An Exploratory Study of the Texture Research Investigational Platform (TRIP) to Evaluate Bone Texture Score of Distal Femur DXA Scans – A TBS-Based Approach

Abstract

Poor bone status is associated with increased complications following orthopedic surgery. Therefore, assessing site-specific skeletal status prior to or after orthopedic surgery to optimize outcomes is appealing. The trabecular bone score (TBS) approach, a surrogate for microarchitecture, was adapted to the Texture Research Investigational Platform (TRIP), which allows assessment of many skeletal sites imaged by various modalities. TRIP generates a bone texture score (TBS ORTHO), which could potentially guide surgical decision-making and offer insight into postsurgical fracture risk. As distal femur bone loss occurs following total knee arthroplasty (TKA), we hypothesized that TBS ORTHO after TKA would identify poorer texture in the operated femur compared to the nonoperated. We evaluated 30 subjects (15 M/15 F) with unilateral TKA 2–5 yr previously, mean age 67.9 yr and body mass index 30 kg/m2. Using a Lunar iDXA, lumbar spine and entire femur scans were obtained, the latter using the atypical femur fracture feature. Distal femur bone mineral density (BMD) and TBS ORTHO were obtained using manual regions of interest (ROI) at 15% and 25% of leg length from the intercondylar notch. TBS ORTHO was determined using distal femur DICOM images and TRIP v1.0 (Medimaps, France). Differences in operated vs nonoperated femur were evaluated by paired t test. As previously reported, operated leg BMD was approx 10% lower at 15% and 25% ROIs. Similarly, TBS ORTHO values in the operated leg were approx 5% lower (p < 0.05) at these same ROIs. Distal femur TBS ORTHO and BMD were largely unrelated. TBS ORTHO reproducibility at these ROIs was approx 3.5%. In conclusion, this pilot study documents the feasibility of reproducibly obtaining distal femur TBS ORTHO values. Lower values were observed in the surgical leg, consistent with the bone loss that follows TKA. Further work is indicated to refine TRIP use and evaluate whether such data provides guidance for surgical decision-making and improves periprosthetic fracture prediction.