scholarly journals Analysis of lymph nodes metastasis in hypopharyngeal squamous cell carcinoma based on contrast‐enhanced computed tomography imaging

2021 ◽  
Vol 5 (4) ◽  
pp. 237-243
Author(s):  
Dongqing Wang ◽  
Shuguang Zhang ◽  
Jin Xu ◽  
Limin Zhai ◽  
Baosheng Li
Keyword(s):  
Computed Tomography ◽  
Squamous Cell Carcinoma ◽  
Lymph Nodes ◽  
Cell Carcinoma ◽  
Computed Tomography Imaging ◽  
Tomography Imaging ◽  
Lymph Nodes Metastasis ◽  
Contrast Enhanced ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

scholarly journals Deep Learning for the Preoperative Diagnosis of Metastatic Cervical Lymph Nodes on Contrast-Enhanced Computed ToMography in Patients with Oral Squamous Cell Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 600
Author(s):  
Hayato Tomita ◽  
Tsuneo Yamashiro ◽  
Joichi Heianna ◽  
Toshiyuki Nakasone ◽  
Tatsuaki Kobayashi ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Squamous Cell Carcinoma ◽  
Deep Learning ◽  
Oral Squamous Cell Carcinoma ◽  
Lymph Nodes ◽  
Cell Carcinoma ◽  
Cervical Lymph Nodes ◽  
Contrast Enhanced ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

We investigated the value of deep learning (DL) in differentiating between benign and metastatic cervical lymph nodes (LNs) using pretreatment contrast-enhanced computed tomography (CT). This retrospective study analyzed 86 metastatic and 234 benign (non-metastatic) cervical LNs at levels I–V in 39 patients with oral squamous cell carcinoma (OSCC) who underwent preoperative CT and neck dissection. LNs were randomly divided into training (70%), validation (10%), and test (20%) sets. For the validation and test sets, cervical LNs at levels I–II were evaluated. Convolutional neural network analysis was performed using Xception architecture. Two radiologists evaluated the possibility of metastasis to cervical LNs using a 4-point scale. The area under the curve of the DL model and the radiologists’ assessments were calculated and compared at levels I–II, I, and II. In the test set, the area under the curves at levels I–II (0.898) and II (0.967) were significantly higher than those of each reader (both, p < 0.05). DL analysis of pretreatment contrast-enhanced CT can help classify cervical LNs in patients with OSCC with better diagnostic performance than radiologists’ assessments alone. DL may be a valuable diagnostic tool for differentiating between benign and metastatic cervical LNs.

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