Regularity and correlation analysis of regional lymph node metastasis in nonoperative patients with non-small cell lung cancer based on positron emission tomography/computed tomography images.

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.

Multiparametric ultrasound assessment of axillary lymph nodes in patients with breast cancer.

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.

The value of postoperative contrast-enhanced ultrasound parameters in lymph node metastasis, tumor node metastasis, and treatment response evaluation of resected hepatocellular carcinoma.

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.

Computed tomography-based radiomics nomogram for prediction of lympho-vascular and perineural invasion in esophageal squamous cell cancer patients: a retrospective cohort study.

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.

[Diagnostic value of fluorescence lymphography for sentinel lymph node biopsy in breast cancer. Summary experience of several specialized centers]. / Diagnosticheskaya tsennost' flyuorestsentnoi limfografii dlya biopsii signal'nykh limfaticheskikh uzlov pri rake molochnoi zhelezy. Obobshchayushchii opyt neskol'kikh spetsializirovannykh tsentrov.

OBJECTIVE: To study the diagnostic value of fluorescent lymphography for sentinel lymph node biopsy in breast cancer. MATERIAL AND METHODS: The cohort study, conducted at 4 specilized centers between June 2019 and March 2024, included 333 patients with cT1-4 N0-1M0 breast cancer. 50 patients received neoadjuvant systemic therapy, 14 of them had single metastases, confirmed by cytological or histological methods, which clinically completely regressed after systemic treatment. Immediately before the operation, 1 ml (5mg) of indocyanine green was injected subareolarly or subcutaneously into the tumor projection. Fluorescence imaging was performed using various devices for ICG navigation in the open surgical field - MARS, IC-Flow, Stryker SPY-PHI, IC-GOR. In 78 patients after sentinel lymph node biopsy standard axillary lymphadenectomy was performed. RESULTS: Detection level was 99.1%. The average number of sentinel lymph nodes was 3.4. Metastatic lesions of sentinel lymph nodes were detected in 54 of 330 patients (16.4%). The average number of metastatic lymph nodes was 1.6; in 90.7% of cases metastases to 1-2 lymph nodes were registered. Intraoperative morphological examination revealed metastases only in 59% of cases. No systemic adverse events were recorded. The false-negative error rate in the group of patients who underwent axillary lymphadenectomy was 6.6%. The overall accuracy of fluorescent lymphography for sentinel lymph node biopsy in breast cancer was 94%. CONCLUSION: The SLNB technique using fluorescence lymphography is safe and highly accurate as a stand-alone method.

A multicenter dataset for lymph node clinical target volume delineation of nasopharyngeal carcinoma.

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.

Novel deep learning radiomics nomogram-based multiparametric MRI for predicting the lymph node metastasis in rectal cancer: A dual-center study.

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.

Investigation of the distribution of inguinal lymph nodes and delineation of the inguinal clinical target volume using 18F-FDG PET/CT.

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 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT). METHODS: Inguinal LNM in patients with biopsy-proven pelvic malignancies were identified using 18F-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 18F-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 18F-FDG PET/CT, we investigated the distribution pattern of inguinal LNM and propose a more comprehensive guideline for inguinal CTV delineation.

Contrast-Enhanced Ultrasound-Based Radiomics for the Prediction of Axillary Lymph Nodes Status in Breast Cancer.

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.

Single-Center Experience With Dynamic Contrast-Enhanced Magnetic Resonance Lymphangiography for Diagnosing Lymphatic Disorders and Guiding Percutaneous Embolization.

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.

Single-center external validation and reconstruction of multiple predictive models for skip lateral lymph node metastasis in papillary thyroid carcinoma.

Objective: The unique metastatic pattern of skip lateral lymph node metastasis (SLLNM) in PTC patients may lead to missed diagnosis of lateral cervical metastatic lymph nodes. Therefore, many different SLLNM prediction models were constructed. In this study, partially eligible models (Hu 2020, Wang 2020, and Zhao 2023 nomograms) were selected for external validation, and then new variables were incorporated for model reconstruction to extend clinical applicability. Methods: 576 PTC patients from our center were selected to evaluate the performance of the three nomograms using the receiver operating characteristic curve (ROC), calibration curves, and decision curve analyses (DCA). Three new variables were added to calibrate the model, including assessment of LN status on ultrasound (US-SLLNM), the distance from the tumor to the capsule (Capsular distance), and the number of central lymph node dissections (CLND number). Univariate and multivariate logistic regression analyses were used to screen independent predictors to reconstruct the model, and 1000 Bootstrap internal validations were performed. Results: SLLNM were present in 69/576 patients (12.0%). In external validation, the area under the ROC curves (AUCs) for Hu 2020, Wang 2020, and Zhao 2023 nomograms were 0.695 (95% CI:0.633-0.766), 0.792 (95% CI=0.73-0.845), and 0.769 (95% CI:0.713-0.824), respectively. The calibration curves for the three models were overall poorly fitted; DCA showed some net clinical benefit. Model differentiation and net clinical benefit improved by adding three new variables. Based on multivariate analysis, female, age, and maximum tumor diameter ≤ 10 mm, located at the upper pole, Capsular distance < 0mm, US-SLLNM, CLND number ≤ 5 were identified as independent predictors of SLLNM and were used to construct the new model. After 1000 Bootstrap internal validations, the mean AUC of the model was 0.870 (95% CI:0.839-0.901), the calibration curve was close to the ideal curve, and the net clinical benefit was significant. Conclusion: Overall, these nomograms were well differentiated and provided some net clinical benefit, but with varying degrees of underestimation or overestimation of the actual risk and high false-negative rates. New dynamic nomogram was constructed based on the addition of new variables and larger samples, showing better performance.

Preoperative dual-energy computed tomography and positron-emission tomography evaluation of lymph node metastasis in esophageal squamous cell carcinoma.

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.

Optimal management of breast cancer with physical exam negative/radiological abnormal axilla.

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.

MRI radiomics and biological correlations for predicting axillary lymph node burden in early-stage breast cancer.

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.

Impact of mediastinal tumor burden and lymphatic spread in locally advanced non-small-cell lung cancer: A secondary analysis of the multicenter randomized PET-Plan trial.

PURPOSE: The aim of this secondary analysis of the prospective randomized phase 2 PET-Plan trial (ARO-2009-09; NCT00697333) was to evaluate the impact of mediastinal tumor burden and lymphatic spread in patients with locally advanced non-small-cell lung cancer (NSCLC). METHODS: All patients treated per protocol (n = 172) were included. Patients received isotoxically dose-escalated chemoradiotherapy up to a total dose of 60-74 Gy in 30-37 fractions, aiming as high as possible while adhering to normal tissue constraints. Radiation treatment (RT) planning was based on an 18F-FDG PET/CT targeting all lymph node (LN) stations containing CT positive LNs (i.e. short axis diameter > 10 mm), even if PET-negative (arm A) or targeting only LN stations containing PET-positive nodes (arm B). LN stations were classified into echelon 1 (ipsilateral hilum), 2 (ipsilateral station 4 and 7), and 3 (rest of the mediastinum, contralateral hilum). The endpoints were overall survival (OS), progression-free survival (PFS), and freedom from local progression (FFLP). RESULTS: The median follow-up time (95 % confidence interval [CI]) was 41.1 (33.8 - 50.4) months. Patients with a high absolute number of PET-positive LN stations had worse OS (hazard ratio [HR] = 1.09; 95 % CI 0.99 - 1.18; p = 0.05) and PFS (HR = 1.12; 95 % CI 1.04 - 1.20; p = 0.003), irrespective of treatment arm allocation. The prescribed RT dose to the LNs did not correlate with any of the endpoints when considering all patients. However, in patients in arm B (i.e., PET-based selective nodal irradiation), prescribed RT dose to each LN station correlated significantly with FFLP (HR=0.45; 95 % CI 0.24-0.85; p = 0.01). Furthermore, patients with involvement of echelon 3 LN stations had worse PFS (HR = 2.22; 95 % CI 1.16-4.28; p = 0.02), also irrespective of allocation. CONCLUSION: Mediastinal tumor burden and lymphatic involvement patterns influence outcome in patients treated with definitive chemoradiotherapy for locally advanced NSCLC. Higher dose to LNs did not improve OS, but did improve FFLP in patients treated with PET-based dose-escalated RT.

Study protocol for Near-infrared molecular imaging for lung cancer detection and treatment during mini-invasive surgery (phase II Trial) - (the RECOGNISE study).

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).

Serum tumor markers: potential indicators for occult lymph node metastasis in clinical T1 - 2N0M0 small cell lung cancer patients.

In their letter-to-the-editor entitled "Letter to the Editor: Incidence rate of occult lymph node metastasis in clinical T1 - 2N0M0 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 T1 - 2N0M0 (cT1 - 2N0M0) 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 cT1 - 2N0M0 SCLC patients. Additionally, further exploration and confirmation through prospective, large-scale studies with robust external validation are needed.

Automatic segmentation of esophageal cancer, metastatic lymph nodes and their adjacent structures in CTA images based on the UperNet Swin network.

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.

Cross-sectional investigation of the distribution characteristics and prognostic significance of lateral lymph nodes in patients with rectal cancer.

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.