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To explore the application value of postoperative contrast-enhanced ultrasound (CEUS) parameters for lymph node metastasis (LNM), tumor, node, metastasis staging, and treatment response evaluation of resected hepatocellular carcinoma (HCC). We retrospectively analyzed 100 patients with liver cancer who underwent liver CEUS at our hospital between October 2020 and October 2022. The patient's LNM, pathological staging, and therapeutic effects were recorded based on the histopathological results. CEUS parameters were analyzed and compared CEUS parameters between different lymph node metastases, pathological stages, and therapeutic effects. Twenty-three patients experienced LNM, 77 patients did not experience LNM; and the rise time (RT), peak intensity (PI), and area under the curve (AUC) of the metastatic group were significantly smaller than those of the nonmetastatic group (P < .05). 44 cases were classified into groups I to II by pathological staging, and 56 cases were classified into groups III to IV. The RT, PI, and AUC of groups III to IV were significantly lower than those of groups I-II (P < .05). Seventy-nine cases were complete necrosis, 21 cases were residual or recurrent; The RT, PI, and AUC of the residual or recurrent group were significantly lower than those of the complete necrosis group (P < .05). The receiver operating characteristic curve shows that RT, PI, and AUC have a certain value in evaluating LNM, pathological staging, and treatment response of HCC, and the combined evaluation/evaluation value of these 3 factors is relatively high. The postoperative CEUS parameters RT, PI, and AUC can be used for LNM, pathological staging evaluation, and treatment response evaluation of HCC. Moreover, the combination of the 3 parameters is feasible and valuable in evaluating LNM, tumor, node, metastasis staging, and treatment response of HCC., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Background: The pragmatic role of dynamic contrast-enhanced magnetic resonance lymphangiography (DCMRL) needs to be evaluated and compared across distinct lymphatic disorders. We aimed to evaluate the performance of DCMRL for identifying the underlying causes of lymphatic disorders and to define the potential benefit of DCMRL for planning lymphatic interventions., Methods: Patients who underwent DCMRL between August 2017 and July 2022 were included in this retrospective analysis. DCMRL was performed with intranodal injection of a gadolinium-based contrast medium through inguinal lymph nodes under local anesthesia. Technical success of DCMRL and feasibility of percutaneous embolization were assessed based on the lymphatic anatomy visualized by DCMRL. Based on the underlying causes, clinical outcomes were evaluated and compared., Results: Seventy consecutive patients were included. The indications were traumatic chylothorax (n = 42), traumatic chylous ascites (n = 11), and nontraumatic lymphatic leak (n = 17). The technical success rate of DCMRL was the highest in association with nontraumatic lymphatic disorders (94.1% [16/17]), followed by traumatic chylothorax (92.9% [39/42]) and traumatic chylous ascites (81.8% [9/11]). Thirty-one (47.7%) patients among 65 patients who underwent technically successful DCMRL had feasible anatomy for intervention. Clinical success was achieved in 90.3% (28/31) of patients with feasible anatomy for radiologic intervention, while 62.5% (10/16) of patients with anatomical challenges showed improvement. Most patients with traumatic chylothorax showed improvement (92.9% [39/42]), whereas only 23.5% (4/17) of patients with nontraumatic lymphatic disorders showed clinical improvement., Conclusion: DCMRL can help identify the underlying causes of lymphatic disorders. The performance of DCMRL and clinical outcomes vary based on the underlying cause. The feasibility of lymphatic intervention can be determined using DCMRL, which can help in predicting clinical outcomes., Competing Interests: The authors have no potential conflicts of interest to disclose., (© 2024 The Korean Academy of Medical Sciences.)

Objective: Radiotherapy is a crucial treatment modality for pelvic cancers, but uncertainties persist in defining the clinical target volume (CTV) for the inguinal lymphatic drainage region. Suboptimal CTV delineation may compromise treatment efficacy and result in subpar disease control. This study aimed to investigate and map the distribution of lymph node metastases (LNM) in the groin area to facilitate an improved and detailed CTV definition using 18 F-fluorodeoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT)., Methods: Inguinal LNM in patients with biopsy-proven pelvic malignancies were identified using 18 F-FDG PET/CT scan. The longitudinally nearest axial plane was determined based on six typical bony landmarks, and the axial direction relative to the femoral artery of LNM was recorded. The distances from the LNM to the nearest edge of the femoral artery were measured on the axial plane. An optimal margin to cover 95% of LNM was estimated to develop contouring recommendations., Results: In this study, 500 positive LNM were identified by 18 F-FDG PET/CT among 185 patients with primary pelvic malignancies. Relative to the femoral artery, lymph nodes were distributed laterally (10:00-11:00, n = 35), anteriorly (12:00-1:00, n = 213), and medially (2:00-4: 00, n = 252). For CTV delineation, the recommended distances from the femoral artery on the SFH were lateral 19 mm, anterior 19 mm, and medial 25 mm; on the SGT were lateral 26 mm, anterior 20 mm, and medial 25 mm; on the SPS were lateral 28 mm, anterior 29 mm, and medial 26 mm; on the IPS were anterior 29 mm and medial 28 mm; on the IIT were anterior 27 mm and medial 27 mm; on the ILT were anterior 25 mm and medial 23 mm. Use interpolation to contour the area between six axial slices, including any radiographically suspicious LNM., Conclusions: Using 18 F-FDG PET/CT, we investigated the distribution pattern of inguinal LNM and propose a more comprehensive guideline for inguinal CTV delineation., (© 2024. The Author(s).)

Purpose: To develop and evaluate a nomogram that integrates clinical parameters with deep learning radiomics (DLR) extracted from Magnetic Resonance Imaging (MRI) data to enhance the predictive accuracy for preoperative lymph node (LN) metastasis in rectal cancer., Methods: A retrospective analysis was conducted on 356 patients diagnosed with rectal cancer. Of these, 286 patients were allocated to the training set, and 70 patients comprised the external validation cohort. Preprocessed T2-weighted and diffusion-weighted imaging performed preoperatively facilitated the extraction of DLR features. Five machine learning algorithms-k-nearest neighbor, light gradient boosting machine, logistic regression, random forest, and support vector machine-were utilized to develop DLR models. The most effective algorithm was identified and used to establish a clinical DLR (CDLR) nomogram specifically designed to predict LN metastasis in rectal cancer. The performance of the nomogram was evaluated using receiver operating characteristic curve analysis., Results: The logistic regression classifier demonstrated significant predictive accuracy using the DLR signature, achieving an Area Under the Curve (AUC) of 0.919 in the training cohort and 0.778 in the external validation cohort. The integrated CDLR nomogram exhibited robust predictive performance across both datasets, with AUC values of 0.921 in the training cohort and 0.818 in the external validation cohort. Notably, it outperformed both the clinical model, which had AUC values of 0.770 and 0.723 in the training and external validation cohorts, respectively, and the stand-alone DLR model., Conclusion: The nomogram derived from multiparametric MRI data, referred to as the CDLR model, demonstrates strong predictive efficacy in forecasting LN metastasis in rectal cancer., (© 2024. The Author(s).)

Background: Definitive concurrent chemoradiotherapy (CCRT) is the standard treatment for locally advanced, inoperable non-small cell lung cancer (NSCLC). Previous studies have mainly focused on examining local failure and recurrence patterns after surgery and the principles of lymph node metastasis (LNM) in surgical candidates with NSCLC. However, these studies were just only able to guide postoperative radiotherapy (PORT) and the patterns of LNM in patients with resected NSCLC was inadequate to represent that in locally advanced inoperable NSCLC patients for guiding target volume delineation of CCRT. In this study, we aimed to analyze the metastasis regularities and establish the correlations between different lymph node levels in NSCLC patients without any intervention using positron emission tomography/computed tomography (PET/CT) images., Methods: Overall, 358 patients with N1-N3 NSCLC admitted in our hospital between 2018 and 2022 were retrospectively analyzed. The diagnosis of metastatic lymph nodes was reviewed and determined using the European Organization for Research and Treatment of Cancer standard and the standardized value of the PET/CT examination. Univariate and multivariate analysis were performed to investigate the correlations between the different levels were evaluated by using of the chi-square test and logistic regression model., Results: The lymph nodes with the highest metastasis rates in patients with left lung cancer were in order as follows: 10L, 4L, 5, 4R, and 7; while in those with right lung cancer they were 10R, 4R, 7, 2R, and 1R. Notably, we found left lung patients were more likely to have contralateral hilar, mediastinal and supraclavicular lymph nodes involved, and the right lung group exhibited a higher propensity for ipsilateral mediastinum and supraclavicular lymph node invasion. Furthermore, correlation analysis revealed there were significant correlative patterns in the LNM across different levels., Conclusions: This study elucidated the patterns of primary LNM in patients with NSCLC who had not undergone surgery (without any treatment interventions) and the correlations between lymph node levels. These findings were expected to provide useful reference for target volume delineation in definitive concurrent chemoradiotherapy in locally advanced NSCLC patients., (© 2024. The Author(s).)

Purpose: Lympho-vascular invasion (LVI) and perineural invasion (PNI) have been established as prognostic factors in various types of cancers. The preoperative prediction of LVI and PNI has the potential to guide personalized medicine strategies for patients with esophageal squamous cell cancer (ESCC). This study investigates whether radiomics features derived from preoperative contrast-enhanced CT could predict LVI and PNI in ESCC patients., Methods and Materials: A retrospective cohort of 544 ESCC patients who underwent esophagectomy were included in this study. Preoperative contrast-enhanced CT images, pathological results of PNI and LVI, and clinical characteristics were collected. For each patient, the gross tumor volume (GTV-T) and lymph nodes volume (GTV-N) were delineated and four categories of radiomics features (first-order, shape, textural and wavelet) were extracted from GTV-T and GTV-N. The Mann-Whitney U test was used to select significant features associated with LVI and PNI in turn. Subsequently, radiomics signatures for LVI and PNI were constructed using LASSO regression with ten-fold cross-validation. Significant clinical characteristics were combined with radiomics signature to develop two nomogram models for predicting LVI and PNI, respectively. The area under the curve (AUC) and calibration curve were used to evaluate the predictive performance of the models., Results: The radiomics signature for LVI prediction consisted of 28 features, while the PNI radiomics signature comprised 14 features. The AUCs of the LVI radiomics signature were 0.77 and 0.74 in the training and validation groups, respectively, while the AUCs of the PNI radiomics signature were 0.69 and 0.68 in the training and validation groups. The nomograms incorporating radiomics signatures and significant clinical characteristics such as age, gender, thrombin time and D-Dimer showed improved predictive performance for both LVI (AUC: 0.82 and 0.80 in the training and validation group) and PNI (AUC: 0.75 and 0.72 in the training and validation groups) compared to the radiomics signature alone., Conclusion: The radiomics features extracted from preoperative contrast-enhanced CT of gross tumor and lymph nodes have demonstrated their potential in predicting LVI and PNI in ESCC patients. Furthermore, the incorporation of clinical characteristics has shown additional value, resulting in improved predictive performance., (© 2024. The Author(s).)

The presence and extent of metastatic disease in axillary lymph nodes (ALNs) in the setting of breast cancer (BC) are important factors for staging and therapy planning. The purpose of this study was to perform a multiparametric sonographic evaluation of ALNs to better differentiate between benign and metastatic nodes. Ninety-nine patients (mean age 54.1 y) with 103 BCs were included in this study, and 103 ALNs were examined sonographically. B-mode parameters, such as size in two dimensions, shape, cortical thickness and capsule outline, were obtained, followed by vascularity assessment via colour Doppler and microflow imaging and stiffness evaluation via shear wave elastography. Postoperative histopathological evaluation was the reference standard. In the statistical analysis, logistic regression and ROC analyses were conducted to search for feature patterns of both types of ALNs to evaluate the prediction qualities of the analysed variables and their combinations. For a cortex larger than 3 mm, without a circumscribed margin of the LN capsule and SWE (E max > 26 kPa), the AUC was 0.823. Multiparametric assessment, which combined conventional US, quantitative SWE and vascularity analysis, was superior to the single-parameter approach in the evaluation of ALNs., (© 2024. The Author(s).)

The deep learning (DL)-based prediction of accurate lymph node (LN) clinical target volumes (CTVs) for nasopharyngeal carcinoma (NPC) radiotherapy (RT) remains challenging. One of the main reasons is the variability of contours despite standardization processes by expert guidelines in combination with scarce data sharing in the community. Therefore, we retrospectively generated a 262-subjects dataset from four centers to develop the DL models for LN CTVs delineation. This dataset included 440 computed tomography images from different scanning phases, disease stages and treatment strategies. Three clinical expert boards, each comprising two experts (totalling six experts), manually delineated six basic LN CTVs on separate cohorts as the ground truth according to LN involvement and clinical requirements. Several state-of-the-art segmentation algorithms were evaluated on this benchmark, showing promising results for LN CTV segmentation. In conclusion, this work built a multicenter LN CTV segmentation dataset, which may be the first dataset for automatic LN CTV delineation development and evaluation, serving as a benchmark for future research., (© 2024. The Author(s).)

Background: Breast cancer is the leading cause of cancer-related deaths in the female population. Axillary lymph nodes (ALN) are a group of the most common metastatic sites of breast cancer. Timely assessment of ALN status is of paramount clinical importance for medical decision making., Aims: To utilize contrast-enhanced ultrasound (CEUS)-based radiomics models for noninvasive pretreatment prediction of ALN status., Methods and Results: Clinical data and pretreatment CEUS images of primary breast tumors were retrospectively studied to build radiomics signatures for pretreatment prediction of nodal status between May 2015 and July 2021. The cases were divided into the training cohorts and test cohorts in a 9:1 ratio. The mRMR approach and stepwise forward logistic regression technique were used for feature selection, followed by the multivariate logistic regression technique for building radiomics signatures in the training cohort. The confusion matrix and receiver operating characteristic (ROC) analysis were used for accessing the prediction efficacy of the radiomics models. The radiomics models, which consist of six features, achieved predictive accuracy with the area under the ROC curve (AUC) of 0.713 in the test set for predicting lymph node metastasis., Conclusion: The CEUS-based radiomics is promising to be developed as a reliable noninvasive tool for predicting ALN status., (© 2024 The Author(s). Cancer Reports published by Wiley Periodicals LLC.)

Background: Breast cancer-related lymphedema (BCRL) is a disabling and frequently occurring condition after treatment for breast cancer. Studying lymph anatomy by means of indocyanine green (ICG) lymphography is a promising tool to help better understand BCRL. The aim of this study is to investigate the relation between ICG lymphography characteristics and the risk of developing BCRL. Methods and Results: Patients scheduled for breast surgery with either unilateral axillary lymph node dissection or sentinel lymph node biopsy between November 2017 and May 2019 were included. Patients were assessed at baseline and up to 36 months postsurgery. BCRL was defined as an increase of ≥5% relative arm volume difference compared with the presurgical difference. In total, 128 patients were included. During 36 months of follow-up, 45 patients (35.2%) developed BCRL. The number of lymph vessels before surgery was not a statistically significant risk factor for developing BCRL ( p = 0.8485). However, an increase in the number of lymph vessels compared with baseline was a significant protective factor for developing BCRL (odds ratio = 0.8). An increase of one lymph vessel corresponds to a 19% relative risk reduction of developing BCRL. The presence of lymph nodes at baseline and the change in the presence of lymph nodes compared with baseline were no predictors for the development of BCRL ( p = 0.0986 and p = 0.8910, respectively). Conclusions: An increase in the number of lymph vessels visualized by ICG lymphography compared with baseline is a protective factor for developing BCRL. Therapies with the ability to increase the number of lymph vessels can thus possibly decrease the risk of developing BCRL.

Competing Interests: Die Autorinnen/Autoren geben an, dass kein Interessenkonflikt besteht.

Introduction: In this study, we investigated the clinical outcomes of patients who underwent surgery with proven lymph node metastasis., Methods: Patients who were operated for lung cancer with pN1 or pN2 were examined in the study. The clinicopathological features and survival of the subjects were evaluated according to pN1-pN2 status, presence of neoadjuvant treatment, Positron emission tomography and computed tomography (PET/CT) avidity on mediastinal lymph nodes and specific lymph node stations., Results: The study examines 100 patients operated from January 2016 to December 2021. Number of cases with pN1 and pN2 disease were 45 (45%) and 55 (55%) respectively. Thirty (30%) patients received neoadjuvant treatment. The 5-year overall survival (OS) and disease-free survival (DFS) of the patients were computed as 42.5% and 42.4% correspondingly. The 5-year cancer-related survival was 55.3%. In pN2 cohort, 5-year DFS was 67.9% in the neoadjuvant group and 15.9% in the non-neoadjuvant group (P = 0.042). In non-neoadjuvant group, 5-year DFS was 19.9% in cases with mediastinal PET/CT avidity and 56.3% in patients without mediastinal PET/CT avidity (P = 0.018). In pN2 disease, the presence of subcarinal or paratracheal lymph node metastasis did not create a significant difference in 5-year OS or DFS, but pulmonary ligament lymph node metastasis was found to be linked with worse survival in both 5-year OS (P = 0.005) and DFS (P = 0.017)., Conclusion: The main elements related with poor prognosis were absence of neoadjuvant treatment and pulmonary ligament lymph node metastasis in pN2 disease, detecting PET/CT avid mediastinal lymph nodes in non-neoadjuvant group., (© 2024 Royal Australasian College of Surgeons.)

Background: The status of axillary lymph nodes (ALN) plays a critical role in the management of patients with breast cancer. It is an urgent demand to develop highly accurate, non-invasive methods for predicting ALN status., Purpose: To evaluate the efficacy of ultrasound radiofrequency (URF) time-series parameters, in combination with clinical data, in predicting ALN metastasis in patients with breast cancer., Material and Methods: We prospectively gathered clinicopathologic and ultrasonic data from patients diagnosed with breast cancer. Various machine-learning (ML) models were developed using all available features to determine the most efficient diagnostic model. Subsequently, distinct prediction models were created using the optimal ML model, and their diagnostic performances were evaluated and compared., Results: The study encompassed 240 patients, of whom 88 had lymph node metastases. A leave-one-out cross-validation (LOOCV) method was used to split the entire dataset into training and testing subsets. The random forest ML model outperformed the other algorithms, with an area under the curve (AUC) of 0.92. Prediction models based on clinical, ultrasonic, URF parameters, clinical + ultrasonic, clinical + URF, and ultrasonic + URF parameters had AUCs of 0.56, 0.79, 0.78, 0.90, 0.80, and 0.84, respectively, in the testing set. The comprehensive diagnostic model (clinical + ultrasonic + URF parameters) demonstrated strong diagnostic capability, with an AUC of 0.94 in the testing set, exceeding any single prediction model., Conclusion: The combined model (clinical + ultrasonic + URF parameters) could be used preoperatively to predict lymph node status, offering valuable input for the design of individualized surgical approaches., Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Objectives: The aim was to assess the technical success of percutaneous ultrasound-guided fine needle aspirates of gastrointestinal wall lesions and evaluate predictors of success. Secondary aims included comparing the cytological diagnosis with histopathology, evaluating the utility of concurrent locoregional lymph node cytology and assessing the procedure's complication rate., Material and Methods: Gastrointestinal wall cytology from 75 dogs and 70 cats obtained between 2018 and 2023 were reviewed and categorised as successful (resulting in a diagnostic cytology report) and accurate (resulting in the correct diagnosis when compared to histopathology). Unsuccessful fine needle aspirates, not submitted for cytology, were not recorded. Variables recorded included animal signalment, lesion and lymph node's appearance on ultrasound, size, location, number of smears submitted and experience of the ultrasonographer., Results: One hundred and fifty-two reports were analysed. Eighty-eight (58%) were successful: three normal epithelium, 21 inflammatory processes and 64 neoplasms. Variables associated with increased technical success included description of a mass, higher number of slides submitted and thickness of gastrointestinal lesion on ultrasound. Comparison with histopathology, performed for 17 lesions, showed discrepancies in eight, complete agreement in seven and partial in two. Eighty-four loco-regional lymph nodes were sampled, of which, 67 were successful (80%) and 52 brought additional clinical information (supporting GI wall cytology or diagnosing neoplasia not identified on GI wall cytology). No complication strictly attributable to gastrointestinal wall sampling was reported but when possibly related, death of the patient occurred in 2.5% of cases., Clinical Significance: Ultrasound-guided fine needle aspirate of gastrointestinal wall had moderate accuracy and was unsuccessful in 42% of cases, but technical success increased when sampling mass lesions, thicker intestinal layers and submitting more slides., (© 2024 The Author(s). Journal of Small Animal Practice published by John Wiley & Sons Ltd on behalf of British Small Animal Veterinary Association.)

To develop a clinical-radiomics nomogram based on spectral CT multi-parameter images for predicting lymph node metastasis in colorectal cancer. A total of 76 patients with colorectal cancer and 156 lymph nodes were included. The clinical data of the patients were collected, including gender, age, tumor location and size, preoperative tumor markers, etc. Three sets of conventional images in the arterial, venous, and delayed phases were obtained, and six sets of spectral images were reconstructed using the arterial phase spectral data, including virtual monoenergetic images (40 keV, 70 keV, 100 keV), iodine density maps, iodine no water maps, and virtual non-contrast images. Radiomics features of lymph nodes were extracted from the above images, respectively. Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were used to select features. A clinical model was constructed based on age and carcinoembryonic antigen (CEA) levels. The radiomics features selected were used to generate a composed radiomics signature (Com-RS). A nomogram was developed using age, CEA, and the Com-RS. The models' prediction efficiency, calibration, and clinical application value were evaluated by the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis, respectively. The nomogram outperforms the clinical model and the Com-RS (AUC = 0.879, 0.824). It is well calibrated and has great clinical application value. This study developed a clinical-radiomics nomogram based on spectral CT multi-parameter images, which can be used as an effective tool for preoperative personalized prediction of lymph node metastasis in colorectal cancer., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Purpose: To determine the performance of volumetric dual energy low kV and iodine radiomic features for the differentiation of intrathoracic lymph node histopathology, and influence of contrast protocol., Materials and Methods: Intrathoracic lymph nodes with histopathologic correlation (neoplastic, granulomatous sarcoid, benign) within 90 days of DECT chest imaging were volumetrically segmented. 1691 volumetric radiomic features were extracted from iodine maps and low-kV images, totaling 3382 features. Univariate analysis was performed using 2-sample t-test and filtered for false discoveries. Multivariable analysis was used to compute AUCs for lymph node classification tasks., Results: 129 lymph nodes from 72 individuals (mean age 61 ± 15 years) were included, 52 neoplastic, 51 benign, and 26 granulomatous-sarcoid. Among all contrast enhanced DECT protocol exams (routine, PE and CTA), univariable analysis demonstrated no significant differences in iodine and low kV features between neoplastic and non-neoplastic lymph nodes; in the subset of neoplastic versus benign lymph nodes with routine DECT protocol, 199 features differed (p = .01- < 0.05). Multivariable analysis using both iodine and low kV features yielded AUCs >0.8 for differentiating neoplastic from non-neoplastic lymph nodes (AUC 0.86), including subsets of neoplastic from granulomatous (AUC 0.86) and neoplastic from benign (AUC 0.9) lymph nodes, among all contrast protocols., Conclusions: Volumetric DECT radiomic features demonstrate strong collective performance in differentiation of neoplastic from non-neoplastic intrathoracic lymph nodes, and are influenced by contrast protocol., Competing Interests: Declaration of competing interest SLW disclosed no relevant relationships. WHM research collaborator with Siemens Healthineers. TO Siemens Healthineers employee. PB disclosed no relevant relationships. JPK Speaker honorarium and research collaborator Siemens Healthineers. LA speaker honorarium and research collaborator with Siemens Healthineers., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Introduction: This study examines the relationship between location of the primary tumor and specific nodal metastases in clinical stage 1 non-small cell lung cancer (NSCLC) patients undergoing lobectomy., Methods: We retrospectively analyzed all lobectomies performed at a single institution, between January 2005 and December 2019, for clinical stage I NSCLC patients. Patients selected for this study were clinically node negative (cN0) by positron emission tomography-computed tomography scan and selectively by endobronchial ultrasound or mediastinoscopy. Cases of postoperative pathologic nodal upstaging were identified among these patients. For each patient upstaged, the specific lymph node stations found to be positive were recorded. Descriptive statistics, chi-squared tests, and Fisher's exact test were utilized to identify independent risk factors for upstaging to specific N1 and N2 lymph node stations. All clinical and pathologic staging information was retrospectively normalized to the International Association for the Study of Lung Cancer 8th Edition TNM Classification., Results: The research cohort included 645 patients. The mean age was 68 years (standard deviation ± 9.2), 54% were female, and 88% were White, 11% Black, and 1% other. Twelve percent (n = 75) were upstaged from cN0 to pN1 or pN2 upon final pathologic examination: 41 to pN1 (54.7%) and 34 to pN2 (45.3%). The primary tumor location with the highest rate of nodal upstaging was the left upper lobe (LUL) (12.8%). Tumors in the right middle lobe had the lowest rate of unsuspected nodal metastases (8.8%). Out of all upstaged patients, there were no positive level eight lymph nodes, and only 1 patient with a positive level nine lymph node. Lymph node levels five and six were only positive in LUL primary tumors, a relationship that approached statistical significance (P = 0.0797). No patients with a LUL primary tumor had a positive level seven lymph node. Upstaging at station 12 was significantly associated with the location of the primary tumor, occurring less often in tumors originating in the right upper lobe in comparison to other lobes (P = 0.0288)., Conclusions: We identified relationships between the location of a primary tumor and specific nodal upstaging in patients with clinical stage I NSCLC who undergo lobectomy. We found the following: 1) only 1 patient had a positive level eight or nine lymph node out of 645 patients; 2) only LUL primary tumors demonstrated upstaging to level five or six lymph nodes; and 3) right upper lobe tumors were significantly less likely to be associated with a positive level 12 lymph node., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Accurate diagnosis of lymph node (LN) metastasis is vital for prognosis and treatment in patients with breast cancer. Imaging 1modalities such as ultrasound (US), MRI, CT, and 18F-FDG PET/CT are used for preoperative assessment. While conventional US is commonly recommended due to its resolution and sensitivity, it has limitations such as operator subjectivity and difficulty detecting small metastases. This review shows the microanatomy of axillary LNs to enhance accurate diagnosis and the characteristics of contrast-enhanced US (CE-US), which utilizes intravascular microbubble contrast agents, making it ideal for vascular imaging. A significant focus of this review is on distinguishing between two types of CE-US techniques for axillary LN evaluation: perfusion CE-US and lymphatic CE-US. Perfusion CE-US is used to assess LN metastasis via transvenous contrast agent administration, while lymphatic CE-US is used to identify sentinel LNs and diagnose LN metastasis through percutaneous contrast agent administration. This review also highlights the need for future research to clarify the distinction between studies involving "apparently enlarged LNs" and "clinical node-negative" cases in perfusion CE-US research. Such research standardization is essential to ensure accurate diagnostic performance in various clinical studies. Future studies should aim to standardize CE-US methods for improved LN metastasis diagnosis, not only in breast cancer but also across various malignancies., (© 2024. The Author(s).)

Background: Due to the establishment of screening mammography for breast cancer detection, the number of non-palpable lesions has increased. Thus, an optimal localization system is mandatory for the excision of non-palpable breast tumors., Objective: The aim of the study is to report the feasibility Surgical Marker Navigation (SMN) system Sirius Pintuition® for the excision of non-palpable breast tumors and non-palpable axillary lymph nodes., Methods: A retrospective observational study of patients undergoing breast-conserving surgery and lymph node excision guided by SMN between December 2022 and May 2023 was performed., Results: A total of 84 patients underwent excision of non-palpable breast tumors (77; 91.7%) or non-palpable axillary lymph-nodes (7; 8.3%) using SMN. In total, 94 markers were placed, in 74 patients (88.1%) only one marker was placed, whereas in 10 patients (11.9%) two markers were placed to correctly localize the lesion in the operating room. Most markers were placed using ultrasonographic guidance (69; 82.1%). Seventy-seven patients underwent breast-conserving surgery (91.7%) and 7 (8.3%) lymph node excision. In 10 cases (11.9%), the marker was accidentally displaced during surgery due to the use of magnetized instruments, although the specimen could be removed. In sum, all the markers were removed from the patients, although the marker retrieval rate, as we defined it (percentage of patients in whom the initial excised specimen contained the marker divided by the total number of patients), was 88.1%., Conclusion: The use of Sirius Pintuition® SMN for non-palpable breast tumors and non-palpable lymph nodes is feasible, with a retrieval rate of 88.1%., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: Prostate-specific membrane antigen (PSMA)-targeted radioguided surgery (RGS) has gained increased interest in prostate cancer (PCa). This analysis aims to evaluate the feasibility, safety, and limitations of RGS with a novel drop-in gamma probe in primary PCa., Patients and Methods: The data of 13 patients with primary PCa undergoing RGS were analyzed retrospectively. After preoperative administration of 99m Tc-PSMA-I&S, a SPECT/CT was conducted and a robotic radical prostatectomy was performed the following day including intraoperative assessment of the lymph node stations using a novel robotic drop-in gamma probe. This was followed by an extended pelvic lymph node dissection (ePLND) with ex vivo control measurement using the drop-in and a conventional rigid gamma probe., Results: Eleven patients (median PSA value of 11 ng/mL) had high-risk and 2 patients had intermediate-risk PCa. Overall, a median of 22 ePLND lymph nodes were dissected. In 1 patient, preoperative SPECT/CT imaging showed suspicious lymph nodes, which could be confirmed intraoperatively with the robotic drop-in probe and subsequently in the final histopathological analysis. RGS failed to identify 2 patients with micrometastases (<3 mm) preoperatively and intraoperatively. No postoperative complications related to 99m Tc-PSMA-I&S RGS or ePLND occurred., Conclusions: RGS with the novel drop-in gamma probe and 99m Tc-PSMA-I&S allows for a reliable intraoperative screening for lymph node metastases in robot-assisted radical prostatectomy for primary PCa with an acceptable safety profile. However, limitations in the detection of micrometastases need to be overcome before omitting extended ePLND in patients at risk for lymphatic spread., Competing Interests: Conflicts of interest and sources of funding: No external funding or sponsorship was received for this study or publication of this article. N.N.H. has received honoraria for presentations from Intuitive Surgical, Janssen, and Pajunk, and compensation for travel from Bayer, Astellas, Pfizer, and Janssen. C.F. has obtained compensation for travel by Lightpoint. O.K. has received compensation for travel from Astellas., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: This study proposed a three-dimensional (3D) multi-modal learning-based model for the automated prediction and classification of lymph node metastasis in patients with non-small cell lung cancer (NSCLC) using computed tomography (CT) images and clinical information., Methods: We utilized clinical information and CT image data from 4239 patients with NSCLC across multiple institutions. Four deep learning algorithm-based multi-modal models were constructed and evaluated for lymph node classification. To further enhance classification performance, a soft-voting ensemble technique was applied to integrate the outcomes of multiple multi-modal models., Results: A comparison of the classification performance revealed that the multi-modal model, which integrated CT images and clinical information, outperformed the single-modal models. Among the four multi-modal models, the Xception model demonstrated the highest classification performance, with an area under the curve (AUC) of 0.756 for the internal test dataset and 0.736 for the external validation dataset. The ensemble model (SEResNet50&#95;DenseNet121&#95;Xception) exhibited even better performance, with an AUC of 0.762 for the internal test dataset and 0.751 for the external validation dataset, surpassing the multi-modal model's performance., Conclusions: Integrating CT images and clinical information improved the performance of the lymph node metastasis prediction models in patients with NSCLC. The proposed 3D multi-modal lymph node prediction model can serve as an auxiliary tool for evaluating lymph node metastasis in patients with non-pretreated NSCLC, aiding in patient screening and treatment planning., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Aim: The aim of this study was to describe the technique of DCMRL to identify central lymphatic abnormalities in patients with primary lymphatic anomalies and discuss utility of the findings., Materials and Methods: Twenty-eight patients with primary lymphatic abnormalities underwent dynamic magnetic resonance imaging (MRI) following injection of gadolinium directly into inguinal lymph nodes at a tertiary lymphovascular referral center., Results: Technical success was achieved in 23 patients (82.1%). Pathological imaging findings included obstructed, hypoplastic, or absent lymphatic channels with collateralization/rerouting or reflux of flow, lymphangiectasia, lymphatic pseudoaneurysms, and lymph leaks. Protocol modifications for improved imaging are highlighted including technical aspects of lymph node injection, image acquisition and MRI parameters. In two patients, imaging findings warranted embolization of the abnormal lymphatic channels with subsequent symptomatic improvement., Conclusion: DCMRL has been shown to be a safe, reproducible technique in patients with primary lymphatic anomalies enabling imaging of the central lymphatic system., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The objectives of this study were to create a mutual conversion system between contrast-enhanced computed tomography (CECT) and non-CECT images using a cycle generative adversarial network (cycleGAN) for the internal jugular region. Image patches were cropped from CT images in 25 patients who underwent both CECT and non-CECT imaging. Using a cycleGAN, synthetic CECT and non-CECT images were generated from original non-CECT and CECT images, respectively. The peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) were calculated. Visual Turing tests were used to determine whether oral and maxillofacial radiologists could tell the difference between synthetic versus original images, and receiver operating characteristic (ROC) analyses were used to assess the radiologists' performances in discriminating lymph nodes from blood vessels. The PSNR of non-CECT images was higher than that of CECT images, while the SSIM was higher in CECT images. The Visual Turing test showed a higher perceptual quality in CECT images. The area under the ROC curve showed almost perfect performances in synthetic as well as original CECT images. In conclusion, synthetic CECT images created by cycleGAN appeared to have the potential to provide effective information in patients who could not receive contrast enhancement., (© 2024. The Author(s), under exclusive licence to The Society of The Nippon Dental University.)

Purpose: To evaluate the safety and effectiveness of magnetic resonance (MR) imaging-guided cryoablation of prostate cancer metastatic lymph nodes (LNs)., Materials and Methods: Fifty-two patients with prostate cancer who underwent MR imaging-guided LN ablation from September 2013 to June 2022 were retrospectively reviewed. Of these, 6 patients were excluded because adequate ablation margins (3-5 mm) could not be achieved secondary to adjacent structures. The remaining 46 patients (mean age, 70 years [SD ± 7]) underwent 55 MR imaging-guided cryoablation procedures of metastatic LNs (25 in the pelvic sidewall, 20 within the pelvic region, and 10 in the abdomen) with procedural intent of complete ablation. Locoregional tumor control (ie, technical success in the target LN) was evaluated on initial follow-up positron emission tomography (PET) scans at a mean of 4 months (SD ± 2). Preablation and postablation prostate-specific antigen (PSA) levels were recorded. Imaging follow-up continued until a median of 27.5 months (range: 3-108 months)., Results: Ninety-five percent (52/55) of treated LNs demonstrated no considerable activity on PET scans at initial follow-up at 4 months (SD ± 2). PSA decreased to an undetectable level of <0.1 ng/mL after cryoablation in 14 of 46 (30.4%) patients with corresponding lack of activity in 13 of 46 (28.2%) patients on continued PET imaging follow-up. Only 6 of 55 (10.9%) patients had transient adverse events, which all resolved with no long-term sequelae., Conclusions: MR imaging-guided percutaneous cryoablation of metastatic LNs is a safe and technically effective technique for treating metastatic prostate cancer in LNs., (Copyright © 2024 SIR. Published by Elsevier Inc. All rights reserved.)

Introduction: Prostate-specific membrane antigen radioguided surgery (PSMA-RGS) might identify lymph node invasion (LNI) in prostate cancer (PCa) patients undergoing extended pelvic lymph node dissection (ePLND). The optimal target-to-background (TtB) ratio to define RGS positivity is still unknown., Materials & Methods: Ad interim analyses which focused on 30 patients with available pathological information were conducted. All patients underwent preoperative PSMA positron emission tomography (PET). 99m-Technetium-PSMA imaging and surgery ([ 99m Tc]Tc-PSMA-I&S) was administered the day before surgery. In vivo measurements were conducted using an intraoperative gamma probe. Performance characteristics and implications associated with different TtB ratios were assessed., Results: Overall, 9 (30%) patients had LNI, with 22 (13%) and 80 (11%) positive regions and lymph nodes, respectively. PSMA-RGS showed uptakes in 12 (40%) vs. 7 (23%) vs. 6 (20%) patients for a TtB ratio ≥ 2 vs. ≥ 3 vs. ≥ 4. At a per-region level, sensitivity, specificity and accuracy for a TtB ratio ≥ 2 vs. ≥ 3 vs. ≥ 4 were 72%, 88% and 87% vs. 54%, 98% and 92% vs. 36%, 99% and 91%. Performing ePLND only in patients with suspicious spots at PSMA PET (n = 7) would have spared 77% ePLNDs at the cost of missing 13% (n = 3) pN1 patients. A TtB ratio ≥ 2 at RGS identified 8 (24%) suspicious areas not detected by PSMA PET, of these 5 (63%) harbored LNI, with one pN1 patient (11%) that would have been missed by PSMA PET. Adoption of a TtB ratio ≥ 2 vs. ≥ 3 vs. ≥ 4, would have allowed to spare 18 (60%) vs. 23 (77%) vs. 24 (80%) ePLNDs missing 2 (11%) vs. 3 (13%) vs. 4 (17%) pN1 patients., Conclusions: PSMA-RGS using a TtB ratio ≥ 2 to identify suspicious nodes, could allow to spare > 50% ePLNDs and would identify additional pN1 patients compared to PSMA PET and higher TtB ratios., (© 2024. The Author(s).)

The aim of the current study is to investigate the diagnostic value of R2* mapping versus reduced field-of-view diffusion-weighted imaging (rDWI) of the primary lesion of rectal cancer for preoperative prediction of nonenlarged lymph node metastasis (NLNM). Eighty-one patients with pathologically confirmed rectal cancer underwent preoperative R2* mapping and rDWI sequences before total mesorectal excisions and accompanying regional lymph node dissections. Two radiologists independently performed whole-tumor measurements of R2* and apparent diffusion coefficient (ADC) parameters on primary lesions of rectal cancer. Patients were divided into positive (NLNM+) and negative (NLNM-) groups based on their pathological analysis. The tumor location, maximum diameter of the tumor, and maximum short diameter of the lymph node were assessed. R2* and ADC, pT stage, tumor grade, status of mesorectal fascia, and extramural vascular invasion were also studied for their potential relationships with NLNM using multivariate logistic regression analysis. The NLNM+ group had significantly higher R2* (43.56 ± 8.43 vs. 33.87 ± 9.57, p < 0.001) and lower ADC (1.00 ± 0.13 vs. 1.06 ± 0.22, p = 0.036) than the NLNM- group. R2* and ADC were correlated to lymph node metastasis (r = 0.510, p < 0.001 for R2*; r = -0.235, p = 0.035 for ADC). R2* and ADC showed good and moderate diagnostic abilities in the assessment of NLNM status with corresponding area-under-the-curve values of 0.795 and 0.636. R2* provided a significantly better diagnostic performance compared with ADC for the prediction of NLNM status (z = 1.962, p = 0.0498). The multivariate logistic regression analysis demonstrated that R2* was a compelling factor of lymph node metastasis (odds ratio = 56.485, 95% confidence interval: 5.759-554.013; p = 0.001). R2* mapping had significantly higher diagnostic performance than rDWI from the primary tumor of rectal cancer in the prediction of NLNM status., (© 2024 John Wiley & Sons Ltd.)

Introduction: While mediastinoscopy is considered the gold standard for mediastinal node sampling, it is to some extent being superseded by endobronchial ultrasound. The objective of this study was to evaluate the different practices in our center regarding mediastinal lymph node sampling in lung cancer patients., Methods: Data were collected from patients having undergone mediastinal lymph node sampling by video-assisted-mediastinoscopy (VM) or by endobronchial ultrasound (EBUS) in our center between August 2020 and July 2023. The modalities of the two procedures and their diagnostic accuracy were analyzed, as was their evolution over time., Results: The 362 patients comprised 217 who were sampled by EBUS and 145 by VM. Overall, the procedures became more frequent, with EBUS tending to supersede VM. The number of harvested lymph nodes gradually grew, and less unforeseen lymph node invasion and upstaging occurred., Conclusion: The arrival in our center of endobronchial ultrasound yielded an overall increase of lymph node sampling despite a decrease in the number of mediastinoscopy procedures performed. Reinforced compliance with guidelines is needed to improve the diagnostic accuracy of these techniques and to better ensure quality of care., (Copyright © 2024 SPLF. Published by Elsevier Masson SAS. All rights reserved.)

Objective: To assess the diagnostic performance of 18F-fluoro-2-deoxy-d-glucose (18F-FDG) positron emission tomograpy (PET)/computed tomography (CT) in nodal staging before radical cystectomy (RC) and pelvic lymph node dissection (PLND) for bladder cancer (BCa)., Materials and Methods: This analysis was based on a cohort of 199 BCa patients undergoing RC and bilateral PLND between 2015 and 2022. Neoadjuvant chemotherapy (NAC) or immunotherapy (NAI) was administered after oncological evaluation. All patients received preoperative 18F-FDG PET/CT to assess extravesical disease. Point estimates for true negative, false negative, false positive, true positive, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of conventional imaging and PET/CT were calculated. Subgroup analysis in patients receiving neoadjuvant treatment was performed., Results: At preoperative evaluation, 30 patients (15.1%) had 48 suspicious nodal spots on 18F-FDG PET/CT. At RC and bilateral PLND, a total of 4871 lymph nodes (LNs) were removed with 237 node metastases corresponding to 126 different regions. Pathological node metastases were found in 17/30 (57%) vs 39/169 patients (23%) with suspicious vs negative preoperative 18F-FDG PET/CT, respectively (sensitivity = 0.30, specificity = 0.91, PPV = 0.57, NPV = 0.77, accuracy = 0.74). On per-region analysis including 1367 nodal regions, LN involvement was found in 19/48 (39%) vs 105/1319 (8%) suspicious vs negative regions at PET/CT, respectively (sensitivity = 0.15, specificity = 0.98, PPV = 0.40, NPV = 0.92, ACC = 0.90). Similar results were observed for patients receiving NAC (n = 44, 32.1%) and NAI (n = 93, 67.9% [per-patient: sensitivity = 0.36, specificity = 0.91, PPV = 0.59, NPV = 0.80, accuracy = 0.77; per-region: sensitivity = 0.12, specificity = 0.98, PPV = 0.32, NPV = 0.93, ACC = 0.91]). Study limitations include its retrospective design and limited patient numbers., Conclusions: In eight out of 10 patients with negative preoperative 18F-FDG PET/CT, pN0 disease was confirmed at final pathology. No differences were found based on NAC vs NAI treatment. These findings suggest that 18F-FDG PET/CT could play a role in the preoperative evaluation of nodal metastases in BCa patients, although its cost-effectiveness is uncertain., (© 2024 The Authors. BJU International published by John Wiley & Sons Ltd on behalf of BJU International.)

Introduction: Ultrasound (US) has an important place in imaging ulceroglandular type patients with tularemia. This study is a case series addressing the imaging findings of US and US shear-wave elastography in ulceroglandular type tularemia., Description: Three patients, two women, and one man, were included in our case series. The patients were admitted to our hospital with neck swelling, pain, and a palpable mass. After the diagnosis of tularemia was made as a result of the examinations performed on the patients, they were evaluated again with US and US shear-wave elastography., Discussion: Since there are many diagnoses including ulceroglandular tularemia in the differential diagnosis of swelling, pain, and palpable mass in the neck, the patient must undergo a thorough evaluation process. US shear-wave elastography can provide significant benefits in identification and treatment follow-up in order to understand the ulceroglandular mass formation observed in the neck in tularemia and the stiffness and morphology of the tissues in the lymph nodes where involvement is observed and to distinguish them from the surrounding tissue., (© 2024 Wiley Periodicals LLC.)

Background: While there are established international consensuses on the delineation of pelvic lymph node regions (LNRs), significant inter- and intra-observer variabilities persist. Contouring these clinical target volumes for irradiation in pelvic malignancies is both time-consuming and labor-intensive., Purpose: The purpose of this study was to develop a deep learning model of pelvic LNRs delineation for patients with pelvic cancers., Methods: Planning computed tomography (CT) studies of 160 patients with pelvic primary malignancies (including rectal, prostate, and cervical cancer) were retrospectively collected and divided into training set (n = 120) and testing set (n = 40). Six pelvic LNRs, including abdominal presacral, pelvic presacral, internal iliac nodes, external iliac nodes, obturator nodes, and inguinal nodes were delineated by two radiation oncologists as ground truth (Gt) contours. The cascaded multi-heads U-net (CMU-net) was constructed based on the Gt contours from training cohort, which was subsequently verified in the testing cohort. The automatic delineation of six LNRs (Auto) was evaluated using dice similarity coefficient (DSC), average surface distance (ASD), 95th percentile Hausdorff distance (HD95), and a 7-point scale score., Results: In the testing set, the DSC of six pelvic LNRs by CMU-net model varied from 0.851 to 0.942, ASD from 0.381 to 1.037 mm, and HD95 from 2.025 to 3.697 mm. No significant differences were founded in these three parameters between postoperative and preoperative cases. 95.9% and 96.2% of auto delineations by CMU-net model got a score of 1-3 by two expert radiation oncologists, respectively, meaning only minor edits needed., Conclusions: The CMU-net was successfully developed for automated delineation of pelvic LNRs for pelvic malignancies radiotherapy with improved contouring efficiency and highly consistent, which might justify its implementation in radiotherapy work flow., (© 2024 American Association of Physicists in Medicine.)

Objective: The aim of this study was to develop a 18 F-fluorodeoxyglucose ( 18 F-FDG) positron emission tomography/computed tomography (PET/CT) radiomic model for predicting mediastinal lymph node metastasis (LNM) in presurgical patients with lung adenocarcinoma. Methods: The study enrolled 320 patients with lung adenocarcinoma (288 internal and 32 external cases) and extracted 190 radiomic features using the LIFEx package. Optimal radiomic features to build a radiomic model were selected using the least absolute shrinkage and selection operator algorithm. Logistic regression was used to build the clinical and complex (combined radiomic and clinical variables) models. Results: Ten radiomic features were selected. In the training group, the area under the receiver operating characteristic curve of the complex model was significantly higher than that of the radiomic and clinical models [0.924 (95% CI: 0.887-0.961) vs. 0.863 (95% CI: 0.814-0.912; p  = 0.001) and 0.838 (95% CI: 0.783-0.894; p  = 0.000), respectively]. The sensitivity, specificity, accuracy, and positive and negative predictive values of the radiomic model were 0.857, 0.790, 0.811, and 0.651 and 0.924, respectively, which were better than that of visual evaluation (0.539, 0.724, 0.667, and 0.472 and 0.775, respectively) and PET semiquantitative analyses (0.619, 0.732, 0.697, and 0.513 and 0.808, respectively). Conclusions: 18 F-FDG PET/CT radiomics showed good predictive performance for LNM and improved the N-stage accuracy of lung adenocarcinoma.

Purpose: In breast cancer (BC) patients with clinical axillary lymph node metastasis (cN+) undergoing neoadjuvant therapy (NAT), precise axillary lymph node (ALN) assessment dictates therapeutic strategy. There is a critical demand for a precise method to assess the axillary lymph node (ALN) status in these patients., Materials and Methods: A retrospective analysis was conducted on 160 BC patients undergoing NAT at Fujian Medical University Union Hospital. We analyzed baseline and two-cycle reassessment dynamic contrast-enhanced MRI (DCE-MRI) images, extracting 3668 radiomic and 4096 deep learning features, and computing 1834 delta-radiomic and 2048 delta-deep learning features. Light Gradient Boosting Machine (LightGBM), Support Vector Machine (SVM), RandomForest, and Multilayer Perceptron (MLP) algorithms were employed to develop risk models and were evaluated using 10-fold cross-validation., Results: Of the patients, 61 (38.13 %) achieved ypN0 status post-NAT. Univariate and multivariable logistic regression analyses revealed molecular subtypes and Ki67 as pivotal predictors of achieving ypN0 post-NAT. The SVM-based "Data Amalgamation" model that integrates radiomic, deep learning features, and clinical data, exhibited an outstanding AUC of 0.986 (95 % CI: 0.954-1.000), surpassing other models., Conclusion: Our study illuminates the challenges and opportunities inherent in breast cancer management post-NAT. By introducing a sophisticated, SVM-based "Data Amalgamation" model, we propose a way towards accurate, dynamic ALN assessments, offering potential for personalized therapeutic strategies in BC., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Purpose: To investigate whether deep cervical lymph node (DCLN) ligation alters intracranial cerebrospinal fluid (CSF) tracer dynamics and outflow using a rat model with intrathecal dynamic contrast-enhanced (DCE) MRI., Methods: Six bilateral DCLN-ligated and six sham-operated rats were subjected to DCE MRI with Gd-BTDO3A, and dynamic T1-weighted images were acquired. ROIs were collected from the CSF at the C1 level (CSF&#95;C1), CSF between the olfactory bulbs (CSF&#95;OB), CSF at the pituitary recess (CSF&#95;PitR), and CSF at the pineal recess (CSF&#95;PinR), upper nasal turbinate (UNT), olfactory bulbs, cerebrum, and the jugular region. Time-intensity curves were evaluated, and the maximum slope, peak timing, peak signal ratio, and elimination half-life for the four CSF ROIs and UNT were calculated and compared., Results: Delayed tracer arrival in the rostral CSF space and the nasal cavity with tracer retention in the ventral CSF space were observed in the ligation group. The maximum slopes were smaller in the ligation group at UNT (sham: 0.075 ± 0.0061, ligation: 0.044 ± 0.0086/min, P = 0.011). A significant difference was not detected in peak timings. The peak signal ratio values were lower in the ligation group at UNT (sham: 2.12 ± 0.19, ligation: 1.72 ± 0.11, P = 0.011). The elimination half-life was delayed in the ligation group at CSF&#95;C1 (sham: 30.5 ± 2.70, ligation: 44.4 ± 12.6 min, P = 0.043), CSF&#95;OB (sham: 30.2 ± 2.67, ligation: 44.8 ± 7.47 min, P = 0.021), and CSF&#95;PitR (sham: 30.2 ± 2.49, ligation: 41.3 ± 7.57 min, P = 0.021)., Conclusion: The DCLN ligation in rats blocked CSF outflow into the nasal cavity and caused CSF retention.

Purpose: To investigate the detectability of lymph node metastasis in patients with esophageal squamous cell carcinoma using a combination of dual-energy computed tomography (CT) and positron-emission tomography (PET) parameters., Methods: We analyzed dual-energy CT and PET preoperative data in 27 consecutive patients with esophageal squamous cell carcinoma (23 men, 4 women; mean age, 73.7 years). We selected lymph nodes with a short-axis diameter of ≥5 mm and measured CT values, iodine concentrations, fat fractions, long- and short-axis diameters, and ratio of long- and short-axis diameters. We performed visual assessment of lymph node characteristics based on dual-energy CT and determined the maximum standardized uptake value via PET. The measured values were postoperatively compared between pathologically confirmed metastatic and nonmetastatic lymph nodes. Stepwise logistic regression analysis was performed to determine factors associated with lymph node metastasis. Diagnostic accuracy was assessed via receiver operating characteristic curve analysis., Results: Overall, 18 metastatic and 37 nonmetastatic lymph nodes were detected. CT values, iodine concentrations, fat fractions, and the maximum standardized uptake values differed significantly between metastatic and nonmetastatic lymph nodes (p < 0.05). Stepwise logistic regression showed that iodine concentration and the maximum standardized uptake value were significant predictors of metastatic lymph nodes. The areas under the curve of iodine concentrations and maximum standardized uptake values were 0.809 and 0.833, respectively. The area under the curve of the combined parameters was 0.884, with 83.3% sensitivity and 86.5% specificity., Conclusion: Combined dual-energy CT and PET parameters improved the diagnosis of lymph node metastasis in patients with esophageal cancer., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Sun et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Purpose: The population in Western countries differs significantly from that in Eastern countries, and the prevalence of lateral pelvic lymph node (LPLN) involvement in Western populations remains largely unknown due to the limited application of LPLN dissection (LPLND). This discrepancy is primarily attributed to the higher body mass index commonly observed in Western populations, which increases the risk of intraoperative complications. Consequently, the aim of this study is to describe a specific Western clinico-radiological selection tool for LPLND, namely, the lateral pelvic lymph node positivity (LPLNP) score., Methods: This retrospective single center study was designed to elaborate the LPLNP score, which was further tested on a prospective cohort of patients. Clinical and MRI factors associated with LPLN involvement were identified, and logistic regression was used to establish the LPLNP score., Results: In the retrospective series, 120 patients underwent lateral pelvic lymph node dissection. After stepwise logistic regression, five parameters were ultimately included in the LPLNP score. When tested on 66 prospectively selected patients, 40 with an LPLNP score > 0.23 (corresponding to the highest sensitivity and specificity) underwent LPLND: 22 patients (55%) had pathologically confirmed positive LPLN. The negative predictive value of the LPLNP score was 96%, with a sensitivity of 95.7% and a specificity of 58.1%., Conclusion: The LPLNP score was developed based on the largest group of Western patients with locally advanced rectal cancer. This scoring system demonstrated high sensitivity and specificity during validation on the prospective series, correctly identifying LPLN involvement in 55% of cases., (© 2024. The Author(s).)

In their letter-to-the-editor entitled "Letter to the Editor: Incidence rate of occult lymph node metastasis in clinical T 1 - 2 N 0 M 0 small cell lung cancer patients and radiomic prediction based on contrast-enhanced CT imaging: a multicenter study", Prof. Chen et al. provided insightful comments and suggestions on our original study. We appreciate the authors' feedback and have conducted a preliminary exploration of the predictive value of serum tumor markers (TMs) for occult lymph node metastasis (OLM) in clinical T 1 - 2 N 0 M 0 (cT 1 - 2 N 0 M 0 ) small cell lung cancer (SCLC) patients. The results indicate that neuron-specific enolase (NSE), carbohydrate antigen 125 (CA125), and squamous cell carcinoma antigen (SCC) have potential predictive value for detecting OLM in cT 1 - 2 N 0 M 0 SCLC patients. Additionally, further exploration and confirmation through prospective, large-scale studies with robust external validation are needed., (© 2024. The Author(s).)

Aim: Chronic venous disease is a common pathology characterized by valvular incompetence and venous hypertension. The venous network of the lymph nodes at the Scarpa triangle connects the superficial and the deep venous systems. This study aimed to describe infrainguinal intranodal venous dilatations and to evaluate the connection with peripheral venous disease., Material and Methods: The study included 183 subjects (116 women, 67 men) who underwent Doppler ultrasound examinations of the venous system of the inferior limb in the context of chronic venous disease. The diagnosis of lymph node varices was based on well-defined criteria and the severity of the lymph node varices was established using an original classification., Results: There was a statistically significant, moderately strong association, between the presence of intranodal varices and the great saphenous vein reflux (φ=0.341, p=0.000). There was a moderate-to-high positive correlation between intranodal varices and the chronic venous disease stage (rrb=0.457, p=0.000)., Conclusions: Patients with more advanced stages of chronic venous insufficiency have a higher probability of presenting intranodal varices. Lymph node venous network identification could considerably impact clinical decision-making and treatment choices.

Background: This study investigated the clinical value of breast magnetic resonance imaging (MRI) radiomics for predicting axillary lymph node metastasis (ALNM) and to compare the discriminative abilities of different combinations of MRI sequences., Methods: This study included 141 patients diagnosed with invasive breast cancer from two centers (center 1: n = 101, center 2: n = 40). Patients from center 1 were randomly divided into training set and test set 1. Patients from center 2 were assigned to the test set 2. All participants underwent preoperative MRI, and four distinct MRI sequences were obtained. The volume of interest (VOI) of the breast tumor was delineated on the dynamic contrast-enhanced (DCE) postcontrast phase 2 sequence, and the VOIs of other sequences were adjusted when required. Subsequently, radiomics features were extracted from the VOIs using an open-source package. Both single- and multisequence radiomics models were constructed using the logistic regression method in the training set. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and precision of the radiomics model for the test set 1 and test set 2 were calculated. Finally, the diagnostic performance of each model was compared with the diagnostic level of junior and senior radiologists., Results: The single-sequence ALNM classifier derived from DCE postcontrast phase 1 had the best performance for both test set 1 (AUC = 0.891) and test set 2 (AUC = 0.619). The best-performing multisequence ALNM classifiers for both test set 1 (AUC = 0.910) and test set 2 (AUC = 0.717) were generated from DCE postcontrast phase 1, T2-weighted imaging, and diffusion-weighted imaging single-sequence ALNM classifiers. Both had a higher diagnostic level than the junior and senior radiologists., Conclusions: The combination of DCE postcontrast phase 1, T2-weighted imaging, and diffusion-weighted imaging radiomics features had the best performance in predicting ALNM from breast cancer. Our study presents a well-performing and noninvasive tool for ALNM prediction in patients with breast cancer., (© 2024. The Author(s).)

Background and Aims: Preoperative prediction of axillary lymph node (ALN) burden in patients with early-stage breast cancer is pivotal for individualised treatment. This study aimed to develop a MRI radiomics model for evaluating the ALN burden in early-stage breast cancer and to provide biological interpretability to predictions by integrating radiogenomic data., Methods: This study retrospectively analyzed 1211 patients with early-stage breast cancer from four centers, supplemented by data from The Cancer Imaging Archive (TCIA) and Duke University (DUKE). MRI radiomic features were extracted from dynamic contrast-enhanced MRI images and an ALN burden-related radscore was constructed by the backpropagation neural network algorithm. Clinical and combined models were developed, integrating ALN-related clinical variables and radscore. The Kaplan-Meier curve and log-rank test were used to assess the prognostic differences between the predicted high- and low-ALN burden groups in both Center I and DUKE cohorts. Gene set enrichment and immune infiltration analyses based on transcriptomic TCIA and TCIA Breast Cancer dataset were used to investigate the biological significance of the ALN-related radscore., Results: The MRI radiomics model demonstrated an area under the curve of 0.781-0.809 in three validation cohorts. The predicted high-risk population demonstrated a poorer prognosis (log-rank P < .05 in both cohorts). Radiogenomic analysis revealed migration pathway upregulation and cell differentiation pathway downregulation in the high radscore groups. Immune infiltration analysis confirmed the ability of radiological features to reflect the heterogeneity of the tumor microenvironment., Conclusions: The MRI radiomics model effectively predicted the ALN burden and prognosis of early-stage breast cancer. Moreover, radiogenomic analysis revealed key cellular and immune patterns associated with the radscore., (© 2024. The Author(s).)

For breast cancer patients with physical exam node negative but radiological finding node abnormal (cN0/rNa), the NCCN and ASCO guidelines recommend sentinel lymph node biopsy (SLNB) as the first-line axillary staging. However, patients who undergo surgery firstly may be upstaged to pathological II-III status, and these patients happen to be the adaptive population of neoadjuvant therapy (NAT). There is no consensus on the optimal management of cN0/rNa patients. The aim is to explore the optimal management strategy of these patients. We performed a retrospective real-world study of 1414 cN0/rNa patients from June 2014 to October 2022. There were 1003 patients underwent surgery first and 411 patients underwent surgery after NAT. We analyzed the real-world conditions of these patients, compared axilla tumor burden between these two groups. In addition, we compared benefit ratio of axillary surgery and regional nodal irradiation (RNI) de-escalation under the two strategies. Among 1003 patients underwent surgery first, the positive and negative rates of fine needle aspiration (FNA) were 18.5% and 81.5%, respectively. There were 66.1% had ≤ 2 lymph nodes+. There were 40.8% of FNA+ patients could be exempted from ALND underwent surgery first. In 411 patients underwent surgery after NAT, the FNA positive and negative rates were 60.8% and 49.2%, respectively. There were 54.4% of FNA+ patients achieved axilla pathologic complete response (apCR) and could omit ALND after NAT. The apCR was 67.3% in HER2+/TNBC subtypes. According to the NSABP-B51 trial, there were 0 and 54.4% of FNA+ patients could omit RNI among surgery first and after NAT, respectively. Among 1-2 sentinel lymph node (SLN)-positive patients underwent surgery first, with a median follow-up 49 months, there was no difference of survival benefit between SLNB-only and SLNB-ALND. Compared with 1-2 SLN+ patients without RNI, RNI could bring better invasive disease-free survival (97.38% vs. 89.36%, P = 0.046) and breast cancer special survival (100% vs. 94.68%, P = 0.020). It is safe to perform SLNB omitting ALND when detected 1-2 positive SLNs in cN0/rNa patients. Patients with HER2+/TNBC subtypes underwent surgery after NAT had more chance to benefit from dual de-escalation, including axillary surgery and RNI de-escalation., (© 2024. The Author(s).)

Introduction: To date, radical surgery remains the best curative option in patients with early-stage lung cancer. In patients with small lung lesions, video-assisted thoracic surgery (VATS) should be increasingly chosen as a fundamental alternative to thoracotomy as it is associated with less postoperative pain and better quality of life. This scenario necessarily increases the need for thoracic surgeons to implement new localization techniques. The conventional near-infrared (NIR) indocyanine green (ICG) method demonstrated a significant limitation in deep cancer recognition, principally due to its intrinsic low-depth tissue penetration. Similarly, the lymph-node sentinel approach conducted by the ICG method was demonstrated to be inefficient, mainly due to the non-specificity of the tracker and the irregular pathway of pulmonary lymph node drainage. Our study aims to evaluate the effectiveness of Cetuximab- IRDye800CW in marking lung nodules and mediastinal lymph nodes., Methods and Analysis: This study is defined as an open-label, single-arm, single-stage phase II trial evaluating the effectiveness of Cetuximab-IRDye800CW in detecting tumors and lymph-node metastases in patients with lung cancer who are undergoing video-assisted thoracic surgery (VATS). Cetuximab is a monoclonal antibody that binds, inhibits, and degrade the EGFR. The IRDye ® 800CW, an indocyanine-type NIR fluorophore, demonstrated enhanced tissue penetration compared to other NIR dyes. The combination with the clinical approved monoclonal antibody anti-epidermal growth factor EGFR Cetuximab (Cetuximab-IRDye800) has shown promising results as a specific tracker in different cancer types (i.e., brain, pancreas, head, and neck). The study's primary outcome is focused on the proportion of patients with lung nodules detected during surgery using an NIR camera. The secondary outcomes include a broad spectrum of items, including the proportion of patients with detection of unexpected cancer localization during surgery by NIR camera and the proportion of patients with negative surgical margins, the evaluation of the time spawns between the insertion of the NIR camera and the visualization of the nodule and the possible morbidity of the drug assessed during and after the drug infusion., Ethics and Dissemination: This trial has been approved by the Ethical Committee of Azienda Ospedaliera Universitaria Città della Salute e della Scienza di Torino (Torino, Italy) and by the Italian Medicines Agency (AIFA). Findings will be written as methodology papers for conference presentations and published in peer-reviewed journals. The Azienda Ospedaliera Universitaria Città della Salute e della Scienza di Torino, the University of Torino, and the AIRC Public Engagement Divisions will help identify how best to publicize the findings.Trial registration EudraCT 202,100,645,430., Clinicaltrials: gov NCT06101394 (October 23, 2023)., (© 2024. The Author(s).)

Objective: To predict preoperative inguinal lymph node metastasis in vulvar cancer patients using a machine learning model based on imaging features and clinical data from pelvic magnetic resonance imaging (MRI)., Methods: 52 vulvar cancer patients were divided into a training set (n=37) and validation set (n=15). Clinical data and MRI images were collected, and regions of interest were delineated by experienced radiologists. A total of 1688 quantitative imaging features were extracted using the Radcloud platform. Dimensionality reduction and feature selection were applied, resulting in a radiomics signature. Clinical characteristics were screened, and a combined model integrating the radiomics signature and significant clinical features was constructed using logistic regression. Four machine learning classifiers (K nearest neighbor, random forest, adaptive boosting, and latent dirichlet allocation) were trained and validated. Model performance was evaluated using the receiver operating characteristic curve and the area under the curve (AUC), as well as decision curve analysis., Results: The radiomics score significantly differentiated between lymph node metastasis positive and negative patients in both the training and validation sets. The combined model demonstrated excellent discrimination, with AUC values of 0.941 and 0.933 in the training and validation sets, respectively. The calibration curve and decision curve analysis confirmed the model's high predictive accuracy and clinical utility. Among the machine learning classifiers, latent dirichlet allocation and random forest models achieved AUC values >0.7 in the validation set. Integrating all four classifiers resulted in a total model with an AUC of 0.717 in the validation set., Conclusion: Radiomics combined with artificial intelligence can provide a new method for prediction of inguinal lymph node metastasis of vulvar cancer before surgery., Competing Interests: Competing interests: None declared., (© IGCS and ESGO 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Information about the distribution characteristics and prognostic significance of lateral lymph nodes (LLNs) on primary computed tomography (CT) scan in rectal cancer patients is lacking., Methods: Between January 2013 and December 2016, patients with pathologically proved rectal cancer and pretreatment abdominal enhanced CT in our department were screened. We firstly redivided LLNs into seven categories based on their locations. Then, the number and distribution of all measurable LLNs and the characteristics of the largest LLN in each lateral compartment were recorded. Furthermore, we investigated the long-term outcomes in patients with different LLN characteristics and LLN risk scoring., Results: A total of 572 patients were enrolled in this study. About 80% of patients had measurable LLNs, and most patients developed measurable LLNs in the obturator cranial compartment. Lateral local recurrence (LLR) was observed in 20 patients, which accounted for 83.3% of the local recurrence (LR). Patients with the largest LLN short-axis diameter >10 mm had a poor prognosis, which was similar to that in patients with simultaneous distant metastasis (SDM). Patients with LLN risk scoring ≥2 had a worse prognosis than those with LLN risk scoring <2, while better than those with SDM., Conclusion: This study suggests that LLR is the main locoregional recurrence pattern. Most rectal cancer patients have measurable LLNs on primary CT scan. However, patients with enlarged LLNs <10 mm or LLN risk scoring <2 still have a significantly better prognosis than patients with SDM, which indicated the potential value of locoregional treatment for these LLNs., (© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.)

Objective: To create a deep-learning automatic segmentation model for esophageal cancer (EC), metastatic lymph nodes (MLNs) and their adjacent structures using the UperNet Swin network and computed tomography angiography (CTA) images and to improve the effectiveness and precision of EC automatic segmentation and TN stage diagnosis., Methods: Attention U-Net, UperNet Swin, UNet++ and UNet were used to train the EC segmentation model to automatically segment the EC, esophagus, pericardium, aorta and MLN from CTA images of 182 patients with postoperative pathologically proven EC. The Dice similarity coefficient (DSC), sensitivity, and positive predictive value (PPV) were used to assess their segmentation effectiveness. The volume of EC was calculated using the segmentation results, and the outcomes and times of automatic and human segmentation were compared. All statistical analyses were completed using SPSS 25.0 software., Results: Among the four EC autosegmentation models, the UperNet Swin had the best autosegmentation results with a DSC of 0.7820 and the highest values of EC sensitivity and PPV. The esophagus, pericardium, aorta and MLN had DSCs of 0.7298, 0.9664, 0.9496 and 0.5091. The DSCs of the UperNet Swin were 0.6164, 0.7842, 0.8190, and 0.7259 for T1-4 EC. The volume of EC and its adjacent structures between the ground truth and UperNet Swin model were not significantly different., Conclusions: The UperNet Swin showed excellent efficiency in autosegmentation and volume measurement of EC, MLN and its adjacent structures in different T stage, which can help to T and N stage diagnose EC and will save clinicians time and energy., (© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.)

Objective: To investigate the potential association among preoperative breast MRI features, axillary nodal burden (ANB), and disease-free survival (DFS) in patients with early-stage breast cancer., Materials and Methods: We retrospectively reviewed 297 patients with early-stage breast cancer (cT1-2N0M0) who underwent preoperative MRI between December 2016 and December 2018. Based on the number of positive axillary lymph nodes (LNs) determined by postoperative pathology, the patients were divided into high nodal burden (HNB; ≥3 positive LNs) and non-HNB (<3 positive LNs) groups. Univariable and multivariable logistic regression analyses were performed to identify independent risk factors associated with ANB. Predictive efficacy was evaluated using the receiver operating characteristic (ROC) curve and area under the curve (AUC). Univariable and multivariable Cox proportional hazards regression analyses were performed to determine preoperative features associated with DFS., Results: We included 47 and 250 patients in the HNB and non-HNB groups, respectively. Multivariable logistic regression analysis revealed that multifocality/multicentricity (adjusted odds ratio [OR] = 3.905, 95% confidence interval [CI]: 1.685-9.051, P = 0.001) and peritumoral edema (adjusted OR = 3.734, 95% CI: 1.644-8.479, P = 0.002) were independent risk factors for HNB. Combined peritumoral edema and multifocality/multicentricity achieved an AUC of 0.760 (95% CI: 0.707-0.807) for predicting HNB, with a sensitivity and specificity of 83.0% and 63.2%, respectively. During the median follow-up period of 45 months (range, 5-61 months), 26 cases (8.75%) of breast cancer recurrence were observed. Multivariable Cox proportional hazards regression analysis indicated that younger age (adjusted hazard ratio [HR] = 3.166, 95% CI: 1.200-8.352, P = 0.021), larger tumor size (adjusted HR = 4.370, 95% CI: 1.671-11.428, P = 0.002), and multifocality/multicentricity (adjusted HR = 5.059, 95% CI: 2.166-11.818, P < 0.001) were independently associated with DFS., Conclusion: Preoperative breast MRI features may be associated with ANB and DFS in patients with early-stage breast cancer., Competing Interests: The authors have no potential conflicts of interest to disclose., (Copyright © 2024 The Korean Society of Radiology.)

Objective: This study aimed to analyze the correlation between the ultrasonic measured size (ULMS) and actual pathological measured size (APMS) of papillary thyroid microcarcinoma (PTMC), and to investigate the association of tumor size with metastatic central lymph nodes (CLNM).", Methods: A total of 500 cases with PTMC (APMS) who underwent surgery between August 2009 and May 2016 were reviewed. Paired t test, multivariable logistic regression and ROC curve were used for analyzing the data. The difference and correlation between the APMS and the ULMS were detected by paired t test. The multivariable logistic regression model and Receiver Operating Characteristic curve (ROC) curve area were used to predict the impact of lesion size of PTMC on the risk of CLNM., Results: The overall actual pathological measured value of specimens was smaller than the ultrasonic measured value (among ULMS PTMC, the average value of difference D was -0.775 mm, 95%CI: -0.839 mm~ -0.712 mm, P = .000). The ultrasonic tumor size (P = .000, OR=1.129, 95%CI: 1.084-1.175) was the risk factor for CLNM. The central lymph node metastasis rate in 500 cases (APMS with ≤ 10 mm) was 37.2%, while 32.6% in 396 cases with ULMS. The CLNM rates of s3 mm-10 mm PTMC single lesions were 20%, 18.18%, 14.89%, 18.18%, 36.73%, 36.36%, 35.29%, and 38.71%, respectively. The metastasis rate of a single lesion≤ 6 mm was significantly lower than that of> 6 mm, which was lower than 20%. The ROC curve indicated that the ULMS was a risk factor for CLNM (optimal threshold of 6.5 mm), 5 or more CLNM (optimal threshold of 6.5 mm), and bilateral CLNM (optimal threshold of 8.5 mm)., Conclusion: Ultrasound size is a predictive factor for CLNM in thyroid cancer and that PTMC with a diameter < 6 mm still poses a risk for central metastasis. Prophylactic central dissection is still recommended for PTMC patients, except for those with a single lesion of less than 6 mm in maximum diameter.