Quantitative Three-dimensional Assessment of Knee Joint Space Width from Weight-bearing CT.
Quantitative Three-dimensional Assessment of Knee Joint Space Width from Weight-bearing CT.
复制标题
基于负重CT的膝关节间隙宽度的定量三维评估
作者:
Imaging of structural disease in osteoarthritis has traditionally relied on MRI and radiography. Joint space mapping (JSM) can quantitatively map joint space width (JSW) in three dimensions (3-D) from CT To demonstrate reproducibility, repeatability, and feasibility of JSM at the knee using weight-bearing CT. Two convenience samples of weight-bearing CT of both knees acquired from 2014 to 2018 and radiographic Kellgren and Lawrence grade (KLG) ≤2 were analyzed retrospectively with JSM to deliver 3-D JSW maps. For reproducibility, three sets of knees were used for novice training, then JSM output was compared against an expert. JSM was also performed on 2-week follow-up imaging in the second cohort yielding 3-D JSW difference maps for repeatability. Statistical parametric mapping was performed on all knees (KLG=0-4) to show feasibility of surface-based analysis in 3-D. Reproducibility (20 individuals, 58±7 years, body mass index 28±6 kg/m2, 14 women) and repeatability (9 individuals, 53±6 years, 26±4 kg/m2, 7 women) reached best performance of less than ±0.1mm in the central medial tibiofemoral joint space for individuals without radiographic disease. Average root mean square coefficient of variation values were <5% across all groups. Statistical parametric mapping (33 individuals, 57±7 years, 27±6 kg/m2, 23 women) showed that the central-to-posterior medial joint space was significantly narrower by 0.5 mm for each increment in KLG (threshold p<.05). A single knee (KLG=2) demonstrated baseline versus 24-month change in 3-D JSW distribution beyond smallest detectable difference across the lateral joint space. Joint space mapping is feasible at the knee with weight-bearing CT, demonstrating a relationship between three-dimensional joint space width distribution and structural joint disease. It is reliably learned by novice users, can be personalized to disease phenotypes, and can achieve a smallest detectable difference at least 50% better than the reported best performance of radiography. Joint space mapping of weight-bearing knee CT can deliver personalized quantitative measurements of joint space width in three dimensions that are structurally relevant in osteoarthritis, learnable by novice users, and highly repeatable.
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影响因子:
7
作者:
Ornetti P;Brandt K;Hellio-Le Graverand MP;Hochberg M;Hunter DJ;Kloppenburg M;Lane N;Maillefert JF;Mazzuca SA;Spector T;Utard-Wlerick G;Vignon E;Dougados M
通讯作者:
Dougados M
影响因子:
2.3
作者:
Raunig DL;McShane LM;Pennello G;Gatsonis C;Carson PL;Voyvodic JT;Wahl RL;Kurland BF;Schwarz AJ;Gönen M;Zahlmann G;Kondratovich MV;O'Donnell K;Petrick N;Cole PE;Garra B;Sullivan DC;QIBA Technical Performance Working Group
通讯作者:
QIBA Technical Performance Working Group
影响因子:
4
作者:
Bousson, V.;Lowitz, T.;Laredo, J. -D.
通讯作者:
Laredo, J. -D.
影响因子:
7
作者:
Altman, R. D.;Gold, G. E.
通讯作者:
Gold, G. E.
影响因子:
2.1
作者:
Segal, Neil A.;Bergin, John;Anderson, Donald D.
通讯作者:
Anderson, Donald D.