Assessment Of Node Status Research Articles

Machine learning-based radiomics for guiding lymph node dissection in clinical stage I lung adenocarcinoma: a multicenter retrospective study.

Preoperative assessment of lymph node status is critical in managing lung cancer, as it directly impacts the surgical approach and treatment planning. However, in clinical stage I lung adenocarcinoma (LUAD), determining lymph node metastasis (LNM) is often challenging due to the limited sensitivity of conventional imaging modalities, such as computed tomography (CT) and positron emission tomography/CT (PET/CT). This study aimed to establish an effective radiomics prediction model using multicenter data for early assessment of LNM risk in patients with clinical stage I LUAD. The goal is to provide a basis for formulating lymph node dissection strategies before surgery in early-stage lung cancer patients. A total of 578 patients with LUAD from three medical centers [Cancer Hospital, Chinese Academy of Medical Sciences (CCAM), the First Affiliated Hospital of Chongqing Medical University (1CMU), and Beijing Chao-Yang Hospital (BCYH)] who underwent preoperative chest CT were divided into three groups, the training group (n=336), the testing group (n=167), and the independent validation group (n=75). The records of 1,316 radiomics features of each primary tumor were extracted. The least absolute shrinkage and selection operator (LASSO) analysis and multivariable logistic regression were used to reduce the data dimensionality, select features, and construct the prediction models. In the training group, the area under the curve (AUC) for the clinical model, radiomics model, and composite model were 0.820, 0.871, and 0.883, respectively. In the testing group, the AUC for the clinical model, radiomics model, and composite model were 0.897, 0.915, and 0.934, respectively. In the validation set, the AUC of the radiomics model was the highest at 0.870, while the composite model and clinical model had AUCs of 0.841 and 0.710, respectively. The results of the Delong test showed that the AUCs of the radiomics model and composite model were significantly higher than those of the clinical model in both the training and validation groups. The decision curve analysis showed that the radiomics nomogram was clinically useful. This study developed and validated a radiomics prediction model, which enables easy LNM prediction in stage I LUAD patients. This model provides a basis for formulating lymph node dissection strategies before surgery and helps to better determine the tumor node metastasis stage of the early-stage LUAD.

Lymph node assessment in cervical cancer: current approaches.

Cervical cancer (CC) is the fourth most common neoplasia in women worldwide. Although early-stage CC is often curable, 40 to 50% of patients are diagnosed at a locally advanced stage. Metastatic disease accounts for the principal cause of death. Lymph node (LN) status is a major factor impacting treatment options andprognosis. Historically, CC was staged based only on clinical findings. However, in 2018, imaging modalities and/or pathological findings were included in the International Federation of Gynecology and Obstetrics (FIGO) staging classification. In the last decades, LN status assessment has evolved considerably. Full pelvic lymphadenectomy used to be the only way to determine LN status. Currently, several options exist: surgery with full lymphadenectomy, sentinel lymph node (SLN) biopsy or imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET). Regarding surgery, the SLN biopsy technique has become a standard procedure in cases of CC, with indocyanine green (ICG) being the preferred dye. Pelvic MRI is a valuable imaging technique modality for the evaluation of pelvic LNs. In locally advanced or in early-stage disease with suspicious LNs on CT scans or MRI, PET/CT is recommended for assessment of nodal and distant status. The best strategy for LN assessment remains a highly controversial topic in the literature. In this article, we aim to review and compare the advantages and limitations of each modality, i.e. imaging or surgical (lymphadenectomy or SLN biopsy) approaches.

Future of sentinel node biopsy in ovarian cancer.

The rationale on the use of sentinel lymph node (SLN) biopsy in the surgical staging of apparent early-stage ovarian cancer (OC) is supported by the fact that diagnostic and prognostic role of systematic staging lymphadenectomy has been determined but its therapeutic significance is still matter of controversy. Moreover, SLN biopsy represents an option to decrease intra- and postoperative morbidity. The present review aims to provide an overview on the current and future role of SLN in OC. Most recent evidence shows that the overall mean per patient SLN detection rate in case of indocyanine green (ICG) alone was 58.6% compared with 95% in case of ICG + technetium, and with 52.9% in case of technetium alone or in combination with blue dye ( P < 0.001). Site of injection has been reported to be in both ovarian ligaments in majority of studies (utero-ovarian ligament and infundibulo-pelvic ligament), before or after ovarian mass removal, at time of primary or re-staging surgery and by minimally invasive or open approach. Cervical injection has been recently proposed to replace utero-ovarian injection. SLN detection rate in patients with confirmed ovarian malignancy varied across different studies ranging between 9.1% and 91.3% for the injection in the utero-ovarian ligament and migration to pelvic lymph nodes and between 27.3% and 100% for the injection in the infundibulo-pelvic ligament and migration to para-aortic lymph nodes. No intra- or postoperative complication could be attributed directly to SLN biopsy. The sensitivity and the accuracy of SLN in detecting lymphatic metastasis ranged between 73.3-100% and 96-100%, respectively. In up to 40% of positive SLNs, largest metastatic deposit was classified as micro-metastasis or isolated tumor cells, which would have been missed without ultrastaging protocol. SLN biopsy represents a promising tool to assess lymph node status in apparent early-stage OC. The type and volume of injected tracer need to be considered as appear to affect SLN detection rate. Ultrastaging protocol is essential to detect low volume metastasis. Sensitivity and accuracy of SLN biopsy are encouraging, providing tracer injection in both uterine and ovarian ligaments.

Laparoscopic Indocyanine Green-Guided Sentinel Lymph Node Biopsy for Gallbladder Neoplasms.

Surgical resection, the only potentially curative treatment for gallbladder cancer (GBC), entails an extended cholecystectomy with portal lymphadenectomy. Lymph node dissection is a key staging procedure, but its therapeutic value is unclear. Additionally, it is technically challenging and potentially harmful. Methods for better assessment of lymph node status are needed. This report presents a case of indocyanine green (ICG)-guided sentinel lymph node biopsy (SNLB) for a patient with a gallbladder mass suspicious for GBC. An 81-year-old woman consulted for abdominal discomfort. Abdominal ultrasound showed an intraluminal gallbladder mass suspicious for GBC. Staging imaging did not show liver invasion, lymphadenopathy, or distant metastasis. Given the woman's advanced age and limited extent of disease, a laparoscopic extended cholecystectomy with an ICG-guided SLNB was performed. Injection of 1 ml of ICG (0.125 mg/mL) into the gallbladder bed was performed using a 22-gauge needle, avoiding direct injection into the gallbladder wall. A near-infrared camera was used to visualize real-time ICG flow through the lymphatic vessels of the gallbladder toward the cystic node. Then, a sentinel lymph node posterolateral to the bile duct (station 12b) was identified. The node was resected and sent for permanent section. The procedure continued with an extended cholecystectomy. Pathology showed an intracholecystic papillary neoplasm with high-grade dysplasia. Cystic and sentinel lymph nodes were negative for malignancy. For patients with gallbladder neoplasms, ICG-guided SLNB is a feasible technique that could allow for treatment de-escalation. Further evaluation in clinical trials is needed.

Different tracers for sentinel node detection in gynecologic oncology.

In the past decade, sentinel lymph node (SLN) mapping has progressively substituted full lymphadenectomies in gynecologic oncology. In this article, we review the most relevant and the latest literature on this topic. In endometrial and cervical cancer, the current evidence further support the value of indocyanine green (ICG) as tracer of choice for SLN mapping. Experience in vulvar cancer is more limited, with ICG used together with technetium-99 m (Tc-99m) as a dual tracer but ICG, so far, has not been a game changer in this setting as it has been for cervical and endometrial cancer. For most gynecologic cancers, ICG fluorescence imaging is considered now a days the tracer of choice for lymphatic mapping. However, in early-stage vulvar cancer, SLN biopsy with radioactive tracer continues to be the standard-of-care in lymph node status assessment.

A Concordance Between Clinical and Pathological Tumor Staging of Oral Squamous Cell Carcinoma: An Institutional Study.

Among oral diseases, oral cancer is the primary cause of death and poses a serious health risk. Primary tumor (T) - regional lymph node (N) - distant metastasis (M) comprising (TNM) staging is crucial for planning treatment strategies for patients with oral squamous cell carcinoma (OSCC). This study evaluated the predictive accuracy of clinical TNM staging of OSCC to histopathological staging (pTNM) in an institutional setting. Fifty-four consecutive histologically confirmed, surgically treated OSCC cases were evaluated for TNM staging. The study compared the clinical staging at the time of surgery with the pathological staging obtained from excisional biopsy reports. Microsoft Excel (Microsoft® Corp., Redmond, WA, USA) was used for the data compilation and descriptive analysis. The chi-square test, analysis of variance (ANOVA), and Tukey's Honest Significant Difference (HSD) posthoc test were used to compare the data for statistical significance with p value <0.05 using Statistical Package for the Social Sciences (IBM SPSS Statistics for Windows, IBM Corp., Version 23.0, Armonk, NY). The alveolar mucosa (n=22, 40.74%) was the most frequently occurring site, followed by the tongue (n=17, 31.48%). Out of the 54 included cases, based on clinical tumor size, there were T1 (n=6), T2 (n=13), T3 (n=13), T4a (n=16) and T4b (n=6). T2 tumors were usually upstaged (n=7) while T4a (n=8) tumors were most often downstaged. T4a (n=8) had the best concordance between clinical and histopathological staging, followed by T2, T3, and T1. In nodal status, N1 showed the most variation. The chi-squared test showed statistical significance for tumor size comparison (p <0.001) and nodal status comparison (p=0.002). ANOVA test did not show any statistical significance. Tukey's HSD posthoc test showed statistical significance (p=0.034) for N0 and N1 status. The highest concordance was shown by N0 and N1 followed by N2b. Preoperative radiological and clinical assessments are essential for deciding on a patient's course of treatment. However, not all patients may require radiographs to determine tumor size or nodal status assessment. Accurate diagnosis is vital for the treatment planning of OSCC.

Impact of clinical lymph node status on survival in patients with intrahepatic cholangiocarcinoma undergoing liver resection plus lymphadenectomy.

Liver resection plus lymphadenectomy is essential to ensure precise staging in patients with intrahepatic cholangiocarcinoma (ICC). This study aimed to investigate the influence of the clinical status of lymph nodes on the survival outcomes in ICC patients. Between January 2015 and December 2020, consecutive patients diagnosed with ICC who underwent liver resection plus lymphadenectomy were enrolled. Clinical assessment of lymph node status included positron emission tomography/computed tomography examination by radiologists pre-operatively, alongside intraoperative abdominal examination by the surgical team. Retrospective collection and analysis of clinical information alongside survival data were performed to assess outcomes. The study included a total of 359 patients, with 291 (81.0%) and 151 (42.1%) displaying clinically and pathologically positive lymph nodes, respectively. The clinical assessment method had a sensitivity of 81.2% and a specificity of 54.3%. Following a median follow-up period of 32 months, the overall survival (OS) rates at 1, 3, and 5 years were 69.1%, 50.6%, and 41.2%, respectively, while the disease-free survival (DFS) rates were 60.7%, 42.8%, and 40.1%, respectively, across the cohort. Patients who had clinically positive but pathologically negative lymph nodes recorded the highest median OS (52 months) and median DFS (32 months). Conversely, those who were clinically negative but pathologically positive experienced the lowest median OS (16 months) and median DFS (8 months). The current approach to clinically assessing lymph node status in ICC has a significant rate of false positives. Patients with clinically positive but pathologically negative lymph nodes exhibit the most favourable survival outcomes.

Accuracy of ICG compared with technetium-99 m for sentinel lymph node biopsy in vulvar cancer

PurposeSentinel lymph node biopsy with radioactive tracer is the standard-of-care in lymph node status assessment in vulvar cancer. Indocyanine green fluorescence-ICG is a promising detection method, due to its advantages over technetium-99 m. In vulvar cancer, the procedure is controversial due to study heterogeneity and the small sample size in previous studies. This study evaluates ICG sentinel lymph node detection compared with the criterion-standard with technetium (dual modality method). MethodsPreoperative technetium and intraoperative ICG for sentinel lymph node have been prospectively evaluated in early-stage vulvar cancer. The primary endpoint was to determine accuracy in the detection rate for ICG compared with technetium. Secondary objectives included tracer modality relationship with obesity, tumor size and location. ResultsIn total, 75 patients participated at 8 centers; 38 had lateral and 37 had midline vulvar tumors. The overall sentinel lymph node detection rate was 85.3 % for technetium and 82.7 % for ICG. For lateral tumors, the detection rate was 84.2 % vs. 89.5 %, while it was 86.5 % vs. 75.7 % for middle tumors, using technetium and ICG, respectively. The median sentinel node harvest was 1.7 (range 1–4), with 24 % metastatic involvement. The sensitivity and positive predictive value for ICG based on the standard technique with technetium was 91.08 % (95 % CI, 83.76–95.84) and 94.8 % (95 % CI, 84.84–96.48), respectively. No significant differences were found comparing the two tracers in patients with midline lesions, obesity (body mass index ≥ 30) and tumor size ≥ 2–4 cm. Conclusion(s)ICG shows comparable performance parameters to the gold-standard of radioisotope localization.

Identification of Optimal Parameters for Assessing Lymph Node Status of Patients with Esophageal Squamous Cell Carcinoma After Neoadjuvant Chemoradiotherapy.

This study aimed to compare the prognostic discrimination power of pretreatment pathologic N stage (prepN), lymph node tumor regression grade (LNTRG), and posttreatment pathologic N (ypN) category for esophageal squamous cell carcinoma (ESCC) patients who received neoadjuvant chemoradiotherapy (nCRT) plus surgery. The study reviewed 187 ESCC patients from two medical centers who underwent nCRT plus surgery. Pathologic LNTRG was defined by the proportion of viable tumor area within the tumor bed in lymph nodes (LNs). An average LNTRG then was calculated by averaging the tumor regression grade (TRG) score of all resected LNs. Lymph nodes containing regression changes or vital tumor cells were used for interpretation of the prepN stage, which reflects the estimated number of originally involved LNs. The ypN, prepN, and LNTRG categories had significant prognostic stratification power (p < 0.001, log-rank test). Multivariable cox regression showed that all three categories were independent prognostic factors of disease-free survival (DFS) (p < 0.05). The LNTRG category showed a better prognostic value for DFS prediction than the ypN and prepN categories (Akaike information criterion [AIC]: LNTRG [933.69], ypN [937.56], prepN [937.45]). Additionally, the superior predictive capacity of the LNTRG category was demonstrated by decision curve analysis. Similar results were discovered for patients with remaining diseased LNs. The three staging categories had prognostic relevance for DFS, with the LNTRG category seeming to have better prognostic indication power. Comprehensive consideration of the ypN status, prepN status, and LN regression may allow for better prognostic stratification of patients.

Predictors of Bilateral SLN Radiocolloid Detection in Endometrial Carcinoma.

Introduction Sentinel lymph node (SLN) mapping is an alternative method to conventional lymphadenectomy for nodal status assessment in patients with stage I/II endometrial carcinoma (EC). This study aimed to analyze the potential predictors of unsuccessful bilateral detection of SLN after the application of radiocolloid in EC. Materials and Methods A prospective, observational, cross-sectional study was performed on 41 patients with EC in preoperative stage I, who underwent SLN mapping after cervical application of 4mCi 99m Tc-SENTI-SCINT. The demographic, clinical, and tumor-related data were obtained from the patient's medical records. Univariate analysis was used to analyze the potential factors associated with an unsuccessful bilateral SLN biopsy. Results The bilateral SLN detection rate of planar lymphoscintigraphy, single photon emission computed tomography/computed tomography, and gamma probe was 29.26, 41.46, and 26.82%, correspondingly. None of the 16 analyzed risk factors showed statistical significance for nonconclusive bilateral SLN biopsy. Conclusion Larger scale studies are needed to determine the exact risk factors for unsuccessful bilateral mapping of the lymphatic drainage after cervical application of the radiotracers. This will eventually lead to improvement in bilateral SLN detection in EC patients, so unilateral lymphadenectomy could be avoided.

Compression Optical Coherence Elastography for Assessing Lymph Node Status in Early Breast Cancer

Введение. Оценка состояния лимфатических узлов является важным фактором для определения стадии заболевания и выбора оптимальной тактики лечения при раке молочной железы (РМЖ). В настоящее время, остается потребность в применении новых высокоразрешающих методов визуализации, позволяющих интраоперационно оценивать статус лимфатических узлов, удаление которых будет достоверно определять степень распространения опухолевого процесса в регионарных лимфатических коллекторах без лимфаденэктомии. Таким методом может стать компрессионная оптическая когерентная эластография (К-ОКЭ), способная оценивать упругие свойства биотканей, которые значительно изменяются при метастатическом поражении лимфатических узлов. Цель исследования – изучить с помощью метода К-ОКЭ линейные (жесткость) и нелинейные упругие свойства лимфатических узлов при наличии или отсутствии в них метастазов РМЖ. Материалы и методы. Всего было исследовано 27 послеоперационных сигнальных и аксиллярных лимфатических узлов у 24 пациентов с верифицированным РМЖ с клинической стадией T1-2N0M0. В исследовании использовался скоростной спектральный мультимодальный ОКТ прибор (Институт прикладной физики РАН, Россия), который обеспечивает выполнение К-ОКЭ с вычислением абсолютных значений жесткости (модуля Юнга в кПа) и параметра упругой нелинейности ткани. Верификацию полученных ОКТ данных проводили с помощью стандартного гистологического исследования и все лимфатические узлы были разделены на четыре группы: нормальные (неактивные) (n=6), реактивные с фолликулярной гиперплазией (n=7), реактивные с синусовым гистиоцитозом (n=8) и метастатические (n=6). Результаты. В результате было установлено, что нормальные лимфатические узлы на изображениях К-ОКЭ характеризуются самыми низкими значениями жесткости в области коры с сохраненными лимфоидными фолликулами (&lt;200 кПа). Реактивные лимфатические узлы с фолликулярной гиперплазией демонстрируют умеренное повышение жесткости (200-300 кПа) в области коры и более выраженное увеличение жесткости (400-600 кПа) в областях синусового гистиоцитоза. Метастатические лимфатические узлы характеризуются самыми высокими значениями жесткости (&gt; 600 кПа). Взаимодополняющая оценка линейных и нелинейных упругих параметров ткани позволило с высокой статистической значимостью (р&lt;0.001) дифференцировать все четыре основные состояния лимфатических узлов. Выводы. К-ОКЭ позволяет дифференцировать нормальные, реактивные и метастатические лимфатические узлы. К-ОКЭ демонстрирует высокий потенциал для быстрой интраоперационной оценки статуса лимфатических узлов в реальном времени и сохранения непораженных узлов.

The minimal number of examined lymph nodes for accurate nodal staging and favorable prognosis in T1-2 supraglottic laryngeal squamous cell carcinoma

ObjectiveThe study aimed to investigate the minimal number of examined lymph nodes (ELNs) for accurate assessment of lymph node status and favorable prognosis in patients with stage T1-2 supraglottic laryngeal squamous cell carcinoma (LSCC) who received radical resection. MethodsPatients with stage T1-2 supraglottic LSCC from the Surveillance, Epidemiology, and End Results (SEER) database and the Chinese Academy of Medical Sciences, Cancer Hospital/National Cancer Center (NCC) were reviewed. The association of the ELN count with the identification of nodal metastasis and overall survival (OS) was analyzed using a multivariate regression model. Locally weighted scatterplot smoothing fitting curve and the ‘changepoint’ package were adopted to identify the optimal cut points using R. ResultsA total of 429 patients from the SEER database and 53 patients from NCC were enrolled. The probability of identifying nodal metastasis was positively related to the ELN count. For patients diagnosed with pathological stage N0 (pN0) disease, the mortality risks rapidly decreased when the amount of ELNs exceeded ten, and those with ELNs >10 had better OS. ConclusionAn adequate amount of ELNs benefits precise nodal staging in patients with stage T1-2 supraglottic LSCC. Ten lymph nodes are the minimum number of ELNs. For pN0 patients, an ELN count ≤10 is an unfavorable prognostic factor.

An [18F]FDG PET/3D-ultrashort echo time MRI-based radiomics model established by machine learning facilitates preoperative assessment of lymph node status in non-small cell lung cancer.

To develop an [18F]FDG PET/3D-UTE model based on clinical factors, three-dimensional ultrashort echo time (3D-UTE), and PET radiomics features via machine learning for the assessment of lymph node (LN) status in non-small cell lung cancer (NSCLC). A total of 145 NSCLC patients (training, 101 cases; test, 44 cases) underwent whole-body [18F]FDG PET/CT and chest [18F]FDG PET/MRI were enrolled. Preoperative clinical factors and 3D-UTE, CT, and PET radiomics features were analyzed. The Mann-WhitneyUtest, LASSO regression, and SelectKBest were used for feature extraction. Five machine learning algorithms were used to establish prediction models, which were evaluated by the area under receiver-operator characteristic (ROC), DeLong test, calibration curves, and decision curve analysis (DCA). A prediction model based on random forest, consisting of four clinical factors, six 3D-UTE, and six PET radiomics features, was used as the final model for PET/3D-UTE. The AUCs of this model were 0.912 and 0.791 in the training and test sets, respectively, which not only showed different degrees of improvement over individual models such as clinical, 3D-UTE, and PET (AUC-training = 0.838, 0.834, and 0.828, AUC-test = 0.756, 0.745, and 0.768, respectively) but also achieved the similar diagnostic efficacy as the optimal PET/CT model (AUC-training = 0.890, AUC-test = 0.793). The calibration curves and DCA indicated good consistency (C-index, 0.912) and clinical utility of this model, respectively. The [18F]FDG PET/3D-UTE model based on clinical factors, 3D-UTE, and PET radiomics features using machine learning methods could noninvasively assess the LN status of NSCLC. A machine learning model of 18F-fluorodeoxyglucose positron emission tomography/ three-dimensional ultrashort echo time could noninvasively assess the lymph node status of non-small cell lung cancer, which provides a novel method with less radiation burden for clinical practice. • The 3D-UTE radiomics model using the PLS-DA classifier was significantly associated with LN status in NSCLC and has similar diagnostic performance as the clinical, CT, and PET models. • The [18F]FDG PET/3D-UTE model based on clinical factors, 3D-UTE, and PET radiomics features using the RF classifier could noninvasively assess the LN status of NSCLC and showed improved diagnostic performance compared to the clinical, 3D-UTE, and PET models. • In the assessment of LN status in NSCLC, the [18F]FDG PET/3D-UTE model has similar diagnostic efficacy as the [18F]FDG PET/CT model that incorporates clinical factors and CT and PET radiomics features.

Magnetic resonance imaging in preoperative assessment of the mesorectal nodal status of patients with rectal cancer – Can it be trusted?

PurposeMagnetic resonance imaging (MRI) is a fundamental diagnostic modality for the evaluation of primary rectal cancer, but MRI assessment of nodal involvement remains a confounding factor. MethodThis prospective cohort study was conducted to investigate the accuracy of preoperative MRI in the assessment of nodal status by comparing histopathology reports to MRI findings on a node-by-node basis in 69 patients with rectal cancer. ResultsPrimary surgery was performed in 40 (58.0%) patients; 29 (42.0%) study patients underwent neoadjuvant chemoradiotherapy (CRT). Histopathological examination revealed T1 tumour in 8 (11.6%) patients, T2 tumour in 30 (43.5%), and T3 tumour in 25 (36.2%). In total, 897 lymph nodes (LNs) have been harvested (13.1 ± 5.4 LNs per specimen). There were 77 MRI-suspicious LNs, 21 (27.3%) of which were histologically proven malignant.The sensitivity of MRI for assessing nodal involvement was 51.2% and specificity 93.4%. Of the 28 patients with MRI-suspicious LNs the diagnosis was correct in 42.8%. The MRI accuracy was 33.3% in “primary surgery” subgroup (n = 18, malignant LNs found in 6 patients). Diagnosis of MRI-negative LNs was correct in 90.2% of study patients; malignant nodes were found in 9.8% of patients initially classified as cN0. ConclusionsMRI prediction of nodal status in patients with rectal cancer has very low accuracy. Decisions regarding neoadjuvant CRT should not be based on MRI assessment of nodal status, but on the MRI evaluation of tumour depth invasion (T stage and relationship between the tumour and mesorectal fascia).

Value of non-coding RNAs to assess lymph node status in cervical cancer.

Cervical cancer (CC) is the fourth cancer in women and is the leading cause of cancer death in 42 countries. Lymph node metastasis is a determinant prognostic factor, as underlined in the latest FIGO classification. However, assessment of lymph node status remains difficult, despite the progress of imaging such as PET-CT and MRI. In the specific setting of CC, all data underlined the need for new biomarkers easily available to assess lymph node status. Previous studies have underlined the potential value of ncRNA expression in gynecological cancers. In this review, we aimed to evaluate the contribution of ncRNAs in tissue and biofluid samples to determine lymph node status in CC with potential impact on both surgical and adjuvant therapies. In tissue samples, our analysis found that there are arguments to support the role of ncRNAs in physiopathology, differential diagnosis from normal tissue, preinvasive and invasive tumors. In biofluids, despite small studies especially concerning miRNAs expression, promising data opens up new avenue to establish a non-invasive signature for lymph node status as well as a tool to predict response to neo- and adjuvant therapies, thus improving management algorithm of patients with CC.

A PROSPECTIVE OBSERVATIONAL STUDY OF RESPONSE TO NEOADJUVANT CHEMOTHERAPY IN LOCALLY ADVANCED BREAST CANCER IN TERTIARY CENTRE

Introduction: Carcinoma of the breast from the very beginning has been a feared disease.' Till today, there is an aura of fear that surrounds the mention of this name 'breast cancer'. Neoadjuvant chemotherapy (NAC) is increasingly used to treat patients with locally advanced breast cancer (LABC). Such regimens can increase rates of breast-conserving therapy (BCT) compared with post-operative chemotherapy 2 and may minimize the need for aggressive nodal surgery with axillary lymph node dissection. To assess Aims: the change of clinical staging after Neoadjuvant Chemotherapy, Assessment of Lymph node status after neoadjuvant Chemotherapy and type of surgery suitable after neoadjuvant Chemotherapy. The present study was a hospital Materials and method: based observational study. The study conducted in Nil Ratan Sircar Medical College &amp; Hospital. The study duration was One year (June 2021 to May 2022). 50 patients were included in this study. In our study, all patients [50 (100.0%)] had Lymph node involvement. We Result: showed that, most of the patients had Stage IIIA [25 (50.0%)]. However, Stage IIIB [15 (32.0%)] followed by Stage IIIC [10 (20.0%)] which was statistically signicant (p=.00168).It was found that, all patients [50 (100.0%)] had Anterior Chemotherapy. Our study showed that, most of the patients had Stage IIB after chemotherapy [22 (44.0%)] and it was statistically not signicant (p&lt; .14706) (z=1.4499). In our study, higher number of patients had Down stage Result [35 (70.0%)] followed by Same Result [15 (30.0%)] but this was statistically signicant (p=.00006) (z=4). We showed that, the mean Tumor size of patients was [7.2880± 1.4822 (cm)] and mean % of size reduction of patients was [58.0000± 15.0509]. we Conclusion: conclude that, the change of clinical staging after Neoadjuvant Chemotherapy, Lymph node status after neoadjuvant Chemotherapy

The optimal number of examined lymph nodes for accurate nodal staging and favorable prognosis of oral tongue squamous cell carcinoma

ObjectiveThe study aimed to determine the optimal count of examined lymph nodes (ELN) for accurate assessment of lymph node status and favorable long-term survival in patients with oral tongue squamous cell carcinoma (OTSCC) who received radical resection. MethodsPatients with OTSCC who received radical resection between 2004 and 2015 were enrolled from the Surveillance, Epidemiology, and End Results database (SEER) and were randomly divided into two cohorts. The association of ELN count with nodal migration and overall survival (OS) was analyzed using a multivariate regression model with the adjustment of relevant factors. Locally weighted scatterplot smoothing (LOWESS) and ‘strucchange’ package were adopted to identify the optimal cut points using R. ResultsA total of 2077 patients were included in this study. The optimal cut points of ELN count for accurate nodal staging and favorable OS were 19 and 15, respectively. The probability of detecting positive lymph nodes (PLN) significantly increased in patients with ELN count ≥ 19 in comparison to those with ELN count < 19 (training set, P < 0.001; validation set, P = 0.012). A better postoperative prognosis was observed in patients with ELN count ≥ 15 than those with fewer ELN (training set, P = 0.001, OR: 0.765; validation set, P = 0.016, OR: 0.678). ConclusionThe optimal cut point of ELN count to ensure the accuracy of nodal staging and to achieve a favorable postoperative prognosis were 19 and 15, respectively. The ELN count beyond the cutoff values might improve the accuracy of cancer staging and OS.

Nomograms for Prediction of High-Volume Lymph Node Metastasis in Papillary Thyroid Carcinoma Patients.

The coexistence rate between chronic lymphocytic thyroiditis (CLT) and papillary thyroid carcinoma (PTC) is quite high. Whether CLT influences metastatic lymph nodes remains uncertain. High-volume lymph node metastasis is recommended as an unfavorable pathological feature. We aimed to investigate risk factors for high-volume central lymph node metastasis (CLNM) and lateral lymph node metastasis (LLNM) in PTC patients. Retrospective cohort study. Changzhou First People's Hospital. Clinicopathological characteristics of 1094 PTC patients who underwent surgery in our center from January 2019 to November 2021 were analyzed. The number of metastatic lymph nodes in the central compartment and lateral compartment were lower in the CLT group. We demonstrated that age, BRAF V600E, shape, and the number of foci were risk factors for high-volume CLNM in patients with CLT. For patients without CLT, sex, age, tumor size, number of foci, and margin were risk factors for high-volume CLNM. Tumor size, number of foci, location, and CLNM were all risk factors for high-volume LLNM in patients with or without CLT. Body mass index was only associated with high-volume LLNM in CLT patients. All the above factors were incorporated into nomograms, which showed perfect discriminative ability. Separate predictive systems should be used for CLT and non-CLT patients for a more accurate clinical assessment of lymph node status. Our nomograms of predicting high-volume CLNM and LLNM could facilitate risk-stratified management of PTC recurrence and treatment decisions.

Research Progress in Imaging-based Diagnosis of Benign and Malignant Enlarged Lymph Nodes in Non-small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) can be detected with enlarged lymph nodes on imaging, but their benignity and malignancy are difficult to determine directly, making it difficult to stage the tumor and design radiotherapy target volumes. The clinical diagnosis of malignant lymph nodes is often based on the short diameter of lymph nodes ≥1 cm or the maximum standard uptake value ≥2.5, but the sensitivity and specificity of these criteria are too low to meet the clinical needs. In recent years, many advances have been made in diagnosing benign and malignant lymph nodes using other imaging parameters, and with the development of radiomics, deep learning and other technologies, models of mining the image information of enlarged lymph node regions further improve the diagnostic accuracy. The purpose of this paper is to review recent advances in imaging-based diagnosis of benign and malignant enlarged lymph nodes in NSCLC for more accurate and noninvasive assessment of lymph node status in clinical practice. .

Applying Explainable Machine Learning Models for Detection of Breast Cancer Lymph Node Metastasis in Patients Eligible for Neoadjuvant Treatment.

Due to recent changes in breast cancer treatment strategy, significantly more patients are treated with neoadjuvant systemic therapy (NST). Radiological methods do not precisely determine axillary lymph node status, with up to 30% of patients being misdiagnosed. Hence, supplementary methods for lymph node status assessment are needed. This study aimed to apply and evaluate machine learning models on clinicopathological data, with a focus on patients meeting NST criteria, for lymph node metastasis prediction. From the total breast cancer patient data (n = 8381), 719 patients were identified as eligible for NST. Machine learning models were applied for the NST-criteria group and the total study population. Model explainability was obtained by calculating Shapley values. In the NST-criteria group, random forest achieved the highest performance (AUC: 0.793 [0.713, 0.865]), while in the total study population, XGBoost performed the best (AUC: 0.762 [0.726, 0.795]). Shapley values identified tumor size, Ki-67, and patient age as the most important predictors. Tree-based models achieve a good performance in assessing lymph node status. Such models can lead to more accurate disease stage prediction and consecutively better treatment selection, especially for NST patients where radiological and clinical findings are often the only way of lymph node assessment.