Impact of Metastatic Lymph Node Ratio on Survival and Prognosis in Rectal Carcinoma: A Retrospective Cohort Study.

Objective This study aimed to evaluate the impact of the metastatic lymph node ratio (mtLNR) on survival outcomes and prognosis in patients with rectal carcinoma, in comparison with other clinicopathological factors. Methods A retrospective cohort analysis was conducted on 97 patients with rectal adenocarcinoma who underwent surgical treatment at Erol Olçok Training and Research Hospital between January 2017 and December 2022. The inclusion criteria consisted of patients over 18 years of age and the absence of hematological disorders or concurrent inflammatory conditions. The patients' demographic data, tumor characteristics, surgical details, lymph node (LN) status, mtLNR, and survival outcomes were analyzed. The optimal cutoff value of mtLNR for predicting mortality was determined using receiver operating characteristic (ROC) curve analysis. Kaplan-Meier survival analysis was employed to estimate overall survival (OS) and disease-free survival (DFS), and differences between groups were evaluated using the log-rank test. The Cox proportional hazards model was used to calculate hazard ratios (HRs) for all-cause mortality. Statistical significance was set at p<0.05. Results The mean age of the patients was 70.31 ± 11.57 years, with 65.98% being male. Low anterior resection (LAR) was performed in 83.51% of the patients, and laparoscopic surgery was conducted in 26.8%. The median OS for the entire cohort was 24 months (range: 3-60). Patients were divided into two groups based on mtLNR, with the cutoff value set at 0.2183. A high mtLNR was significantly associated with poorer DFS and OS (p=0.021 and p=0.003, respectively). Moreover, patients with an mtLNR>0.2183 exhibited significantly higher rates of recurrence, lymphovascular invasion (LVI), and perineural invasion (PNI) compared to those with a lower mtLNR (all p<0.001). The optimal cutoff value of mtLNR predicted mortality with a specificity of 81.4% and a sensitivity of 48.1% (area under the curve (AUC) 0.662, p=0.012). Kaplan-Meier analysis showed a significant difference in survival between the two groups; the risk of all-cause mortality was 3.71 times higher in patients with mtLNR>0.2183 (p=0.002). Conclusion The mtLNR is a strong determinant of survival and prognosis in patients with rectal carcinoma. High mtLNR values are associated with worse survival outcomes and more aggressive tumor characteristics. The findings suggest that mtLNR should be considered in clinical decision-making processes. These results indicate that mtLNR could be a valuable prognostic tool in clinical decision-making.

PET radiomics-based lymphovascular invasion prediction in lung cancer using multiple segmentation and multi-machine learning algorithms.

The current study aimed to predict lymphovascular invasion (LVI) using multiple machine learning algorithms and multi-segmentation positron emission tomography (PET) radiomics in non-small cell lung cancer (NSCLC) patients, offering new avenues for personalized treatment strategies and improving patient outcomes. One hundred and twenty-six patients with NSCLC were enrolled in this study. Various automated and semi-automated PET image segmentation methods were applied, including Local Active Contour (LAC), Fuzzy-C-mean (FCM), K-means (KM), Watershed, Region Growing (RG), and Iterative thresholding (IT) with different percentages of the threshold. One hundred five radiomic features were extracted from each region of interest (ROI). Multiple feature selection methods, including Minimum Redundancy Maximum Relevance (MRMR), Recursive Feature Elimination (RFE), and Boruta, and multiple classifiers, including Multilayer Perceptron (MLP), Logistic Regression (LR), XGBoost (XGB), Naive Bayes (NB), and Random Forest (RF), were employed. Synthetic Minority Oversampling Technique (SMOTE) was also used to determine if it boosts the area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE). Our results indicated that the combination of SMOTE, IT (with 45% threshold), RFE feature selection and LR classifier showed the best performance (AUC = 0.93, ACC = 0.84, SEN = 0.85, SPE = 0.84) followed by SMOTE, FCM segmentation, MRMR feature selection, and LR classifier (AUC = 0.92, ACC = 0.87, SEN = 1, SPE = 0.84). The highest ACC belonged to the IT segmentation (with 45 and 50% thresholds) alongside Boruta feature selection and the NB classifier without SMOTE (ACC = 0.9, AUC = 0.78 and 0.76, SEN = 0.7, and SPE = 0.94, respectively). Our results indicate that selection of appropriate segmentation method and machine learning algorithm may be helpful in successful prediction of LVI in patients with NSCLC with high accuracy using PET radiomics analysis.

Distribution characteristics of immune infiltration and lymphovascular invasion in patients with breast cancer skin recurrence.

BACKGROUND: To assess the distribution characteristics of immune infiltration and lymphovascular invasion in breast cancer skin recurrence patients. METHODS: We retrospectively analyzed the clinicopathological data of patients who underwent radical surgery for primary breast cancer and experienced skin recurrence between January 2001 and April 2019. Immune and lymphovascular biomarkers were quantified in primary breast cancers, skin lesions and visceral metastatic lesions. Differences in biomarkers distribution between matched tissues were statistically analyzed using the Wilcoxon signed-rank test and Kruskal-Wallis one-way ANOVA. RESULTS: A total of 71 female breast cancer patients were reviewed in this study. Our study found that the expression levels of various lymphocyte immune markers in primary tumor specimens were higher than those in skin recurrences. The expression of CD8, CD57 and CD31 in primary breast cancer was higher than those in the skin. Compared to visceral metastatic lesions, D2-40 was highly expressed in the skin, while CD8 tended to decrease. In the skin specimens, the expression of CD8 (P < 0.001), FOXP3 (P = 0.006) and CD68 (P < 0.001) in the intratumoral area was higher, while the expression of CD57 (P < 0.001) was higher in the peritumoral area. Analyzing specimens from the same patient at different time points of skin progression, it was found that the expression of peritumoral CD4 decreased (P = 0.044) as the disease progressed. The low expression of D2-40 and CD163 in the skin lesions suggested a decrease in DFS. CONCLUSION: The immune microenvironment of breast cancer skin recurrence may be in a state of suppression, and this suppression may intensify with disease progression. The pattern of skin recurrence may be more inclined toward lymphatic invasion. Our study provides new insights into the biological behaviors of this disease and its response to immunotherapy.

LVI-PathNet: Segmentation-classification pipeline for detection of lymphovascular invasion in whole slide images of lung adenocarcinoma.

Lymphovascular invasion (LVI) in lung cancer is a significant prognostic factor that influences treatment and outcomes, yet its reliable detection is challenging due to interobserver variability. This study aims to develop a deep learning model for LVI detection using whole slide images (WSIs) and evaluate its effectiveness within a pathologist's information system. Experienced pathologists annotated blood vessels and invading tumor cells in 162 WSIs of non-mucinous lung adenocarcinoma sourced from two external and one internal datasets. Two models were trained to segment vessels and identify images with LVI features. DeepLabV3+ model achieved an Intersection-over-Union of 0.8840 and an area under the receiver operating characteristic curve (AUC-ROC) of 0.9869 in vessel segmentation. For LVI classification, the ensemble model achieved a F1-score of 0.9683 and an AUC-ROC of 0.9987. The model demonstrated robustness and was unaffected by variations in staining and image quality. The pilot study showed that pathologists' evaluation time for LVI detecting decreased by an average of 16.95%, and by 21.5% in "hard cases". The model facilitated consistent diagnostic assessments, suggesting potential for broader applications in detecting pathological changes in blood vessels and other lung pathologies.

Prediction of lymphovascular invasion of gastric cancer based on contrast-enhanced computed tomography radiomics.

Background: Lymphovascular invasion (LVI) is a significant risk factor for lymph node metastasis in gastric cancer (GC) and is closely related to the prognosis and recurrence of GC. This study aimed to establish clinical models, radiomics models and combination models for the diagnosis of GC vascular invasion. Methods: This study enrolled 146 patients with GC proved by pathology and who underwent radical resection of GC. The patients were assigned to the training and validation cohorts. A total of 1,702 radiomic features were extracted from contrast-enhanced computed tomography images of GC. Logistic regression analyses were performed to establish a clinical model, a radiomics model and a combined model. The performance of the predictive models was measured by the receiver operating characteristic (ROC) curve. Results: In the training cohort, the age of LVI negative (-) patients and LVI positive (+) patients were 62.41 ± 8.41 and 63.76 ± 10.08 years, respectively, and there were more male (n = 63) than female (n = 19) patients in the LVI (+) group. Diameter and differentiation were the independent risk factors for determining LVI (-) and (+). A combined model was found to be relatively highly discriminative based on the area under the ROC curve for both the training (0.853, 95% CI: 0.784-0.920, sensitivity: 0.650 and specificity: 0.907) and the validation cohorts (0.742, 95% CI: 0.559-0.925, sensitivity: 0.736 and specificity: 0.700). Conclusions: The combined model had the highest diagnostic effectiveness, and the nomogram established by this model had good performance. It can provide a reliable prediction method for individual treatment of LVI in GC before surgery.

Snail Expression as a Prognostic Factor in Colorectal Adenocarcinoma.

OBJECTIVE: The aim of this study was to analyze the expression of Snail in the colorectal adenocarcinoma. METHODS: This study used a cross-sectional design. Seventy four paraffin embedded block of Colorectal Adenocarcinoma were assessed using Snail rabbit polyclonal antibody and their expression were performed using Olympus CX-43 light microscope. The relationship between Snail expression with histopathological grading, tumor budding grading, lymphovascular invasion and metastases of colorectal adenocarcinoma ability were statistically analyzed by Mann Whitney tests and presented in tables using SPSS 27. RESULT: From 74 samples examined, in samples with low grade tumor budding (n=11), there were 9 samples (81.8%) with weak expression, while those with strong expression were 2 samples (18.2%). In samples with intermediate grade tumor budding (n=28), there were 17 samples (60.7%) with weak expression, while those with strong expression were 11 samples (39.3%). In samples with high grade tumor budding (n=35), there were 13 samples (37.1%) with weak expression, while those with strong expression were 22 samples (62.9%). In samples with lymphovascular invasion (n=14), there were 10 samples (71.4%) with strong expression, while those with weak expression were 4 samples (28.6%). In samples with metastases (n=23), there were 16 samples (69.6%) with strong expression, while those with weak expression were 7 samples (30.4%). There was a significant relationship between the expression of Snail with tumor budding grade (p=0.003), lymphovascular invasion and metastases (p=<0.001), but there was no significant relationship with histopathological grade (p=0.942). CONCLUSION: The Snail expression can be used as a prognostic factor in colorectal adenocarcinoma.

Can negative axillary ultrasound reliably predict pathologically negative axillary lymph node status in breast cancer patients with cT ≤3 cm, cN0, and HER2-positive?-a retrospective, single-institution study.

Background: Breast cancer (BC) is the leading cancer in women globally, with human epidermal growth factor receptor 2 (HER2)-positive subtype accounting for 15-20% of cases and exhibiting aggressive behavior. The standard of care for operable BC has evolved to include neoadjuvant systemic therapy, which can guide treatment decisions and improve outcomes, particularly in HER2+ BC. This study aims to investigate whether axillary ultrasound has a good negative predictive value (NPV) for early HER2 BC patients and to identify clinicopathological factors that can impact the axillary lymph node metastasis. Methods: This retrospective, single-center study evaluated the medical records of 135 patients with HER2+ BC, cT ≤3 cm, and clinically negative axillary lymph nodes from 2018 to 2020. The study aimed to determine the NPV of axillary ultrasound for pathologically negative axillary lymph node status and to identify factors associated with axillary lymph node metastasis. Results: The NPV of axillary ultrasound was 78.5%, increasing to 89.6% and 93.3% when considering 0-1 and 0-2 metastatic lymph nodes, respectively. Lymphovascular invasion (LVI) was significantly associated with axillary lymph node metastasis, with a 2.2-fold increased risk. Conclusions: Axillary ultrasound shows good predictive value for axillary lymph node negativity in HER2+ BC patients with small tumors. However, the presence of LVI increases the risk of metastasis, suggesting a need for neoadjuvant chemotherapy. These findings contribute to personalized treatment strategies for early HER2+ BC, emphasizing the role of axillary ultrasound in clinical decision-making.

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.

Targeted Inhibition of Lymphovascular Invasion Formation with CREKA Peptide-Modified Silicasomes to Boost Chemotherapy in Bladder Cancer.

Despite its significant clinical efficacy as a first-line treatment for advanced bladder cancer, cisplatin-based chemotherapy provides a limited benefit for patients with lymphovascular invasion (LVI), which is characterized by the presence of tumor emboli within blood vessels and associated with enhanced cisplatin resistance and metastatic potential. Notably, platelets, a critical component of LVI, hinder the delivery of chemotherapeutic agents to tumors and facilitate metastasis. Consequently, platelet function inhibition holds the potential to disrupt LVI formation, as well as augment the antitumor activity of cisplatin. Herein, we developed a tumor microenvironment-targeted nanodrug with lipid-coated mesoporous silica nanoparticles (silicasomes) that synergistically combines cisplatin with an antiplatelet agent, tirofiban, for bladder cancer treatment. The customized nanodrug can concurrently prevent LVI formation and enhance the chemotherapeutic efficacy without significant adverse effects. This study supports the integration of chemotherapy and antiplatelet therapy via a silicasome-based nanosystem as a highly promising strategy for bladder cancer management.

Spermatocytic tumor with extensive lymphovascular invasion in a young male.

Spermatocytic tumors are rare testicular cancers, accounting for less than 1 % of all testicular neoplasms, usually affecting older men. This report details a 35-year-old male with a spermatocytic tumor featuring extensive lymphovascular invasion. The patient had a painless, slow-growing right testicular mass, with normal serum tumor markers. Ultrasound and CT scans suggested malignancy. Post-orchiectomy, histopathology confirmed a spermatocytic tumor with polymorphic cells and lymphovascular invasion. Immunohistochemical staining was positive for SALL4 and CD117, negative for OCT4, AFP, and CD30. The patient underwent chemotherapy and remained recurrence-free for a year, highlighting the need for accurate diagnosis and long-term monitoring.

Triple Positive Oral Squamous Cell Carcinoma Patients Predict Poor Survival Outcomes: Multiple Factor Positivity Warrants the Need for Modified Treatment Approaches.

Objectives: The presence of lymphovascular invasion (LVI), perineural invasion (PNI) and extranodal extension (ENE) have shown adverse outcomes in oral squamous cell carcinoma (OSCC). This study evaluated the impact of LVI, PNI and ENE, individually and in combination, on survival outcomes in OSCC. Material and Methods: A retrospective analysis of a prospectively maintained oral cancer database was done from January 2017 to March 2023. All consecutive OSCC patients who underwent curative intent surgery were included. The triple-positive group was defined by the presence of all three features (LVI/PNI/ENE), while the double-positive group had the presence of two features. The disease-free survival (DFS) and overall survival (OS) analysis was done between different study groups. Results: A total of 255 patients were included in the analysis. The LVI, PNI and ENE positivity was 13%, 26% and 11%, respectively. There were 19 patients (7%) with double-positive and ten patients (4%) with triple-positive disease. The triple-positive group had lower DFS than non-triple-positive (0% vs 57%, p-value 0.001) and lower OS (0% vs 72%, p-value 0.003). The median DFS and OS of the triple-positive group were eight months and 24 months, respectively. Similarly, the double-positive group also had statistically significant inferior DFS (p-value 0.007) and OS (p-value 0.002) compared to the single-positive/triple-negative group. Conclusion: The triple-positive disease had poor outcomes, with no patients achieving disease-free or overall survival at the 5-year follow-up. The presence of multiple adverse factors necessitates modification of adjuvant therapy and therapeutic strategy, which may enhance survival outcomes.

Multiphases DCE-MRI Radiomics Nomogram for Preoperative Prediction of Lymphovascular Invasion in Invasive Breast Cancer.

RATIONALE AND OBJECTIVES: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) radiomics had been used to evaluate lymphovascular invasion (LVI) in patients with breast cancer. However, no studies had explored the associations between features from delayed phase as well as multiphases DCE-MRI and the LVI status. Thus, we aimed to develop an efficient nomogram based on multiphases DCE-MRI to predict the LVI status in invasive (IBC) breast cancer patients. MATERIALS AND METHODS: A retrospective analysis was conducted on preoperative clinical, pathological, and DCE-MRI data of 173 breast cancer patients. All patients were randomly assigned into training set (n=121) and validation set (n=52) in 7:3 ratio. The clinical, pathologic, and conventional MRI characteristics were then subjected to univariate and multivariate logistic regression analysis, and the clinical risk factors with P < 0.05 in the multivariate logistic regression were used to build clinical models. Different single-phase models (early phase, peak phase, and terminal phase), as well as a multiphases model integrating radiomics features from multiple phases, were established. Furthermore, a preoperative radiomics nomogram model was constructed by combining the rad-score of the multiphases model with clinicopathologic independent risk factors. Finally, the performance of the multiphases model, clinical model, and rad-score was compared using receiver operating characteristic (ROC) curves, area under the curve (AUC) values, and decision curve analysis (DCA). The clinical utility of the rad-score was evaluated using calibration curves, and Delong test was used to compare the differences in AUC values among the different models. RESULTS: The axillary lymph nodes (ALN) status and Ki-67 had been identified as clinicopathologic independent predictors and a clinical model had been constructed. Image features that were extracted from the terminal phase of the DCE-MRI exhibited notably superior predictive performances compared to features from the other single phases. Particularly, in the multiphases model, terminal phase features were identified as potentially providing more predictive information. Among the nine features that were found to be associated with LVI in the multiphase model, one was derived from the early phase, two from the peak phase, and six from the terminal phase, indicating that terminal phase features contributed significantly more information towards predicting LVI. Evaluation of the nomogram performance revealed promising results in both the training set (AUCs: clinical model vs. multiphase model vs. nomogram=0.734 vs. 0.840 vs. 0.876) and the validation set (AUCs: clinical model vs. multiphase model vs. nomogram=0.765 vs. 0.753 vs. 0.832). CONCLUSION: The DCE-MRI-based radiomics model demonstrated utility in predicting LVI status, features of the terminal phase offered more valuable information particularly. The preoperative radiomics nomogram enhanced the diagnostic capability of identifying LVI status in IBC patients, and might aid clinicians in making personalized treatment decisions.

Molecular expression of Forkhead Box C2 gene (FOXC2) and Prospero homeobox gene (PROX-1) in oral squamous carcinoma and their correlation with clinicopathological parameters: A prospective cohort study.

Background: Forkhead box C2 gene (FOXC2) acts as an epithelial-mesenchymal transition (EMT) inducer while Prospero homeobox 1 gene (PROX-1) function as a regulator of lymphangiogenesis and angiogenesis in oral squamous cell carcinoma (OSCC). It is presumed that PROX-1 has both tumour-suppressive and oncogenic effects. The main aim of this study is to evaluate the role of PROX-1 and FOXC2 in the invasion and progression of OSCC cases and to correlate their expression with various histopathological parameters. Materials and Methods: A prospective cohort study was conducted in a total sample size of 52 OSCC tissues and histologically tumour-free margins of 20. mRNA expression and protein levels of FOXC2 and PROX-1 were evaluated using real-time PCR and sandwich enzyme-linked immunosorbent assay techniques. Chi-square analysis and correlation analysis were done. Kaplan-Meier analysis evaluated the survival rate. Results: Mean Ct values of FOXC2 were 1.915 ± 0.519 and PROX-1 was 0.061 ± 0.173. There was a significant 2-fold increase in the FOXC2 expression and a 0.5-fold decrease in the PROX-1 expression in OSCC tissue. Increased levels of FOXC2 protein and decreased levels of PROX-1 with a mean difference of 1.64 ± 0.73 ng/ml and 1.27 ± 0.33 ng/ml were observed in OSCC compared to histologically tumour-free margins. A significant positive correlation was found between the FOXC2 expression and clinicopathological parameters such as staging, perineural invasion (PNI) and lymphovascular invasion (LVI) whereas PROX-1 showed a significant negative correlation with histopathological parameters such as staging, PNI, LVI and tumour staging. There was a significant positive correlation between the PROX-1 and histologically tumour-free margins in disease-free survival patients (P-value = 0.03). Conclusion: FOXC2 and PROX-1 expressions were correlated with lymphovascular invasion, OSCC tumour staging and PNI. Thus, FOXC2 and PROX-1 could be possible therapeutic targets in the treatment of OSCC that can inhibit the EMT in OSCC and thereby favouring a better prognosis.

Correlation Between the Number of Pathological Risk Factors and Postoperative Prognosis in Patients with Stage I Lung Adenocarcinoma.

BACKGROUND: Although visceral pleural invasion, lymphovascular invasion, tumor spread through air spaces, and poor differentiation are pathological risk factors associated with unfavorable prognosis in patients with lung adenocarcinoma, the cumulative impact of these factors on prognosis remains unclear. METHODS: We enrolled 1532 patients with stage I lung adenocarcinoma. Patients were divided according to the number of risk factors as follows: Group A (without risk factors), Group B (one risk factor), and Group C (multiple risk factors). Moreover, we stratified patients into two subgroups based on tumor size (≤ 3 cm, 3-4 cm). Kaplan-Meier analysis was used to evaluate 5-year disease-free survival (DFS) and overall survival (OS). RESULTS: Overall, 949, 404, and 179 patients were included in Groups A, B, and C, respectively. Group C had a larger tumor size and more cases of extrathoracic recurrence than the other groups. The 5-year DFS and OS gradually decreased across Groups A to C (DFS: 94.3%, 80.6%, and 64.3%, respectively, p < 0.001; OS: 97.2%, 92.7%, and 77%, respectively, p < 0.001). A similar trend was observed for tumors ≤ 3 cm in size (DFS: 95.2%, 83.2%, and 68.5%, respectively, p < 0.001; OS: 97.6%, 94.1%, and 79.6%, respectively, p < 0.001), but a less pronounced trend was observed for tumors between 3 and 4 cm in size (DFS: 72.1, 60.8, and 43.3%, respectively, p = 0.054; OS: 85.7, 82.1, and 64.7%, respectively, p = 0.16). CONCLUSIONS: Postoperative survival worsened with increasing pathological risk factors in patients with stage I lung adenocarcinoma, especially those with tumor size ≤ 3 cm.

Lymphovascular invasion in colorectal cancers: can we predict it preoperatively?

PURPOSE: This study aimed to investigate preoperative predictors of lymphovascular invasion (LVI), which is a poor prognostic factor usually detected postoperatively in patients with colorectal cancer. METHODS: Results for all patients operated on for colorectal cancer between January 1, 2006, and December 31, 2021, were retrospectively analyzed. Potential preoperative factors and postoperative pathology results were recorded. The patients were categorized as those with LVI and those without LVI. Potential factors that may be associated with LVI were compared between the 2 groups. RESULTS: The study included 335 patients. The incidence of LVI was 3.11 times higher in patients with ascending colon tumors (odds ratio [OR], 3.11; 95% confidence interval [CI], 1.34-7.23; P=0.008) and 4.28 times higher in those with metastatic tumors (OR, 4.28; 95% CI, 2.18-8.39; P<0.001). Diabetes mellitus was inversely related to LVI in colorectal cancer patients; specifically, LVI was 56% less common in colorectal cancer patients with diabetes mellitus, irrespective of its duration (OR, 0.44; 95% CI, 0.25-0.76; P<0.001). CONCOUSION: The presence of preoperative LVI in colorectal cancer patients is difficult to predict. In particular, the effect of the effect of factors such as chronic disease accompanied by microvascular pathologies on LVI is still unclear. Advances in the neoadjuvant treatment of colorectal cancer patients, who are becoming more widespread every day, will encourage the investigation of different methods of preoperatively predicting LVI as a poor prognostic factor in these patients.

Lymphovascular Invasion is an Independent Negative Prognostic Factor in Esophageal Adenocarcinoma.

BACKGROUND: The significance of lymphovascular invasion (LVI) in esophageal adenocarcinoma (EAC) has not yet been described. Potential utility as an adjunct to current staging guidelines remains unknown. METHODS: The National Cancer Database was queried from 2006 to 2020. Univariate and multivariable models, Kaplan Meier method, and log-rank test were used. Subgroup analyses by pN stage were conducted. RESULTS: Of 9,689 patients, 23.2% had LVI. LVI was an independent prognostic factor (hazard ratio [HR] 1.401, 95% confidence interval [CI] 1.307-1.502, p < 0.0001) with reduction in median survival to 20.0 months (95% CI 18.9-21.4) from 39.7 months (95% CI 37.8-42.3, p < 0.0001). Multivariable survival analysis adjusted on pN and pT stage found that patients with LVI had decreased survival in a given pN stage (p < 0.001). pN0/LVI+ patients had a similar prognosis to the higher staged pN1/LVI- (28.6 months), although pN1/LVI- patients did slightly worse (p = 0.0135). Additionally, patients with pN1/LVI+ had equivalent survival compared with pN2/LVI- (p = 0.178) as did pN2/LVI+ patients compared with pN3/LVI- (p = 0.995). CONCLUSIONS: In these data, LVI is an independent negative prognostic factor in EAC. LVI was associated with a survival reduction similar to an upstaged nodal status irrespective of T stage. Patients with LVI may be better classified at a higher pN stage.

Evaluation of the risk factors of metastasis to central cervical lymph nodes in patients with papillary thyroid carcinoma.

Background: Papillary thyroid cancer, comprising 80% of thyroid malignancies in iodine-sufficient areas, can be effectively treated if detected early before metastasis. Cervical lymph nodes are a common site of metastasis, prompting some surgeons to suggest prophylactic dissection in all patients. To minimize potential side effects, this study aims to identify patients benefiting from this procedure by assessing risk factors for central lymph node metastasis. Methods and materials: This descriptive-analytical study was conducted on 150 patients with papillary thyroid cancer. The samples included cases in which central lymph node involvement was ruled out clinically and radiologically. After proving papillary cancer in the pathology sample, the variables of age, sex, frequency of central lymph node involvement, tumor size, location of thyroid involvement, multi-centric involvement, multi-focal involvement, presence of microcalcification, capsular invasion, lymphovascular invasion, and pathology were analyzed. The results were presented with descriptive statistics. Results: The percentage of central lymph node involvement in this study was reported as 9.3%. In the analysis, capsular invasion (P=0.01), lymphovascular invasion (P=0.0001) and involvement of the upper thyroid pole (P=0.001) were identified as risk factors for central lymph node involvement. There was no significant relationship between the variables of age, sex, tumor size, pathology, multi-centricity and multifocality and central lymph node involvement. Conclusion: Involvement of central lymph nodes in patients with capsular invasion, lymphovascular invasion, and involvement of the upper thyroid bridge is far more common than in other patients, and central lymph node dissection is recommended in patients with several of the above risk factors.

Predictive value of MRI-based deep learning model for lymphovascular invasion status in node-negative invasive breast cancer.

To retrospectively assess the effectiveness of deep learning (DL) model, based on breast magnetic resonance imaging (MRI), in predicting preoperative lymphovascular invasion (LVI) status in patients diagnosed with invasive breast cancer who have negative axillary lymph nodes (LNs). Data was gathered from 280 patients, including 148 with LVI-positive and 141 with LVI-negative lesions. These patients had undergone preoperative breast MRI and were histopathologically confirmed to have invasive breast cancer without axillary LN metastasis. The cohort was randomly split into training and validation groups in a 7:3 ratio. Radiomics features for each lesion were extracted from the first post-contrast dynamic contrast-enhanced (DCE)-MRI. The Least Absolute Shrinkage and Selection Operator (LASSO) regression method and logistic regression analyses were employed to identify significant radiomic features and clinicoradiological variables. These models were established using four machine learning (ML) algorithms and one DL algorithm. The predictive performance of the models (radiomics, clinicoradiological, and combination) was assessed through discrimination and compared using the DeLong test. Four clinicoradiological parameters and 10 radiomic features were selected by LASSO for model development. The Multilayer Perceptron (MLP) model, constructed using both radiomic and clinicoradiological features, demonstrated excellent performance in predicting LVI, achieving a high area under the curve (AUC) of 0.835 for validation. The DL model (MLP-radiomic) achieved the highest accuracy (AUC = 0.896), followed by DL model (MLP-combination) with an AUC of 0.835. Both DL models were significantly superior to the ML model (RF-clinical) with an AUC of 0.720. The DL model (MLP), which integrates radiomic features with clinicoradiological information, effectively aids in the preoperative determination of LVI status in patients with invasive breast cancer and negative axillary LNs. This is beneficial for making informed clinical decisions.

Adjuvant therapy for intermediate risk factors in oral cancer: Can we reach a consensus?

Oral carcinoma is a common disease that poses challenges in treatment management, especially for advanced cases. Adjuvant therapies, such as radiation and chemoradiation therapy, are typically used for advanced oral cancer patients. However, there is uncertainty regarding the use of adjuvant therapy for early-stage patients with certain soft histological parameters. The UICC manual of clinical oncology suggests that adjuvant therapy for such parameters is desirable but not essential. These parameters include perineural invasion, lymphovascular invasion, single nodal positivity, and patterns of invasion, which complicate the decision-making process for including adjuvant therapy. This review aims to provide evidence-based literature for effectively managing this patient group and developing treatment protocols based on current evidence.

Quantitative parameters of dual-layer spectral detector computed tomography for evaluating differentiation grade and lymphovascular and perineural invasion in colorectal adenocarcinoma.

PURPOSE: To explore the predictive value of dual-layer spectral detector CT (SDCT) quantitative parameters for determining differentiation grade, lymphovascular invasion (LVI) and perineural invasion (PNI) in colorectal adenocarcinoma (CRAC) patients. METHODS: A total of 106 eligible patients with CRAC were included in this study. Spectral parameters, including CT values at 40 and 100 keV, the effective atomic number (Zeff), the iodine concentration (IC), the slope of the spectral Hounsfield unit (HU) curve (λHU), and the normalized iodine concentration (NIC) in the arterial phase (AP) and venous phase (VP), were compared according to the differentiation grade and the status of LVI and PNI. The diagnostic accuracies of the quantitative parameters with statistical significance were determined via receiver operating characteristic (ROC) curves, and the area under the curve (AUC) was calculated. RESULTS: There were 57 males and 49 females aged 43-86 (69 ± 10) years. The measured values of the spectral quantitative parameters of the CRAC were consistent within the observer (ICC range: 0.800-0.926). The 40 keV-AP, IC-AP, NIC-AP, 40 keV-VP, and IC-VP were significantly different among the different differentiation grades in the CRAC (P = 0.040, AUC = 0.673; P = 0.035, AUC = 0.684; P = 0.031, AUC = 0.639; P = 0.044, AUC = 0.663 and P = 0.035, AUC = 0.666, respectively). A statistically significant difference was observed in 40 keV-VP, 100 keV-VP, Zeff-VP, IC-VP, and λHU-VP between LVI-positive and LVI-negative patients (P = 0.003, AUC = 0.688; P = 0.015, AUC = 0.644; P = 0.001, AUC = 0.688; P = 0.001, AUC = 0.703 and P = 0.003, AUC = 0.677, respectively). There were no statistically significant differences in the values of the spectral parameters of the PNI state of patients with CRAC (P > 0.05). CONCLUSION: The quantitative parameters of SDCT had good diagnostic efficacy in differentiating between different grades and statuses of LVI in patients with CRAC; however, SDCT did not have value for identifying the state of PNI.