Literature DB >> 27765856

Reliability of PET/CT Shape and Heterogeneity Features in Functional and Morphologic Components of Non-Small Cell Lung Cancer Tumors: A Repeatability Analysis in a Prospective Multicenter Cohort.

Marie-Charlotte Desseroit1,2, Florent Tixier2,3, Wolfgang A Weber4, Barry A Siegel5, Catherine Cheze Le Rest2,3, Dimitris Visvikis6, Mathieu Hatt6.   

Abstract

The main purpose of this study was to assess the reliability of shape and heterogeneity features in both the PET and the low-dose CT components of PET/CT. A secondary objective was to investigate the impact of image quantization.
Methods: A Health Insurance Portability and Accountability Act-compliant secondary analysis of deidentified prospectively acquired PET/CT test-retest datasets of 74 patients from multicenter Merck and American College of Radiology Imaging Network trials was performed. Metabolically active volumes were automatically delineated on PET with a fuzzy locally adaptive bayesian algorithm. Software was used to semiautomatically delineate the anatomic volumes on the low-dose CT component. Two quantization methods were considered: a quantization into a set number of bins (quantization B) and an alternative quantization with bins of fixed width (quantization W). Four shape descriptors, 10 first-order metrics, and 26 textural features were evaluated. Bland-Altman analysis was used to quantify repeatability. Features were subsequently categorized as very reliable, reliable, moderately reliable, or poorly reliable with respect to the corresponding volume variability.
Results: Repeatability was highly variable among features. Numerous metrics were identified as poorly or moderately reliable. Others were reliable or very reliable in both modalities and in all categories (shape and first-, second-, and third-order metrics). Image quantization played a major role in feature repeatability. Features were more reliable in PET with quantization B, whereas quantization W showed better results in CT.
Conclusion: The test-retest repeatability of shape and heterogeneity features in PET and low-dose CT varied greatly among metrics. The level of repeatability also depended strongly on the quantization step, with different optimal choices for each modality. The repeatability of PET and low-dose CT features should be carefully considered when selecting metrics to build multiparametric models.
© 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Entities:  

Keywords:  PET/CT; radiomics; repeatability; texture analysis

Mesh:

Year:  2016        PMID: 27765856      PMCID: PMC5331937          DOI: 10.2967/jnumed.116.180919

Source DB:  PubMed          Journal:  J Nucl Med        ISSN: 0161-5505            Impact factor:   10.057


  35 in total

1.  Impact of Image Reconstruction Settings on Texture Features in 18F-FDG PET.

Authors:  Jianhua Yan; Jason Lim Chu-Shern; Hoi Yin Loi; Lih Kin Khor; Arvind K Sinha; Swee Tian Quek; Ivan W K Tham; David Townsend
Journal:  J Nucl Med       Date:  2015-07-30       Impact factor: 10.057

2.  18F-FDG PET uptake characterization through texture analysis: investigating the complementary nature of heterogeneity and functional tumor volume in a multi-cancer site patient cohort.

Authors:  Mathieu Hatt; Mohamed Majdoub; Martin Vallières; Florent Tixier; Catherine Cheze Le Rest; David Groheux; Elif Hindié; Antoine Martineau; Olivier Pradier; Roland Hustinx; Remy Perdrisot; Remy Guillevin; Issam El Naqa; Dimitris Visvikis
Journal:  J Nucl Med       Date:  2014-12-11       Impact factor: 10.057

Review 3.  Radiomics: extracting more information from medical images using advanced feature analysis.

Authors:  Philippe Lambin; Emmanuel Rios-Velazquez; Ralph Leijenaar; Sara Carvalho; Ruud G P M van Stiphout; Patrick Granton; Catharina M L Zegers; Robert Gillies; Ronald Boellard; André Dekker; Hugo J W L Aerts
Journal:  Eur J Cancer       Date:  2012-01-16       Impact factor: 9.162

4.  Reproducibility and Prognosis of Quantitative Features Extracted from CT Images.

Authors:  Yoganand Balagurunathan; Yuhua Gu; Hua Wang; Virendra Kumar; Olya Grove; Sam Hawkins; Jongphil Kim; Dmitry B Goldgof; Lawrence O Hall; Robert A Gatenby; Robert J Gillies
Journal:  Transl Oncol       Date:  2014-02-01       Impact factor: 4.243

5.  Uncertainty analysis of quantitative imaging features extracted from contrast-enhanced CT in lung tumors.

Authors:  Jinzhong Yang; Lifei Zhang; Xenia J Fave; David V Fried; Francesco C Stingo; Chaan S Ng; Laurence E Court
Journal:  Comput Med Imaging Graph       Date:  2015-12-14       Impact factor: 4.790

6.  Use of registration-based contour propagation in texture analysis for esophageal cancer pathologic response prediction.

Authors:  Stephen S F Yip; Thibaud P Coroller; Nina N Sanford; Elizabeth Huynh; Harvey Mamon; Hugo J W L Aerts; Ross I Berbeco
Journal:  Phys Med Biol       Date:  2016-01-07       Impact factor: 3.609

7.  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

Review 8.  Statistical methods used to test for agreement of medical instruments measuring continuous variables in method comparison studies: a systematic review.

Authors:  Rafdzah Zaki; Awang Bulgiba; Roshidi Ismail; Noor Azina Ismail
Journal:  PLoS One       Date:  2012-05-25       Impact factor: 3.240

9.  Quantitative assessment of the asphericity of pretherapeutic FDG uptake as an independent predictor of outcome in NSCLC.

Authors:  Ivayla Apostolova; Julian Rogasch; Ralph Buchert; Heinz Wertzel; H Jost Achenbach; Jens Schreiber; Sandra Riedel; Christian Furth; Alexandr Lougovski; Georg Schramm; Frank Hofheinz; Holger Amthauer; Ingo G Steffen
Journal:  BMC Cancer       Date:  2014-12-01       Impact factor: 4.430

10.  The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis.

Authors:  Ralph T H Leijenaar; Georgi Nalbantov; Sara Carvalho; Wouter J C van Elmpt; Esther G C Troost; Ronald Boellaard; Hugo J W L Aerts; Robert J Gillies; Philippe Lambin
Journal:  Sci Rep       Date:  2015-08-05       Impact factor: 4.379

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  44 in total

1.  [18]Fluorodeoxyglucose Positron Emission Tomography for the Textural Features of Cervical Cancer Associated with Lymph Node Metastasis and Histological Type.

Authors:  Wei-Chih Shen; Shang-Wen Chen; Ji-An Liang; Te-Chun Hsieh; Kuo-Yang Yen; Chia-Hung Kao
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-04-14       Impact factor: 9.236

2.  Tumor Subregion Evolution-Based Imaging Features to Assess Early Response and Predict Prognosis in Oropharyngeal Cancer.

Authors:  Jia Wu; Michael F Gensheimer; Nasha Zhang; Meiying Guo; Rachel Liang; Carrie Zhang; Nancy Fischbein; Erqi L Pollom; Beth Beadle; Quynh-Thu Le; Ruijiang Li
Journal:  J Nucl Med       Date:  2019-08-16       Impact factor: 10.057

3.  Radiomics in nuclear medicine: robustness, reproducibility, standardization, and how to avoid data analysis traps and replication crisis.

Authors:  Alex Zwanenburg
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-06-25       Impact factor: 9.236

4.  Integrating manual diagnosis into radiomics for reducing the false positive rate of 18F-FDG PET/CT diagnosis in patients with suspected lung cancer.

Authors:  Fei Kang; Wei Mu; Jie Gong; Shengjun Wang; Guoquan Li; Guiyu Li; Wei Qin; Jie Tian; Jing Wang
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-07-18       Impact factor: 9.236

Review 5.  Texture analysis of medical images for radiotherapy applications.

Authors:  Elisa Scalco; Giovanna Rizzo
Journal:  Br J Radiol       Date:  2016-11-25       Impact factor: 3.039

6.  Prognostic value of 18F-FDG PET/CT with texture analysis in patients with rectal cancer treated by surgery.

Authors:  Masatoshi Hotta; Ryogo Minamimoto; Yoshimasa Gohda; Kenta Miwa; Kensuke Otani; Tomomichi Kiyomatsu; Hideaki Yano
Journal:  Ann Nucl Med       Date:  2021-05-04       Impact factor: 2.668

Review 7.  Radiomics in Oncological PET/CT: Clinical Applications.

Authors:  Jeong Won Lee; Sang Mi Lee
Journal:  Nucl Med Mol Imaging       Date:  2017-10-20

8.  Repeatability of [68Ga]DKFZ11-PSMA PET Scans for Detecting Prostate-specific Membrane Antigen-positive Prostate Cancer.

Authors:  Joseph R Osborne; Teja M Kalidindi; Blesida J Punzalan; Kishore Gangangari; Daniel E Spratt; Wolfgang A Weber; Steven M Larson; Naga Vara Kishore Pillarsetty
Journal:  Mol Imaging Biol       Date:  2017-12       Impact factor: 3.488

Review 9.  Clinical applications of textural analysis in non-small cell lung cancer.

Authors:  Iain Phillips; Mazhar Ajaz; Veni Ezhil; Vineet Prakash; Sheaka Alobaidli; Sarah J McQuaid; Christopher South; James Scuffham; Andrew Nisbet; Philip Evans
Journal:  Br J Radiol       Date:  2017-10-27       Impact factor: 3.039

10.  Correlations between metabolic texture features, genetic heterogeneity, and mutation burden in patients with lung cancer.

Authors:  Seung Hwan Moon; Jinho Kim; Je-Gun Joung; Hongui Cha; Woong-Yang Park; Jin Seok Ahn; Myung-Ju Ahn; Keunchil Park; Joon Young Choi; Kyung-Han Lee; Byung-Tae Kim; Se-Hoon Lee
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-08-25       Impact factor: 9.236

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