Stereotactic radiosurgery with immune checkpoint inhibitors for brain metastases: a meta-analysis study.

BACKGROUND: Immune checkpoint inhibitors (ICIs) are an emerging tool in the treatment of brain metastases (BMs), Stereotactic radiosurgery (SRS), traditionally used for BMs, elicits an immune brain response and can act synergistically with ICIs. We aim to investigate the efficacy of ICI administered with SRS and determine the impact of timing on BM response. METHODS: A systematical search was performed to identify potential studies concerning BMs managed with SRS alone or with SRS + ICI with relative timing administration (ICI concurrent with SRS, ICI nonconcurrent with SRS, SRS before ICI, SRS after ICI). The overall survival (OS), 12-month OS, local progression-free survival (LPFS), 12-month local brain control (LBC), distant progression-free survival (DPFS), 12-month distant brain control (DBC), and adverse events (intracranial hemorrhage, radionecrosis) were analyzed using the random-effects model. RESULTS: A total of 16 retrospective studies with 1356 BM patients were included. Compared to nonconcurrent therapy, concurrent therapy revealed a significantly longer OS (HR= 1.43; p = 0.008) and 12-months LBC (HR = 1.91; p = 0.04), a similar 12-months DBC (HR = 1.12; p = 0.547) and higher complication rate (R = 0.77; p = 0.346). Concurrent therapy leads to a significantly higher OS compared to ICI before SRS (HR = 2.55; p = 0.0003). CONCLUSION: The combination of SRS with ICI improves patients' clinical and radiological outcomes. The effectiveness of the combination is subject to the identification of an optimal therapeutic window.

Impact of low level radiation on concentrations of some trace elements in radiation workers.

INTRODUCTION: Small variations in trace element levels may cause important physiological changes in the human body. This study aims to evaluate five important trace elements in radiation workers. METHOD: In this study, 44 radiation workers and an equal number of non-radiation workers were selected as the case and control group, respectively. The concentrations of iron, magnesium, zinc, copper, and selenium in the serum of the participants were measured using an Atomic Absorption Spectrometry (AAS). RESULTS: The mean concentrations of iron, magnesium, zinc, copper, and selenium for the case group were 107.3 µg/dl, 2.3 mg/dl, 80.9 µg/dl, 112.6 µg/dl and 216.7 ng/ml, respectively. The results for the control group were 121.9 µg/dl, 2.3 mg/dl, 82.3 µg/dl, 112.8 µg/dl and 225.2 ng/ml, respectively. CONCLUSIONS: The mean concentration of iron in the case group was significantly lower than the control group (p-value = 0.012), while the concentrations of other elements in both of the groups were not significantly different. In the case group, except magnesium (p-value = 0.021), no significant relationship was found between age and the elemental concentrations. According to Spearman's test, there was a meaningful statistical correlation between the sex and concentration of iron, Mg, Zn, and Se. Also, the correlation between the concentration of magnesium and the weights of radiation workers was significant (p-value =0.044).

A cascade transformer-based model for 3D dose distribution prediction in head and neck cancer radiotherapy.

Objective. Radiation therapy is one of the primary methods used to treat cancer in the clinic. Its goal is to deliver a precise dose to the planning target volume while protecting the surrounding organs at risk (OARs). However, the traditional workflow used by dosimetrists to plan the treatment is time-consuming and subjective, requiring iterative adjustments based on their experience. Deep learning methods can be used to predict dose distribution maps to address these limitations.Approach. The study proposes a cascade model for OARs segmentation and dose distribution prediction. An encoder-decoder network has been developed for the segmentation task, in which the encoder consists of transformer blocks, and the decoder uses multi-scale convolutional blocks. Another cascade encoder-decoder network has been proposed for dose distribution prediction using a pyramid architecture. The proposed model has been evaluated using an in-house head and neck cancer dataset of 96 patients and OpenKBP, a public head and neck cancer dataset of 340 patients.Main results. The segmentation subnet achieved 0.79 and 2.71 for Dice and HD95 scores, respectively. This subnet outperformed the existing baselines. The dose distribution prediction subnet outperformed the winner of the OpenKBP2020 competition with 2.77 and 1.79 for dose and dose-volume histogram scores, respectively. Besides, the end-to-end model, including both subnets simultaneously, outperformed the related studies.Significance. The predicted dose maps showed good coincidence with ground-truth, with a superiority after linking with the auxiliary segmentation task. The proposed model outperformed state-of-the-art methods, especially in regions with low prescribed doses. The codes are available athttps://github.com/GhTara/Dose_Prediction.

Efficacy of stereotactic radiosurgery as single or combined therapy for brain metastasis: A systematic review and meta-analysis.

To determine the efficacy of stereotactic radiosurgery (SRS) in treating patients with brain metastases (BMs), a network meta-analysis (NMA) of randomized controlled trials (RCTs) and a direct comparison of cohort studies were performed. Relevant literature regarding the effectiveness of SRS alone and in combination with whole-brain radiotherapy (WBRT) and surgery was retrieved using systematic database searches up to April 2019. The patterns of overall survival (OS), one-year OS, progression-free survival (PFS), one-year local brain control (LBC), one-year distant brain control (DBC), neurological death (ND), and complication rate were analyzed. A total of 18 RCTs and 37 cohorts were included in the meta-analysis. Our data revealed that SRS carried a better OS than SRS+WBRT (p = 0.048) and WBRT (p = 0.041). Also, SRS+WBRT demonstrated a significantly improved PFS, LBC, and DBC compared to WBRT alone and SRS alone. Finally, SRS achieved the same LBC as high as surgery, but intracranial relapse occurred considerably more frequently in the absence of WBRT. However, there were not any significant differences in ND and toxicities between SRS and other groups. Therefore, SRS alone may be a better alternative since increased patient survival may outweigh the increased risk of brain tumor recurrence associated with it.

Asymmetric alterations of white matter integrity in patients with insomnia disorder.

Despite the adverse consequences of insomnia disorder for both individuals and society, the underlying neurobiological processes are poorly understood. The purpose was to further understand the alterations of white matter tracts in patients with insomnia and their association with sleep variables and also to determine if diffusion tensor imaging measures would be a useful disease marker. Twenty-six patients with insomnia and 26 age-matched healthy volunteers underwent diffusion tensor imaging. We employed an automated probabilistic tractography analysis approach using TRActs Constrained by UnderLying Anatomy (TRACULA) to quantify diffusion measures in major white matter tracts. We found significantly increased fractional anisotropy in the right cingulum-angular bundle and uncinate fasciculus in patients group compared to controls. Moreover, the mean diffusivity and radial diffusivity were reduced in the right cingulum-angular bundle in patients group in comparison with controls. We also found significantly increased fractional anisotropy along the bilateral cingulum-angular bundle and right uncinate fasciculus in patients. Also, mean and radial diffusivity were reduced along the right cingulum-angular bundle in patients group compared to controls. There is a significant positive correlation between fractional anisotropy and Epworth Sleepiness Scale scores. Moreover, there are negative correlations between mean, radial and axial diffusivity and total sleep time and sleep efficiency and also positive correlations between mean, radial and axial diffusivity and duration of disease and Pittsburgh Sleep Quality Index scores. This study showed the importance of examining whole-tract and waypoint white matter integrity in insomnia disorder. We found asymmetric widespread white matter integrity changes in patients with insomnia.

Deep learning approaches for automated classification and segmentation of head and neck cancers and brain tumors in magnetic resonance images: a meta-analysis study.

PURPOSE: Deep learning (DL) has led to widespread changes in automated segmentation and classification for medical purposes. This study is an attempt to use statistical methods to analyze studies related to segmentation and classification of head and neck cancers (HNCs) and brain tumors in MRI images. METHODS: PubMed, Web of Science, Embase, and Scopus were searched to retrieve related studies published from January 2016 to January 2020. Studies that evaluated the performance of DL-based models in the segmentation, and/or classification and/or grading of HNCs and/or brain tumors were included. Selected studies for each analysis were statistically evaluated based on the diagnostic performance metrics. RESULTS: The search results retrieved 1,664 related studies, of which 30 studies were eligible for meta-analysis. The overall performance of DL models for the complete tumor in terms of the pooled Dice score, sensitivity, and specificity was 0.8965 (95% confidence interval (95% CI): 0.76-0.9994), 0.9132 (95% CI: 0.71-0.994) and 0.9164 (95% CI: 0.78-1.00), respectively. The DL methods achieved the highest performance for classifying three types of glioma, meningioma, and pituitary tumors with overall accuracies of 96.01%, 99.73%, and 96.58%, respectively. Stratification of glioma tumors by high and low grading revealed overall accuracies of 94.32% and 94.23% for the DL methods, respectively. CONCLUSION: Based on the obtained results, we can acknowledge the significant ability of DL methods in the mentioned applications. Poor reporting in these studies challenges the analysis process, so it is recommended that future studies report comprehensive results based on different metrics.

Preclinical studies of [61Cu]ATSM as a PET radiopharmaceutical for fibrosarcoma imaging.

[61Cu]diacetyl-bis(N4-methylthiosemicarbazone) ([61Cu] ATSM) was prepared using in house-made diacetyl-bis(N4-methylthiosemicarbazone) (ATSM) ligand and [61Cu]CuCl2 produced via the natZn(p, x)61Cu (180 muA proton irradiation, 22 MeV, 3.2 h) and purified by a ion chromatography method. [61Cu]ATSM radiochemical purity was >98 %, as shown by HPLC and RTLC methods. [61Cu]ATSM was administered into normal and tumor bearing rodents for up to 210 minutes, followed by biodistribution and co-incidence imaging studies. Significant tumor/non-tumor accumulation was observed either by animal sacrification or imaging. [61Cu]ATSM is a positron emission tomography (PET) radiotracer for tumor hypoxia imaging.

Evaluating the effect of the vacuum bag on the dose distribution in radiation therapy.

INTRODUCTION: Immobilization of patients in radiation therapy can be performed with a vacuum bag (VB). The aim of this study is to measure the effect of the VB in the surface and depth dose of patients in radiation therapy. MATERIALS AND METHODS: The effect of the VB on the surface dose and depth dose is measured in clinical conditions. Various dosimeters were used in following measurements: parallel plate chamber for depth dose, farmer ionization chamber for various gantry angles, and Mapcheck2 dosimeter for various thicknesses of VB. The effect of VB cap, which may be placed in the beam path, is also measured using EDR2 film. The measurements were performed for 6 MV and 18 MV photons with an Oncor linac. RESULTS: The increase of 30% and 25% in the surface dose with VB was observed for 6 MV and 18 MV, respectively. Though due to the use of VB, the reduction of the absorbed dose at a 5 cm depth is under 1% and can be ignored in MU calculation. For various thicknesses of VB, 8-14 cm, the attenuation of the primary beam were up to 2.5% for 6 MV and 1.2% for 18 MV photon. The presence of VB cap in the path of radiation reduced the depth dose up to 15% and 11% for 6 MV and 18 MV, respectively. CONCLUSION: The use of VB can increase the surface dose of the patient up to 30% and this fact should be considered in treatment planning. For some lateral fields the cap of the VB may interfere with radiation field. If the cap of VB is placed in the beam path, it can cause a cold spot in tumor. DISCUSSION: The use of VB can increase the surface dose of the patient up to 30%. For some lateral fields, the cap of the VB might interfere with the radiation field. If the cap of VB is placed in the beam path, it can cause a cold spot in the tumor volume.

Markerless Respiratory Tumor Motion Prediction Using an Adaptive Neuro-fuzzy Approach.

BACKGROUND: Accurate delivery of the prescribed dose to moving lung tumors is a key challenge in radiation therapy. Tumor tracking involves real-time specifying the target and correcting the geometry to compensate for the respiratory motion, that's why tracking the tumor requires caution. This study aims to develop a markerless lung tumor tracking method with a high accuracy. METHODS: In this study, four-dimensional computed tomography (4D-CT) images of 10 patients were used, and all the slices which contained the tumor were contoured for all patients. The first four phases of 4D-CT images which contained tumors were selected as input of the software, and the next six phases were considered as the output. A hybrid intelligent method, adaptive neuro-fuzzy inference system (ANFIS), was used to evaluate motion of lung tumor. The root mean square error (RMSE) was used to investigate the accuracy of ANFIS performance for tumor motion prediction. RESULTS: For predicting the positions of contoured tumors, the averages of RMSE for each patient were calculated for all the patients. The results showed that the RMSE did not have a major variation. CONCLUSIONS: The data in the 4D-CT images were used for motion tracking instead of using markers that lead to more information of tumor motion with respect to methods based on marker location.

Modification of the gamma function for the recognition of over- and under-dose regions in three dimensions.

In order to evaluate two-dimensional radiation dose distributions, an algorithm called the Gamma function has recently been modified. The current study concentrates on modification of the gamma function as a three-dimensional dose distribution evaluation tool, and includes the recognition of over-dose/under-dose areas. Using a sign term, the conventional gamma function separates the disagreed areas into two parts: over-dose and under-dose areas. The new gamma function was modified using an extension of the dose difference criterion, ΔD, from two dimensions into three dimensions. In order to provide two-dimensional dose maps for analysis, several images were acquired for a range of regular and irregular radiation fields using a Scanning Liquid Ionization Chamber Electronic Portal Imaging Device. The raw images were then converted into two-dimensional transmitted dose maps using an empirical method. They were utilized as reference dose maps. Translational and rotational manipulations were performed on the reference dose distribution maps to provide evaluated dose maps. The reference and evaluated dose maps were then compared using conventional and modified gamma tools. The results indicated that the modified algorithm is able to enhance the over- and under-dose regions. In addition, a slight increase of the agreement percentage for reference and evaluated dose maps were observed by the extension of ΔD to three dimensions. It is concluded that the modified method is more realistic and applicable for the evaluation of both two-dimensional and three-dimensional dose distributions.

An investigation of gamma background radiation in Hamadan province, Iran.

The general population, everywhere in the world is exposed to a small dose of ionising radiation from natural sources. Stochastic effects such as cancer and genetic disorders are caused when living creatures are exposed to low doses. In Iran, it is measured in some cities, especially in high-background areas such as Ramsar, but so far there is no measurement in the Hamadan province. Hamadan is located in the west of Iran. Measurements were performed using a RDS-110 survey meter, CaSO(4):Dy thermoluminecense dosimetries (TLDs) and a Harshaw 4000 TLD reader. To estimate the dose rate  outdoors, four stations along the main directions (north, south, west and east) and one in the town centre were selected. Mean annual X and gamma equivalent dose in Hamadan province are 1.12±0.22  and 1.66±0.07 mSv, which related to RDS-110 survey meter and TLDs measurements, respectively. The TLDs and RDS-110 results are representative of the external photon radiation doses for the selected monitoring locations and for those locations for the hours during which the measurements were taken, respectively. Maximum and minimum of external photon radiation doses are related to Hamadan and Kaboudar-Ahang towns, respectively. According to the results of the study, it seems that the annual X and gamma equivalent dose in Hamadan province exceeded the global mean external exposure amounts by the UNSCEAR, and further studies are needed to measure internal exposures to determine the total environmental radiation level in  Hamadan province.