Tomography, Volume 6, Issue 4 (December 2020) – 8 articles

¹⁸F-fluoromisonidazole (FMISO) positron emission tomography (PET) is a widely used noninvasive imaging modality for assessing hypoxia. We describe the first spatial comparison of FMISO PET with an ex vivo reference standard for hypoxia across whole tumor volumes. Eighteen rats were orthotopically implanted with C6 or 9L brain tumors and made to undergo FMISO PET scanning. Whole brains were excised, sliced into 1-mm-thick sections, optically cleared, and fluorescently imaged for pimonidazole using an in vivo imaging system. FMISO maximum tumor uptake, maximum tumor-to-cerebellar uptake (TCmax), and hypoxic fraction (extracted 110 minutes after FMISO injection) were correlated with analogous metrics derived from pimonidazole fluorescence images. FMISO SUVmax was not significantly different between C6 and 9L brain tumors (P = 0.70), whereas FMISO TCmax and hypoxic fraction were significantly greater for C6 tumors (P < 0.01). FMISO TCmax was significantly correlated with the maximum tumor pimonidazole intensity (ρ = 0.76, P < 0.01), whereas FMISO SUVmax was not. FMISO tumor hypoxic fraction was significantly correlated with the pimonidazole-derived hypoxic fraction (ρ = 0.78, P < 0.01). Given that FMISO TCmax and tumor hypoxic fraction had strong correlations with the pimonidazole reference standard, these metrics may offer more reliable measures of tumor hypoxia than conventional PET uptake metrics (SUVmax). The voxel-wise correlation between FMISO uptake and pimonidazole intensity for a given tumor was strongly dependent on the tumor’s TCmax (ρ = 0.81, P < 0.01) and hypoxic fraction (ρ = 0.85, P < 0.01), indicating PET measurements within individual voxels showed greater correlation with pimonidazole reference standard in tumors with greater hypoxia. Full article

Radiotherapy is a common approach for the treatment of a wide variety of cancer types. Available data indicate that nanoparticles can enhance the effect of radiotherapy. We report the use of human mesenchymal stem cells to selectively deliver gold nanoparticles (GNPs) to MDA-MB-231 breast tumor xenografts in mice for the purpose of enhancing the effect of radiation therapy. Targeted delivery of GNPs to the tumor site, followed by irradiation of the tumor, enabled control of tumor growth. The results indicate that tumor-selective GNP delivery by human mesenchymal stem cells may represent a viable way to enhance the effectiveness of radiotherapy. Full article

We aim to extend the use of image quality metrics (IQMs) from static magnetic resonance imaging (MRI) applications to dynamic MRI studies. We assessed the use of 2 IQMs, the root mean square error and structural similarity index, in evaluating the reconstruction of quantitative dynamic contrast-enhanced (DCE) MRI data acquired using golden-angle sampling and compressed sensing (CS). To address the difficulty of obtaining ground-truth knowledge of parameters describing dynamics in real patient data, we developed a Matlab simulation framework to assess quantitative CS-DCE-MRI. We began by validating the response of each IQM to the CS-MRI reconstruction process using static data and the performance of our simulation framework with simple dynamic data. We then extended the simulations to the more realistic extended Tofts model. When assessing the Tofts model, we tested 4 different methods of selecting a reference image for the IQMs. Results from the retrospective static CS-MRI reconstructions showed that each IQM is responsive to the CS-MRI reconstruction process. Simulations of a simple contrast evolution model validated the performance of our framework. Despite the complexity of the Tofts model, both IQM scores correlated well with the recovery accuracy of a central model parameter for all reference cases studied. This finding may form the basis of algorithms for automated selection of image reconstruction aspects, such as temporal resolution, in golden-angle-sampled CS-DCE-MRI. These further suggest that objective measures of image quality may find use in general dynamic MRI applications. Full article

Extensive coronary artery calcium (CAC) diminishes the accuracy of coronary computed tomography angiography (CCTA). Many imagers adjust CCTA acquisition parameters depending on a preCCTA Agatston CAC score to optimize diagnostic accuracy. Typical preCCTA CAC imaging adds considerably to radiation exposure, partially attributable to imaging beyond the area known for highest CAC, the proximal coronary arteries. We aimed to determine whether a z-axis reduced scan length (RSL) would identify the majority of CAC and provide adequate information to computed tomography angiography providers relative to a standard full-scan length (FSL) preCCTA noncontrast CT. We retrospectively examined 200 subjects. The mean CAC scores detected in RSL and FSL were 77.4 (95% CI 50.6 to 104.3) and 93.9 (95% CI 57.3 to 130.5), respectively. RSL detected 81% of the FSL CAC. Among false negatives, with no CAC detected in RSL, FSL CAC severity was minimal (mean score 2.8). There was high concordance, averaging 88%, between CCTA imaging parameter adjustment decisions made by 2 experienced imagers based on either RSL or FSL. CAC detected and decision concordance decreased with increasing CAC burden. CAC detected was lower, and false negatives were more common in the right coronary artery owing to its anatomic course, placing larger segments outside RSL. Axial scan length and effective dose decreased 59% from FSL (∼14.5 cm/∼1.1 mSv) to RSL (∼5.9 cm/∼0.45 mSv). This retrospective study suggests that RSL identifies most CAC, results in similar CCTA acquisition parameter modifications, and reduces radiation exposure. Our colleagues corroborated these results in a recently published prospective study. Full article

Spatial resolution of metabolic imaging with hyperpolarized ¹³C-labeled substrates is limited owing to the multidimensional nature of spectroscopic imaging and the transient characteristics of dissolution dynamic nuclear polarization. In this study, a patch-based algorithm (PA) is proposed to enhance spatial resolution of hyperpolarized ¹³C human brain images by exploiting compartmental information from the corresponding high-resolution ¹H images. PA was validated in simulation and phantom studies. Effects of signal-to-noise ratio, upsampling factor, segmentation, and slice thickness on reconstructing ¹³C images were evaluated in simulation. PA was further applied to low-resolution human brain metabolite maps of hyperpolarized [1-¹³C] pyruvate and [1-¹³C] lactate with 3 compartment segmentations (gray matter, white matter, and cerebrospinal fluid). The performance of PA was compared with other conventional interpolation methods (sinc, nearest-neighbor, bilinear, and spline interpolations). The simulation and the phantom tests showed that PA improved spatial resolution by up to 8 times and enhanced the image contrast without compromising quantification accuracy or losing the intracompartment signal inhomogeneity, even in the case of low signal-to-noise ratio or inaccurate segmentation. PA also improved spatial resolution and image contrast of human ¹³C brain images. Dynamic analysis showed consistent performance of the proposed method even with the signal decay along time. In conclusion, PA can enhance low-resolution hyperpolarized ¹³C images in terms of spatial resolution and contrast by using a priori knowledge from high-resolution ¹H magnetic resonance imaging while preserving quantification accuracy and intracompartment signal inhomogeneity. Full article

Cognitive impairment amongst Parkinson’s disease (PD) patients is highly prevalent and associated with an increased risk of dementia. There is growing evidence that altered cerebrovascular functions contribute to cognitive impairment. Few studies have compared cerebrovascular changes in PD patients with normal and impaired cognition and those with mild-cognitive-impairment (MCI) without movement disorder. Here, we investigated arteriolar-cerebral-blood-volume (CBVa), an index reflecting the homeostasis of the most actively regulated segment in the microvasculature, using advanced MRI in various brain regions in PD and MCI patients and matched controls. Our goal is to find brain regions with altered CBVa that are specific to PD with normal and impaired cognition, and MCI-without-movement-disorder, respectively. In PD patients with normal cognition (n = 10), CBVa was significantly decreased in the substantia nigra, caudate and putamen when compared to controls. In PD patients with impaired cognition (n = 6), CBVa showed a decreasing trend in the substantia nigra, caudate and putamen, but was significantly increased in the presupplementary motor area and intracalcarine gyrus compared to controls. In MCI-patients-without-movement-disorder (n = 18), CBVa was significantly increased in the caudate, putamen, hippocampus and lingual gyrus compared to controls. These findings provide important information for efforts towards developing biomarkers for the evaluation of potential risk of PD dementia (PDD) in PD patients. The current study is limited in sample size and therefore is exploratory in nature. The data from this pilot study will serve as the basis for power analysis for subsequent studies to further investigate and validate the current findings. Full article

The diagnosis of patients with suspected angiomyolipoma relies on the detection of abundant macroscopic intralesional fat, which is always of no use to differentiate fat-poor angiomyolipoma (fp-AML) from renal cell carcinoma and diagnosis of fp-AML excessively depends on individual experience. Texture analysis was proven to be a potentially useful biomarker for distinguishing between benign and malignant tumors because of its capability of providing objective and quantitative assessment of lesions by analyzing features that are not visible to the human eye. This review aimed to summarize the literature on the use of texture analysis to diagnose patients with fat-poor angiomyolipoma vs those with renal cell carcinoma and to evaluate its current application, limitations, and future challenges in order to avoid unnecessary surgical resection. Full article

Many labs have been developing cellular magnetic resonance imaging (MRI), using both superparamagnetic iron oxide nanoparticles (SPIONs) and fluorine-19 (¹⁹F)-based cell labels, to track immune and stem cells used for cellular therapies. Although SPION-based MRI cell tracking has very high sensitivity for cell detection, SPIONs are indirectly detected owing to relaxation effects on protons, producing negative magnetic resonance contrast with low signal specificity. Therefore, it is not possible to reliably quantify the local tissue concentration of SPION particles, and cell number cannot be determined. ¹⁹F-based cell tracking has high specificity for perfluorocarbon-labeled cells, and ¹⁹F signal is directly related to cell number. However, ¹⁹F MRI has low sensitivity. Magnetic particle imaging (MPI) is a new imaging modality that directly detects SPIONs. SPION-based cell tracking using MPI displays great potential for overcoming the challenges of MRI-based cell tracking, allowing for both high cellular sensitivity and specificity, and quantification of SPION-labeled cell number. Here we describe nanoparticle and MPI system factors that influence MPI sensitivity and resolution, quantification methods, and give our perspective on testing and applying MPI for cell tracking. Full article