Validation of an individualized home-made superficial brachytherapy mold applied for deep nonmelanoma skin cancer

Background: This study was conducted to evaluate the effect of brachytherapy (BT) customized mold [Condensation silicone elastomer (ProtesilTM)] and its thickness on the dose distribution pattern of deep nonmelanoma skin cancers (NMSC). Materials and methods: Four blocks of mold material were constructed in 5, 10, 15, and 20 mm thickness and 100 × 100 mm2 area by a plastic cast. The high dose rate (HDR) plus treatment planning system (TPS) (Version 3, Eckert & Ziegler BEBIG Gmbh, Berlin, Germany) with a 60Co source (model: Co0.A86, EZAG BEBIG, Berlin, Germany) as an high dose rate brachytherapy (HDR-BT) source was used. Solid phantom and MOSFETTM and GAFCHROMICTM EBT3 film dosimeters were used for experimental dosimetry of the different thicknesses (up to 20 mm) of BT customized mold. Skin dose and dose to different depths were evaluated. Result: The TPS overestimated the calculated dose to the surface. Skin dose can be reduced from 250% to 150% of the prescription dose by increasing mold thickness from 5 mm to 20 mm. There was a 7.7% difference in the calculated dose by TPS and the measured dose by MOSFET. There was a good agreement between film dosimetry, MOSFET detector, and TPS’ results in depths less than 5 mm. Conclusion: Each BT department should validate any individualized material chosen to construct the customized surface BT mold. Increasing the mold thickness can treat lesions without overexposing the skin surface. Superficial BT can be recommended as an appropriate treatment option for some deep NMSC lesions (up to 20 mm) with pre-planning considerations employing thicker molds

Correlation between gastric volume and organs at risk dose in adjuvant radiotherapy for left breast cancer

BACKGROUND: The role of the gastric volume on the dose-effect relationship for these organs has not been investigated. The aim of the study was to evaluate the correlation between gastric volume and dose-volume histogram (DVH) parameters of the heart, left lung and stomach during left breast cancer radiotherapy (RT). MATERIALS AND METHODS: Ninety-nine left breast cancer patients who got adjuvant radiotherapy were included. Study was classified into two groups based on treatment field arrangements: 1) breast tangential fields only (T) and 2) breast tangential and supraclavicular fields (TS). Organs DVHs were extracted. Descriptive statistics, Pearson correlation, linear regression analyses, and receiver operating characteristic (ROC) analyses were performed. RESULTS: There is a direct but not significant correlation between the gastric volume and doses to the stomach and left lung. For a 100-cc increase in the gastric volume, the stomach maximum dose and the V50 increased by 3 Gy and 4%, respectively. For the left lung, V4 and V5 increased by 1% for TS cases. Considering ROC analysis results, one can make a decision for about 74% of patients due to their left lung DVH parameters, using gastric volume as a known input data. The correlation between gastric volume and heart dose was not significant. CONCLUSIONS: The gastric volume of about 170 cc or less can result in lower dose to the stomach and ipsilateral lung during left breast cancer radiotherapy, especially for TS cases. To reach this gastric volume threshold, patients should be fast for 2 hours before the procedure of CT simulation and treatment

Artificial neural network based gynaecological image-guided adaptive brachytherapy treatment planning correction of intra-fractional organs at risk dose variation

Purpose : Intra-fractional organs at risk (OARs) deformations can lead to dose variation during image-guided adaptive brachytherapy (IGABT). The aim of this study was to modify the final accepted brachytherapy treatment plan to dosimetrically compensate for these intra-fractional organs-applicators position variations and, at the same time, fulfilling the dosimetric criteria. Material and methods : Thirty patients with locally advanced cervical cancer, after external beam radiotherapy (EBRT) of 45-50 Gy over five to six weeks with concomitant weekly chemotherapy, and qualified for intracavitary high-dose-rate (HDR) brachytherapy with tandem-ovoid applicators were selected for this study. Second computed tomography scan was done for each patient after finishing brachytherapy treatment with applicators in situ. Artificial neural networks (ANNs) based models were used to predict intra-fractional OARs dose-volume histogram parameters variations and propose a new final plan. Results : A model was developed to estimate the intra-fractional organs dose variations during gynaecological intracavitary brachytherapy. Also, ANNs were used to modify the final brachytherapy treatment plan to compensate dosimetrically for changes in ‘organs-applicators’, while maintaining target dose at the original level. Conclusions : There are semi-automatic and fast responding models that can be used in the routine clinical workflow to reduce individually IGABT uncertainties. These models can be more validated by more patients’ plans to be able to serve as a clinical tool

Predicting severe radiation-induced oral mucositis in head and neck cancer patients using integrated baseline CT radiomic, dosimetry, and clinical features: A machine learning approach

Purpose: To establish the early prediction models of radiation-induced oral mucositis (RIOM) based on baseline CT-based radiomic features (RFs), dosimetric data, and clinical features by machine learning models for head and neck cancer (HNC) patients. Methods: In this single-center prospective study, 49 HNCs treated with curative intensity modulated radiotherapy (IMRT) were enrolled. Baseline CT images (i.e., CT simulation), dosimetric, and clinical features were collected. RIOM was assessed using CTCAE v.5.0. RFs were extracted from manually-contoured oral mucosa structures. Minimum-redundancy-maximum-relevance (mRMR) method was applied to select the most informative radiomics, dosimetric, and clinical features. Then, binary prediction models were constructed for predicting acute RIOM based on the top mRMR-ranked radiomics, dosimetric, and clinical features alone or in combination, using random forest classifier algorithm. The predictive performance of models was assessed using the area under the receiver operating curve (AUC), accuracy, weighted-average based sensitivity, precision, and F1-measure. Results: Among extracted features, the top 10 RFs, the top 5 dose-volume features, and the top 5 clinical features were selected using mRMR method. The model exploiting the integrated features (10-radiomics + 5-dosimetric + 5-clinical) achieved the best prediction with AUC, accuracy, sensitivity, precision, and F1-measure values of 91.7 %, 90.0 %, 83.0 % 100.0 %, and 91.0 %, respectively. The model developed using baseline CT RFs alone provided the best performance compared to dose-volume features or clinical features alone, with an AUC of 87.0 %. Conclusion: Our results suggest that the integration of baseline CT radiomic features with dosimetric and clinical features showed promising potential to improve the performance of machine learning models in early prediction of RIOM. The ultimate goal is to personalize radiotherapy for HNC patients

Hydrogen nanobubbles: A novel approach toward radio-sensitization agents

Background: Ocular melanoma is a rare kind of eye malignancy that threatens the patient's eyesight. Radiotherapy and surgical removal are the most commonly used therapeutic modalities, and nanomedicine has lately entered this field. Brachytherapy using Ruthenium-106 (106Ru) ophthalmic plaques has been used for decades to treat ocular melanoma, with the applicator placed on the patient's eyes until the prescribed dose reaches the tumor apex. Purpose: To investigate the efficiency of hydrogen nanobubbles (H2-NBs) employment during intraocular melanoma brachytherapy using a106Ru electron emitter plaque. Methods: The Monte Carlo (MC) simulation and experimental investigation using a 3D-designed phantom and thermoluminescence dosimetry (TLD) were employed. Various concentrations of H2-NBs with a diameter of 100 nm were simulated inside tumor tissue. The results were presented as deposited energy and dose enhancement factor (DEF). An equivalent Resin phantom of the human eyeball was made using AutoCAD and 3D-Printer technologies. The glass-bead TLDs dosimeter were employed and placed inside the phantom. Results: Using a 1% concentration of H2-NBs, a DEF of 93% and 98% were achieved at the tumor apex of 10 mm from the experimental setup and MC simulation, respectively. For simulated concentrations of 0.1%, 0.3%, 0.5%, 1%, and 4% H2-NBs, a maximum dose enhancement of 154%, 174%, 188%, 200%, and 300% were achieved, respectively, and a dose reduction was seen at about 3 mm from the plaque surface. Conclusion: H2-NBs can be used as an absorbed dose enhancer in106Ru eye brachytherapy because of their unique physical characteristics. Reducing plaque implantation time on the patient's eye, reducing sclera absorbed dose, and decreasing the risk of patients' healthy organs irradiation are reported as some of the potential benefits of using H2-NBs.</p