Evaluation of Dosimetry Formalisms in Intraoperative Radiation Therapy of Glioblastoma.

PURPOSE: The intraoperative radiotherapy in newly diagnosed glioblastoma multiforme (INTRAGO) clinical trial assesses survival in patients with glioblastoma treated with intraoperative radiation therapy (IORT) using the INTRABEAM. Treatment planning for INTRABEAM relies on vendor-provided in-water depth dose curves obtained according to the TARGeted Intraoperative radioTherapy (TARGIT) dosimetry protocol. However, recent studies have shown discrepancies between the estimated TARGIT and delivered doses. This work evaluates the effect of the choice of dosimetry formalism on organs at risk (OAR) doses. METHODS AND MATERIALS: A treatment planning framework for INTRABEAM was developed to retrospectively calculate the IORT dose in 8 INTRAGO patients. These patients received an IORT prescription dose of 20 to 30 Gy in addition to external beam radiation therapy. The IORT dose was obtained using (1) the TARGIT method; (2) the manufacturer's V4.0 method; (3) the CQ method, which uses an ionization chamber Monte Carlo (MC) calculated factor; (4) MC dose-to-water; and (5) MC dose-to-tissue. The IORT dose was converted to 2 Gy fractions equivalent dose. RESULTS: According to the TARGIT method, the OAR dose constraints were respected in all cases. However, the other formalisms estimated a higher mean dose to OARs and revealed 1 case where the constraint for the brain stem was exceeded. The addition of the external beam radiation therapy and TARGIT IORT doses resulted in 10 cases of OARs exceeding the dose constraints. The more accurate MC calculation of dose-to-tissue led to the highest dosimetric differences, with 3, 3, 2, and 2 cases (out of 8) exceeding the dose constraint to the brain stem, optic chiasm, optic nerves, and lenses, respectively. Moreover, the mean cumulative dose to brain stem exceeded its constraint of 66 Gy with the MC dose-to-tissue method, which was not evident with the current INTRAGO clinical practice. CONCLUSIONS: The current clinical approach of calculating the IORT dose with the TARGIT method may considerably underestimate doses to nearby OARs. In practice, OAR dose constraints may have been exceeded, as revealed by more accurate methods.

Monte Carlo calculation of the TG-43 dosimetry parameters for the INTRABEAM source with spherical applicators.

OBJECTIVE: The relative TG-43 dosimetry parameters of the INTRABEAM (Carl Zeiss Meditec AG, Jena, Germany) bare probe were recently reported by Ayala Alvarezet al(2020Phys. Med. Biol.65245041). The current study focuses on the dosimetry characterization of the INTRABEAM source with the eight available spherical applicators according to the TG-43 formalism using Monte Carlo (MC) simulations. APPROACH: This report includes the calculated dose-rate conversion coefficients that determine the absolute dose rate to water at a reference point of 10 mm from the applicator surface, based on calibration air-kerma rate measurements at 50 cm from the source on its transverse plane. Since the air-kerma rate measurements are not yet provided from a standards laboratory for the INTRABEAM, the values in the present study were calculated with MC. This approach is aligned with other works in the search for standardization of the dosimetry of electronic brachytherapy sources. As a validation of the MC model, depth dose calculations along the source axis were compared with calibration data from the source manufacturer. MAIN RESULTS: The calculated dose-rate conversion coefficients were 434.0 for the bare probe, and 683.5, 548.3, 449.9, 376.5, 251.0, 225.6, 202.8, and 182.6 for the source with applicators of increasing diameter from 15 to 50 mm, respectively. The radial dose and the 2D anisotropy functions of the TG-43 formalism were also obtained and tabulated in this document. SIGNIFICANCE: This work presents the data required by a treatment planning system for the characterization of the INTRABEAM system in the context of intraoperative radiotherapy applications.

Clinical Implication of Dosimetry Formalisms for Electronic Low-Energy Photon Intraoperative Radiation Therapy.

PURPOSE: Intraoperative radiation therapy (IORT) using the INTRABEAM, a miniature x-ray source, has shown to be effective in treating breast cancer. However, recent investigations have suggested a significant deviation between the reported and delivered doses. In this work, the dose delivered by INTRABEAM in the TARGIT breast protocol was investigated, along with the dose from the Xoft Axxent, another source used in breast IORT. METHODS AND MATERIALS: The absorbed dose from the INTRABEAM was determined from ionization chamber measurements using: (a) the manufacturer-recommended formula (Zeiss V4.0 method), (b) a Monte Carlo calculated chamber conversion factor (CQ method), and (c) the formula consistent with the TARGIT breast protocol (TARGIT method). The dose from the Xoft Axxent was determined from ionization chamber measurements using the Zeiss V4.0 method and calculated using the American Association of Physicists in Medicine TG-43 formalism. RESULTS: For a nominal TARGIT prescription of 20 Gy, the dose at the INTRABEAM applicator surface ranged from 25.2 to 31.7 Gy according to the CQ method for the largest (5 cm) and smallest (1.5 cm) diameter applicator, respectively. The Zeiss V4.0 method results were 7% to 10% lower (23.2 to 28.6 Gy). At 1 cm depth, the CQ and Zeiss V4.0 absorbed doses were also larger than those predicted by the TARGIT method. The dose at 1 cm depth from the Xoft Axxent for a surface dose of 20 Gy was slightly less than INTRABEAM (3%-7% compared with CQ method). An exception was for the 3 cm applicator, where the Xoft dose was appreciably lower (31%). CONCLUSIONS: The doses delivered in the TARGIT breast protocol with INTRABEAM were significantly greater than the prescribed 20 Gy and depended on the size of spherical applicator used. Breast IORT treatments with the Xoft Axxent received less dose compared with TARGIT INTRABEAM, which could have implications for studies comparing clinical outcomes between the 2 devices.

An investigation into the INTRABEAM miniature x-ray source dosimetry using ionization chamber and radiochromic film measurements.

PURPOSE: Intraoperative radiotherapy using The INTRABEAM System (Carl Zeiss Meditec AG, Jena, Germany), a miniature low-energy x-ray source, has proven to be an effective modality in the treatment of breast cancer. However, some uncertainties remain in its dosimetry. In this work, we investigated the INTRABEAM system dosimetry by performing ionization chamber and radiochromic film measurements of absorbed dose in a water phantom. METHODS: Ionization chamber measurements were performed with a PTW 34013 parallel-plate soft x-ray chamber at source to detector distances of 5 to 30 mm calculated using (a) the dose formula consistent with the TARGIT breast protocol (TARGIT), (b) the formula recommended by the manufacturer (Zeiss), and (c) the recently proposed CQ formalism of Watson et al. (Physics in Medicine & Biology, 2018;63:015016) EBT3 Gafchromic film measurements were made at the same depths in water. To account for the energy dependence of EBT3 film, multiple dose response calibration curves were employed across a range of photon beam qualities relevant to the INTRABEAM spectrum in water. RESULTS: At all depths investigated, the TARGIT dose was significantly lower than that measured by the Zeiss and CQ methods, as well as film. These dose differences ranged from 14% to as large as 80%. In general, the doses measured by film, and the Zeiss and CQ methods were in good agreement to within measurement uncertainties (5-6%). CONCLUSIONS: These results suggest that the TARGIT dose underestimates the physical dose to water from the INTRABEAM source. Understanding the correlation between the TARGIT and physical dose is important for any studies wishing to make dosimetric comparisons between the INTRABEAM and other radiation emitting devices.

Determination of absorbed dose to water from a miniature kilovoltage x-ray source using a parallel-plate ionization chamber.

Electronic brachytherapy sources are widely accepted as alternatives to radionuclide-based systems. Yet, formal dosimetry standards for these devices to independently complement the dose protocol provided by the manufacturer are lacking. This article presents a formalism for calculating and independently verifying the absorbed dose to water from a kV x-ray source (The INTRABEAM System) measured in a water phantom with an ionization chamber calibrated in terms of air-kerma. This formalism uses a Monte Carlo (MC) calculated chamber conversion factor, [Formula: see text], to convert air-kerma in a reference beam to absorbed dose to water in the measurement beam. In this work [Formula: see text] was determined for a PTW 34013 parallel-plate ionization chamber. Our results show that [Formula: see text] was sensitive to the chamber plate separation tolerance, with differences of up to 15%. [Formula: see text] was also found to have a depth dependence which varied with chamber plate separation (0 to 10% variation for the smallest and largest cavity height, over 3 to 30 mm depth). However for all chamber dimensions investigated, [Formula: see text] was found to be significantly larger than the manufacturer reported value, suggesting that the manufacturer recommended method of dose calculation could be underestimating the dose to water.

Technical Note: Effect of explicit M and N-shell atomic transitions on a low-energy x-ray source.

PURPOSE: In EGSnrc, atomic transitions to and from the M and N-shells are treated in an average way by default. This approach is justified in which the energy difference between explicit and average M and N-shell binding energies is less than 1 keV, and for most applications can be considered negligible. However, for simulations of low energy x-ray sources on thin, high-Z targets, characteristic x-rays can make up a significant portion of the source spectra. As of release V4-2.4.0, EGSnrc has included an option to enable a more complete algorithm of all atomic transitions available in the EADL compilation. In this paper, the effect of M and N-shell averaging on the calculation of half-value layer (HVL) and relative depth dose (RDD) curve of a 50 kVp intraoperative x-ray tube with a thin gold target was investigated. METHODS: A 50 kVp miniature x-ray source with a gold target (The INTRABEAM System, Carl Zeiss, Germany) was modeled with the EGSnrc user code cavity, both with and without M and N-shell averaging. From photon fluence spectra simulations, the source HVLs were determined analytically. The same source model was then used with egs_chamber to calculate RDD curves in water. RESULTS: A 4% increase of HVL was reported when accounting for explicit M and N-shell transitions, and up to a 9% decrease in local relative dose for normalization at 3 mm depth in water. CONCLUSIONS: The EGSnrc default of using averaged M and N-shell binding energies has an observable effect on the HVL and RDD of a low energy x-ray source with high-Z target. For accurate modeling of this class of devices, explicit atomic transitions should be included.

Implementation of an efficient Monte Carlo calculation for CBCT scatter correction: phantom study.

Cone-beam computed tomography (CBCT) images suffer from poor image quality, in a large part due to contamination from scattered X-rays. In this work, a Monte Carlo (MC)-based iterative scatter correction algorithm was implemented on measured phantom data acquired from a clinical on-board CBCT scanner. An efficient EGSnrc user code (egs_cbct) was used to transport photons through an uncorrected CBCT scan of a Catphan 600 phantom. From the simulation output, the contribution from primary and scattered photons was estimated in each projection image. From these estimates, an iterative scatter correction was performed on the raw CBCT projection data. The results of the scatter correction were compared with the default vendor reconstruction. The scatter correction was found to reduce the error in CT number for selected regions of interest, while improving contrast-to-noise ratio (CNR) by 18%. These results demonstrate the performance of the proposed scatter correction algorithm in improving image quality for clinical CBCT images.

Metabolic outcomes in young children with type 1 diabetes differ between treatment centers: the Hvidoere Study in Young Children 2009.

OBJECTIVE: To investigate whether center differences in glycemic control are present in prepubertal children <11 yr with type 1 diabetes mellitus. RESEARCH DESIGN AND METHODS: This cross-sectional study involved 18 pediatric centers worldwide. All children, <11 y with a diabetes duration ≥12 months were invited to participate. Case Record Forms included information on clinical characteristics, insulin regimens, diabetic ketoacidosis (DKA), severe hypoglycemia, language difficulties, and comorbidities. Hemoglobin A1c (HbA1c) was measured centrally by liquid chromatography (DCCT aligned, range: 4.4-6.3%; IFFC: 25-45 mmol/mol). RESULTS: A total of 1133 children participated (mean age: 8.0 ± 2.1 y; females: 47.5%, mean diabetes duration: 3.8 ± 2.1 y). HbA1c (overall mean: 8.0 ± 1.0%; range: 7.3-8.9%) and severe hypoglycemia frequency (mean 21.7 events per 100 patient-years), but not DKA, differed significantly between centers (p < 0.001 resp. p = 0.179). Language difficulties showed a negative relationship with HbA1c (8.3 ± 1.2% vs. 8.0 ± 1.0%; p = 0.036). Frequency of blood glucose monitoring demonstrated a significant but weak association with HbA1c (r = -0.17; p < 0.0001). Although significant different HbA1c levels were obtained with diverse insulin regimens (range: 7.3-8.5%; p < 0.001), center differences remained after adjusting for insulin regimen (p < 0.001). Differences between insulin regimens were no longer significant after adjusting for center effect (p = 0.199). CONCLUSIONS: Center differences in metabolic outcomes are present in children <11 yr, irrespective of diabetes duration, age, or gender. The incidence of severe hypoglycemia is lower than in adolescents despite achieving better glycemic control. Insulin regimens show a significant relationship with HbA1c but do not explain center differences. Each center's effectiveness in using specific treatment strategies remains the key factor for outcome.

Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.).

Genomic selection can increase genetic gain per generation through early selection. Genomic selection is expected to be particularly valuable for traits that are costly to phenotype and expressed late in the life cycle of long-lived species. Alternative approaches to genomic selection prediction models may perform differently for traits with distinct genetic properties. Here the performance of four different original methods of genomic selection that differ with respect to assumptions regarding distribution of marker effects, including (i) ridge regression-best linear unbiased prediction (RR-BLUP), (ii) Bayes A, (iii) Bayes Cπ, and (iv) Bayesian LASSO are presented. In addition, a modified RR-BLUP (RR-BLUP B) that utilizes a selected subset of markers was evaluated. The accuracy of these methods was compared across 17 traits with distinct heritabilities and genetic architectures, including growth, development, and disease-resistance properties, measured in a Pinus taeda (loblolly pine) training population of 951 individuals genotyped with 4853 SNPs. The predictive ability of the methods was evaluated using a 10-fold, cross-validation approach, and differed only marginally for most method/trait combinations. Interestingly, for fusiform rust disease-resistance traits, Bayes Cπ, Bayes A, and RR-BLUB B had higher predictive ability than RR-BLUP and Bayesian LASSO. Fusiform rust is controlled by few genes of large effect. A limitation of RR-BLUP is the assumption of equal contribution of all markers to the observed variation. However, RR-BLUP B performed equally well as the Bayesian approaches.The genotypic and phenotypic data used in this study are publically available for comparative analysis of genomic selection prediction models.

Accelerating the domestication of trees using genomic selection: accuracy of prediction models across ages and environments.

• Genomic selection is increasingly considered vital to accelerate genetic improvement. However, it is unknown how accurate genomic selection prediction models remain when used across environments and ages. This knowledge is critical for breeders to apply this strategy in genetic improvement. • Here, we evaluated the utility of genomic selection in a Pinus taeda population of c. 800 individuals clonally replicated and grown on four sites, and genotyped for 4825 single-nucleotide polymorphism (SNP) markers. Prediction models were estimated for diameter and height at multiple ages using genomic random regression best linear unbiased predictor (BLUP). • Accuracies of prediction models ranged from 0.65 to 0.75 for diameter, and 0.63 to 0.74 for height. The selection efficiency per unit time was estimated as 53-112% higher using genomic selection compared with phenotypic selection, assuming a reduction of 50% in the breeding cycle. Accuracies remained high across environments as long as they were used within the same breeding zone. However, models generated at early ages did not perform well to predict phenotypes at age 6 yr. • These results demonstrate the feasibility and remarkable gain that can be achieved by incorporating genomic selection in breeding programs, as long as models are used at the relevant selection age and within the breeding zone in which they were estimated.

Hydraulic architecture and tracheid allometry in mature Pinus palustris and Pinus elliottii trees.

Pinus palustris Mill. (longleaf pine, LL) and Pinus elliottii Engelm. var. elliottii (slash pine, SL) frequently co-occur in lower coastal plain flatwoods of the USA, with LL typically inhabiting slightly higher and better-drained microsites than SL. The hydraulic architecture and tracheid dimensions of roots, trunk and branches of mature LL and SL trees were compared to understand their role in species microsite occupation. Root xylem had higher sapwood-specific hydraulic conductivity (k(s)) and was less resistant to cavitation compared with branches and trunk sapwood. Root k(s) of LL was significantly higher than SL, whereas branch and trunk k(s) did not differ between species. No differences in vulnerability to cavitation were observed in any of the organs between species. Across all organs, there was a significant but weak trade-off between water conduction efficiency and safety. Tracheid hydraulic diameter (D(h)) was strongly correlated with k(s) across all organs, explaining >73% of the variation in k(s). In contrast, tracheid length (L(t)) explained only 2.4% of the variability. Nevertheless, for trunk xylem, k(s) was 39.5% higher at 20 m compared with 1.8 m; this increase in k(s) was uncorrelated with D(h) and cell-wall thickness but was strongly correlated with the difference in L(t). Tracheid allometry markedly changed between sapwood of roots, trunks and branches, possibly reflecting different mechanical constraints. Even though vulnerability to cavitation was not different for sapwood of roots, branches or the trunks of LL and SL, higher sapwood to leaf area ratio and higher maximum sapwood-specific hydraulic conductivity in roots of LL are functional traits that may provide LL with a competitive advantage on drier soil microsites.

Multinational study in children and adolescents with newly diagnosed type 1 diabetes: association of age, ketoacidosis, HLA status, and autoantibodies on residual beta-cell function and glycemic control 12 months after diagnosis.

OBJECTIVE: To identify predictors of residual beta-cell function and glycemic control during the first 12 months after the diagnosis of type 1 diabetes (T1D). SUBJECTS AND METHODS: Clinical information and blood samples were collected from 275 children. HbA1c, antibodies, HLA typing and mixed meal-stimulated C-peptide levels 1, 6, and 12 months after diagnosis were analyzed centrally. RESULTS: Mean age at diagnosis was 9.1 yr. DKA with standard bicarbonate <15 mmol/L was associated with significantly poorer residual beta-cell function 1 (p = 0.004) and 12 months (p = 0.0003) after diagnosis. At 12 months, the decline in stimulated C-peptide levels compared with the levels at 1 month was 69% in the youngest age group and 50% in patients 10 yr and above (p < 0.001). Stimulated C-peptide at 12 months was predicted by younger age (p < 0.02) and bicarbonate levels at diagnosis (p = 0.005), and by stimulated C-peptide (p < 0.0001), postmeal blood glucose (p = 0.0004), insulin antibodies (IA; p = 0.02) and glutamic acid decarboxylase antibodies (GADA; p = 0.0004) at 1 month. HbA1c at 12 months was predicted by HbA1c at diagnosis (p < 0.0001), GADA at 1 month (p = 0.01), and non-white Caucasian ethnicity (p = 0.002). CONCLUSIONS: Younger age, ketoacidosis at diagnosis, and IA and GADA 1 month after diagnosis were the strongest explanatory factors for residual beta-cell function at 12 months. Glycemic control at 12 months was influenced predominantly by ethnicity, HbA1c at diagnosis, and GADA at 1 month.

Continuing stability of center differences in pediatric diabetes care: do advances in diabetes treatment improve outcome? The Hvidoere Study Group on Childhood Diabetes.

OBJECTIVE: To reevaluate the persistence and stability of previously observed differences between pediatric diabetes centers and to investigate the influence of demography, language communication problems, and changes in insulin regimens on metabolic outcome, hypoglycemia, and ketoacidosis. RESEARCH DESIGN AND METHODS: This was an observational cross-sectional international study in 21 centers, with clinical data obtained from all participants and A1C levels assayed in one central laboratory. All individuals with diabetes aged 11-18 years (49.4% female), with duration of diabetes of at least 1 year, were invited to participate. Fourteen of the centers participated in previous Hvidoere Studies, allowing direct comparison of glycemic control across centers between 1998 and 2005. RESULTS: Mean A1C was 8.2 +/- 1.4%, with substantial variation between centers (mean A1C range 7.4-9.2%; P < 0.001). There were no significant differences between centers in rates of severe hypoglycemia or diabetic ketoacidosis. Language difficulties had a significant negative impact on metabolic outcome (A1C 8.5 +/- 2.0% vs. 8.2 +/- 1.4% for those with language difficulties vs. those without, respectively; P < 0.05). After adjustement for significant confounders of age, sex, duration of diabetes, insulin regimen, insulin dose, BMI, and language difficulties, the center differences persisted, and the effect size for center was not reduced. Relative center ranking since 1998 has remained stable, with no significant change in A1C. CONCLUSIONS: Despite many changes in diabetes management, major differences in metabolic outcome between 21 international pediatric diabetes centers persist. Different application between centers in the implementation of insulin treatment appears to be of more importance and needs further exploration.