scholarly journals Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features

IEEE Access ◽  
2014 ◽  
Vol 2 ◽  
pp. 1418-1426 ◽  
Author(s):  
Samuel H. Hawkins ◽  
John N. Korecki ◽  
Yoganand Balagurunathan ◽  
Yuhua Gu ◽  
Virendra Kumar ◽  
...  
2013 ◽  
Vol 40 (12) ◽  
pp. 121916 ◽  
Author(s):  
Luke A. Hunter ◽  
Shane Krafft ◽  
Francesco Stingo ◽  
Haesun Choi ◽  
Mary K. Martel ◽  
...  

2019 ◽  
Vol 9 (6) ◽  
pp. 1131-1137
Author(s):  
Xiaoteng Lu ◽  
Jing Gong ◽  
Shengdong Nie

This study aims to investigate the prognosis factors of non-small cell lung cancer (NSCLC) based on CT image features and develop a new quantitative image feature prognosis approach using CT images. Firstly, lung tumors were segmented and images features were extracted. Secondly, the Kaplan-Meier method was used to have a univariate survival analysis. A multiple survival analysis was carried out with the method of COX regression model. Thirdly, SMOTE algorithm was took to make the feature data balanced. Finally, classifiers based on WEKA were established to test the prognosis ability of independent prognosis factors. Univariate analysis results reflected that six features had significant influence on patients' prognosis. After multivariate analysis, angular second moment, srhge and volume were significantly related to the survival situation of NSCLC patients (P < 0.05). According to the results of classifiers, these three features could make a well prognosis on the NSCLC. The best classification accuracy was 78.4%. The results of our study suggested that angular second moment, srhge and volume were high potential independent prognosis factors of NSCLC.


2021 ◽  
Vol 9 (3) ◽  
pp. e002262
Author(s):  
Justin Ferdinandus ◽  
Martin Metzenmacher ◽  
Lukas Kessler ◽  
Lale Umutlu ◽  
Clemens Aigner ◽  
...  

IntroductionImmunotherapy is the new standard of care in advanced nonsmall cell lung cancer (NSCLC). Recently published data show that treatment discontinuation after 12 months of nivolumab treatment is associated with shorter survival. Therefore, the ideal duration of immunotherapy remains unclear, and finding markers of beneficial outcomes is of great importance. Here, we determine the proportion of complete metabolic responses (CMR) in patients who have not progressed after 24 months of immunotherapy.MethodsThis is a retrospective analysis of 45 patients with positron emission tomography using 2-[18F]fluoro-2-deoxy-D-glucose imaging for assessment of residual metabolic activity after at least 24 months. CMR was defined as uptake in tumor lesions below background levels, using mediastinum as a reference. ResultsOut of 45 patients, 29 patients had a CMR (64%). CMR was observed more frequently in non-first-line patients. Patients with CMR were younger (median 65.7 vs 75.5, p=0.03). Fourteen patients with CMR have discontinued therapy and have not progressed until time of analysis; however, median follow-up was only 5.6 (range 0.8–17.0) months.ConclusionAfter a minimum of 24 months of palliative immunotherapy for NSCLC, CMR occurred in almost two thirds of patients. Potentially, achievement of CMR might identify patients, for whom palliative immunotherapy may be safely discontinued.


2003 ◽  
Vol 106 (6) ◽  
pp. 913-918 ◽  
Author(s):  
Sonata Jarmalaite ◽  
Annamaria Kannio ◽  
Sisko Anttila ◽  
Juozas R. Lazutka ◽  
Kirsti Husgafvel-Pursiainen

2014 ◽  
Vol 26 (1) ◽  
pp. 3-17 ◽  
Author(s):  
Juan P. Cata ◽  
Vijaya Gottumukkala ◽  
Dilip Thakar ◽  
Dinesh Keerty ◽  
Rodolfo Gebhardt ◽  
...  

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