Literature DB >> 26020832

Prognostic value of computed tomography texture features in non-small cell lung cancers treated with definitive concomitant chemoradiotherapy.

Su Yeon Ahn1, Chang Min Park, Sang Joon Park, Hak Jae Kim, Changhoon Song, Sang Min Lee, Holman Page McAdams, Jin Mo Goo.   

Abstract

OBJECTIVES: The aim of this study was to investigate whether the computed tomography (CT) texture features of primary tumors are associated with the overall survival (OS) of non-small cell lung cancer (NSCLC) patients undergoing definitive concomitant chemoradiotherapy (CCRT).
MATERIALS AND METHODS: In this retrospective study, 98 patients (83 men and 15 women; mean age, 61.9 ± 8.0 years) with unresectable NSCLCs (stage IIIA, 45; stage IIIB, 53) underwent definitive CCRT at our institution from January 2006 to December 2011. Patients were followed up for 3 years or until death. The CT texture parameters of primary tumors were extracted from contrast-enhanced CT images taken before CCRT using an in-house software program. Each texture parameter was dichotomized based on their optimal cutoff values obtained from receiver operating characteristics curve analysis. Three-year OS was compared between the dichotomized subgroups using Kaplan-Meier analysis and the log-rank test. Multivariate Cox regression analysis was performed to determine significant prognostic factors.
RESULTS: The 3-year cumulative survival rate was 0.51. The mean 3-year OS was 24.0 months (95% confidence interval, 21.5-26.6 months). There were no significant differences in 3-year OS according to tumor stage or histologic subtypes. However, entropy (P = 0.030), skewness (P = 0.021), and mean attenuation (P = 0.030) were shown to be significantly associated with 3-year OS. Multivariate Cox regression analysis revealed that higher entropy (adjusted hazard ratio [HR],2.31; P = 0.040), higher skewness (adjusted HR,1.92; P = 0.046), and higher mean attenuation (adjusted HR,1.93; P = 0.028) were independent predictors of decreased 3-year OS.
CONCLUSIONS: Computed tomography texture features have the potential to be used as prognostic biomarkers in unresectable NSCLC patients undergoing definitive CCRT.

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Year:  2015        PMID: 26020832     DOI: 10.1097/RLI.0000000000000174

Source DB:  PubMed          Journal:  Invest Radiol        ISSN: 0020-9996            Impact factor:   6.016


  38 in total

1.  Texture features of colorectal liver metastases on pretreatment contrast-enhanced CT may predict response and prognosis in patients treated with bevacizumab-containing chemotherapy: a pilot study including comparison with standard chemotherapy.

Authors:  Marco Ravanelli; Giorgio Maria Agazzi; Elena Tononcelli; Elisa Roca; Paolo Cabassa; Gianluca Baiocchi; Alfredo Berruti; Roberto Maroldi; Davide Farina
Journal:  Radiol Med       Date:  2019-06-06       Impact factor: 3.469

2.  Quantitative Assessment of Variation in CT Parameters on Texture Features: Pilot Study Using a Nonanatomic Phantom.

Authors:  K Buch; B Li; M M Qureshi; H Kuno; S W Anderson; O Sakai
Journal:  AJNR Am J Neuroradiol       Date:  2017-03-24       Impact factor: 3.825

3.  CT texture analysis of pancreatic cancer.

Authors:  Kumar Sandrasegaran; Yuning Lin; Michael Asare-Sawiri; Tai Taiyini; Mark Tann
Journal:  Eur Radiol       Date:  2018-08-16       Impact factor: 5.315

Review 4.  Pulmonary quantitative CT imaging in focal and diffuse disease: current research and clinical applications.

Authors:  Mario Silva; Gianluca Milanese; Valeria Seletti; Alarico Ariani; Nicola Sverzellati
Journal:  Br J Radiol       Date:  2018-01-12       Impact factor: 3.039

5.  Combined radiomics-clinical model to predict malignancy of vertebral compression fractures on CT.

Authors:  Choong Guen Chee; Min A Yoon; Kyung Won Kim; Yusun Ko; Su Jung Ham; Young Chul Cho; Bumwoo Park; Hye Won Chung
Journal:  Eur Radiol       Date:  2021-03-19       Impact factor: 5.315

6.  Hepatocellular carcinoma: CT texture analysis as a predictor of survival after surgical resection.

Authors:  Lucie Brenet Defour; Sébastien Mulé; Arthur Tenenhaus; Tullio Piardi; Daniele Sommacale; Christine Hoeffel; Gérard Thiéfin
Journal:  Eur Radiol       Date:  2018-08-29       Impact factor: 5.315

7.  Metastatic melanoma: pretreatment contrast-enhanced CT texture parameters as predictive biomarkers of survival in patients treated with pembrolizumab.

Authors:  Carole Durot; Sébastien Mulé; Philippe Soyer; Aude Marchal; Florent Grange; Christine Hoeffel
Journal:  Eur Radiol       Date:  2019-01-15       Impact factor: 5.315

8.  Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer?

Authors:  Xenia Fave; Dennis Mackin; Jinzhong Yang; Joy Zhang; David Fried; Peter Balter; David Followill; Daniel Gomez; A Kyle Jones; Francesco Stingo; Jonas Fontenot; Laurence Court
Journal:  Med Phys       Date:  2015-12       Impact factor: 4.071

9.  Radiomics for Classifying Histological Subtypes of Lung Cancer Based on Multiphasic Contrast-Enhanced Computed Tomography.

Authors:  Linning E; Lin Lu; Li Li; Hao Yang; Lawrence H Schwartz; Binsheng Zhao
Journal:  J Comput Assist Tomogr       Date:  2019 Mar/Apr       Impact factor: 1.826

Review 10.  MRI of the endometrium - from normal appearances to rare pathology.

Authors:  Roxana Pintican; Vlad Bura; Marta Zerunian; Janette Smith; Helen Addley; Susan Freeman; Damiano Caruso; Andrea Laghi; Evis Sala; Mercedes Jimenez-Linan
Journal:  Br J Radiol       Date:  2021-07-08       Impact factor: 3.629

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