Correlation between spleen density and prognostic outcomes in patients with colorectal cancer after curative resection.

OBJECTIVE: The objective of this study was to investigate the correlation between spleen density and the prognostic outcomes of patients who underwent curative resection for colorectal cancer (CRC). METHODS: The clinical data of patients who were diagnosed with CRC and underwent radical resection were retrospectively analyzed. Spleen density was determined using computed tomography. Analysis of spleen density in relation to overall survival (OS) and disease-free survival (DFS) utilizing the Kaplan-Meier method. Univariate and multivariate Cox regression models were used to screen for independent prognostic factors, and a nomogram was constructed to predict OS and DFS. Moreover, internally validated using a bootstrap resamplling method. RESULTS: Two hundred twelve patients were included, of whom 23 (10.85%) were defined as having a diffuse reduction of spleen density (DROSD) based on diagnostic cutoff values (spleen density≦37.00HU). Kaplan-Meier analysis indicated that patients with DROSD had worse OS and DFS than those non-DROSD (P < 0.05). Multivariate Cox regression analysis revealed that DROSD, carbohydrate antigen 199 (CA199) > 37 U/mL, tumor node metastasis (TNM) stage III-IV, laparoscopy-assisted operation and American Society of Anesthesiology (ASA) score were independent risk factors for 3-year DFS. DROSD, CA199 > 37 U/mL, TNM stage III-IV, hypoalbuminemia, laparoscopy-assisted operation and ASA score were chosen as predictors of for 3-year OS. Nomograms showed satisfactory accuracy in predicting OS and DFS using calibration curves, decision curve analysis and bootstrap resamplling method. CONCLUSION: Patients with DROSD who underwent curative resection have worse 3-year DFS and OS. The nomogram demonstrated good performance, particularly in predicting 3-year DFS with a net clinical benefit superior to well-established risk calculator.

Deep learning prediction of esophageal squamous cell carcinoma invasion depth from arterial phase enhanced CT images: a binary classification approach.

BACKGROUND: Precise prediction of esophageal squamous cell carcinoma (ESCC) invasion depth is crucial not only for optimizing treatment plans but also for reducing the need for invasive procedures, consequently lowering complications and costs. Despite this, current techniques, which can be invasive and costly, struggle with achieving the necessary precision, highlighting a pressing need for more effective, non-invasive alternatives. METHOD: We developed ResoLSTM-Depth, a deep learning model to distinguish ESCC stages T1-T2 from T3-T4. It integrates ResNet-18 and Long Short-Term Memory (LSTM) networks, leveraging their strengths in spatial and sequential data processing. This method uses arterial phase CT scans from ESCC patients. The dataset was meticulously segmented by an experienced radiologist for effective training and validation. RESULTS: Upon performing five-fold cross-validation, the ResoLSTM-Depth model exhibited commendable performance with an accuracy of 0.857, an AUC of 0.901, a sensitivity of 0.884, and a specificity of 0.828. These results were superior to the ResNet-18 model alone, where the average accuracy is 0.824 and the AUC is 0.879. Attention maps further highlighted influential features for depth prediction, enhancing model interpretability. CONCLUSION: ResoLSTM-Depth is a promising tool for ESCC invasion depth prediction. It offers potential for improvement in the staging and therapeutic planning of ESCC.

The psoas muscle density as a predictor of postoperative complications in elderly patients undergoing rectal cancer resection.

Background: Muscle depletion that impairs normal physiological function in elderly patients leads to poor prognosis. This study aimed to evaluate the association between total abdominal muscle area (TAMA), total psoas area (TPA), psoas muscle density (PMD), and short-term postoperative complications in elderly patients with rectal cancer. Methods: All elderly patients underwent rectal cancer resection with perioperative abdominal computed tomography (CT). Complications were assessed according to the Clavien-Dindo classification. Severe complications were defined as grade III-V following the Clavien-Dindo classification. Univariate and multivariate analyses were performed to evaluate risk factors of short-term severe postoperative complications. Results: The cohort consisted of 191 patients with a mean age of 73.60 ± 8.81 years. Among them, 138 (72.25%) patients had Clavien-Dindo 0- II, 53 (27.75%) patients had severe postoperative complications (Clavien-Dindo III-V), and 1(0.52%) patient died within 30 days of surgery. PMD was significantly higher in the Clavien-Dindo 0-II cohort compared to the Clavien-Dindo III-V cohort (p=0.004). Nevertheless, TAMA and TPA failed to exhibit significant differences. Moreover, the multivariate regression analysis implied that advanced age [OR 1.07 95%CI (1.02-1.13) p=0.013], male [OR 5.03 95%CI (1.76-14.41) p=0.003], high charlson comorbidity index (CCI) score [OR 3.60 95%CI (1.44-9.00) p=0.006], and low PMD [OR 0.94 95%CI (0.88-0.99) p=0.04] were independent risk factors of Clavien-Dindo III-V. Conclusion: Preoperative assessment of the PMD on CT can be a simple and practical method for identifying elderly patients with rectal cancer at risk for severe postoperative complications.

T1-weighted images-based radiomics for structural lesions evaluation in patients with suspected axial spondyloarthritis.

PURPOSE: The aim of this study was to investigate the feasibility of radiomics based on T1-weighted images (T1WI) for assessing sacroiliac joint (SIJ) structural lesions in patients with suspected axial spondyloarthritis (axSpA). MATERIALS AND METHODS: A total of 266 patients with clinical suspicion of axSpA between December 2016 and January 2022 were enrolled. Structural lesions were assessed on low-dose CT (ldCT) and MRI, respectively. Radiomic features, extracted from SIJ T1WI, were included to generate the radiomics model. The performance of the radiomics model was evaluated using receiver operating characteristic (ROC) curve. Furthermore, point-biserial correlation analysis was used to interpret the associations between the radiomic feature and structural lesions. RESULTS: Using ldCT as the reference standard, the radiomics model showed favorable performance for detecting positive global structural lesions in the training cohort (AUC, 0.82 [95% CI: 0.76, 0.88]) and validation cohort (AUC, 0.82 [95% CI: 0.72, 0.91]. Experienced MRI raters yielded predictive AUCs of 0.73 (95% CI: 0.67, 0.79), and 0.74 (95% CI: 0.66, 0.83) in the training and validation cohort, respectively. The seven radiomic features included in the radiomics model showed significant correlation with different kinds of structural lesions (P all < 0.05). Among them, Wavelet.LHL_firstorder_90Percentile showed the strongest association with fat lesion (r = 0.48, P < 0.05). CONCLUSION: The radiomics analysis with T1WI could effectively detect SIJ structural lesions and achieved expert-level performance. Each radiomic feature was correlated with different structural lesions significantly, which might inform radiomic-based applications for axSpA intelligent diagnosis.

Prognostic value of LI-RADS category on MRI in patients with primary hepatic lymphoepithelioma-like carcinoma.

OBJECTIVES: To compare the clinical and MRI features of primary hepatic lymphoepithelioma-like carcinoma (LELC) categorized as LR-M or LR-4/5 using the Liver Imaging Reporting and Data System (LI-RADS) version 2018 and to determine the prognostic factors for recurrence-free survival (RFS). METHODS: In this retrospective study, 37 patients with surgically confirmed LELC were included. Two independent observers evaluated preoperative MRI features according to the LI-RADS version 2018. Clinical and imaging features were compared between two groups. RFS and the associated factors were evaluated using Cox proportional hazards regression analysis, Kaplan-Meier analysis, and log-rank test. RESULTS: In total, 37 patients (mean age, 58.5 ± 10.3 years) were evaluated. Sixteen (43.2%) LELCs were categorized as LR-M and twenty-one (56.8%) LELCs were categorized as LR-4/5. In the multivariate analysis, the LR-M category was an independent factor for RFS (HR 7.908, 95% CI 1.170-53.437; p = 0.033). RFS rates were significantly lower in patients with LR-M LELCs than in patients with LR-4/5 LELCs (5-year RFS rate, 43.8% vs.85.7%; p = 0.002). CONCLUSION: The LI-RADS category was significantly associated with postsurgical prognosis of LELC, with tumor categorized as LR-M having a worse RFS than those categorized as LR-4/5. KEY POINTS: • Lymphoepithelioma-like carcinoma patients categorized as LR-M have worse recurrence-free survival than those categorized as LR-4/5. • MRI-based LI-RADS categorization was an independent factor for postoperative prognosis of primary hepatic lymphoepithelioma-like carcinoma.

Role of spleen density in predicting postoperative complications in patients with acute mesenteric ischemia.

BACKGROUND: Acute mesenteric ischemia (AMI) is a life-threatening surgical emergency with a poor prognosis. This study assessed the association of diffuse reduction of spleen density (DROSD) with postoperative complications and identified risk factors for adverse outcomes in AMI patients after surgery. METHODS: Patients who were diagnosed with AMI and underwent surgical operations between April 2006 and July 2021 were enrolled. Spleen density was assessed using preoperative non-enhanced computed tomography. The lowest quartile of spleen density in all patients was regarded as the cutoff value for DROSD. Univariate and multivariate analyses were performed to determine the risk factors related to postoperative outcomes after surgery. RESULTS: According to the diagnostic cutoff, patients with a spleen density ≤49.07 HU were defined as DROSD. In a cohort of 97 patients, 34.0% developed complications within 30 days of surgery. The multivariate analysis illustrated that DROSD was an independent risk factor for prognostic outcomes in AMI patients after surgery. CONCLUSION: Patients with low spleen density were prone to postoperative complications. As an imaging method, preoperative assessment of spleen density is a novel predictor that can be used clinically to identify high-risk AMI patients with poor prognosis.

Can radiomics replace the SPARCC scoring system in evaluating bone marrow edema of sacroiliac joints in patients with axial spondyloarthritis?

OBJECTIVES: To develop an objective and efficient method based on radiomics to evaluate bone marrow edema (BMO) of sacroiliac joints (SIJs) by magnetic resonance imaging (MRI) in patients with axial spondyloarthritis (axSpA) and to compare with the Spondyloarthritis Research Consortium of Canada (SPARCC) scoring system. METHODS: From September 2013 to March 2022, patients with axSpA who underwent 3.0T SIJ-MRI were included and were randomly divided into training and validation cohorts at a ratio of 7:3. The optimal radiomics features selected from the SIJ-MRI in the training cohort were included to generate the radiomics model. The performance of the model was evaluated by ROC analysis and decision curve analysis (DCA). Rad scores were calculated using the radiomics model. The responsiveness was compared for Rad scores and SPARCC scores. We also assessed the correlation between the Rad score and SPARCC score. RESULTS: A total of 558 patients were finally included. The radiomics model showed favorable discrimination of a SPARCC score <2 or ≥2 both in the training (AUC, 0.90; 95% CI: 0.87-0.93) and validation cohorts (AUC, 0.90; 95% CI, 0.86-0.95). DCA confirmed that the model was clinically useful. Rad score showed higher responsiveness to treatment-related change than SPARCC score. Furthermore, a significant correlation was noted between the Rad score and SPARCC score when scoring the status of BMO (rs=0.80, P < 0.001), and a strong correlation was noted when scoring the change in BMO (r=0.70, P < 0.001). CONCLUSION: The study proposed a radiomics model to accurately quantify the BMO of SIJs in patients with axSpA, providing an alternative to the SPARCC scoring system. Key Points • The Rad score is an index with high validity for the objective and quantitative evaluation of bone marrow edema (BMO) of the sacroiliac joints in axial spondyloarthritis. • The Rad score is a promising tool to monitor the change of BMO upon treatment.

Role of Platelet to Lymphocyte Ratio and Red Cell Distribution Width in Predicting Postoperative Complications in Patients with Acute Mesenteric Ischemia.

BACKGROUND: The predictive values of the platelet to lymphocyte ratio (PLR) and red cell distribution width (RDW) have been demonstrated in different types of abdominal surgery. The aim of this study was to investigate the interest of the preoperative PLR and RDW as predictors of 30-day postoperative complications in patients with acute mesenteric ischemia (AMI). METHODS: Clinical data of 105 AMI patients were retrospectively reviewed. Postoperative complications were evaluated by the Clavien-Dindo classification. The cutoff values for neutrophil to lymphocyte ratio (NLR), PLR, and RDW were determined by receiver operating characteristic curves. Univariate and multivariate analyses evaluating the risk factors for postoperative complications were performed. RESULTS: In the univariate analyses, advanced age, female, anemia, high white blood cell (WBC), high PLR, high NLR, high RDW, Charlson comorbidity index (CCI) score ≥2, and bowel resection were associated with the postoperative complications. A multivariable analysis revealed that advanced age, high PLR, high RDW, and bowel resection were independent predictors of postoperative complications. CONCLUSIONS: The PLR and RDW might play important roles in evaluation of the risk of postoperative complications in AMI patients. The preoperative PLR and RDW are simple and useful predictors of postoperative complications in AMI patients.

The psoas muscle density as a predictor of postoperative complications and 30-day mortality for acute mesenteric ischemia patients.

OBJECTIVE: Low muscle mass and quality is associated with poor surgical outcomes. Psoas muscle density (PMD)is a validated surrogate for muscle quality that can be easily measured from a clinical computed tomography (CT) scan. The objective of this study was to investigate the association between PMD and short-term postoperative outcomes in patients with acute mesenteric ischemia (AMI). METHODS: From April 2006 and September 2019, the clinical data of all patients who underwent surgical intervention with a preoperative diagnosis of AMI and had preoperative non-contrast CT images available were retrospectively reviewed. PMD was measured by CT at the third lumbar vertebra. The lowest quartile of PMD for men and women in all patients was used as sex-specific cut-off values for low PMD. Univariate and multivariate analyses evaluating risk factors of postoperative complications and 30-day mortality were performed. RESULTS: The cohort consisted of 88 patients with a mean age of 58.8 ± 16.2 years, of whom 21 (23.9%) patients had low PMD based on the diagnostic cut-off values (40.5 HU for men and 28.4 HU for women), 35 (39.8%) patients developed complications within 30 days of the operation, and 10 (11.3%) patients died within 30 days of surgery. Low PMD patients had a higher risk of postoperative complications and 30-day mortality than patients without low PMD patients. In a multivariate analysis, low PMD and low psoas muscle area (PMA) were independent predictors of postoperative complications. However, only low PMD remained an independent risk factor for 30-day mortality. CONCLUSIONS: Preoperative assessment of the PMD on CT can be a practical method for identifying AMI patients at risk for postoperative complications and 30-day mortality.

A predictive clinical-radiomics nomogram for diagnosing of axial spondyloarthritis using MRI and clinical risk factors.

OBJECTIVES: Construct and validate a nomogram model integrating the radiomics features and the clinical risk factors to differentiating axial spondyloarthritis (axSpA) in low back pain patients undergone sacroiliac joint (SIJ)-MRI. METHODS: A total of 638 patients confirmed as axSpA (n = 424) or non-axSpA (n = 214) who were randomly divided into training (n = 447) and validation cohorts (n = 191). Optimal radiomics signatures were constructed from the 3.0 T SIJ-MRI using maximum relevance-minimum redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) algorithm in the training cohort. We also included six clinical risk predictors to build the clinical model. Incorporating the independent clinical factors and Rad-score, a nomogram model was constructed by multivariable logistic regression analysis. The performance of the clinical, Rad-score, and nomogram models were evaluated by ROC analysis, calibration curve and decision curve analysis (DCA). RESULTS: A total of 1316 features were extracted and reduced to 15 features to build the Rad-score. The Rad-score allowed a good discrimination in the training (AUC, 0.82; 95% CI: 0.77, 0.86) and the validation cohort (AUC, 0.82; 95% CI: 0.76, 0.88). The clinical-radiomics nomogram model also showed favourable discrimination in the training (AUC, 0.90; 95% CI: 0.86, 0.93) and the validation cohort (AUC, 0.90; 95% CI: 0.85, 0.94). Calibration curves (P >0.05) and DCA demonstrated the nomogram was useful for axSpA diagnosis in the clinical environment. CONCLUSION: The study proposed a radiomics model was able to separate axSpA and non-axSpA. The clinical-radiomics nomogram can increase the efficacy for differentiating axSpA, which might facilitate clinical decision-making process.

MicroRNA-151 Attenuates Apoptosis of Endothelial Cells Induced by Oxidized Low-density Lipoprotein by Targeting Interleukin-17A (IL-17A).

Apoptosis of endothelial cells plays an important role in atherosclerosis (AS). MicroRNAs (miRNAs) have been confirmed to participate in the process of endothelial cell apoptosis. The main purpose of this study was to investigate the mechanism of miR-151 and interleukin-17A (IL-17A) in apoptosis of atherosclerotic endothelial cells. The expression levels of miR-151 in human aortic endothelial cells (HAEC) after Ox-LDL treatment were detected by qRT-PCR. The expression levels of IL-17A were detected by qRT-PCR and Western blot. The effects of miR-151 and IL-17A on the apoptosis rate were detected by flow cytometry. The relationship between miR-151 and IL-17A was assessed by bioinformatics analysis and luciferase assay. The expression levels of miR-151 in HAEC after Ox-LDL treatment were reduced, and the expression of IL-17A was upregulated. MiR-151 and si-IL-17A inhibited the apoptosis rate of aortic endothelial cells treated by Ox-LDL. MiR-151 and si-IL-17A reduced the expression levels of c-caspase-9, c-caspase-3, and BAX proteins in Ox-LDL-treated HAEC and increased the expression levels of Bcl-2. MiR-151 inhibited the apoptosis of endothelial cells in AS, and IL-17A was a new target for miR-151. Our findings provided a potential treatment for atherosclerosis in the treatment of AS. Graphical abstract.

Role of Frailty and Comorbidity Status in Predicting Morbidity and Mortality in Patients with Acute Mesenteric Ischemia.

BACKGROUND: This study was performed to determine the association of frailty and comorbidity status with postoperative morbidity and mortality in patients with acute mesenteric ischemia (AMI). METHODS: Patients diagnosed with AMI between April 2006 and September 2019 were enrolled in this study. Frailty was evaluated by sarcopenia which was diagnosed by third lumbar vertebra psoas muscle area (PMA). Comorbidity status was evaluated by the Charlson Comorbidity Index (CCI) score. Univariate and multivariate analyses evaluating the risk factors for postoperative morbidity and mortality were performed. RESULTS: Of the 174 patients, 86 were managed conservatively and 88 underwent surgery. In surgically managed patients, 39.8% developed complications within 30 days of surgery. Ten patients died within 30 days of the operation. In the univariate analyses, white blood cell >10 g/L, low PMA, CCI score ≥2, and bowel resection were associated with postoperative complications. Multivariate analysis revealed that low PMA, CCI score ≥2, and bowel resection were independent predictors of postoperative complications. CONCLUSIONS: This study demonstrated that low PMA, CCI score ≥2, and bowel resection were independent risk factors for postoperative complications in patients with AMI. Preoperative assessment of frailty using PMA and the evaluation of comorbidity status using CCI may serve as helpful tools in preoperative risk assessment and should be integrated into scoring systems for surgically treated AMI.

Prediction of lymph node metastasis by PET/CT metabolic parameters in patients with esophageal squamous cell carcinoma.

OBJECTIVE: The aim of this study was to investigate the capability of F-FDG PET/computed tomography (CT)-related metabolic parameters to predict lymph node metastasis (LNM) and occult lymph node metastasis (OLNM) in patients with esophageal squamous cell carcinoma (ESCC). METHODS: Totally 84 patients undergoing curative esophagectomy with lymph node dissection were enrolled in this study. Metabolic tumor volume (MTV) was measured using threshold-based methods with a threshold of 40% maximum standardized uptake value (SUVmax). The derivative of the volume (V)-threshold (T) function (volume difference/threshold difference) was defined as the heterogeneity factor (HF). In addition, SUVmax, SUVmean, total lesion glycolysis (TLG), maximum tumor-to-blood SUV ratio (SURmax), SURmean and several clinicopathologic parameters were analyzed to identify risk factors of LNM and OLNM. RESULTS: SUVmax, SUVmean, MTV, TLG, SURmax, SURmean and HF were significantly different between LNM (+) and LNM (-). The optimal cut-off values of those parameters were 12.5, 8.34, 15.01, 117.185, 7.885, 4.855 and 0.300, respectively. Logistic regression analysis showed that MTV (OR = 1.127, P = 0.04) and SURmax (OR = 1.446, P = 0.004) were independent predictors of LNM, with sensitivity and specificity were 51.2%, 83.7% vs. 53.7%, 79.1%. In univariate and multivariate analysis, MTV was the sole parameter associated with OLMN (P = 0.024). CONCLUSION: MTV and SURmax were statistically significant predictors of LNM in patients with ESCC, while MTV was a predictor of OLNM. High SURmax and MTV may indicate that the treatment planning should be tailored, which may improve patient prognosis.

Spectral CT Analysis of Solitary Pulmonary Nodules for Differentiating Malignancy from Benignancy: The Value of Iodine Concentration Spatial Distribution Difference.

OBJECTIVE: The objective is to assess the value of spatial distribution difference in iodine concentration between malignant and benign solitary pulmonary nodules (SPNs) by analyzing multiple parameters of spectral CT. METHODS: Sixty patients with 39 malignant nodules and 21 benign nodules underwent chest contrast CT scans using spectral imaging mode during pulmonary arterial phase (PP), arterial phase (AP), and venous phase (VP). Iodine concentrations of proximal and distal regions in pulmonary nodules on iodine-based material decomposition images were recorded. Normalized iodine concentration (NIC) and the differences in NIC between the proximal and the distal regions (dNIC) were calculated. The two-sample t-test and Mann-Whitney U-test were performed to compare the multiple parameters generated from spectral CT between malignant and benign nodules. Receiver operating characteristic (ROC) curves were generated to calculate sensitivity and specificity. RESULTS: NIC in the proximal region (NICpro) and NIC in the distal region (NICdis) between malignant and benign nodules at AP (NICpro, P=0.012; NICdis, P=0.024), and VP (NICpro, P=0.005; NICdis, P =0.004) were significantly different. NICpro at PP (P = 0.037) was also found significantly different between malignant and benign nodules; however, no significant differences were found in NICdis at PP (P = 0.093). In addition, the dNIC of malignant nodules was significantly higher than that of benign ones at PP (median and interquartiles (0.31, 0.11, 0.57 versus -0.26, -0.5, -0.1); p≤0.001), AP (mean dNIC, 0.093 ±0.094 versus -0.075±0.060; p≤0.001), and VP (mean dNIC, 0.171±0.137 versus -0.183±0.127; p≤0.001). The sensitivity and specificity (93%, 95%, respectively) of dNIC during VP were higher than other parameters, with a threshold value of -0.07. CONCLUSIONS: Spectral CT imaging with multiple parameters such as NICpro, NICdis, and dNIC may be a new method for differentiating malignant SPNs from benign ones.