Patient-Specific Quality Assurance in Pencil Beam Scanning by 2-Dimensional Array

Purpose: This study aimed to determine the characteristics of 2D ionization chamber array and the confidence limits of the gamma passing rate in pencil beam scanning proton therapy. Materials and Methods: The Varian ProBeam Compact spot-scanning system and the PTW OCTAVIUS 1500XDR array were used as a proton therapy system and detector, respectively. Our methods consisted of 2 parts: (1) the characteristics of the detector were tested and (2) patient-specific quality assurance was performed and evaluated by gamma analysis using dose-difference and distance-to-agreement criteria of 3% and 2 mm, respectively, with 123 treatment plans in head and neck, breast, chest, abdomen, and pelvic regions. Results: The PTW OCTAVIUS 1500XDR array had good reproducibility, uniformity, linearity, repetition rate, and monitor unit per spot within 0.1%, with accuracy, energy dependence, and measurement depth within 0.5%. The overall uncertainty of the PTW OCTAVIUS 1500XDR array was 2.49%. For field size and range shifter, using gamma analysis, the passing rate was 100%. The overall results of patient-specific quality assurance with the gamma evaluation were 98.9% ± 1.6% in 123 plans and confidence limit was 95.7%. Conclusion: The PTW OTAVIUS 1500XDR offered effective performance in pencil beam scanning proton therapy

LINE-1 methylation status of endogenous DNA double-strand breaks

DNA methylation and the repair of DNA double-strand breaks (DSBs) are important processes for maintaining genomic integrity. Although DSBs can be produced by numerous agents, they also occur spontaneously as endogenous DSBs (EDSBs). In this study, we evaluated the methylation status of EDSBs to determine if there is a connection between DNA methylation and EDSBs. We utilized interspersed repetitive sequence polymerase chain reaction (PCR), ligation-mediated PCR and combined bisulfite restriction analysis to examine the extent of EDSBs and methylation at long interspersed nuclear element-1 (LINE-1) sequences nearby EDSBs. We tested normal white blood cells and several cell lines derived from epithelial cancers and leukemias. Significant levels of EDSBs were detectable in all cell types. EDSBs were also found in both replicating and non-replicating cells. We found that EDSBs contain higher levels of methylation than the cellular genome. This hypermethylation is replication independent and the methylation was present in the genome at the location prior to the DNA DSB. The differences in methylation levels between EDSBs and the rest of the genome suggests that EDSBs are differentially processed, by production, end-modification, or repair, depending on the DNA methylation status

Organ and Effective Doses from A Multidetector Computed Tomography in Chest Examination

The growth of Multidetector Computed Tomography (MDCT) associated with the large number of images per examination offers many clinical benefits. It is easy to use for radiologist and physician, and these reasons are the cause of increasing exposure for populations rapidly. Organ and effective doses from CT examination are the important quantities to assess radiation risk. The objective of this study is to calculate the organ and effective doses from patient data. The beam data was collected for 30 cases of patient over 20 years old underwent 64 slices GE VCT MDCT scanner in the chest examinations. The computed tomography dose index (CTDI) values were measured in air and in body phantom with SOLIDOSE ionization chamber then the CTDI values and the exposed parameters were entered in ImPACT CT Patient Dosimetry Calculator version 1.0 for calculation of organ and effective doses. The exposure parameters of chest protocol were 120 kVp, 330 mA, 0.6 sec rotation time, and 1.375 pitch. The average scan length was 34.9 cm for the range of 23.1 to 56.5 cm. The high organ doses in the irradiated field occurred in lung, breast, esophagus, heart, stomach, liver, adrenal gland, kidney, pancreas, spleen and small intestine, the maximum dose ranged from 15 to 23.0 mGy. The average effective dose was 8.6 mSv with the range of 5.7 to 13.0 mSv.  The maximum number of scan series of examination was three which made the maximum effective dose of 39.0 mSv. The scan length was one of the variable factors that made the higher organ and effective doses in CT examination. The more series of examination was another factor to increase the organ and effective doses. The estimated radiation risk for cancer and hereditary effect for chest CT examination was about 5 cases for 10,000 populations. This study has shown that the CT doses used in clinical practice are not higher than commonly report but the careful used of radiation must be considered. Estimated organ and effective doses in chest MDCT scanning are a guide line for radiologists and physicians in order to judge the frequency of scan and suitable scan length. Keywords: organ dose, effective dose, Computed Tomography Dose Index, Multidetector Computed Tomograph

Evaluation of a new method for metal artifact reducing in computed tomographic images

Background: The common streak artifacts in computed tomographic (CT) images result from metal implants in patients. Metal artifact suppresses and obstructs diagnosis or misdiagnoses as it occurred in ten percent of the patients’ tomographic images. Objectives: To develop the method for metal artifact reduction in CT images using MATLAB software and implement it in phantoms with the metal artifact as well as in patients with the metal artifact in the head and neck region. Materials and methods: The new method of metal artifact reduction in CT images using MATLAB software. The homogeneous polymethylmethacrylate (PMMA) phantom, the Alderson Rando phantom, and patients with a metal implant in the head and neck region were scanned by the Philips Brilliance Big Bore CT system. Commercial orthopedic metal artifact reduction (OMAR) software and a new method software were applied to the CT images of phantoms and patients. The quantitative analysis of image quality on a metal artifact of the head and neck region was evaluated in the percent noise. The qualitative analysis in clinical imaging was evaluated in scoring by two radiologists with the same experience. Results: In the Alderson Rando phantom, the new algorithm indicated higher efficiency in metal artifact reduction than OMAR software. In contrast, for the patient at head and neck CT images with metal artifact reduction, OMAR, and the new method showed comparable results. The new method suppressed the artifact in homogeneous PMMA, Alderson Rando phantoms, and patients with a metal implant in the head and neck region with approximately 40%, 40%, and 60% percentage of noise reduction, respectively. The qualitative analysis by two radiologists showed comparable results of OMAR and the new method. Conclusion: The efficiency of metal artifact reduction of the new method is better than no correction and OMAR in homogeneous PMMA phantom and Alderson Rando phantom. However, the efficiency of OMAR is better than the new method, and no correction regarding the percent noise.</p

Multimodality radiomics for tumor prognosis in nasopharyngeal carcinoma.

BackgroundThe prognosis of nasopharyngeal carcinoma (NPC) is challenging due to late-stage identification and frequently undetectable Epstein-Barr virus (EBV) DNA. Incorporating radiomic features, which quantify tumor characteristics from imaging, may enhance prognosis assessment.PurposeTo investigate the predictive power of radiomic features on overall survival (OS), progression-free survival (PFS), and distant metastasis-free survival (DMFS) in NPC.Materials and methodsA retrospective analysis of 183 NPC patients treated with chemoradiotherapy from 2010 to 2019 was conducted. All patients were followed for at least three years. The pretreatment CT images with contrast medium, MR images (T1W and T2W), as well as gross tumor volume (GTV) contours, were used to extract radiomic features using PyRadiomics v.2.0. Robust and efficient radiomic features were chosen using the intraclass correlation test and univariate Cox proportional hazard regression analysis. They were then combined with clinical data including age, gender, tumor stage, and EBV DNA level for prognostic evaluation using Cox proportional hazard regression models with recursive feature elimination (RFE) and were optimized using 20 repetitions of a five-fold cross-validation scheme.ResultsIntegrating radiomics with clinical data significantly enhanced the predictive power, yielding a C-index of 0.788 ± 0.066 to 0.848 ± 0.079 for the combined model versus 0.745 ± 0.082 to 0.766 ± 0.083 for clinical data alone (pConclusionsThe combination of multimodality radiomic features from CT and MR images could offer superior predictive performance for OS, PFS, and DMFS compared to relying on conventional clinical data alone

Improved prediction of radiation-induced hypothyroidism in nasopharyngeal carcinoma using pre-treatment CT radiomics

Abstract When planning radiation therapy, late effects due to the treatment should be considered. One of the most common complications of head and neck radiation therapy is hypothyroidism. Although clinical and dosimetric data are routinely used to assess the risk of hypothyroidism after radiation, the outcome is still unsatisfactory. Medical imaging can provide additional information that improves the prediction of hypothyroidism. In this study, pre-treatment computed tomography (CT) radiomics features of the thyroid gland were combined with clinical and dosimetric data from 220 participants to predict the occurrence of hypothyroidism within 2 years after radiation therapy. The findings demonstrated that the addition of CT radiomics consistently and significantly improves upon conventional model, achieving the highest area under the receiver operating characteristic curve (AUCs) of 0.81 ± 0.06 with a random forest model. Hence, pre-treatment thyroid CT imaging provides useful information that have the potential to improve the ability to predict hypothyroidism after nasopharyngeal radiation therapy

Epigallocatechin-3-gallate protects pro-acinar epithelia against salivary gland radiation injury

10.3390/ijms22063162International Journal of Molecular Sciences226Jan-1

Clinical features and their coefficients in the clinical model for prediction.

(A) overall survival (OS), (B) progression-free survival (PFS), and (C) distant metastasis-free survival (DMFS) in patients with nasopharyngeal carcinoma. (PDF)</p

Patient demographics.

BackgroundThe prognosis of nasopharyngeal carcinoma (NPC) is challenging due to late-stage identification and frequently undetectable Epstein-Barr virus (EBV) DNA. Incorporating radiomic features, which quantify tumor characteristics from imaging, may enhance prognosis assessment.PurposeTo investigate the predictive power of radiomic features on overall survival (OS), progression-free survival (PFS), and distant metastasis-free survival (DMFS) in NPC.Materials and methodsA retrospective analysis of 183 NPC patients treated with chemoradiotherapy from 2010 to 2019 was conducted. All patients were followed for at least three years. The pretreatment CT images with contrast medium, MR images (T1W and T2W), as well as gross tumor volume (GTV) contours, were used to extract radiomic features using PyRadiomics v.2.0. Robust and efficient radiomic features were chosen using the intraclass correlation test and univariate Cox proportional hazard regression analysis. They were then combined with clinical data including age, gender, tumor stage, and EBV DNA level for prognostic evaluation using Cox proportional hazard regression models with recursive feature elimination (RFE) and were optimized using 20 repetitions of a five-fold cross-validation scheme.ResultsIntegrating radiomics with clinical data significantly enhanced the predictive power, yielding a C-index of 0.788 ± 0.066 to 0.848 ± 0.079 for the combined model versus 0.745 ± 0.082 to 0.766 ± 0.083 for clinical data alone (ppConclusionsThe combination of multimodality radiomic features from CT and MR images could offer superior predictive performance for OS, PFS, and DMFS compared to relying on conventional clinical data alone.</div