Literature DB >> 26724663

Dynamic contrast-enhanced perfusion area detector CT for non-small cell lung cancer patients: Influence of mathematical models on early prediction capabilities for treatment response and recurrence after chemoradiotherapy.

Yoshiharu Ohno1, Hisanobu Koyama2, Yasuko Fujisawa3, Takeshi Yoshikawa4, Shinichiro Seki2, Naoki Sugihara3, Kazuro Sugimura2.   

Abstract

PURPOSE: To determine the capability and influence of the mathematical method on dynamic contrast-enhanced (CE-) perfusion area detector CT (ADCT) for early prediction of treatment response as well as progression free and overall survival (PFS and OS) of non-small cell lung cancer (NSCLC) patients treated with chemoradiotherapy.
MATERIALS AND METHODS: Sixty-six consecutive stage III NSCLC patients underwent dynamic CE-perfusion ADCT examinations, chemoradiotherapy and follow-up examinations. Response Evaluation Criteria in Solid Tumors (RECIST) criteria were used to divide all patients into responders and non-responders. Differences in each of the indices for all targeted lesions between measurements obtained 2 weeks prior to the first and the third course of chemotherapy were determined for all patients. ROC analyses were employed to determine the capability of perfusion indices as markers for distinguishing RECIST responders from non-responders. To evaluate their capability for early prediction of therapeutic effect, OS of perfusion index-based responders and non-responders were compared by using the Kaplan-Meier method followed by log-rank test.
RESULTS: Area under the curve (Az) for total perfusion by means of the dual-input maximum slope method was significantly larger than that of pulmonary arterial perfusion using the same method (p=0.007) and of perfusion with the single-input maximum slope method (p=0.007). Mean OS demonstrated significantly difference between responder- and non-responder groups for total perfusion (p=0.02).
CONCLUSION: Mathematical models have significant influence on assessment for early prediction of treatment response, disease progression and overall survival using dynamic CE-perfusion ADCT for NSCLC patients treated with chemoradiotherapy.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  CT; Chemoradiotherapy; Non-small cell lung cancer; Perfusion; Therapeutic effect

Mesh:

Substances:

Year:  2015        PMID: 26724663     DOI: 10.1016/j.ejrad.2015.11.009

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  12 in total

Review 1.  Contrast-enhanced CT- and MRI-based perfusion assessment for pulmonary diseases: basics and clinical applications.

Authors:  Yoshiharu Ohno; Hisanobu Koyama; Ho Yun Lee; Sachiko Miura; Takeshi Yoshikawa; Kazuro Sugimura
Journal:  Diagn Interv Radiol       Date:  2016 Sep-Oct       Impact factor: 2.630

Review 2.  Pulmonary Functional Imaging: Part 1-State-of-the-Art Technical and Physiologic Underpinnings.

Authors:  Yoshiharu Ohno; Joon Beom Seo; Grace Parraga; Kyung Soo Lee; Warren B Gefter; Sean B Fain; Mark L Schiebler; Hiroto Hatabu
Journal:  Radiology       Date:  2021-04-06       Impact factor: 29.146

3.  Multislice Analysis of Blood Flow Values in CT Perfusion Studies of Lung Cancer.

Authors:  Silvia Malavasi; Domenico Barone; Giampaolo Gavelli; Alessandro Bevilacqua
Journal:  Biomed Res Int       Date:  2017-01-10       Impact factor: 3.411

4.  Intra-observer and inter-observer agreements for the measurement of dual-input whole tumor computed tomography perfusion in patients with lung cancer: Influences of the size and inner-air density of tumors.

Authors:  Qingle Wang; Zhiyong Zhang; Fei Shan; Yuxin Shi; Wei Xing; Liangrong Shi; Xingwei Zhang
Journal:  Thorac Cancer       Date:  2017-06-06       Impact factor: 3.500

Review 5.  [Quantitative Imaging Assessment of Tumor Response to Chemoradiation 
in Lung Cancer].

Authors:  Yuxin Jiao; Yanping Ren; Xiangpeng Zheng
Journal:  Zhongguo Fei Ai Za Zhi       Date:  2017-06-20

6.  Simulation analysis for tumor radiotherapy based on three-component mathematical models.

Authors:  Wen-Song Hong; Gang-Qing Zhang
Journal:  J Appl Clin Med Phys       Date:  2019-03       Impact factor: 2.102

7.  Dual-input tracer kinetic modeling of dynamic contrast-enhanced MRI in thoracic malignancies.

Authors:  Sang Ho Lee; Andreas Rimner; Joseph O Deasy; Margie A Hunt; Neelam Tyagi
Journal:  J Appl Clin Med Phys       Date:  2019-10-11       Impact factor: 2.102

8.  Dynamic Contrast-enhanced Area-detector CT vs Dynamic Contrast-enhanced Perfusion MRI vs FDG-PET/CT: Comparison of Utility for Quantitative Therapeutic Outcome Prediction for NSCLC Patients Undergoing Chemoradiotherapy.

Authors:  Shinichiro Seki; Yasuko Fujisawa; Masao Yui; Yuji Kishida; Hisanobu Koyama; Shigeharu Ohyu; Naoki Sugihara; Takeshi Yoshikawa; Yoshiharu Ohno
Journal:  Magn Reson Med Sci       Date:  2019-03-18       Impact factor: 2.471

9.  Useful Parameters in Dynamic Contrast-enhanced Ultrasonography for Identifying Early Response to Chemotherapy in a Rat Liver Tumor Model.

Authors:  Ryosuke Taiji; Hideyuki Nishiofuku; Toshihiro Tanaka; Kiyoyuki Minamiguchi; Yasushi Fukuoka; Natsuhiko Saito; Hidehiko Taguchi; Takeshi Matsumoto; Nagaaki Marugami; Toshiko Hirai; Kimihiko Kichikawa
Journal:  J Clin Imaging Sci       Date:  2021-03-15

10.  18F-FDG PET and DCE kinetic modeling and their correlations in primary NSCLC: first voxel-wise correlative analysis of human simultaneous [18F]FDG PET-MRI data.

Authors:  Florent L Besson; Brice Fernandez; Sylvain Faure; Olaf Mercier; Andrei Seferian; Xavier Mignard; Sacha Mussot; Cecile le Pechoux; Caroline Caramella; Angela Botticella; Antonin Levy; Florence Parent; Sophie Bulifon; David Montani; Delphine Mitilian; Elie Fadel; David Planchard; Benjamin Besse; Maria-Rosa Ghigna-Bellinzoni; Claude Comtat; Vincent Lebon; Emmanuel Durand
Journal:  EJNMMI Res       Date:  2020-07-30       Impact factor: 3.138

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