Automated Lung Segmentation from Computed Tomography Images of Normal and COVID-19 Pneumonia Patients.

Background: Automated image segmentation is an essential step in quantitative image analysis. This study assesses the performance of a deep learning-based model for lung segmentation from computed tomography (CT) images of normal and COVID-19 patients. Methods: A descriptive-analytical study was conducted from December 2020 to April 2021 on the CT images of patients from various educational hospitals affiliated with Mashhad University of Medical Sciences (Mashhad, Iran). Of the selected images and corresponding lung masks of 1,200 confirmed COVID-19 patients, 1,080 were used to train a residual neural network. The performance of the residual network (ResNet) model was evaluated on two distinct external test datasets, namely the remaining 120 COVID-19 and 120 normal patients. Different evaluation metrics such as Dice similarity coefficient (DSC), mean absolute error (MAE), relative mean Hounsfield unit (HU) difference, and relative volume difference were calculated to assess the accuracy of the predicted lung masks. The Mann-Whitney U test was used to assess the difference between the corresponding values in the normal and COVID-19 patients. P<0.05 was considered statistically significant. Results: The ResNet model achieved a DSC of 0.980 and 0.971 and a relative mean HU difference of -2.679% and -4.403% for the normal and COVID-19 patients, respectively. Comparable performance in lung segmentation of normal and COVID-19 patients indicated the model's accuracy for identifying lung tissue in the presence of COVID-19-associated infections. Although a slightly better performance was observed in normal patients. Conclusion: The ResNet model provides an accurate and reliable automated lung segmentation of COVID-19 infected lung tissue.A preprint version of this article was published on arXiv before formal peer review (https://arxiv.org/abs/2104.02042).

Different Methods of Measuring Neutron Dose/Fluence Generated During Radiation Therapy with Megavoltage Beams.

Medical linear accelerators (linacs) are the most frequently applied radiation therapy machines in the locoregional treatment of cancers by producing either high-energy electron or photon beams. However, with high-energy photons (>8 MeV), interaction of these photons with different high-Z nuclei of materials in components of the linac head unavoidably generates neutrons. On the other hand, the average energy of these generated neutrons has almost the highest radiation-weighting factor. Therefore, the produced neutrons should not be neglected. There are various tools for the measurement of neutron dose/fluence generated in a megavoltage linac, including thermoluminescent dosimeters, solid-state nuclear track detectors, bubble detectors, activation foils, Bonner sphere systems, and ionization chamber pairs. In this review article, each of the above-mentioned dosimetric methods will be described in detail.

Folic acid functionalized nanoparticles as pharmaceutical carriers in drug delivery systems.

Conventional chemotherapeutic approaches in cancer therapy such as surgery, chemotherapy, and radiotherapy have several disadvantages due to their nontargeted distributions in the whole body. On the other hand, nanoparticles (NPs) based therapies are remarkably progressing to solve several limitations of conventional drug delivery systems (DDSs) including nonspecific biodistribution and targeting, poor water solubility, weak bioavailability and biodegradability, low pharmacokinetic properties, and so forth. The enhanced permeability and retention effect escape from P-glycoprotein trap in cancer cells as a passive targeting mechanism, and active targeting strategies are also other most important advantages of NPs in cancer diagnosis and therapy. Folic acid (FA) is one of the biologic molecules which has been targeted overexpressed-folic acid receptor (FR) on the surface of cancer cells. Therefore, conjugation of FA to NPs most easily enhances the FR-mediated targeting delivery of therapeutic agents. Here, the recent works in FA which have been decorated NPs-based DDSs are discussed and cancer therapy potency of these NPs in clinical trials are presented.

Photosensitizer effects of MWCNTs-COOH particles on CT26 fibroblastic cells exposed to laser irradiation.

In the current study, photosensitizer effect of carboxylate multiwalled carbon nanotubes (MWCNTs-COOH) on CT26 fibroblastic cells following near infrared (NIR) irradiation was quantized in photo-thermal therapy (PTT). Moreover, it was tried to achieve optimal dose of MWCNTs-COOH and laser exposure time. Characterizations of MWCNTs-COOH were scrutinized using scanner electron microscope (SEM), spectrophotometer, and particle size analyzer. The seeded CT26 cells were treated with nontoxic concentrations of MWCNTs-COOH and then irradiated. Finally, viability (%) of the CT26 cells was determined using MTT assay. The findings revealed that 10, 50, and 80 µg/mL of MWCNTs-COOH have remarkable photosensitizer effects on CT26 cancerous cell lines against NIR irradiation (2.5 W/cm2). It was shown that using the 80 µg/mL concentration of MWCNTs-COOH against 60, 120, 180, 240, and 300 s of NIR irradiation and also, 10 and 50 µg/mL concentration of MWCNTs-COOH against 180, 240, and 300 s of NIR irradiation can lead to significant decrease in mean cell viability (%) by more than 50%. According to the obtained data, it seems that using the PPT with MWCNTs-COOH, as adjunct therapy in CT26 fibroblastic cells, can help to increase therapeutic ratio of main modalities of cancer treatment such as radiotherapy, chemotherapy, and surgery.

Estimation of radiation dose-reduction factor for cerium oxide nanoparticles in MRC-5 human lung fibroblastic cells and MCF-7 breast-cancer cells.

In the current study, radiation dose-reduction factor (DRF) of nanoceria or cerium oxide nanoparticles (CONPs) in MRC-5 Human Lung Fibroblastic Cells and MCF-7 Breast-Cancer Cells was estimated. Characterization of CONPs was determined using scanner electron microscope (SEM), energy dispersive spectroscopy (EDS), transmission electron microscopy (TEM) and spectrophotometer. Then, six plans were designed with different radiation dose values on planning target value. The obtained MRC-5 and MCF-7 cells were treated with non-toxic concentrations of CONPs and then exposed. Finally, cell viability (%) of the cell lines was determined using MTT assay. The findings showed that CONPs have no significant radioprotective effect against 10 cGy radiation dose value. Nevertheless, 70 µM CONPs resulted in a significant radioprotection against 100, 200, 300, 400 and 500 cGy radiation dose values compared with the control group in MRC-5 cells. For all radiation dose values, mean cell viability (%) of MCF-7 had not increased significantly at the presence of nanoceria compared with control group. According to the findings, it was revealed that the use of CONPs have a significant radioprotective effect on normal lung cells, while they do not provide any protection for MCF-7 cancer cells. These properties can help to increase therapeutic ratio of radiotherapy.