scholarly journals Transverse colon invasion from intrahepatic cholangiocarcinoma with lymph node metastasis in the regional mesocolon: a case report

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Kenta Aso ◽  
Kyoji Ito ◽  
Nobuyuki Takemura ◽  
Fuyuki Inagaki ◽  
Fuminori Mihara ◽  
...  
Keyword(s):  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Lymph Nodes ◽  
Intrahepatic Cholangiocarcinoma ◽  
Transverse Colon ◽  
Gallbladder Wall ◽  
Right Hemicolectomy ◽  
R0 Resection ◽  
Transverse Mesocolon ◽  
Node Metastasis

Abstract Background Intrahepatic cholangiocarcinoma (ICC) is an aggressive cancer with high frequency of extrahepatic metastasis at diagnosis. However, there have been very few reports of direct invasion to transverse mesocolon with lymph node metastasis in the regional mesocolon. Case presentation A 71-year-old man presented to our hospital with anorexia and weight loss. Abdominal computed tomography (CT) revealed enlarged gallbladder wall with intrahepatic tumor extended from the gallbladder. The transverse colon was located adjacent to the gallbladder and its wall was thickened, indicating tumor invasion. Some enlarged lymph nodes were observed in the transverse mesocolon, suggesting metastatic or inflammatory lymph node swelling. Percutaneous liver biopsy detected poorly differentiated adenocarcinoma. After confirming the absence of remote metastasis and peritoneal dissemination, surgical resection including right hepatectomy and right hemicolectomy was performed. The pathological diagnosis was adenosquamous carcinoma of the liver and lymph node metastasis in the transverse mesocolon. The surgical margins were negative and R0 resection was achieved. Although adjuvant chemotherapy was administered, follow-up CT detected multiple metastases to the lung 4 months after surgery. The patient died 12 months after the operation. Conclusions Direct colon invasion from ICC may cause lymph node metastasis in the regional mesocolon. Careful assessment is necessary for the diagnosis of enlarged lymph nodes in ICC with direct colon invasion.

scholarly journals Dedicated Axillary MRI-Based Radiomics Analysis for the Prediction of Axillary Lymph Node Metastasis in Breast Cancer

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 757
Author(s):  
Sanaz Samiei ◽  
Renée W. Y. Granzier ◽  
Abdalla Ibrahim ◽  
Sergey Primakov ◽  
Marc B. I. Lobbes ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Lymph Nodes ◽  
Axillary Lymph Node ◽  
Axillary Lymph Node Metastasis ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Mr Images ◽  
Node Metastasis

Radiomics features may contribute to increased diagnostic performance of MRI in the prediction of axillary lymph node metastasis. The objective of the study was to predict preoperative axillary lymph node metastasis in breast cancer using clinical models and radiomics models based on T2-weighted (T2W) dedicated axillary MRI features with node-by-node analysis. From August 2012 until October 2014, all women who had undergone dedicated axillary 3.0T T2W MRI, followed by axillary surgery, were retrospectively identified, and available clinical data were collected. All axillary lymph nodes were manually delineated on the T2W MR images, and quantitative radiomics features were extracted from the delineated regions. Data were partitioned patient-wise to train 100 models using different splits for the training and validation cohorts to account for multiple lymph nodes per patient and class imbalance. Features were selected in the training cohorts using recursive feature elimination with repeated 5-fold cross-validation, followed by the development of random forest models. The performance of the models was assessed using the area under the curve (AUC). A total of 75 women (median age, 61 years; interquartile range, 51–68 years) with 511 axillary lymph nodes were included. On final pathology, 36 (7%) of the lymph nodes had metastasis. A total of 105 original radiomics features were extracted from the T2W MR images. Each cohort split resulted in a different number of lymph nodes in the training cohorts and a different set of selected features. Performance of the 100 clinical and radiomics models showed a wide range of AUC values between 0.41–0.74 and 0.48–0.89 in the training cohorts, respectively, and between 0.30–0.98 and 0.37–0.99 in the validation cohorts, respectively. With these results, it was not possible to obtain a final prediction model. Clinical characteristics and dedicated axillary MRI-based radiomics with node-by-node analysis did not contribute to the prediction of axillary lymph node metastasis in breast cancer based on data where variations in acquisition and reconstruction parameters were not addressed.

Peritumoral lymph nodes in pancreatic cancer revisited; is it truly equivalent to lymph node metastasis?

2021 ◽  
Author(s):  
Yoonhyeong Byun ◽  
Kyoung‐Bun Lee ◽  
Jin‐Young Jang ◽  
Youngmin Han ◽  
Yoo Jin Choi ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Lymph Nodes ◽  
Node Metastasis

scholarly journals Intrahepatic cholangiocarcinoma patients without indications of lymph node metastasis not benefit from lymph node dissection

Oncotarget ◽  
2017 ◽  
Vol 8 (69) ◽  
pp. 113817-113827 ◽  
Author(s):  
Jie Hu ◽  
Fei-Yu Chen ◽  
Kai-Qian Zhou ◽  
Cheng Zhou ◽  
Ya Cao ◽  
...  
Keyword(s):  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Lymph Node Dissection ◽  
Intrahepatic Cholangiocarcinoma ◽  
Node Dissection ◽  
Node Metastasis

scholarly journals Development and Validation a Nomogram for Predicting the Third Station Lymph Node Metastasis in Early Gastric Cancer

2021 ◽  
Author(s):  
Xiaoxiao Wang ◽  
Cong Li ◽  
Mengjie Fang ◽  
Liwen Zhang ◽  
Lianzhen Zhong ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gastric Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Lymph Nodes ◽  
Validation Cohort ◽  
Predictive Accuracy ◽  
Clinical Risk Factors ◽  
Node Metastasis ◽  
Clinical Risk

Abstract Background:This study aimed to evaluate the value of radiomic nomogram in predicting lymph node metastasis in T1-2 gastric cancer according to the No. 3 station lymph nodes.Methods:A total of 159 T1-2 gastric cancer (GC) patients who had undergone surgery with lymphadenectomy between March 2012 and November 2017 were retrospectively collected and divided into a primary cohort (n = 80) and a validation cohort (n = 79). Radiomic features were extracted from both tumor region and No. 3 station lymph nodes (LN) based on computed tomography (CT) images per patient. Then, key features were selected using minimum redundancy maximum relevance algorithm and fed into two radiomic signatures, respectively. Meanwhile, the predictive performance of clinical risk factors was studied. Finally, a nomogram was built by merging radiomic signatures and clinical risk factors and evaluated by the area under the receiver operator characteristic curve (AUC) as well as decision curve.Results: Two radiomic signatures, reflecting phenotypes of the tumor and LN respectively, were significantly associated with LN metastasis. A nomogram incorporating two radiomic signatures and CT-reported LN metastasis status showed good discrimination of LN metastasis in both the primary cohort (AUC: 0.915; 95% confidence interval [CI]: 0.832-0.998) and validation cohort (AUC: 0.908; 95%CI: 0.814-1.000). The decision curve also indicated its potential clinical usefulness.Conclusions:The nomogram received favorable predictive accuracy in predicting No.3 station LN metastasis in T1-2 GC, and could assist the choice of therapy.

scholarly journals Genomic Heterogeneity and Clonal Evolution in Gastroesophageal Junction Cancer Revealed by Single Cell DNA Sequencing

2021 ◽  
Vol 11 ◽  
Author(s):  
Qingke Duan ◽  
Chao Tang ◽  
Zhao Ma ◽  
Chuangui Chen ◽  
Xiaobin Shang ◽  
...  
Keyword(s):  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Lymph Nodes ◽  
Dna Sequencing ◽  
Single Cell ◽  
Single Cells ◽  
Clonal Evolution ◽  
Gastroesophageal Junction ◽  
Common Mutation ◽  
Node Metastasis

Gastroesophageal junction (GEJ) cancer is a tumor that occurs at the junction of stomach and esophagus anatomically. GEJ cancer frequently metastasizes to lymph nodes, however the heterogeneity and clonal evolution process are unclear. This study is the first of this kind to use single cell DNA sequencing to determine genomic variations and clonal evolution related to lymph node metastasis. Multiple Annealing and Looping Based Amplification Cycles (MALBAC) and bulk exome sequencing were performed to detect single cell copy number variations (CNVs) and single nucleotide variations (SNVs) respectively. Four GEJ cancer patients were enrolled with two (Pt.3, Pt.4) having metastatic lymph nodes. The most common mutation we found happened in the TTN gene, which was reported to be related with the tumor mutation burden in cancers. Significant intra-patient heterogeneity in SNVs and CNVs were found. We identified the SNV subclonal architecture in each tumor. To study the heterogeneity of CNVs, the single cells were sequenced. The number of subclones in the primary tumor was larger than that in lymph nodes, indicating the heterogeneity of primary site was higher. We observed two patterns of multi-station lymph node metastasis: one was skip metastasis and the other was to follow the lymphatic drainage. Taken together, our single cell genomic analysis has revealed the heterogeneity and clonal evolution in GEJ cancer.

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