. The best prediction result was obtained with a GLCM feature set using SVRlin, which had the lowest prediction error (RSME = 1.040+/-0.143, R2 = 0.544) and which was significantly lower that the standard approach of using BMD.mean and MultiReg (RSME = 1.093+/-0.133, R2 = 0.490, p<0.0001). The combined sets including BMD.mean and GLCM features had a similar or slightly lower performance than using only GLCM features. The results indicate that the performance of high-dimensional BMD features extracted from MDCT images in predicting the biomechanical strength of proximal femur specimens can be significantly improved by using support vector regression.
    Proceedings of SPIE - The International Society for Optical Engineering 02/2012; DOI:10.1117/12.911402 · 0.20 Impact Factor
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    ABSTRACT: The standard diagnostic technique for assessing osteoporosis is dual X-ray absorptiometry (DXA) measuring bone mass parameters. In this study, a combination of DXA and trabecular structure parameters (acquired by computed tomography [CT]) most accurately predicted the biomechanical strength of the proximal femur and allowed for a better prediction than DXA alone. An automated 3D segmentation algorithm was applied to determine specific structure parameters of the trabecular bone in CT images of the proximal femur. This was done to evaluate the ability of these parameters for predicting biomechanical femoral bone strength in comparison with bone mineral content (BMC) and bone mineral density (BMD) acquired by DXA as standard diagnostic technique. One hundred eighty-seven proximal femur specimens were harvested from formalin-fixed human cadavers. BMC and BMD were determined by DXA. Structure parameters of the trabecular bone (i.e., morphometry, fuzzy logic, Minkowski functionals, and the scaling index method [SIM]) were computed from CT images. Absolute femoral bone strength was assessed with a biomechanical side-impact test measuring failure load (FL). Adjusted FL parameters for appraisal of relative bone strength were calculated by dividing FL by influencing variables such as body height, weight, or femoral head diameter. The best single parameter predicting FL and adjusted FL parameters was apparent trabecular separation (morphometry) or DXA-derived BMC or BMD with correlations up to r = 0.802. In combination with DXA, structure parameters (most notably the SIM and morphometry) added in linear regression models significant information in predicting FL and all adjusted FL parameters (up to R(adj) = 0.872) and allowed for a significant better prediction than DXA alone. A combination of bone mass (DXA) and structure parameters of the trabecular bone (linear and nonlinear, global and local) most accurately predicted absolute and relative femoral bone strength.
    Osteoporosis International 10/2009; 21(9):1553-64. DOI:10.1007/s00198-009-1090-z · 4.17 Impact Factor
  • Journal of Clinical Densitometry 01/2009; 12(1):125-125. DOI:10.1016/j.jocd.2008.07.108 · 1.60 Impact Factor
  • Journal of Clinical Densitometry 01/2009; 12(1):112-113. DOI:10.1016/j.jocd.2008.07.045 · 1.60 Impact Factor
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    ABSTRACT: To prospectively evaluate an automated volume of interest (VOI)-fitting algorithm for quantitative computed tomography (CT) of proximal femur specimens, correlate bone mineral density (BMD) with biomechanically determined bone strength in vitro, and compare that correlation with those observed at dual-energy x-ray absorptiometry (DXA) measurement of BMD. The study was compliant with institutional and legislative requirements; donors had dedicated their body for education and research before death. Multidetector CT and DXA scans were acquired in 178 proximal femur specimens harvested from human cadavers (91 women, 87 men; mean age at death, 79 years +/- 10.2; range, 52-100 years). An automated VOI-fitting algorithm was used to calculate BMD and bone mineral content (BMC) in the head, neck, and trochanter from CT findings and pixel distribution parameters. The femur failure load (FL) was determined by using a mechanical test. Quantitative CT BMD, quantitative CT pixel distribution parameters, DXA BMD, and FL were correlated at multiple regression analysis. Mean precision errors in quantitative CT BMD measurements at segmentation with repositioning were 0.56%, 2.26%, and 0.61% for the head, neck, and trochanter, respectively. For the head, neck, and trochanter, respectively, r values were 0.77, 0.53, and 0.59 for the correlation between quantitative CT BMD and FL and 0.74, 0.55, and 0.65 for the correlation between quantitative CT BMC and FL (P < .001). Values ranged from 0.77 to 0.80 for correlations between DXA BMD and FL and from 0.73 to 0.82 for correlations between DXA BMC and FL (P < .001). In a multiple regression model that included quantitative CT pixel distributions, adjusted multivariate correlation coefficient values for correlations with FL increased to up to 0.88. Regional BMD of the proximal femur can be determined in vitro from quantitative CT data with high precision by using an automated VOI-fitting algorithm. The best multiple regression model for predicting FL included DXA BMD and regional quantitative CT BMD measurements.
    Radiology 05/2008; 247(2):472-81. DOI:10.1148/radiol.2472070982 · 6.21 Impact Factor
  • F. Eckstein, E.-M. Lochmüller, V. Kuhn, T. Jämsä
    Journal of Clinical Densitometry 04/2007; 10(2). DOI:10.1016/j.jocd.2007.03.011 · 1.60 Impact Factor
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    ABSTRACT: To investigate in vitro the calcaneal trabecular bone structure in elderly human donors with high spatial resolution magnetic resonance (MR) imaging at 3.0 T and 1.5 T, to quantitatively compare MR measures of bone microarchitecture with those from micro-computed tomography (CT), and to compare the performance of 3.0-T MR imaging with that of 1.5-T MR imaging in differentiating donors with spinal fractures from those without spinal fractures. The study was performed in line with institutional and legislative requirements; all donors had dedicated their body for educational and research purposes prior to death. Sagittal MR images of 49 human calcaneus cadaveric specimens were obtained (mean age of donors, 79.5 years +/- 11 [standard deviation]; 26 male donors, 23 female donors). After the spatial coregistering of images acquired at 3.0-T and 1.5-T MR imaging, the signal-to-noise-ratios and structural parameters obtained at each magnetic field strength were compared in corresponding sections. Micro-CT was performed on calcaneus cores obtained from corresponding regions in 40 cadaveric specimens. Vertebral deformities of the thoracic and lumbar spine were radiographically classified by using the spinal fracture index. Diagnostic performance of the structural parameters in differentiating donors with vertebral fractures from those without was assessed by using receiver operator characteristic (ROC) analysis, including area under the ROC curve (A(z)). Correlations between structural parameters at 3.0-T MR imaging and those at micro-CT were significantly higher (P < .05) than correlations between structural parameters at 1.5-T MR imaging and those at micro-CT (trabecular thickness, r = 0.76 at 3.0 T vs r = 0.57 at 1.5 T). Trabecular dimensions were amplified at 3.0 T because of increasing susceptibility artifacts. Also, higher ROC values were found for structural parameters at 3.0 T than at 1.5 T, but differences were not significant (trabecular thickness, A(z) = 0.75 at 3.0 T vs A(z) = 0.66 at 1.5 T, P > .05). MR imaging at 3.0 T provided a better measure of the trabecular bone structure than did MR imaging at 1.5 T. There was a trend for better differentiation of donors with from those without osteoporotic vertebral fractures at 3.0 T than at 1.5 T.
    Radiology 05/2006; 239(2):488-96. DOI:10.1148/radiol.2392050574 · 6.21 Impact Factor
  • RöFo - Fortschritte auf dem Gebiet der R 01/2006; 178. DOI:10.1055/s-2006-940663 · 1.96 Impact Factor
  • P. Pulkkinen, F. Eckstein, E.-M. Lochmüller, V. Kuhn, T. Jämsä
    Journal of Biomechanics 01/2006; 39. DOI:10.1016/S0021-9290(06)82887-3 · 2.50 Impact Factor
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    ABSTRACT: High-resolution magnetic resonance imaging (hrMRI) has recently made it possible to evaluate trabecular bone structure in vivo. Despite obvious gender differences in fracture incidence at the distal radius, little is known about gender differences in trabecular bone microarchitecture and its relationship to the structural strength of the forearm. The aim of this study was to determine trabecular bone structure in the distal radius of elderly women and men and its correlation with failure loads of the distal radius as determined in a fall configuration. Specifically, we tested the hypotheses that structural indices differ between women and men and that they offer information that is independent from BMD for predicting structural strength. Intact right arms were obtained from 73 formalin-fixed cadavers (age 80+/-11 years, 43 women, 30 men). Trabecular structural indices (apparent bone volume fraction [app. BV/TV], trabecular number [app. Tb.N], trabecular separation [app. Tb.Sp], trabecular thickness [app. Tb.Th] and fractal dimension [Frac.Dim]) were assessed in the distal metaphysis, using hrMRI with 156 microm in-plane resolution and proprietary digital image analysis, while BMD was measured with dual X-ray absorptiometry (DXA). Women displayed significantly lower BMD (-29.8%, p <0.001), app. BV/TV (-8.2%, p <0.05) and app. Tb.Th (-10.2%, p <0.001) than men, whereas app. Tb.N, app. Tb.Sp. and fractal dimension did not differ significantly. Structural parameters differed between normal and osteopenic women (BV/TV: -11%, p <0.01; Tb.Th: -8%, p <0.001) and between normal and osteoporotic women BV/TV: -21%, p <0.001; Tb.Th: -16%, p <0.001). App. BV/TV, app. Tb.Th and fractal dimension provided information independent from BMD in the prediction of radial failure loads in multiple regression models. These findings imply that it should be of clinical interest to monitor both bone mass and trabecular microstructure for predicting osteoporotic fracture risk.
    Osteoporosis International 09/2005; 16(9):1124-33. DOI:10.1007/s00198-004-1823-y · 4.17 Impact Factor
  • E M Lochmüller, K Friese
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    ABSTRACT: Today, mothers-to-be with an uncomplicated pregnancy are advised to practice sports on a regular basis. If they follow this advice, they put on less weight and recover more quickly from the stresses and strains of parturition, thanks to their higher level of general fitness. In addition, practicing sports helps to prevent postural damage, back pain, varices and thrombosis. The most suitable forms of sport are those of the aerobic type, such as jogging, swimming, cycling or aerobic calisthenics. However, exercises in the fitness studio and moderate strength training are also admissible provided that consideration is given to contraindications and warning signals.
    MMW Fortschritte der Medizin 05/2005; 147(16):28-9, 31.
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    ABSTRACT: The diagnosis of osteoporosis is generally based on the assessment of bone mineral content with dual X-ray absorptiometry (DXA) but does not account for the spatial distribution and inherent material properties of the tissue. Peripheral quantitative computed tomography (pQCT) permits one to measure the compartment-specific density and geometry-based parameters of cortical bone. Quantitative ultrasound (QUS) parameters are associated with material properties of cortical bone. The purpose of this study was to test the hypothesis that pQCT and cortical QUS provide additional information to DXA in predicting structural strength of the distal radius. The intact right arm and the isolated left radius were harvested from 70 formalin-fixed cadavers (age 79+/-11 years). The bone mineral content (BMC) was assessed with DXA at the radial metaphysis and shaft. pQCT was also used at the metaphysis and the shaft, while QUS was employed only at the shaft. The failure loads of the radius were assessed by use of a 3-point bending test (isolated radius) and a complex fall simulation (intact arm). The BMC (DXA) displayed a correlation of r=0.96 with the failure moments in 3-point bending ( P<0.001). The correlation between failure load and geometry-based parameters (pQCT) ranged from r=0.85 to r=0.96 and was r=0.64 for the speed of sound (QUS) ( P <0.001). Cortical thickness (pQCT) improved the prediction marginally (r=0.964) in combination with DXA. For the fall simulation, the correlation coefficients were r=0.76 for BMC (DXA) of the shaft, r=0.83 for metaphyseal bone content (pQCT), r=0.55 for QUS, and ranged from r=0.59 to r=0.74 for geometry-based parameters at the shaft (pQCT). pQCT and QUS parameters provided no significant improvement versus DXA alone. Measurement of bone mass by DXA or pQCT thus appears to be sufficient as a surrogate of mechanical strength and fracture risk of the distal radius.
    Osteoporosis International 06/2004; 15(5):375-81. DOI:10.1007/s00198-003-1551-8 · 4.17 Impact Factor
  • B Gerber, A Krause, E.-M Lochmüller, W Janni, K Friese
    Zentralblatt für Gynäkologie 06/2004; 126(3):167-169. DOI:10.1055/s-2004-822695
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    E.-M. Lochmüller, K. Friese
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    ABSTRACT: Der vorliegende bersichtsartikel beschreibt den aktuellen Stand des Themas Schwangerschaft und Sport und gibt konkrete Empfehlungen, welche Sportarten in der Schwangerschaft in welchem Umfang betrieben werden knnen. Zunchst werden relevante muskuloskelettale, kardiorespiratorische, thermoregulatorische und endokrine Vernderungen whrend der Schwangerschaft beschrieben. In den folgenden Abschnitten werden die Auswirkungen von sportlicher Aktivitt whrend der Schwangerschaft auf den mtterlichen Organismus und den Organismus des Ungeborenen diskutiert. Den Themen Leistungssport und Krperliche Aktivitt im Wasser sind eigene Abschnitte gewidmet. Der Artikel schliet mit Empfehlungen zu spezifischen Sportarten, dem Ausdauer- und Krafttraining in der Schwangerschaft. Kontraindikationen und Warnsignale whrend physischer Aktivitt werden beschrieben. Bei unaufflligem Schwangerschaftsverlauf berwiegen die Vorteile sportlicher Aktivitt klar die potenziellen Risiken. Sogar bislang krperlich inaktiven Schwangeren ist daher der Beginn von leichter sportlicher Aktivitt im 2. Trimenon zu empfehlen.This review article summarizes work on physical exercise and sports in pregnancy and gives specific recommendations, which types of sports can be performed to what extent during pregnancy. First we summarize relevant musculoskeletal, cardiorespiratory, theromoregulatory and endocrine changes during pregnancy. Subsequent parts of the article describe the effect of physical activity on the maternal and fetal organism. Distinct paragraphs discuss athletics and physical activity in water. The article gives recommendations with regard to specific types of sport, endurance training, and weight training during pregnancy. Contraindications and warning signals during physical activity are described. During uncomplicated pregnancy advantages of sportive activity clearly exceed potential risks. Therefore, previously inactive pregnant women are recommended to take up mild physical exercise during the 2nd trimenon.
    Der Gynäkologe 04/2004; 37(5):459-466. DOI:10.1007/s00129-004-1519-6
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    ABSTRACT: Osteoporotic vertebral fractures typically have a gradual onset, frequently remain clinically undetected, and do not seem to be related to traumatic events. The osteoporotic vertebrae may therefore be expected to display a less "optimal" bone architecture, leading to an uneven load distribution over the bone material. We evaluated the trabecular load distribution in an osteoporotic and a healthy vertebra under normal daily loading by combining three recent innovations: high resolution computed tomography (microCT) of entire bones, microfinite element analyses (microFEA), and parallel supercomputers. Much to our surprise, the number of highly loaded trabeculae was not higher in the osteoporotic vertebra than in the healthy one under normal daily loads (8% and 9%, respectively). The osteoporotic trabeculae were more oriented in the longitudinal direction, compensating for effects of bone loss and ensuring adequate stiffness for normal daily loading. The increased orientation did, however, make the osteoporotic structure less resistant against collateral "error" loads. In this case, the number of overloaded trabeculae in the osteoporotic vertebra was higher than in the healthy one (13% and 4%, respectively). These results strengthen the paradigm of a strong relationship between bone morphology and external loads applied during normal daily life. They also indicate that vertebral fractures result from actions like forward flexion or lifting, loads that may not be "daily" but are normally not traumatic either. If future clinical imaging techniques would enable such high-resolution images to be obtained in vivo, the combination of microCT and microFEA would produce a powerful tool to diagnose osteoporosis.
    Bone 04/2004; 34(3):510-6. DOI:10.1016/j.bone.2003.12.001 · 4.46 Impact Factor
  • EM Lochmüller, M Priemel, V Kuhn, F Eckstein, K Friese
    Geburtshilfe und Frauenheilkunde 12/2003; 63(12). DOI:10.1055/s-2003-815265 · 0.96 Impact Factor
  • E.-M. Lochmüller, F. Eckstein
    Osteologie/Osteology 01/2002; 11(03):154-177. DOI:10.1024/1019-1291.11.3.154 · 0.42 Impact Factor

Publication Stats

796 Citations
90.18 Total Impact Points


  • 2009–2014
    • Paracelsus Medical University Salzburg
      • Institute of Anatomy und Musculoskeletal Research
      Salzburg, Salzburg, Austria
  • 2008
    • Technische Universität München
      München, Bavaria, Germany
  • 1997–2005
    • Ludwig-Maximilians-University of Munich
      • • Institute of Veterinary Anatomy
      • • Institute for Anatomy and Cell Biology
      München, Bavaria, Germany
  • 2001
    • Universität Bern
      Berna, Bern, Switzerland