Computerized evaluation scheme to detect metastasis in sentinel lymph nodes using contrast-enhanced computed tomography before breast cancer surgery

2018 ◽  
Vol 12 (1) ◽  
pp. 55-60 ◽  
Author(s):  
Hiroshi Ashiba ◽  
Ryohei Nakayama
Keyword(s):  
Breast Cancer ◽  
Computed Tomography ◽  
Lymph Nodes ◽  
Sentinel Lymph Nodes ◽  
Cancer Surgery ◽  
Breast Cancer Surgery ◽  
Evaluation Scheme ◽  
Contrast Enhanced ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

scholarly journals Using Computed Tomography Lymphography for Mapping of Sentinel Lymph Nodes in Patients with Breast Cancer

2021 ◽  
Vol 11 ◽  
pp. 43
Author(s):  
Arimichi Kamata ◽  
Taku Miyamae ◽  
Masaki Koizumi ◽  
Harigane Kohei ◽  
Hideki Sarukawa ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Computed Tomography ◽  
Lymph Node ◽  
Lymph Nodes ◽  
Indigo Carmine ◽  
Sentinel Lymph Nodes ◽  
Breast Cancer Surgery ◽  
Lymph Vessel ◽  
Breast Cancer Patients ◽  
Identification Rate

Objectives: In breast cancer surgery, the combined use of the dye method and radioisotope (RI) method is recommended for identifying sentinel lymph nodes. However, the RI method is difficult to license, expensive, and difficult to introduce. Thus, we introduced computed tomography lymphography (CTLG) and investigated the characteristics and usefulness of CTLG. Material and Methods: Among breast cancer patients who underwent surgery during a 6-year period from January 2013 to December 2018, CTLG was performed on 141 patients with clinically negative lymph node metastasis. These cases were then retrospectively investigated. The number and location of lymph vessel, true sentinel lymph nodes, and the positional relationships with surrounding muscles and blood vessels were confirmed from the constructed 3D images. The actual surgeries were then performed using a dye method with indigo carmine based on images obtained using CTLG. Results: CTLG was able to identify lymph vessels and true sentinel lymph nodes in 131 of the 141 cases (92.91%). There were 97 patients in whom the first true sentinel lymph node reached from the breast was one node, 30 with two nodes, and 4 with three nodes. Moreover, there were three cases in which sentinel lymph nodes were present at Level II. During surgery, sentinel lymph nodes were identified in 131 patients (92.91%) using dye. Conclusion: CTLG has a high identification rate in sentinel lymph nodes, and it is considered a convenient and useful examination method because a lot of information, such as the number and position of sentinel lymph nodes, can be obtained.

Contrast-enhanced computed tomography for diagnosing the intraductal component and small invasive foci of Breast Cancer

Breast Cancer ◽  
2001 ◽  
Vol 8 (1) ◽  
pp. 10-15 ◽  
Author(s):  
Sadako Akashi-Tanaka ◽  
Takashi Fukutomi ◽  
Kunihisa Miyakawa ◽  
Takeshi Nanasawa ◽  
Kaneyuki Matsuo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Computed Tomography ◽  
Contrast Enhanced ◽  
Intraductal Component ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

scholarly journals Prediction of Metastasis in the Axillary Lymph Nodes of Patients With Breast Cancer: A Radiomics Method Based on Contrast-Enhanced Computed Tomography

2021 ◽  
Vol 11 ◽  
Author(s):  
Chunmei Yang ◽  
Jing Dong ◽  
Ziyi Liu ◽  
Qingxi Guo ◽  
Yue Nie ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Computed Tomography ◽  
Classification Accuracy ◽  
Cancer Metastasis ◽  
Support Vector ◽  
Axillary Lymph ◽  
Model Based ◽  
Contrast Enhanced ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

BackgroundThe use of traditional techniques to evaluate breast cancer is restricted by the subjective nature of assessment, variation across radiologists, and limited data. Radiomics may predict axillary lymph node metastasis (ALNM) of breast cancer more accurately.PurposeThe aim was to evaluate the diagnostic performance of a radiomics model based on ALNs themselves that used contrast-enhanced computed tomography (CECT) to detect ALNM of breast cancer.MethodsWe retrospectively enrolled 402 patients with breast cancer confirmed by pathology from January 2016 to October 2019. Three hundred and ninety-six features were extracted for all patients from axial CECT images of 825 ALNs using Artificial Intelligent Kit software (GE Medical Systems, Version V3.1.0.R). Next, the radiomics model was trained, validated, and tested for predicting ALNM in breast cancer by using a support vector machine algorithm. Finally, the performance of the radiomics model was evaluated in terms of its classification accuracy and the value of the area under the curve (AUC).ResultsThe radiomics model yielded the best classification accuracy of 89.1% and the highest AUC of 0.92 (95% CI: 0.91-0.93, p=0.002) for discriminating ALNM in breast cancer in the validation cohorts. In the testing cohorts, the model also demonstrated better performance, with an accuracy of 88.5% and an AUC of 0.94 (95% CI: 0.93-0.95, p=0.005) for predicting ALNM in breast cancer.ConclusionThe radiomics model based on CECT images can be used to predict ALNM in breast cancer and has significant potential in clinical noninvasive diagnosis and in the prediction of breast cancer metastasis.

scholarly journals Contrast Enhanced Computed Tomography Characterization of Fluorodeoxygluocose-Avid Regional and Non-Regional Lymph Nodes in Patients with Suspicion of Metastatic Bladder Cancer

2013 ◽  
Vol 3 ◽  
pp. 66 ◽  
Author(s):  
Muhammad A. Chaudhry ◽  
Richard Wahl ◽  
Lujaien Al-Rubaiey Kadhim ◽  
Atif Zaheer
Keyword(s):  
Computed Tomography ◽  
Bladder Cancer ◽  
Lymph Nodes ◽  
Metastatic Disease ◽  
Metastatic Bladder Cancer ◽  
Contrast Enhanced ◽  
Pet Ct ◽  
Average Size ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

Objective: The objective of this study is to assess if size alone can predict the presence of metastatic disease within lymph nodes seen on contrast enhanced-computed tomography (CE-CT) in patients with suspicion of metastatic bladder cancer and also to evaluate the nodal distribution and morphological characteristics of fluorodeoxygluocose (FDG) avid lymph nodes on CE-CT. Materials and Methods: A retrospective analysis from 2002 to 2009 was performed on patients with suspicion of recurrent disease undergoing restaging FDG-positron emission tomography (PET)/CT. Standardized uptake value (SUVmax) adjusted for lean body mass was recorded in abnormal lymph nodes in the abdominopelvic region. Distribution, size, shape, presence of necrosis and clustering of the FDG-avid lymph nodes was assessed on CE-CT obtained within 4 weeks of the PET/CT. The abnormal nodes were then compared with non-FDG avid lymph nodes on the contralateral side serving as control. Results: A total of 103 lymph nodes were found to be FDG-avid in 14 patients on 17 PET/CT examinations. Overall, mean SULmax was 4.7 (range: 1.6-10.7), which is significantly higher than background of 1.5 (P < 0.05). Regional pelvic lymph nodes were FDG-avid in 93% of patients and metastatic extra-pelvic in 100% of patients. The overall average size of the FDG avid lymph nodes on CE-CT was 11 mm with a third of these measuring 3-8 mm. The average size of FDG-avid lymph nodes was 11 mm in the paraaortic region 13 mm in the common iliac 9 mm in the internal iliac and 13 mm in the external iliac regions. Nearly 88.4% of lymph nodes were round in shape, clustering was present in 68% and necrosis in 7% and average size of lymph nodes that served as controls was 6 mm with reniform morphology in 92% and absence of clustering and necrosis. Conclusion: Overlap in size exists between FDG-avid pathological and non-pathological lymph nodes seen on CE-CT in patients with metastatic bladder cancer. Other characteristic such as abnormal morphology and clustering are useful adjuncts in the evaluation of nodal metastatic disease.

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