Zeitschrift fur Medizinische Physik最新文献

Background: Dosimetric validation of single isocenter multi-target radiosurgery plans is difficult due to conditions of electronic disequilibrium and the simultaneous irradiation of multiple off-axis lesions dispersed throughout the volume. Here we report the benchmarking of a customizable Monte Carlo secondary dose calculation algorithm specific for multi-target radiosurgery which future users may use to guide their commissioning and clinical implementation.

Purpose: To report the generation, validation, and clinical benchmarking of a volumetric Monte Carlo (MC) dose calculation beam model for single isocenter radiosurgery of intracranial multi-focal disease.

Methods: The beam model was prepared within SciMoCa (ScientificRT, Munich Germany), a commercial independent dose calculation software, with the aim of broad availability via the commercial software for use with single isocenter radiosurgery. The process included (1) definition & acquisition of measurement data required for beam modeling, (2) tuning model parameters to match measurements, (3) validation of the beam model via independent measurements and end-to-end testing, and finally, (4) clinical benchmarking and validation of beam model utility in a patient specific QA setting. We utilized a 6X Flattening-Filter-Free photon beam from a TrueBeam STX linear accelerator (Siemens Healthineers, Munich Germany).

Results: In addition to the measured data required for standard IMRT/VMAT (depth dose, central axis profiles & output factors, leaf gap), beam modeling and validation for single-isocenter SRS required central axis and off axis (5 cm & 9 cm) small field output factors and comparison between measurement and simulation of backscatter with aperture for jaw much greater than MLCs. Validation end-to-end measurements included SRS MapCHECK in StereoPHAN geometry (2%/1 mm Gamma = 99.2% ± 2.2%), and OSL & scintillator measurements in anthropomorphic STEEV phantom (6 targets, volume = 0.1-4.1cc, distance from isocenter = 1.2-7.9 cm) for which mean difference was -1.9% ± 2.2%. For 10 patient cases, MC for individual PTVs was -0.8% ± 1.5%, -1.3% ± 1.7%, and -0.5% ± 1.8% for mean dose, D_95%, and D_1%, respectively. This corresponded to custom passing rates action limits per AAPM TG-218 guidelines of ±5.2%, ±6.4%, and ±6.3%, respectively.

Conclusions: The beam modeling, validation, and clinical action criteria outlined here serves as a benchmark for future users of the customized beam model within SciMoCa for single isocenter radiosurgery of multi-focal disease.

Introduction: Deep learning-based approaches are increasingly being used for the reconstruction of accelerated MRI scans. However, presented analyses are frequently lacking in-detail evaluation of basal measures like resolution or signal-to-noise ratio. To help closing this gap, spatially resolved maps of image resolution and noise enhancement (g-factor) are determined and assessed for typical model- and data-driven MR reconstruction methods in this paper.

Methods: MR data from a routine brain scan of a patient were undersampled in retrospect at R = 4 and reconstructed using two data-driven (variational network (VN), U-Net) and two model based reconstructions methods (GRAPPA, TV-constrained compressed sensing). Local resolution was estimated by the width of the main-lobe of a local point-spread function, which was determined for every single pixel by reconstructing images with an additional small perturbation. G-factor maps were determined using a multiple replica method.

Results: GRAPPA showed good spatial resolution, but increased g-factors (1.43-1.84, 75% quartile) over all other methods. The images delivered from compressed sensing suffered most from low local resolution, in particular in homogeneous areas of the image. VN and U-Net show similar resolution with mostly moderate local blurring, slightly better for U-Net. For all methods except GRAPPA the resolution as well as the g-factors depend on the anatomy and the direction of undersampling.

Conclusion: Objective image quality parameters, local resolution and g-factors have been determined. The examined data driven methods show less local blurring than compressed sensing. The noise enhancement for reconstructions using CS, VN and U-Net is elevated at anatomical contours but is drastically reduced with respect to GRAPPA. Overall, the applied framework provides the possibility for more detailed analysis of novel reconstruction approaches incorporating non-linear and non-stationary transformations.

¹²⁹Xe hyperpolarized gas chemical exchange saturation transfer (HyperCEST) MRI has been suggested as molecular imaging modality but translation to in vivo imaging has been slow, likely due to difficulties of synthesizing suitable molecules. Cucurbit[6]uril-either in readily available non-functionalized or potentially in functionalized form-may, combined with ¹²⁹Xe HyperCEST MRI, prove useful as a switchable ¹²⁹Xe MR contrast agent but the likely differential properties of contrast generation in individual chemical compartments as well as the influence of ¹²⁹Xe signal drifts encountered in vivo on HyperCEST MRI are unknown. Here, HyperCEST z spectroscopy and chemical shift imaging with compartment-specific analysis are performed in a total of 10 rats using cucurbit[6]uril injected i.v. and under a protocol employing spontaneous respiration. Differences in intensity of the HyperCEST effect between chemical compartments and anatomical regions are investigated. Strategies to mitigate influence of signal instabilities associated with drifts in physiological parameters are developed. It is shown that presence of cucurbit[6]uril can be readily detected under spontaneous ¹²⁹Xe inhalation mostly in aqueous tissues further away from the lung. Differences of effect intensity in individual regions and compartments must be considered in HyperCEST data interpretation. In particular, there seems to be almost no effect in lipids. ¹²⁹Xe HyperCEST MR measurements utilizing spontaneous respiration protocols and extended measurement times are feasible. HyperCEST MRI of non-functionalized cucurbit[6]uril may create contrast between anatomical structures in vivo.

This study describes a method to validate a radiation transport model that quantifies the number of DNA double-strand breaks (DSB) produced in the lymphocyte nucleus by internal ex vivo irradiation of whole blood with the radionuclides ⁹⁰Y, ^99mTc, ¹²³I, ¹³¹I, ¹⁷⁷Lu, ²²³Ra, and ²²⁵Ac in a test vial using the GATE/Geant4 code at the macroscopic level and the Geant4-DNA code at the microscopic level.

Methods: The simulation at the macroscopic level reproduces an 8 mL cylindrical water-equivalent medium contained in a vial that mimics the geometry for internal ex vivo blood irradiation. The lymphocytes were simulated as spheres of 3.75 µm radius randomly distributed, with a concentration of 125 spheres/mL. A phase-space actor was attached to each sphere to register all the entering particles. The simulation at the microscopic level for each radionuclide was performed using the Geant4-DNA tool kit, which includes the clustering example centered on a density-based spatial clustering of applications with noise (DBSCAN) algorithm. The irradiation source was constructed by generating a single phase space from the sum of all phase spaces. The lymphocyte nucleus was defined as a water sphere of a 3.1 µm radius. The absorbed dose coefficients for lymphocyte nuclei (d_Lymph) were calculated and compared with macroscopic whole blood absorbed dose coefficients (d_Blood). The DBSCAN algorithm was used to calculate the number of DSBs. Lastly, the number of DSB∙cell^-1∙mGy^-1 (simulation) was compared with the number of radiation-induced foci per cell and absorbed dose (RIF∙cell^-1∙mGy^-1) provided by experimental data for gamma and beta emitting radionuclides. For alpha emitters, d_Lymph and the number of α-tracks∙100 cell^-1∙mGy^-1 and DBSs∙µm^-1 were calculated using experiment-based thresholds for the α-track lengths and DBSs/track values. The results were compared with the results of an ex vivo study with ²²³Ra.

Results: The d_Lymph values differed from the d_Blood values by -1.0% (⁹⁰Y), -5.2% (^99mTc), -22.3% (¹²³I), 0.35% (¹³¹I), 2.4% (¹⁷⁷Lu), -5.6% (²²³Ra) and -6.1% (²²⁵Ac). The number of DSB∙cell^-1∙mGy^-1 for each radionuclide was 0.015 DSB∙cell^-1∙mGy^-1 (⁹⁰Y), 0.012 DSB∙cell^-1∙mGy^-1 (^99mTc), 0.014DSB∙cell^-1∙mGy^-1 (¹²³I), 0.012 DSB∙cell^-1∙mGy^-1 (¹³¹I), and 0.016 DSB∙cell^-1∙mGy^-1 (¹⁷⁷Lu). These values agree very well with experimental data. The number of α-tracks∙100 cells^-1∙mGy^-1 for ²²³Ra and ²²⁵Ac w

Three types of gamma radiation detectors associated with distributed electronics namely, NaI (Tl), HPGe and LaBr₃(Ce) are compared primarily focusing on electronic noise and scattering noise. Additionally, detectors of same make, material, size and electronics are also compared. A methodology is proposed to select the most suitable detector for computed tomography (CT) among the available options. Standard deviation parameter is employed to estimate electronic noise without performing CT experiment. Kanpur theorem-1(KT-1) is used to estimate the scattering noise quantitatively after verifying its sensitivity to scattering noise. The impact of scattering noise on CT profiles is evaluated using dice similarity dice coefficient. A good resemblance between KT-1 and dice coefficient is observed. A maximum difference of 56% in scattering noise is observed when five detectors used simultaneously instead of single detector whereas a discrepancy of 85% is observed between different types of radiation detectors. As far as ease of handling, operational and capital cost is concern one has to compromise minimum 12% of accuracy in CT reconstruction if NaI (Tl) detector is used with respect to best alternative available. The proposed methodology can be applied to measurement that require minimal scattering interference data other than CT experiments. The manufacturer can add noise level of detector as a characteristic parameter in the data sheet.

The standard diffusion MRI model with intra- and extra-axonal water pools offers a set of microstructural parameters describing brain white matter architecture. However, non-linearities in the standard model and diffusion data contamination by noise and imaging artefacts make estimation of diffusion metrics challenging. In order to develop reliable diffusion approaches and to avoid computational model degeneracy, additional theoretical assumptions allowing stable numerical implementations are required. Advanced diffusion approaches allow for estimation of intra-axonal water fraction (AWF), describing a key structural characteristic of brain tissue. AWF can be interpreted as an indirect measure or proxy of neurite density and has a potential as useful clinical biomarker. Established diffusion approaches such as white matter tract integrity, neurite orientation dispersion and density imaging (NODDI), and spherical mean technique provide estimates of AWF within their respective theoretical frameworks. In the present study, we estimated AWF metrics using different diffusion approaches and compared measures of brain asymmetry between the different metrics in a sub-sample of 182 subjects from the UK Biobank. Multivariate decomposition by mean of linked independent component analysis revealed that the various AWF proxies derived from the different diffusion approaches reflect partly non-overlapping variance of independent components, with distinct anatomical distributions and sensitivity to age. Further, voxel-wise analysis revealed age-related differences in AWF-based brain asymmetry, indicating less apparent left-right hemisphere difference with higher age. Finally, we demonstrated that NODDI metrics suffer from a quite strong dependence on used numerical algorithms and post-processing pipeline. The analysis based on AWF metrics strongly depends on the used diffusion approach and leads to poorly reproducible results.

Objective: To investigate the feasibility of cerebral metabolic rate of oxygen consumption (CMRO₂) measurements with MRI at 3 Tesla in different brain regions.

Methods: CMRO₂ represents a key indicator of the physiological state of brain tissue. Dynamic ¹⁷O-MRI with inhalation of isotopically enriched ¹⁷O gas has been used to quantify global CMRO₂ in brain white (WM) and gray matter (GM). However, global CMRO₂ can only reflect the overall oxygen metabolism of the brain and cannot provide enough information on local tissue oxygen metabolism. To investigate the feasibility of determination of regional CMRO₂ at a clinical 3 T MRI system, CMRO₂ values in frontal, parietal and occipital WM and GM were determined in 5 healthy volunteers and compared to evaluate the regional differences of oxygen metabolism in WM and GM. Additionally, regional CMRO₂ values were determined in deep brain structures including thalamus, dorsal striatum, caudate nucleus and insula cortex and in the cerebella, and compared with literature values from ¹⁵O-PET studies.

Results: In cortical GM the determined CMRO₂ values were in good agreement with the literature, whereas values in WM were about 32-48% higher than literature values. Regional analysis revealed a significantly higher CMRO₂ in the occipital GM compared to the frontal and parietal GM. By contrast, no significant difference of CMRO₂ was observed across the WM. In addition, CMRO₂ in deep brain structures was lower compared to literature values and in the cerebella a good hemispheric symmetry of the tissue oxygen metabolism was found.

Conclusion: Dynamic ¹⁷O-MRI enables direct, non-invasive determination of regional CMRO₂ in brain structures in healthy volunteers at 3T.