Dual-Region Computed Tomography Radiomics-Based Machine Learning Predicts Subcarinal Lymph Node Metastasis in Patients with Non-small Cell Lung Cancer.

BACKGROUND: Noninvasively and accurately predicting subcarinal lymph node metastasis (SLNM) for patients with non-small cell lung cancer (NSCLC) remains challenging. This study was designed to develop and validate a tumor and subcarinal lymph nodes (tumor-SLNs) dual-region computed tomography (CT) radiomics model for predicting SLNM in NSCLC. METHODS: This retrospective study included NSCLC patients who underwent lung resection and SLNs dissection between January 2017 and December 2020. The radiomic features of the tumor and SLNs were extracted from preoperative CT, respectively. Ninety machine learning (ML) models were developed based on tumor region, SLNs region, and tumor-SLNs dual-region. The model performance was assessed by the area under the curve (AUC) and validated internally by fivefold cross-validation. RESULTS: In total, 202 patients were included in this study. ML models based on dual-region radiomics showed good performance for SLNM prediction, with a median AUC of 0.794 (range, 0.686-0.880), which was superior to those of models based on tumor region (median AUC, 0.746; range, 0.630-0.811) and SLNs region (median AUC, 0.700; range, 0.610-0.842). The ML model, which is developed by using the naive Bayes algorithm and dual-region features, had the highest AUC of 0.880 (range of cross-validation, 0.825-0.937) among all ML models. The optimal logistic regression model was inferior to the optimal ML model for predicting SLNM, with an AUC of 0.727. CONCLUSIONS: The CT radiomics showed the potential for accurately predicting SLNM in NSCLC patients. The ML model with dual-region radiomic features has better performance than the logistic regression or single-region models.

Radiomics model of contrast-enhanced computed tomography for predicting the recurrence of acute pancreatitis.

OBJECTIVES: To predict the recurrence of acute pancreatitis (AP) by constructing a radiomics model of contrast-enhanced computed tomography (CECT) at AP first attack. METHODS: We retrospectively enrolled 389 first-attack AP patients (271 in the primary cohort and 118 in the validation cohort) from three tertiary referral centers; 126 and 55 patients endured recurrent attacks in each cohort. Four hundred twelve radiomics features were extracted from arterial and venous phase CECT images, and clinical characteristics were gathered to develop a clinical model. An optimal radiomics signature was chosen using a multivariable logistic regression or support vector machine. The radiomics model was developed and validated by incorporating the optimal radiomics signature and clinical characteristics. The performance of the radiomics model was assessed based on its calibration and classification metrics. RESULTS: The optimal radiomics signature was developed based on a multivariable logistic regression with 10 radiomics features. The classification accuracy of the radiomics model well predicted the recurrence of AP for both the primary and validation cohorts (87.1% and 89.0%, respectively). The area under the receiver operating characteristic curve (AUC) of the radiomics model was significantly better than that of the clinical model for both the primary (0.941 vs. 0.712, p = 0.000) and validation (0.929 vs. 0.671, p = 0.000) cohorts. Good calibration was observed for all the models (p > 0.05). CONCLUSIONS: The radiomics model based on CECT performed well in predicting AP recurrence. As a quantitative method, radiomics exhibits promising performance in terms of alerting recurrent patients to potential precautions. KEY POINTS: • The incidence of recurrence after an initial episode of acute pancreatitis is high, and quantitative methods for predicting recurrence are lacking. • The radiomics model based on contrast-enhanced computed tomography performed well in predicting the recurrence of acute pancreatitis. • As a quantitative method, radiomics exhibits promising performance in terms of alerting recurrent patients to the potential need to take precautions.

The potential pathway of FOXC1 high expression in regulating the proliferation, migration, cell cycle and epithelialmesenchymal transition of basal-like breast cancer and in vivo imaging.

PURPOSE: To investigate the role of high forkhead box C1 (FOXC1) expression in basal-like breast cancer (BLBC) cells in vitro and in vivo, as well as its potential regulatory pathway. METHODS: Stable MDA-MB-231 cells, a type of BLBC cells, with high FOXC1 expression and luciferase (FOXC1) were established. The parental MDA-MB-231 cells with luciferase served as the control group. Proliferation, migratory capabilities and the cell cycle were evaluated. The tumorigenicity and the spontaneous pulmonary metastasis were measured in mice in vivo. In vivo imaging was also performed. Histopathology, immunohistochemical analysis and microarray processing were evaluated. Paired Student's t-test was used. RESULTS: The proliferation and migratory ability of FOXC1- MDA-MB-231 cells were enhanced significantly (p<0.05). Spontaneous pulmonary metastases were observed in 2 out of 5 mice, but no pulmonary metastases were observed in control animals. There were more FOXC1 cells in the G1 phase compared to the control (p<0.05), but there were also significant reductions of cells in the S and G2 phases (p<0.05). The CD31 and endoglin (CD105) expression in the FOXC1 tumor was higher than in the control, especially CD105 (p<0.05). The total fluorescence expression quantity of FOXC1 was higher than in the control cells (p<0.05), and the apparent diffusion coefficient (ADC) values were lower compared with the control (p<0.05). One pathway with the most gene enrichment (p38 MAPK signalling) may play a key role in regulating BLBC cell proliferation, migration, cell cycle and epithelial-mesenchymal transition (EMT) through the interaction of related critical regulatory genes (IL-6 and FOXC1). CONCLUSION: High FOXC1 enhanced the proliferation, migratory ability and EMT of BLBC cells. This function may be regulated by IL-6 and FOXC1 through the p38 MAPK signalling pathway.

Nomogram for Predicting Microvascular Invasion in Hepatocellular Carcinoma Using Gadoxetic Acid-Enhanced MRI and Intravoxel Incoherent Motion Imaging.

RATIONALE AND OBJECTIVES: Microvascular invasion (MVI) is an important risk factor in hepatocellular carcinoma (HCC), but it can only be determined through histopathological results. The aim of this study was to develop and validate a nomogram for preoperative prediction MVI in HCC using gadoxetic acid-enhanced magnetic resonance imaging (MRI) and intravoxel incoherent motion imaging (IVIM). MATERIALS AND METHODS: From July 2017 to September 2022, 148 patients with surgically resected HCC who underwent preoperative gadoxetic acid-enhanced MRI and IVIM were included in this retrospective study. Clinical indicators, imaging features, and diffusion parameters were compared between the MVI-positive and MVI-negative groups using the chi-square test, Mann-Whitney U test, and independent sample t test. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance in predicting MVI. Univariate and multivariate analyses were conducted to identify the significant clinical-radiological variables associated with MVI. Subsequently, a predictive nomogram that integrates clinical-radiological risk factors and diffusion parameters was developed and validated. RESULTS: Serum alpha-fetoprotein level, tumor size, nonsmooth tumor margin, peritumoral hypo-intensity on hepatobiliary phase (HBP), apparent diffusion coefficient value and D value were statistically significant different between MVI-positive group and MVI-negative group. The results of multivariate analysis identified tumor size (odds ratio [OR], 0.786; 95% confidence interval [CI], 0.675-0.915; P < .01), nonsmooth tumor margin (OR, 2.299; 95% CI, 1.005-5.257; P < .05), peritumoral hypo-intensity on HBP (OR, 2.786; 95% CI, 1.141-6.802; P < .05) and D (OR, 0.293; 95% CI,0.089-0.964; P < .05) was the independent risk factor for the status of MVI. In ROC analysis, the combination of peritumoral hypo-intensity on HBP and D demonstrated the highest area under the curve value (0.902) in prediction MVI status, with sensitivity 92.8% and specificity 87.7%. The nomogram exhibited excellent predictive performance with C-index of 0.936 (95% CI 0.895-0.976) in the patient cohort, and had well-fitted calibration curve. CONCLUSION: The nomogram incorporating clinical-radiological risk factors and diffusion parameters achieved satisfactory preoperative prediction of the individualized risk of MVI in patients with HCC.

MRI-Based Radiomics and Delta-Radiomics Models of the Patella Predict the Radiographic Progression of Osteoarthritis: Data From the FNIH OA Biomarkers Consortium.

RATIONALE AND OBJECTIVES: To analyse the MRI-based radiomics and delta-radiomics features to establish radiomics models for predicting the radiographic progression of osteoarthritis (OA). MATERIALS AND METHODS: The data used in this research come from the dataset of the FNIH Biomarker Consortium Project within the Osteoarthritis Initiative (OAI). 565 participants randomly divided into training and validation groups at a 7:3 ratio. The training cohort consisted of 395 participants and included 202 cases. The validation cohort consisted of 170 participants and included 87 cases. Least absolute shrinkage and selection operator (LASSO) was used for feature selection. Support vector machine (SVM) was used to establish radiomics models and clinical and biomarker models for predicting the radiographic progression of OA. The predictive ability of the model was evaluated by the area under the curve (AUC). RESULTS: The baseline, 24 M, Delta, and two combination radiomics models (Baseline and Delta, 24 M and Delta) all showed good predictive performance in the training and validation cohorts, with the combination model exhibiting the best performance. In the training cohort, the AUCs were 0.851 (95% CI: 0.812-0.890), 0.825 (95% CI: 0.784-0.865), 0.804 (95% CI: 0.761-0.847), 0.892 (95% CI: 0.860-0.924) and 0.884 (95% CI: 0.851-0.917), respectively. The AUCs in the validation cohort were 0.741 (95% CI: 0.667-0.814), 0.786 (95% CI: 0.716-0.856), 0.745 (95% CI: 0.671-0.819), 0.781 (95% CI: 0.711-0.851) and 0.802 (95% CI: 0.736-0.869), respectively. As compared, the clinical and biomarker models have AUC < 0.74. The DeLong test showed that the predictive performance of the radiomics models in the training and validation cohorts was significantly better than that of the clinical and biomarker models (P < 0.001). CONCLUSION: The MRI-based radiomics models of the patella all showed good predictive performance performed better than the clinical and biomarker models in predicting the radiographic progression of OA. Delta radiomics can improve the predictive performance of the single time model, the combined model of 24 M and Delta provided the best predictive performance.

Factors affecting osteogenesis and chondrogenic differentiation of mesenchymal stem cells in osteoarthritis.

Osteoarthritis (OA) is a common degenerative joint disease that often involves progressive cartilage degeneration and bone destruction of subchondral bone. At present, clinical treatment is mainly for pain relief, and there are no effective methods to delay the progression of the disease. When this disease progresses to the advanced stage, the only treatment option for most patients is total knee replacement surgery, which causes patients great pain and anxiety. As a type of stem cell, mesenchymal stem cells (MSCs) have multidirectional differentiation potential. The osteogenic differentiation and chondrogenic differentiation of MSCs can play vital roles in the treatment of OA, as they can relieve pain in patients and improve joint function. The differentiation direction of MSCs is accurately controlled by a variety of signaling pathways, so there are many factors that can affect the differentiation direction of MSCs by acting on these signaling pathways. When MSCs are applied to OA treatment, the microenvironment of the joints, injected drugs, scaffold materials, source of MSCs and other factors exert specific impacts on the differentiation direction of MSCs. This review aims to summarize the mechanisms by which these factors influence MSC differentiation to produce better curative effects when MSCs are applied clinically in the future.

Targeting Ferroptosis in Bone-Related Diseases: Facts and Perspectives.

Ferroptosis is a new cell fate decision discovered in recent years. Unlike apoptosis, autophagy or pyroptosis, ferroptosis is characterized by iron-dependent lipid peroxidation and mitochondrial morphological changes. Ferroptosis is involved in a variety of physiological and pathological processes. Since its discovery, ferroptosis has been increasingly studied concerning bone-related diseases. In this review, we focus on the latest research progress and prospects, summarize the regulatory mechanisms of ferroptosis, and discuss the role of ferroptosis in the pathogenesis of bone-related diseases, such as osteoporosis (OP), osteoarthritis (OA), rheumatoid arthritis (RA), and osteosarcoma (OS), as well as its therapeutic potential.

Radiotherapy modulates tumor cell fate decisions: a review.

Cancer has always been a worldwide problem, and the application of radiotherapy has greatly improved the survival rate of cancer patients. Radiotherapy can modulate multiple cell fate decisions to kill tumor cells and achieve its therapeutic effect. With the development of radiotherapy technology, how to increase the killing effect of tumor cells and reduce the side effects on normal cells has become a new problem. In this review, we summarize the mechanisms by which radiotherapy induces tumor cell apoptosis, necrosis, necroptosis, pyroptosis, ferroptosis, autophagy, senescence, mitotic catastrophe, and cuproptosis. An in-depth understanding of these radiotherapy-related cell fate decisions can greatly improve the efficiency of radiotherapy for cancer.

Adiponectin, May Be a Potential Protective Factor for Obesity-Related Osteoarthritis.

Osteoarthritis (OA) is the most common joint disease in elderly individuals and seriously affects quality of life. OA has often been thought to be caused by body weight load, but studies have increasingly shown that OA is an inflammation-mediated metabolic disease. The current existing evidence suggests that OA is associated with obesity-related chronic inflammation as well as abnormal lipid metabolism in obesity, such as fatty acids (FA) and triglycerides. Adiponectin, a cytokine secreted by adipose tissue, can affect the progression of OA by regulating obesity-related inflammatory factors. However, the specific molecular mechanism has not been fully elucidated. According to previous research, adiponectin can promote the metabolism of FA and triglycerides, which indicates that it is a potential protective factor for OA through many mechanisms. This article aims to review the mechanisms of chronic inflammation, FA and triglycerides in OA, as well as the potential mechanisms of adiponectin in regulating chronic inflammation and promoting FA and triglyceride metabolism. Therefore, adiponectin may have a protective effect on obesity-related OA, which could provide new insight into adiponectin and the related mechanisms in OA.

Radiomics models based on multi-sequence MRI for preoperative evaluation of MUC4 status in pancreatic ductal adenocarcinoma: a preliminary study.

Background: Mucin 4 (MUC4) overexpression promotes tumorigenesis and increases the aggressiveness of pancreatic ductal adenocarcinoma (PDAC). To date, no study has reported the association between radiomics and MUC4 expression in PDAC. Thus, we aimed to explore the utility of radiomics based on multi-sequence magnetic resonance imaging (MRI) to predict the status of MUC4 expression in PDAC preoperatively. Methods: This retrospective study included 52 patients with PDAC who underwent MRI. The patients were divided into two groups based on MUC4 expression status. Two feature sets were extracted from the arterial and portal phases (PPs) of dynamic contrast-enhanced MRI (DCE-MRI). Univariate analysis, minimum redundancy maximum relevance (MRMR), and principal component analysis (PCA) were performed for the feature selection of each dataset, and features with a cumulative variance of 90% were selected to develop radiomics models. Clinical characteristics were gathered to develop a clinical model. The selected radiomics features and clinical characteristics were modeled by multivariable logistic regression. The combined model integrated radiomics features from different selected data sets and clinical characteristics. The classification metrics were applied to assess the discriminatory power of the models. Results: There were 22 PDACs with a high expression of MUC4 and 30 PDACs with a low expression of MUC4. The area under the receiver operating characteristic (ROC) curve (AUC) values of the arterial phase (AP) model, the PP model, and the combined model were 0.732 (0.591-0.872), 0.709 (0.569-0.849), and 0.861 (0.760-0.961), respectively. The AUC of the clinical model was 0.666 (0.600-0.682). The combined model that was constructed outperformed the AP, the PP, and the clinical models (P<0.05, although no statistical significance was observed in the combined model vs. AP model). Conclusions: Radiomics models based on multi-sequence MRI have the potential to predict MUC4 expression levels in PDAC.

The Clinical Characteristics and CT Findings of Parotid and Submandibular Gland Tumours.

OBJECTIVE: To investigate the clinical characteristics and CT findings of parotid and submandibular gland tumours. Materials and methods. From May 2017 to April 2020, all patients with clinically proven parotid and submandibular gland enlargement and palpable masses underwent CT examinations. All patients were confirmed by pathology after surgery. The clinical characteristics and CT features were observed and evaluated. The mean density values before and after enhancement were measured and analyzed. The chi-square test, one-way ANOVA, and Student's t-test were used. RESULTS: Ninety-four patients with a total of 94 unilateral tumours in the parotid and submandibular glands were enrolled, including 38 pleomorphic adenomas (PAs), 27 Warthin's tumours (WTs), and 29 malignant tumours (MTs). The majority of the PAs (28/38) and MTs (23/29) were located in the parotid gland; the others were located in the submandibular gland. All the WTs were in the parotid gland. The most common benign tumours of the parotid gland were PAs (28/38, 73.7%) and WTs (27/27, 100%), and the most common MTs were mucoepidermoid carcinoma, acinic cell carcinoma, and squamous cell carcinoma (4/29, 13.8%). The most common benign and malignant tumours in the submandibular gland were PAs (10/38, 26.3%) and ductal adenocarcinomas (3/4, 75%). The majority of PA patients (28/38) were female, compared with WT (2/27) (P < 0.001) and malignant tumour patients (10/29) (P < 0.01). A significant difference was also found between WTs and MTs in female patients (P < 0.05). The mean age of PA patients was 43.4 ± 12.1 years, which was lower than that of WTs (62.1 ± 11.7) and MTs (58 ± 14.18) (P < 0.001, P < 0.001, and P=0.244, respectively). On CT imaging, the mean diameter of the PAs and WTs was significantly smaller than that of the MTs (P=0.001 and P < 0.001), and no difference was observed between the PAs and WTs (P=0.275). In the parotid gland, the superficial lobe was more frequently involved than the deep lobe (PAs, 22 : 6; WTs, 17 : 10; and MTs, 15 : 8). The majority of PAs and WTs demonstrated round shapes (25/38, 19/27) and were well defined (30/38, 24/27); by contrast, most MTs were lobulated, irregular shapes (24/29), and ill defined (25/29). On plain CT, the PAs were usually homogeneous, while MTs were frequently heterogeneous, with more necrosis, larger cystic areas, and more haemorrhage or calcification. The mean CT values of PAs, WTs, and MTs were 39.2 ± 3.9 HU, 39.1 ± 3.0 HU, and 37.6 ± 3.1 HU (P > 0.05), respectively. On contrast CT, the WTs were significantly enhanced compared with MTs and PAs, with mean CT values of 53.5 ± 4.0 HU, 84.4 ± 6.0 HU, and 65.2 ± 3.8 HU, respectively (all P < 0.001). The mean CT value changes for PAs, WTs, and MTs (∆) were 14.4 ± 3.0 HU, 45.3 ± 4.5 HU, and 27.7 ± 2.5 HU, respectively. Significant differences were observed between ∆PAs and ∆WTs, ∆PAs and ∆MTs, and ∆WTs and ∆MTs (all P < 0.001). CONCLUSION: Parotid and submandibular gland tumours have some typical clinical characteristics and CT findings, and plain and early contrast-phase CT combined with clinical parameters may be helpful for diagnosis.

Liver injury associated with acute pancreatitis: The current status of clinical evaluation and involved mechanisms.

Acute pancreatitis (AP) is a very common acute disease, and the mortality rate of severe AP (SAP) is between 15% and 35%. The main causes of death are multiple organ dysfunction syndrome and infections. The mortality rate of patients with SAP related to liver failure is as high as 83%, and approximately 5% of the SAP patients have fulminant liver failure. Liver function is closely related to the progression and prognosis of AP. In this review, we aim to elaborate on the clinical manifestations and mechanism of liver injury in patients with AP.

Contribution of CT Features in the Diagnosis of COVID-19.

The outbreak of novel coronavirus disease 2019 (COVID-19) first occurred in Wuhan, Hubei Province, China, and spread across the country and worldwide quickly. It has been defined as a major global health emergency by the World Health Organization (WHO). As this is a novel virus, its diagnosis is crucial to clinical treatment and management. To date, real-time reverse transcription-polymerase chain reaction (RT-PCR) has been recognized as the diagnostic criterion for COVID-19. However, the results of RT-PCR can be complemented by the features obtained in chest computed tomography (CT). In this review, we aim to discuss the diagnosis and main CT features of patients with COVID-19 based on the results of the published literature, in order to enhance the understanding of COVID-19 and provide more detailed information regarding treatment.

iRGD: A Promising Peptide for Cancer Imaging and a Potential Therapeutic Agent for Various Cancers.

Poor penetration into the tumor parenchyma and the reduced therapeutic efficacy of anticancer drugs and other medications are the major problems in tumor treatment. A new tumor-homing and penetrating peptide, iRGD (CRGDK/RGPD/EC), can be effectively used to combine and deliver imaging agents or anticancer drugs into tumors. The different "vascular zip codes" expressed in different tissues can serve as targets for docking-based (synaptic) delivery of diagnostic and therapeutic molecules. αv-Integrins are abundantly expressed in the tumor vasculature, where they are recognized by peptides containing the RGD integrin recognition motif. The iRGD peptide follows a multistep tumor-targeting process: First, it is proteolytically cleaved to generate the CRGDK fragment by binding to the surface of cells expressing αv integrins (αvß3 and αvß5). Then, the fragment binds to neuropilin-1 and penetrates the tumor parenchyma more deeply. Compared with conventional RGD peptides, the affinity of iRGD for αv integrins is in the mid to low nanomolar range, and the CRGDK fragment has a stronger affinity for neuropilin-1 than that for αv integrins because of the C-terminal exposure of a conditional C-end Rule (CendR) motif (R/KXXR/K), whose receptor proved to be neuropilin-1. Consequently, these advantages facilitate the transfer of CRGDK fragments from integrins to neuropilin-1 and consequently deeper penetration into the tumor. Due to its specific binding and strong affinity, the iRGD peptide can deliver imaging agents and anticancer drugs into tumors effectively and deeply, which is useful in detecting the tumor, blocking tumor growth, and inhibiting tumor metastasis. This review aims to focus on the role of iRGD in the imaging and treatment of various cancers.

MR imaging for acute pancreatitis: the current status of clinical applications.

Acute pancreatitis is a common clinical acute abdomen. Imaging examinations play an important role in the management of acute pancreatitis. MR imaging is a noninvasive examination with high tissue contrast and a variety of acquisition sequences that can help determine the diagnosis, complications and severity of acute pancreatitis. The acute pancreatitis classification working group modified the Atlanta classification in 2012 to improve clinical evaluations and standardize the radiologic nomenclature for acute pancreatitis. In particular, the redefinition of necrotizing pancreatitis offers a new understanding of this disease. In clinical practice, there is still a lack of unifying standards between radiologists and physicians, such as for the imaging features of pseudocysts, walled-off necrosis, peripancreatic necrosis and especially for the MR imaging features of acute pancreatitis. In this article, we review the 2012 revised Atlanta classification of acute pancreatitis and recent advances in the clinical applications of MR imaging (MRI) in acute pancreatitis by showing how MRI can provide more optimized information for clinical diagnosis and treatment plan.

Could intravoxel incoherent motion diffusion-weighted magnetic resonance imaging be feasible and beneficial to the evaluation of gastrointestinal tumors histopathology and the therapeutic response?

Gastrointestinal tumors (GTs) are among the most common tumors of the digestive system and are among the leading causes of cancer death worldwide. Functional magnetic resonance imaging (MRI) is crucial for assessment of histopathological changes and therapeutic responses of GTs before and after chemotherapy and radiotherapy. A new functional MRI technique, intravoxel incoherent motion (IVIM), could reveal more detailed useful information regarding many diseases. Currently, IVIM is widely used for various tumors because the derived parameters (diffusion coefficient, D; pseudo-perfusion diffusion coefficient, D*; and perfusion fraction, f) are thought to be important surrogate imaging biomarkers for gaining insights into tissue physiology. They can simultaneously reflect the microenvironment, microcirculation in the capillary network (perfusion) and diffusion in tumor tissues without contrast agent intravenous administration. The sensitivity and specificity of these parameters used in the evaluation of GTs vary, the results of IVIM in GTs are discrepant and the variability of IVIM measurements in response to chemotherapy and/or radiotherapy in these studies remains a source of controversy. Therefore, there are questions as to whether IVIM diffusion-weighted MRI is feasible and helpful in the evaluation of GTs, and whether it is worthy of expanded use.

The biomarkers changes in serum and the correlation with quantitative MRI markers by histopathologic evaluation of the cartilage in surgically-induced osteoarthritis rabbit model.

PURPOSE: To investigate the biomarkers change in serum and the correlation with quantitative MRI markers by histopathologic evaluation of the cartilage in surgically-induced osteoarthritis(OA) rabbit model. MATERIALS AND METHODS: Thirty-six mature New Zealand rabbits were used. Eighteen rabbits were divided into six groups randomly and equally and subjected to surgery using the improved Hulth method. The other eighteen rabbits were also allocated into six groups randomly and equally which served as the control. At multiple time points after surgery, the BMP-2, CTX-II and COMP levels in the serum were analyzed by ELISA, and quantitative MRI was performed. Histopathology was examined with HE, and Mankin scores were assessed. The changes in the biochemical biomarkers and imaging markers in the OA groups were compared with those in the control groups using paired-samples T tests. The correlation of quantitative MRI markers with biomarkers and Mankin scores were analyzed. The analysis of Mankin scores was conducted with non-parametric wilcoxon signed rank tests. RESULTS: The BMP-2 levels were increased at various times after surgery, and significant differences were observed between the OA and control groups(all the P values <0.001). CTX-II levels were significantly elevated at several intervals after surgery, including W2, W8, W12, W16 and W20(P=0.019, 0.004, 0.007, <0.001 and 0.016 respectively), but not at W4(P=0.764). Significant differences in the COMP levels from W2 to W20 were observed between the OA and the control groups(P<0.001, <0.001, <0.001, <0.001,=0.002 and =0.004 respectively). The T2 values increased at W8 post-surgery and were significantly different between the OA and control groups(P=0.001, <0.001, <0.001 and <0.001 respectively). T2* values increased from W2 to W20 and were significantly different between the control and OA groups(P=0.002, =0.001, <0.001, <0.001, =0.001 and <0.001 respectively). T2 values had significant correlation with BMP-2 and CTX-II(P<0.001 and =0.014), except COMP(P=0.305)., while the correlation of T2* values with BMP-2, CTX-II and COMP was significant(P=0.043, 0.005 and 0.025 respectively). In addition, a positive correlation of T2 values and Mankin scores was observed(P<0.001). CONCLUSION: With the relevance of the multiple time point analysis of the serum biomarkers and imaging markers compared with histological findings, BMP-2, CTX-II and COMP combined with T2 and T2* can be used to reflect and monitor OA progression potentially.

Quantitative evaluation in combination with nonquantitative evaluation in early patellar cartilage osteoarthritis at 3.0 T.

PURPOSE: To evaluate quantitative T1 and T2 relaxation times and magnetization transfer ratios (MTRs) in the early diagnosis of patellar cartilage osteoarthritis (OA) and to quantify and possibly refine the current Kellgren-Lawrence score criteria. MATERIALS AND METHODS: A total of 92 cases of knee joints with 40 normal volunteers and 30 patients with OA were prospectively evaluated. The knee joints with OA were divided into mild and moderate groups according to the Kellgren-Lawrence score criteria. The discriminative analysis method was used to analyze the accuracy of the original grouped cases correctly classified by age, sex, T1 relaxation times, T2 relaxation times, and MTR values. Linear regression analysis was used between T1 relaxation time, T2 relaxation time, and MTR values. RESULTS: The mean T1 relaxation times decreased with the severity of OA, and a significant difference was only found between the normal and moderate OA groups (P<0.05). The mean T2 relaxation times increased, and significant differences were found between the normal and mild OA groups and the normal and moderate OA groups (P<0.001). The MTR values were 35.8%±4.2%, 36.1%±3.2%, and 35.4%±3.8%, respectively. There were no significant differences between the normal and OA groups. In addition, T1 relaxation times were positively correlated with MTR values (P<0.01). A discriminative analysis using a synthesis of all the influential factors indicated a high accuracy rate (93.9%) for the correct classification of the original grouped cases. CONCLUSION: Quantitative T1 and T2 relaxation times were useful in the diagnosis of early OA; T2 relaxation times were more relatively sensitive. The functional usefulness of MTR values may be limited. T1 relaxation times positively correlated with MTR values. Multiple quantitative parameters, combined with some relative nonquantitative clinical parameters and Kellgren-Lawrence scores, may be useful in the early stage of OA and provide better information for clinical treatment and follow-up.

CT and MR imaging patterns for pancreatic carcinoma invading the extrapancreatic neural plexus (Part II): Imaging of pancreatic carcinoma nerve invasion.

Computed tomography (CT) and magnetic resonance imaging (MRI) are excellent modalities which have the ability to detect, depict and stage the nerve invasion associated with pancreatic carcinoma. The aim of this article is to review the CT and MR patterns of pancreatic carcinoma invading the extrapancreatic neural plexus and thus provide useful information which could help the choice of treatment methods. Pancreatic carcinoma is a common malignant neoplasm with a high mortality rate. There are many factors influencing the prognosis and treatment options for those patients suffering from pancreatic carcinoma, such as lymphatic metastasis, adjacent organs or tissue invasion, etc. Among these factors, extrapancreatic neural plexus invasion is recognized as an important factor when considering the management of the patients.

CT and MR imaging patterns for pancreatic carcinoma invading the extrapancreatic neural plexus (Part I): Anatomy, imaging of the extrapancreatic nerve.

Pancreatic carcinoma is an extremely high-grade malignant tumor with fast development and high mortality. The incidence of pancreatic carcinoma continues to increase. Peripancreatic invasion and metastasis are the main characteristics and important prognostic factors in pancreatic carcinoma, especially invasion into the nervous system; pancreatic nerve innervation includes the intrapancreatic and extrapancreatic nerves. A strong grasp of pancreatic nerve innervation may contribute to our understanding of pancreatic pain modalities and the metastatic routes for pancreatic carcinomas. Computed tomography (CT) and magnetic resonance imaging (MRI) are helpful techniques for depicting the anatomy of extrapancreatic nerve innervation. The purpose of the present work is to show and describe the anatomy of the extrapancreatic neural plexus and to elucidate its characteristics using CT and MRI, drawing on our own previous work and the research findings of others.