Analyzing the post-contrast attenuation of the esophageal wall on routine contrast-enhanced MDCT examination can improve the diagnostic accuracy in response evaluation of the squamous cell esophageal carcinoma to neoadjuvant chemoradiotherapy in comparison with the esophageal wall thickness

2019 ◽  
Vol 44 (5) ◽  
pp. 1722-1733
Author(s):  
Aleksandra Djuric-Stefanovic ◽  
Aleksandra Jankovic ◽  
Dusan Saponjski ◽  
Marjan Micev ◽  
Suzana Stojanovic-Rundic ◽  
...  
Author(s):  
Talha Ahmed Qureshi ◽  
Muhammad Wasif ◽  
Muhammad Sohail Awan ◽  
Adnan yar Muhammad ◽  
Ainulakbar Mughal ◽  
...  

Abstract Objectives: To evaluate the diagnostic accuracy of contrast enhanced CT scan to detect cervical nodal metastasis in oral cavity squamous cell carcinoma keeping final histopathology as gold standard. Methods: Cross sectional study conducted from 1st January 2015 - 31st October 2016. All patients undergoing surgery who had their CT scans done at our centre were included in the study. Diagnostic accuracy of CT scans was calculated using final histopathology as gold standard. All CT scan were reviewed by consultant radiologist. Results: Total 100 patients were reviewed, 70% were female, 55% had buccal and 32% had tongue cancer. 11 cases of T1, 20 cases of T2 , 4 cases of T3 and 21 cases of T4 stages were staged similarly by CT scan and histopathology, the kappa value of38.8%, p value <0.01. 6 cases of N1, 1 case of N2a , 9 cases of N2b, 3 cases of N2c, 1 case of N3 and 29 cases of N0 stages were staged similarly by CT scan and histopathology, with kappa value of 28.1%, p value of  <0.01. Sensitivity, specificity, positive predictive value, negative predictive value and overall diagnostic accuracy were 83%,61%,70.9%,76.3% and 73% respectively. Conclusion: CT scan is useful for preoperative staging of oral cavity squamous cell carcinoma with an overall diagnostic accuracy of 73%, currently there are no superior diagnostic modalities. However, Due to low specificity and negative predictive value elective neck dissection should still be done in a negative CT scan for cervical lymph node metastases. Keywords: Oral Cavity,


2020 ◽  
Vol 11 (9) ◽  
pp. 2618-2629
Author(s):  
Hui‐Jiang Gao ◽  
Yu‐Cheng Wei ◽  
Lei Gong ◽  
Nan Ge ◽  
Bin Han ◽  
...  

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Ninlawan Thammasiri ◽  
Chutimon Thanaboonnipat ◽  
Nan Choisunirachon ◽  
Damri Darawiroj

Abstract Background It is difficult to examine mild to moderate feline intra-thoracic lymphadenopathy via and thoracic radiography. Despite previous information from computed tomographic (CT) images of intra-thoracic lymph nodes, some factors from animals and CT setting were less elucidated. Therefore, this study aimed to investigate the effect of internal factors from animals and external factors from the CT procedure on the feasibility to detect the intra-thoracic lymph nodes. Twenty-four, client-owned, clinically healthy cats were categorized into three groups according to age. They underwent pre- and post-contrast enhanced CT for whole thorax followed by inter-group evaluation and comparison of sternal, cranial mediastinal, and tracheobronchial lymph nodes. Results Post contrast-enhanced CT appearances revealed that intra-thoracic lymph nodes of kittens were invisible, whereas the sternal, cranial mediastinal, and tracheobronchial nodes of cats aged over 7 months old were detected (6/24, 9/24 and 7/24, respectively). Maximum width of these lymph nodes were 3.93 ± 0.74 mm, 4.02 ± 0.65 mm, and 3.51 ± 0.62 mm, respectively. By age, lymph node sizes of these cats were not significantly different. Transverse lymph node width of males was larger than that of females (P = 0.0425). Besides, the detection score of lymph nodes was affected by slice thickness (P < 0.01) and lymph node width (P = 0.0049). Furthermore, an irregular, soft tissue structure, possibly the thymus, was detected in all juvenile cats and three mature cats. Conclusions Despite additional information on intra-thoracic lymph nodes in CT images, which can be used to investigate lymphatic-related abnormalities, age, sex, and slice thickness of CT images must be also considered.


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