Literature DB >> 24752672

Textural Parameters of Tumor Heterogeneity in ¹⁸F-FDG PET/CT for Therapy Response Assessment and Prognosis in Patients with Locally Advanced Rectal Cancer.

Ralph A Bundschuh1, Julia Dinges2, Larissa Neumann2, Martin Seyfried2, Norbert Zsótér3, Laszló Papp3, Robert Rosenberg4, Karen Becker5, Sabrina T Astner6, Martin Henninger7, Ken Herrmann8, Sibylle I Ziegler2, Markus Schwaiger2, Markus Essler9.   

Abstract

UNLABELLED: (18)F-FDG PET/CT is effective in the assessment of therapy response. Changes in glucose uptake or tumor size are used as a measure. Tumor heterogeneity was found to be a promising predictive and prognostic factor. We investigated textural parameters for their predictive and prognostic capability in patients with rectal cancer using histopathology as the gold standard. In addition, a comparison to clinical outcome was performed.
METHODS: Twenty-seven patients with rectal cancer underwent (18)F-FDG PET/CT before, 2 wk after the start, and 4 wk after the completion of neoadjuvant chemoradiotherapy. In all PET/CT scans, conventional parameters (tumor volume, diameter, maximum and mean standardized uptake values, and total lesion glycolysis [TLG]) and textural parameters (coefficient of variation [COV], skewness, and kurtosis) were determined to assess tumor heterogeneity. Values on pretherapeutic PET/CT as well as changes early in the course of therapy and after therapy were compared with histopathologic response. In addition, the prognostic value was assessed by correlation with time to progression and survival time.
RESULTS: The COV showed a statistically significant capability to assess histopathologic response early in therapy (sensitivity, 68%; specificity, 88%) and after therapy (79% and 88%, respectively). Thereby, the COV had a higher area under the curve in receiver-operating-characteristic analysis than did any analyzed conventional parameter for early and late response assessment. The COV showed a statistically significant capability to evaluate disease progression and to predict survival, although the latter was not statistically significant.
CONCLUSION: Tumor heterogeneity assessed by the COV, being superior to the investigated conventional parameters, is an important predictive factor in patients with rectal cancer. Furthermore, it can provide prognostic information. Therefore, its application is an important step for personalized treatment of rectal cancer.
© 2014 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Entities:  

Keywords:  coefficient of variation; prognostic parameter; rectal cancer; therapy monitoring; tumor heterogeneity

Mesh:

Substances:

Year:  2014        PMID: 24752672     DOI: 10.2967/jnumed.113.127340

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


  62 in total

1.  Quantitative radiomics: impact of stochastic effects on textural feature analysis implies the need for standards.

Authors:  Matthew J Nyflot; Fei Yang; Darrin Byrd; Stephen R Bowen; George A Sandison; Paul E Kinahan
Journal:  J Med Imaging (Bellingham)       Date:  2015-08-05

2.  Preoperative prediction of regional lymph node metastasis of colorectal cancer based on 18F-FDG PET/CT and machine learning.

Authors:  Jiahong He; Quanshi Wang; Yin Zhang; Hubing Wu; Yongsheng Zhou; Shuangquan Zhao
Journal:  Ann Nucl Med       Date:  2021-03-18       Impact factor: 2.668

3.  A pilot study for texture analysis of 18F-FDG and 18F-FLT-PET/CT to predict tumor recurrence of patients with colorectal cancer who received surgery.

Authors:  Masatoyo Nakajo; Yoriko Kajiya; Atsushi Tani; Megumi Jinguji; Masayuki Nakajo; Masaki Kitazono; Takashi Yoshiura
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-08-03       Impact factor: 9.236

Review 4.  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

5.  Correlation between tumour characteristics, SUV measurements, metabolic tumour volume, TLG and textural features assessed with 18F-FDG PET in a large cohort of oestrogen receptor-positive breast cancer patients.

Authors:  Charles Lemarignier; Antoine Martineau; Luis Teixeira; Laetitia Vercellino; Marc Espié; Pascal Merlet; David Groheux
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-02-10       Impact factor: 9.236

Review 6.  Immune Checkpoint Imaging in Oncology: A Game Changer Toward Personalized Immunotherapy?

Authors:  Susanne Lütje; Georg Feldmann; Markus Essler; Peter Brossart; Ralph A Bundschuh
Journal:  J Nucl Med       Date:  2020-01-10       Impact factor: 10.057

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

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

9.  Impact of image reconstruction methods on quantitative accuracy and variability of FDG-PET volumetric and textural measures in solid tumors.

Authors:  Ali Ketabi; Pardis Ghafarian; Mohammad Amin Mosleh-Shirazi; Seyed Rabi Mahdavi; Arman Rahmim; Mohammad Reza Ay
Journal:  Eur Radiol       Date:  2018-10-02       Impact factor: 5.315

10.  Assessment of tumor heterogeneity in treatment-naïve adrenocortical cancer patients using (18)F-FDG positron emission tomography.

Authors:  Rudolf A Werner; Matthias Kroiss; Masatoyo Nakajo; Dirk O Mügge; Stefanie Hahner; Martin Fassnacht; Andreas Schirbel; Christina Bluemel; Takahiro Higuchi; Laszló Papp; Norbert Zsótér; Andreas K Buck; Ralph A Bundschuh; Constantin Lapa
Journal:  Endocrine       Date:  2016-05-02       Impact factor: 3.633

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