OC-0495 Use of radiomics in the recurrence patterns after IMRT for head and neck cancer: a preliminary study
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Purpose or ObjectiveCirculating tumor cells (CTCs) are detectable in many cancers, including breast and lung cancer, where they can have prognostic significance.However, because of the lack of a suitable detection method, there are no useful data on CTCs in patients undergoing radiotherapy.The only US Food and Drug Administration-approved methodology, the CellSearch platform, uses epithelial cellular adhesion molecule EpCAM, exploiting the positivity of carcinomas to common epithelial markers.The monitoring of CTCs under chemotherapy showed a correlation of persistent CTCs and shorter survival in breast cancer.This indicates stronger defense mechanisms in the remaining CTCs.More efficient DNA repair capacity could contribute to such stronger resistance.The aim of this study is to identify relevant DNA damage response pathways in CTCs and peripheral blood lymphocytes under radiotherapy and their possible implications for the adjustment of future therapies. Material and MethodsUp to now 47 patients with brain metastases of breast and lung cancer (n=21/26) receiving radiotherapy were included in the study.Blood samples were collected before, at the end of radiotherapy and at the first followup (87 blood samples so far).The number of CTCs at the first follow-up was compared with clinical treatment response (e.g.MRI/CT and performance status).Enumeration and characterization of CTCs were done using the CellSearch®system.Apoptosis was measured in CTCs (in vivo irradiation) with the help of the M30 antibody in the CellSearch®system and DNA damage repair analyzed by yH2AX and 53BP1 foci detection was analyzed in primary lymphocytes (ex vivo irradiation). ResultsCTCs were detectable in 19% of lung cancer and 38% of breast cancer patients with brain metastases before start of radiotherapy.Quantitative changes in the number of CTCs under local radiotherapy were measurable in all patients.In the lung cancer group, 40% of patients showed an increase of CTCs after irradiation.This percentage was much higher in the breast cancer group with 75%.To specify whether the observed increase in number was due to vital or lethal CTCs an apoptotic marker (M30) was stained in addition in the same samples.In 82% the increase in CTC number was accompanied by apoptosis.After correction for this the number of vital CTCs decreased, indicating treatment response.This is mirrored by the clinical follow up via MRI/CT (evaluation under way) after different radiation schedules (whole brain vs. stereotactic treatment).The same treatment response was detectable in the DNA-damage response assessment parameters. ConclusionThe results indicate that monitoring DNA repair in CTCs and primary lymphocytes is already showing promising potential for judging treatment response after radiotherapy in the metastatic state of disease.The increase in apoptotic cells under radiotherapy suggests ineffective DNA repair and thus a local response to therapy.On the other hand, if persistent CTCs are present, this indicates efficient DNA repair and a poor prognosis.Cite
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Ideally, radiomics features and radiomics signatures can be used as imaging biomarkers for diagnosis, staging, prognosis, and prediction of tumor response.Thus, the number of published radiomics studies is increasing exponentially, leading to a myriad of new radiomics-based evidence for lung cancer.Consequently, it is challenging for radiologists to keep up with the development of radiomics features and their clinical applications.In this article, we review the basics to advanced radiomics in lung cancer to guide young researchers who are eager to start exploring radiomics investigations.In addition, we also include technical issues of radiomics, because knowledge of the technical aspects of radiomics supports a well-informed interpretation of the use of radiomics in lung cancer.
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Abstract: Lung cancers exhibit strong phenotypic differences that can be visualized noninvasively by medical imaging. Radiomics, a concept introduced in 2012, refers to the comprehensive quantification of tumor phenotypes by applying a large number of quantitative image features (watch the animation: https://youtu.be/Tq980GEVP0Y and the website www.radiomics.org). Here, we review the literature related to radiomics for lung cancer. We found 11 papers related to computed tomography (CT) radiomics, 3 to radiomics or texture analysis with positron emission tomography (PET) and 8 relating to PET/CT radiomics. There are two main applications of radiomics, the classification of lung nodules (diagnostic) or prognostication of established lung cancer (theragnostic). There are quite a few methodological issues in most of the reviewed papers. Only 5 studies, out of the 22, were externally validated. Overall, it is clear that radiomics offers great potential in improving diagnosis and patient stratification in lung cancer. It may also have a real clinical impact, as imaging is routinely used in clinical practice, providing an unprecedented opportunity to improve decision support in lung cancer treatment at low cost.
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Since the concept of radiomics was proposed, both domestic and foreign scholars have successively carried out many scientific researches on radiomics. Domestic and foreign research teams and their corresponding research have achieved certain results in radiomics, but we still face many challenges on the clinical application of radiomics-based models. Currently radiomics is still facing challenges. We should certainly pay attention to the research hotspots, existing problems, and future perspectives of radiomics.自影像组学的概念提出以来，国内外学者相继开展了众多关于影像组学的科学研究。国内外研究团队及其相应的研究在影像学上都取得了一定的成果，然而距离影像组学模型的临床应用，仍面临着诸多挑战。关于影像组学的研究热点、存在问题，以及未来的发展方向都需要关注和重视。.
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Abstract Radiomics has the potential to personalize patient treatment by using medical images that are already being acquired in clinical practice. Recently, with the development of computational and imaging technology, radiotherapy has brought unlimited opportunities driven by radiomics in individual cancer treatment and precision medicine care. This article reviews the advances in the application of radiomics in lung cancer, head and neck cancer, and other cancer sites. Additionally, we comment on the future challenges of radiomic research.
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Purpose or ObjectiveFirst dose-painting clinical trials are ongoing, even though the largest challenge of dose-painting has not been solved yet: to robustly redistribute the dose to the different regions of the tumor.Efforts to derive dose-response relations for different tumor regions rely on strong assumptions.Without accounting for uncertainty in the assumed dose-response relations, the potential gain of dose-painting may be lost.The goal of this study is to implement an automated treatment planning approach for dose-painting that takes into account uncertainties both in dose-response relations and in patient positioning directly into the optimization.Such that even in the presence of large uncertainties the delivered dosepainting plan is unlikely to perform worse than current clinical practice with homogeneous prescriptions. Material and MethodsDose response relations in TCP (tumor control probability) are modeled by a sigmoid shaped function, using 2 parameters to describe the dose level and cell sensitivity.Each voxel has its own tuple of parameters, and the parameters were assumed to follow probability distributions for which the mean and the variance were known.The expected TCP over all uncertainty distributions was optimized.Random positioning uncertainties were dealt with by convolving the pencil beam kernels with a Gaussian.For systematic geometrical uncertainties, a worst case optimization was implemented, to ensure adequate dose delivery in 95% of the geometrical scenarios.The method was implemented in our in house developed TPS and applied to a 3D ellipsoid phantom with a spherical tumor with a resistant shell and sensitive core and to a NSCLC cancer patient case with 3 subvolumes that were assumed to vary in radio-sensitivity.The effect of different probability distributions for cell sensitivity was investigated. ResultsAs expected, in the absence of dose-response and positioning uncertainties (red line), the dose to the resistant ring of the phantom (light gray in Fig 1) is considerably higher than to the sensitive core (dark gray).However, as the uncertainty in dose response relations increases (blue and green lines), the dose difference between the subvolumes decreases, even though the expected cell sensitivities do not change.Including positioning uncertainties leads to further smearing out of the dose (black line).Fig 2 demonstrates the effect on a real lung patient case with high risk GTV (white), low risk GTV (black), lymph nodes (pink).
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