Literature DB >> 34359737

A Multicentre Evaluation of Dosiomics Features Reproducibility, Stability and Sensitivity.

Lorenzo Placidi1, Eliana Gioscio2, Cristina Garibaldi3, Tiziana Rancati2, Annarita Fanizzi4, Davide Maestri5, Raffaella Massafra4, Enrico Menghi6, Alfredo Mirandola5, Giacomo Reggiori7, Roberto Sghedoni8, Pasquale Tamborra4, Stefania Comi9, Jacopo Lenkowicz1, Luca Boldrini1, Michele Avanzo10.   

Abstract

Dosiomics is a texture analysis method to produce dose features that encode the spatial 3D distribution of radiotherapy dose. Dosiomic studies, in a multicentre setting, require assessing the features' stability to dose calculation settings and the features' capability in distinguishing different dose distributions. Dose distributions were generated by eight Italian centres on a shared image dataset acquired on a dedicated phantom. Treatment planning protocols, in terms of planning target volume coverage and dose-volume constraints to the organs at risk, were shared among the centres to produce comparable dose distributions for measuring reproducibility/stability and sensitivity of dosiomic features. In addition, coefficient of variation (CV) was employed to evaluate the dosiomic features' variation. We extracted 38,160 features from 30 different dose distributions from six regions of interest, grouped by four features' families. A selected group of features (CV < 3 for the reproducibility/stability studies, CV > 1 for the sensitivity studies) were identified to support future multicentre studies, assuring both stable features when dose distributions variation is minimal and sensitive features when dose distribution variations need to be clearly identified. Dosiomic is a promising tool that could support multicentre studies, especially for predictive models, and encode the spatial and statistical characteristics of the 3D dose distribution.

Entities:  

Keywords:  dose distribution texture analysis; dosiomics; multicentric study; radiation dosimetry; radiotherapy; reproducibility; sensitivity; stability

Year:  2021        PMID: 34359737     DOI: 10.3390/cancers13153835

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


  4 in total

Review 1.  Precision Medicine in Head and Neck Cancers: Genomic and Preclinical Approaches.

Authors:  Giacomo Miserocchi; Chiara Spadazzi; Sebastiano Calpona; Francesco De Rosa; Alice Usai; Alessandro De Vita; Chiara Liverani; Claudia Cocchi; Silvia Vanni; Chiara Calabrese; Massimo Bassi; Giovanni De Luca; Giuseppe Meccariello; Toni Ibrahim; Marco Schiavone; Laura Mercatali
Journal:  J Pers Med       Date:  2022-05-24

2.  Impact of Interfractional Error on Dosiomic Features.

Authors:  Chanon Puttanawarut; Nat Sirirutbunkajorn; Narisara Tawong; Suphalak Khachonkham; Poompis Pattaranutaporn; Yodchanan Wongsawat
Journal:  Front Oncol       Date:  2022-06-10       Impact factor: 5.738

Review 3.  Deep Learning With Radiomics for Disease Diagnosis and Treatment: Challenges and Potential.

Authors:  Xingping Zhang; Yanchun Zhang; Guijuan Zhang; Xingting Qiu; Wenjun Tan; Xiaoxia Yin; Liefa Liao
Journal:  Front Oncol       Date:  2022-02-17       Impact factor: 6.244

4.  Simulation CT-based radiomics for prediction of response after neoadjuvant chemo-radiotherapy in patients with locally advanced rectal cancer.

Authors:  Pierluigi Bonomo; Jairo Socarras Fernandez; Daniela Thorwarth; Marta Casati; Lorenzo Livi; Daniel Zips; Cihan Gani
Journal:  Radiat Oncol       Date:  2022-04-28       Impact factor: 4.309

  4 in total

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