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OC-0062 Development & validation of prognostic and predictive models in limited-stage small-cell lung cancer
2019
Radiotherapy and Oncology
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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
2018
PLoS ONE
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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
2018
Journal of Radiation Research
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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
2021
International Journal of Molecular Sciences
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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
2020
Cancers of the Head & Neck
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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
2019
Frontiers in Oncology
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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]
2019
Machine Learning in Medicine and Biology [Working Title]
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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
2021
Quantitative Imaging in Medicine and Surgery
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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
2020
BMC Cancer
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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
2018
PLoS ONE
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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
2017
Medical Physics (Lancaster)
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(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
2022
Journal for ImmunoTherapy of Cancer
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, 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
2021
International Journal of Biological Sciences
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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
2015
Journal of Nuclear Medicine
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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
2017
Scientific Reports
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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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