scholarly journals Computed Tomography-Based Structural Analysis for Predicting Fracture Risk in Children with Benign Skeletal Neoplasms

2010 ◽  
Vol 92 (9) ◽  
pp. 1827-1833 ◽  
Author(s):  
Natalie L Leong ◽  
Megan E Anderson ◽  
Mark C Gebhardt ◽  
Brian D Snyder
Keyword(s):  
Computed Tomography ◽  
Structural Analysis ◽  
Fracture Risk ◽  
Skeletal Neoplasms

Quantitative computed tomography for prediction of vertebral fracture risk

Bone ◽  
1985 ◽  
Vol 6 (1) ◽  
pp. 1-7 ◽  
Author(s):  
C.E. Cann ◽  
H.K. Genant ◽  
F.O. Kolb ◽  
B. Ettinger
Keyword(s):  
Computed Tomography ◽  
Vertebral Fracture ◽  
Fracture Risk ◽  
Quantitative Computed Tomography ◽  
Vertebral Fracture Risk

Radiology of Osteoporosis

2016 ◽  
Vol 67 (1) ◽  
pp. 28-40 ◽  
Author(s):  
Thomas M. Link
Keyword(s):  
Computed Tomography ◽  
Fracture Risk ◽  
New Technologies ◽  
Assessment Tool ◽  
Quantitative Computed Tomography ◽  
Osteoporotic Fractures ◽  
Fragility Fractures ◽  
Bone Architecture ◽  
Mineral Density ◽  
Fracture Risk Assessment Tool

The radiologist has a number of roles not only in diagnosing but also in treating osteoporosis. Radiologists diagnose fragility fractures with all imaging modalities, which includes magnetic resonance imaging (MRI) demonstrating radiologically occult insufficiency fractures, but also lateral chest radiographs showing asymptomatic vertebral fractures. In particular MRI fragility fractures may have a nonspecific appearance and the radiologists needs to be familiar with the typical locations and findings, to differentiate these fractures from neoplastic lesions. It should be noted that radiologists do not simply need to diagnose fractures related to osteoporosis but also to diagnose those fractures which are complications of osteoporosis related pharmacotherapy. In addition to using standard radiological techniques radiologists also use dual-energy x-ray absorptiometry (DXA) and quantitative computed tomography (QCT) to quantitatively assess bone mineral density for diagnosing osteoporosis or osteopenia as well as to monitor therapy. DXA measurements of the femoral neck are also used to calculate osteoporotic fracture risk based on the Fracture Risk Assessment Tool (FRAX) score, which is universally available. Some of the new technologies such as high-resolution peripheral computed tomography (HR-pQCT) and MR spectroscopy allow assessment of bone architecture and bone marrow composition to characterize fracture risk. Finally radiologists are also involved in the therapy of osteoporotic fractures by using vertebroplasty, kyphoplasty, and sacroplasty. This review article will focus on standard techniques and new concepts in diagnosing and managing osteoporosis.

Quantitative structural analysis of trabecular alveolar bone in the mandible by multidetector computed tomography: Differences according to tooth presence and type

2019 ◽  
Vol 61 (3) ◽  
pp. 225-233
Author(s):  
R. Sanz-Requena ◽  
A. Ten Esteve ◽  
V. Hervás Briz ◽  
G. García-Martí ◽  
M. Beltrán ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Structural Analysis ◽  
Multidetector Computed Tomography ◽  
Alveolar Bone

scholarly journals Association of 3D Geometric Measures Derived From Quantitative Computed Tomography With Hip Fracture Risk in Older Men

2016 ◽  
Vol 31 (8) ◽  
pp. 1550-1558 ◽  
Author(s):  
Jan Borggrefe ◽  
Timm de Buhr ◽  
Smriti Shrestha ◽  
Lynn M Marshall ◽  
Eric Orwoll ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Hip Fracture ◽  
Fracture Risk ◽  
Quantitative Computed Tomography ◽  
Older Men ◽  
Hip Fracture Risk

scholarly journals Bone Mineral Density of the Tarsals and Metatarsals With Reloading

2008 ◽  
Vol 88 (6) ◽  
pp. 766-779 ◽  
Author(s):  
Mary Kent Hastings ◽  
Judy Gelber ◽  
Paul K Commean ◽  
Fred Prior ◽  
David R Sinacore
Keyword(s):  
Computed Tomography ◽  
Bone Mineral Density ◽  
Case Report ◽  
Fracture Risk ◽  
Bone Mineral ◽  
Weight Bearing ◽  
Quantitative Computed Tomography ◽  
Case Description ◽  
Mineral Density ◽  
Lateral Column

Background and PurposeBone mineral density (BMD) decreases rapidly with prolonged non–weight bearing. Maximizing the BMD response to reloading activities after NWB is critical to minimizing fracture risk. Methods for measuring individual tarsal and metatarsal BMD have not been available. This case report describes tarsal and metatarsal BMD with a reloading program, as revealed by quantitative computed tomography (QCT).Case DescriptionA 24-year-old woman was non–weight bearing for 6 weeks after right talocrural arthroscopy. Tarsal and metatarsal BMD were measured with QCT 9 weeks (before reloading) and 32 weeks (after reloading) after surgery. A 26-week progressive reloading program was completed. Change scores were calculated for BMD before reloading and BMD after reloading for the total foot (average of all tarsals and metatarsals), tarsals, metatarsals, bones of the medial column (calcaneus, navicular, cuneiforms 1 and 2, and metatarsal 1), and bones of the lateral column (calcaneus, cuboid, cuneiform 3, and metatarsals 2–5). The percent differences in BMD between the involved side and the uninvolved side were calculated.OutcomesBefore reloading, BMD of the involved total foot was 9% lower than that on the uninvolved side. After reloading, BMD increased 22% and 21% for the total foot, 16% and 14% for the tarsals, 29% and 30% for the metatarsals, 14% and 15% for the medial column bones, and 28% and 26% for the lateral column bones on the involved and uninvolved sides, respectively. After reloading, BMD of the involved total foot remained 8% lower than that on the uninvolved side.DiscussionThe increase in BMD with reloading was not uniform across all pedal bones; the metatarsals showed a greater increase than the tarsals, and the lateral column bones showed a greater increase than the medial column bones.

Osteoporotic Hip Fracture Prediction: Is T-Score-Based Criterion Enough? A Hip Structural Analysis-Based Model

2018 ◽  
Vol 140 (11) ◽  
Author(s):  
Alessandra Aldieri ◽  
Mara Terzini ◽  
Giangiacomo Osella ◽  
Adriano M. Priola ◽  
Alberto Angeli ◽  
...  
Keyword(s):  
Hip Fracture ◽  
Structural Analysis ◽  
Fracture Risk ◽  
Proximal Femur ◽  
Patient Specific ◽  
Multivariate Linear Regression Analysis ◽  
Hip Structural Analysis ◽  
Mineral Density ◽  
Neck Shaft Angle ◽  
Adopted Model

At present, the current gold-standard for osteoporosis diagnosis is based on bone mineral density (BMD) measurement, which, however, has been demonstrated to poorly estimate fracture risk. Further parameters in the hands of the clinicians are represented by the hip structural analysis (HSA) variables, which include geometric information of the proximal femur cross section. The purpose of this study was to investigate the suitability of HSA parameters as additional hip fracture risk predictors. With this aim, twenty-eight three-dimensional patient-specific models of the proximal femur were built from computed tomography (CT) images and a sideways fall condition was reproduced by finite element (FE) analyses. A tensile or compressive predominance based on minimum and maximum principal strains was determined at each volume element and a risk factor (RF) was calculated. The power of HSA variables combinations to predict the maximum superficial RF values was assessed by multivariate linear regression analysis. The optimal regression model, identified through the Akaike information criterion (AIC), only comprises two variables: the buckling ratio (BR) and the neck-shaft angle (NSA). In order to validate the study, the model was tested on two additional patients who suffered a hip fracture after a fall. The results classified the patients in the high risk level, confirming the prediction power of the adopted model.

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