Comparison of Hyperpolarized 3He and 129Xe MR Imaging in Cystic Fibrosis Patients

MRI Application and Challenges of Hyperpolarized Carbon-13 Pyruvate in Translational and Clinical Cardiovascular Studies: A Literature Review

Cardiovascular disease shows, or may even be caused by, changes in metabolism. Hyperpolarized magnetic resonance spectroscopy and imaging is a technique that could assess the role of different aspects of metabolism in heart disease, allowing real-time metabolic flux assessment in vivo. In this review, we introduce the main hyperpolarization techniques. Then, we summarize the use of dedicated radiofrequency 13C coils, and report a state of the art of 13C data acquisition. Finally, this review provides an overview of the pre-clinical and clinical studies on cardiac metabolism in the healthy and diseased heart. We furthermore show what advances have been made to translate this technique into the clinic in the near future and what technical challenges still remain, such as exploring other metabolic substrates.

Hyperpolarized 129Xe MRI, 99mTc scintigraphy, and SPECT in lung ventilation imaging: a quantitative comparison

RATIONALE AND OBJECTIVES

The current clinical standard for functional imaging of patients with lung ailments is nuclear medicine scintigraphy and Single Photon Emission Computed Tomography (SPECT) which detect the gamma decay of inhaled radioactive tracers. Hyperpolarized (HP) Xenon-129 MRI (XeMRI) of the lungs has recently been FDA approved and provides similar functional images of the lungs with higher spatial resolution than scintigraphy and SPECT. Here we compare Technetium-99m (99mTc) diethylene-triamine-pentaacetate scintigraphy and SPECT with HP XeMRI in healthy controls, asthma, and chronic obstructive pulmonary disorder (COPD) patients.

MATERIALS AND METHODS

59 subjects, healthy, with asthma, and with COPD, underwent 99mTc scintigraphy/SPECT, standard spirometry, and HP XeMRI. XeMRI and SPECT images were registered for direct voxel-wise signal comparisons. Images were also compared using ventilation defect percentage (VDP), and a standard 6-compartment method. VDP calculated from XeMRI and SPECT images was compared to spirometry.

RESULTS

Median Pearson correlation coefficient for voxel-wise signal comparison was 0.698 (0.613-0.782) between scintigraphy and XeMRI and 0.398 (0.286-0.502) between SPECT and XeMRI. Correlation between VDP measures was r = 0.853, p < 0.05. VDP separated asthma and COPD from the control group and was significantly correlated with FEV1, FEV1/FVC, and FEF 25-75.

CONCLUSION

HP XeMRI provides equivalent information to 99mTc SPECT and standard spirometry measures. Additionally, XeMRI is non-invasive, hence it could be used for longitudinal studies for evaluating emerging treatment for lung ailments.

Paediatric Thoracic Imaging in Cystic Fibrosis in the Era of Cystic Fibrosis Transmembrane Conductance Regulator Modulation

Cystic fibrosis (CF) is one of the most common progressive life-shortening genetic conditions worldwide. Ground-breaking translational research has generated therapies that target the primary cystic fibrosis transmembrane conductance regulator (CFTR) defect, known as CFTR modulators. A crucial aspect of paediatric CF disease is the development and progression of irreversible respiratory disease in the absence of clinical symptoms. Accurate thoracic diagnostics have an important role to play in this regard. Chest radiographs are non-specific and insensitive in the context of subtle changes in early CF disease, with computed tomography (CT) providing increased sensitivity. Recent advancements in imaging hardware and software have allowed thoracic CTs to be acquired in paediatric patients at radiation doses approaching that of a chest radiograph. CFTR modulators slow the progression of CF, reduce the frequency of exacerbations and extend life expectancy. In conjunction with advances in CT imaging techniques, low-dose thorax CT will establish a central position in the routine care of children with CF. International guidelines regarding the choice of modality and timing of thoracic imaging in children with CF are lagging behind these rapid technological advances. The continued progress of personalised medicine in the form of CFTR modulators will promote the emergence of personalised radiological diagnostics.

Comparison of ventilation defects quantified by Technegas SPECT and hyperpolarized 129Xe MRI

Introduction: The ideal contrast agents for ventilation SPECT and MRI are Technegas and ¹²⁹Xe gas, respectively. Despite increasing interest in the clinical utility of ventilation imaging, these modalities have not been directly compared. Therefore, our objective was to compare the ventilation defect percent (VDP) assessed by Technegas SPECT and hyperpolarized ¹²⁹Xe MRI in patients scheduled to undergo lung cancer resection with and without pre-existing obstructive lung disease. Methods: Forty-one adults scheduled to undergo lung cancer resection performed same-day Technegas SPECT, hyperpolarized ¹²⁹Xe MRI, spirometry, and diffusing capacity of the lung for carbon monoxide (DL_CO). Ventilation abnormalities were quantified as the VDP using two different methods: adaptive thresholding (VDP_T) and k-means clustering (VDP_K). Correlation and agreement between VDP quantified by Technegas SPECT and ¹²⁹Xe MRI were determined by Spearman correlation and Bland-Altman analysis, respectively. Results: VDP measured by Technegas SPECT and ¹²⁹Xe MRI were correlated (VDP_T: r = 0.48, p = 0.001; VDP_K: r = 0.63, p < 0.0001). A 2.0% and 1.6% bias towards higher Technegas SPECT VDP was measured using the adaptive threshold method (VDP_T: 23.0% ± 14.0% vs. 21.0% ± 5.2%, p = 0.81) and k-means method (VDP_K: 9.4% ± 9.4% vs. 7.8% ± 10.0%, p = 0.02), respectively. For both modalities, higher VDP was correlated with lower FEV₁/FVC (SPECT VDP_T: r = -0.38, p = 0.01; MRI VDP_K: r = -0.46, p = 0.002) and DL_CO (SPECT VDP_T: r = -0.61, p < 0.0001; MRI VDP_K: r = -0.68, p < 0.0001). Subgroup analysis revealed that VDP measured by both modalities was significantly higher for participants with COPD (n = 13) than those with asthma (n = 6; SPECT VDP_T: p = 0.007, MRI VDP_K: p = 0.006) and those with no history of obstructive lung disease (n = 21; SPECT VDP_T: p = 0.0003, MRI VDP_K: p = 0.0003). Discussion: The burden of ventilation defects quantified by Technegas SPECT and ¹²⁹Xe MRI VDP was correlated and greater in participants with COPD when compared to those without. Our observations indicate that, despite substantial differences between the imaging modalities, quantitative assessment of ventilation defects by Technegas SPECT and ¹²⁹Xe MRI is comparable.

Image- versus histogram-based considerations in semantic segmentation of pulmonary hyperpolarized gas images

PURPOSE

To characterize the differences between histogram-based and image-based algorithms for segmentation of hyperpolarized gas lung images.

METHODS

Four previously published histogram-based segmentation algorithms (ie, linear binning, hierarchical k-means, fuzzy spatial c-means, and a Gaussian mixture model with a Markov random field prior) and an image-based convolutional neural network were used to segment 2 simulated data sets derived from a public (n = 29 subjects) and a retrospective collection (n = 51 subjects) of hyperpolarized 129Xe gas lung images transformed by common MRI artifacts (noise and nonlinear intensity distortion). The resulting ventilation-based segmentations were used to assess algorithmic performance and characterize optimization domain differences in terms of measurement bias and precision.

RESULTS

Although facilitating computational processing and providing discriminating clinically relevant measures of interest, histogram-based segmentation methods discard important contextual spatial information and are consequently less robust in terms of measurement precision in the presence of common MRI artifacts relative to the image-based convolutional neural network.

CONCLUSIONS

Direct optimization within the image domain using convolutional neural networks leverages spatial information, which mitigates problematic issues associated with histogram-based approaches and suggests a preferred future research direction. Further, the entire processing and evaluation framework, including the newly reported deep learning functionality, is available as open source through the well-known Advanced Normalization Tools ecosystem.

Quantification of Phenotypic Variability of Lung Disease in Children with Cystic Fibrosis

Cystic fibrosis (CF) lung disease has the greatest impact on the morbidity and mortality of patients suffering from this autosomal-recessive multiorgan disorder. Although CF is a monogenic disorder, considerable phenotypic variability of lung disease is observed in patients with CF, even in those carrying the same mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene or CFTR mutations with comparable functional consequences. In most patients with CF, lung disease progresses from childhood to adulthood, but is already present in infants soon after birth. In addition to the CFTR genotype, the variability of early CF lung disease can be influenced by several factors, including modifier genes, age at diagnosis (following newborn screening vs. clinical symptoms) and environmental factors. The early onset of CF lung disease requires sensitive, noninvasive measures to detect and monitor changes in lung structure and function. In this context, we review recent progress with using multiple-breath washout (MBW) and lung magnetic resonance imaging (MRI) to detect and quantify CF lung disease from infancy to adulthood. Further, we discuss emerging data on the impact of variability of lung disease severity in the first years of life on long-term outcomes and the potential use of this information to improve personalized medicine for patients with CF.