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Schwannomas are usually benign tumors typically found in the head, neck, and extremities, with approximately 3% originating in the retroperitoneum. In this case, a young male presented with incidental masses in the left kidney and retroperitoneum. Abdominal pelvic enhanced computerized tomography (CT) revealed a tumor apparently originating from the left kidney, along with a retroperitoneal mass suspected to be a metastatic lymph node. Subsequently, a radical nephrectomy of the left kidney and retroperitoneal mass resection was performed. Pathological examination confirmed the left kidney mass as renal clear cell carcinoma and the retroperitoneal mass as schwannoma. The patient recovered uneventfully and was discharged from the hospital. A 6-month postoperative follow-up showed no evidence of recurrence. Preoperative diagnosis of schwannomas concurrent with other concurrent malignancies in rare sites, such as the retroperitoneum, is challenging due to their rare and non-specific radiological features. Although retroperitoneal schwannomas are rare, they should be considered in the differential diagnosis during CT examinations for renal cancer. Additionally, the advantages of a multidisciplinary team approach should be utilized in tumor management.

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BACKGROUND: The number of metastatic lymph nodes (MLNs) is crucial for the survival of nasopharyngeal carcinoma (NPC), but manual counting is laborious. This study aims to explore the feasibility and prognostic value of automatic MLNs segmentation and counting. METHODS: We retrospectively enrolled 980 newly diagnosed patients in the primary cohort and 224 patients from two external cohorts. We utilized the nnUnet model for automatic MLNs segmentation on multimodal magnetic resonance imaging. MLNs counting methods, including manual delineation-assisted counting (MDAC) and fully automatic lymph node counting system (AMLNC), were compared with manual evaluation (Gold standard). RESULTS: In the internal validation group, the MLNs segmentation results showed acceptable agreement with manual delineation, with a mean Dice coefficient of 0.771. The consistency among three counting methods was as follows 0.778 (Gold vs. AMLNC), 0.638 (Gold vs. MDAC), and 0.739 (AMLNC vs. MDAC). MLNs numbers were categorized into three-category variable (1-4, 5-9, > 9) and two-category variable (<4, ≥ 4) based on the gold standard and AMLNC. These categorical variables demonstrated acceptable discriminating abilities for 5-year overall survival (OS), progression-free, and distant metastasis-free survival. Compared with base prediction model, the model incorporating two-category AMLNC-counting numbers showed improved C-indexes for 5-year OS prediction (0.658 vs. 0.675, P = 0.045). All results have been successfully validated in the external cohort. CONCLUSIONS: The AMLNC system offers a time- and labor-saving approach for fully automatic MLNs segmentation and counting in NPC. MLNs counting using AMLNC demonstrated non-inferior performance in survival discrimination compared to manual detection.

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Stage pIIIA/N2 non-small cell lung cancer (NSCLC) is primarily treated by complete surgical resection combined with neoadjuvant/adjuvant therapies. However, up to 40% of patients experience tumor recurrence. Here, we studied 119 stage pIIIA/N2 NSCLC patients who received complete surgery plus adjuvant chemotherapy (CT) or chemoradiotherapy (CRT). The paired tumor and resection margin samples were analyzed using next-generation sequencing (NGS). Although all patients were classified as negative resection margins by histologic methods, NGS revealed that 47.1% of them had molecularly positive surgical margins. Patients who tested positive for NGS-detected residual tumors had significantly shorter disease-free survival (DFS) (P = 0.002). Additionally, metastatic lymph node ratio, erb-b2 receptor tyrosine kinase 2 (ERBB2) mutations, and SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a, member 4 (SMARCA4) mutations were also independently associated with DFS. We used these four features to construct a COX model that could effectively estimate recurrence risk and prognosis. Notably, mutational profiling through broad-panel NGS could more sensitively detect residual tumors than the conventional histologic methods. Adjuvant CT and adjuvant CRT exhibited no significant difference in eliminating locoregional recurrence risk for stage pIIIA/N2 NSCLC patients with molecularly positive surgical margins.

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BACKGROUND: The recurrence of thyroid cancer poses challenges compounded by postoperative fibrosis and anatomic changes. By overcoming the limitations of current localizing dye techniques, indocyanine green-macroaggregated albumin-hyaluronic acid (ICG-MAA-HA) mixture dye promises improved localization. This study aimed to evaluate the efficacy and safety of the dye for recurrent thyroid cancer. METHODS: The nine patients in this study underwent surgery and postoperative ultrasonography. The dye was injected into recurrent lesions in all the patients preoperatively. During surgery, the lesions were confirmed with an imaging system before and after excision. If the lesion was unidentifiable with the naked eye, surgical excision was performed under the corresponding fluorescent guide. Side effects related to the dye injection and completeness of the surgery were evaluated. RESULTS: No side effects such as bleeding, skin tattooing, or pain during or after the dye injection were reported, and no discoloration occurred that interfered with the surgical field of view during surgery. In three cases (33.3 %), because it was difficult to localize metastatic lesions with the naked eye, the operation was successfully completed using an imaging system. The completeness of the surgical resection was confirmed by ultrasonography after an average of 5 months postoperatively. CONCLUSION: The study found that ICG-MAA-HA dye effectively located metastatic and recurrent thyroid cancer and had favorable results in terms of minimal procedural side effects and potential for assisting the surgeon. A large-scale multi-institutional study is necessary to prove the clinical significance regarding patient survival and disease control.

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OBJECTIVE: The accurate diagnosis of superficial lymphadenopathy is challenging. We aim to explore a non-invasive and accurate machine-learning method for distinguishing benign lymph nodes, lymphoma, and metastatic lymph nodes. METHODS: The clinical data and ultrasound images of 160 patients with superficial lymphadenopathy (58 benign lymph nodes, 62 lymphoma, 40 metastatic lymph nodes) admitted to our hospital from January 2020 to November 2022 were retrospectively studied. Patients were randomly divided into a training set and test set according to the ratio of 6:4. Firstly, the radiomics features of each lymph node were extracted, and then a series of statistical methods were used to avoid over-fitting. Then, the gradient boosting machine(GBM) was used to build the model. The area under receiver(AUC) operating characteristic curve, precision, recall rate and F1 value were calculated to evaluate the effectiveness of the model. RESULTS: Ten robust features were selected to build the model. The AUC values of benign lymph nodes, lymphoma and metastatic lymph nodes in the training set were 1.00, 0.98 and 0.99, and the AUC values of the test set were 0.96, 0.84 and 0.90, respectively. CONCLUSION: It was a reliable and non-invasive method for the differential diagnosis of lymphadenopathy based on the model constructed by machine learning.

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Ultrasonography is the preferred modality for detailed evaluation of enlarged lymph nodes (LNs) identified on computed tomography and/or magnetic resonance imaging, owing to its high spatial resolution. However, the diagnostic performance of ultrasonography depends on the examiner's expertise. To support the ultrasonographic diagnosis, we developed YOLOv7-based deep learning models for metastatic LN detection on ultrasonography and compared their detection performance with that of highly experienced radiologists and less experienced residents. We enrolled 462 B- and D-mode ultrasound images of 261 metastatic and 279 non-metastatic histopathologically confirmed LNs from 126 patients with head and neck squamous cell carcinoma. The YOLOv7-based B- and D-mode models were optimized using B- and D-mode training and validation images and their detection performance for metastatic LNs was evaluated using B- and D-mode testing images, respectively. The D-mode model's performance was comparable to that of radiologists and superior to that of residents' reading of D-mode images, whereas the B-mode model's performance was higher than that of residents but lower than that of radiologists on B-mode images. Thus, YOLOv7-based B- and D-mode models can assist less experienced residents in ultrasonographic diagnoses. The D-mode model could raise the diagnostic performance of residents to the same level as experienced radiologists.

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PURPOSE: The aim of this study was to develop and externally validate a nomogram to accurately predict the overall survival (OS) of patients with gastric adenocarcinoma who underwent radical gastrectomy. MATERIALS AND METHODS: A total of 3492 patients with gastric adenocarcinoma who underwent radical gastrectomy from 2012 to 2017 were included as the training cohort. Survival analysis was performed via Kaplan Meier method and log-rank test. Independent postoperative prognostic factors in patients with gastric adenocarcinoma were analyzed using univariate and multifactorial COX analysis methods. The prognosis nomogram was established in the training cohort and verified externally in the Surveillance, Epidemiology and End Results (SEER) database. RESULTS: According to the univariate and multifactorial COX analyses, metastatic lymph node ratio (MLNR) and five other independent prognostic factors (age at surgery, type of gastrectomy, tumor size, T stage, and pathological grade) were included in the prognostic nomogram. The nomogram had better prognostic predictive ability than the American Joint Committee on Cancer (AJCC) TNM staging in both the training (C-index: 0.736 VS. 0.668) and external validation cohort (C-index: 0.712 VS. 0.627). The calibration plots showed that the predicted survival rate was in good agreement with the actual survival rate. And the decision curve analysis (DCA) curves revealed that nomogram showed stronger ability in predicting 1-year, 3-year, and 5-year OS. CONCLUSION: This study estimated the excellent prognostic predictive power and clinical application potential of the MLNR-based nomogram, which may be used to facilitate postoperative clinical treatment decisions and potentially improve patient survival outcomes.

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Intramesorectal lymph node metastasis after radical surgery of prostate cancer is rare in clinical practice. This paper reported 2 cases of intramesorectal lymph node metastasis and resection after operation for prostate cancer. Patient 1 underwent laparoscopic radical prostatectomy 5 years ago, who was followed up closely after surgery, and was diagnosed with mesorectal lymph node metastasis by MRI examination. Patient 2 underwent robot-assisted laparoscopic radical prostatectomy 2 months ago, who was followed up by pelvic MRI and mesorectal lymph node metastasis was revealed. Both patients underwent fluorescence laparoscopic mesenteric lymphadenectomy in our department. With 4 to 6 month of follow-up after surgery, MRI examination showed no recurrence of tumor.

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BACKGROUND: The metastatic lymph node (LN) ratio (LNR) has shown to be an important prognostic factor in various gastrointestinal malignancies. Nevertheless, the prognostic significance of LNR in gallbladder carcinoma (GBC) remains to be determined. METHODS: From January 2007 to January 2018, 144 advanced GBC patients (T2-4 stages) who underwent curative surgery with at least 6 LNs retrieved were enrolled. Receiver operating characteristic (ROC) curve was performed to identify the optimal cut-off value for LNR. The clinicopathological features stratified by LNR level were analyzed. Meanwhile, univariate and multivariate Cox regression proportional hazard models were performed to identify risk factors for overall survival (OS). RESULTS: The optimal cut-off point for LNR was 0.28 according to the ROC curve. LNR>0.28 was associated with higher rate of D2 LN dissection (P=0.004) and higher tumor stages (P<0.001). Extent of liver resection, extrahepatic bile duct resection, tumor stage, LNR, margin status, tumor differentiation, and perineural invasion were associated with OS in univariate analysis (all P<0.05). GBC patients with LNR≤0.28 had a significantly longer median OS compared to those with LNR>0.28 (27.5 vs 18 months, P=0.004). Multivariate analysis indicated that tumor stage (T2 vs T3/T4; hazard ratio (HR) 1.596; 95% confidence interval (CI) 1.195-2.132), LNR (≤0.28 vs >0.28; HR 0.666; 95% CI 0.463-0.958), margin status (R0 vs R1; HR 1.828; 95% CI 1.148-2.910), and tumor differentiation (poorly vs well/moderately; HR 0.670; 95% CI 0.589-0.892) were independent prognostic factors for GBC (all P<0.05). CONCLUSIONS: LNR is correlated to advanced GBC prognosis and is a potential prognostic factor for advanced GBC with at least 6 LNs retrieved.

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BACKGROUND: Tumor-node-metastasis (TNM) staging is the central gastric cancer (GC) staging system, but it has some disadvantages. However, the lymph node ratio (LNR) can be used regardless of the type of lymphadenectomy and is considered an important prognostic factor. This study aimed to evaluate the relationship between LNR and survival in patients who underwent curative GC surgery. METHODS: All patients who underwent radical gastric surgery between January 2014 and June 2022 were retrospectively evaluated. Clinicopathological features of tumors, TNM stage, and survival rates were analyzed. LNR was defined as the ratio between metastatic lymph nodes and total lymph nodes removed. The LNR groups were classified as follows: LNR0 = 0, 0.01 < LNR1 ≤ 0.1, 0.1 < LNR2 ≤ 0.25 and LNR3 > 0.25. Tumor characteristics and overall survival (OS) of the patients were compared between LNR groups. RESULTS: After exclusion, 333 patients were analyzed. The mean age was 62 ± 14 years. According to the LNR classification, no difference was found between groups regarding age and sex. However, TNM stage III disease was significantly more common in LNR3 patients. Most patients (43.2%, n = 144) were in the LNR3 group. In terms of tumor characteristics (lymphatic, vascular, and perineural invasion), the LNR3 group had significantly poorer prognostic factors. The Cox regression model defined LNR3, TNM stage II-III disease, and advanced age as independent risk factors for survival. Patients with LNR3 demonstrated the lowest 5-year OS rate (35.7%) (estimated mean survival was 30 ± 1.9 months) compared to LNR 0-1-2. CONCLUSION: Our study showed that a high LNR was significantly associated with poor OS in patients who underwent curative gastrectomy. LNR can be used as an independent prognostic predictor in GC patients.

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Background and Objectives: Small bowel adenocarcinomas (SBAs) are rare tumors of the gastrointestinal system. Lymph node metastasis in patients with curatively resected SBAs is associated with poor prognosis. In this study, we determined the prognostic utility of the number of removed lymph nodes and the metastatic lymph node ratio (the N ratio). Materials and Methods: The data of 97 patients who underwent curative SBA resection in nine hospitals of Turkey were retrospectively evaluated. Univariate and multivariate analyses of potentially prognostic factors including the N ratio and the numbers of regional lymph nodes removed were evaluated. Results: Univariate analysis showed that perineural and vascular invasion, metastatic lymph nodes, advanced TNM stage, and a high N ratio were significant predictors of poor survival. Multivariate analysis revealed that the N ratio was a significant independent predictor of disease-specific survival (DSS). The group with the lowest N ratio exhibited the longest disease-free survival (DFS) and DSS; these decreased significantly as the N ratio increased (both, p < 0.001). There was no significant difference in either DFS or DSS between groups with low and high numbers of dissected lymph nodes (i.e., <13 and ≥13) (both, p = 0.075). Conclusions: We found that the N ratio was independently prognostic of DSS in patients with radically resected SBAs. The N ratio is a convenient and accurate measure of the severity of lymph node metastasis.

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This study aims to determine the diagnostic accuracy of staging PET/CT and neck MRI in patients with laryngeal carcinoma and to assess the value of PET/CT in predicting progression-free survival (PFS) and overall survival (OS). Sixty-eight patients who had both modalities performed before treatment between 2014 and 2021 were included in this study. The sensitivity and specificity of PET/CT and MRI were evaluated. PET/CT had 93.8% sensitivity, 58.3% specificity, and 75% accuracy for nodal metastasis, whereas MRI had 68.8%, 61.1%, and 64.7% accuracy, respectively. At a median follow-up of 51 months, 23 patients had developed disease progression and 17 patients had died. Univariate-survival analysis revealed all utilized PET parameters as significant prognostic factors for OS and PFS (p-value < 0.03 each). In multivariate analysis, metabolic-tumor volume (MTV) and total lesion glycolysis (TLG) predicted better PFS (p-value < 0.05 each). In conclusion, PET/CT improves the accuracy of nodal staging in laryngeal carcinoma over neck MRI and adds to the prognostication of survival outcomes through the use of several PET metrics.

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BACKGROUND: Immune checkpoint blockade (ICB) elicits a strong and durable therapeutic response, but its application is limited by disparate responses and its associated immune-related adverse events (irAEs). Previously, in a murine model of lymph node (LN) metastasis, we showed that intranodal administration of chemotherapeutic agents using a lymphatic drug delivery system (LDDS) elicits stronger therapeutic responses in comparison to systemic drug delivery approaches, while minimizing systemic toxicity, due to its improved pharmacokinetic profile at the intended site. Importantly, the LN is a reservoir of immunotherapeutic targets. We therefore hypothesized that metastatic LN-targeted ICB can amplify anti-tumor response and uncouple it from ICB-induced irAEs. METHODS: To test our hypothesis, models of LN and distant metastases were established with luciferase expressing LM8 cells in MXH10/Mo-lpr/lpr mice, a recombinant inbred strain of mice capable of recapitulating ICB-induced interstitial pneumonia. This model was used to interrogate ICB-associated therapeutic response and immune related adverse events (irAEs) by in vivo imaging, high-frequency ultrasound imaging and histopathology. qPCR and flowcytometry were utilized to uncover the mediators of anti-tumor immunity. RESULTS: Tumor-bearing LN (tbLN)-directed CTLA4 blockade generated robust anti-tumor response against local and systemic metastases, thereby improving survival. The anti-tumor effects were accompanied by an upregulation of effector CD8T cells in the tumor-microenvironment and periphery. In comparison, non-specific CTLA4 blockade was found to elicit weaker anti-tumor effect and exacerbated ICI-induced irAEs, especially interstitial pneumonia. Together these data highlight the importance of tbLN-targeted checkpoint blockade for efficacious response. CONCLUSIONS: Intranodal delivery of immune checkpoint inhibitors to metastatic LN can potentiate therapeutic response while minimizing irAEs stemming from systemic lowering of immune activation threshold.

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Indocyanine green (ICG) has been used to detect several types of tumors; however, its ability to detect metastatic lymph nodes (LNs) remains unclear. Our goal was to determine the feasibility of ICG in detecting metastatic LNs. We established a mouse model and evaluated the potential of ICG. The feasibility of detecting metastatic LNs was also evaluated in patients with lung or esophageal cancer, detected with computed tomography (CT) or positron-emission tomography (PET)/CT, and scheduled to undergo surgical resection. Tumors and metastatic LNs were successfully detected in the mice. In the clinical study, the efficacy of ICG was evaluated in 15 tumors and fifty-four LNs with suspected metastasis or anatomically key regional LNs. All 15 tumors were successfully detected. Among the fifty-four LNs, eleven were pathologically confirmed to have metastasis; all eleven were detected in ICG fluorescence imaging, with five in CT and seven in PET/CT. Furthermore, thirty-four LNs with no signals were pathologically confirmed as nonmetastatic. Intravenous injection of ICG may be a useful tool to detect metastatic LNs and tumors. However, ICG is not a targeting agent, and its relatively low fluorescence makes it difficult to use to detect tumors in vivo. Therefore, further studies are needed to develop contrast agents and devices that produce increased fluorescence signals.

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Background and Objectives: The purpose of this study is to evaluate the relationship between lymph node status (the number of resected lymph nodes; the number of metastatic lymph nodes, LNM, and lymph node ratio, LNR) and biochemical recurrence, disease-free survival (DFS), as well as overall survival (OS) in medullary thyroid carcinoma (MTC). Methods: This study enrolled MTC patients at Tianjin Medical University Cancer Institute and Hospital between 2011 and 2019. We used Logistic regression analysis, Cox regression models and Kaplan-Meier test to identify risk factors influencing biochemical recurrence, DFS, and OS. Results: We identified 160 patients who satisfied the inclusion criteria from 2011 to 2019. We used ROC analysis to define the cut-off value of LNR with 0.24. Multifocality, preoperative calcitonin levels, pathologic N stage, resected lymph nodes, LNM, LNR, and the American Joint Committee on Cancer (AJCC) clinical stage were significant (P < 0.05) prognostic factors influencing biochemical cure. In univariable analyses, gross extrathyroidal extension, preoperative calcitonin levels, pathologic T classification, pathologic N stage, resected lymph nodes, LNM, LNR, AJCC clinical stage, and biochemical cure were significant (P < 0.05) factors of DFS. When the multivariable analysis was performed, LNR was identified as predictor of DFS (HR = 4.818, 95% CI [1.270-18.276]). Univariable Cox regression models reflected that tumor size, pathologic N stage, and LNR were predictor of OS. Furthermore, multivariable analysis manifested that LNR was predictor of OS (HR = 10.061, 95% CI [1.222-82.841]). Conclusions: This study illustrated that LNR was independent prognostic factor of DFS and OS in MTC. In addition, LNR influenced biochemical cure. Further investigations are needed to determine the optimal cut-off value for predicting prognosis.

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This is a case of [68 Ga]Ga-Prostate-specific membrane antigen (PSMA)-11 PET/CT in a 73-years old patient presenting high Prostate Specific Antigen (PSA) levels despite both multi-parametric magnetic resonance imaging (mpMRI) and 12-core saturation biopsy negative for prostate cancer (Pca). This is a highly interesting case because, despite the advanced metastatic spread at initial presentation as showed by [68Ga]Ga-PSMA-PET/CT, the primary Pca was detected by none of the diagnostic techniques (12 random sample biopsy, mpMRI, PSMA PET/CT). However, [68Ga]Ga-PSMA-PET/CT showed a suspicious axillary lesion suitable for biopsy, which finally resulted as Pca metastasis. This case report is therefore a brilliant example of how [68Ga]Ga-PSMA-PET/CT optimized patient's management.

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PURPOSE: The Ki67 index and lymph node ratio (LNR) have been proposed as components of alternative pathological classification schemes, but the most appropriate classification for patients with medullary thyroid cancer (MTC) remains unknown. The aim of the present study was to examine the usefulness of a new grading system combining the Ki67 index and LNR as a predictor of prognostic and disease-free survival (DFS) in MTC. METHODS: We conducted a retrospective study of patients with MTC who were registered at Sun Yat-sen University Cancer Center, Guangzhou, P. R. China from June 2003 to October 2021. The DFS rates were assessed using risk-adjusted Cox proportional hazard regression modeling to explore the relationship among pathological features, nutritional status and DFS. The Ki67 index (cutoff value: 5% and 10%) and LNR (cutoff value: 0.2 and 0.3) were combined to create a new grading system. RESULTS: In total, 101 matched patients were assessed. The integrated grading system showed better separation of Kaplan Meier (KM) curves for DFS. As the grading stage progressed, there was a significant stepwise decrease in DFS, which was better than Ki67, LNR and N staging alone. According to the grading system, the high-risk group had a worse prognosis. CONCLUSION: The proposed grading scheme demonstrated a better prognostic performance in MTC patients than the Ki67, LNR and N staging alone. However, larger scale studies are needed to further verify our findings.

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IMPORTANCE: Accurate pre-treatment prediction of distant metastasis in patients with Nasopharyngeal Carcinoma (NPC) enables the implementation of appropriate treatment strategies for high-risk individuals. PURPOSE: To develop and assess a Convolutional Neural Network (CNN) model using pre-therapy Magnetic Resonance (MR) imaging to predict distant metastasis in NPC patients. METHODS: We retrospectively reviewed data of 441 pathologically diagnosed NPC patients who underwent complete radiotherapy and chemotherapy at Renmin Hospital of Wuhan University (Hubei, China) between February 2012 and March 2018. Using Adobe Photoshop, an experienced radiologist segmented MR images with rectangular regions of interest. To develop an accurate model according to the primary tumour, Cervical Metastatic Lymph Node (CMLN), the largest area of invasion of the primary tumour, and image segmentation methods, we constructed intratumoural and intra-peritumoural datasets that were used for training and test of the transfer learning models. Each model's precision was assessed according to its receiver operating characteristic curve and accuracy. Generated high-risk-related Grad-Cams demonstrated how the model captured the image features and further verified its reliability. RESULTS: Among the four models, all intra-peritumoural datasets performed better than the corresponding intratumoural datasets, with the CMLN intra-peritumoural dataset exhibiting the best performance (average area under the curves (AUCs) = 0.88). There was no significant difference between average AUCs of the Max and NPC tumour datasets. AUCs of the eight datasets for the four models were higher than those of the Tumour-Node-Metastasis staging system (AUC=0.67). In most datasets, the xception model had higher AUCs than other models. The efficientnet-b0 and xception models efficiently extracted high-risk features. CONCLUSION: The CNN model predicted distant metastasis in NPC patients with high accuracy. Compared to the primary tumour, the CMLN better predicted distant metastasis. In addition to intratumoural data, peritumoural information can facilitate the prediction of distant metastasis. With a larger sample size, datasets of the largest areas of tumour invasion may achieve meaningful accuracy. Among the models, xception had the best overall performance.

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BACKGROUND: No specific guideline exists for risk stratification based on lymph node (LN) status in pediatric thyroid cancer. The purpose of our study is to identify optimal values of lymph node ratio (LNR) and largest metastatic LN size for predicting recurrent/persistent disease, especially in children with lateral neck metastasis (N1b). METHODS: We conducted a retrospective study from January 1997 to June 2018 at Samsung Medical Center. A total of 50 papillary thyroid carcinoma (PTC) patients who underwent total thyroidectomy + both central neck dissection (CND) + modified radical neck dissection (MRND) (unilateral or bilateral) was enrolled. RESULTS: The median follow-up duration was 60.8 months (range, 6.2-247 months). The mean age was 14.6 years, and the mean tumor size was 2.9 cm. Mean size of the largest metastatic LN was 1.5 cm. Mean value of central LNR was 0.6, and mean value of lateral LNR was 0.3. Largest metastatic LN size [HR = 2.0 (95% CI 1.0-4.0), p = 0.040] and lateral LNR [HR = 43.6 (95% CI 2.2-871.0), p = 0.014] were significant prognostic factors for recurrence. The optimal combination of lateral LNR and largest metastatic LN size to predict recurrence were 0.3 and 2.5 cm, respectively, with the largest AUC (AUC at 60 months = 77.4) and significant p-value (p = 0.009 and p = 0.021) (Table 3). Kaplan-Meier curves showed significant differences in recurrence-free survival (RFS) rates among four groups (Fig. 2A,2B). CONCLUSIONS: In pediatric PTC patients with N1b, lateral LNR and largest metastatic LN size are significant predictors for recurrence. Children with lateral LNR > 0.3 or any metastatic lymph node > 2.5 cm in the largest dimension have higher risk for recurrence. Children are classified as extensive N1b if lateral LNR > 0.3 or pathologic N1 with largest LN size > 2.5 cm, and vice versa.

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Cervical cancer (CC) is one of the most frequent female malignancies worldwide. However, the molecular mechanism of lymph node metastasis in CC remains unclear. In this study, we investigated the transcriptome profile of 51,507 single cells from primary tumors, positive lymph nodes (P-LN), and negative lymph nodes (N-LN) using single-cell sequencing. Validation experiments were performed using bulk transcriptomic datasets and immunohistochemical assays. Our results indicated that epithelial cells in metastatic LN were associated with cell- cycle-related signaling pathways, such as E2F targets, and mitotic spindle, and immune response-related signaling pathways, such as allograft rejection, IL2_STAT5_signaling, and inflammatory response. However, epithelial cells in primary tumors exhibited high enrichment of epithelial-mesenchymal translation (EMT), oxidative phosphorylation, and interferon alpha response. Our analysis then indicated that metastasis LN exhibited an early activated tumor microenvironment (TME) characterized by the decrease of naive T cells and an increase of cytotoxicity CD8 T cells, NK cells, FOXP3+ Treg cells compared with normal LN. By comparing the differently expressed gene of macrophages between tumor and metastatic LN, we discovered that C1QA+ MRC1low macrophages were enriched in a tumor, whereas C1QA+ MRC1high macrophages were enriched in metastatic LN. Finally, we demonstrated that cancer-associated fibroblasts (CAFs) in P-LN were associated with immune regulation, while CAFs in tumor underwent EMT. Our findings offered novel insights into the mechanisms of research, diagnosis, and therapy of CC metastasis.

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