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Technical note: precision and accuracy of a commercially available CT optically stimulated luminescent dosimetry system for the measurement of CT dose index.

ABSTRACT: To determine the precision and accuracy of CTDI(100) measurements made using commercially available optically stimulated luminescent (OSL) dosimeters (Landaur, Inc.) as beam width, tube potential, and attenuating material were varied.One hundred forty OSL dosimeters were individually exposed to a single axial CT scan, either in air, a 16-cm (head), or 32-cm (body) CTDI phantom at both center and peripheral positions. Scans were performed using nominal total beam widths of 3.6, 6, 19.2, and 28.8 mm at 120 kV and 28.8 mm at 80 kV. Five measurements were made for each of 28 parameter combinations. Measurements were made under the same conditions using a 100-mm long CTDI ion chamber. Exposed OSL dosimeters were returned to the manufacturer, who reported dose to air (in mGy) as a function of distance along the probe, integrated dose, and CTDI(100).The mean precision averaged over 28 datasets containing five measurements each was 1.4% ± 0.6%, range = 0.6%-2.7% for OSL and 0.08% ± 0.06%, range = 0.02%-0.3% for ion chamber. The root mean square (RMS) percent differences between OSL and ion chamber CTDI(100) values were 13.8%, 6.4%, and 8.7% for in-air, head, and body measurements, respectively, with an overall RMS percent difference of 10.1%. OSL underestimated CTDI(100) relative to the ion chamber 21∕28 times (75%). After manual correction of the 80 kV measurements, the RMS percent differences between OSL and ion chamber measurements were 9.9% and 10.0% for 80 and 120 kV, respectively.Measurements of CTDI(100) with commercially available CT OSL dosimeters had a percent standard deviation of 1.4%. After energy-dependent correction factors were applied, the RMS percent difference in the measured CTDI(100) values was about 10%, with a tendency of OSL to underestimate CTDI relative to the ion chamber. Unlike ion chamber methods, however, OSL dosimeters allow measurement of the radiation dose profile.

SUBMITTER: Vrieze TJ

PROVIDER: S-EPMC3482257 | biostudies-other | 2012 Nov

REPOSITORIES: biostudies-other

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Project description:To evaluate and compare the theoretically achievable accuracy of two families of two-parameter photon cross-section models: basis vector model (BVM) and modified parametric fit model (mPFM).The modified PFM assumes that photoelectric absorption and scattering cross-sections can be accurately represented by power functions in effective atomic number and/or energy plus the Klein-Nishina cross-section, along with empirical corrections that enforce exact prediction of elemental cross-sections. Two mPFM variants were investigated: the widely used Torikoshi model (tPFM) and a more complex "VCU" variant (vPFM). For 43 standard soft and bony tissues and phantom materials, all consisting of elements with atomic number less than 20 (except iodine), we evaluated the theoretically achievable accuracy of tPFM and vPFM for predicting linear attenuation, photoelectric absorption, and energy-absorption coefficients, and we compared it to a previously investigated separable, linear two-parameter model, BVM.For an idealized dual-energy computed tomography (DECT) imaging scenario, the cross-section mapping process demonstrates that BVM more accurately predicts photon cross-sections of biological mixtures than either tPFM or vPFM. Maximum linear attenuation coefficient prediction errors were 15% and 5% for tPFM and BVM, respectively. The root-mean-square (RMS) prediction errors of total linear attenuation over the 20 keV to 1000 keV energy range of tPFM and BVM were 0.93% (tPFM) and 0.1% (BVM) for adipose tissue, 0.8% (tPFM) and 0.2% (BVM) for muscle tissue, and 1.6% (tPFM) and 0.2% (BVM) for cortical bone tissue. With exception of the thyroid and Teflon, the RMS error for photoelectric absorption and scattering coefficient was within 4% for the tPFM and 2% for the BVM. Neither model predicts the photon cross-sections of thyroid tissue accurately, exhibiting relative errors as large as 20%. For the energy-absorption coefficients prediction error, RMS errors for the BVM were less than 1.5%, while for the tPFM, the RMS errors were as large as 16%.Compared to modified PFMs, BVM shows superior potential to support dual-energy CT cross-section mapping. In addition, the linear, separable BVM can be more efficiently deployed by iterative model-based DECT image-reconstruction algorithms.

Project description:Background and objective: Commercially available cannabidiol (CBD) products are increasingly being used for medicinal purposes, including for the treatment of various neurological conditions, but there are growing concerns around adherence to quality control measures that protect consumers. This study was conducted to assess the purity and label accuracy of commercially available CBD products. Methods: Commercially available CBD products were chosen from the open stream of commerce in the United States based on formulations as a tincture, gummy, vape, or topical product. Cannabinoid concentrations were analyzed to verify label accuracy including "full spectrum," "broad spectrum," and "CBD isolate" claims on the product label. Analysis for the presence of contaminants included evaluation for heavy metals, pesticides, and residual solvents. Labeled and actual total amounts of CBD and levels of impurities such as heavy metals, residual solvents, and pesticides were measured. Results: A total of 202 CBD products (100 tinctures, 48 gummies, 34 vape products, and 20 topicals) were chosen to represent a broad sample in the United States. Of the products tested (full spectrum, n = 84; broad spectrum, n = 28; CBD isolate, n = 37), 26% did not meet the definition for product type claimed on the packaging. The majority of products (74%) deviated from their label claim of CBD potency by at least 10%. Heavy metals were detected 52 times across 44 of the 202 products tested, with lead being the most prevalent heavy metal. Residual solvents were detected 446 times across 181 of 202 products, with the highest concentrations reported for hexane, m/p-xylene, methanol, and o-xylene. Of 232 pesticides tested, 26 were found 55 times across 30 products. A total of 3% of heavy metals, 1% of residual solvents, and 1% of pesticides violated >1 regulatory threshold. Discussion: This study demonstrated that the majority of commercially available CBD products tested within the current study are inaccurately labeled. Heavy metals, residual solvents, and pesticides were found in several products, some of which violated regulatory thresholds. Thus, uniform compliance with CBD quality control measures is lacking and raises consumer protection concerns. Improved regulatory oversight of this industry is recommended.

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Project description:BackgroundMost studies on synthetic computed tomography (sCT) generation for brain rely on in-house developed methods. They often focus on performance rather than clinical feasibility. Therefore, the aim of this work was to validate sCT images generated using a commercially available software, based on a convolutional neural network (CNN) algorithm, to enable MRI-only treatment planning for the brain in a clinical setting.MethodsThis prospective study included 20 patients with brain malignancies of which 14 had areas of resected skull bone due to surgery. A Dixon magnetic resonance (MR) acquisition sequence for sCT generation was added to the clinical brain MR-protocol. The corresponding sCT images were provided by the software MRI Planner (Spectronic Medical AB, Sweden). sCT images were rigidly registered and resampled to CT for each patient. Treatment plans were optimized on CT and recalculated on sCT images for evaluation of dosimetric and geometric endpoints. Further analysis was also performed for the post-surgical cases. Clinical robustness in patient setup verification was assessed by rigidly registering cone beam CT (CBCT) to sCT and CT images, respectively.ResultsAll sCT images were successfully generated. Areas of bone resection due to surgery were accurately depicted. Mean absolute error of the sCT images within the body contour for all patients was 62.2 ± 4.1 HU. Average absorbed dose differences were below 0.2% for parameters evaluated for both targets and organs at risk. Mean pass rate of global gamma (1%/1 mm) for all patients was 100.0 ± 0.0% within PTV and 99.1 ± 0.6% for the full dose distribution. No clinically relevant deviations were found in the CBCT-sCT vs CBCT-CT image registrations. In addition, mean values of voxel-wise patient specific geometric distortion in the Dixon images for sCT generation were below 0.1 mm for soft tissue, and below 0.2 mm for air and bone.ConclusionsThis work successfully validated a commercially available CNN-based software for sCT generation. Results were comparable for sCT and CT images in both dosimetric and geometric evaluation, for both patients with and without anatomical anomalies. Thus, MRI Planner is feasible to use for radiotherapy treatment planning of brain tumours.

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Technical note: precision and accuracy of a commercially available CT optically stimulated luminescent dosimetry system for the measurement of CT dose index.

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