Follow-up study evaluating the long term outcome of chondromimetic in the treatment of osteochondral defects in the knee

© 2020 by the authors. Scaffolds are thought to be a key element needed for successful cartilage repair treatments, and this prospective extension study aimed to evaluate long-term structural and clinical outcomes following osteochondral defect treatment with a cell-free biphasic scaffold. Structural outcomes were assessed using quantitative 3-D magnetic resonance imaging (MRI) and morphological segmentation to determine the percentage of defect filling and repair cartilage T2 relaxation times, and clinical outcomes were determined with the modified Cincinnati Rating System, and the Knee Injury and Osteoarthritis Outcome Score (KOOS). Seventeen subjects with osteochondral defects in the knee were treated with ChondroMimetic scaffolds, from which 15 returned for long-term evaluation at a mean follow-up of 7.9 - 0.3 years. The defects treated were trochlear donor sites for mosaicplasty in 13 subjects, and medial femoral condyle defects in 2 subjects. MRI analysis of scaffold-treated defects found a mean total defect filling of 95.2 - 3.6%, and a tissue mean T2 relaxation time of 52.5 - 4.8 ms, which was identical to the T2 of ipsilateral control cartilage (52.3 - 9.2 ms). The overall modified Cincinnati Rating System score was statistically significant from baseline (p = 0.0065), and KOOS subscales were equivalent to other cartilage repair techniques. ChondroMimetic treatment resulted in a consistently high degree of osteochondral defect filling with durable, cartilage-like repair tissue at 7.9 years, potentially associated with clinical improvement

Clinical performance of a multiparametric MRI-based post concussive syndrome index

IntroductionDiffusion Tensor Imaging (DTI) has revealed measurable changes in the brains of patients with persistent post-concussive syndrome (PCS). Because of inconsistent results in univariate DTI metrics among patients with mild traumatic brain injury (mTBI), there is currently no single objective and reliable MRI index for clinical decision-making in patients with PCS.PurposeThis study aimed to evaluate the performance of a newly developed PCS Index (PCSI) derived from machine learning of multiparametric magnetic resonance imaging (MRI) data to classify and differentiate subjects with mTBI and PCS history from those without a history of mTBI.Materials and methodsData were retrospectively extracted from 139 patients aged between 18 and 60 years with PCS who underwent MRI examinations at 2 weeks to 1-year post-mTBI, as well as from 336 subjects without a history of head trauma. The performance of the PCS Index was assessed by comparing 69 patients with a clinical diagnosis of PCS with 264 control subjects. The PCSI values for patients with PCS were compared based on the mechanism of injury, time interval from injury to MRI examination, sex, history of prior concussion, loss of consciousness, and reported symptoms.ResultsInjured patients had a mean PCSI value of 0.57, compared to the control group, which had a mean PCSI value of 0.12 (p = 8.42e-23) with accuracy of 88%, sensitivity of 64%, and specificity of 95%, respectively. No statistically significant differences were found in the PCSI values when comparing the mechanism of injury, sex, or loss of consciousness.ConclusionThe PCSI for individuals aged between 18 and 60 years was able to accurately identify patients with post-concussive injuries from 2 weeks to 1-year post-mTBI and differentiate them from the controls. The results of this study suggest that multiparametric MRI-based PCSI has great potential as an objective clinical tool to support the diagnosis, treatment, and follow-up care of patients with post-concussive syndrome. Further research is required to investigate the replicability of this method using other types of clinical MRI scanners

Abstract

A novel method for the automated three-dimensional extraction and measurement of soft tissue lesions in CT imagery is presented. Extraction is carried out using a hybrid algorithm that incorporates elements from both competitive region growth and deformable template techniques. This algorithm is tested against manual tracing and shown to provide significantly improved performance using three performance metrics: speed, precision, and accuracy. 1

Increased investment in research could potentially save South Africa’s wheat sector

Wandile Sihlobo argues that import tariffs in South Africa’s wheat sector will not save the industry, the focus must be placed on breeding new wheat cultivars which will give higher yields

Minimum joint space width (mJSW) of patellofemoral joint on standing “skyline” radiographs: test-retest reproducibility and comparison with quantitative magnetic resonance imaging (qMRI)

info:eu-repo/semantics/publishe

The use of sequential MR image sets for determining tibiofemoral motion: Reliability of coordinate systems and accuracy of motion tracking algorithm

The use of magnetic resonance imaging has been proposed by many investigators for establishment of joint reference systems and kinematic tracking of musculoskeletal joints. In this study, the intraobserver and interobserver reliability of a strategy to establish anatomic reference systems using manually selected fiducial points were quantified for seven sets of MR images of the human knee joint. The standard error of the measurement of the intraobserver and interobserver errors were less than 2.6%, and 1.2 mm for relative tibiofemoral orientation and displacement, respectively. An automated motion tracking algorithm was also validated with a controlled motion experiment in a cadaveric knee joint. The controlled displacements and rotations prescribed in our motion tracking validation were highly correlated to those predicted (Pearson\u27s correlation=0.99, RMS errors =0.39 mm, 0.38°). Finally, the system for anatomic reference system definition and motion tracking was demonstrated with a set of MR images of in vivo passive flexion in the human knee