China
Africa
Explore chapters and articles related to this topic
Properties of the Digital Image
Published in Michael Ljungberg, Handbook of Nuclear Medicine and Molecular Imaging for Physicists, 2022
The partial volume effect refers to the mix of signal intensity from different objects due to limited spatial resolution (Figure 9.12). When pixel or voxel values not only reflect signal from a specific object coordinate, but also have contributions from nearby coordinates, their values represent a mixture of object intensity from different tissues. The cause of partial volume effects may be both the limited resolution of the scanner and limitations imposed by the sampling interval (pixel or voxel size).
Targeted Molecular Radiotherapy – Clinical Considerations and Dosimetry*
Published in W. P. M. Mayles, A. E. Nahum, J.-C. Rosenwald, Handbook of Radiotherapy Physics, 2021
The calculation of mean absorbed doses precludes the determination of the distribution of absorbed dose, regarded as essential information for EBRT and for brachytherapy. Voxelised dosimetry, whereby each voxel is considered as a target, can in principle overcome this limitation. This has the distinct advantage that the volume of a voxel is well defined, although partial-volume effects caused by the limited spatial resolution of the imaging system present challenges for accurate quantification. Determination of the distribution of absorbed dose enables the generation of dose-volume histograms, which may then be used to estimate tumour control probabilities and normal-tissue complication probabilities (Cremonesi et al. 2014b; Dewaraja et al. 2013; see also Chapter 44 and Section 57.7).
Integrated PET and MRI of the heart
Published in Yi-Hwa Liu, Albert J. Sinusas, Hybrid Imaging in Cardiovascular Medicine, 2017
Ciprian Catana, David E. Sosnovik
Alternatively, methods that apply the correction before kinetic modeling have been developed. In an approach similar to the ones used for brain gray/white matter partial volume effects correction, an idealized image of the myocardial wall obtained directly from the PET images was convolved with the point spread function of the scanner to derive the spill-over and recovery coefficients (Nuyts et al. 1996). In a more recent implementation, high-resolution contrast-enhanced CT images were used to define the volumes of interest (Du et al. 2013). Using simulations, the authors also showed that the most accurate estimates of the activity are obtained when partial volume effect correction is performed independently for the images obtained from each gate (i.e., corresponding to the different phases of the cardiac cycle). This, however, requires a gated contrast-enhanced CT exam, which significantly increases the patient’s radiation exposure. An interesting aspect revealed by this study was that the contrast between diseased and healthy tissue is actually affected by partial volume effects, with the highest accuracy being achieved when the defect is considered as a separate volume of interest. This highlights the need for a high-resolution high-contrast imaging technique, such as late Gd contrast-enhanced MRI, that is capable of providing anatomical and physiological information for accurately defining these volumes of interest for improving quantification in cardiac PET.
Dual-zone material assignment method for correcting partial volume effects in image-based bone models
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2023
Brendan Inglis, Daniel Grumbles, Hannah L. Dailey
Partial volume effects (PVEs) are a known byproduct of medical imaging and image-based finite element analysis (FEA). Partial volume effects first arise at the image-acquisition stage. In computed tomography (CT) imaging, when tissues of widely different absorption are captured within the same CT voxel, they produce an effective local X-ray attenuation (Hounsfield Unit [HU]) that is proportional to the weighted average value for the tissues within the volume (Keyak et al. 1990; Merz et al. 1996; Cattaneo et al. 2001; Taddei et al. 2004). These partial volume effects appear as image “blur” at tissue boundaries, such as between mineralized and non-mineralized tissue (Falcinelli et al. 2016) and when resolving thin features in cortical bone (Pakdel et al. 2012). The blur creates a halo effect that thickens the apparent cortical geometry (Rittweger et al. 2004). These effects can be mitigated by acquiring images with smaller voxels, but they are inevitable. Image-acquisition PVEs can be mitigated through image deblurring using a deconvolution filter by estimating the point spread function of the acquired image, computing its inverse, and convolving the acquired image with that inverse (Pakdel et al. 2014; 2016).
Elevated regional cerebral blood flow in adults with 22q11.2 deletion syndrome
Published in The World Journal of Biological Psychiatry, 2023
Maurice Pasternak, Zahra Shirzadi, Henk J. M. M. Mutsaerts, Erik Boot, Nancy J. Butcher, Bradley J. MacIntosh, Tracy Heung, Anne S. Bassett, Mario Masellis
There are limitations to note in addition to the small sample size. Given that all patients with a history of psychosis used antipsychotic medications, we could not assess the potential impact of drug effects on perfusion. Also, we were unable to investigate the effects of a comorbid diagnosis of Parkinson’s disease on CBF, given that only one individual met diagnostic criteria for this condition in the 22q11DS group (Butcher et al. 2017). While we did not perform partial volume correction, grey matter volume was included as a covariate in the voxel-based analytical model. Furthermore, CBF was higher on a regional basis in 22q11DS compared to controls, which contrasts with the reduced grey matter volume observed in that of 22q11DS. Therefore, partial volume effects are unlikely to explain our CBF results.
Analysis of fiber strain in the human tongue during speech
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2020
Arnold D. Gomez, Maureen L. Stone, Jonghye Woo, Fangxu Xing, Jerry L. Prince
Larger deformations are characterized by larger extensions than contractions, with the latter reaching more than 25% in some muscles compared to the former, which remain less than 10%, suggesting some limit on sarcomere contraction. Similarity of motion was particularly clear in muscles occupying a relatively large volume (primarily the GGA and T muscles). This observation can be explained from both a mechanical and an experimental perspective. Mechanically, relatively uniform motion across a large muscle facilitates deformation stemming from volume-preserving shifts in order to achieve large changes in length with a relatively small amount of sarcomeric contraction. Larger muscles may also be more efficient at producing motions associated with a common set of target phonemes. Thus, we speculate that the overall tongue shape is driven by the larger muscles, while more idiosyncratic shape variations may be associated with smaller muscles—those that also exhibited more differences across participants. From an experimental perspective, larger volumes are less susceptible to imaging artifacts such as partial volume, and are less prone to errors in muscular placement that may stem from the model. Based on the experimental viewpoint, we can explain why smaller muscles (particularly the SG muscle, but also the IL muscle) exhibited the least amount of consistency across subjects and greater variance on the waveforms.