Literature DB >> 32635216

Potential Added Value of PET/CT Radiomics for Survival Prognostication beyond AJCC 8th Edition Staging in Oropharyngeal Squamous Cell Carcinoma.

Stefan P Haider1,2, Tal Zeevi3, Philipp Baumeister2, Christoph Reichel2, Kariem Sharaf2, Reza Forghani4, Benjamin H Kann5, Benjamin L Judson6, Manju L Prasad7, Barbara Burtness8, Amit Mahajan1, Seyedmehdi Payabvash1.   

Abstract

Accurate risk-stratification can facilitate precision therapy in oropharyngeal squamous cell carcinoma (OPSCC). We explored the potential added value of baseline positron emission tomography (PET)/computed tomography (CT) radiomic features for prognostication and risk stratification of OPSCC beyond the American Joint Committee on Cancer (AJCC) 8th edition staging scheme. Using institutional and publicly available datasets, we included OPSCC patients with known human papillomavirus (HPV) status, without baseline distant metastasis and treated with curative intent. We extracted 1037 PET and 1037 CT radiomic features quantifying lesion shape, imaging intensity, and texture patterns from primary tumors and metastatic cervical lymph nodes. Utilizing random forest algorithms, we devised novel machine-learning models for OPSCC progression-free survival (PFS) and overall survival (OS) using "radiomics" features, "AJCC" variables, and the "combined" set as input. We designed both single- (PET or CT) and combined-modality (PET/CT) models. Harrell's C-index quantified survival model performance; risk stratification was evaluated in Kaplan-Meier analysis. A total of 311 patients were included. In HPV-associated OPSCC, the best "radiomics" model achieved an average C-index ± standard deviation of 0.62 ± 0.05 (p = 0.02) for PFS prediction, compared to 0.54 ± 0.06 (p = 0.32) utilizing "AJCC" variables. Radiomics-based risk-stratification of HPV-associated OPSCC was significant for PFS and OS. Similar trends were observed in HPV-negative OPSCC. In conclusion, radiomics imaging features extracted from pre-treatment PET/CT may provide complimentary information to the current AJCC staging scheme for survival prognostication and risk-stratification of HPV-associated OPSCC.

Entities:  

Keywords:  HPV; PET/CT; head and neck cancer; imaging biomarker; oropharyngeal squamous cell carcinoma; quantitative imaging; radiomics; risk stratification; survival analysis

Year:  2020        PMID: 32635216     DOI: 10.3390/cancers12071778

Source DB:  PubMed          Journal:  Cancers (Basel)        ISSN: 2072-6694            Impact factor:   6.639


  11 in total

Review 1.  Role of Texture Analysis in Oropharyngeal Carcinoma: A Systematic Review of the Literature.

Authors:  Eleonora Bicci; Cosimo Nardi; Leonardo Calamandrei; Michele Pietragalla; Edoardo Cavigli; Francesco Mungai; Luigi Bonasera; Vittorio Miele
Journal:  Cancers (Basel)       Date:  2022-05-16       Impact factor: 6.575

Review 2.  Radiomics in Oncological PET Imaging: A Systematic Review-Part 1, Supradiaphragmatic Cancers.

Authors:  David Morland; Elizabeth Katherine Anna Triumbari; Luca Boldrini; Roberto Gatta; Daniele Pizzuto; Salvatore Annunziata
Journal:  Diagnostics (Basel)       Date:  2022-05-27

3.  The coronal plane maximum diameter of deep intracerebral hemorrhage predicts functional outcome more accurately than hematoma volume.

Authors:  Stefan P Haider; Adnan I Qureshi; Abhi Jain; Hishan Tharmaseelan; Elisa R Berson; Shahram Majidi; Christopher G Filippi; Adrian Mak; David J Werring; Julian N Acosta; Ajay Malhotra; Jennifer A Kim; Lauren H Sansing; Guido J Falcone; Kevin N Sheth; Seyedmehdi Payabvash
Journal:  Int J Stroke       Date:  2021-10-13       Impact factor: 6.948

4.  Radiomics Analysis of PET and CT Components of 18F-FDG PET/CT Imaging for Prediction of Progression-Free Survival in Advanced High-Grade Serous Ovarian Cancer.

Authors:  Xihai Wang; Zaiming Lu
Journal:  Front Oncol       Date:  2021-04-13       Impact factor: 6.244

5.  CT angiographic radiomics signature for risk stratification in anterior large vessel occlusion stroke.

Authors:  Emily W Avery; Jonas Behland; Adrian Mak; Stefan P Haider; Tal Zeevi; Pina C Sanelli; Christopher G Filippi; Ajay Malhotra; Charles C Matouk; Christoph J Griessenauer; Ramin Zand; Philipp Hendrix; Vida Abedi; Guido J Falcone; Nils Petersen; Lauren H Sansing; Kevin N Sheth; Seyedmehdi Payabvash
Journal:  Neuroimage Clin       Date:  2022-05-07       Impact factor: 4.891

6.  Machine-Learning-Derived Nomogram Based on 3D Radiomic Features and Clinical Factors Predicts Progression-Free Survival in Lung Adenocarcinoma.

Authors:  Guixue Liu; Zhihan Xu; Yaping Zhang; Beibei Jiang; Lu Zhang; Lingyun Wang; Geertruida H de Bock; Rozemarijn Vliegenthart; Xueqian Xie
Journal:  Front Oncol       Date:  2021-06-23       Impact factor: 6.244

7.  Admission computed tomography radiomic signatures outperform hematoma volume in predicting baseline clinical severity and functional outcome in the ATACH-2 trial intracerebral hemorrhage population.

Authors:  Stefan P Haider; Adnan I Qureshi; Abhi Jain; Hishan Tharmaseelan; Elisa R Berson; Tal Zeevi; Shahram Majidi; Christopher G Filippi; Simon Iseke; Moritz Gross; Julian N Acosta; Ajay Malhotra; Jennifer A Kim; Lauren H Sansing; Guido J Falcone; Kevin N Sheth; Seyedmehdi Payabvash
Journal:  Eur J Neurol       Date:  2021-07-18       Impact factor: 6.288

Review 8.  Application of radiomics and machine learning in head and neck cancers.

Authors:  Zhouying Peng; Yumin Wang; Yaxuan Wang; Sijie Jiang; Ruohao Fan; Hua Zhang; Weihong Jiang
Journal:  Int J Biol Sci       Date:  2021-01-01       Impact factor: 6.580

9.  Discrimination of Cancer Stem Cell Markers ALDH1A1, BCL11B, BMI-1, and CD44 in Different Tissues of HNSCC Patients.

Authors:  Kariem Sharaf; Axel Lechner; Stefan P Haider; Robert Wiebringhaus; Christoph Walz; Gisela Kranz; Martin Canis; Frank Haubner; Olivier Gires; Philipp Baumeister
Journal:  Curr Oncol       Date:  2021-07-19       Impact factor: 3.677

Review 10.  [Artificial intelligence in otorhinolaryngology].

Authors:  Stefan P Haider; Kariem Sharaf; Philipp Baumeister; Christoph A Reichel
Journal:  HNO       Date:  2021-08-10       Impact factor: 1.284

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