Optimizing dual energy cone beam CT protocols for preclinical imaging and radiation research

Objective: The aim of this work was to investigate whether quantitative dual-energy CT (DECT) imaging is feasible for small animal irradiators with an integrated cone-beam CT (CBCT) system. Methods: The optimal imaging protocols were determined by analyzing different energy combinations and dose levels. The influence of beam hardening effects and the performance of a beam hardening correction (BHC) were investigated. In addition, two systems from different manufacturers were compared in terms of errors in the extracted effective atomic numbers (Z(eff)) and relative electron densities (rho(e)) for phantom inserts with known elemental compositions and relative electron densities. Results: The optimal energy combination was determined to be 50 and 90kVp. For this combination, Z(eff) and r rho(e) can be extracted with a mean error of 0.11 and 0.010, respectively, at a dose level of 60cGy. Conclusion: Quantitative DECT imaging is feasible for small animal irradiators with an integrated CBCT system. To obtain the best results, optimizing the imaging protocols is required. Well-separated X-ray spectra and a sufficient dose level should be used to minimize the error and noise for Z(eff) and rho(e). When no BHC is applied in the image reconstruction, the size of the calibration phantom should match the size of the imaged object to limit the influence of beam hardening effects. No significant differences in Z(eff) and rho(e) errors are observed between the two systems from different manufacturers. Advances in knowledge: This is the first study that investigates quantitative DECT imaging for small animal irradiators with an integrated CBCT system

The influence of respiratory motion on dose delivery in a mouse lung tumour irradiation using the 4D MOBY phantom

OBJECTIVE: During precision irradiation of a preclinical lung tumour model, the tumour is subject to breathing motion and it can partially move out of the irradiation field. This work aimed to perform a quantitative analysis of the impact of respiratory motion on a mouse lung tumour irradiation with small fields. METHODS: A four-dimensional digital mouse whole body phantom (MOBY) with a virtual 4-mm spherical lung tumour at different locations in both lungs is used to simulate a breathing anaesthetized mouse in different breathing phases representing a full breathing cycle. The breathing curve is determined by fluoroscopic imaging of an anaesthetized mouse. Each MOBY time frame is loaded in a dedicated treatment planning system (small animal radiotherapy-Plan) and is irradiated by a full arc with a 5-mm circular collimator. Mean and time-dependent organ doses are calculated for the tumour, heart and spinal cord. RESULTS: Depending on the location of the lung tumour, an overestimation of the mean tumour dose up to 11% is found. The mean heart dose could be both overestimated or underestimated because the heart moves in or out of the irradiation field depending on the beam target location. The respiratory motion does not affect the mean spinal cord dose. A dose gradient is visible in the time-dependent tumour dose distribution. CONCLUSION: In the future, new methods need to be developed to track the lung tumour motion before preclinical irradiation to adjust the irradiation plan. Margins, collimator diameter and target dose could be changed easily, but they all have their drawbacks. State-of-the-art clinical techniques such as respiratory gating or motion tracking may offer a solution for the cold spots in the time-dependent tumour dose. Advances in knowledge: A suitable method is found to quantify changes in organ dose due to respiratory motion in mouse lung tumour image-guided precision irradiation

The effect of different image reconstruction techniques on pre-clinical quantitative imaging and dual-energy CT

OBJECTIVE: To analyse the effect of different image reconstruction techniques on image quality and dual energy CT (DECT) imaging metrics. METHODS: A software platform for pre-clinical cone beam CT X-ray image reconstruction was built using the open-source reconstruction toolkit. Pre-processed projections were reconstructed with filtered back-projection and iterative algorithms, namely Feldkamp, Davis, and Kress (FDK), Iterative FDK, simultaneous algebraic reconstruction technique (SART), simultaneous iterative reconstruction technique and conjugate gradient. Imaging metrics were quantitatively assessed, using a quality assurance phantom, and DECT analysis was performed to determine the influence of each reconstruction technique on the relative electron density (rho(e)) and effective atomic number (Z(eff)) values. RESULTS: Iterative reconstruction had favourable results for the DECT analysis: a significantly smaller spread for each material in the rho(e)-Z(eff) space and lower Z(eff) and rho(e) residuals (on average 24 and 25% lower, respectively). In terms of image quality assurance, the techniques FDK, Iterative FDK and SART provided acceptable results. The three reconstruction methods showed similar geometric accuracy, uniformity and CT number results. The technique SART had a contrast-to-noise ratio up to 76% higher for solid water and twice as high for Teflon, but resolution was up to 28% lower when compared to the other two techniques. CONCLUSIONS: Advanced image reconstruction can be beneficial, but the benefit is small, and calculation times may be unacceptable with current technology. The use of targeted and downscaled reconstruction grids, larger, yet practicable, pixel sizes and GPU are recommended. ADVANCES IN KNOWLEDGE: An iterative CBCT reconstruction platform was build using RTK

The impact of dual energy CT imaging on dose calculations for pre-clinical studies

Abstract Background To investigate the feasibility of using dual-energy CT (DECT) for tissue segmentation and kilovolt (kV) dose calculations in pre-clinical studies and assess potential dose calculation accuracy gain. Methods Two phantoms and an ex-vivo mouse were scanned in a small animal irradiator with two distinct energies. Tissue segmentation was performed with the single-energy CT (SECT) and DECT methods. A number of different material maps was used. Dose calculations were performed to verify the impact of segmentations on the dose accuracy. Results DECT showed better overall results in comparison to SECT. Higher number of DECT segmentation media resulted in smaller dose differences in comparison to the reference. Increasing the number of materials in the SECT method yielded more instability. Both modalities showed a limit to which adding more materials with similar characteristics ceased providing better segmentation results, and resulted in more noise in the material maps and the dose distributions. The effect was aggravated with a decrease in beam energy. For the ex-vivo specimen, the choice of only one high dense bone for the SECT method resulted in large volumes of tissue receiving high doses. For the DECT method, the choice of more than one kind of bone resulted in lower dose values for the different tissues occupying the same volume. For the organs at risk surrounded by bone, the doses were lower when using the SECT method in comparison to DECT, due to the high absorption of the bone. SECT material segmentation may lead to an underestimation of the dose to OAR in the proximity of bone. Conclusions The DECT method enabled the selection of a higher number of materials thereby increasing the accuracy in dose calculations. In phantom studies, SECT performed best with three materials and DECT with seven for the phantom case. For irradiations in preclinical studies with kV photon energies, the use of DECT segmentation combined with the choice of a low-density bone is recommended

Murine vs human tissue compositions: implications of using human tissue compositions for photon energy absorption in mice

METHODS: Dual energy CT (DECT) images of 9 female mice were used to extract the effective atomic number Z(eff) and the relative electron density rho(e) for each voxel in the images. To investigate the influence of the tissue compositions on the absorbed radiation dose for a typical kilovoltage photon beam, mass energy-absorption coefficients mu(en)/rho were calculated for 10 different tissues in each mouse. RESULTS: Differences between human and murine tissue compositions can lead to errors around 7.5 % for soft tissues and 20.1 % for bone tissues in mu(en)/rho values for kilovoltage photon beams. When considering the spread within tissues, these errors can increase up to 17.5 % for soft tissues and 53.9 % for bone tissues within only a single standard deviation away from the mean tissue value. CONCLUSION: This study illustrates the need for murine reference tissue data. However, assigning only a single mean reference value to an entire tissue can still lead to large errors in dose calculations given the large spread within tissues of mu(en)/rho values found in this study. Therefore, new methods such as DECT and spectral CT imaging need to be explored, which can be important next steps in improving tissue assignment for dose calculations in small animal radiotherapy. ADVANCES IN KNOWLEDGE: This is the first study that investigates the implications of using human tissue compositions for dose calculations in mice for kilovoltage photon beams

Dual-energy CT quantitative imaging:a comparison study between twin-beam and dual-source CT scanners

Purpose: To assess image quality and to quantify the accuracy of relative electron densities (rho(e)) and effective atomic numbers (Z(eff)) for three dual-energy computed tomography (DECT) scanners: a novel single-source split-filter (i. e., twin-beam) and two dual-source scanners. Methods: Measurements were made with a second generation dual-source scanner at 80/140Sn kVp, a third-generation twin-beam single-source scanner at 120 kVp with gold (Au) and tin (Sn) filters, and a third-generation dual-source scanner at 90/150Sn kVp. Three phantoms with tissue inserts were scanned and used for calibration and validation of parameterized methods to extract rho(e) and Z(eff), whereas iodine and calcium inserts were used to quantify Contrast-to-Noise-Ratio (CNR). Spatial resolution in tomographic images was also tested. Results: The third-generation scanners have an image resolution of 6.2, similar to 0.5 lp/cm higher than the second generation scanner. The twin-beam scanner has low imaging contrast for iodine materials due to its limited spectral separation. The parameterization methods resulted in calibrations with low fit residuals for the dual-source scanners, yielding values of rho(e) and Z(eff) close to the reference values (errors within 1.2% for rho(e) and 6.2% for Z(eff) for a dose of 20 mGy, excluding lung substitute tissues). The twin-beam scanner presented overall higher errors (within 3.2% for rho(e) and 28% for Z(eff), also excluding lung inserts) and also larger variations for uniform inserts. Conclusions: Spatial resolution is similar for the three scanners. The twin-beam is able to derive qe and Z(eff), but with inferior accuracy compared to both dual-source scanners. (C) 2016 American Association of Physicists in Medicin

Automatic multiatlas based organ at risk segmentation in mice

Objective: During the treatment planning of a preclinical small animal irradiation, which has time limitations for reasons of animal wellbeing and workflow efficiency, the time consuming organ at risk (OAR) delineation is performed manually. This work aimed to develop, demonstrate, and quantitatively evaluate an automated contouring method for six OARs in a preclinical irritation treatment workflow. Methods: Microcone beam CT images of nine healthy mice were contoured with an in-house developed multiatlas-based image segmentation (MABIS) algorithm for six OARs: kidneys, eyes, heart, and brain. The automatic contouring was compared with the manual delineation using three quantitative metrics: the Dice Similarity Coefficient (DSC), 95th percentile Hausdorff Distance, and the centre of mass displacement. Results: A good agreement between manual and automatic contouring was found for OARS with sharp organ boundaries. For the brain and the heart, the median DSC was larger than 0.94, the median 95th Hausdorff Distance smaller than 0.44 mm, and the median centre of mass displacement smaller than 0.20 mm. Lower DSC values were obtained for the other OARs, but the median DSC was still larger than 0.74 for the left eye, 0.69 for the right eye, 0.89 for the left kidney and 0.80 for the right kidney. Conclusion: The MABIS algorithm was able to delineate six OARs with a relatively high accuracy. Segmenting OARS with sharp organ boundaries performed better than low contrast OARs. Advances in knowledge: A MABIS algorithm is developed, evaluated, and demonstrated in a preclinical small animal irradiation research workflow

Detection of anatomical changes in lung cancer patients with 2D time-integrated, 2D time-resolved and 3D time-integrated portal dosimetry: a simulation study

The aim of this work is to assess the performance of 2D time-integrated (2D-TI), 2D time-resolved (2D-TR) and 3D time-integrated (3D-TI) portal dosimetry in detecting dose discrepancies between the planned and (simulated) delivered dose caused by simulated changes in the anatomy of lung cancer patients.For six lung cancer patients, tumor shift, tumor regression and pleural effusion are simulated by modifying their CT images. Based on the modified CT images, time-integrated (TI) and time-resolved (TR) portal dose images (PDIs) are simulated and 3D-TI doses are calculated. The modified and original PDIs and 3D doses are compared by a gamma analysis with various gamma criteria. Furthermore, the difference in the D-95% (Delta D-95%) of the GTV is calculated and used as a gold standard. The correlation between the gamma fail rate and the Delta D-95% is investigated, as well the sensitivity and specificity of all combinations of portal dosimetry method, gamma criteria and gamma fail rate threshold.On the individual patient level, there is a correlation between the gamma fail rate and the Delta D-95%, which cannot be found at the group level. The sensitivity and specificity analysis showed that there is not one combination of portal dosimetry method, gamma criteria and gamma fail rate threshold that can detect all simulated anatomical changes.This work shows that it will be more beneficial to relate portal dosimetry and DVH analysis on the patient level, rather than trying to quantify a relationship for a group of patients. With regards to optimizing sensitivity and specificity, different combinations of portal dosimetry method, gamma criteria and gamma fail rate should be used to optimally detect certain types of anatomical changes.</p