Exploring the Risk Factors for the Misdiagnosis of Osteonecrosis of Femoral Head: A Case-Control Study

Multi-sequence MRI-based radiomics: An objective method to diagnose early-stage osteonecrosis of the femoral head

OBJECTIVES

This study investigated the use of radiomics for diagnosing early-stage osteonecrosis of the femoral head (ONFH) by extracting features from multiple MRI sequences and constructing predictive models.

MATERIALS AND METHODS

We conducted a retrospective review, collected MR images of early-stage ONFH (102 from institution A and 20 from institution B) and healthy femoral heads (102 from institution A and 20 from institution B) from two institutions. We extracted radiomics features, handled batch effects using Combat, and normalized features using z-score. We employed the Least absolute shrinkage and selection operator (LASSO) algorithm, along with Max-Relevance and Min-Redundancy (mRMR), to select optimal features for constructing radiomics models based on single, double, and multi-sequence MRI data. We evaluated performance using receiver operating characteristic (ROC) and precision-recall (PR) curves, and compared area under curve of ROC (AUC-ROC) values with the DeLong test. Additionally, we studied the diagnostic performance of the multi-sequence radiomics model and radiologists, compared the diagnostic outcomes of the model and radiologists using the Fisher exact test.

RESULTS

We studied 122 early-stage ONFH and 122 normal femoral heads. The multi-sequence model exhibited the best diagnostic performance among all models (AUC-ROC, PR-AUC for training set: 0.96, 0.961; validation set: 0.96, 0.97; test set: 0.94, 0.94), and it outperformed three resident radiologists on the external testing group with an accuracy of 87.5 %, sensitivity of 85.00 %, and specificity of 90.00 % (p < 0.01), highlighting the robustness of our findings.

CONCLUSIONS

Our study underscored the novelty of the multi-sequence radiomics model in diagnosing early-stage ONFH. By leveraging features extracted from multiple imaging sequences, this approach demonstrated high efficacy, indicating its potential to advance early diagnosis for ONFH. These findings provided important guidance for enhancing early diagnosis of ONFH through radiomics methods, offering new avenues and possibilities for clinical practice and patient care.

Proteomic profiling of extracellular vesicles derived from human serum for the discovery of biomarkers in Avascular necrosis

BACKGROUND

Avascular necrosis (AVN) is a medical condition characterized by the destruction of bone tissue due to a diminished blood supply. When the rate of tissue destruction surpasses the rate of regeneration, effective treatment becomes challenging, leading to escalating pain, arthritis, and bone fragility as the disease advances. A timely diagnosis is imperative to prevent and initiate proactive treatment for osteonecrosis. We explored the potential of differentially expressed proteins in serum-derived extracellular vesicles (EVs) as biomarkers for AVN of the femoral head in humans. We analyzed the genetic material contained in serum-derived exosomes from patients for early diagnosis, treatment, and prognosis of avascular necrosis.

METHODS

EVs were isolated from the serum of both patients with AVN and a control group of healthy individuals. Proteomic analyses were conducted to compare the expression patterns of these proteins by proteomic analysis using LC-MS/MS.

RESULTS

Our results show that the levels of IGHV3-23, FN1, VWF, FGB, PRG4, FCGBP, and ZSWIM9 were upregulated in the EVs of patients with AVN compared with those of healthy controls. ELISA results showed that VWF and PRG4 were significantly upregulated in the patients with AVN.

CONCLUSIONS

These findings suggest that these EV proteins could serve as promising biomarkers for the early detection and diagnosis of AVN. Early diagnosis is paramount for effective treatment, and the identification of new osteonecrosis biomarkers is essential to facilitate swift diagnosis and proactive intervention. Our study provides novel insights into the identification of AVN-related biomarkers that can enhance clinical management and treatment outcomes.

Deep Learning Approach for Diagnosing Early Osteonecrosis of the Femoral Head Based on Magnetic Resonance Imaging

BACKGROUND

The diagnosis of early osteonecrosis of the femoral head (ONFH) based on magnetic resonance imaging (MRI) is challenging due to variability in the surgeon's experience level. This study developed an MRI-based deep learning system to detect early ONFH and evaluated its feasibility in the clinic.

METHODS

We retrospectively evaluated clinical MRIs of the hips that were performed in our institution from January 2019 to June 2022 and collected all MRIs diagnosed with early ONFH. An advanced convolutional neural network (CNN) was trained and optimized; then, the diagnostic performance of the CNN was evaluated according to its accuracy, sensitivity, and specificity. We also further compared the CNN's performance with that of orthopaedic surgeons.

RESULTS

Overall, 11,061 images were retrospectively included in the present study and were divided into three datasets with ratio 7:2:1. The area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity of the CNN model for identifying early ONFH were 0.98, 98.4, 97.6, and 98.6%, respectively. In our review panel, the averaged accuracy, sensitivity, and specificity for identifying ONFH were 91.7, 87.0, and 94.1% for attending orthopaedic surgeons; 87.1, 84.0, and 89.3% for resident orthopaedic surgeons; and 97.1, 96.0, and 97.9% for deputy chief orthopaedic surgeons, respectively.

CONCLUSION

The deep learning system showed a comparable performance to that of deputy chief orthopaedic surgeons in identifying early ONFH. The success of deep learning diagnosis of ONFH might be conducive to assisting less-experienced surgeons, especially in large-scale medical imaging screening and community scenarios lacking consulting experts.

Automatic detection of early osteonecrosis of the femoral head from various hip pathologies using deep convolutional neural network: a multi-centre study

PURPOSE

The aim of this study was to develop a deep convolutional neural network (DCNN) for detecting early osteonecrosis of the femoral head (ONFH) from various hip pathologies and evaluate the feasibility of its application.

METHODS

We retrospectively reviewed and annotated hip magnetic resonance imaging (MRI) of ONFH patients from four participated institutions and constructed a multi-centre dataset to develop the DCNN system. The diagnostic performance of the DCNN in the internal and external test datasets was calculated, including area under the receiver operating characteristic curve (AUROC), accuracy, precision, recall, and F1 score, and gradient-weighted class activation mapping (Grad-CAM) technique was used to visualize its decision-making process. In addition, a human-machine comparison trial was performed.

RESULTS

Overall, 11,730 hip MRI segments from 794 participants were used to develop and optimize the DCNN system. The AUROC, accuracy, and precision of the DCNN in internal test dataset were 0.97 (95% CI, 0.93-1.00), 96.6% (95% CI: 93.0-100%), and 97.6% (95% CI: 94.6-100%), and in external test dataset, they were 0.95 (95% CI, 0.91- 0.99), 95.2% (95% CI, 91.1-99.4%), and 95.7% (95% CI, 91.7-99.7%). Compared with attending orthopaedic surgeons, the DCNN showed superior diagnostic performance. The Grad-CAM demonstrated that the DCNN placed focus on the necrotic region.

CONCLUSION

Compared with clinician-led diagnoses, the developed DCNN system is more accurate in diagnosing early ONFH, avoiding empirical dependence and inter-reader variability. Our findings support the integration of deep learning systems into real clinical settings to assist orthopaedic surgeons in diagnosing early ONFH.

Hip Preservation or Total Hip Arthroplasty? A Retrospective Case-Control Study of Factors Influencing Arthroplasty Decision-Making for Patients with Osteonecrosis of the Femoral Head in China

OBJECTIVE

At present, there is no consensus or guidance on indications for osteonecrosis of the femoral head (ONFH) patients to receive hip arthroplasty (THA) treatment. This study aims to explore the factors that influence the decision-making for THA in patients with ONFH, and to provide references for clinical decision for ONFH patients to be indicated for THA or hip preservation.

METHODS

This retrospective case-control study involved data for ONFH patients from July 2016 to October 2021 from the China Osteonecrosis of the Femoral Head Database (CONFHD). The patients with ONFH, and unilateral hip affected at the first visit were divided into THA group and non-THA group according to if they had undergone THA treatment. The differences between the two groups of patients in terms of gender, age at the time of consultation, body mass index (BMI), etiology, onset side, association research circulation osseous (ARCO) stage, hip joint function, visual analog scale (VAS), etc. were analyzed. Multivariate binomial logistic regression analysis was then applied to evaluate the risk factors of ONFH patients who underwent THA during the first visit.

RESULTS

A total of 640 patients were recruited for analysis, including 209 cases from the THA group and 431 cases from the non-THA group. The results of univariate analysis showed that the two groups of patients were significantly different in the following six indicators: age (59 vs. 46, Z = -9.58, p < 0.001), duration of disease (78 vs. 17, Z = -16.14, p < 0.001), gender composition (χ²  = 8.09, p = 0.004), disease etiology (χ²  = 33.04, p < 0.001), ARCO stage (χ²  = 334.86, p < 0.001), flexion of hip joint (χ²  = 172.33, p < 0.001). However, the comparison between the two groups on VAS (Z = -0.82, p = 0.41), BMI (Z = -1.35, p = 0.18), and onset side (χ²  = 1.53, p = 0.22) did not obviously differ. The results regression analysis showed that the age at the time of consultation, duration of disease, ARCO stage, and the hip joint function affected the decision making if the patients should undergo THA. The results of receiver operating characteristic curve (ROC) analysis showed that aforementioned indicators were satisfactory in predicting whether patients with ONFH would be treated with THA. The regression model using the above four indicators as comprehensive indicators has satisfactory performance in predicting whether to perform THA, and the area under the curve (AUC) is 93.94%.

CONCLUSION

These factors such as age, duration of disease, ARCO stage, and hip flexion function should be considered comprehensively before making decisions to perform THA or not in our clinical practice.

Transcriptomic analysis reveals genetic factors regulating early steroid-induced osteonecrosis of the femoral head

The present study aimed to explore the signaling pathways involved in development of early steroid-induced osteonecrosis of the femoral head (SONFH) and identify diagnostic biomarkers regulating peripheral blood in SONFH patients. We downloaded transcriptome data and identified differentially expressed genes (DEGs) using the R software. We used ClusterProfiler to perform enrichment analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, and analyzed protein-protein interactions using the STRING database. Network X was used to visualize the networks in Python. A total of 584 DEGs were identified, of which 294 and 290 were upregulated and downregulated, respectively. Enrichment analysis showed that the DEGs were mainly involved in red blood cell differentiation, cell protein catabolism, gas transportation, activation of myeloid leukocytes, phagocytosis, and inflammatory response. Pathway analysis revealed that these DEGs were involved in regulation of mitophagy-animal, human T-cell leukemia virus-1 infection, Forkhead box O, phagocytosis, osteoclast differentiation, and cytokine-cytokine receptor interaction. Quantitative real-time polymerase chain reaction results were consistent with findings from protein-protein interaction network analysis. Several genes, including peroxiredoxin 2, haptoglobin, matrix metallopeptidase 8, formyl peptide receptor 2, and integrin subunit alpha X, promote SONFH occurrence by regulating the redox, inflammatory response, and osteoblast and osteoclast structure and function pathways. They may be important targets for designing approaches for early diagnosis and treatment of SONFH.

Osteonecrosis of the Femoral Head: A Multidisciplinary Approach in Diagnostic Accuracy

Osteonecrosis of the Femoral Head (ONFH) is a disabling disease affecting up to 30,000 people yearly in the United States alone. Diagnosis and staging of this pathology are both technically and logistically challenging, usually relying on imaging studies. Even anatomopathological studies, considered the gold standard for identifying ONFH, are not exempt from problems. In addition, the diagnosis is often made by different healthcare specialists, including orthopedic surgeons and radiologists, using different imaging modes, macroscopic features, and stages. Therefore, it is not infrequent to find disagreements between different specialists. The aim of this paper is to clarify the association and accuracy of ONFH diagnosis between healthcare professionals. To this end, femoral head specimens from patients with a diagnosis of ONFH were collected from patients undergoing hip replacement surgery. These samples were later histologically analyzed to establish an ONFH diagnosis. We found that clinico-radiological diagnosis of ONFH evidences a high degree of histological confirmation, thus showing an acceptable diagnostic accuracy. However, when the diagnoses of radiologists and orthopedic surgeons are compared with each other, there is only a moderate agreement. Our results underscore the need to develop an effective diagnosis based on a multidisciplinary approach to enhance currently limited accuracy and reliability.

Complex Polypathology Infectious, Rheumatological, Neurological and Orthopedic – Real Challenge for Functional Rehabilitation - Case Report

Introduction. Infectious and autoimmune rheumatic diseases (ARDs) are closely linked. Apart from the challenging, sometimes differential, diagnosis between these conditions, it is recognized that microbes play an important role in the pathogenesis of the latter. Material and method. We present the case of a 45-year-old female patient from our rehabilitation department, with complex pathology (infectious, neurological, rheumatological and orthopedic pathology) that began more than 15 years ago. The patient’s pathological history began insidiously at theage of 30 when she was diagnosed with neurotoxoplasmosis. She received anticoagulant, antiepileptic, steroidal, antibiotic and antihelmintic treatment. After four years, the patient shows insidious onset of inflammatory pain in the large joints and in 2010 is diagnosed with seropositive rheumatoid arthritis, according to American College of Rheumatism/European League against rheumatism (ACR/EULAR) criteria with symmetric impairment of the large joints (shoulder, elbow, hip, knee, ankle). Despite the treatment with disease-modifying anti-rheumatic drugs (DMARDs) received, in the following years she needed 4 arthroplasties in the large joints due to osteonecrosis. Conclusions. On clinical grounds, infections, especially chronic infections, can cause a plethora of autoimmune phenomena, thus mimicking ARDs. Therefore, the differential diagnosis between ARDs and infectious diseases is sometimes challenging as they often display similar clinical manifestations. It is highlighted that the immune system can be our friend or our foe considering that its function and dysregulation are the common denominators in autoimmune and infectious diseases. In the era of new drugs and new therapeutic strategies, safety of the patients should always be our first concern.