Post-chemo-radiotherapy response and pseudo-progression evaluation on glioma cell types by multi-parametric magnetic resonance imaging: a prospective study.

BACKGROUND: We focused on Differentiated pseudoprogression (PPN) of progression (PN) and the response to radiotherapy (RT) or chemoradiotherapy (CRT) using diffusion and metabolic imaging. METHODS: Seventy-five patients with glioma were included in this prospective study (approved by the Iranian Registry of Clinical Trials (IRCT) (IRCT20230904059352N1) in September 2023). Contrast-enhanced lesion volume (CELV), non-enhanced lesion volume (NELV), necrotic tumor volume (NTV), and quantitative values ​​of apparent diffusion coefficient (ADC) and magnetic resonance spectroscopy (Cho/Cr, Cho/NAA and NAA/Cr) were calculated by a neuroradiologist using a semi-automatic method. All patients were followed at one and six months after CRT. RESULTS: The results of the study showed statistically significant changes before and six months after RT-CRT for M-CELV in all glioma types (𝑝 < 0.05). In glioma cell types, the changes in M-ADC, M-Cho/Cr, and Cho/NAA indices for PN were incremental and greater for PPN patients. M-NAA/Cr ratio decreased after six months which was significant only on PN for GBM, and Epn (𝑝 < 0.05). A significant difference was observed between diffusion indices, metabolic ratios, and CELV changes after six months in all types (𝑝 < 0.05). None of the patients were suspected PPN one month after treatment. The DWI/ADC indices had higher sensitivity and specificity (98.25% and 96.57%, respectively). CONCLUSION: The results of the present study showed that ADC values and Cho/Cr and Cho/NAA ratios can be used to differentiate between patients with PPN and PN, although ADC is more sensitive and specific.

A radiobiological comparison of hypo-fractionation versus conventional fractionation for breast cancer 3D-conformal radiation therapy.

BACKGROUND: The present research was aimed to compare the toxicity and effectiveness of conventional fractionated radiotherapy versus hypo-fractionated radiotherapy in breast cancer utilizing a radiobiological model. MATERIALS AND METHODS: Thirty-five left-sided breast cancer patients without involvement of the supraclavicular and axillary lymph nodes (with the nodal stage of N0) that had been treated with conventional or hypo-fractionated were incorporated in this study. A radiobiological model was performed to foretell normal tissue complication probability (NTCP) and tumor control probability (TCP). RESULTS: The data represented that TCP values for conventional and hypo-fractionated regimens were 99.16 ± 0.09 and 95.96 ± 0.48, respectively (p = 0.00). Moreover, the NTCP values of the lung for conventional and hypo-fractionated treatment were 0.024 versus 0.13 (p = 0.035), respectively. Also, NTCP values of the heart were equal to zero for both regimens. CONCLUSION: In summary, hypo-fractionated regimens had comparable efficacy to conventional fraction radiation therapy in the case of dosimetry parameters for patients who had left breast cancer. But, utilizing the radiobiological model, conventional fractionated regimens presented better results compared to hypo-fractionated regimens.

Protective effects of doxepin cream on radiation dermatitis in breast cancer: A single arm double-blind randomized clinical trial.

AIMS: Breast cancer is the most frequently occurring cancer in women. Lumpectomy followed by radiotherapy is suggested to be as effective as a total mastectomy. Radiation-induced dermatitis often occurs as a result of breast radiotherapy. Recent studies suggest that doxepin has promising anti-inflammatory properties. This study was undertaken to evaluate the effects of doxepin therapy on radiation dermatitis. METHODS: A double-blind randomized clinical trial was launched from 2016 to 2017, with a total of 48 patients who had undergone breast-conserving surgery and received postoperative radiation therapy. Radiotherapy was applied 5 days per week for 5 weeks. Adverse dermatological effects were evaluated by a physician at the beginning of the fifth week of radiotherapy and the patients were then randomly assigned (1:1 ratio) to receive either doxepin (5%) or placebo cream for 7 days. RESULTS: There were no significant differences in the dermatitis grade between doxepin and placebo groups at baseline (P > .5). The occurrence of acute dermatitis (grade 2 or higher) was significantly lower with the use of doxepin than with placebo (P ≤ .0001, Zα = 1.96 at 95% confidence interval). CONCLUSION: Doxepin cream prevents dermatitis grade 2 or higher during post-operative breast irradiation. Doxepin cream is easy to use, affordable and prevents pain and irritation.

Utilizing 808 nm laser for sensitizing of melanoma tumors to megavoltage radiation therapy.

Melanotic melanoma has high content of melanin and laser can destroy melanin-containing cells through thermal effect. In this study, the therapeutic effect of 808 nm laser therapy was investigated on B16-F10 melanoma tumor growth and tumor-bearing mice survival time. In addition, as laser can destroy melanin as the main cause of melanoma radioresistance, the effect of laser administration to enhance radiation therapy efficacy at B16-F10 cancer cells was evaluated in vitro and in vivo. Laser therapy (1 W/cm2 × 4 min) could cause significant (P < 0.05) inhibition of melanoma tumors' growth (~ 61%) and about three times increase of the tumor-bearing mice survival time in comparison with no-treatment group. In addition, the mice which were treated with 1 W/cm2 × 4 min laser administration plus 6 Gy megavoltage radiation therapy exhibited ~ 68% lesser tumors' volume and 27 days increase of survival time in comparison with 6 Gy irradiated tumor-bearing mice. Also, significantly higher (P < 0.05) tumor necrosis percentage was observed at the histopathological slides of 1 W/cm2 × 4 min laser + RT treated mice tumors (57 ± 12%) in comparison with radiation therapy group (31 ± 10%). Therefore, not only laser therapy can inhibit melanoma tumors' growth per se but also its combination with radiation therapy can cause a significant enhancement of radiation therapy efficacy. The laser administration can be used as a radiosensitizing method for melanotic melanoma radiation therapy.

Ultra-small but ultra-effective: Folic acid-targeted gold nanoclusters for enhancement of intracranial glioma tumors' radiation therapy efficacy.

The aim of the present study is to investigate folic acid and BSA decorated gold nanoclusters (FA-AuNCs) effect on the enhancement of intracranial C6 glioma tumors radiation therapy (RT) efficacy. Inductively coupled plasma optical emission spectrometry (ICP-OES) measurements exhibited about 2.5 times more FA-AuNCs uptake by C6 cancer cells (32.8 ng/106 cells) than the normal cells. FA-AuNCs had significantly higher concentration in the brain tumors (8.1 µg/mg) in comparison with surrounding normal brain tissue (4.3 µg/mg). Moreover, FA-AuNCs exhibited dose enhancement factor (DEF) of 1.6. The glioma-bearing rats' survival times were almost doubled at radiation therapy + FA-AuNCs (25.0 ±â€¯1.5 days) in comparison with no-treatment group (12.8 ±â€¯0.7 days). The Ki-67 labeling index was 48.89% ±â€¯9.93 for control, 29.98% ±â€¯8.32 for RT, and 11.53% ±â€¯7.65 for RT + FA-AuNCs. Therefore, FA-AuNCs can be effective radiosensitizers for intracranial glioma tumors RT.

Evaluation of rs1982073 polymorphism of transforming growth factor-ß1 in glioblastoma.

BACKGROUND: Glioblastoma (GBM) is the most common and invasive form of primary malignant brain tumors, with a survival rate of about 1 year. Transforming growth factor-ß1 (TGF-ß1) plays a very important role in tissue homeostasis and cancers. It seems that polymorphism of T29C (L10P, rs1982073, or rs1800470), which has been studied in various cancers such as breast and colon, creates the significant differences plays an important role in GBM prognosis and treatment. In this study, we evaluated the effect of T29C (rs1982073) polymorphism of TGF-ß1 gene in GBM. MATERIALS AND METHODS: This study was conducted on 100 cases of GBM including 47 paraffin-embedded brain tissue samples and 53 blood samples from another 53 GBM patients, who was under therapy, and 150 were controls. The TGF-ß rs1982073 single-nucleotide polymorphism (SNP) was identified by the NCBI and genotyping was performed by high-resolution melt (HRM) assay. Melt curves from HRM which suspected to SNP were selected and subjected to direct sequencing. Finally, the collected data were entered into the SPSS software (Version. 20) and mean ± standard deviation or n (%) was used to show the data. RESULTS: The mean age in GBM group was 51.63 ± 13.27 years. Accordingly, the two groups were matched in terms of age and gender (P > 0.05). The frequency of GG genotype was significantly higher in GBM patients. In contrast, although the frequency of AG genotype was higher in GBM group, it was not statistically significant. Furthermore, the presence of G allele was significantly more frequent than A allele in GBM patients. CONCLUSION: Findings of the present study supports that the Pro10Leu, rs1982073, or rs1800470 SNP in TGF-ß1 is found to be expressed significantly more in GBM patients as it was found in breast cancer.

Could FA-PG-SPIONs act as a hyperthermia sensitizing agent? An in vitro study.

The therapeutic effect of polyglycerol coated iron oxide nanoparticles (PG-SPIONs, non-targeted nanoparticles) and folic acid-conjugated polyglycerol coated iron oxide nanoparticles (FA-PG-SPIONs, targeted nanoparticles) in combination with hyperthermia on viability of HeLa cells was investigated. It was observed that coated and uncoated SPIONs have spherical shapes with an average diameter of 17.9 ±â€¯2.85 nm and 5.4 ±â€¯0.75 nm, respectively. The penetration rate for cells treated with targeted nanoparticles was shown to be more than that of non-targeted nanoparticles. Moreover, it was revealed that the treatment of cells with ≥ 50 µg/ml FA-PG-SPIONs in combination with hyperthermia induced cytotoxicity in comparison to control cells. The results also showed that increasing the concentrations of targeted nanoparticles (FA-PG-SPIONs) and heating time would increase the value of thermal enhancement factor (TEF). In contrast, TEF values were not increased with increasing heating time and concentrations of non-targeted nanoparticles (PG-SPIONs). On the other hand, TEF values were increased with increasing concentrations and heating time so that the maximum TEF value was obtained at the highest concentration (FA-PG-SPION, 200 µg/ml) as well as the longest heating duration (60 min). Thus, it is concluded that FA-PG-SPIONs with concentrations ≥ 100 µg/ml could be introduced and used as hyperthermia sensitizing agents leading to enhanced cancer therapy efficiency.

Prospective Prediction of Treatment Response in High-Grade Glioma Patients using Pre-Treatment Tumor ADC Value and miR-222 and miR-205 Expression Levels in Plasma.

Background: Treatment response in High-grade Glioma (HGG) patients changes based on their genetic and biological characteristics. MiRNAs, as important regulators of drug and radiation resistance, and the Apparent Diffusion Coefficients (ADC) value of tumor can be used as a prognostic predictor for glioma. Objective: This study aimed to identify some of the pre-treatment individual patient features for predicting the treatment response in HGG patients. Material and Methods: In this prospective study, 18 HGG patients, who were candidated for chemo-radiation treatment, participated after informed consent of the patients. The investigated features were the expression level of miR-222 and miR-205 in plasma, the ADC value of tumor, Body Mass Index (BMI), and age. Treatment response was assessed, and Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to obtain a model to predict the treatment response. Mann-Whitney U test was also applied to select the variables with a significant relationship with patients' treatment response. Results: The LASSO coefficients for miR-205, miR-222, tumor's mean ADC value, BMI, and age were 3.611, -1.683, 2.468, -0.184, and -0.024, respectively. Mann-Whitney U test results showed miR-205 and tumor's mean ADC significantly related to treatment response (P-value<0.05). Conclusion: The miR-205 expression level of the patient in plasma and tumor's mean ADC value has the potential for prognostic predictors in HGG.

Dosiomics-based detection of dose distribution variations in helical tomotherapy for prostate cancer patients: influence of treatment plan parameters.

The stability of dosiomics features (DFs) and dose-volume histogram (DVH) parameters for detecting disparities in helical tomotherapy planned dose distributions was assessed. Treatment plans of 18 prostate patients were recalculated using the followings: field width (WF) (2.5 vs. 5), pitch factor (PF) (0.433 vs. 0.444), and modulation factor (MF) (2.5 vs. 3). From each of the eight plans per patient, ninety-three original and 744 wavelet-based DFs were extracted, using 3D-Slicer software, across six regions including: target volume (PTV), pelvic lymph nodes (PTV-LN), PTV + PTV-LN (PTV-All), one cm rind around PTV-All (PTV-Ring), rectum, and bladder. For the resulting DFs and DVH parameters, the coefficient of variation (CV) was calculated, and using hierarchical clustering, the features were classified into low/high variability. The significance of parameters on instability was analyzed by a three-way analysis of variance. All DF's were stable in PTV, PTV-LN, and PTV-Ring (average CV ( CV ¯ )  ≤ 0.36). Only one feature in the bladder ( CV ¯  = 0.9), rectum ( CV ¯  = 0.4), and PTV-All ( CV ¯  = 0.37) were considered unstable due to change in MF in the bladder and WF in the PTV-All. The value of CV ¯ for the wavelet features was much higher than that for the original features. Out of 225 unstable wavelet features, 84 features had CV ¯  ≥ 1. The CVs for all the DVHs remained very small ( CV ¯ < 0.06). This study highlights that the sensitivity of DFs to changes in tomotherapy planning parameters is influenced by the region and the DFs, particularly wavelet features, surpassing the effectiveness of DVHs.

Safety evaluation of the trastuzumab biosimilar in Iranian women with HER2-positive breast cancer undergoing adjuvant chemotherapy: a post-marketing surveillance.

BACKGROUND: Trastuzumab is a humanized monoclonal antibody against the human epidermal growth factor receptor 2 (HER2). This post-marketing surveillance evaluates the safety of a trastuzumab biosimilar (AryoTrust), produced by AryoGen Co. Iran in Iranian women with HER2-positive non-metastatic breast cancer (BC). RESEARCH DESIGN AND METHODS: The patients who had undergone adjuvant chemotherapy regimens received trastuzumab every 3 weeks for nine cycles. The study started in February 2017 and finished in August 2022. Data regarding safety were collected using booklets and then analyzed. RESULTS: A total of 597 women with a mean ±SD age of 48.13 ± 10.18 years underwent 5,313 injection cycles. They received pre-study chemotherapies consisting of anthracyclines, taxanes, both, or other medications in 6.70, 7.20, 82.41, and 2.01% of the cases, respectively. One hundred and thirty-nine patients experienced at least one adverse event (AE). The most common AEs were decreased ejection fraction (EF, 5.7%), peripheral neuropathy (5.36%), and nausea (5.19%). Meningioma was the only life-threatening serious AE. Furthermore, bone pain and infusion-related reactions were the two most common grade three AEs. Nevertheless, the mean EF of patients did not change notably during the study. CONCLUSIONS: The results demonstrate that this trastuzumab biosimilar is a generally well tolerated and safe treatment for HER2-positive BC. CLINICAL TRIAL REGISTRATION: www.clinicaltrials.gov identifier is NCT06021379.

Radiomics based predictive modeling of rectal toxicity in prostate cancer patients undergoing radiotherapy: CT and MRI comparison.

BACKGROUND: Rectal toxicity is one of the common side effects after radiotherapy in prostate cancer patients. Radiomics is a non-invasive and low-cost method for developing models of predicting radiation toxicity that does not have the limitations of previous methods. These models have been developed using individual patients' information and have reliable and acceptable performance. This study was conducted by evaluating the radiomic features of computed tomography (CT) and magnetic resonance (MR) images and using machine learning (ML) methods to predict radiation-induced rectal toxicity. METHODS: Seventy men with pathologically confirmed prostate cancer, eligible for three-dimensional radiation therapy (3DCRT) participated in this prospective trial. Rectal wall CT and MR images were used to extract first-order, shape-based, and textural features. The least absolute shrinkage and selection operator (LASSO) was used for feature selection. Classifiers such as Random Forest (RF), Decision Tree (DT), Logistic Regression (LR), and K-Nearest Neighbors (KNN) were used to create models based on radiomic, dosimetric, and clinical data alone or in combination. The area under the curve (AUC) of the receiver operating characteristic curve (ROC), accuracy, sensitivity, and specificity were used to assess each model's performance. RESULTS: The best outcomes were achieved by the radiomic features of MR images in conjunction with clinical and dosimetric data, with a mean of AUC: 0.79, accuracy: 77.75%, specificity: 82.15%, and sensitivity: 67%. CONCLUSIONS: This research showed that as radiomic signatures for predicting radiation-induced rectal toxicity, MR images outperform CT images.

Auto-Segmentation and Classification of Glioma Tumors with the Goals of Treatment Response Assessment Using Deep Learning Based on Magnetic Resonance Imaging.

Glioma is the most common primary intracranial neoplasm in adults. Radiotherapy is a treatment approach in glioma patients, and Magnetic Resonance Imaging (MRI) is a beneficial diagnostic tool in treatment planning. Treatment response assessment in glioma patients is usually based on the Response Assessment in Neuro Oncology (RANO) criteria. The limitation of assessment based on RANO is two-dimensional (2D) manual measurements. Deep learning (DL) has great potential in neuro-oncology to improve the accuracy of response assessment. In the current research, firstly, the BraTS 2018 Challenge dataset included 210 HGG and 75 LGG were applied to train a designed U-Net network for automatic tumor and intra-tumoral segmentation, followed by training of the designed classifier with transfer learning for determining grading HGG and LGG. Then, designed networks were employed for the segmentation and classification of local MRI images of 49 glioma patients pre and post-radiotherapy. The results of tumor segmentation and its intra-tumoral regions were utilized to determine the volume of different regions and treatment response assessment. Treatment response assessment demonstrated that radiotherapy is effective on the whole tumor and enhancing region with p-value ≤ 0.05 with a 95% confidence level, while it did not affect necrosis and peri-tumoral edema regions. This work demonstrated the potential of using deep learning in MRI images to provide a beneficial tool in the automated treatment response assessment so that the patient can obtain the best treatment.

Prediction of Normal Tissue Complication Probability (NTCP) After Radiation Therapy Using Imaging and Molecular Biomarkers and Multivariate Modelling.

The aim of this study was to design a predictive radiobiological model of normal brain tissue in low-grade glioma following radiotherapy based on imaging and molecular biomarkers. Fifteen patients with primary brain tumors prospectively participated in this study and underwent radiation therapy. Magnetic resonance imaging (MRI) was obtained from the patients, including T1- and T2-weighted imaging and diffusion tensor imaging (DTI), and a generalized equivalent dose (gEUD) was calculated. The radiobiological model of the normal tissue complication probability (NTCP) was performed using the variables gEUD; axial diffusivity (AD) and radial diffusivity (RD) of the corpus callosum; and serum protein S100B by univariate and multivariate logistic regression XLIIIrd Sir Peter Freyer Memorial Lecture and Surgical Symposium (2018). Changes in AD, RD, and S100B from baseline up to the 6 months after treatment had an increasing trend and were significant in some time points (P-value < 0.05). The model resulting from RD changes in the 6 months after treatment was significantly more predictable of necrosis than other univariate models. The bivariate model combining RD changes in Gy40 dose-volume and gEUD, as well as the trivariate model obtained using gEUD, RD, and S100B, had a higher predictive value among multivariate models at the sixth month of the treatment. Changes in RD diffusion indices and in serum protein S100B value were used in the early-delayed stage as reliable biomarkers for predicting late-delayed damage (necrosis) caused by radiation in the corpus callosum. Current findings could pave the way for intervention therapies to delay the severity of damage to white matter structures, minimize cognitive impairment, and improve the quality of life of patients with low-grade glioma.

PrACTiC: A Predictive Algorithm for Chemoradiotherapy-Induced Cytopenia in Glioblastoma Patients.

BACKGROUND: Chemotherapy-induced cytopenia is the most frequent side effect of chemoradiotherapy in glioblastoma patients which may lead to reduced delivery of treatment. This study aims to develop a predictive model that is able to forecast the cytopenia induced by temozolomide (TMZ) during concomitant chemoradiotherapy. METHODS: Medical records of 128 patients with newly diagnosed glioblastoma were evaluated to extract the baseline complete blood test before and during the six weeks of chemoradiotherapy to create a dataset for the development of ML models. Using the constructed dataset, different ML algorithms were trained and tested. RESULTS: Our proposed algorithm achieved accuracies of 85.6%, 88.7%, and 89.3% in predicting thrombocytopenia, lymphopenia, and neutropenia, respectively. CONCLUSIONS: The algorithm designed and developed in this study, called PrACTiC, showed promising results in the accurate prediction of thrombocytopenia, neutropenia, and lymphopenia induced by TMZ in glioblastoma patients. PrACTiC can provide valuable insight for physicians and help them to make the necessary treatment modifications and prevent the toxicities.

Investigating the number of radiation fields in intensity-modulated radiotherapy plans of optic nerve sheath meningioma patients using dose gradient index.

Purpose: In optic nerve radiotherapy, vital organs are very close to the target volume, they are highly sensitive to radiation and have low dose tolerance. In this regard, evaluating dose fall-off steepness around the target volume is required to assess various intensity-modulated radiation therapy (IMRT) plans in the treatment of the optic nerve sheath meningioma (ONSM) patients.Materials and Methods: Thirteen ONSM patients were analyzed with three IMRT techniques, including three (IMRT-3F), five (IMRT-5F), and seven fields (IMRT-7F). These plans were studied using Dmean, Dmax, D2%, D98%, V100%, uniformity index (UI), homogeneity index (HI), conformity index (CI), and specifically the dose gradient indices (DGIs).Results: The values of Dmaxand Dmeanfor IMRT-3F, IMRT-5F and IMRT-7F were (5637.42 ± 57.08, 5322.84 ± 83.86), (5670.51 ± 67.87, 5383.00 ± 58.45), and (5692.99 ± 31.65, 5405.72 ± 51.73), respectively, which were increased with increment in the number of IMRT fields from 3 to 7. The UI and HI indices were significantly different between IMRT-3F and IMRT-7F (p = 0.010 and p = 0.005, respectively), and CI was close to the ideal value (0.99 ± 0.01) in IMRT-7F. The significant findings of the dose gradient indices represented smaller values in IMRT-7F, which led to a faster dose fall-off, particularly at the 70%-85% isodose levels around the target.Conclusion: Increasing the number of radiation fields in IMRT treatment plans of ONSM patients had a considerable difference in both the dosimetric parameters of the target volume and at-risk organs, as well as the dose gradient indices. Overall, IMRT-7F could be considered as a preferred technique in the treatment of this meningioma.

DETERMINATION OF THE NEUTRON CONTAMINATION DURING BRAIN RADIOTHERAPY USING A MODERATED-BORON TRIFLUORIDE DETECTOR AND THE MCNP MONTE CARLO CODE.

This study aimed to determine the neutron dose equivalent to the thyroid gland and eye lens in brain tumor radiation therapy with 15- and 18-MV three-dimensional conformal methods (3D-CRT). A Monte Carlo simulation was performed using the Monte Carlo N-particle transport code to calculate neutron fluence and ambient dose equivalent (H*(10)). Afterward, these parameters were measured using a model NRD roentgen equivalent in man (REM) neutron detector (Thermo Electron Corporation, USA) equipped with Eberline's ASP-2e rate meter. Finally, the organ neutron dose equivalent was obtained by applying depth corrections to the measured ambient dose equivalent at the distance of the organ center from the central beam axis. The ratio of the out-of-field photon dose equivalent, measured previously, to the neutron dose equivalent in the eye lens was high due to its proximity to the radiation field. In contrast, this ratio remained unexpectedly high in the thyroid gland that is far from the central beam axis (about 15 cm). The calculated neutron parameters agreed with the measurements. The present study findings indicate that external field photon dose is the main source of thyroid gland biological effects in radiotherapy of brain tumors. In addition, it is appropriate to apply the model NRD REM neutron detector for measuring neutron contamination from high-energy linear accelerators inside and outside the treatment field.

Optimization of Mouse-on-Mouse Immunohistochemistry by Utilizing Fluorescent-dye Conjugated Secondary Anti-Mouse Antibody.

The application of mouse monoclonal antibody for immunostaining the mouse tissues results in a high rate of background noise because of the interaction of the secondary antibody with endogenous immunoglobulins and other immune components. The most advised blocking strategy for the mouse-on-mouse immunostaining is the use of anti-mouse Fab fragments. Nevertheless, the commercial kits containing Fab fragment are costly and unavailable in many research laboratories. In this study, we provide evidence showing the potential of the fluorescent-dye conjugated secondary anti-mouse antibody for reducing the background noise in the mouse-on-mouse immunohistochemistry. Furthermore, our findings demonstrate the inadequacy of goat serum/protein-blocking solution alone as an immunohistochemistry blocking system for reducing the background noise.

Diagnostic and prognostic value of stem cell factor plasma level in glioblastoma multiforme patients.

BACKGROUND: Investigation of novel blood-circulating agents as potential biomarkers for glioblastoma multiforme (GBM) patients' diagnosis and monitoring has gained lots of attention, due to limitations of imaging modalities and invasive tissue biopsy procedures. The present study aims to assess the diagnostic and prognostic values of preoperative stem cell factor (SCF) plasma level in GBM patients. METHODS: Preoperative plasma samples from 58 GBM patients and 20 patients with nonglial tumors and 30 healthy controls were obtained. SCF levels were measured by employing the enzyme-linked immunosorbent assay test and the values were compared between these three groups. Then, the association of SCF plasma level and tumor volume, progression-free survival (PFS), and overall survival (OS) for the GBM patients were evaluated. RESULTS: Mean preoperative SCF plasma level of the GBM patients (2.80 ± 1.52 ng/ml) was significantly higher (p < 0.0001) than the healthy controls (0.80 ± 0.24 ng/ml) and patients with nonglial tumor (1.41 ± 0.76 ng/ml). Receiver operating characteristic analysis revealed that the preoperative SCF plasma level could distinguish the GBM patients from healthy controls and patients with nonglial tumors with the area under curve values of 0.915 and 0.790, respectively. However, no significant association was observed between the GBM patients' preoperative SCF plasma levels and tumors' volume (Spearman Rho correlation coefficient, 0.1847; 95% CI, p = 0.1652). The GBM patients were divided into two subgroups based on mean preoperative SCF plasma levels (2.80 ng/ml). No significant difference was observed between the patients' PFS (p = 0.3792) and OS (p = 0.1469) at these two subgroups. CONCLUSION: Taking together, the SCF plasma level can serve as a novel diagnostic blood-circulating biomarker for patients with GBM. However, its plasma level is not correlated with GBM patients' tumor volume, PFS, or OS.

Early Detection of Radiation-Induced Injury and Prediction of Cognitive Deficit by MRS Metabolites in Radiotherapy of Low-Grade Glioma.

PURPOSE: To compare the sensitivity of MRS metabolites and MoCA and ACE-R cognitive tests in the detection of radiation-induced injury in low grade glioma (LGG) patients in early and early delayed postradiation stages. METHODS: MRS metabolite ratios of NAA/Cr and Cho/Cr, ACE-R and MoCA cognitive tests, and dosimetric parameters in corpus callosum were analyzed during RT and up to 6-month post-RT for ten LGG patients. RESULTS: Compared to pre RT baseline, a significant decline in both NAA/Cr and Cho/Cr in the corpus callosum was seen at the 4th week of RT, 1, 3, and 6-month post-RT. These declines were detected at least 3 months before the detection of declines in cognitive functions by ACE-R and MoCA tools. Moreover, NAA/Cr alterations at 4th week of RT and 1-month post-RT were significantly negatively correlated with the mean dose received by the corpus callosum, as well as the corpus callosum 40 Gy dose volume, i.e., the volume of the corpus callosum receiving a dose greater than 40 Gy. CONCLUSION: MRS-based biomarkers may be more sensitive than the state-of-the-art cognitive tests in the prediction of postradiation cognitive impairments. They would be utilized in treatment planning and dose sparing protocols, with a specific focus on the corpus callosum in the radiation therapy of LGG patients.

Improvement of metallic artifacts in computed tomography in the absence of artifact reduction algorithms for spinal treatment planning applications.

AIM OF STUDY: The goal of this research was to investigate if application of optimized imaging parameters, recommended in literature, would be effective in producing the image quality required for treatment planning of spinal radiation fields with metallic implants. MATERIALS AND METHODS: CT images from an anthropomorphic torso phantom with and without spinal implants were acquired using different imaging protocols: raising kVp and mAs, reducing the pitch and applying an extended CT scale (ECTS) technique. Profiles of CT number (CT#) were produced using DICOM data of each image. The effect of artifact on dose calculation accuracy was investigated using the image data in the absence of implant as a reference and the recommended electron density tolerance levels (Δρe). RESULTS: Raising the kVp was the only method that produced improvement to some degree in CT# in artifact regions. Application of ECTS improved CT# values only for metal. CONCLUSIONS: Although raising the kVp was effective in reducing metallic artifact, the significance of this effect on Δρe values in corrected images depends on the required tolerance for treatment planning dose calculation accuracy. ECTS method was only successful in correcting the CT number range in the metal. Although, application of ECTS method did not have any effect on artifact regions, its use is necessary in order to improve delineation of metal and accuracy of attenuation calculations in metal, provided that the treatment planning system can use an extended CT# calibration curve. Also, for Monte Carlo calculations using patient's images, ECTS-post-processed-CT images improve dose calculation accuracy for impure metals.