Between-scanner differences in measures of bone and body composition can obscure or exaggerate physiological differences in multi-site studies or the magnitude of changes in longitudinal studies. We conducted a cross-calibration study at two bone imaging centres in The Gambia, West Africa where DXA (dual-energy X-ray absorptiometry) and pQCT (peripheral Quantitative-Computed Tomography) are routinely used. Repeat scans were obtained from 64 Gambian adults (58% Male) aged Mean(SD) 30.9 (13.5) years with Mean(SD) body mass index (BMI) 21.7 (4.0) kg\/m(2), using DXA (GE Lunar iDXA, whole body [WB], total hip [TH], lumbar spine [LS]) and pQCT (Stratec XCT2000L\/XCT2000, tibia 4%, 50% sites). Between-scanner differences were tested using paired t tests (p < 0.05). Between-scanner correlation was explored with linear regression, and cross-calibration equations derived. Bland-Altman analysis investigated machine trend\/bias. When differences were detected (p < 0.05), cross-calibration equations were applied to urban values, with t tests and Bland Altman analysis repeated. Between-scanner differences exceeded the predefined level of statistical significance (p < 0.05) for WB aBMD and BA; all pQCT measures vBMD, BMC, cortical cross-sectional area (CSA) and stress-strain index (SSI). Between-scanner correlation was high (R(2):0.92-0.99), except pQCT Mu.Den (R(2) = 0.51). Bland Altman plots indicated bias increased with increasing BMD. Cross-calibration equations attenuated all between-scanner differences and systematic bias. Cross-calibration, particularly of pQCT scanners, is an important consideration in multi-site studies particularly where between population comparisons are intended. Our experiences and findings may be generalisable to other resource-limited settings where the logistics of sourcing parts and in-country repair may result in lengthy scanner downtime.\n<\/p>\n","protected":false},"excerpt":{"rendered":"
Between-scanner differences in measures of bone and body composition can obscure or exaggerate physiological differences in multi-site studies or the<\/p>\n","protected":false},"author":22,"parent":0,"menu_order":0,"template":"","format":"standard","meta":{"_acf_changed":false},"tags":[],"thema":[5924,5866],"produktgruppe":[5825],"literatur_kategorie":[7221],"class_list":["post-166628","literatur","type-literatur","status-publish","format-standard","hentry","thema-clinical-studies","thema-diagnostics-using-leonardo-pqct","produktgruppe-pqct-en","literatur_kategorie-clinical-studies"],"acf":[],"_links":{"self":[{"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/literatur\/166628","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/literatur"}],"about":[{"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/types\/literatur"}],"author":[{"embeddable":true,"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/users\/22"}],"version-history":[{"count":0,"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/literatur\/166628\/revisions"}],"wp:attachment":[{"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/media?parent=166628"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/tags?post=166628"},{"taxonomy":"thema","embeddable":true,"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/thema?post=166628"},{"taxonomy":"produktgruppe","embeddable":true,"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/produktgruppe?post=166628"},{"taxonomy":"literatur_kategorie","embeddable":true,"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/literatur_kategorie?post=166628"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}