T1ρ and T2 of articular cartilage after acl injury predict patient-reported outcomes at 3 years after acl reconstruction

Abstract

Purpose: Osteoarthritis (OA) is one of the leading causes of long-term pain and disabilities associated with musculoskeletal disorders. Effective treatment and disease-progression slowdown depend on early detection and quantification of risk. However, current disease parameters, like joint space width (JSW), have proven to be insufficient for the prediction of OA. The purpose of the present study was to investigate if combining fractal-and entropy-based bone texture analyses with joint space width (JSW) and joint space area (JSA) may improve prediction of OA. Methods: Conventional posterior-anterior (PA) knee radiographs of men and women were obtained from the Multicenter Osteoarthritis Study (MOST) database. Oriented fractal-and entropy based texture algorithms were developed, using state-of-the-art computer hardware and software as well as specific machinelearning algorithms. The selected subchondral area used for textural analyses included 4 regions of interest (ROI) in the proximal tibia and one on each condyle of the distal femur (Fig. 1). Furthermore, JSW and JSA were assessed using newly developed and fully automated software. Results: 1092 conventional knee radiographs obtained from one study center were screened for eligibility. Of these, a total of 574 radiographs (230 women, 344 men) met the inclusion criteria, i.e. a Kellgren & Lawrence (KL) score of 0 at baseline. At month 84, 41 female and 79 male patients had developed KL!1, and 189 female and 265 male patients remained at KL0. Area-Under-the-Curve (AUC) for incident OA using JSW/JSA and clinical features was 0.67±0.08 for women, and 0.61±0.1 for men. In contrast, combining fractal/entropybased texture, JSW/A and clinical features resulted in significantly improved AUC for women and men (0.80±0.07 for women and 0.69±0.1 for men, respectively). To test whether these differences in predicting incident-OA were significant, we performed classifier comparison: t ¼ 3.84; p < 10-3 for women, and t ¼ 3.38; p < 10-3 for men. Conclusions: This study provides strong evidence, that a combination of fractal-and entropy-based textural analyses of plain subchondral bone radiographs together with JSW/A and clinical features is superior to JSW/A and clinical features alone in predicting incident OA in men and women.

Knee MRI biomarkers associated with structural, functional and symptomatic changes at least a year from ACL injury - A systematic review

“…All full-text manuscripts were retrieved and screened, with 11 studies meeting the inclusion criteria [21][22][23][24][25][26][27][28][29][30][31]. Twenty conference abstracts also met the criteria and, as per Cochrane recommendations [32,33], can be found in Supplementary File 3 [34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53]. Excluded studies can be found in Supplementary File 4, with the two most common reasons for exclusion being participant age outside the specified range and time to follow-up within a year from injury.…”

Whole knee joint mapping using a phase modulated UTE adiabatic T1ρ (PM‐UTE‐AdiabT1ρ) sequence

“…The 3D MAPSS CW-T 1ρ sequence has been widely used to evaluate tissue degeneration and monitor compositional changes longitudinally in the MSK system. [31][32][33][34][35][36] Some of the sequence features in 3D MAPSS, such…”

“…The 3D MAPSS CW‐T 1ρ sequence has been widely used to evaluate tissue degeneration and monitor compositional changes longitudinally in the MSK system 31–36 . Some of the sequence features in 3D MAPSS, such as magnetization reset, phase modulation, and VFA scheme, 23 have been successfully incorporated in the PM‐UTE‐AdiabT 1ρ sequence.…”