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Fractal-based radiomic approach to predict complete pathological response after chemo-radiotherapy in rectal cancer

Davide Cusumano, Nicola Dinapoli, Luca Boldrini, Giuditta Chiloiro, Roberto Gatta, Carlotta Masciocchi, Jacopo Lenkowicz, Calogero Casà, Andrea Damiani, Luigi Azario, Johan Van Soest, Andre Dekker (+3 others)
2017 Radiologia Medica  
This approach was implemented in a radiomic workflow and applied to 198 T2-weighted pre-treatment magnetic resonance (MR) images of LARC patients.  ...  Fractal-based radiomic approach to predict complete pathological response after chemo-radiotherapy in rectal cancer. Radiologia medica, 123(4), 286-295. https://doi.  ...  of fractal dimensions, as performed by Szigeti et al., on lung cancer CT images [20] .  ... 
doi:10.1007/s11547-017-0838-3 pmid:29230678 fatcat:6efty3l6prazlgpz4umbywbypu

Fractal-Based Radiomic Approach to Tailor the Chemotherapy Treatment in Rectal Cancer: A Generating Hypothesis Study

Carmela Di Dio, Giuditta Chiloiro, Davide Cusumano, Francesco Catucci, Luca Boldrini, Angela Romano, Elisa Meldolesi, Fabio Marazzi, Barbara Corvari, Brunella Barbaro, Riccardo Manfredi, Vincenzo Valentini (+1 others)
2021 Frontiers in Oncology  
At the univariate analysis, the only feature showing significance in predicting 5yDFS was the maximum fractal dimension of the subpopulation identified considering 30% and 50% as threshold levels (maxFD30  ...  CT regimen for stage III LARC cancer patients.  ...  Conclusion: This study suggests that radiomic analysis of MR T2-w images can be used to define the optimal concomitant CT regimen for stage III LARC cancer patients.  ... 
doi:10.3389/fonc.2021.774413 pmid:34956893 pmcid:PMC8695680 fatcat:6xzzwayj5rhtjkbjmbsvlei3uq

Radiomics: a new application from established techniques

Vishwa Parekh, Michael A. Jacobs
2016 Expert Review of Precision Medicine and Drug Development  
Radiomics is defined as the high throughput extraction of quantitative imaging features or texture (radiomics) from imaging to decode tissue pathology and creating a high dimensional data set for feature  ...  The increasing use of biomarkers in cancer have led to the concept of personalized medicine for patients.  ...  b) Computed Tomography-Al-Kadi and Watson implemented the differential box counting based fractal analysis method as well as lacunarity analysis on contrast enhanced (CE) CT images for differentiation  ... 
doi:10.1080/23808993.2016.1164013 pmid:28042608 pmcid:PMC5193485 fatcat:fw4a4asugffq5fjwrlllrgadge

Radiomics in Cancer Radiotherapy: a Review [article]

Jiwoong Jeong, Arif Ali, Tian Liu, Hui Mao, Walter J. Curran, Xiaofeng Yang
2019 arXiv   pre-print
This review will attempt to comprehensively and critically discuss the various aspects of radiomics including its workflow, applications to different modalities, potential applications in cancer radiotherapy  ...  Radiomics is a nascent field in quantitative imaging that uses advanced algorithms and considerable computing power to describe tumor phenotypes, monitor treatment response, and assess normal tissue toxicity  ...  The wealth of CT data available for analysis as well as the ease of application makes radiomic analysis of CT images desirable.  ... 
arXiv:1910.02102v2 fatcat:joyhcr3r4bgivf6bn3tu4jiy2a

Magnetic resonance imaging (MRI)-based radiomics for prostate cancer radiotherapy

Fei Yang, John C. Ford, Nesrin Dogan, Kyle R. Padgett, Adrian L. Breto, Matthew C. Abramowitz, Alan Dal Pra, Alan Pollack, Radka Stoyanova
2018 Translational Andrology and Urology  
"Radiomics", as it refers to the extraction and analysis of large number of advanced quantitative radiological features from medical images using high throughput methods, is perfectly suited as an engine  ...  The article is structured as follows: first, we describe the radiomic approach; and second, we discuss the radiomic pipeline as tailored for RT of prostate cancer.  ...  Radiomics Radiomics, as applied to oncology, is a type of quantitative medical image analysis that exploits image "features" as biomarkers to aid in tumor detection and localization as well as prediction  ... 
doi:10.21037/tau.2018.06.05 pmid:30050803 pmcid:PMC6043736 fatcat:22h5rn2rings7jmnh2v3fdiekm

Radiomics in head and neck cancer: from exploration to application

Andrew J. Wong, Aasheesh Kanwar, Abdallah S. Mohamed, Clifton D. Fuller
2016 Translational Cancer Research  
Here we present an overview of radiomic texture analysis methods as well as the software infrastructure, review the developments of radiomics in head and neck cancer applications, discuss unmet challenges  ...  Head and neck cancers present a unique set of diagnostic and therapeutic challenges by nature of its complex anatomy and heterogeneity.  ...  Upon analysis of features extracted from pre-treatment CT images from four independent lung and head and neck cancer cohorts (878 patients total), they showed that lung and head and neck radiomic clusters  ... 
doi:10.21037/tcr.2016.07.18 pmid:30627523 pmcid:PMC6322843 fatcat:c3rlhvvksfexjioi5e6ewktbf4

Investigation of Radiation-Induced Toxicity in Head and Neck Cancer Patients through Radiomics and Machine Learning: A Systematic Review

Roberta Carbonara, Pierluigi Bonomo, Alessia Di Rito, Vittorio Didonna, Fabiana Gregucci, Maria Paola Ciliberti, Alessia Surgo, Ilaria Bonaparte, Alba Fiorentino, Angela Sardaro, Nihal Ahmad
2021 Journal of Oncology  
Studies assessing the use of radiomics combined with machine learning in predicting radiation-induced toxicity in head and neck cancer patients were specifically included.  ...  Published reports suggested the potential of radiomics combined with machine learning methods in the prediction and assessment of radiation-induced toxicities, supporting a tailored radiation treatment  ...  However, addressing MRI complex standardization is paramount.  ... 
doi:10.1155/2021/5566508 fatcat:n4e5nzvljrh5vlgjecspnujyra

Texture analysis of medical images for radiotherapy applications

Elisa Scalco, Giovanna Rizzo
2017 British Journal of Radiology  
The high-throughput extraction of quantitative information from medical images, known as radiomics, has grown in interest due to the current necessity to quantitatively characterize tumour heterogeneity  ...  Review article: Texture analysis of medical image in radiotherapy BJR  ...  Tumori, Milan, Italy; and the Department of Radiology of ASST degli Spedali Civili di Brescia, Brescia, Italy, for providing MRI images.  ... 
doi:10.1259/bjr.20160642 pmid:27885836 pmcid:PMC5685100 fatcat:2ko66us7wfg23lhia3dc74dcxi

Radiomics for radiation oncologists: Are we ready to go?

Loïg Vaugier, Ludovic Ferrer, Laurence Mengue, Emmanuel Jouglar
2020 BJR|Open  
Radiomics have emerged as an exciting field of research over the past few years, with very wide potential applications in personalised and precision medicine of the future.  ...  Radiomics could impact on all steps of the treatment pipeline, once the limitations in terms of robustness and reproducibility are overcome.  ...  cancers. 1 Most of these studies have relied on a pre-treatment multimodal (CT, MRI or PET) analysis.  ... 
doi:10.1259/bjro.20190046 pmid:33178967 pmcid:PMC7594896 fatcat:kgpixb4pqzdf5iqs426r5afqqe

Role of MRI‑based radiomics in locally advanced rectal cancer (Review)

Siyu Zhang, Mingrong Yu, Dan Chen, Peidong Li, Bin Tang, Jie Li
2021 Oncology Reports  
MRI‑based radiomics provides valuable data and is expected to become an imaging biomarker for predicting treatment response and prognosis.  ...  Radiomics is characterized by the extraction of high‑dimensional quantitative features from medical imaging data, followed by data analysis and model construction, which can be used for tumor diagnosis  ...  Li et al (97) combined the two imaging modalities of CT and MRI to establish a radiomics model, while comparing it with separate CT or MRI models.  ... 
doi:10.3892/or.2021.8245 pmid:34935061 pmcid:PMC8717123 fatcat:frrqoi7q55bkbpuzneudyaruxe

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

Eleonora Bicci, Cosimo Nardi, Leonardo Calamandrei, Michele Pietragalla, Edoardo Cavigli, Francesco Mungai, Luigi Bonasera, Vittorio Miele
2022 Cancers  
Six, thirteen, and seven articles used MRI, CT, and PET, respectively, as the imaging techniques by which texture analysis was performed.  ...  differentiation of HPV-positive versus HPV-negative cancers, (3) the detection of cancers not visualised by imaging alone, and (4) the assessment of lymph node metastases from unknown primary carcinomas  ...  Based on our results, texture analysis is a useful additional tool for the detection of OPSCC in combination with currently used imaging techniques, such as CT, MRI and PET/CT.  ... 
doi:10.3390/cancers14102445 pmid:35626048 pmcid:PMC9139172 fatcat:wiisd6z7ffho3byozp3dfuyflq

Radiomics – the value of the numbers in present and future radiology

Mateusz Patyk, Jurand Silicki, Rafał Mazur, Roksana Kręcichwost, Dąbrówka Sokołowska Dąbek, Urszula Zaleska-Dorobisz
2018 Polish Journal of Radiology  
tomography (CT), magnetic resonance imaging (MRI), or positron emission tomography (PET) images, by means of appropriate created algorithms.  ...  This article is intended to explain the idea of radiomics, the mechanisms of data acquisition, existing possibilities, and the challenges incurred by radiologists and physicians at the stage of making  ...  In oncology, neurology, or autoimmunological diseases, modern imaging technologies such as computer tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), scintigraphy,  ... 
doi:10.5114/pjr.2018.75794 pmid:30627231 pmcid:PMC6323541 fatcat:kbt34edfq5fcvalc5xs5q4wctq

The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges

Zhenyu Liu, Shuo Wang, Di Dong, Jingwei Wei, Cheng Fang, Xuezhi Zhou, Kai Sun, Longfei Li, Bo Li, Meiyun Wang, Jie Tian
2019 Theranostics  
On the basis of a great quantity of radiographic images and novel computational technologies, researchers developed and validated radiomic models that may improve the accuracy of diagnoses and therapy  ...  Progress in computational methods, especially in artificial intelligence for medical image process and analysis, has converted these images into quantitative and minable data associated with clinical events  ...  Radiomics was first proposed using CT images [1] and soon after was applied in the analysis of MR images [2] .  ... 
doi:10.7150/thno.30309 pmid:30867832 pmcid:PMC6401507 fatcat:zlupwckeajdfzgknpqexuuscce

Radiomics in the Setting of Neoadjuvant Radiotherapy: A New Approach for Tailored Treatment

Valerio Nardone, Luca Boldrini, Roberta Grassi, Davide Franceschini, Ilaria Morelli, Carlotta Becherini, Mauro Loi, Daniela Greto, Isacco Desideri
2021 Cancers  
Results: This paper contains a narrative report and a critical discussion of radiomics approaches in different fields of neoadjuvant radiotherapy, including esophageal cancer, lung cancer, sarcoma, and  ...  The evaluation of the efficacy of the induction strategy is made possible by performing imaging investigations before and after the neoadjuvant therapy and is usually challenging.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/cancers13143590 fatcat:awywvlbplvf2tawx5y6iuhxfwm

Responsible Radiomics Research for Faster Clinical Translation

Martin Vallières, Alex Zwanenburg, Bodgan Badic, Catherine Cheze Le Rest, Dimitris Visvikis, Mathieu Hatt
2017 Journal of Nuclear Medicine  
Secondly, a set of CT images of a lung cancer patient was used to standardize the image processing steps.  ...  Imaging modalities such as 2-deoxy-2-18F-fluoro-D-glucose (18F-FDG) positron emission tomography (PET), X-ray computed tomography (CT) and magnetic resonance imaging (MRI) are minimally invasive and would  ... 
doi:10.2967/jnumed.117.200501 pmid:29175982 pmcid:PMC5807530 fatcat:jm5qijrrhrdjbdzmdyrdf7zok4
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