Predictive risk score for isolated brain metastasis in non-small cell lung cancer.

Background: Brain metastasis is common with non-small cell lung cancer (NSCLC). Patients with some early-stage cancers don't benefit from routine brain imaging. Currently clinical stage alone is used to justify additional brain imaging. Other clinical and demographic characteristics may be associated with isolated brain metastasis (IBM). We aimed to define the most salient clinical features associated with synchronous IBM, hypothesizing that clinical and demographic factors could be used to determine the risk of brain metastasis. Methods: The National Cancer Database was used to identify patients with NSCLC from 2016-2020. Primary outcome was the presence of IBM relative to patients without evidence of any metastasis. Cohorts were divided into test and validation. The test cohort was used to identify risk factors for IBM using multivariable logistic regression. Using the regression, a scoring system was created to estimate the rate of synchronous IBM. The accuracy of the scoring system was evaluated with receiver operating characteristic (ROC) analysis using the validation cohort. Results: Study population consisted of 396,113 patients: 25,907 IBM and 370,206 without metastatic disease. IBM was associated with age, clinical T stage, clinical N stage, Charlson/Deyo comorbidity score, histology, and grade. A scoring system using these factors showed excellent accuracy in the test and validation cohort in ROC analysis (0.806 and 0.805, respectively). Conclusions: Clinical and demographic characteristics can be used to stratify the risk of IBM among patients with NSCLC and provide an evidence-based method to identify patients who require dedicated brain imaging in the absence of other metastatic disease.

Peritoneal metastasis of a cerebellar medulloblastoma through a ventriculoperitoneal shunt: A case report.

Medulloblastoma is a frequent and aggressive pediatric tumor. It causes intracranial hypertension, necessitating ventriculoperitoneal shunting with surgical resection. Intraperitoneal metastases are rare and result from the migration of neoplastic cells through the shunt and into the peritoneal cavity. This metastatic form involving the ventriculoperitoneal shunt has a poor prognosis, making therapeutic management even more difficult. We report the case of a 14-year-old boy with a history of medulloblastoma of the cerebellum who was initially treated with complete resection of the tumor with placement of a ventriculoperitoneal shunt, followed by radiotherapy and chemotherapy, with good progression until he presented to the emergency department with acute abdominal symptoms. Imaging revealed multiple peritoneal masses with intra- and retroperitoneal lymphadenopathies. An ultrasound-guided biopsy revealed a metastatic medulloblastoma in the peritoneal cavity, and the patient underwent chemotherapy. The placement of the ventriculoperitoneal shunt in the tumor dissemination is therefore to blame.

Immunotherapy in gastric cancer with liver metastasis: Challenges and opportunities.

In this editorial, we review the article by Liu et al published in the World Journal of Gastrointestinal Surgery investigating the efficacy and safety of immunotherapy in patients with gastric cancer (GC) and liver metastasis. GC, the fifth most commonly diagnosed malignancy worldwide, presents a significant challenge due to its multifactorial etiology and a grim prognosis for unresectable or recurrent cases. The advent of immune checkpoint inhibitors (ICIs) has revolutionized oncology; yet liver metastasis has been associated with reduced response rates, progression-free survival, and overall survival in various malignancies. The CheckMate-649 and KEYNOTE-859 trials demonstrated promising results with ICIs in advanced GC, particularly in patients with liver metastasis. However, a meta-analysis of liver metastatic solid tumors revealed worse outcomes with ICIs, highlighting the need for further investigation. While combined therapies, including ICIs with local treatments, show promise in improving outcomes, the nuanced landscape of ICIs in liver metastatic GC necessitates continued research for robust conclusions. The current contradictions in the literature underscore the importance of cautious interpretation and the exploration of tailored approaches to enhance clinical efficacy in this challenging patient population.

Prediction and analysis of albumin-bilirubin score combined with liver function index and carcinoembryonic antigen on liver metastasis of colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is a common malignant tumor, and liver metastasis is one of the main recurrence and metastasis modes that seriously affect patients' survival rate and quality of life. Indicators such as albumin bilirubin (ALBI) score, liver function index, and carcinoembryonic antigen (CEA) have shown some potential in the prediction of liver metastasis but have not been fully explored. AIM: To evaluate its predictive value for liver metastasis of CRC by conducting the combined analysis of ALBI, liver function index, and CEA, and to provide a more accurate liver metastasis risk assessment tool for clinical treatment guidance. METHODS: This study retrospectively analyzed the clinical data of patients with CRC who received surgical treatment in our hospital from January 2018 to July 2023 and were followed up for 24 months. According to the follow-up results, the enrolled patients were divided into a liver metastasis group and a nonliver metastasis group and randomly divided into a modeling group and a verification group at a ratio of 2:1. The risk factors for liver metastasis in patients with CRC were analyzed, a prediction model was constructed by least absolute shrinkage and selection operator (LASSO) logistic regression, internal validation was performed by the bootstrap method, the reliability of the prediction model was evaluated by subject-work characteristic curves, calibration curves, and clinical decision curves, and a column graph was drawn to show the prediction results. RESULTS: Of 130 patients were enrolled in the modeling group and 65 patients were enrolled in the verification group out of the 195 patients with CRC who fulfilled the inclusion and exclusion criteria. Through LASSO regression variable screening and logistic regression analysis. The ALBI score, alanine aminotransferase (ALT), and CEA were found to be independent predictors of liver metastases in CRC patients [odds ratio (OR) = 8.062, 95% confidence interval (CI): 2.545-25.540], (OR = 1.037, 95%CI: 1.004-1.071) and (OR = 1.025, 95%CI: 1.008-1.043). The area under the receiver operating characteristic curve (AUC) for the combined prediction of CRLM in the modeling group was 0.921, with a sensitivity of 78.0% and a specificity of 95.0%. The H-index was 0.921, and the H-L fit curve had χ2 = 0.851, a P value of 0.654, and a slope of the calibration curve approaching 1. This indicates that the model is extremely accurate, and the clinical decision curve demonstrates that it can be applied effectively in the real world. We conducted internal verification of one thousand resamplings of the modeling group data using the bootstrap method. The AUC was 0.913, while the accuracy was 0.869 and the kappa consistency was 0.709. The combination prediction of liver metastasis in patients with CRC in the verification group had an AUC of 0.918, sensitivity of 85.0%, specificity of 95.6%, C-index of 0.918, and an H-L fitting curve with χ 2 = 0.586, P = 0.746. CONCLUSION: The ALBI score, ALT level, and CEA level have a certain value in predicting liver metastasis in patients with CRC. These three criteria exhibit a high level of efficacy in forecasting liver metastases in patients diagnosed with CRC. The risk prediction model developed in this work shows great potential for practical application.

Machine learning prediction model for gray-level co-occurrence matrix features of synchronous liver metastasis in colorectal cancer.

BACKGROUND: Synchronous liver metastasis (SLM) is a significant contributor to morbidity in colorectal cancer (CRC). There are no effective predictive device integration algorithms to predict adverse SLM events during the diagnosis of CRC. AIM: To explore the risk factors for SLM in CRC and construct a visual prediction model based on gray-level co-occurrence matrix (GLCM) features collected from magnetic resonance imaging (MRI). METHODS: Our study retrospectively enrolled 392 patients with CRC from Yichang Central People's Hospital from January 2015 to May 2023. Patients were randomly divided into a training and validation group (3:7). The clinical parameters and GLCM features extracted from MRI were included as candidate variables. The prediction model was constructed using a generalized linear regression model, random forest model (RFM), and artificial neural network model. Receiver operating characteristic curves and decision curves were used to evaluate the prediction model. RESULTS: Among the 392 patients, 48 had SLM (12.24%). We obtained fourteen GLCM imaging data for variable screening of SLM prediction models. Inverse difference, mean sum, sum entropy, sum variance, sum of squares, energy, and difference variance were listed as candidate variables, and the prediction efficiency (area under the curve) of the subsequent RFM in the training set and internal validation set was 0.917 [95% confidence interval (95%CI): 0.866-0.968] and 0.09 (95%CI: 0.858-0.960), respectively. CONCLUSION: A predictive model combining GLCM image features with machine learning can predict SLM in CRC. This model can assist clinicians in making timely and personalized clinical decisions.

Analysis of lymph node metastasis and survival prognosis in early gastric cancer patients: A retrospective study.

BACKGROUND: Early gastric cancer (EGC) is a common malignant tumor of the digestive system, and its lymph node metastasis and survival prognosis have been concerning. By retrospectively analyzing the clinical data of EGC patients, we can better understand the status of lymph node metastasis and its impact on survival and prognosis. AIM: To evaluate the prognosis of EGC patients and the factors that affect lymph node metastasis. METHODS: The clinicopathological data of 1011 patients with EGC admitted to our hospital between January 2015 and December 2023 were collected in a retrospective cohort study. There were 561 males and 450 females. The mean age was 58 ± 11 years. The patient underwent radical gastrectomy. The status of lymph node metastasis in each group was determined according to the pathological examination results of surgical specimens. The outcomes were as follows: (1) Lymph node metastasis in EGC patients; (2) Analysis of influencing factors of lymph node metastasis in EGC; and (3) Analysis of prognostic factors in patients with EGC. Normally distributed measurement data are expressed as mean ± SD, and a t test was used for comparisons between groups. The data are expressed as absolute numbers or percentages, and the chi-square test was used for comparisons between groups. Rank data were compared using a nonparametric rank sum test. A log-rank test and a logistic regression model were used for univariate analysis. A logistic stepwise regression model and a Cox stepwise regression model were used for multivariate analysis. The Kaplan-Meier method was used to calculate the survival rate and construct survival curves. A log-rank test was used for survival analysis. RESULTS: Analysis of influencing factors of lymph node metastasis in EGC. The results of the multifactor analysis showed that tumor length and diameter, tumor site, tumor invasion depth, vascular thrombus, and tumor differentiation degree were independent influencing factors for lymph node metastasis in patients with EGC (odds ratios = 1.80, 1.49, 2.65, 5.76, and 0.60; 95%CI: 1.29-2.50, 1.11-2.00, 1.81-3.88, 3.87-8.59, and 0.48-0.76, respectively; P < 0.05). Analysis of prognostic factors in patients with EGC. All 1011 patients with EGC were followed up for 43 (0-13) months. The 3-year overall survival rate was 97.32%. Multivariate analysis revealed that age > 60 years and lymph node metastasis were independent risk factors for prognosis in patients with EGC (hazard ratio = 9.50, 2.20; 95%CI: 3.31-27.29, 1.00-4.87; P < 0.05). Further analysis revealed that the 3-year overall survival rates of gastric cancer patients aged > 60 years and ≤ 60 years were 99.37% and 94.66%, respectively, and the difference was statistically significant (P < 0.05). The 3-year overall survival rates of patients with and without lymph node metastasis were 95.42% and 97.92%, respectively, and the difference was statistically significant (P < 0.05). CONCLUSION: The lymph node metastasis rate of EGC patients was 23.64%. Tumor length, tumor site, tumor infiltration depth, vascular cancer thrombin, and tumor differentiation degree were found to be independent factors affecting lymph node metastasis in EGC patients. Age > 60 years and lymph node metastasis are independent risk factors for EGC prognosis.

Predicting distant metastasis in nasopharyngeal carcinoma using gradient boosting tree model based on detailed magnetic resonance imaging reports.

BACKGROUND: Development of distant metastasis (DM) is a major concern during treatment of nasopharyngeal carcinoma (NPC). However, studies have demonstrated improved distant control and survival in patients with advanced NPC with the addition of chemotherapy to concomitant chemoradiotherapy. Therefore, precise prediction of metastasis in patients with NPC is crucial. AIM: To develop a predictive model for metastasis in NPC using detailed magnetic resonance imaging (MRI) reports. METHODS: This retrospective study included 792 patients with non-distant metastatic NPC. A total of 469 imaging variables were obtained from detailed MRI reports. Data were stratified and randomly split into training (50%) and testing sets. Gradient boosting tree (GBT) models were built and used to select variables for predicting DM. A full model comprising all variables and a reduced model with the top-five variables were built. Model performance was assessed by area under the curve (AUC). RESULTS: Among the 792 patients, 94 developed DM during follow-up. The number of metastatic cervical nodes (30.9%), tumor invasion in the posterior half of the nasal cavity (9.7%), two sides of the pharyngeal recess (6.2%), tubal torus (3.3%), and single side of the parapharyngeal space (2.7%) were the top-five contributors for predicting DM, based on their relative importance in GBT models. The testing AUC of the full model was 0.75 (95% confidence interval [CI]: 0.69-0.82). The testing AUC of the reduced model was 0.75 (95%CI: 0.68-0.82). For the whole dataset, the full (AUC = 0.76, 95%CI: 0.72-0.82) and reduced models (AUC = 0.76, 95%CI: 0.71-0.81) outperformed the tumor node-staging system (AUC = 0.67, 95%CI: 0.61-0.73). CONCLUSION: The GBT model outperformed the tumor node-staging system in predicting metastasis in NPC. The number of metastatic cervical nodes was identified as the principal contributing variable.

Anal metastasis in esophageal cancer: A case report.

BACKGROUND: Esophageal cancer is the sixth leading cause of cancer-related death and eighth most common cancer, affecting > 450000 people worldwide. Esophageal squamous cell carcinoma is the most common histological type, whereas esophageal adenoid cystic carcinoma (EACC) is rare. The liver is the most common distant metastatic site in esophageal cancer. Anal metastasis is rare and has not been reported in clinical practice before. Here, we report anal metastases in a patient with EACC after regular chemotherapy and surgical resection. CASE SUMMARY: A 61-year-old esophageal cancer patient was found to have lung and brain metastases during standardized treatment. The patient's treatment plan was continuously adjusted according to the latest treatment guidelines. However, the patient subsequently noticed rectal bleeding and itching, and after obtaining pathology results at the local hospital, anal metastasis of esophageal cancer was diagnosed. CONCLUSION: Postoperative pathology and immunohistochemistry confirmed EACC with rare anal metastasis. More exploration of EACC diagnosis and treatment is needed.

Possible association between polyomaviruses and gastrointestinal complications: a narrative review.

Polyomaviruses are a group of small, double-stranded DNA viruses that are known to be associated with the development of certain human diseases, but there is evidence that these viruses might be associated with gastrointestinal (GI) cancers. Several polyomaviruses have been identified, such as JC polyomavirus (JCPyV), BK polyomavirus (BKPyV) and recently Merkel cell polyomavirus (MCPyV). Although the direct effects of polyomaviruses on transformation of human cells and cancer development are not clearly recognized, their association with certain human diseases including GI cancers has been proposed through several molecular and epidemiological studies. For example, JCPyV and BKPyV have been linked to colorectal cancer, as there is growing evidence of finding viral genomes in cancerous tissues. Nevertheless, the major role of JCPyV, BKPyV and MCPyV in colorectal cancer progression is still under extensive investigation, and further surveys is required to establish a conclusive cause-and-effect relationship. Understanding the role of these viruses in cancer development has significant implications for diagnosis, treatment, and prevention strategies. It seems that proving a causal link between polyomaviruses and GI cancers might provide a novel path for targeted therapies or design and development of specific therapeutic vaccines. In addition, performing research on the possible link can provide insights into the underlying molecular mechanisms of carcinogenesis, potentially leading to the identification of novel biomarkers. This review focuses on polyomaviruses, in particular a recently discovered polyomavirus, MCPyV, and their possible link with human gastrointestinal disorders.

Histone Methyltransferase SUV39H2 Supports Nasopharyngeal Carcinoma Cell Metastasis by Regulation of SIRT1.

Nasopharyngeal carcinoma (NPC) is a malignant tumor with high metastatic features originating from the nasopharynx. However, the underlying mechanism of Suppressor of variegation 3-9 homolog 2 (SUV39H2) in NPC remains poorly understood. RT-qPCR was carried out to examine SUV39H2 and SIRT1 expression in NPC tissues and cells. Kaplan-Meier method was utilized to evaluate the association between SUV39H2 level and overall survival. The function of SUV39H2 and SIRT1 in NPC cell viability, metastasis, and apoptosis was tested through CCK-8, transwell, and flow cytometry experiments. Here, it was uncovered that SUV39H2 level was augmented in NPC tissues and cells. Moreover, SUV39H2 expedited NPC cell viability, metastasis, and inhibited apoptosis, while SIRT1 addition reversed these impacts. Besides, SUV39H2 induced H3K9me3 enhancement to repress SIRT1 transcription via binding to SIRT1 promoter. Collectively, our results demonstrated upregulated SUV39H2 aggravated NPC tumorigenesis through SIRT1, which may offer a potential therapeutic target for NPC.

Cellular senescence in metastatic prostate cancer: A therapeutic opportunity or challenge (Review).

The treatment of patients with metastatic prostate cancer (PCa) is considered to be a long­standing challenge. Conventional treatments for metastatic PCa, such as radical prostatectomy, radiotherapy and androgen receptor­targeted therapy, induce senescence of PCa cells to a certain extent. While senescent cells can impede tumor growth through the restriction of cell proliferation and increasing immune clearance, the senescent microenvironment may concurrently stimulate the secretion of a senescence­associated secretory phenotype and diminish immune cell function, which promotes PCa recurrence and metastasis. Resistance to established therapies is the primary obstacle in treating metastatic PCa as it can lead to progression towards an incurable state of disease. Therefore, understanding the molecular mechanisms that underly the progression of PCa is crucial for the development of novel therapeutic approaches. The present study reviews the phenomenon of treatment­induced senescence in PCa, the dual role of senescence in PCa treatments and the mechanisms through which senescence promotes PCa metastasis. Furthermore, the present review discusses potential therapeutic strategies to target the aforementioned processes with the aim of providing insights into the evolving therapeutic landscape for the treatment of metastatic PCa.

[Corrigendum] Ophiopogonin B suppresses the metastasis and angiogenesis of A549 cells in vitro and in vivo by inhibiting the EphA2/Akt signaling pathway.

Subsequently to the publication of the above article, an interested reader drew to the authors' attention that, for the scratch­wound assay experiments shown in Fig. 3C, two images appeared to overlap [specifically, the '0 h / Control' and 0 h / OP­B (5 µmol/l) data panels], albeit with different magnification and after a 180° rotation. The authors have examined their original data, and realize that an inadvertent error was made in assembling the images in the figure; specifically, the images of 5 and 10 µmol/l OP­B treatment for 0 h were both misused. The corrected version of Fig. 3, showing all the correct data for Fig. 3C, is shown on the next page. Note that these errors did not affect the overall conclusions reported in the paper. All the authors agree with the publication of this corrigendum, and are grateful to the Editor of Oncology Reports for allowing them the opportunity to publish this. They also apologize to the readership for any inconvenience caused. [Oncology Reports 40: 1339­1347, 2018; DOI: 10.3892/or.2018.6531].

Role of elective neck dissection in cT2N0 maxillary sinus squamous cell carcinoma.

Our objective was to examine the impact of elective neck dissection (END) on the prognosis of patients with cT2N0 maxillary sinus squamous cell carcinoma (MS-SCC) and to determine factors that predict the occurrence of occult metastasis in this patient population. A retrospective analysis was conducted using data from the SEER database. Patients with cT2N0 MS-SCC were included in the study and divided into two groups: those who received END and those who did not. The impact of END on disease-specific survival (DSS) and overall survival (OS) was assessed using propensity score matching. Multivariate logistic regression analysis was performed to determine predictors for occult metastasis. A total of 180 patients were included in the study, with 40 cases receiving END. Following propensity score matching, patients treated with END and those without showed similar DSS and OS rates. Occult metastasis was observed in 9 patients, corresponding to a rate of 22.5%. High-grade tumors were independently associated with a higher risk of occult metastasis compared to low-grade tumors (hazard ratio 1.52, 95% confidence interval 1.17-2.00). cT2 MS-SCC carries an occult metastasis rate of 22.5%, with histologic grade being the primary determinant of occult metastasis. END does not confer a significant survival benefit in this patient population.

Detection of cell-free tumor DNA in cerebrospinal fluid as a diagnostic biomarker for leptomeningeal melanoma metastasis: A case series.

Leptomeningeal melanoma metastases (LMM) are associated with poor survival. Diagnosis is based on clinical presentation, brain MRI and cerebrospinal fluid (CSF) analysis. Inconclusive findings at initial presentation can delay treatment. In this single-center case series, detection of BRAFV600- and NRASQ61-mutant cell-free tumor DNA (cfDNA) in CSF was evaluated as a complementary diagnostic biomarker. In 12 patients with clinical suspicion of LMM, a retrospective analysis of MRI, CSF cytology and cfDNA analysis on 1 mL of CSF using the Idylla® platform was carried out. Nine patients displayed MRI abnormalities suggesting LMM. CSF analysis identified malignant cells in three patients (including one without MRI abnormalities). BRAFV600- or NRASQ61-mutant cfDNA was detected in CSF of nine patients (eight with and one without MRI abnormalities; all patients with positive CSF cytology). Subsequent follow-up confirmed LMM in all patients with positive and in one patient with a negative CSF cfDNA analysis (sensitivity 81.8%; specificity 100%). Our findings suggest that analyzing BRAFV600- and NRASQ61-mutant cfDNA in CSF using the Idylla® platform holds promise as a sensitive and specific complementary diagnostic biomarker for LMM, particularly in case of inconsistency between imaging and CSF cytology. The 110-min analysis can facilitate urgent treatment decisions.

RBM7 deficiency promotes breast cancer metastasis by coordinating MFGE8 splicing switch and NF-kB pathway.

Aberrant alternative splicing is well-known to be closely associated with tumorigenesis of various cancers. However, the intricate mechanisms underlying breast cancer metastasis driven by deregulated splicing events remain largely unexplored. Here, we unveiled that RBM7 is decreased in lymph node and distant organ metastases of breast cancer as compared to primary lesions and low expression of RBM7 is correlated with the reduced disease-free survival of breast cancer patients. Breast cancer cells with RBM7 depletion exhibited an increased potential for lung metastasis compared to scramble control cells. The absence of RBM7 stimulated breast cancer cell migration, invasion, and angiogenesis. Mechanistically, RBM7 controlled the splicing switch of MFGE8, favoring the production of the predominant isoform of MFGE8, MFGE8-L. This resulted in the attenuation of STAT1 phosphorylation and alterations in cell adhesion molecules. MFGE8-L exerted an inhibitory effect on the migratory and invasive capability of breast cancer cells, while the truncated isoform MFGE8-S, which lack the second F5/8 type C domain had the opposite effect. In addition, RBM7 negatively regulates the NF-κB cascade and an NF-κB inhibitor could obstruct the increase in HUVEC tube formation caused by RBM7 silencing. Clinically, we noticed a positive correlation between RBM7 expression and MFGE8 exon7 inclusion in breast cancer tissues, providing new mechanistic insights for molecular-targeted therapy in combating breast cancer.

Rectal metastasis arising from breast cancer: a case report.

Breast cancer is the most common cancer among women worldwide. Breast cancer often metastasizes to the regional lymph nodes, bone, brain, liver, and lungs, whereas gastrointestinal tract metastases are rare. Herein, we present a rare case of rectal metastasis from breast cancer that occurred during palliative chemotherapy. A 69-year-old female with a history of invasive ductal carcinoma, negative for hormonal receptors and positive for human epidermal growth factor receptor 2 (HER2) receptor, underwent various treatments, including neoadjuvant chemotherapy, breast-conserving surgery, and adjuvant therapy. Eight months postoperatively, the patient experienced axillary lymph node recurrence, requiring palliative chemotherapy. Despite ongoing treatment, metastatic lesions were confirmed in the lungs and pleura. During palliative chemotherapy, the patient developed anal pain, and subsequent examination revealed an infiltrating rectal lesion. Despite histological confirmation of metastatic breast carcinoma and tubular adenoma, a multidisciplinary decision was made regarding palliative chemotherapy over surgical intervention. Eribulin was administered, but due to the patient's inability to tolerate the treatment, she passed away 3 months after rectal lesion diagnosis. Although breast cancer metastasis to the rectum is rare, clinicians should consider the possibility of rectal involvement and perform a digital rectal examination if anal symptoms are present.

Radiomics and machine learning analysis of liver magnetic resonance imaging for prediction and early detection of tumor response in colorectal liver metastases.

PURPOSE: The aim of this study was to demonstrate the effectiveness of a machine learning-based radiomics model for distinguishing tumor response and overall survival in patients with unresectable colorectal liver metastases (CRLM) treated with targeted biological therapy. METHODS: We prospectively recruited 17 patients with unresectable liver metastases of colorectal cancer, who had been given targeted biological therapy as the first line of treatment. All patients underwent liver magnetic resonance imaging (MRI) three times up until 8 weeks after chemotherapy. We evaluated the diagnostic performance of machine learning-based radiomics model in tumor response of liver MRI compared with the guidelines for the Response Evaluation Criteria in Solid Tumors. Overall survival was evaluated using the Kaplan-Meier analysis and compared to the Cox proportional hazard ratios following univariate and multivariate analyses. RESULTS: Performance measurement of the trained model through metrics showed the accuracy of the machine learning model to be 76.5%, and the area under the receiver operating characteristic curve was 0.857 (95% confidence interval [CI], 0.605-0.976; P < 0.001). For the patients classified as non-progressing or progressing by the radiomics model, the median overall survival was 17.5 months (95% CI, 12.8-22.2), and 14.8 months (95% CI, 14.2-15.4), respectively (P = 0.431, log-rank test). CONCLUSION: Machine learning-based radiomics models could have the potential to predict tumor response in patients with unresectable CRLM treated with biologic therapy.

Enhancement on CT for preoperative diagnosis of metastatic lymph nodes in thyroid cancer: a comparison across experience levels.

OBJECTIVES: To investigate the diagnostic performance and interobserver agreement of quantitative CT parameters indicating strong lymph node (LN) enhancement in differentiated thyroid cancer (DTC), comparing them with qualitative analysis by radiologists of varying experience. MATERIALS AND METHODS: This study included 463 LNs from 399 patients with DTC. Three radiologists independently analyzed strong LN enhancement on CT. Qualitative analysis of strong enhancement was defined as LN cortex showing greater enhancement than adjacent muscles on the arterial phase. Quantitative analysis included the mean attenuation value (MAV) of LN on arterial phase (LNA) and venous phase (LNV), LNA normalized to the common carotid artery (NAVCCA), internal jugular vein (NAVIJV), and sternocleidomastoid muscle (NAVSCM), attenuation difference [AD; (LNA - MAVSCM)], and relative washout ratio [((LNA - LNV)/LNA) × 100]. The interobserver agreement and diagnostic performance of the quantitative and qualitative analyses were evaluated. RESULTS: Interobserver agreement was excellent for all quantitative CT parameters (ICC, 0.83-0.94) and substantial for qualitative assessment (κ = 0.61). All CT parameters except for LNV showed good diagnostic performance for metastatic LNs (AUC, 0.81-0.85). NAVCCA (0.85, 95% CI: 0.8-0.9) and AD (0.85, 95% CI: 0.81-0.89) had the highest AUCs. All quantitative parameters except for NAVIJV had significantly higher AUCs than qualitative assessments by inexperienced radiologists, with no significant difference from assessments by an experienced radiologist. CONCLUSION: Quantitative assessment of LN enhancement on arterial phase CT showed higher interobserver agreement and AUC values than qualitative analysis by inexperienced radiologists, supporting the need for a standardized quantitative CT parameter-based model for determining strong LN enhancement. CLINICAL RELEVANCE STATEMENT: When assessing strong LN enhancement in DTC, quantitative CT parameters indicating strong enhancement can improve interobserver agreement, regardless of experience level. Therefore, the development of a standardized diagnostic model based on quantitative CT parameters might be necessary. KEY POINTS: Accurate preoperative assessment of LN metastasis in thyroid cancer is crucial. Quantitative CT parameters indicating strong LN enhancement demonstrated excellent interobserver agreement and good diagnostic performance. Quantitative assessment of contrast enhancement offers a more objective model for the identification of metastatic LNs.

Mechanical deformation and death of circulating tumor cells in the bloodstream.

The circulation of tumor cells through the bloodstream is a significant step in tumor metastasis. To better understand the metastatic process, circulating tumor cell (CTC) survival in the circulation must be explored. While immune interactions with CTCs in recent decades have been examined, research has yet to sufficiently explain some CTC behaviors in blood flow. Studies related to CTC mechanical responses in the bloodstream have recently been conducted to further study conditions under which CTCs might die. While experimental methods can assess the mechanical properties and death of CTCs, increasingly sophisticated computational models are being built to simulate the blood flow and CTC mechanical deformation under fluid shear stresses (FSS) in the bloodstream.Several factors contribute to the mechanical deformation and death of CTCs as they circulate. While FSS can damage CTC structure, diverse interactions between CTCs and blood components may either promote or hinder the next metastatic step-extravasation at a remote site. Overall understanding of how these factors influence the deformation and death of CTCs could serve as a basis for future experiments and simulations, enabling researchers to predict CTC death more accurately. Ultimately, these efforts can lead to improved metastasis-specific therapeutics and diagnostics specific in the future.

An Intramyocardial Mass Mimicking ST-Segment Elevation Myocardial Infarct at Presentation.

ST-segment elevation on the electrocardiogram typically indicates acute myocardial infarction but can mimic ST-segment elevation myocardial infarction in various conditions. We present a case of a patient with an intramyocardial mass and anterior ST-segment elevation without significant myocardial biomarker elevation. Multimodality imaging was crucial in revealing cardiac metastasis as the attributable cause.