title: Fracture discrimination by combined bone mineral density (BMD) and microarchitectural texture analysis.
abstract: The use of bone mineral density (BMD) for fracture discrimination may be improved by considering bone microarchitecture. Texture parameters such as trabecular bone score (TBS) or mean Hurst parameter (H) could help to find women who are at high risk of fracture in the non-osteoporotic group. The purpose of this study was to combine BMD and microarchitectural texture parameters (spine TBS and calcaneus H) for the detection of osteoporotic fractures. Two hundred and fifty five women had a lumbar spine (LS), total hip (TH), and femoral neck (FN) DXA. Additionally, texture analyses were performed with TBS on spine DXA and with H on calcaneus radiographs. Seventy-nine women had prevalent fragility fractures. The association with fracture was evaluated by multivariate logistic regressions. The diagnostic value of each parameter alone and together was evaluated by odds ratios (OR). The area under curve (AUC) of the receiver operating characteristics (ROC) were assessed in models including BMD, H, and TBS. Women were also classified above and under the lowest tertile of H or TBS according to their BMD status. Women with prevalent fracture were older and had lower TBS, H, LS-BMD, and TH-BMD than women without fracture. Age-adjusted ORs were 1.66, 1.70, and 1.93 for LS, FN, and TH-BMD, respectively. Both TBS and H remained significantly associated with fracture after adjustment for age and TH-BMD: OR 2.07 [1.43; 3.05] and 1.47 [1.04; 2.11], respectively. The addition of texture parameters in the multivariate models didn't show a significant improvement of the ROC-AUC. However, women with normal or osteopenic BMD in the lowest range of TBS or H had significantly more fractures than women above the TBS or the H threshold. We have shown the potential interest of texture parameters such as TBS and H in addition to BMD to discriminate patients with or without osteoporotic fractures. However, their clinical added values should be evaluated relative to other risk factors.
authors.affiliation: I3MTO, EA4708, Université d'Orléans, 1, Rue Porte-Madeleine, Orléans, BP 2439, 45032 Cedex 1, France, jerome.touvier@laposte.net.
authors.forename: J
authors.initials: J
authors.lastname: Touvier
authors.forename: R
authors.initials: R
authors.lastname: Winzenrieth
authors.forename: H
authors.initials: H
authors.lastname: Johansson
authors.forename: J P
authors.initials: JP
authors.lastname: Roux
authors.forename: J
authors.initials: J
authors.lastname: Chaintreuil
authors.forename: H
authors.initials: H
authors.lastname: Toumi
authors.forename: R
authors.initials: R
authors.lastname: Jennane
authors.forename: D
authors.initials: D
authors.lastname: Hans
authors.forename: E
authors.initials: E
authors.lastname: Lespessailles
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D015519:Bone Density; D002111:Calcaneus / Q000000981:diagnostic imaging; D016022:Case-Control Studies; D005260:Female; D005602:France; D006801:Humans; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D015663:Osteoporosis, Postmenopausal / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000503:physiopathology; D058866:Osteoporotic Fractures / Q000517:prevention & control; D011859:Radiography; D012189:Retrospective Studies