Literature DB >> 34172602

Reliability of Quantitative 18F-FDG PET/CT Imaging Biomarkers for Classifying Early Response to Chemoradiotherapy in Patients With Locally Advanced Non-Small Cell Lung Cancer.

Kevin P Horn1, Hannah M T Thomas2, Hubert J Vesselle1, Paul E Kinahan1, Robert S Miyaoka1, Ramesh Rengan2, Jing Zeng2, Stephen R Bowen.   

Abstract

PURPOSE OF THE REPORT: We evaluated the reliability of 18F-FDG PET imaging biomarkers to classify early response status across observers, scanners, and reconstruction algorithms in support of biologically adaptive radiation therapy for locally advanced non-small cell lung cancer. PATIENTS AND METHODS: Thirty-one patients with unresectable locally advanced non-small cell lung cancer were prospectively enrolled on a phase 2 trial (NCT02773238) and underwent 18F-FDG PET on GE Discovery STE (DSTE) or GE Discovery MI (DMI) PET/CT systems at baseline and during the third week external beam radiation therapy regimens. All PET scans were reconstructed using OSEM; GE-DMI scans were also reconstructed with BSREM-TOF (block sequential regularized expectation maximization reconstruction algorithm incorporating time of flight). Primary tumors were contoured by 3 observers using semiautomatic gradient-based segmentation. SUVmax, SUVmean, SUVpeak, MTV (metabolic tumor volume), and total lesion glycolysis were correlated with midtherapy multidisciplinary clinical response assessment. Dice similarity of contours and response classification areas under the curve were evaluated across observers, scanners, and reconstruction algorithms. LASSO logistic regression models were trained on DSTE PET patient data and independently tested on DMI PET patient data.
RESULTS: Interobserver variability of PET contours was low for both OSEM and BSREM-TOF reconstructions; intraobserver variability between reconstructions was slightly higher. ΔSUVpeak was the most robust response predictor across observers and image reconstructions. LASSO models consistently selected ΔSUVpeak and ΔMTV as response predictors. Response classification models achieved high cross-validated performance on the DSTE cohort and more variable testing performance on the DMI cohort.
CONCLUSIONS: The variability FDG PET lesion contours and imaging biomarkers was relatively low across observers, scanners, and reconstructions. Objective midtreatment PET response assessment may lead to improved precision of biologically adaptive radiation therapy.
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

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Year:  2021        PMID: 34172602      PMCID: PMC8490284          DOI: 10.1097/RLU.0000000000003774

Source DB:  PubMed          Journal:  Clin Nucl Med        ISSN: 0363-9762            Impact factor:   10.782


  34 in total

1.  Impact of different image reconstructions on PET quantification in non-small cell lung cancer: a comparison of adenocarcinoma and squamous cell carcinoma.

Authors:  Michael Messerli; Fotis Kotasidis; Irene A Burger; Daniela A Ferraro; Urs J Muehlematter; Corina Weyermann; David Kenkel; Gustav K von Schulthess; Philipp A Kaufmann; Martin W Huellner
Journal:  Br J Radiol       Date:  2019-02-26       Impact factor: 3.039

2.  Voxel Forecast for Precision Oncology: Predicting Spatially Variant and Multiscale Cancer Therapy Response on Longitudinal Quantitative Molecular Imaging.

Authors:  Stephen R Bowen; Daniel S Hippe; W Art Chaovalitwongse; Chunyan Duan; Phawis Thammasorn; Xiao Liu; Robert S Miyaoka; Hubert J Vesselle; Paul E Kinahan; Ramesh Rengan; Jing Zeng
Journal:  Clin Cancer Res       Date:  2019-05-29       Impact factor: 12.531

3.  Mid-radiotherapy PET/CT for prognostication and detection of early progression in patients with stage III non-small cell lung cancer.

Authors:  Michael F Gensheimer; Julian C Hong; Christine Chang-Halpenny; Hui Zhu; Neville C W Eclov; Jacqueline To; James D Murphy; Heather A Wakelee; Joel W Neal; Quynh-Thu Le; Wendy Y Hara; Andrew Quon; Peter G Maxim; Edward E Graves; Michael R Olson; Maximilian Diehn; Billy W Loo
Journal:  Radiother Oncol       Date:  2017-08-19       Impact factor: 6.280

4.  Response assessment using 18F-FDG PET early in the course of radiotherapy correlates with survival in advanced-stage non-small cell lung cancer.

Authors:  Wouter van Elmpt; Michel Ollers; Anne-Marie C Dingemans; Philippe Lambin; Dirk De Ruysscher
Journal:  J Nucl Med       Date:  2012-08-09       Impact factor: 10.057

5.  Final results of phase III trial in regionally advanced unresectable non-small cell lung cancer: Radiation Therapy Oncology Group, Eastern Cooperative Oncology Group, and Southwest Oncology Group.

Authors:  W Sause; P Kolesar; I V Taylor S; D Johnson; R Livingston; R Komaki; B Emami; W Curran; R Byhardt; A R Dar; A Turrisi
Journal:  Chest       Date:  2000-02       Impact factor: 9.410

6.  High-dose radiation improved local tumor control and overall survival in patients with inoperable/unresectable non-small-cell lung cancer: long-term results of a radiation dose escalation study.

Authors:  Feng-Ming Kong; Randall K Ten Haken; Matthew J Schipper; Molly A Sullivan; Ming Chen; Carlos Lopez; Gregory P Kalemkerian; James A Hayman
Journal:  Int J Radiat Oncol Biol Phys       Date:  2005-10-01       Impact factor: 7.038

7.  Pre-treatment FDG-PET predicts the site of in-field progression following concurrent chemoradiotherapy for stage III non-small cell lung cancer.

Authors:  Nitin Ohri; Bilal Piperdi; Madhur K Garg; William R Bodner; Rasim Gucalp; Roman Perez-Soler; Steven M Keller; Chandan Guha
Journal:  Lung Cancer       Date:  2014-11-06       Impact factor: 5.705

Review 8.  From RECIST to PERCIST: Evolving Considerations for PET response criteria in solid tumors.

Authors:  Richard L Wahl; Heather Jacene; Yvette Kasamon; Martin A Lodge
Journal:  J Nucl Med       Date:  2009-05       Impact factor: 10.057

9.  Effects of concomitant cisplatin and radiotherapy on inoperable non-small-cell lung cancer.

Authors:  C Schaake-Koning; W van den Bogaert; O Dalesio; J Festen; J Hoogenhout; P van Houtte; A Kirkpatrick; M Koolen; B Maat; A Nijs
Journal:  N Engl J Med       Date:  1992-02-20       Impact factor: 91.245

10.  QIN Benchmarks for Clinical Translation of Quantitative Imaging Tools.

Authors:  Keyvan Farahani; Darrell Tata; Robert J Nordstrom
Journal:  Tomography       Date:  2019-03
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  3 in total

1.  Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer.

Authors:  Parisa Forouzannezhad; Dominic Maes; Daniel S Hippe; Phawis Thammasorn; Reza Iranzad; Jie Han; Chunyan Duan; Xiao Liu; Shouyi Wang; W Art Chaovalitwongse; Jing Zeng; Stephen R Bowen
Journal:  Cancers (Basel)       Date:  2022-02-26       Impact factor: 6.575

Review 2.  Adding predictive and diagnostic values of pulmonary ground-glass nodules on lung cancer via novel non-invasive tests.

Authors:  Yizong Ding; Chunming He; Xiaojing Zhao; Song Xue; Jian Tang
Journal:  Front Med (Lausanne)       Date:  2022-08-18

3.  Radiation and immune checkpoint inhibitor-mediated pneumonitis risk stratification in patients with locally advanced non-small cell lung cancer: role of functional lung radiomics?

Authors:  Hannah M T Thomas; Daniel S Hippe; Parisa Forouzannezhad; Balu Krishna Sasidharan; Paul E Kinahan; Robert S Miyaoka; Hubert J Vesselle; Ramesh Rengan; Jing Zeng; Stephen R Bowen
Journal:  Discov Oncol       Date:  2022-09-01
  3 in total

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