Combination of single-source dual-energy computed tomography (CT) parameters and extracellular volume fraction for predicting lymphovascular and perineural invasion in colorectal cancer.

Background: Lymphovascular invasion (LVI) and perineural invasion (PNI) are important histopathological variables that are directly related to the survival and recurrence of patients with colorectal cancer (CRC). Preoperative prediction of LVI and PNI status in CRC is helpful in selecting patients requiring appropriate adjuvant therapy and evaluating prognosis. This study aimed to investigate the value of combining single-source dual-energy computed tomography (ssDECT)-derived parameters with extracellular volume (ECV) fraction for preoperative evaluation of LVI and PNI in CRC. Methods: This retrospective study included patients with CRC who underwent contrast-enhanced ssDECT. All diagnoses were confirmed through histopathology, and the patients were classified into positive and negative groups based on the presence of LVI/PNI. Clinical data were collected. In the arterial (AP), venous (VP) and delayed phases (DP), the ssDECT-derived parameters were measured by two radiologists. The measurement consistency was evaluated using intraclass correlation coefficients. Differences between the two groups were analyzed using the t-test, Mann-Whitney U test, or Chi-square test. Binary logistic regression was employed to construct models incorporating multiple parameters. The diagnostic performance of various parameters or models was assessed by analyzing receiver operating characteristic curves. Results: In total, 118 patients with CRC were included in the study. Serum carcinoembryonic antigen levels, T and N stages, and histological grades differed between the two groups (all P<0.05). The ssDECT-derived parameters in the VP and DP of LVI/PNI-positive group were higher than those of -negative group (all P<0.05). The ECV fraction in the DP of LVI/PNI-positive group was higher than that of -negative group (P=0.001). Discriminating capability analysis demonstrated that the diagnostic efficacies of the DP parameters were superior to those of the VP parameters, and the normalized iodine concentration in the DP exhibited the best performance [area under the curve (AUC): 0.750; 95% confidence interval (CI): 0.648-0.852]. The combination of ECV DP with clinical and ssDECT-derived parameters demonstrated the highest discriminative capability (AUC: 0.857; 95% CI: 0.786-0.928). Conclusions: ssDECT-derived parameters and ECV fraction may serve as non-invasive tools for predicting the LVI/PNI status in CRC.

Tumour-pleura relationship on computed tomography (CT) provides effective risk stratification for peripheral pulmonary nodules with Lung Imaging Reporting and Data System (Lung-RADS) score of 4X.

Background: Pulmonary nodules with Lung Imaging Reporting and Data System (Lung-RADS) 4X are of greater clinical significance, and accurate differentiation of pathological types and visceral pleural invasion (VPI) of Lung-RADS 4X peripheral pulmonary nodules before treatment can aid in stratification. This study set out to investigate whether the tumour-pleura relationship on computed tomography (CT) can provide effective risk stratification for peripheral pulmonary nodules with Lung-RADS 4X. Methods: This was a single institution, retrospective study of 482 consecutive patients with Lung-RADS score 4X, who were pathologically diagnosed with tuberculous granuloma and adenocarcinoma from January 2019 to December 2023. We assessed clinical factors (baseline characteristics and tumour markers) and CT findings. Univariate and multivariate logistic regression analyses were used to determine the classification of pulmonary nodules and predictors of VPI. Results: Multivariate analysis revealed that gender [odds ratio (OR) =0.392; P<0.001], carcinoembryonic antigen (CEA) level (OR =8.331; P<0.001), type of nodules (OR =13.551 and 7.478; P<0.001 and P=0.016) and maximum base width of soft tissue component on the pleura side (OR =0.857; P=0.005) were significant independent factors for distinguishing tuberculous granuloma from adenocarcinoma. And the type of linear connection between lesion and pleura (OR =3.936; P<0.001), and the maximum base width of soft tissue components on the pleura side (OR =1.359; P=0.001) were correlated independently with VPI. The area under the curve (AUC) for predicting pulmonary nodules classification was 82.60% [95% confidence interval (CI): 78.85-86.35%), and the AUC for predicting VPI was 76.10% (95% CI: 69.83-82.38%). Conclusions: The tumour-pleura relationship will be helpful in further risk stratification for peripheral pulmonary nodules with a score of Lung-RADS 4X.

Deep learning radiomic nomogram outperforms the clinical model in distinguishing intracranial solitary fibrous tumors from angiomatous meningiomas and can predict patient prognosis.

OBJECTIVES: To evaluate the value of a magnetic resonance imaging (MRI)-based deep learning radiomic nomogram (DLRN) for distinguishing intracranial solitary fibrous tumors (ISFTs) from angiomatous meningioma (AMs) and predicting overall survival (OS) for ISFT patients. METHODS: In total, 1090 patients from Beijing Tiantan Hospital, Capital Medical University, and 131 from Lanzhou University Second Hospital were categorized as primary cohort (PC) and external validation cohort (EVC), respectively. An MRI-based DLRN was developed in PC to distinguish ISFTs from AMs. We validated the DLRN and compared it with a clinical model (CM) in EVC. In total, 149 ISFT patients were followed up. We carried out Cox regression analysis on DLRN score, clinical characteristics, and histological stratification. Besides, we evaluated the association between independent risk factors and OS in the follow-up patients using Kaplan-Meier curves. RESULTS: The DLRN outperformed CM in distinguishing ISFTs from AMs (area under the curve [95% confidence interval (CI)]: 0.86 [0.84-0.88] for DLRN and 0.70 [0.67-0.72] for CM, p < 0.001) in EVC. Patients with high DLRN score [per 1 increase; hazard ratio (HR) 1.079, 95% CI: 1.009-1.147, p = 0.019] and subtotal resection (STR) [per 1 increase; HR 2.573, 95% CI: 1.337-4.932, p = 0.004] were associated with a shorter OS. A statistically significant difference in OS existed between the high and low DLRN score groups with a cutoff value of 12.19 (p < 0.001). There is also a difference in OS between total excision (GTR) and STR groups (p < 0.001). CONCLUSION: The proposed DLRN outperforms the CM in distinguishing ISFTs from AMs and can predict OS for ISFT patients. CLINICAL RELEVANCE STATEMENT: The proposed MRI-based deep learning radiomic nomogram outperforms the clinical model in distinguishing ISFTs from AMs and can predict OS of ISFT patients, which could guide the surgical strategy and predict prognosis for patients. KEY POINTS: Distinguishing ISFTs from AMs based on conventional radiological signs is challenging. The DLRN outperformed the CM in our study. The DLRN can predict OS for ISFT patients.

Response of soybean Cd to soil Cd and pH and its associated health risk in a high geological background area in Guizhou Province, Southwest China.

This study comprehensively examined the accumulation of cadmium (Cd) in soybeans grown in low- and high-Cd soils around the high geological background areas in Guizhou province. The aim was to analyze the relationship between soybean Cd and soil pH and soil Cd, alongside assessing the potential carcinogenic and non-carcinogenic risks associated with Cd in soybeans. Cd content of soybeans cultivated in the high-Cd area (0.430 mg/kg) was significantly higher than that in low-Cd areas (0.156 mg/kg) (P < 0.05). Biological concentration factors (BCFs) of soybean for Cd in low- and high-Cd areas were 0.282 and 0.314, respectively, with no significant differences (P > 0.05). Multiple linear regression results indicated that soil pH was a determining factor for Cd accumulation in soybeans in both areas. Furthermore, soil pH and soil Cd could accurately predict Cd accumulation in soybeans according to the neural network model. These findings suggest that regulating soil pH could reduce Cd accumulation in soybeans in areas with high geological background. In both areas, there was no significant non-carcinogenic risk for the adult population (HQ value < 1) through soybean consumption. However, according to the Monte Carlo model, the percentage of Cd in soybeans exceeding the acceptable range (CR value > 1.00 × 10 -04) in areas was 99.18%, indicating an unacceptable carcinogenic risk for the adult population. Our discussion revealed that reducing the soybean intake and increasing soil pH did not effectively lower the carcinogenic risk of Cd in soybeans to an acceptable range (CR value ≤ 1.00 × 10 -04). These findings necessitate further exploration of alternative remediation strategies to ensure the safe production of soybeans, such as screening for low-Cd accumulation soybean varieties and implementing the combined remediation strategies.

Tibial periosteum flap combined with autologous bone grafting in the treatment of Gustilo-IIIB/IIIC open tibial fractures.

Purpose: Gustilo IIIB/C injuries are common for tibia diaphysis fractures with high rates of nonunion, osteomyelitis, and amputation. However, the managements on tibial Gustilo IIIB/C injuries are still controversial and individual. The aim of this study is to introduce the tibial periosteum flap combined with autologous bone grafting to treat Gustilo-IIIB/IIIC injuries. Methods: Sixteen Gustilo type IIIB/C tibial fracture patients who underwent tibial periosteum flaps with autologous bone grafting surgeries were retrospectively studied. In the first stage, the wound was treated with debridement and the fracture was reduced and fixed with an external fixator. After covering with vacuum sealing drainage for 7 days, the wound areas were repaired by flaps. When the flaps survived and external fixators were removed, the tibial periosteum flaps were taken with autologous bone grafting for bone defects. Results: The tibia fractures were comminuted fractures with mean size of segment bone defects 3.1 ± 1.3 cm. All the flaps survived and the wound healed in the first stage after an average of 1.5 ± 0.6 months. The mean size of the flap was 13.2 ± 2.8 cm × 7.3 ± 3.1 cm. All the autografts healed in 4.5 ± 0.7 months without infection and malunion. There was no pain in the affected limb. The weight-bearing and walking function were restored. Conclusion: Tibial periosteum flap combined with autologous bone grafting is effective to treat bone-skin defect of leg with Gustilo-IIIB/IIIC injury.

Comparison of operatively and nonoperatively treated isolated mason type II radial head fractures: a systematic review and meta-analysis.

BACKGROUND: Radial head fractures are the most common bony injury of the elbow in adults. The current literature does not agree on whether isolated stable type II radial head fractures should be treated operatively or nonoperatively. This review aims to determine the preferred treatment for Mason type II radial head fractures and compare the outcomes of conservative and surgical treatment. METHODS: Our study used PRISMA guidelines and conducted a thorough search of multiple electronic databases, including PubMed, Cochrane, Embase, Web of Science, CNKI, and Wanfang databases, initially identifying 545 relevant publications on surgical and conservative treatment of Mason type II radial head fractures. The final search date for this study is July 7, 2024.Through a comprehensive meta-analysis, we evaluated several outcomes, including functional scores (DASH, OES, and MEPS scores), clinical outcomes (elbow flexion, elbow extension deficit, elbow pronation, and elbow supination), and complication rate (total complications and elbow pain). The mean difference (MD) was compared for continuous outcomes, and the odds ratios (ORs) were compared for categorical outcomes. RESULT: A total of 271 patients from 4 studies met the inclusion criteria. Among them, 142 patients received surgical treatment and 129 patients received non-surgical treatment. The study found no statistically significant differences between surgical and non-surgical treatments in DASH, OES, MEPS, elbow flexion, elbow extension impairment, and elbow pain. Compared with surgical treatment, non-surgical treatment was associated with greater elbow pronation (OR = -3.10, 95% CI = [-4.96, -1.25], P = 0.55, I2 = 0%) and a lower complication rate (OR = 5.54, 95% CI = [1.79, 17.14], P = 0.42, I2 = 0%). CONCLUSION: Based on the current evidence, conservative management of isolated Mason II radial head fractures yields favorable therapeutic outcomes with a low incidence of complications.

Integrated MRI radiomics, tumor microenvironment, and clinical risk factors for improving survival prediction in patients with glioblastomas.

PURPOSE: To construct a comprehensive model for predicting the prognosis of patients with glioblastoma (GB) using a radiomics method and integrating clinical risk factors, tumor microenvironment (TME), and imaging characteristics. MATERIALS AND METHODS: In this retrospective study, we included 148 patients (85 males and 63 females; median age 53 years) with isocitrate dehydrogenase-wildtype GB between January 2016 and April 2022. Patients were randomly divided into the training (n = 104) and test (n = 44) sets. The best feature combination related to GB overall survival (OS) was selected using LASSO Cox regression analyses. Clinical, radiomics, clinical-radiomics, clinical-TME, and clinical-radiomics-TME models were established. The models' concordance index (C-index) was evaluated. The survival curve was drawn using the Kaplan-Meier method, and the prognostic stratification ability of the model was tested. RESULTS: LASSO Cox analyses were used to screen the factors related to OS in patients with GB, including MGMT (hazard ratio [HR] = 0.642; 95% CI 0.414-0.997; P = 0.046), TERT (HR = 1.755; 95% CI 1.095-2.813; P = 0.019), peritumoral edema (HR = 1.013; 95% CI 0.999-1.027; P = 0.049), tumor purity (TP; HR = 0.982; 95% CI 0.964-1.000; P = 0.054), CD163 + tumor-associated macrophages (TAMs; HR = 1.049; 95% CI 1.021-1.078; P < 0.001), CD68 + TAMs (HR = 1.055; 95% CI 1.018-1.093; P = 0.004), and the six radiomics features. The clinical-radiomics-TME model had the best survival prediction ability, the C­index was 0.768 (0.717-0.819). The AUC of 1­, 2­, and 3­year OS prediction in the test set was 0.842, 0.844, and 0.795, respectively. CONCLUSION: The clinical-radiomics-TME model is the most effective for predicting the survival of patients with GB. Radiomics features, TP, and TAMs play important roles in the prognostic model.

Optimization of Different Extraction Methods for Phenolic Compound Verbascoside from Chinese Olea europaea Leaves Using Deep Eutectic Solvents: Impact on Antioxidant and Anticancer Activities.

Chinese Olea europaea leaves, rich in verbascosides, were extracted using ultrasound-assisted extraction (UAE) and wall-breaking extraction (WBE) with deep eutectic solvents (Optimal UAE: 55 min, 200 mL/g liquid-solid ratio, 20% moisture, yielding 206.23 ± 0.58 mg GAE/g total phenolic content (TPC) and 1.59 ± 0.04% verbascoside yield (VAY); Optimal WBE: 140 s, 210 mL/g, 30% moisture, giving 210.69 ± 0.97 mg GAE/g TPC and 1.33 ± 0.2% VAY). HPLC analysis showed that young leaves accumulated higher TPC and phenolic compounds. Among the five olive varieties, Koroneiki and Chemlal showed the highest TPC in UAE, while Arbosana and Chemlal excelled in WBE. WBE yielded a higher TPC and rutin, whereas UAE marginally increased other phenolics. Additionally, the DPPH• assay showed that WBE-extracted verbascoside-rich extracts (VREs) of Chemlal exhibited high antioxidant activity (EC50 of 57 mg/mL), but Koroneiki-VREs exhibited lower activity against the ABTS•+ radical (EC50 of 134 mg/mL). Remarkably, the UAE/WBE-extracted Chemlal-VREs promoted the normal esophageal Het-1A cell line at 25 µg/mL for 24 h; yet, the esophageal cancer Eca-109 cells were sensibly inhibited, especially at 50 µg/mL; and the cell viability decreased dramatically. The results confirmed WBE as a relatively efficient method, and the Chemlal variety may be an excellent source of verbascoside.

Magnetic resonance imaging-based radiomics for predicting infiltration levels of CD68+ tumor-associated macrophages in glioblastomas.

PURPOSE: Tumor-associated macrophages (TAMs) are important biomarkers of tumor invasion and prognosis in patients with glioblastoma. We combined the imaging and radiomics features of preoperative MRI to predict CD68+ macrophage infiltration. METHODS: Clinical, MRI image, and pathology data of 188 patients with glioblastoma were analyzed. Overall, 143 patients were included in the training (n = 101) and validation (n = 42) sets, whereas 45 patients were included in an independent test set. The optimal cut-off value (14.8%) was based on the minimum p-value formed by the Kaplan-Meier survival analysis and log-rank tests which divided patients into groups with high CD68+ TAMs (≥ 14.8%) and low CD68+ TAMs (< 14.8%). Regions of interest and radiomics features extraction were based on contrast-enhanced T1-weighted images (CE-T1WI) and T2WI. Multi-parameter stepwise regression was used to create the clinical, radiomics, and combined models, each evaluated using the receiver operating characteristic curve. Decision curve analysis was used to assess the clinical applicability of the nomogram. RESULTS: A clinical model based on the minimum apparent diffusion coefficient (ADCmin) revealed an area under the curve (AUC) of 0.768, 0.764, and 0.624 for the training set, validation set, and test set, respectively. The 2D radiomics model, based on two features, revealed an AUC of 0.783, 0.724, and 0.789 for the training, validation, and test sets, respectively. The 3D radiomics model, based on three features, revealed AUCs of 0.823, 0.811, and 0.787 for the training, validation, and test sets, respectively. The combined model, with ADCmin and radiomics features, showed the best performance, with AUCs of 0.865, 0.822, and 0.776 for the training, validation, and test sets, respectively. The calibration curve of the combined model nomogram showed good agreement between the estimated and actual probabilities. CONCLUSION: The combined model constructed using ADCmin, a quantitative imaging parameter, combined with five key radiomics features can be used to evaluate the extent of CD68+ macrophages before surgery.

Left atrial appendage thrombus is associated with a higher fractal dimension in patients with atrial fibrillation.

PURPOSE: To assess the anatomical complexity of the left atrial appendage (LAA) using fractal dimension (FD) based on cardiac computed tomography angiography (CTA) and the association between LAA FD and LAA thrombosis. MATERIALS AND METHODS: Patients with atrial fibrillation (AF) who underwent both cardiac CTA and transesophageal echocardiography (TEE) between December 2018 and December 2022 were retrospectively analyzed. Patients were categorized into normal (n = 925), circulatory stasis (n = 82), and thrombus groups (n = 76) based on TEE results and propensity score matching (PSM) was performed for subsequent analysis. FD was calculated to quantify the morphological heterogeneity of LAA. Independent risk factors for thrombus were screened using logistic regression. The diagnostic performance of FD and CHA2DS2-VaSc score for predicting thrombus was evaluated using the area under the receiver operating characteristics curve (AUC). RESULTS: LAA FD was higher in the thrombus group (1.61 [1.49, 1.70], P < 0.001) than in the circulatory stasis (1.33 [1.18, 1.47]) and normal groups (1.30 [1.18, 1.42]) both before and after PSM. LAA FD was also an independent risk factor in the thrombus (OR [odds ratio] = 570,861.15 compared to normal, 41,122.87 compared to circulatory stasis; all P < 0.001) and circulatory stasis group (OR = 98.87, P = 0.001) after PSM. The diagnostic performance of LAA FD was significantly better than the CHA2DS2-VaSc score in identifying thrombus. CONCLUSIONS: Patients with high LAA FD are more likely to develop LAA thrombus, and the use of FD provides an effective method for assessing the risk of thrombosis in AF patients, thereby guiding individualized clinical treatment.

Enhancing Outcome Prediction in Intracerebral Hemorrhage Through Deep Learning: A Retrospective Multicenter Study.

RATIONALE AND OBJECTIVES: This study aimed to employ deep learning techniques to analyze and validate an automatic prognostic biomarker for predicting outcomes following intracerebral hemorrhage (ICH). MATERIALS AND METHODS: This study included patients with ICH whose onset-to-imaging time (OIT) was less than 6 h. Patients were randomly divided into training and test sets at a 7:3 ratio. Using the Resnet50 deep learning method, we extracted features from the hematoma and perihematomal edema (PHE) areas and constructed a 90-day prognosis prediction model using logistic regression. To evaluate predictive efficacy and clinical significance, we employed logistic regression to train three models: Clinical, Deep Score, and the combined Clinical-Deep Learning (Merge). RESULTS: Our study comprised 1098 patients (652 male, 446 female), with a mean Glasgow Coma Scale (GCS) score of 10. Univariate and multivariate analyses identified age, intraventricular hemorrhage (IVH), hematoma and PHE volume, and admission GCS score as independent prognostic factors. Additionally, 15 deep learning features were retained through LASSO regression. In the training set, the AUC values for the three models were as follows: Clinical model (0.88), Deep Score (0.91), and Merge model (0.94). In the test set, the Merge model exhibited a significantly higher AUC value than the other models. Calibration curves revealed satisfactory calibration of the Merge model nomogram in both training and test sets. CONCLUSION: Our Merge model nomogram is an objective and effective prognostic tool, offering personalized risk assessments for 90-day functional outcomes in patients with ICH.

Predicting Durable Clinical Benefits of Postoperative Adjuvant Chemotherapy in Non-small Cell Lung Cancer: A Nomogram Based on CT Imaging and Immune Type.

PURPOSE: To develop a model based on conventional CT signs and the tumor microenvironment immune types (TIMT) to predict the durable clinical benefits (DCB) of postoperative adjuvant chemotherapy in non-small cell lung cancer (NSCLC). METHODS AND MATERIALS: A total of 205 patients with NSCLC underwent preoperative CT and were divided into two groups: DCB (progression-free survival (PFS) ≥ 18 months) and non-DCB (NDCB, PFS <18 months). The density percentiles of PD-L1 and CD8 + tumor-infiltrating lymphocytes (TIL) were quantified to estimate the TIMT. Clinical characteristics and conventional CT signs were collected. Multivariate logistic regression was employed to select the most discriminating parameters, construct a predictive model, and visualize the model as a nomogram. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to evaluate prediction performance and clinical utility. RESULTS: Precisely 118 patients with DCB and 87 with NDCB in NSCLC received postoperative adjuvant chemotherapy. TIMT was statistically different between the DCB and NDCB groups (P < 0.05). Clinical characteristics (neuron-specific enolase, squamous cell carcinoma antigen, Ki-76, and cM stage) and conventional CT signs (spiculation, bubble-like lucency, pleural retraction, maximum diameter, and CT value of the venous phase) varied between the four TIMT groups (P < 0.05). Furthermore, clinical characteristics (lymphocyte count [LYMPH] and cM stage) and conventional CT signs (bubble-like lucency and Pleural effusion) differed between the DCB and NDCB groups (P < 0.05). Multivariate analysis revealed that TIMT, cM stage, LYMPH, and pleural effusion were independently associated with DCB and were used to construct a nomogram. The area under the curve (AUC) of the combined model was 0.70 (95%CI: 0.64-0.76), with sensitivity and specificity of 0.73 and 0.60, respectively. CONCLUSION: Conventional CT signs and the TIMT offer a promising approach to predicting clinical outcomes for patients treated with postoperative adjuvant chemotherapy in NSCLC.

Predicting lymphovascular invasion in N0 stage non-small cell lung cancer: A nomogram based on Dual-energy CT imaging and clinical findings.

PURPOSE: To construct a nomogram for predicting lymphovascular invasion (LVI) in N0 stage non-small cell lung cancer (NSCLC) using dual-energy computed tomography (DECT) findings combined with clinical findings. METHODS: We retrospectively recruited 135 patients with N0 stage NSCLC from two hospitals underwent DECT before surgery and were divided into development cohort (n = 107) and validation cohort (n = 28). The clinical findings (baseline characteristics, biochemical markers, serum tumor markers and Immunohistochemical markers), DECT-derived parameters (iodine concentration [IC], effective atomic number [Eff-Z] and normalized iodine concentration [NIC], iodine enhancement [IE] and NIC ratio [NICr]) and Fractal dimension (FD) were collected and measured. A nomogram was constructed using significant findings to predict LVI in N0 stage NSCLC and was externally validated. RESULTS: Multivariable analysis revealed that lymphocyte count (LYMPH, odds ratio [OR]: 3.71, P=0.014), IC in arterial phase (ICa, OR: 1.25, P=0.021), NIC in venous phase (NICv, OR: 587.12, P=0.009) and FD (OR: 0.01, P=0.033) were independent significant factors for predicting LVI in N0 stage NSCLC, and were used to construct a nomogram. The nomogram exhibited robust predictive capabilities in both the development and validation cohort, with AUCs of 0.819 (95 % CI: 72.6-90.4) and 0.844 (95 % CI: 68.2-95.8), respectively. The calibration plots showed excellent agreement between the predicted probabilities and the actual rates of positive LVI, on external validation. CONCLUSIONS: Combination of clinical and DECT imaging findings could aid in predicting LVI in N0 stage NSCLC using significant findings of LYMPH, ICa, NICv and FD.

Time from injury to hip-fracture surgery in low-income and middle-income regions: a secondary analysis of data from the International Orthopaedic Multicentre Study in Fracture Care (INORMUS).

BACKGROUND: Globally, fall-related injuries are a substantial problem, and 80% of fatal falls occur in low-income and middle-income countries. We aimed to measure time from injury to hip-fracture surgery in people aged 50 years or older living in low-income and middle-income regions, as well as to measure the proportion of patients with surgical stabilisation of their hip fracture within 72 h of admission to hospital and to identify risk factors associated with surgical delay. METHODS: For this secondary analysis, we analysed data collected from Africa, Latin America, China, India, and Asia (excluding China and India) for the International Orthopaedic Multicentre Study in Fracture Care (INORMUS) between March 29, 2014, and June 15, 2022. Patients from INORMUS were included in this analysis if they were aged 50 years or older and had an isolated, primary hip fracture sustained from a ground-level fall. Staff at participating hospitals identified patients with musculoskeletal injury and referred them for assessment of eligibility. We report time from injury to surgery as three distinct time periods: time from injury to hospital admission, time from admission to surgery, and a total time from injury to surgery. Date and time of injury were self-reported by patients at the time of study recruitment. If time to hospital admission after injury exceeded 24 h, patients reported the primary reason for delayed admission. Reasons for surgery, no surgery, and surgical delay were reported by the treating team. For patients undergoing surgery, multivariable regression analyses were used to identify risk factors for surgical delay. FINDINGS: 4486 adults aged 50 years or older with an isolated, primary hip fracture were enrolled in INORMUS from 55 hospitals in 24 countries. Countries were grouped into five regions: Africa (418 [9·3%] of 4486), Latin America (558 [12·4%]), China (1680 [37·4%]), India (1059 [23·6%]) and Asia (excluding China and India; 771 [17·2%]). Of 4486 patients, 3805 (84·8%) received surgery. The rate of surgery was similar in all regions except in Africa, where only 193 (46·3%) of 418 patients had surgery. Overall, 2791 (62·2%) of 4486 patients were admitted to hospital within 24 h of injury. However, 1019 (22·7%) of 4486 patients had delayed hospital admission of 72 h or more from injury. The two most common reasons for delayed admission of more than 24 h were transfer from another hospital (522 [36·2%] of 1441) and delayed care-seeking because patients thought the injury would heal on its own (480 [33·3%]). Once admitted to hospital, 1451 (38·1%) of 3805 patients who received surgery did so within 72 h (median 4·0 days [IQR 1·7-6·0]). Regional variation was seen in the proportion of patients receiving surgery within 72 h of hospital admission (92 [17·9%] of 514 in Latin America, 53 [27·5%] of 193 in Africa, 454 [30·9%] of 1471 in China, 318 [44·4%] of 716 in Asia [excluding China and India], and 534 [58·6%] of 911 in India). Of all 3805 patients who received operative treatment, 2353 (61·8%) waited 72 h or more from hospital admission. From time of injury, the proportion of patients who were surgically stabilised within 72 h was 889 (23·4%) of 3805 (50 [9·7%] of 517 in Latin America, 31 [16·1%] of 193 in Africa, 277 [18·8%] of 1471 in China, 189 [26·4%] of 716 in Asia [excluding China and India], and 342 [37·5%] of 911 in India). INTERPRETATION: Access to surgery within 72 h of hospital admission was poor, with factors that affected time to surgery varying by region. Data are necessary to understand existing pathways of hip-fracture care to inform the local development of quality-improvement initiatives. FUNDING: The National Health and Medical Research Council of Australia, the Canadian Institutes of Health Research, McMaster Surgical Associates, Hamilton Health Sciences, and the US National Institutes of Health.

Radiomic nomogram for predicting high-risk cytogenetic status in multiple myeloma based on fat-suppressed T2-weighted magnetic resonance imaging.

Rationale and Objectives: Radiomics has demonstrated potential in predicting the cytogenetic status of multiple myeloma (MM). However, the role of single-sequence radiomic nomograms in predicting the high-risk cytogenetic (HRC) status of MM remains underexplored. This study aims to develop and validate radiomic nomograms based on fat-suppressed T2-weighted images (T2WI-FS) for predicting MM's HRC status, facilitating pre-treatment decision-making and prognostic assessment. Materials and methods: A cohort of 159 MM patients was included, comprising 71 HRC and 88 non-HRC cases. Regions of interest within the most significant tumor lesions on T2WI-FS images were manually delineated, yielding 1688 features. Fourteen radiomic features were selected using 10-fold cross-validation, employing methods such as variance thresholds, Student's t-test, redundancy analysis, and least absolute shrinkage and selection operator (LASSO). Logistic regression was utilized to develop three prediction models: a clinical model (model 1), a T2WI-FS radiomic model (model 2), and a combined clinical-radiomic model (model 3). Receiver operating characteristic (ROC) curves evaluated and compared the diagnostic performance of these models. Kaplan-Meier survival analysis and log-rank tests assessed the prognostic value of the radiomic nomograms. Results: Models 2 and 3 demonstrated significantly greater diagnostic efficacy compared to model 1 (p < 0.05). The areas under the ROC curve for models 1, 2, and 3 were as follows: training set-0.650, 0.832, and 0.846; validation set-0.702, 0.730, and 0.757, respectively. Kaplan-Meier survival analysis indicated comparable prognostic values between the radiomic nomogram and MM cytogenetic status, with log-rank test results (p < 0.05) and concordance indices of 0.651 and 0.659, respectively; z-score test results were not statistically significant (p = 0.153). Additionally, Kaplan-Meier analysis revealed that patients in the non-HRC group, low-RS group, and aged ≤ 60 years exhibited the longest overall survival, while those in the HRC group, high-RS group, and aged > 60 years demonstrated the shortest overall survival (p = 0.004, Log-rank test). Conclusions: Radiomic nomograms are capable of predicting the HRC status in MM. The cytogenetic status, radiomics model Rad score, and age collectively influence the overall survival of MM patients. These factors potentially contribute to pre-treatment clinical decision-making and prognostic assessment.

Nomogram of magnetic resonance imaging (MRI) histogram analysis to predict telomerase reverse transcriptase promoter mutation status in glioblastoma.

Background: Telomerase reverse transcriptase promoter (pTERT) status is a strong biomarker to diagnose and predict the prognosis of glioblastoma (GBM). In this study, we explored the predictive value of preoperative magnetic resonance imaging (MRI) histogram analysis in the form of nomogram for evaluating pTERT mutation status in GBM. Methods: The clinical and imaging data of 181 patients with GBM at our hospital between November 2018 and April 2023 were retrospectively assessed. We used the molecular sequencing results to classify the datasets into pTERT mutations (C228T and C250T) and pTERT-wildtype groups. FireVoxel software was used to extract preoperative T1-weighted contrast-enhanced (T1C) histogram parameters of GBM patients. The T1C histogram parameters were compared between groups. Univariate and multivariate logistic regression analyses were used to construct the nomogram, and the predictive efficacy of model was evaluated using calibration and decision curves. Receiver operating characteristic curve was used to assess model performance. Results: Patient age and percentage of unenhanced tumor area showed statistically significant differences between the pTERT mutation and pTERT-wildtype groups (P<0.001). Among the T1C histogram features, the maximum, standard deviation (SD), variance, coefficient of variation (CV), skewness, 5th, 10th, 25th, 95th and 99th percentiles were statistically significantly different between groups (P=0.000-0.040). Multivariate logistic regression analysis showed that age, percentage of unenhanced tumor area, SD and CV were independent risk factors for predicting pTERT mutation status in GBM patients. The logistic regression model based on these four features showed a better sample predictive performance, and the area under the curve (AUC) [95% confidence interval (CI)], accuracy, sensitivity, specificity were 0.842 (0.767-0.917), 0.796, 0.820, and 0.729, respectively. There were no significant differences in the T1C histogram parameters between the C228T and C250T groups (P=0.055-0.854). Conclusions: T1C histogram parameters can be used to evaluate pTERT mutations status in GBM. A nomogram based on conventional MRI features and T1C histogram parameters is a reliable tool for the pTERT mutation status, allowing for non-invasive radiological prediction before surgery.

Comparison between anterior-to-posterior screw fixation versus posterolateral approach plate fixation for posterior malleous fracture: A systematic review and meta-analysis.

PURPOSE: There are two main surgical fixation methods for the posterior malleolar fractures (PMFs), the anterior-to-posterior (AP) screws or via the posterolateral (PL) approach utilizing a buttress plate. This review aims to compare the clinical outcome between the AP screw fixation and the PL plate fixation for treating PMFs. METHODS: We searched all relevant publications about PMFs treated with AP screws or PL plates through electronic databases including the PubMed, the Cochrane Library, the Embase, the Wiley online library and the Web of Science. The meta-analysis was conducted to evaluated clinical outcomes including reduction quality, post-operative function and complications. RESULTS: Six studies (one single randomized controlled trial and five retrospective cohort studies) were enrolled. 172 patients underwent AP screw fixation and 214 patients underwent PL plate fixation with a total of 386 patients (169 males and 217 females). The PL plating group yielded better AOFAS scores(MD = 6.97, 95 % CI=[4.68, 9.27], P＜0.00001, I2 =0 %) and was more likely to achieve excellent anatomical reduction(OR=5.49, 95 % CI=[1.06, 28.42], P = 0.04, I2 =80 %). No differences were found in the bad reduction quality, incidences of complications (arthritis, neuralgia, superficial wound healing problems and implant failure), the walking VAS scores and the dorsiflexion restriction degrees. CONCLUSION: We suggest that the PL plate fixation method has the clinical benefit of achieving anatomical reduction and better AOFAS scores over the AP screw fixation for treating PMFs. No differences were found in the incidences of complications ( arthritis, neuralgia, superficial wound healing problems and implant failure), the walking VAS scores and the dorsiflexion restriction degrees. The posterior approach and the direct reduction are recommended for the treatment of the PMFs. LEVEL OF CONFIDENCE: Ⅱb.

Association between Pericoronary Fat Attenuation Index Values and Plaque Composition Volume Fraction Measured by Coronary Computed Tomography Angiography.

RATIONALE AND OBJECTIVES: The pericoronary fat attenuation index (FAI) values around plaques may reveal the relationship between periplaque vascular inflammation and different plaque component volume fractions. We aimed to evaluate the potential associations between periplaque FAI values and plaque component volume fractions. MATERIALS AND METHODS: 496 patients (1078 lesions) with coronary artery disease, who underwent computed tomography angiography (CCTA) between September 2022 and August 2023, were analyzed retrospectively. Each lesion was characterized and the plaque component volume fractions and periplaque FAI values were measured. Multiple linear regression, weighted quantile sum (WQS) regression, and quantile g-computation (Qgcomp) were used to explore the relationship between plaque component volume fractions and the risk of elevated periplaque FAI values. RESULTS: After adjusting for clinical characteristics, multiple linear regression identified that lipid components volume fraction (ß = 0.162, P < 0.001) were independent risk factors for elevated periplaque FAI values whereas calcified components volume fraction (ß = -0.066, P = 0.025) were independent protective factors. The WQS regression models indicated an increase in the overall confounding effect of the adjusted lipid indices and plaque composition volume fraction on the risk of elevated periplaque FAI values (P = 0.004). Qgcomp analysis indicated lipid component volume fraction and calcified component volume fraction was positively and negatively correlated with elevated plaque FAI values, respectively (all P < 0.05). CONCLUSIONS: Periplaque FAI values quantified by CCTA were strongly correlated with lipid and calcification component volume fractions.

MRI features and tumor-infiltrating CD8 + T cells-based nomogram for predicting meningioma recurrence risk.

OBJECTIVE: This study was based on MRI features and number of tumor-infiltrating CD8 + T cells in post-operative pathology, in predicting meningioma recurrence risk. METHODS: Clinical, pathological, and imaging data of 102 patients with surgically and pathologically confirmed meningiomas were retrospectively analyzed. Patients were divided into recurrence and non-recurrence groups based on follow-up. Tumor-infiltrating CD8 + T cells in tissue samples were quantitatively assessed with immunohistochemical staining. Apparent diffusion coefficient (ADC) histogram parameters from preoperative MRI were quantified in MaZda. Considering the high correlation between ADC histogram parameters, we only chose ADC histogram parameter that had the best predictive efficacy for COX regression analysis further. A visual nomogram was then constructed and the recurrence probability at 1- and 2-years was determined. Finally, subgroup analysis was performed with the nomogram. RESULTS: The risk factors for meningioma recurrence were ADCp1 (hazard ratio [HR] = 0.961, 95% confidence interval [95% CI]: 0.937 ~ 0.986, p = 0.002) and CD8 + T cells (HR = 0.026, 95%CI: 0.001 ~ 0.609, p = 0.023). The resultant nomogram had AUC values of 0.779 and 0.784 for 1- and 2-years predicted recurrence rates, respectively. The survival analysis revealed that patients with low CD8 + T cells counts or ADCp1 had higher recurrence rates than those with high CD8 + T cells counts or ADCp1. Subgroup analysis revealed that the AUC of nomogram for predicting 1-year and 2-year recurrence of WHO grade 1 and WHO grade 2 meningiomas was 0.872 (0.652) and 0.828 (0.751), respectively. CONCLUSIONS: Preoperative ADC histogram parameters and tumor-infiltrating CD8 + T cells may be potential biomarkers in predicting meningioma recurrence risk. CLINICAL RELEVANCE STATEMENT: The findings will improve prognostic accuracy for patients with meningioma and potentially allow for targeted treatment of individuals who have the recurrent form.

Prediction of O(6)-methylguanine-DNA methyltransferase promoter methylation status in IDH-wildtype glioblastoma using MRI histogram analysis.

To evaluate the utility of magnetic resonance imaging (MRI) histogram parameters in predicting O(6)-methylguanine-DNA methyltransferase promoter (pMGMT) methylation status in IDH-wildtype glioblastoma (GBM). From November 2021 to July 2023, forty-six IDH-wildtype GBM patients with known pMGMT methylation status (25 unmethylated and 21 methylated) were enrolled in this retrospective study. Conventional MRI signs (including location, across the midline, margin, necrosis/cystic changes, hemorrhage, and enhancement pattern) were assessed and recorded. Histogram parameters were extracted and calculated by Firevoxel software based on contrast-enhanced T1-weighted images (CET1). Differences and diagnostic performance of conventional MRI signs and histogram parameters between the pMGMT-unmethylated and pMGMT-methylated groups were analyzed and compared. No differences were observed in the conventional MRI signs between pMGMT-unmethylated and pMGMT-methylated groups (all p > 0.05). Compared with the pMGMT-methylated group, pMGMT-unmethylated showed a higher minimum, mean, Perc.01, Perc.05, Perc.10, Perc.25, Perc.50, and coefficient of variation (CV) (all p < 0.05). Among all significant CET1 histogram parameters, minimum achieved the best distinguishing performance, with an area under the curve of 0.836. CET1 histogram parameters could provide additional value in predicting pMGMT methylation status in patients with IDH-wildtype GBM, with minimum being the most promising parameter.