Literature DB >> 32101463

Tumor radiomic features complement clinico-radiological factors in predicting long-term local control and laryngectomy free survival in locally advanced laryngo-pharyngeal cancers.

Jai Prakash Agarwal1, Shwetabh Sinha1, Jayant Sastri Goda1, Kishor Joshi1, Ritesh Mhatre1, Sadhana Kannan2, Sarbani Ghosh Laskar1, Tejpal Gupta1, Vedang Murthy1, Ashwini Budrukkar, Naveen Mummudi1, Balaji Ganeshan3.   

Abstract

OBJECTIVE: To study if pre-treatment CT texture features in locally advanced squamous cell carcinoma of laryngo-pharynx can predict long-term local control and laryngectomy free survival (LFS).
METHODS: Image texture features of 60 patients treated with chemoradiation (CTRT) within an ethically approved study were studied on contrast-enhanced images using a texture analysis research software (TexRad, UK). A filtration-histogram technique was used where the filtration step extracted and enhanced features of different sizes and intensity variations corresponding to a particular spatial scale filter (SSF): SSF = 0 (without filtration), SSF = 2 mm (fine texture), SSF = 3-5 mm (medium texture) and SSF = 6 mm (coarse texture). Quantification by statistical and histogram technique comprised mean intensity, standard-deviation, entropy, mean positive pixels, skewness and kurtosis. The ability of texture analysis to predict LFS or local control was determined using Kaplan-Meier analysis and multivariate cox model.
RESULTS: Median follow-up of patients was 24 months (95% CI:20-28). 39 (65%) patients were locally controlled at last follow-up. 10 (16%) had undergone salvage laryngectomy after CTRT. For both local control & LFS, threshold optimal cut-off values of texture features were analyzed. Medium filtered-texture feature that were associated with poorer laryngectomy free survival were entropy ≥4.54, (p = 0.006), kurtosis ≥4.18; p = 0.019, skewness ≤-0.59, p = 0.001, and standard deviation ≥43.18; p = 0.009). Inferior local control was associated with medium filtered features entropy ≥4.54; p 0.01 and skewness ≤ - 0.12; p = 0.02. Using fine filters, entropy ≥4.29 and kurtosis ≥-0.27 were also associated with inferior local control (p = 0.01 for both parameters). Multivariate analysis showed medium filter entropy as an independent predictor for LFS and local control (p < 0.001 & p = 0.001).
CONCLUSION: Medium texture entropy is a predictor for inferior local control and laryngectomy free survival in locally advanced laryngo-pharyngeal cancer and this can complement clinico-radiological factors in predicting prognosticating these tumors. ADVANCES IN KNOWLEDGE: Texture features play an important role as a surrogate imaging biomarker for predicting local control and laryngectomy free survival in locally advanced laryngo-pharyngeal tumors treated with definitive chemoradiation.

Entities:  

Mesh:

Year:  2020        PMID: 32101463      PMCID: PMC7217564          DOI: 10.1259/bjr.20190857

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  30 in total

1.  Assessment of response to tyrosine kinase inhibitors in metastatic renal cell cancer: CT texture as a predictive biomarker.

Authors:  Vicky Goh; Balaji Ganeshan; Paul Nathan; Jaspal K Juttla; Anup Vinayan; Kenneth A Miles
Journal:  Radiology       Date:  2011-08-03       Impact factor: 11.105

2.  Assessment of tumor heterogeneity by CT texture analysis: can the largest cross-sectional area be used as an alternative to whole tumor analysis?

Authors:  Francesca Ng; Robert Kozarski; Balaji Ganeshan; Vicky Goh
Journal:  Eur J Radiol       Date:  2012-11-26       Impact factor: 3.528

3.  Association between tumor hypoxia and malignant progression in advanced cancer of the uterine cervix.

Authors:  M Hockel; K Schlenger; B Aral; M Mitze; U Schaffer; P Vaupel
Journal:  Cancer Res       Date:  1996-10-01       Impact factor: 12.701

4.  Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage.

Authors:  Balaji Ganeshan; Sandra Abaleke; Rupert C D Young; Christopher R Chatwin; Kenneth A Miles
Journal:  Cancer Imaging       Date:  2010-07-06       Impact factor: 3.909

Review 5.  Clinical applications of tumor volume measurements for predicting outcome in patients with squamous cell carcinoma of the upper aerodigestive tract.

Authors:  Suresh K Mukherji; Ilona M Schmalfuss; Jonas Castelijns; Anthony A Mancuso
Journal:  AJNR Am J Neuroradiol       Date:  2004-09       Impact factor: 3.825

6.  Evaluation of cartilage invasion by laryngeal and hypopharyngeal squamous cell carcinoma with dual-energy CT.

Authors:  Hirofumi Kuno; Hiroaki Onaya; Ryoko Iwata; Tatsushi Kobayashi; Satoshi Fujii; Ryuichi Hayashi; Katharina Otani; Hiroya Ojiri; Takeharu Yamanaka; Mitsuo Satake
Journal:  Radiology       Date:  2012-09-14       Impact factor: 11.105

7.  CT Texture Analysis Potentially Predicts Local Failure in Head and Neck Squamous Cell Carcinoma Treated with Chemoradiotherapy.

Authors:  H Kuno; M M Qureshi; M N Chapman; B Li; V C Andreu-Arasa; K Onoue; M T Truong; O Sakai
Journal:  AJNR Am J Neuroradiol       Date:  2017-10-12       Impact factor: 3.825

8.  Long-term results of RTOG 91-11: a comparison of three nonsurgical treatment strategies to preserve the larynx in patients with locally advanced larynx cancer.

Authors:  Arlene A Forastiere; Qiang Zhang; Randal S Weber; Moshe H Maor; Helmuth Goepfert; Thomas F Pajak; William Morrison; Bonnie Glisson; Andy Trotti; John A Ridge; Wade Thorstad; Henry Wagner; John F Ensley; Jay S Cooper
Journal:  J Clin Oncol       Date:  2012-11-26       Impact factor: 44.544

9.  CT texture analysis in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: A potential imaging biomarker for treatment response and prognosis.

Authors:  Choong Guen Chee; Young Hoon Kim; Kyoung Ho Lee; Yoon Jin Lee; Ji Hoon Park; Hye Seung Lee; Soyeon Ahn; Bohyoung Kim
Journal:  PLoS One       Date:  2017-08-10       Impact factor: 3.240

Review 10.  Intra-tumor heterogeneity of cancer cells and its implications for cancer treatment.

Authors:  Xiao-xiao Sun; Qiang Yu
Journal:  Acta Pharmacol Sin       Date:  2015-09-21       Impact factor: 6.150

View more
  6 in total

1.  Tumor Volume Reduction Rate to Induction Chemotherapy is a Prognostic Factor for Locally Advanced Head and Neck Squamous Cell Carcinoma: A Retrospective Cohort Study.

Authors:  Ting-Chun Lin; Chi-Hsien Huang; Ming-Yu Lien; Fu-Ming Cheng; Kai-Chiun Li; Chih-Yuan Lin; Ying-Chun Lin; Ji-An Liang; Ti-Hao Wang
Journal:  Technol Cancer Res Treat       Date:  2022 Jan-Dec

2.  The application of radiomics in laryngeal cancer.

Authors:  Amarkumar Dhirajlal Rajgor; Shreena Patel; David McCulloch; Boguslaw Obara; Jaume Bacardit; Andrew McQueen; Eric Aboagye; Tamir Ali; James O'Hara; David Winston Hamilton
Journal:  Br J Radiol       Date:  2021-09-29       Impact factor: 3.039

Review 3.  Diagnostic Utility of Radiomics in Thyroid and Head and Neck Cancers.

Authors:  Maryam Gul; Kimberley-Jane C Bonjoc; David Gorlin; Chi Wah Wong; Amirah Salem; Vincent La; Aleksandr Filippov; Abbas Chaudhry; Muhammad H Imam; Ammar A Chaudhry
Journal:  Front Oncol       Date:  2021-07-07       Impact factor: 6.244

4.  Radiomic features based on Hessian index for prediction of prognosis in head-and-neck cancer patients.

Authors:  Quoc Cuong Le; Hidetaka Arimura; Kenta Ninomiya; Yutaro Kabata
Journal:  Sci Rep       Date:  2020-12-04       Impact factor: 4.379

5.  18F-Fluorodeoxyglucose Positron Emission Tomography of Head and Neck Cancer: Location and HPV Specific Parameters for Potential Treatment Individualization.

Authors:  Sebastian Zschaeck; Julian Weingärtner; Elia Lombardo; Sebastian Marschner; Marina Hajiyianni; Marcus Beck; Daniel Zips; Yimin Li; Qin Lin; Holger Amthauer; Esther G C Troost; Jörg van den Hoff; Volker Budach; Jörg Kotzerke; Konstantinos Ferentinos; Efstratios Karagiannis; David Kaul; Vincent Gregoire; Adrien Holzgreve; Nathalie L Albert; Pavel Nikulin; Michael Bachmann; Klaus Kopka; Mechthild Krause; Michael Baumann; Joanna Kazmierska; Paulina Cegla; Witold Cholewinski; Iosif Strouthos; Klaus Zöphel; Ewa Majchrzak; Guillaume Landry; Claus Belka; Carmen Stromberger; Frank Hofheinz
Journal:  Front Oncol       Date:  2022-06-08       Impact factor: 5.738

Review 6.  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

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.