RESUMEN
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.
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Axila , Neoplasias de la Mama , Ganglios Linfáticos , Imagen por Resonancia Magnética , Estadificación de Neoplasias , Humanos , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/patología , Neoplasias de la Mama/genética , Femenino , Imagen por Resonancia Magnética/métodos , Ganglios Linfáticos/patología , Ganglios Linfáticos/diagnóstico por imagen , Persona de Mediana Edad , Axila/diagnóstico por imagen , Axila/patología , Pronóstico , Adulto , Estimación de Kaplan-Meier , Metástasis Linfática/diagnóstico por imagen , Anciano , Estudios Retrospectivos , RadiómicaRESUMEN
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).
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Neoplasias Pulmonares , Imagen Molecular , Cirugía Torácica Asistida por Video , Humanos , Neoplasias Pulmonares/cirugía , Neoplasias Pulmonares/diagnóstico por imagen , Cirugía Torácica Asistida por Video/métodos , Imagen Molecular/métodos , Espectroscopía Infrarroja Corta/métodos , Cetuximab/uso terapéutico , Cetuximab/administración & dosificación , Verde de Indocianina/administración & dosificación , Metástasis Linfática , Femenino , Masculino , Procedimientos Quirúrgicos Mínimamente Invasivos/métodos , Ganglios Linfáticos/patología , Ganglios Linfáticos/diagnóstico por imagen , Ganglios Linfáticos/cirugíaRESUMEN
Accurate lymph node (LN) retrieval during colorectal carcinoma resection is pivotal for precise N-staging and the determination of adjuvant therapy. Current guidelines recommend the examination of at least 12 mesocolic or mesorectal lymph nodes for accurate staging. Traditional histological processing techniques, reliant on visual inspection and palpation, are time-consuming and heavily dependent on the examiner's expertise and availability. Various methods have been documented to enhance LN retrieval from colorectal specimens, including intra-arterial ex vivo methylene blue injection. Recent studies have explored the utility of indocyanine green (ICG) fluorescence imaging for visualizing pericolic lymph nodes and identifying sentinel lymph nodes in colorectal malignancies. This study included 10 patients who underwent colon resection for malignant tumors. During surgery, intravenous ICG dye and an endoscopic camera were employed to assess intestinal perfusion. Post-resection, ex vivo intra-arterial administration of ICG dye was performed on the specimens, followed by routine histological processing and an ICG-assisted lymph node dissection. The objective was to evaluate whether ICG imaging could identify additional lymph nodes compared to routine manual dissection and to assess the clinical relevance of these findings. For each patient, a minimum of 12 lymph nodes (median = 25.5, interquartile range = 12.25, maximum = 33) were examined. ICG imaging facilitated the detection of a median of three additional lymph nodes not identified during routine processing. Metastatic lymph nodes were found in four patients however no additional metastatic nodes were detected with ICG assistance. Our findings suggest that ex vivo intra-arterial administration of indocyanine green dye can augment lymph node dissection, particularly in cases where the number of lymph nodes retrieved is below the recommended threshold of 12.
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Neoplasias Colorrectales , Estudios de Factibilidad , Verde de Indocianina , Escisión del Ganglio Linfático , Ganglios Linfáticos , Humanos , Verde de Indocianina/administración & dosificación , Neoplasias Colorrectales/patología , Neoplasias Colorrectales/diagnóstico por imagen , Neoplasias Colorrectales/cirugía , Proyectos Piloto , Femenino , Masculino , Anciano , Ganglios Linfáticos/patología , Ganglios Linfáticos/diagnóstico por imagen , Persona de Mediana Edad , Escisión del Ganglio Linfático/métodos , Metástasis Linfática/patología , Metástasis Linfática/diagnóstico por imagen , Colorantes , Fluorescencia , Imagen Óptica/métodos , Anciano de 80 o más Años , Colorantes Fluorescentes/administración & dosificaciónRESUMEN
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.
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Biomarcadores de Tumor , Neoplasias Pulmonares , Metástasis Linfática , Carcinoma Pulmonar de Células Pequeñas , Humanos , Neoplasias Pulmonares/sangre , Neoplasias Pulmonares/patología , Neoplasias Pulmonares/diagnóstico , Carcinoma Pulmonar de Células Pequeñas/sangre , Carcinoma Pulmonar de Células Pequeñas/patología , Carcinoma Pulmonar de Células Pequeñas/diagnóstico , Biomarcadores de Tumor/sangre , Estadificación de Neoplasias/métodos , Masculino , Femenino , Antígenos de Neoplasias/sangre , Ganglios Linfáticos/patología , Ganglios Linfáticos/diagnóstico por imagenRESUMEN
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.
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Axila , Neoplasias de la Mama , Biopsia del Ganglio Linfático Centinela , Humanos , Femenino , Neoplasias de la Mama/patología , Neoplasias de la Mama/terapia , Neoplasias de la Mama/cirugía , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/diagnóstico , Persona de Mediana Edad , Estudios Retrospectivos , Biopsia del Ganglio Linfático Centinela/métodos , Adulto , Anciano , Metástasis Linfática , Ganglios Linfáticos/patología , Ganglios Linfáticos/diagnóstico por imagen , Terapia Neoadyuvante/métodos , Examen Físico , Estadificación de Neoplasias , Biopsia con Aguja Fina/métodosRESUMEN
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.
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Axila , Neoplasias de la Mama , Metástasis Linfática , Imagen por Resonancia Magnética , Humanos , Femenino , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/patología , Metástasis Linfática/diagnóstico por imagen , Persona de Mediana Edad , Imagen por Resonancia Magnética/métodos , Adulto , Anciano , Ganglios Linfáticos/diagnóstico por imagen , Ganglios Linfáticos/patología , Invasividad Neoplásica , Estudios Retrospectivos , Medios de Contraste , Curva ROC , RadiómicaRESUMEN
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.
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Axila , Neoplasias de la Mama , Ganglios Linfáticos , Imagen por Resonancia Magnética , Humanos , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/patología , Neoplasias de la Mama/cirugía , Neoplasias de la Mama/mortalidad , Femenino , Persona de Mediana Edad , Estudios Retrospectivos , Axila/diagnóstico por imagen , Imagen por Resonancia Magnética/métodos , Adulto , Supervivencia sin Enfermedad , Ganglios Linfáticos/diagnóstico por imagen , Ganglios Linfáticos/patología , Metástasis Linfática/diagnóstico por imagen , Anciano , Estadificación de Neoplasias , Cuidados Preoperatorios/métodos , Factores de Riesgo , Curva ROCRESUMEN
Objective: To analyze the radiomic and clinical features extracted from 2D ultrasound images of thyroid tumors in patients with Hashimoto's thyroiditis (HT) combined with papillary thyroid carcinoma (PTC) using machine learning (ML) models, and to explore the diagnostic performance of the method in making preoperative noninvasive identification of cervical lymph node metastasis (LNM). Methods: A total of 528 patients with HT combined with PTC were enrolled and divided into two groups based on their pathological results of the presence or absence of LNM. The groups were subsequently designated the With LNM Group and the Without LNM Group. Three ultrasound doctors independently delineated the regions of interest and extracted radiomic features. Two modes, radiomic features and radiomics-clinical features, were used to construct random forest (RF), support vector machine (SVM), LightGBM, K-nearest neighbor (KNN), and XGBoost models. The performance of these five ML models in the two modes was evaluated by the receiver operating characteristic (ROC) curves on the test dataset, and SHapley Additive exPlanations (SHAP) was used for model visualization. Results: All five ML models showed good performance, with area under the ROC curve (AUC) ranging from 0.798 to 0.921. LightGBM and XGBoost demonstrated the best performance, outperforming the other models (P<0.05). The ML models constructed with radiomics-clinical features performed better than those constructed using only radiomic features (P<0.05). The SHAP visualization of the best-performing models indicated that the anteroposterior diameter, superoinferior diameter, original_shape_VoxelVolume, age, wavelet-LHL_firstorder_10Percentile, and left-to-right diameter had the most significant effect on the LightGBM model. On the other hand, the superoinferior diameter, anteroposterior diameter, left-to-right diameter, original_shape_VoxelVolume, original_firstorder_InterquartileRange, and age had the most significant effect on the XGBoost model. Conclusion: ML models based on radiomics and clinical features can accurately evaluate the cervical lymph node status in patients with HT combined with PTC. Among the 5 ML models, LightGBM and XGBoost demonstrate the best evaluation performance.
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Enfermedad de Hashimoto , Metástasis Linfática , Aprendizaje Automático , Cáncer Papilar Tiroideo , Neoplasias de la Tiroides , Ultrasonografía , Humanos , Carcinoma Papilar/diagnóstico por imagen , Enfermedad de Hashimoto/complicaciones , Enfermedad de Hashimoto/diagnóstico por imagen , Ganglios Linfáticos/patología , Ganglios Linfáticos/diagnóstico por imagen , Cuello/diagnóstico por imagen , Radiómica , Curva ROC , Máquina de Vectores de Soporte , Cáncer Papilar Tiroideo/diagnóstico por imagen , Cáncer Papilar Tiroideo/patología , Cáncer Papilar Tiroideo/complicaciones , Neoplasias de la Tiroides/patología , Neoplasias de la Tiroides/diagnóstico por imagen , Ultrasonografía/métodosRESUMEN
OBJECTIVE: The ultrasonographic characteristics of lymph node metastasis in breast cancer patients were retrospectively analyzed, and a predictive nomogram model was constructed to provide an imaging basis for better clinical evaluation. METHODS: B-mode ultrasound was used to retrospectively analyze the imaging characteristics of regional lymph nodes and tumors. Pathological examination confirmed the presence of lymph node metastasis in breast cancer patients. Univariable and multivariable logistic regression analyses were performed to analyze the risk factors for lymph node metastasis. LASSO regression analysis was performed to screen noninvasive indicators, and a nomogram prediction model was constructed for breast cancer patients with lymph node metastasis. RESULTS: A total of 187 breast cancer patients were enrolled, including 74 patients with lymph node metastasis in the positive group and 113 patients without lymph node metastasis in the negative group. Multivariate analysis revealed that pathological type (OR = 4.58, 95% CI: 1.44-14.6, p = 0.01), tumor diameter (OR = 1.37, 95% CI: 1.07-1.74, p = 0.012), spiculated margins (OR = 7.92, 95% CI: 3.03-20.67, p < 0.001), mixed echo of the breast tumor (OR = 37.09, 95% CI: 3.49-394.1, p = 0.003), and unclear lymphatic hilum structure (OR = 16.07, 95% CI: 2.41-107.02, p = 0.004) were independent risk factors for lymph node metastasis. A nomogram model was constructed for predicting breast cancer with lymph node metastasis, incorporating three significantly correlated indicators identified through LASSO regression analysis, namely, tumor spiculated margins, cortical thickness of lymph nodes, and unclear lymphatic hilum structure. The receiver operating characteristic (ROC) curve revealed that the area under the curve (AUC) was 0.717 (95% CI, 0.614-0.820) for the training set and 0.817 (95% CI, 0.738-0.890) for the validation set. The Hosmer-Lemeshow test results for the training set and the validation set were p = 0.9148 and p = 0.1648, respectively. The prediction nomogram has good diagnostic performance. CONCLUSIONS: B-mode ultrasound is helpful in the preoperative assessment of breast cancer patients with lymph node metastasis. The predictive nomogram model, which is based on logistic regression and LASSO regression analysis, is clinically safe, reliable, and highly practical.
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Neoplasias de la Mama , Ganglios Linfáticos , Metástasis Linfática , Nomogramas , Humanos , Neoplasias de la Mama/patología , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/cirugía , Femenino , Metástasis Linfática/diagnóstico por imagen , Estudios Retrospectivos , Persona de Mediana Edad , Ganglios Linfáticos/patología , Ganglios Linfáticos/diagnóstico por imagen , Ganglios Linfáticos/cirugía , Adulto , Pronóstico , Anciano , Factores de Riesgo , Estudios de Seguimiento , Ultrasonografía Mamaria/métodos , Ultrasonografía/métodos , Carcinoma Ductal de Mama/diagnóstico por imagen , Carcinoma Ductal de Mama/patología , Carcinoma Ductal de Mama/cirugía , Carcinoma Ductal de Mama/secundarioRESUMEN
BACKGROUND: The tumor burden within the axillary lymph nodes (ALNs) constitutes a pivotal factor in breast cancer, serving as the primary determinant for treatment decisions and exhibiting a close correlation with prognosis. OBJECTIVE: This study aimed to investigate the potential of ultrasound-based radiomics and clinical characteristics in non-invasively distinguishing between low tumor burden (1-2 positive nodes) and high tumor burden (more than 2 positive nodes) in patients with node-positive breast cancer. METHODS: A total of 215 patients with node-positive breast cancer, who underwent preoperative ultrasound examinations, were enrolled in this study. Among these patients, 144 cases were allocated to the training set, 37 cases to the validation set, and 34 cases to the testing set. Postoperative histopathology was used to determine the status of ALN tumor burden. The region of interest for breast cancer was delineated on the ultrasound image. Nine models were developed to predict high ALN tumor burden, employing a combination of three feature screening methods and three machine learning classifiers. Ultimately, the optimal model was selected and tested on both the validation and testing sets. In addition, clinical characteristics were screened to develop a clinical model. Furthermore, Shapley additive explanations (SHAP) values were utilized to provide explanations for the machine learning model. RESULTS: During the validation and testing sets, the models demonstrated area under the curve (AUC) values ranging from 0.577 to 0.733 and 0.583 to 0.719, and accuracies ranging from 64.9% to 75.7% and 64.7% to 70.6%, respectively. Ultimately, the Boruta_XGB model, comprising five radiomics features, was selected as the final model. The AUC values of this model for distinguishing low from high tumor burden were 0.828, 0.715, and 0.719 in the training, validation, and testing sets, respectively, demonstrating its superiority over the clinical model. CONCLUSIONS: The developed radiomics models exhibited a significant level of predictive performance. The Boruta_XGB radiomics model outperformed other radiomics models in this study.
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Axila , Neoplasias de la Mama , Ganglios Linfáticos , Metástasis Linfática , Carga Tumoral , Ultrasonografía , Humanos , Femenino , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/patología , Persona de Mediana Edad , Axila/diagnóstico por imagen , Ganglios Linfáticos/diagnóstico por imagen , Ganglios Linfáticos/patología , Metástasis Linfática/diagnóstico por imagen , Adulto , Ultrasonografía/métodos , Anciano , Aprendizaje Automático , Valor Predictivo de las Pruebas , RadiómicaRESUMEN
Contrast enhanced ultrasonography enables dynamic evaluation of the microvasculature down to the capillaries when using high resolution ultrasound probes. It's application in the evaluation of axillary lymph nodes in breast cancer patients with clinically negative axilla has been studied in 42 patients. The results of pre operative CEUS evaluation was correlated with histopathology status of axillary nodes after the harvesting of nodes during modified radical mastectomy or sentinel node biopsy. Heterogeneous enhancement with micro bubbles of the axillary nodes was found to be the most distinguishing criteria for malignant nodes.
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Axila , Neoplasias de la Mama , Medios de Contraste , Ganglios Linfáticos , Metástasis Linfática , Biopsia del Ganglio Linfático Centinela , Humanos , Femenino , Neoplasias de la Mama/patología , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/cirugía , Ganglios Linfáticos/patología , Ganglios Linfáticos/diagnóstico por imagen , Ganglios Linfáticos/cirugía , Medios de Contraste/administración & dosificación , Persona de Mediana Edad , Metástasis Linfática/diagnóstico por imagen , Adulto , Biopsia del Ganglio Linfático Centinela/métodos , Anciano , Pronóstico , Ultrasonografía/métodos , Estadificación de Neoplasias , Estudios de SeguimientoRESUMEN
BACKGROUND: Hepatic alveolar echinococcosis (AE) is a severe zoonotic parasitic disease, and accurate preoperative prediction of lymph node (LN) metastasis in AE patients is crucial for disease management, but it remains an unresolved challenge. The aim of this study was to establish a radiomics model for the preoperative prediction of LN metastasis in hepatic AE patients. METHODS: A total of 100 hepatic AE patients who underwent hepatectomy and hepatoduodenal ligament LN dissection at Qinghai Provincial People's Hospital between January 2016 and August 2023 were included in the study. The patients were randomly divided into a training set and a validation set at an 8:2 ratio. Radiomic features were extracted from three-dimensional images of the hepatoduodenal ligament LNs delineated on arterial phase computed tomography (CT) scans of hepatic AE patients. Least absolute shrinkage and selection operator (LASSO) regression was applied for data dimensionality reduction and feature selection. Multivariate logistic regression analysis was performed to develop a prediction model, and the predictive performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). RESULTS: A total of 7 radiomics features associated with LN status were selected using LASSO regression. The classification performances of the training set and validation set were consistent, with area under the operating characteristic curve (AUC) values of 0.928 and 0.890, respectively. The model also demonstrated good stability in subsequent validation. CONCLUSION: In this study, we established and evaluated a radiomics-based prediction model for LN metastasis in patients with hepatic AE using CT imaging. Our findings may provide a valuable reference for clinicians to determine the occurrence of LN metastasis in hepatic AE patients preoperatively, and help guide the implementation of individualized surgical plans to improve patient prognosis.
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Equinococosis Hepática , Escisión del Ganglio Linfático , Ganglios Linfáticos , Tomografía Computarizada por Rayos X , Adulto , Anciano , Femenino , Humanos , Masculino , Persona de Mediana Edad , Equinococosis Hepática/cirugía , Equinococosis Hepática/diagnóstico por imagen , Equinococosis Hepática/patología , Hepatectomía/métodos , Escisión del Ganglio Linfático/métodos , Ganglios Linfáticos/diagnóstico por imagen , Ganglios Linfáticos/parasitología , Ganglios Linfáticos/patología , Ganglios Linfáticos/cirugía , Radiómica , Estudios Retrospectivos , Curva ROC , Tomografía Computarizada por Rayos X/métodosRESUMEN
BACKGROUND: Mediastinal tubercular lymphadenitis is form of extrapulmonary tuberculosis [EPTB]. Clinical presentations are non-specific and diagnosis remains great clinical challenge. Microbiological and or histopathological evidences need to be present in order make diagnosis secure before initiation of anti-tubercular therapy (ATT). Endoscopic ultrasound guided fine needle aspiration (EUS-FNA) provides tissue samples and aids management of this difficult to diagnosed entity. Current study describe role of EUS-FNA and Gene Xpert (GXP) in mediastinal tubercular lymphadenitis. METHODS: Retrospective analysis of 72 patients with mediastinal lymphadenopathy who underwent EUS-FNA were carried out. Linear echoendoscope was used for evaluation mediastinum. EUS echo features of LNs were studied. Twenty two-G needle used was for aspiration tissue sample from pathologic lymph nodes (LNs). FNA samples were analysed by cytology, Acid-Fast Bacilli (AFB) staining and GXP study. All procedures were uneventful without any complications. RESULTS: Forty two patients were diagnosed as tuberculosis (TB) following first EUS-FNA setting. Six patients underwent repeat EUS-FNA procedure following which another 3 were diagnosed as TB while remaining 3 started on empirical ATT based on additional supportive evidences. Forty five patients showed granulomatous inflammation on cytological analysis, AFB positivity noted in 16 (33.33%) patients while GXP in 26 (57.78%) patients. Rifampicin resistance detected in 3 ((6.25%) patients. All patients were followed clinico-radiologically for response to treatment. CONCLUSION: Tuberculous lymphadenitis is the most common cause of mediastinal lymphadenopathy in TB endemic countries. EUS-FNA provides microbiological and histopathological/cytological evidences in this difficult to diagnosed EPTB and thereby avoids empirical ATT.
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Biopsia por Aspiración con Aguja Fina Guiada por Ultrasonido Endoscópico , Ganglios Linfáticos , Tuberculosis Ganglionar , Humanos , Biopsia por Aspiración con Aguja Fina Guiada por Ultrasonido Endoscópico/métodos , Masculino , Tuberculosis Ganglionar/diagnóstico , Tuberculosis Ganglionar/patología , Tuberculosis Ganglionar/tratamiento farmacológico , Femenino , Estudios Retrospectivos , Adulto , Persona de Mediana Edad , Ganglios Linfáticos/patología , Ganglios Linfáticos/diagnóstico por imagen , Adulto Joven , Mycobacterium tuberculosis/aislamiento & purificación , Adolescente , Enfermedades del Mediastino/patología , Enfermedades del Mediastino/diagnóstico , Anciano , Mediastino/patologíaRESUMEN
BACKGROUND: Although accurate preoperative diagnosis of lymph node metastasis is essential for optimizing treatment strategies for low rectal cancer, the accuracy of present diagnostic modalities has room for improvement. OBJECTIVE: The study aimed to establish a high-precision diagnostic method for lymph node metastasis of low rectal cancer using artificial intelligence. DESIGN: A retrospective observational study. SETTINGS: A single cancer center and a college of engineering in Japan. PATIENTS: Patients with low rectal adenocarcinoma who underwent proctectomy, bilateral lateral pelvic lymph node dissection, and contrast-enhanced multidetector row CT (slice ≤1 mm) between July 2015 and August 2021 were included in the present study. All pelvic lymph nodes from the aortic bifurcation to the upper edge of the anal canal were extracted, regardless of whether within or beyond the total mesenteric excision area, and pathological diagnoses were annotated for training and validation. MAIN OUTCOME MEASURES: Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. RESULTS: A total of 596 pathologically negative nodes and 43 positive nodes from 52 patients were extracted and annotated. Four diagnostic methods, with and without using super-resolution images and with and without using 3-dimensional shape data, were performed and compared. The super-resolution + 3-dimensional shape data method had the best diagnostic ability for the combination of sensitivity, negative predictive value, and accuracy (0.964, 0.966, and 0.968, respectively), whereas the super-resolution only method had the best diagnostic ability for the combination of specificity and positive predictive value (0.994 and 0.993, respectively). LIMITATIONS: Small number of patients at a single center and the lack of external validation. CONCLUSIONS: Our results enlightened the potential of artificial intelligence for the method to become another game changer in the diagnosis and treatment of low rectal cancer. See Video Abstract . DIAGNSTICO POR IMGENES CON INTELIGENCIA ARTIFICIAL MEDIANTE SUPERRESOLUCIN Y FORMA D PARA LA METSTASIS EN LOS GANGLIOS LINFTICOS DEL CNCER DE RECTO BAJO UN ESTUDIO PILOTO DE UN SOLO CENTRO: ANTECEDENTES:Aunque el diagnóstico preoperatorio preciso de metástasis en los ganglios linfáticos es esencial para optimizar las estrategias de tratamiento para el cáncer de recto bajo, la precisión de las modalidades de diagnóstico actuales tiene margen de mejora.OBJETIVO:Establecer un método de diagnóstico de alta precisión para las metástasis en los ganglios linfáticos del cáncer de recto bajo utilizando inteligencia artificial.DISEÑO:Un estudio observacional retrospectivo.AJUSTE:Un único centro oncológico y una facultad de ingeniería en Japón.PACIENTES:En el presente estudio se incluyeron pacientes con adenocarcinoma rectal bajo sometidos a proctectomía, disección bilateral de ganglios linfáticos pélvicos laterales y tomografía computarizada con múltiples detectores con contraste (corte ≤1 mm) entre julio de 2015 y agosto de 2021. Se resecaron todos los ganglios linfáticos pélvicos desde la bifurcación aórtica hasta el borde superior del canal anal, independientemente de si estaban dentro o más allá del área de escisión mesentérica total, y se registraron los diagnósticos patológicos para entrenamiento y validación.PRINCIPALES MEDIDAS DE RESULTADO:Sensibilidad, especificidad, valor predictivo positivo, valor predictivo negativo y precisión.RESULTADOS:Se extrajeron y registraron un total de 596 ganglios patológicamente negativos y 43 positivos de 52 pacientes. Se realizaron y compararon cuatro métodos de diagnóstico, con y sin imágenes de súper resolución y sin datos de imagen en 3D. El método de superresolución + datos de imagen en 3D tuvo la mejor capacidad de diagnóstico para la combinación de sensibilidad, valor predictivo negativo y precisión (0,964, 0,966 y 0,968, respectivamente), mientras que el método de súper resolución solo tuvo la mejor capacidad de diagnóstico para la combinación de especificidad y valor predictivo positivo (0,994 y 0,993, respectivamente).LIMITACIONES:Pequeño número de pacientes en un solo centro y falta de validación externa.CONCLUSIONES:Nuestros resultados iluminan el potencial de la inteligencia artificial para que el método se convierta en otro elemento de cambio en el diagnóstico y tratamiento del cáncer de recto bajo. (Traducción ---Dr. Fidel Ruiz Healy ).
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Adenocarcinoma , Inteligencia Artificial , Ganglios Linfáticos , Metástasis Linfática , Neoplasias del Recto , Humanos , Neoplasias del Recto/patología , Neoplasias del Recto/diagnóstico por imagen , Metástasis Linfática/diagnóstico por imagen , Metástasis Linfática/patología , Masculino , Femenino , Proyectos Piloto , Estudios Retrospectivos , Persona de Mediana Edad , Anciano , Ganglios Linfáticos/patología , Ganglios Linfáticos/diagnóstico por imagen , Adenocarcinoma/patología , Adenocarcinoma/diagnóstico por imagen , Adenocarcinoma/diagnóstico , Adenocarcinoma/secundario , Proctectomía/métodos , Imagenología Tridimensional/métodos , Escisión del Ganglio Linfático/métodos , Tomografía Computarizada Multidetector/métodos , Valor Predictivo de las Pruebas , Sensibilidad y Especificidad , Pelvis/diagnóstico por imagen , AdultoRESUMEN
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.
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Ganglios Linfáticos , Tomografía Computarizada por Rayos X , Humanos , Persona de Mediana Edad , Masculino , Femenino , Ganglios Linfáticos/diagnóstico por imagen , Ganglios Linfáticos/patología , Tomografía Computarizada por Rayos X/métodos , Diagnóstico Diferencial , Imagen Radiográfica por Emisión de Doble Fotón/métodos , Estudios Retrospectivos , Medios de Contraste , Anciano , Radiografía Torácica/métodos , RadiómicaRESUMEN
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_DenseNet121_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.
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Carcinoma de Pulmón de Células no Pequeñas , Neoplasias Pulmonares , Metástasis Linfática , Tomografía Computarizada por Rayos X , Humanos , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/patología , Metástasis Linfática/diagnóstico por imagen , Metástasis Linfática/patología , Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Carcinoma de Pulmón de Células no Pequeñas/patología , Carcinoma de Pulmón de Células no Pequeñas/secundario , Masculino , Femenino , Persona de Mediana Edad , Tomografía Computarizada por Rayos X/métodos , Anciano , Aprendizaje Profundo , Imagenología Tridimensional/métodos , Adulto , Estudios Retrospectivos , Anciano de 80 o más Años , Ganglios Linfáticos/patología , Ganglios Linfáticos/diagnóstico por imagenRESUMEN
BACKGROUND: The accurate evaluation of axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer holds great value. This study aimed to develop an artificial intelligence system utilising multiregional dynamic contrast-enhanced MRI (DCE-MRI) and clinicopathological characteristics to predict axillary pathological complete response (pCR) after NAC in breast cancer. METHODS: This study included retrospective and prospective datasets from six medical centres in China between May 2018 and December 2023. A fully automated integrated system based on deep learning (FAIS-DL) was built to perform tumour and ALN segmentation and axillary pCR prediction sequentially. The predictive performance of FAIS-DL was assessed using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. RNA sequencing analysis were conducted on 45 patients to explore the biological basis of FAIS-DL. FINDINGS: 1145 patients (mean age, 50 years ±10 [SD]) were evaluated. Among these patients, 506 were in the training and validation sets (axillary pCR rate of 40.3%), 127 in the internal test set (axillary pCR rate of 37.8%), 414 in the pooled external test set (axillary pCR rate of 48.8%), and 98 in the prospective test set (axillary pCR rate of 43.9%). For predicting axillary pCR, FAIS-DL achieved AUCs of 0.95, 0.93, and 0.94 in the internal test set, pooled external test set, and prospective test set, respectively, which were also significantly higher than those of the clinical model and deep learning models based on single-regional DCE-MRI (all P < 0.05, DeLong test). In the pooled external and prospective test sets, the FAIS-DL decreased the unnecessary axillary lymph node dissection rate from 47.9% to 6.8%, and increased the benefit rate from 52.2% to 86.5%. RNA sequencing analysis revealed that high FAIS-DL scores were associated with the upregulation of immune-mediated genes and pathways. INTERPRETATION: FAIS-DL has demonstrated satisfactory performance in predicting axillary pCR, which may guide the formulation of personalised treatment regimens for patients with breast cancer in clinical practice. FUNDING: This study was supported by the National Natural Science Foundation of China (82371933), National Natural Science Foundation of Shandong Province of China (ZR2021MH120), Mount Taishan Scholars and Young Experts Program (tsqn202211378), Key Projects of China Medicine Education Association (2022KTM030), China Postdoctoral Science Foundation (314730), and Beijing Postdoctoral Research Foundation (2023-zz-012).
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Neoplasias de la Mama , Ganglios Linfáticos , Imagen por Resonancia Magnética , Terapia Neoadyuvante , Humanos , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/patología , Neoplasias de la Mama/diagnóstico por imagen , Femenino , Persona de Mediana Edad , Imagen por Resonancia Magnética/métodos , Ganglios Linfáticos/patología , Ganglios Linfáticos/diagnóstico por imagen , Axila , Adulto , Curva ROC , Medios de Contraste , Aprendizaje Profundo , Metástasis Linfática , Resultado del Tratamiento , Estudios Retrospectivos , Estudios Prospectivos , PronósticoRESUMEN
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.
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Axila , Neoplasias de la Mama , Aprendizaje Profundo , Escisión del Ganglio Linfático , Ganglios Linfáticos , Metástasis Linfática , Imagen por Resonancia Magnética , Terapia Neoadyuvante , Humanos , Femenino , Neoplasias de la Mama/patología , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/terapia , Terapia Neoadyuvante/métodos , Persona de Mediana Edad , Estudios Retrospectivos , Imagen por Resonancia Magnética/métodos , Metástasis Linfática/diagnóstico por imagen , Escisión del Ganglio Linfático/métodos , Adulto , Ganglios Linfáticos/diagnóstico por imagen , Ganglios Linfáticos/patología , Anciano , Medios de Contraste , Máquina de Vectores de Soporte , Valor Predictivo de las Pruebas , RadiómicaRESUMEN
OBJECTIVE: To compare the diagnostic accuracy of Contrast Enhanced Computed Tomography (CECT) compared to conventional imaging modalities and histopathological investigation in cervical lymph node metastasis in adults through a novel meta- analysis. METHOD: The review protocol is registered under PROSPERO(CRD42021225704) and performed in accordance to Preferred Reporting Items for Systematic Reviews and Meta-Analysis - Diagnostic Test Accuracy (PRISMA- DTA) checklist. Databases like PubMed, Google Scholar, EBSCOhost were searched from 2000 to 2023 to identify the diagnostic potential of CECT in cervical lymph node metastasis of oral carcinoma. True-positive, false-positive, true-negative, false-negative, sensitivity, specificity values were extracted or calculated if not present for each study. Quality of selected studies was evaluated based on Quality assessment of diagnostic accuracy studies (QUADAS)- 2 tool. Meta-analysis was performed in Meta-Disc 1.4 software and Review Manager 5.3 using a bivariate model parameter for the pooled sensitivity and pooled specificity. Additional analysis was performed in terms of positive likelihood ratio (+LR), negative likelihood ratio (-LR), diagnostic odds ratio (DOR) and summary receiver operating characteristics (SROC) with Area Under Curve (AUC) and p<0.05 as statistically significant. RESULTS: Six studies were included for qualitative synthesis and as well as for meta-analysis. Two studies had high risk of bias while four studies had low risk of bias. 651 patients underwent CECT and were taken for meta-analysis. The meta-analysis revealed that CECT for diagnosing cervical lymph node metastasis had a pooled sensitivity of 71%, pooled specificity of 14% with 60% Area Under Curve (AUC). +LR of 0.84, -LR of 1.36 and DOR of 0.59. CONCLUSION: CECT has an overall fair diagnostic ability and is a valid and reliable tool in diagnosing the target condition overcoming high reliance on master specialized capacity for their execution and understanding like other conventional imaging techniques. CECT can be concluded for secondary level of prevention for cervical node metastasis of oral carcinoma under early diagnosis and prompt treatment. However, further standardized accuracy studies are indicated to improve the overall diagnostic accuracy of CECT.
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Medios de Contraste , Ganglios Linfáticos , Metástasis Linfática , Neoplasias de la Boca , Tomografía Computarizada por Rayos X , Humanos , Ganglios Linfáticos/patología , Ganglios Linfáticos/diagnóstico por imagen , Metástasis Linfática/diagnóstico por imagen , Neoplasias de la Boca/patología , Neoplasias de la Boca/diagnóstico por imagen , Cuello/diagnóstico por imagen , Cuello/patología , Pronóstico , Sensibilidad y Especificidad , Tomografía Computarizada por Rayos X/métodosRESUMEN
We evaluated the efficacy of indocyanine green fluorescence imaging compared to that of traditional nanocarbon dyes in assessing peri-intestinal lymph node metastasis in patients with colorectal cancer, which is a key prognostic factor. The relationship between indocyanine green fluorescence imaging and histopathological outcomes in patients with colon cancer has also been explored. A retrospective analysis was conducted on 30 patients with colon cancer (from May to October 2023) confirmed by surgical pathology. Tumors were marked with indocyanine green (ICG) or nanocarbon via colonoscopy 16 to 24 hours before surgery. Within 15 minutes after surgery, peri-intestinal lymph node fluorescence imaging and hematoxylin and eosin staining were used to assess the distribution of cancer foci. The correlation between cancer foci distribution, fluorescence intensity, and area under the receiver operating characteristic curve was measured. Among 243 metastatic lymph nodes from 30 patients, 18 were found. After the patients were divided into metastatic and nonmetastatic groups, significant differences in tumor differentiation and stage were noted (Pâ <â .001). The fluorescence intensity was strongly correlated with the presence and proportion of metastasis (area under the receiver operating characteristic curveâ =â 0.931), whereas nanocarbon staining showed no significant correlation (Pâ =â .81). All P values were two-sided, with Pâ <â .05 indicating statistical significance. Lymph nodes with malignant intestinal tumor metastasis displayed weaker ICG fluorescence than did nonmetastatic nodes. Combining ICG and nanocarbon staining techniques enhances intraoperative lymph node dissection and postoperative analysis, indicating their potential utility in colorectal cancer surgery.