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OC-0062 Development & validation of prognostic and predictive models in limited-stage small-cell lung cancer

A. Salem, H. Mistry, S. Falk, G. Price, C. Faivre-Finn
2019 Radiotherapy and Oncology  
radiotherapy (SBRT) in inoperable patients with centrally located non-small cell lung cancer (NSCLC).  ...  & validation of prognostic and predictive models in limited-stage small-cell lung cancer A.  ... 
doi:10.1016/s0167-8140(19)30482-7 fatcat:crdm7icuujgfzbtxer4iwpdnu4

A radiomic approach for adaptive radiotherapy in non-small cell lung cancer patients

Sara Ramella, Michele Fiore, Carlo Greco, Ermanno Cordelli, Rosa Sicilia, Mario Merone, Elisabetta Molfese, Marianna Miele, Patrizia Cornacchione, Edy Ippolito, Giulio Iannello, Rolando Maria D'Angelillo (+1 others)
2018 PLoS ONE  
In our experience, a radiomic signature mixing semantic and image-based features has shown promising results for personalized adaptive radiotherapy in non-small cell lung cancer.  ...  This paper discusses the rationale supporting the concept of radiomics and the feasibility of its application to Non-Small Cell Lung Cancer in the field of radiation oncology research.  ...  In metastatic non small cell lung cancer (NSCLC) patients, molecular information has brought remarkable results thanks to targeted therapies.  ... 
doi:10.1371/journal.pone.0207455 pmid:30462705 pmcid:PMC6248970 fatcat:4r4ql7gvivcqjgjg3tihdviaka

Radiomics and radiogenomics for precision radiotherapy

Jia Wu, Khin Khin Tha, Lei Xing, Ruijiang Li
2018 Journal of Radiation Research  
We will also present some examples of the current results and some emerging paradigms in radiomics and radiogenomics for clinical oncology, with a focus on potential applications in radiotherapy.  ...  Finally, we will highlight the challenges in the field and suggest possible future directions in radiomics to maximize its potential impact on precision radiotherapy.  ...  Wu et al. investigated quantitative radiomic features of FDG-PET and CT for predicting distant metastasis in early-stage non-small cell lung cancer (NSCLC) after stereotactic ablative radiotherapy (SABR  ... 
doi:10.1093/jrr/rrx102 pmid:29385618 pmcid:PMC5868194 fatcat:jgwi4xhp3zcvvg7tzeoubyter4

Liquid Biopsies for Molecular Biology-Based Radiotherapy

Erik S. Blomain, Everett J. Moding
2021 International Journal of Molecular Sciences  
Radiotherapy is one of the most commonly employed cancer treatment modalities, but radiobiologic approaches for personalizing therapy based on tumor biology and individual risks remain to be defined.  ...  Molecular alterations drive cancer initiation and evolution during development and in response to therapy.  ...  Precision radiotherapy for non-small cell lung cancer. J. Biomed. Sci. 2020, 27, 82. [CrossRef] 47.  ... 
doi:10.3390/ijms222011267 pmid:34681925 pmcid:PMC8538046 fatcat:bvkcdaxoqbdfdfrasycgpkeb2i

Applications of radiomics in precision diagnosis, prognostication and treatment planning of head and neck squamous cell carcinomas

Stefan P. Haider, Barbara Burtness, Wendell G. Yarbrough, Seyedmehdi Payabvash
2020 Cancers of the Head & Neck  
In this article, we explore the merits of the most recent addition to the "-omics" concept for the broader field of head and neck cancer - "Radiomics".  ...  This review discusses radiomics studies focused on (molecular) characterization, classification, prognostication and treatment guidance for head and neck squamous cell carcinomas (HNSCC).  ...  Funding There was no funding for this review article.  ... 
doi:10.1186/s41199-020-00053-7 pmid:32391171 pmcid:PMC7197186 fatcat:hezshp55wfhwtdlf77xwzn4jn4

Radiomics and Machine Learning for Radiotherapy in Head and Neck Cancers

Paul Giraud, Philippe Giraud, Anne Gasnier, Radouane El Ayachy, Sarah Kreps, Jean-Philippe Foy, Catherine Durdux, Florence Huguet, Anita Burgun, Jean-Emmanuel Bibault
2019 Frontiers in Oncology  
We then performed a systematic review on radiomics and machine learning outcome prediction models in head and neck cancers.  ...  Radiomics may provide additional data on tumors for improved machine learning powered predictive models, not only on survival, but also on risk of distant metastasis, in field recurrence, HPV status and  ...  For instance, Aerts et al. (6) generated a four feature radiomic signature on a retrospective cohort of 422 patients diagnosed with Non-Small Cell Lung Cancer (NSCLC) treated with curative intent.  ... 
doi:10.3389/fonc.2019.00174 pmid:30972291 pmcid:PMC6445892 fatcat:6e7adsrt2fclfklzsi3ljqmtny

Radiation Oncology in the Era of Big Data and Machine Learning for Precision Medicine [chapter]

Alexander F.I. Osman
2019 Machine Learning in Medicine and Biology [Working Title]  
In this chapter, we provide the interested reader with an overview of the ongoing advances and cutting-edge applications of state-of-the-art ML techniques in radiation oncology process from the radiotherapy  ...  With the era of big data, the utilization of machine learning algorithms in radiation oncology research is growing fast with applications including patient diagnosis and staging of cancer, treatment simulation  ...  The author also specially thanks the IntechOpen for granting this chapter a full funding for Open-Access publication.  ... 
doi:10.5772/intechopen.84629 fatcat:tobl67e5qvgf5mat43ex5lounq

Exploratory ensemble interpretable model for predicting local failure in head and neck cancer: the additive benefit of CT and intra-treatment cone-beam computed tomography features

Howard E. Morgan, Kai Wang, Michael Dohopolski, Xiao Liang, Michael R. Folkert, David J. Sher, Jing Wang
2021 Quantitative Imaging in Medicine and Surgery  
The fused ensemble EBM model achieved high discriminatory ability at predicting LF for head and neck cancer in independent primary and nodal structures.  ...  A 1:2 retrospective case control cohort of patients treated at a single institution with definitive radiotherapy for head and neck cancer who failed locally, in-field at a primary or nodal structure were  ...  CBCT-based radiomics have previously been evaluated in non-small cell lung cancer (25) (26) (27) ; however, to the best of our knowledge, CBCTbased radiomics have yet to be evaluated in HNSCC malignancies  ... 
doi:10.21037/qims-21-274 pmid:34888189 pmcid:PMC8611459 fatcat:rhtqge4vbfhv5neer73chyy4vi

Stereotactic ablative body radiotherapy (SABR) combined with immunotherapy (L19-IL2) versus standard of care in stage IV NSCLC patients, ImmunoSABR: a multicentre, randomised controlled open-label phase II trial

Relinde I. Y. Lieverse, Evert J. Van Limbergen, Cary J. G. Oberije, Esther G. C. Troost, Sine R. Hadrup, Anne-Marie C. Dingemans, Lizza E. L. Hendriks, Franziska Eckert, Crispin Hiley, Christophe Dooms, Yolande Lievens, Monique C. de Jong (+13 others)
2020 BMC Cancer  
About 50% of non-small cell lung cancer (NSCLC) patients have metastatic disease at initial diagnosis, which limits their treatment options and, consequently, the 5-year survival rate (15%).  ...  Immune checkpoint inhibitors (ICI), either alone or in combination with chemotherapy, have become standard of care (SOC) for most good performance status patients.  ...  RL, CO, AMD, EL, ET, DR and PL were responsible for writing, adapting, and submitting the study protocol.  ... 
doi:10.1186/s12885-020-07055-1 pmid:32539805 pmcid:PMC7296663 fatcat:f3oqudktpzdxxhknsjkvb6cr34

18F-fluorodeoxyglucose positron-emission tomography (FDG-PET)-Radiomics of metastatic lymph nodes and primary tumor in non-small cell lung cancer (NSCLC) – A prospective externally validated study

Sara Carvalho, Ralph T. H. Leijenaar, Esther G. C. Troost, Janna E. van Timmeren, Cary Oberije, Wouter van Elmpt, Lioe-Fee de Geus-Oei, Johan Bussink, Philippe Lambin, Aamir Ahmad
2018 PLoS ONE  
Lymph node stage prior to treatment is strongly related to disease progression and poor prognosis in non-small cell lung cancer (NSCLC).  ...  However, few studies have investigated metabolic imaging features derived from pre-radiotherapy 18 F-fluorodeoxyglucose (FDG) positron-emission tomography (PET) of metastatic hilar/mediastinal lymph nodes  ...  This research is also supported by the Dutch technology Foundation STW (grant n˚10696 DuCAT & n˚P14-19 Radiomics STRaTegy), which is the applied science division of NWO, and the Technology Programme of  ... 
doi:10.1371/journal.pone.0192859 pmid:29494598 pmcid:PMC5832210 fatcat:7zru5kyvynb7hk4qgw55flit7e

Imaging features from pretreatment CT scans are associated with clinical outcomes in nonsmall-cell lung cancer patients treated with stereotactic body radiotherapy

Qian Li, Jongphil Kim, Yoganand Balagurunathan, Ying Liu, Kujtim Latifi, Olya Stringfield, Alberto Garcia, Eduardo G. Moros, Thomas J. Dilling, Matthew B. Schabath, Zhaoxiang Ye, Robert J. Gillies
2017 Medical Physics (Lancaster)  
(SBRT) among non-smallcell lung cancer (NSCLC) patients.  ...  Conclusions-Imaging features derived from planning CT demonstrate prognostic value for recurrence following SBRT treatment, and might be helpful in patient stratification.  ...  Gillies reports grants from National Cancer Institute and non-financial support from HealthMyne.  ... 
doi:10.1002/mp.12309 pmid:28464316 pmcid:PMC5553698 fatcat:v4olchfp7bem5oignv32tfdks4

Novel imaging biomarkers predict outcomes in stage III unresectable non-small cell lung cancer treated with chemoradiation and durvalumab

Khalid Jazieh, Mohammadhadi Khorrami, Anas Saad, Mohamed Gad, Amit Gupta, Pradnya Patil, Vidya Sankar Viswanathan, Prabhakar Rajiah, Charles J Nock, Michael Gilkey, Pingfu Fu, Nathan A Pennell (+1 others)
2022 Journal for ImmunoTherapy of Cancer  
, unresectable non-small cell lung cancer (NSCLC) treated with durvalumab (immunotherapy, IO) therapy after chemoradiotherapy (CRT).  ...  Radiomic textural patterns from within and around the target nodules were extracted. A radiomic risk score (RRS) was built and was used to predict PFS and overall survival (OS).  ...  INTRODUCTION Lung cancer is estimated to be the leading cause of cancer-related deaths in the USA in 2021, and non-small cell lung cancer (NSCLC) accounts for around 85% of lung cancer cases. 1 In 2019  ... 
doi:10.1136/jitc-2021-003778 pmid:35256515 pmcid:PMC8905876 fatcat:aifc5sk3dbcupajma45sto5sym

Application of radiomics and machine learning in head and neck cancers

Zhouying Peng, Yumin Wang, Yaxuan Wang, Sijie Jiang, Ruohao Fan, Hua Zhang, Weihong Jiang
2021 International Journal of Biological Sciences  
As one of the cancer types whose treatment and diagnosis rely on imaging examination, radiomics has a very broad application prospect in head and neck cancers (HNC).  ...  In this review, we will introduce the concepts and workflow of radiomics and machine learning and their current applications in head and neck cancers, as well as the directions and applications of artificial  ...  The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.  ... 
doi:10.7150/ijbs.55716 pmid:33613106 pmcid:PMC7893590 fatcat:fohdsz3gcjh6jcnkdudkighraa

Imaging-Based Treatment Adaptation in Radiation Oncology

E. G. C. Troost, D. Thorwarth, W. J. G. Oyen
2015 Journal of Nuclear Medicine  
or chemoradiotherapy; (2) discuss the role of other functional imaging modalities (CT and MRI) in current oncology practice; and (3) introduce additional applications of PET imaging, such as in high-energy  ...  Objectives: On successful completion of this activity, participants should be able to (1) understand the clinical implications of tumor characterization using different PET tracers before and during radiotherapy  ...  24 patients with non-small cell lung cancer (NSCLC).  ... 
doi:10.2967/jnumed.115.162529 pmid:26429959 fatcat:l6by3riq7zeptiovyvvfq75mfe

A comparative study of machine learning methods for time-to-event survival data for radiomics risk modelling

Stefan Leger, Alex Zwanenburg, Karoline Pilz, Fabian Lohaus, Annett Linge, Klaus Zöphel, Jörg Kotzerke, Andreas Schreiber, Inge Tinhofer, Volker Budach, Ali Sak, Martin Stuschke (+13 others)
2017 Scientific Reports  
overall survival for patients with head and neck squamous cell carcinoma.  ...  Radiomics applies machine learning algorithms to quantitative imaging data to characterise the tumour phenotype and predict clinical outcome.  ...  Recently, Parmar et al. 10, 11 , investigated different algorithms in two different studies for patients with non-small cell lung (NSCLC) cancer and locally advanced head and neck squamous cell carcinoma  ... 
doi:10.1038/s41598-017-13448-3 pmid:29038455 pmcid:PMC5643429 fatcat:f7flqmggorbgtkwjjv6iz5f2yi
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