Global-Local Attention Network with Multi-task Uncertainty Loss for Abnormal Lymph Node Detection in MR Images

2022 ◽  
pp. 102345
Author(s):  
Shuai Wang ◽  
Yingying Zhu ◽  
Sungwon Lee ◽  
Daniel C. Elton ◽  
Thomas C. Shen ◽  
...  
Keyword(s):  
Lymph Node ◽  
Mr Images ◽  
Attention Network ◽  
Task Uncertainty

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.

scholarly journals Colorectal Carcinoma: Local Tumor Staging and Assessment of Lymph Node Metastasis by High-Resolution MR Imaging in Surgical Specimens

2009 ◽  
Vol 2009 ◽  
pp. 1-10 ◽  
Author(s):  
Ichiro Yamada ◽  
Norio Yoshino ◽  
Akemi Tetsumura ◽  
Satoshi Okabe ◽  
Masayuki Enomoto ◽  
...  
Keyword(s):  
Lymph Node ◽  
High Resolution ◽  
Lymph Node Metastasis ◽  
Colorectal Carcinoma ◽  
Mr Imaging ◽  
Tumor Staging ◽  
Accurate Method ◽  
Mr Images ◽  
Node Metastasis ◽  
Nodal Size

Purpose. To assess the accuracy of high-resolution MR imaging as a means of evaluating mural invasion and lymph node metastasis by colorectal carcinoma in surgical specimens.Materials and Methods. High-resolution T1-weighted and T2-weighted MR images were obtained in 92 surgical specimens containing 96 colorectal carcinomas.Results. T2-weighted MR images clearly depicted the normal colorectal wall as consisting of seven layers. In 90 (94%) of the 96 carcinomas the depth of mural invasion depicted by MR imaging correlated well with the histopathologic stage. Nodal signal intensity on T2-weighted images (93%) and nodal border contour (93%) were more accurate than nodal size (89%) as indicators of lymph node metastasis, and MR imaging provided the highest accuracy (94%–96%) when they were combined.Conclusion. High-resolution MR imaging is a very accurate method for evaluating both mural invasion and lymph node metastasis by colorectal carcinoma in surgical specimens.

Diagnostic accuracy of ultrasound, 18F-FDG-PET/CT, and fused 18F-FDG-PET-MR images with DWI for the detection of cervical lymph node metastases of HNSCC

2013 ◽  
Vol 18 (3) ◽  
pp. 969-978 ◽  
Author(s):  
Philipp Heusch ◽  
Christoph Sproll ◽  
Christian Buchbender ◽  
Elena Rieser ◽  
Jan Terjung ◽  
...  
Keyword(s):  
Lymph Node ◽  
Diagnostic Accuracy ◽  
Fdg Pet ◽  
Cervical Lymph Node ◽  
Mr Images ◽  
Cervical Lymph Node Metastases ◽  
Pet Ct ◽  
Node Metastases ◽  
18F Fdg ◽  
Fdg Pet Ct

scholarly journals Validation of in vivo nodal staging of solid malignancies with USPIO-enhanced MRI: a workflow protocol

2020 ◽  
Author(s):  
Daphne A.J.J. Driessen ◽  
Didi J.J.M. de Gouw ◽  
Rutger C.H. Stijns ◽  
Geke Litjens ◽  
Bas Israël ◽  
...  
Keyword(s):  
Lymph Node ◽  
Lymph Nodes ◽  
Lymph Node Metastases ◽  
Ex Vivo ◽  
Mr Images ◽  
Trial Register ◽  
Enhanced Mri ◽  
Cancer Types ◽  
Node Metastases

Abstract BackgroundIn various cancer types, the first step towards extended metastatic disease is the presence of lymph node metastases. Imaging methods with sufficient diagnostic accuracy are required to personalize treatment. Lymph node metastases can be detected with ultrasmall superparamagnetic iron oxide (USPIO)-enhanced magnetic resonance imaging (MRI), but this method needs validation. Here, a workflow is presented which is designed to compare MRI-visible lymph nodes on a node-to-node basis with histopathology. MethodsIn patients with prostate, rectal, periampullary, esophageal, and head-and-neck cancer, in vivo USPIO-enhanced MRI was performed to detect lymph nodes suspicious for harboring metastases. After lymphadenectomy, but before histopathological assessment, a 7 Tesla (T) preclinical ex vivo MRI of the surgical specimen was performed, and in vivo MR-images were radiologically matched to ex vivo MR images. Lymph nodes were annotated on the ex vivo MRI for an MR-guided pathological examination of the specimens. ResultsMatching lymph nodes of ex vivo MRI to pathology was feasible in all cancer types. The annotated ex vivo MR images enabled a comparison between USPIO-enhanced in vivo MRI and histopathology which allowed for analyses on nodal, or at least on nodal station level.ConclusionsA workflow was developed to validate in vivo USPIO-enhanced MRI with histopathology. Guiding the pathologist towards lymph nodes in the resection specimens during histopathological work-up allowed analysis at nodal level, or at least nodal station level of in vivo suspicious lymph nodes with corresponding histopathology, providing direct information for validation of in vivo USPIO-enhanced MRI detected lymph nodes. Trial registrationVALINODE data is collected from patients undergoing USPIO-enhanced MRI in the clinical setting. Therefore, the trial has not been registered in an online trial register. 7TNANO1 is registered at Clinicaltrials.gov: NCT02751606, April 26 2016 (https://clinicaltrials.gov/ct2/show/NCT02751606). NANO-PANC is registered at Clinicaltrials.gov: NCT04311047, March 17 2020 (https://www.clinicaltrials.gov/ct2/show/NCT04311047). PRECIES is registered in the Dutch Trial Register: NTR6072, August 5 2016 (https://www.trialregister.nl/trial/5797). USPIO-NECK is registered at Clinicaltrials.gov: NCT03817307, January 25 2019 (https://clinicaltrials.gov/ct2/show/NCT03817307).

Scanning electron microscopy of freeze-fractured prescapular lymph node of caprine

1984 ◽  
Vol 42 ◽  
pp. 244-245
Author(s):  
O. Faroon ◽  
F. Al-Bagdadi ◽  
T. G. Snider ◽  
C. Titkemeyer
Keyword(s):  
Lymph Node ◽  
Lymph Nodes ◽  
Lymphatic System ◽  
Three Dimensional ◽  
Meat Products ◽  
The Body ◽  
Morphological Data ◽  
The World ◽  
Cellular Constituent ◽  
Scanning Electron

The lymphatic system is very important in the immunological activities of the body. Clinicians confirm the diagnosis of infectious diseases by palpating the involved cutaneous lymph node for changes in size, heat, and consistency. Clinical pathologists diagnose systemic diseases through biopsies of superficial lymph nodes. In many parts of the world the goat is considered as an important source of milk and meat products.The lymphatic system has been studied extensively. These studies lack precise information on the natural morphology of the lymph nodes and their vascular and cellular constituent. This is due to using improper technique for such studies. A few studies used the SEM, conducted by cutting the lymph node with a blade. The morphological data collected by this method are artificial and do not reflect the normal three dimensional surface of the examined area of the lymph node. SEM has been used to study the lymph vessels and lymph nodes of different animals. No information on the cutaneous lymph nodes of the goat has ever been collected using the scanning electron microscope.

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