PET/CT for Staging and Diagnosis of Lung Cancer

2011 ◽  
pp. 75-88 ◽  
Author(s):  
Sigrid Stroobants
Keyword(s):  
Lung Cancer ◽  
Pet Ct ◽  
Diagnosis Of Lung Cancer

How to choose PET-CT or CT in the diagnosis of lung cancer

2009 ◽  
Author(s):  
T. Jiang ◽  
X. Zheng ◽  
X. Tao ◽  
H. Liu ◽  
S. Liu
Keyword(s):  
Lung Cancer ◽  
Pet Ct ◽  
Diagnosis Of Lung Cancer

scholarly journals The Efficacy of 18F-FDG PET/CT and Superparamagnetic Nanoferric Oxide MRI in the Diagnosis of Lung Cancer and the Value of 18F-FDG PET/CT in the Prediction of Lymph Node Metastasis

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Lan Yao ◽  
Mingfei Zuo ◽  
Na Zhang ◽  
Tian Bai ◽  
Qicheng Huang
Keyword(s):  
Lung Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Fdg Pet ◽  
The Body ◽  
Node Metastasis ◽  
Pet Ct ◽  
18F Fdg ◽  
Diagnosis Of Lung Cancer ◽  
Fdg Pet Ct

In China, lung cancer is one of the leading causes of death among residents. Early diagnosis is of great significance for early interventional treatment and prolonging survival. PET/CT uses positron radiopharmaceuticals to observe the physiological and biochemical changes of the drug and its metabolites in the body and finally diagnoses the disease. 18F-FDG is a commonly used imaging agent, but its short isotopic half-life limits clinical high-throughput testing. This study retrospectively analyzed the imaging material of 100 lung cancer patients pathologically confirmed. Patients with lymph node metastasis were classified into the LM group ( n = 30 cases), and those with no lymph node metastasis were classified into the NLM group ( n = 70 cases). The results showed that MRI of superparamagnetic nanoferric oxide was better than diagnosis of lung cancer by the 18F-FDG PET/CT and had a high predictive power for lymph node metastasis. These turned out to be high-value lung cancer diagnosis of superparamagnetic nanoferric oxide MRI and high-capacity lymph node metastasis prediction of 18F-FDG PET/CT, which were worthy of implementation.

Three-channel intelligent neoplasm classification system for the diagnosis of lung cancer

2019 ◽  
Vol 7 (3) ◽  
pp. 196-207
Author(s):  
Lev Utkin ◽  
Anna Meldo ◽  
Viktor Kryshtapovich ◽  
Viktor Tiulpin ◽  
Ernest Kasimov ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Classification System ◽  
Diagnosis Of Lung Cancer

Enhancing 18F-FDG-PET/CT analysis in lung cancer patients

2015 ◽  
Vol 54 (06) ◽  
pp. 247-254 ◽  
Author(s):  
A. Kapfhammer ◽  
T. Winkens ◽  
T. Lesser ◽  
A. Reissig ◽  
M. Steinert ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Image Fusion ◽  
Chest Wall ◽  
Fdg Pet ◽  
Ct Image ◽  
Lung Cancers ◽  
Pet Ct ◽  
Peripheral Lung ◽  
Fdg Pet Ct ◽  
Tumour Infiltration

SummaryAim: To retrospectively evaluate the feasibility and value of CT-CT image fusion to assess the shift of peripheral lung cancers with/-out chest wall infiltration, comparing computed tomography acquisitions in shallow-breathing (SB-CT) and deep-inspiration breath-hold (DIBH-CT) in patients undergoing FDG-PET/ CT for lung cancer staging. Methods: Image fusion of SB-CT and DIBH-CT was performed with a multimodal workstation used for nuclear medicine fusion imaging. The distance of intrathoracic landmarks and the positional shift of tumours were measured using semitransparent overlay of both CT series. Statistical analyses were adjusted for confounders of tumour infiltration. Cutoff levels were calculated for prediction of no-/infiltration. Results: Lateral pleural recessus and diaphragm showed the largest respiratory excursions. Infiltrating lung cancers showed more limited respiratory shifts than non-infiltrating tumours. A large respiratory tumour-motility accurately predicted non-infiltration. However, the tumour shifts were limited and variable, limiting the accuracy of prediction. Conclusion: This pilot fusion study proved feasible and allowed a simple analysis of the respiratory shifts of peripheral lung tumours using CT-CT image fusion in a PET/CT setting. The calculated cutoffs were useful in predicting the exclusion of chest wall infiltration but did not accurately predict tumour infiltration. This method can provide additional qualitative information in patients with lung cancers with contact to the chest wall but unclear CT evidence of infiltration undergoing PET/CT without the need of additional investigations. Considering the small sample size investigated, further studies are necessary to verify the obtained results.

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