Tomography, Volume 6, Issue 1 (March 2020) – 6 articles

Computed tomography is nowadays an indispensable tool in medicine used to diagnose multiple diseases. In clinical and emergency room environments, the speed of acquisition and information processing are crucial. CUDA is a software architecture used to work with NVIDIA graphics processing units. In this paper a methodology to accelerate tomographic image reconstruction based on maximum likelihood expectation maximization iterative algorithm and combined with the use of graphics processing units programmed in CUDA framework is presented. Implementations developed here are used to reconstruct images with clinical use. Timewise, parallel versions showed improvement with respect to serial implementations. These differences reached, in some cases, 2 orders of magnitude in time while preserving image quality. The image quality and reconstruction times were not affected significantly by the addition of Poisson noise to projections. Furthermore, our implementations showed good performance when compared with reconstruction methods provided by commercial software. One of the goals of this work was to provide a fast, portable, simple, and cheap image reconstruction system, and our results support the statement that the goal was achieved. Full article

Apparent diffusion coefficient has limits to differentiate solid tumor from normal tissue or edema in glioblastoma (GBM). This study investigated a microstructure model (MSM) in GBM using a clinically available diffusion imaging technique. The MSM was modified to integrate with bi-polar diffusion gradient waveforms, and applied to 30 patients with newly diagnosed GBM. Diffusion-weighted (DW) images acquired on a 3 T scanner with b-values from 0 to 2500 s/mm² were fitted in volumes of interest (VOI_s) of solid tumor to obtain the apparent restriction size of intracellular water (ARS), the fractional volume of intracellular water (V_in), and extracellular (D_ex) water diffusivity. The parameters in solid tumor were compared with those of other tissue types by Students’ t test. For comparison, DW images were fitted by conventional mono-exponential and bi-exponential models. ARS, D_ex, and V_in from the MSM in tumor VOI_s were significantly greater than those in WM, GM, and edema (P values of .01–.001). ARS values in solid tumors (from 21.6 to 34.5 um) had absolutely no overlap with those in all other tissue types (from 0.9 to 3.5 um). V_in values showed a descending order from solid tumor (from 0.32 to 0.52) to WM, GM, and edema (from 0.05 to 0.25), consisting with the descending cellularity in these tissue types. The parameters from mono-exponential and bi-exponential models could not significantly differentiate solid tumor from all other tissue types, particularly from edema. Further development and histopathological validation of the MSM will warrant its role in clinical management of GBM. Full article

Small-animal imaging is an essential tool that provides noninvasive, longitudinal insight into novel cancer therapies. However, considerable variability in image analysis techniques can lead to inconsistent results. We have developed quantitative imaging for application in the preclinical arm of a coclinical trial by using a genetically engineered mouse model of soft tissue sarcoma. Magnetic resonance imaging (MRI) images were acquired 1 day before and 1 week after radiation therapy. After the second MRI, the primary tumor was surgically removed by amputating the tumor-bearing hind limb, and mice were followed for up to 6 months. An automatic analysis pipeline was used for multicontrast MRI data using a convolutional neural network for tumor segmentation followed by radiomics analysis. We then calculated radiomics features for the tumor, the peritumoral area, and the 2 combined. The first radiomics analysis focused on features most indicative of radiation therapy effects; the second radiomics analysis looked for features that might predict primary tumor recurrence. The segmentation results indicated that Dice scores were similar when using multicontrast versus single T2-weighted data (0.863 vs 0.861). One week post RT, larger tumor volumes were measured, and radiomics analysis showed greater heterogeneity. In the tumor and peritumoral area, radiomics features were predictive of primary tumor recurrence (AUC: 0.79). We have created an image processing pipeline for high-throughput, reduced-bias segmentation of multiparametric tumor MRI data and radiomics analysis, to better our understanding of preclinical imaging and the insights it provides when studying new cancer therapies. Full article

Hypoxia is associated with resistance to radiotherapy and chemotherapy in malignant gliomas, and it can be imaged by positron emission tomography with 18F-fluoromisonidazole (18F-FMISO). Previous results for patients with brain cancer imaged with 18F-FMISO at a single center before conventional chemoradiotherapy showed that tumor uptake via T/Bmax (tissue SUVmax/blood SUV) and hypoxic volume (HV) was associated with poor survival. However, in a multicenter clinical trial (ACRIN 6684), traditional uptake parameters were not found to be prognostically significant, but tumor SUVpeak did predict survival at 1 year. The present analysis considered both study cohorts to reconcile key differences and examine the potential utility of adding radiomic features as prognostic variables for outcome prediction on the combined cohort of 72 patients with brain cancer (30 University of Washington and 42 ACRIN 6684). We used both 18F-FMISO intensity metrics (T/Bmax, HV, SUV, SUVmax, SUVpeak) and assessed radiomic measures that determined first-order (histogram), second-order, and higher-order radiomic features of 18F-FMISO uptake distributions. A multivariate model was developed that included age, HV, and the intensity of 18F-FMISO uptake. HV and SUVpeak were both independent predictors of outcome for the combined data set (P < .001) and were also found significant in multivariate prognostic models (P < .002 and P < .001, respectively). Further model selection that included radiomic features showed the additional prognostic value for overall survival of specific higher order texture features, leading to an increase in relative risk prediction performance by a further 5%, when added to the multivariate clinical model.. Full article

Metabolic sex differences have recently been shown to be particularly important in tailoring treatment strategies. Sex has a major effect on fat turnover rates and plasma lipid delivery in the body. Differences in kidney structure and transporters between male and female animals have been found. Here we investigated sex-specific renal pyruvate metabolic flux and whole-kidney functional status in age-matched healthy Wistar rats. Blood oxygenation level–dependent and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) were used to assess functional status. Hyperpolarized [1-13C]pyruvate was used to assess the metabolic differences between male and female rats. Female rats had a 41% ± 3% and 41% ± 5% lower absolute body and kidney weight, respectively, than age-matched male rats. No difference was seen between age-matched male and female rats in the kidney-to-body weight ratio. A 56% ± 11% lower lactate production per mL/100 mL/min was found in female rats than in age-matched male rats measured by hyperpolarized magnetic resonance and DCE MRI. Female rats had a 33% ± 11% higher glomerular filtration rate than age-matched male rats measured by DCE MRI. A similar renal oxygen tension (T2*) was found between age-matched male and female rats as shown by blood oxygenation level–dependent MRI. The results were largely independent of the pyruvate volume and the difference in body weight. This study shows an existing metabolic difference between kidneys in age-matched male and female rats, which indicates that sex differences need to be considered when performing animal experiments. Full article

There are no studies that allow a joint diagnostic or therapeutic intervention for the treatment of fatty liver and urolithiasis, perhaps because it is not known if there is an association between these 2 diseases. We aimed to identify a relationship between renal lithiasis and fatty liver disease by examining for common factors that could be used to reduce their incidence and complications. Our study supports the association of fatty liver and urolithiasis. Given the increase in frequency of these 2 diseases, we believe there is a common pathway within the malabsorptive and metabolic syndromes, thus leading for a new field of research to find a mechanism that allows timely interventions. Full article