No abstract

No abstract

PurposeThere is a need to develop predictive tests that would allow identifying cancer patients with a high risk of developing side effects to radiotherapy. We compared the predictive value of three functional assays: the G0 aberration assay, the G2 aberration assay and the alkaline comet assay in lymphocytes of breast cancer and gynaecological cancer patients.Material and methodsPeripheral blood was collected from 35 patients with breast cancer and 34 patients with gynaecological cancer before the onset of therapy. Chromosomal aberrations were scored in lymphocytes irradiated in the G0 or G2 phase of the cell cycle. DNA repair kinetics was performed with the alkaline comet assay following irradiation of unstimulated lymphocytes. The results were compared with the severity of early and late side effects to radiotherapy.ResultsNo correlation was observed between the results of the assays and the severity of side effects. Moreover, each assay identified different patients as radiosensitive.ConclusionsThere is no simple correlation between the in vitro sensitivity of lymphocytes and the risk of developing early and late side effects.

Knowledge about tumor bed localization and its shape analysis is a crucial factor for preventing irradiation of healthy tissues during supportive radiotherapy and as a result, cancer recurrence. The localization process is especially hard for tumors placed nearby soft tissues, which undergo complex, nonrigid deformations. Among them, breast cancer can be considered as the most representative example. A natural approach to improving tumor bed localization is the use of image registration algorithms. However, this involves two unusual aspects which are not common in typical medical image registration: the real deformation field is discontinuous, and there is no direct correspondence between the cancer and its bed in the source and the target 3D images respectively. The tumor no longer exists during radiotherapy planning. Therefore, a traditional evaluation approach based on known, smooth deformations and target registration error are not directly applicable. In this work, we propose alternative artificial deformations which model the tumor bed creation process. We perform a comprehensive evaluation of the most commonly used deformable registration algorithms: B-Splines free form deformations (B-Splines FFD), different variants of the Demons and TV-L optical flow. The evaluation procedure includes quantitative assessment of the dedicated artificial deformations, target registration error calculation, 3D contour propagation and medical experts visual judgment. The results demonstrate that the currently, practically applied image registration (rigid registration and B-Splines FFD) are not able to correctly reconstruct discontinuous deformation fields. We show that the symmetric Demons provide the most accurate soft tissues alignment in terms of the ability to reconstruct the deformation field, target registration error and relative tumor volume change, while B-Splines FFD and TV-L optical flow are not an appropriate choice for the breast tumor bed localization problem, even though the visual alignment seems to be better than for the Demons algorithm. However, no algorithm could recover the deformation field with sufficient accuracy in terms of vector length and rotation angle differences.

Breast-conserving surgery requires supportive radiotherapy to prevent cancer recurrence. However, the task of localizing the tumor bed to be irradiated is not trivial. The automatic image registration could significantly aid the tumor bed localization and lower the radiation dose delivered to the surrounding healthy tissues. This study proposes a novel image registration method dedicated to breast tumor bed localization addressing the problem of missing data due to tumor resection that may be applied to real-time radiotherapy planning. We propose a deep learning-based nonrigid image registration method based on a modified U-Net architecture. The algorithm works simultaneously on several image resolutions to handle large deformations. Moreover, we propose a dedicated volume penalty that introduces the medical knowledge about tumor resection into the registration process. The proposed method may be useful for improving real-time radiation therapy planning after the tumor resection and, thus, lower the surrounding healthy tissues’ irradiation. The data used in this study consist of 30 computed tomography scans acquired in patients with diagnosed breast cancer, before and after tumor surgery. The method is evaluated using the target registration error between manually annotated landmarks, the ratio of tumor volume, and the subjective visual assessment. We compare the proposed method to several other approaches and show that both the multilevel approach and the volume regularization improve the registration results. The mean target registration error is below 6.5 mm, and the relative volume ratio is close to zero. The registration time below 1 s enables the real-time processing. These results show improvements compared to the classical, iterative methods or other learning-based approaches that do not introduce the knowledge about tumor resection into the registration process. In future research, we plan to propose a method dedicated to automatic localization of missing regions that may be used to automatically segment tumors in the source image and scars in the target image.

Severe xerostomia is noted in the majority of patients irradiated for oropharyngeal cancer. Extracellular microRNAs (miRNAs) may serve as effective tools allowing prediction of radiation-related toxicity. The aim of this study was to create an efficient prognostic miRNA-based test for severe, patient-rated xerostomia 3 months after primary treatment. Methods and Materials: This prospective study enrolled patients with oropharyngeal cancer treated between 2016 and 2018 in 3 centers in Poland. The primary endpoint was severe (grade ≥3) xerostomia as assessed by the European Organisation for

No abstract

Gynaecologic cancers are common among women and treatment includes surgery, radiotherapy or chemotherapy, where the last two methods induce DNA damage in non-targeted cells like peripheral blood lymphocytes (PBL). Damaged normal cells can transform leading to second malignant neoplasms (SMN) but the level of risk and impact of risk modifiers is not well defined. We investigated how radiotherapy alone or in combination with chemotherapy induce DNA damage in PBL of cervix and endometrial cancer patients during therapy. Blood samples were collected from nine endometrial cancer patients (treatment with radiotherapy + chemotherapy—RC) and nine cervical cancer patients (treatment with radiotherapy alone—R) before radiotherapy, 3 weeks after onset of radiotherapy and at the end of radiotherapy. Half of each blood sample was irradiated ex vivo with 2 Gy of gamma radiation in order to check how therapy influenced the sensitivity of PBL to radiation. Analysed endpoints were micronucleus (MN) frequencies, apoptosis frequencies and cell proliferation index. The results were characterised by strong individual variation, especially the MN frequencies and proliferation index. On average, despite higher total dose and larger fields, therapy alone induced the same level of MN in PBL of RC patients as compared to R. This result was accompanied by a higher level of apoptosis and stronger inhibition of cell proliferation in RC patients. The ex vivo dose induced fewer MN, more apoptosis and more strongly inhibited proliferation of PBL of RC as compared to R patients. These results are interpreted as evidence for a sensitizing effect of chemotherapy on radiation cytotoxicity. The possible implications for the risk of second malignant neoplasms are discussed.