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Christoph A. Lill

Researcher at Heidelberg University

Publications -  11
Citations -  1256

Christoph A. Lill is an academic researcher from Heidelberg University. The author has contributed to research in topics: Quantitative computed tomography & Osteoporosis. The author has an hindex of 11, co-authored 11 publications receiving 1167 citations.

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Estimation of distal radius failure load with micro-finite element analysis models based on three-dimensional peripheral quantitative computed tomography images.

TL;DR: It is concluded that application of the techniques investigated here can lead to a better prediction of the bone failure load for bone in vivo than is possible from DXA measurements, structural parameters, or a combination thereof.
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Radius Bone Strength in Bending, Compression, and Falling and Its Correlation With Clinical Densitometry at Multiple Sites

TL;DR: It is concluded that the noninvasive diagnosis of loss of strength at the distal radius should rely on site‐specific measurements with DXA or pQCT and may be the earliest chance to detect individuals at risk of osteoporotic fracture.
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Bone Strength at Clinically Relevant Sites Displays Substantial Heterogeneity and Is Best Predicted From Site‐Specific Bone Densitometry

TL;DR: The data suggest that mechanical competence in the elderly is governed by strong regional variation, and that its loss in osteoporosis may not represent a strictly systemic process.
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Can novel clinical densitometric techniques replace or improve DXA in predicting bone strength in osteoporosis at the hip and other skeletal sites

TL;DR: Testing the hypothesis that peripheral quantitative computed tomography at the distal radius and/or quantitative ultrasound at the calcaneus can serve as replacement or improvement of current methodology for predicting bone strength at the hip and other sites suggests that clinical assessment of femoral fracture risk should preferably rely on femoral DXA.
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Image-based micro-finite-element modeling for improved distal radius strength diagnosis: moving from bench to bedside.

TL;DR: In this article, a 3D micro-finite element (micro-FE) model based on high-resolution images was used to predict the distal radius strength of 54 cadaver arms.