Background: A subject of ongoing debate among orthopedic surgeons is the importance of preserving the posterior cruciate ligament in total knee arthroplasty (TKA), but long-term survival studies are scarce. The aim of this study was to compare long-term survival rates, and clinical and radiological follow up of a double-blind randomized controlled trial comparing posterior cruciate-retaining (PCR) versus posterior-stabilizing (PS) implant design of an AGC TKA.
Methods: A total of 114 patients were included in the survival analysis (PCR n = 61; PS n = 53). Forty-five patients (PCR n = 25; PS n = 20) participated in the long-term follow up using patient-reported outcome measures (Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Short-Form Health Survey (SF-36) and Kujala score (measuring anterior knee pain)). Thirty-one patients were assessed with a physical test (Knee Society Score (KSS)) and radiographs.
Results: Overall survival rate was 95.6% (PCR 98.4% vs. PS 92.5%), with five patients having a major revision (PCR n = 1 vs. PS n = 4, respectively). Satisfying outcome scores for both groups were described at on average 12-year follow up with no significant differences in KSS knee and function scores, WOMAC, SF-36, or Kujala scores between groups. Radiographically, there were no findings of femoral or tibial loosening or polyethylene wear in either group.
Conclusions: Good long-term survival rates were described for the PCR and the PS design of an AGC TKA. There were no significant differences in clinical and radiological outcomes between a PCR and a PS design 12 years postoperatively.
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http://dx.doi.org/10.1016/j.knee.2023.10.006 | DOI Listing |
Alzheimers Res Ther
January 2025
Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA, Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA.
Background: Quantitative susceptibility mapping (QSM) can study the susceptibility values of brain tissue which allows for noninvasive examination of local brain iron levels in both normal and pathological conditions.
Purpose: Our study compares brain iron deposition in gray matter (GM) nuclei between cerebral small vessel disease (CSVD) patients and healthy controls (HCs), exploring factors that affect iron deposition and cognitive function.
Materials And Methods: A total of 321 subjects were enrolled in this study.
BMC Cancer
January 2025
Department of Radiology, Henan Provincial People's Hospital & Zhengzhou University People's Hospital, Zhengzhou, Henan, China.
Objectives: To construct a prediction model based on deep learning (DL) and radiomics features of diffusion weighted imaging (DWI), and clinical variables for evaluating TP53 mutations in endometrial cancer (EC).
Methods: DWI and clinical data from 155 EC patients were included in this study, consisting of 80 in the training set, 35 in the test set, and 40 in the external validation set. Radiomics features, convolutional neural network-based DL features, and clinical variables were analyzed.
BMC Cancer
January 2025
Department of Radiology, Xiangtan Central Hospital, Xiangtan, 411000, P. R. China.
Background: This study aims to quantify intratumoral heterogeneity (ITH) using preoperative CT image and evaluate its ability to predict pathological high-grade patterns, specifically micropapillary and/or solid components (MP/S), in patients diagnosed with clinical stage I solid lung adenocarcinoma (LADC).
Methods: In this retrospective study, we enrolled 457 patients who were postoperatively diagnosed with clinical stage I solid LADC from two medical centers, assigning them to either a training set (n = 304) or a test set (n = 153). Sub-regions within the tumor were identified using the K-means method.
Neurosurg Rev
January 2025
Department of Radiology, Lanzhou University Second Hospital, Lanzhou, 730030, China.
To investigate the value of preoperative MRI features and ADC histogram analysis for evaluating tumor-infiltrating CD8+ T cells in meningiomas. In this single-center cross-sectional study, we conducted a retrospective analysis of clinical, imaging, and pathological data from 84 patients with meningioma and performed immunohistochemical staining to quantitatively evaluate CD8+ T cells. Using X-Tile software, we divided the patients into high-and low-CD8+ T cells groups based on cut-off values.
View Article and Find Full Text PDFClin Rheumatol
January 2025
Department of Interventional Radiology, Affiliated Hospital of Guizhou Medical University, Guiyang, People's Republic of China.
Objectives: Predicting rheumatoid arthritis (RA) progression in undifferentiated arthritis (UA) patients remains a challenge. Traditional approaches combining clinical assessments and ultrasonography (US) often lack accuracy due to the complex interaction of clinical variables, and routine extensive US is impractical. Machine learning (ML) models, particularly those integrating the 18-joint ultrasound scoring system (US18), have shown potential to address these issues but remain underexplored.
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