Predictors of lateral lymph node metastasis and skip metastasis in patients with papillary thyroid microcarcinoma.

Background: Papillary thyroid microcarcinoma (PTMC) is characterized by its favorable prognosis and potential for active surveillance (AS) as a management option. However, the presence of cervical lymph node (LN) metastasis, especially lateral LN metastasis, significantly impacts management and prognosis. Previous studies have focused on post-surgery risk factors for cervical LN metastasis. This study aims to identify predictors of lateral LN metastasis by analyzing pre-operative ultrasonographic findings alongside clinicopathological factors. Methods: A retrospective review of medical records was conducted for patients with PTMC who underwent surgery at Chonnam National University Hwasun Hospital between 2004 and 2013. This is a case-control study that compares patients with lateral LN metastasis (N1b) to age- and sex-matched patients without LN metastasis (N0). Subgroup analysis was performed to evaluate risk factors of skip metastasis. Results: The study included 90 patients with PTMC with lateral LN metastasis (N1b) and 268 age- and sex-matched patients without LN metastasis (N0). The mean age was 49.3 years, and female patients were dominant in both groups. Structural recurrences of 4.4% (4/90) were observed only in the N1b group. The N1b group exhibited a higher frequency of upper lobe tumor location compared to the N0 group (38.9% vs. 16.0%, p < 0.001). There was no significant difference in the locations with the presence of invasion to adjacent organs. A higher proportion of non-parallel shape was observed in the N1b group than the N0 group (80.0% vs. 66.0%, p = 0.013). There were no differences in echogenicity, sonographic feature, margin, and AP diameter of the thyroid gland between the two groups. In multivariate analysis, independent risk factors for lateral LN metastasis included extrathyroidal extension, multiplicity, upper lobe tumor location, and non-parallel shape. Skip metastasis in patients with PTMC was associated with upper lobe tumor location. Conclusion: Detailed ultrasound examinations, evaluating tumor location, number, orientation, and the presence of ETE, are crucial in accurately predicting lateral LN metastasis especially when primary tumor was in the upper lobe to avoid missing skip metastasis. These evaluations can help guide the decision between AS and immediate surgery in patients with PTMC.

Risk factors and development of machine learning diagnostic models for lateral lymph node metastasis in rectal cancer: multicentre study.

BACKGROUND: The diagnostic criteria for lateral lymph node metastasis in rectal cancer have not been established. This research aimed to investigate the risk factors for lateral lymph node metastasis and develop machine learning models combining these risk factors to improve the diagnostic performance of standard imaging. METHOD: This multicentre prospective study included patients who underwent lateral lymph node dissection without preoperative treatment for rectal cancer between 2017 and 2019 in 15 Japanese institutions. First, preoperative clinicopathological factors and magnetic resonance imaging findings were evaluated using multivariable analyses for their correlation with lateral lymph node metastasis. Next, machine learning diagnostic models for lateral lymph node metastasis were developed combining these risk factors. The models were tested in a training set and in an internal validation cohort and their diagnostic performance was tested using receiver operating characteristic curve analyses. RESULTS: Of 212 rectal cancers, 122 patients were selected, including 232 lateral pelvic sides, 30 sides of which had pathological lateral lymph node metastasis. Multivariable analysis revealed that poorly differentiated/mucinous adenocarcinoma, extramural vascular invasion, tumour deposit and a short-axis diameter of lateral lymph node ≥ 6.0 mm were independent risk factors for lateral lymph node metastasis. Patients were randomly divided into a training cohort (139 sides) and a test cohort (93 sides) and machine learning models were computed on the basis of a combination of significant features (including: histological type, extramural vascular invasion, tumour deposit, short- and long-axis diameter of lateral lymph node, body mass index, serum carcinoembryonic antigen level, cT, cN, cM, irregular border and mixed signal intensity). The top three models with the highest sensitivity in the training cohort were as follows: support vector machine (sensitivity, 1.000; specificity, 0.773), light gradient boosting machine (sensitivity, 0.950; specificity, 0.918) and ensemble learning (sensitivity, 0.950; specificity, 0.917). The diagnostic performances of these models in the test cohort were as follows: support vector machine (sensitivity, 0.750; specificity, 0.667), light gradient boosting machine (sensitivity, 0.500; specificity, 0.852) and ensemble learning (sensitivity, 0.667; specificity, 0.864). CONCLUSION: Machine learning models combining multiple risk factors can contribute to improving diagnostic performance of lateral lymph node metastasis.

Diagnostic performance of ultrasonography in pre-operative assessment of lymph nodes in patients with cervical cancer.

OBJECTIVES: To assess the diagnostic performance of ultrasonography in pre-operative assessment of lymph nodes in patients with cervical cancer, to compare the outcomes for pelvic and para-aortic regions, and to detect macrometastases and micrometastases separately. METHODS: Patients were retrospectively included if they met the following inclusion criteria: pathologically verified cervical cancer; ultrasonography performed by one of four experienced sonographers; surgical lymph node staging, at least in the pelvic region-sentinel lymph node biopsy or systematic pelvic lymphadenectomy or debulking. The final pathological examination was the reference standard. RESULTS: 390 patients met the inclusion criteria between 2009 and 2019. Pelvic node macrometastases (≥2 mm) were confirmed in 54 patients (13.8%), and micrometastases (≥0.2 mm and <2 mm) in another 21 patients (5.4%). Ultrasonography had sensitivity 72.2%, specificity 94.0%, and area under the curve (AUC) 0.831 to detect pelvic macrometastases, while sensitivity 53.3%, specificity 94.0%, and AUC 0.737 to detect both pelvic macrometastases and micrometastases (pN1). Ultrasonography failed to detect pelvic micrometastases, with sensitivity 19.2%, specificity 85.2%, and AUC 0.522. There was no significant impact of body mass index on diagnostic accuracy. Metastases in para-aortic nodes (macrometastases only) were confirmed in 16 of 71 patients who underwent para-aortic lymphadenectomy. Ultrasonography yielded sensitivity 56.3%, specificity 98.2%, and AUC 0.772 to identify para-aortic node macrometastases. CONCLUSION: Ultrasonography performed by an experienced sonographer can be considered a sufficient diagnostic tool for pre-operative assessment of lymph nodes in patients with cervical cancer, showing similar diagnostic accuracy in detection of pelvic macrometastases as reported for other imaging methods (18F-fluorodeoxyglucose positron emission tomography/CT or diffusion-weighted imaging/MRI). It had low sensitivity for detection of small-volume macrometastases (largest diameter <5 mm) and micrometastases. The accuracy of para-aortic assessment was comparable to that for pelvic lymph nodes, and assessment of the para-aortic region should be an inseparable part of the examination protocol.

Ga68-PSMA PET for lymph node staging in intermediate and high-risk prostate cancer patients undergoing robotic assisted radical prostatectomy.

BACKGROUND: In intermediate/high risk prostate cancer, preoperative staging exams are mandatory. The aim of these imaging studies is to evaluate eventual lymph nodes involvement and/or metastatic spread of the tumor. Nevertheless, computed tomography (CT), magnetic resonance imaging (MRI), bone scan modalities have controversial sensitivity. Introduction of PET-PSMA and its use also as preoperative exam, seems to improve diagnostic accuracy due to favorable negative predictive value. The aim of this study was to evaluate the accuracy of PET-PSMA as a preoperative staging exam and its accuracy in predicting lymph nodes involvement in intermediate/high risk prostate cancer (PCa) patients. METHODS: A retrospective analysis of 50 patients diagnosed with intermediate/high risk PCa between 2018 and 2022 has been performed. All patients underwent preoperative 68Ga-PSMA PET/CT prior to robot-assisted radical prostatectomy (RARP) + extended pelvic lymph node dissection (ePLND). The cohort was categorized into two groups: pathologically negative lymph nodes (pN0) vs. positive nodes (pN1). A descriptive and comparative analysis was conducted. Correlation analysis between continuous variables was performed using the Spearman's Rank Test. Using lymph nodes histopathological results as reference standard, the diagnostic performance of 68Ga-PSMA PET/CT was calculated. RESULTS: Overall, 50 patients were included. The mean age was 63.3 years with a median prostatic specific antigen (PSA) of 7.7 ng/dL. Forty-four percent of the patients exhibited an International Society of Urological Pathology (ISUP) score of 4 or higher, and 28% had a pT3 stage. Overall, 43 (86%) patients submitted to ePLND did not present lymph node metastases (pN0), while 8 (14%) patients were pN1. PET-PSMA showed low sensitivity in detecting lymph node metastases (25%) while a high specificity in excluding lymph-node disease (88.1%) has been observed. Finally, we noted a significant positive correlation between the total SUVmax of the prostate and the initial total PSA (r=0.38; P=0.019), as well as the percentage of tumor involvement (r=0.383; P=0.022). CONCLUSIONS: Evidence on the role of PET-PSMA in the primary staging of PCa is steadily building up. A positive correlation between SUV and prostate involvement indicates that PET-PSMA could reflect, with a good approximation, the pathological features of the prostate. However, the low sensitivity depicted remains the main limitation. Future prospective studies are needed to determine the impact on patient outcome.

Development and validation of a preoperative radiomics-based nomogram to identify patients who can benefit from splenic hilar lymphadenectomy: a pooled analysis of three prospective trials.

BACKGROUND: The authors aimed to use preoperative computed tomography images to develop a radiomic nomogram to select patients who would benefit from spleen-preserving splenic hilar (No.10) lymphadenectomy (SPSHL). METHODS: A pooled analysis of three distinct prospective studies was performed. The splenic hilar lymph node (SHLN) ratio (sLNR) was established as the quotient of the number of metastatic SHLN to the total number of SHLN. Radiomic features reflecting the phenotypes of the primary tumor (RS1) and SHLN region (RS2) were extracted and used as predictive factors for sLNR. RESULTS: This study included 733 patients: 301 in the D2 group and 432 in the D2+No.10 group. The optimal sLNR cutoff value was set at 0.4, and the D2+No.10 group was divided into three groups: sLNR=0, sLNR ≤0.4, and sLNR >0.4. Patients in the D2+No. 10 group were randomly divided into the training ( n =302) and validation ( n =130) cohorts. The AUCs value of the nomogram, including RS1 and RS2, were 0.952 in the training cohort and 0.888 in the validation cohort. The entire cohort was divided into three groups based on the nomogram scores: low, moderate, and high SHLN metastasis burden groups (LMB, MMB, and HMB, respectively). A similar 5-year OS rate was found between the D2 and D2+No. 10 groups in the LMB and HMB groups. In the MMB group, the 5-year OS of the D2+No. 10 group (73.4%) was significantly higher than that of the D2 group (37.6%) ( P <0.001). CONCLUSIONS: The nomogram showed good predictive ability for distinguishing patients with various SHLN metastasis burdens. It can accurately identify patients who would benefit from SPSHL.

Biparametric MRI of the prostate radiomics model for prediction of pelvic lymph node metastasis in prostate cancers : a two-centre study.

OBJECTIVES: Exploring the value of adding correlation analysis (radiomic features (RFs) of pelvic metastatic lymph nodes and primary lesions) to screen RFs of primary lesions in the feature selection process of establishing prediction model. METHODS: A total of 394 prostate cancer (PCa) patients (263 in the training group, 74 in the internal validation group and 57 in the external validation group) from two tertiary hospitals were included in the study. The cases with pelvic lymph node metastasis (PLNM) positive in the training group were diagnosed by biopsy or MRI with a short-axis diameter ≥ 1.5 cm, PLNM-negative cases in the training group and all cases in validation group were underwent both radical prostatectomy (RP) and extended pelvic lymph node dissection (ePLND). The RFs of PLNM-negative lesion and PLNM-positive tissues including primary lesions and their metastatic lymph nodes (MLNs) in the training group were extracted from T2WI and apparent diffusion coefficient (ADC) map to build the following two models by fivefold cross-validation: the lesion model, established according to the primary lesion RFs selected by t tests and absolute shrinkage and selection operator (LASSO); the lesion-correlation model, established according to the primary lesion RFs selected by Pearson correlation analysis (RFs of primary lesions and their MLNs, correlation coefficient > 0.9), t test and LASSO. Finally, we compared the performance of these two models in predicting PLNM. RESULTS: The AUC and the DeLong test of AUC in the lesion model and lesion-correlation model were as follows: training groups (0.8053, 0.8466, p = 0.0002), internal validation group (0.7321, 0.8268, p = 0.0429), and external validation group (0.6445, 0.7874, p = 0.0431), respectively. CONCLUSION: The lesion-correlation model established by features of primary tumors correlated with MLNs has more advantages than the lesion model in predicting PLNM.

Comparative analysis of F-18 FDG PET/CT images between scrub typhus and systemic lupus erythematosus.

This study evaluated the use of F-18 fluorodeoxyglucose (FDG) PET/CT imaging to differentiate between scrub typhus and systemic lupus erythematosus (SLE) in patients presenting with lymphadenopathy. We carried out a retrospective analysis of 18 scrub typhus patients and seven SLE patients, using various imaging parameters, including lymph node size, spleen and liver lengths, the distance between the two farthest lesions (Dmax), and assessments of glucose metabolism. On FDG PET images, we measured the maximum standardized uptake value (SUVmax) of the lymph nodes, spleen, and liver and the mean standardized uptake value (SUVmean) of the liver and spleen. The Dmax values of scrub typhus patients were significantly longer than those of SLE patients, indicating that lymphadenopathy is more generalized in the patients with scrub typhus. The SUVmax values for the lymph node, spleen, and liver were also higher in patients with scrub typhus, while the SUVmean of the liver and spleen did not differ between the two groups. This study is the first to compare FDG PET/CT images between these two conditions, suggesting the potential of this imaging modality to provide critical diagnostic distinctions.

A study on the correlation of Doppler ultrasound in the diagnosis of cervical lymph nodes in patients with laryngeal and hypopharyngeal cancers: An observational study.

The objective was to assess the diagnostic efficacy of Doppler ultrasound in detecting cervical lymph nodes in patients diagnosed with laryngeal and hypopharyngeal cancers. Patients undergoing surgery for laryngeal and hypopharyngeal cancers in the Otolaryngology Department from January 2021 to January 2023 were included. Two groups, with equal numbers, underwent ultrasound examination and intensive CT examination in the experimental and control groups, respectively, along with routine cervical lymph node dissection. A resident with over 6 years of clinical experience in the otolaryngology department performed routine bilateral cervical lymph node palpation. Sensitivity, specificity, and validity were compared among different examination methods. The McNemar test assessed specificity and sensitivity between palpation, color Doppler ultrasonography, and enhanced CT, while the Kappa concordance test evaluated the concordance between the 2 examination methods. Data were statistically analyzed using SPSS 23.0. Palpation showed a diagnostic sensitivity (DS) of 52.83% and specificity of 91.11% for all patients with cervical lymph node metastasis. Ultrasonography demonstrated a DS of 77.78% and specificity of 81.82% in patients with cervical lymph node metastasis, while intensive CT had a DS of 75.86% and specificity of 60.00%. Statistical significance (P < .05) was observed in the sensitivity between palpation and ultrasonography, and between palpation and enhanced CT. The specificity between enhanced CT and ultrasonography (P = .021) and between palpation and enhanced CT scan (P = .003) both showed statistical significance (P < .05). Doppler ultrasound yields diagnostic results highly consistent with pathological diagnoses in patients with laryngeal and hypopharyngeal cancers. Utilizing Doppler ultrasound can enhance the accuracy of diagnosing these cancers, aiding physicians in devising more suitable treatment plans for patients.

Targeted axillary dissection reduces residual nodal disease in clinically node- positive breast cancer after neoadjuvant chemotherapy.

BACKGROUND: Any advantage of performing targeted axillary dissection (TAD) compared to sentinel lymph node (SLN) biopsy (SLNB) is under debate in clinically node-positive (cN+) patients diagnosed with breast cancer. Our objective was to assess the feasibility of the removal of the clipped node (RCN) with TAD or without imaging-guided localisation by SLNB to reduce the residual axillary disease in completion axillary lymph node dissection (cALND) in cN+ breast cancer. METHODS: A combined analysis of two prospective cohorts, including 253 patients who underwent SLNB with/without TAD and with/without ALND following NAC, was performed. Finally, 222 patients (cT1-3N1/ycN0M0) with a clipped lymph node that was radiologically visible were analyzed. RESULTS: Overall, the clipped node was successfully identified in 246 patients (97.2%) by imaging. Of 222 patients, the clipped lymph nodes were non-SLNs in 44 patients (19.8%). Of patients in cohort B (n=129) with TAD, the clipped node was successfully removed by preoperative image-guided localisation, or the clipped lymph node was removed as the SLN as detected on preoperative SPECT-CT. Among patients with ypSLN(+) (n=109), no significant difference was found in non-SLN positivity at cALND between patients with TAD and RCN (41.7% vs. 46.9%, p=0.581). In the subgroup with TAD with axillary lymph node dissection (ALND; n=60), however, patients with a lymph node (LN) ratio (LNR) less than 50% and one metastatic LN in the TAD specimen were found to have significantly decreased non-SLN positivity compared to others (27.6% vs. 54.8%, p=0.032, and 22.2% vs. 50%, p=0.046). CONCLUSIONS: TAD by imaging-guided localisation is feasible with excellent identification rates of the clipped node. This approach has also been found to reduce the additional non-SLN positivity rate to encourage omitting ALND in patients with a low metastatic burden undergoing TAD.

Preliminary study of indocyanine green-guided laparoscopic lateral lymph node dissection for rectal cancer.

BACKGROUND: LLNM can occur in mid-low rectal cancer, but LLND in patients with rectal cancer presents certain challenges. Recent years have seen the progressive application of ICG fluorescence imaging technology in colorectal surgery. This study aimed to explore the effectiveness of ICG-guided laparoscopic LLND for rectal cancer. METHODS: We applied ICG-guided laparoscopic lateral lymph node dissection in 11 patients diagnosed as rectal cancer with lateral lymph node metastasis. RESULTS: All 11 patients in this group successfully completed ICG-guided laparoscopic LLND for rectal cancer with good lateral lymph node imaging. CONCLUSIONS: ICG-guided laparoscopic LLND for rectal cancer is safe and represents a feasible solution, thereby providing valuable guidance for intraoperative lymph node dissection.

Predictive value of MRI-based deep learning model for lymphovascular invasion status in node-negative invasive breast cancer.

To retrospectively assess the effectiveness of deep learning (DL) model, based on breast magnetic resonance imaging (MRI), in predicting preoperative lymphovascular invasion (LVI) status in patients diagnosed with invasive breast cancer who have negative axillary lymph nodes (LNs). Data was gathered from 280 patients, including 148 with LVI-positive and 141 with LVI-negative lesions. These patients had undergone preoperative breast MRI and were histopathologically confirmed to have invasive breast cancer without axillary LN metastasis. The cohort was randomly split into training and validation groups in a 7:3 ratio. Radiomics features for each lesion were extracted from the first post-contrast dynamic contrast-enhanced (DCE)-MRI. The Least Absolute Shrinkage and Selection Operator (LASSO) regression method and logistic regression analyses were employed to identify significant radiomic features and clinicoradiological variables. These models were established using four machine learning (ML) algorithms and one DL algorithm. The predictive performance of the models (radiomics, clinicoradiological, and combination) was assessed through discrimination and compared using the DeLong test. Four clinicoradiological parameters and 10 radiomic features were selected by LASSO for model development. The Multilayer Perceptron (MLP) model, constructed using both radiomic and clinicoradiological features, demonstrated excellent performance in predicting LVI, achieving a high area under the curve (AUC) of 0.835 for validation. The DL model (MLP-radiomic) achieved the highest accuracy (AUC = 0.896), followed by DL model (MLP-combination) with an AUC of 0.835. Both DL models were significantly superior to the ML model (RF-clinical) with an AUC of 0.720. The DL model (MLP), which integrates radiomic features with clinicoradiological information, effectively aids in the preoperative determination of LVI status in patients with invasive breast cancer and negative axillary LNs. This is beneficial for making informed clinical decisions.

Predictive value of an ultrasound-based radiomics model for central lymph node metastasis of papillary thyroid carcinoma.

Purpose: We aimed to explore the predictive value of an ultrasound-based radiomics model for the central lymph node metastasis of papillary thyroid carcinoma. Methods: A total of 126 patients with papillary thyroid carcinoma treated between February 2021 and February 2023 were retrospectively enrolled and assigned into metastasis group (n=59, with cervical central lymph node metastasis) or non-metastasis group (n=67, without metastasis) based on surgical and pathological findings. Intergroup comparisons were conducted on the results of contrast-enhanced ultrasonography, preoperative conventional ultrasonography, as well as real-time shear wave elastography. Results: The maximum lesion diameter, echo, margin, capsule invasion, calcification, average elasticity modulus (Eavg), rising time (RT), and peak intensity (PI) had diagnostic value for papillary thyroid carcinoma, and their combination exhibited higher diagnostic value (area under the curve: 0.817). The logistic regression model was built, and the maximum lesion diameter, hypoechoic/extremely hypoechoic, lobulated or irregular margin (95% confidence interval: 1.451-6.755), capsule invasion, microcalcification/macrocalcification or peripheral calcification, high-level Eavg, low-level RT and high-level PI served as risk elements affecting papillary thyroid carcinoma from the aspect of central lymph node metastasis (odds ratio>1, P<0.05). According to the logistic regression model, the model was reliable and stable (area under the curve: 0.889, P<0.05). Conclusion: The established ultrasound-based radiomics model can be utilized for early identifying the central lymph node metastasis of papillary thyroid carcinoma.

Intrathoracic Lymph Node Microcalcifications are Associated With a High Prevalence of Malignancy and Anaplastic Lymphoma Kinase Rearrangement: The "Calce" Study.

BACKGROUND: Microcalcifications are acknowledged as a malignancy risk factor in multiple cancers. However, the prevalence and association of intrathoracic lymph node (ILN) calcifications with malignancy remain unexplored. METHODS: In this cross-sectional study, we enrolled patients with known/suspected malignancy and an indication for endosonography for diagnosis or ILN staging. We assessed the prevalence and pattern of calcified ILNs and the prevalence of malignancy in ILNs with and without calcifications. In addition, we evaluated the genomic profile and PD-L1 expression in lung cancer patients, stratifying them based on the presence or absence of ILN calcifications. RESULTS: A total of 571 ILNs were sampled in 352 patients. Calcifications were detected in 85 (24.1%) patients and in 94 (16.5%) ILNs, with microcalcifications (78/94, 83%) being the predominant type. Compared with ILNs without calcifications (214/477, 44.9%), the prevalence of malignancy was higher in ILNs with microcalcifications (73/78, 93.6%; P<0.0001) but not in those with macrocalcifications (7/16, 43.7%; P=0.93). In patients with lung cancer, the high prevalence of metastatic involvement in ILNs displaying microcalcifications was independent of lymph node size (< or >1 cm) and the clinical stage (advanced disease; cN2/N3 disease; cN0/N1 disease). The anaplastic lymphoma kinase (ALK) rearrangement was significantly more prevalent in patients with than in those without calcified ILNs (17.4% vs. 1.7%, P<0.001), and all of them exhibited microcalcifications. CONCLUSION: ILN microcalcifications are common in patients undergoing endosonography for suspected malignancy, and they are associated with a high prevalence of metastatic involvement and ALK rearrangement.

Using T2-weighted magnetic resonance imaging-derived radiomics to classify cervical lymphadenopathy in children.

BACKGROUND: Cervical lymphadenopathy is common in children and has diverse causes varying from benign to malignant, their similar manifestations making differential diagnosis difficult. OBJECTIVE: This study aimed to investigate whether radiomic models using conventional magnetic resonance imaging (MRI) could classify pediatric cervical lymphadenopathy. METHODS: A total of 419 cervical lymph nodes from 146 patients, and encompassing four common etiologies (Kikuchi disease, reactive hyperplasia, suppurative lymphadenitis and malignancy), were randomly divided into training and testing sets in a ratio of 7:3. For each lymph node, 1,218 features were extracted from T2-weighted images. Then, the least absolute shrinkage and selection operator (LASSO) models were used to select the most relevant ones. Two models were built using a support vector machine classifier, one was to classify benign and malignant lymph nodes and the other further distinguished four different diseases. The performance was assessed by receiver operating characteristic curves and decision curve analysis. RESULTS: By LASSO, 20 features were selected to construct a model to distinguish benign and malignant lymph nodes, which achieved an area under the curve (AUC) of 0.89 and 0.80 in the training and testing sets, respectively. Sixteen features were selected to construct a model to distinguish four different cervical lymphadenopathies. For each etiology, Kikuchi disease, reactive hyperplasia, suppurative lymphadenitis, and malignancy, an AUC of 0.97, 0.91, 0.88, and 0.87 was achieved in the training set, and an AUC of 0.96, 0.80, 0.82, and 0.82 was achieved in the testing set, respectively. CONCLUSION: MRI-derived radiomic analysis provides a promising non-invasive approach for distinguishing causes of cervical lymphadenopathy in children.

A novel fully automatic segmentation and counting system for metastatic lymph nodes on multimodal magnetic resonance imaging: Evaluation and prognostic implications in nasopharyngeal carcinoma.

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

Application of radiomics for preoperative prediction of lymph node metastasis in colorectal cancer: a systematic review and meta-analysis.

BACKGROUND: Colorectal cancer (CRC) stands as the third most prevalent cancer globally, projecting 3.2 million new cases and 1.6 million deaths by 2040. Accurate lymph node metastasis (LNM) detection is critical for determining optimal surgical approaches, including preoperative neoadjuvant chemoradiotherapy and surgery, which significantly influence CRC prognosis. However, conventional imaging lacks adequate precision, prompting exploration into radiomics, which addresses this shortfall by converting medical images into reproducible, quantitative data. METHODS: Following PRISMA, Supplemental Digital Content 1 (http://links.lww.com/JS9/C77) and Supplemental Digital Content 2 (http://links.lww.com/JS9/C78), and AMSTAR-2 guidelines, Supplemental Digital Content 3 (http://links.lww.com/JS9/C79), we systematically searched PubMed, Web of Science, Embase, Cochrane Library, and Google Scholar databases until 11 January 2024, to evaluate radiomics models' diagnostic precision in predicting preoperative LNM in CRC patients. The quality and bias risk of the included studies were assessed using the Radiomics Quality Score (RQS) and the modified Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Subsequently, statistical analyses were conducted. RESULTS: Thirty-six studies encompassing 8039 patients were included, with a significant concentration in 2022-2023 (20/36). Radiomics models predicting LNM demonstrated a pooled area under the curve (AUC) of 0.814 (95% CI: 0.78-0.85), featuring sensitivity and specificity of 0.77 (95% CI: 0.69, 0.84) and 0.73 (95% CI: 0.67, 0.78), respectively. Subgroup analyses revealed similar AUCs for CT and MRI-based models, and rectal cancer models outperformed colon and colorectal cancers. Additionally, studies utilizing cross-validation, 2D segmentation, internal validation, manual segmentation, prospective design, and single-center populations tended to have higher AUCs. However, these differences were not statistically significant. Radiologists collectively achieved a pooled AUC of 0.659 (95% CI: 0.627, 0.691), significantly differing from the performance of radiomics models (P<0.001). CONCLUSION: Artificial intelligence-based radiomics shows promise in preoperative lymph node staging for CRC, exhibiting significant predictive performance. These findings support the integration of radiomics into clinical practice to enhance preoperative strategies in CRC management.

Spectral CT for preoperative diagnosis of N2 station lymph node metastasis in solid T1 non-small cell lung cancer.

PURPOSE: To evaluate the diagnostic value of spectral CT for the preoperative diagnosis of N2 station lymph nodes metastasis in solid T1 non-small cell lung cancer (NSCLC). METHOD: For this retrospective study, dual-phase contrast agent-enhanced CT was performed in patients with NSCLC from September 2019 to June 2023. Quantitative spectral CT parameters measurements were performed by 2 radiologists independently. Logistic regression analysis and Delong test were performed. RESULTS: 60 NSCLC patients (mean age, 62.85 years ± 8.49, 44men) were evaluated. A total of 121 lymph nodes (38 with metastasis) were enrolled. There was no significant difference in the slope of the spectral Hounsfield unit curve (λHu) on arterial phase (AP) or venous phase (VP) between primary lesions and metastatic lymph nodes (P > 0.05), but significant difference in VP λHu between primary lesions and non-metastatic lymph nodes (P < 0.001). The CT40KeV, λHu, normalized iodine concentration (nIC), normalized effective atomic number (nZeff) measured during both AP and VP were lower in metastatic lymph nodes than in non-metastatic lymph nodes (all P < 0.05). Short-axis diameter (S) of metastatic lymph nodes was higher than non-metastatic lymph nodes (P < 0.001). Area under the curve (AUC) for S performed the highest (0.788) in diagnosing metastatic lymph nodes. When combined with VP λHu, VP nZeff, AUC increased to 0.871. CONCLUSION: Spectral CT is a complementary means for the preoperative diagnosis of N2 station lymph nodes metastasis in solid T1 NSCLC. The combined parameters have higher diagnostic efficiency.

Indocyanine green near-infrared fluorescence-assisted video endoscopic inguinal lymph node dissection for rectal cancer: a single-center experience.

BACKGROUND: This study aimed to investigate the safety and feasibility of indocyanine green near-infrared fluorescence (ICG-NIR) fluorescence-guided video-endoscopic inguinal lymphadenectomy (VEIL) for rectal cancer with inguinal lymph node metastasis (ILNM). METHODS: A retrospective analysis was conducted on 11 patients with rectal cancer who underwent ICG-NIR fluorescence-guided VEIL, assessing various parameters such as operation time, intraoperative bleeding, number of harvested lymph nodes, intraoperative and postoperative complications, and follow-up. RESULTS: Regarding surgical procedures for ILNM, unilateral surgery was performed in 7 cases (54.5%) and bilateral surgery in 4 cases (45.5%). Among these 15 ICG-NIR-guided VEIL surgeries in 11 patients, positive fluorescence visualization was achieved in 13 operations (86.7%). The median estimated blood loss was 10 ml, and the median operation time was 90 min. One case (6.7%) required conversion to open surgery. The median duration of the drain tube was 12 days, and the median length of postoperative hospital stay was 20 days. Postoperative complications were observed, including incisional infection in 2 cases (18.2%), lymphatic leakage in 5 cases (45.5%), urinary infection in 1 case (9.1%), and pneumonia in 3 cases (27.3%). Complications such as skin necrosis, lower limb venous thrombosis, lower limb swelling, or impaired movement were observed during the postoperative follow-up period. No cases of primary lesion, groin, or pelvic lymph node recurrence were observed. CONCLUSION: ICG-NIR fluorescence-guided VEIL is a safe and feasible surgical treatment for rectal cancer with ILNM. ICG fluorescence guidance holds promise as a more personalized and precise approach for VEIL in rectal cancer surgery.