New method for 3D parametric visualization of contrast-enhanced pulmonary perfusion MRI data

Ten years of chest MRI for patients with cystic fibrosis : Translation from the bench to clinical routine

BACKGROUND

Despite recent advances in our knowledge about the pathophysiology and treatment of cystic fibrosis (CF), pulmonary involvement remains the most important determinant of morbidity and mortality in patients with CF. Since lung function testing may not be sensitive enough for subclinical disease progression, and because young children may have normal spirometry results over a longer period of time, imaging today plays an increasingly important role in clinical routine and research for the monitoring of CF lung disease. In this regard, chest magnetic resonance imaging (MRI) could serve as a radiation-free modality for structural and functional lung imaging.

METHODS

Our research agenda encompassed the entire process of development, implementation, and validation of appropriate chest MRI protocols for use with infant and adult CF patients alike.

RESULTS

After establishing a general MRI protocol for state-of-the-art clinical 1.5-T scanners based on the available sequence technology, a semiquantitative scoring system was developed followed by cross-validation of the method against the established modalities of computed tomography, radiography, and lung function testing. Cross-sectional studies were then set up to determine the sensitivity of the method for the interindividual variation of the disease and for changes in disease severity after treatment. Finally, the MRI protocol was implemented at multiple sites to be validated in a multicenter setting.

CONCLUSION

After more than a decade, lung MRI has become a valuable tool for monitoring CF in clinical routine application and as an endpoint for clinical studies.

An Improved Full Convolutional Network Combined with Conditional Random Fields for Brain MR Image Segmentation Algorithm and its 3D Visualization Analysis

Existing brain region segmentation algorithms based on deep convolutional neural networks (CNN) are inefficient for object boundary segmentation. In order to enhance the segmentation accuracy of brain tissue, this paper proposed an object region segmentation algorithm that combines pixel-level information and semantic information. Firstly, we extract semantic information by CNN with the attention module and get the coarse segmentation results through a specific pixel-level classifier. Then, we exploit conditional random fields to model the relationship between the underlying pixels so as to get local features. Finally, the semantic information and the local pixel-level information are respectively used as the unary potential and the binary potential of the Gibbs distribution, and the combination of both can obtain the fine region segmentation algorithm based on the fusion of pixel-level information and the semantic information. A large number of qualitative and quantitative test results show that our proposed algorithm has higher precision than the existing state-of-the-art deep feature models, which can better solve the problem of rough edge segmentation and produce good 3D visualization effect.

Magnetic resonance imaging of cystic fibrosis lung disease

Lung involvement in cystic fibrosis (CF) disease continues to be a major life-limiting factor of this autosomal recessive genetic disorder. Efforts made toward early diagnosis and advances in therapy have led to sustained survival of affected patients, and many are now of adult age. Because imaging provides detailed information on regional distribution of CF lung disease, repetitive imaging is required for severity assessment and therapy monitoring not only in clinical routine but also for interventional trials. Computed tomography has long succeeded chest radiograph because it provides the highest morphologic detail of airway and parenchymal changes. This is inseparably accompanied by an increase in radiation exposure to CF individuals, who are critically susceptible to, and may accumulate, relevant doses during their lifetime. Magnetic resonance imaging (MRI) as an ionizing radiation-free cross-sectional imaging modality is capable of depicting anatomic hallmarks of CF lung disease at lower spatial resolution but with enhanced tissue characterization. Comprehensive functional lung imaging (imaging of respiratory mechanics, ventilation, and lung perfusion) provides valuable additional information that cannot or can hardly be obtained by any other single diagnostic procedure. The present review article strives to present the current state of lung MRI in CF, as well as its future perspectives. Functional MRI of the CF lung is at the threshold of being considered a routine application, which, supporting early diagnosis, may help to further improve the survival of CF patients.

Correlation analysis of dual-energy CT iodine maps with quantitative pulmonary perfusion MRI

AIM: To correlate dual-energy computed tomography (DECT) pulmonary angiography derived iodine maps with parameter maps of quantitative pulmonary perfusion magnetic resonance imaging (MRI).

METHODS: Eighteen patients with pulmonary perfusion defects detected on DECT derived iodine maps were included in this prospective study and additionally underwent time-resolved contrast-enhanced pulmonary MRI [dynamic contrast enhanced (DCE)-MRI]. DCE-MRI data were quantitatively analyzed using a pixel-by-pixel deconvolution analysis calculating regional pulmonary blood flow (PBF), pulmonary blood volume (PBV) and mean transit time (MTT) in visually normal lung parenchyma and perfusion defects. Perfusion parameters were correlated to mean attenuation values of normal lung and perfusion defects on DECT iodine maps. Two readers rated the concordance of perfusion defects in a visual analysis using a 5-point Likert-scale (1 = no correlation, 5 = excellent correlation).

RESULTS: In visually normal pulmonary tissue mean DECT and MRI values were: 22.6 ± 8.3 Hounsfield units (HU); PBF: 58.8 ± 36.0 mL/100 mL per minute; PBV: 16.6 ± 8.5 mL; MTT: 17.1 ± 10.3 s. In areas with restricted perfusion mean DECT and MRI values were: 4.0 ± 3.9 HU; PBF: 10.3 ± 5.5 mL/100 mL per minute, PBV: 5 ± 4 mL, MTT: 21.6 ± 14.0 s. The differences between visually normal parenchyma and areas of restricted perfusion were statistically significant for PBF, PBV and DECT (P < 0.0001). No linear correlation was found between MRI perfusion parameters and attenuation values of DECT iodine maps (PBF: r = 0.35, P = 0.15; PBV: r = 0.34, P = 0.16; MTT: r = 0.41, P = 0.08). Visual analysis revealed a moderate correlation between perfusion defects on DECT iodine maps and the parameter maps of DCE-MRI (mean score 3.6, κ 0.45).

CONCLUSION: There is a moderate visual but not statistically significant correlation between DECT iodine maps and perfusion parameter maps of DCE-MRI.

MRI of the lung (3/3)-current applications and future perspectives

Background

MRI of the lung is recommended in a number of clinical indications. Having a non-radiation alternative is particularly attractive in children and young subjects, or pregnant women.

Methods

Provided there is sufficient expertise, magnetic resonance imaging (MRI) may be considered as the preferential modality in specific clinical conditions such as cystic fibrosis and acute pulmonary embolism, since additional functional information on respiratory mechanics and regional lung perfusion is provided. In other cases, such as tumours and pneumonia in children, lung MRI may be considered an alternative or adjunct to other modalities with at least similar diagnostic value.

Results

In interstitial lung disease, the clinical utility of MRI remains to be proven, but it could provide additional information that will be beneficial in research, or at some stage in clinical practice. Customised protocols for chest imaging combine fast breath-hold acquisitions from a “buffet” of sequences. Having introduced details of imaging protocols in previous articles, the aim of this manuscript is to discuss the advantages and limitations of lung MRI in current clinical practice.

Conclusion

New developments and future perspectives such as motion-compensated imaging with self-navigated sequences or fast Fourier decomposition MRI for non-contrast enhanced ventilation- and perfusion-weighted imaging of the lung are discussed.

Main Messages

• MRI evolves as a third lung imaging modality, combining morphological and functional information.

• It may be considered first choice in cystic fibrosis and pulmonary embolism of young and pregnant patients.

• In other cases (tumours, pneumonia in children), it is an alternative or adjunct to X-ray and CT.

• In interstitial lung disease, it serves for research, but the clinical value remains to be proven.

• New users are advised to make themselves familiar with the particular advantages and limitations.

Computed tomography and magnetic resonance imaging in cystic fibrosis lung disease

Computed tomography (CT) is the current "gold standard" for assessment of lung morphology and is so far the most reliable imaging modality for monitoring cystic fibrosis (CF) lung disease. CT has a much higher radiation exposure than chest x-ray. The cumulative radiation dose for life-long repeated CT scans has limited its use for CF patients as their life expectancy increases. Clearly, no dose would be preferable over low dose when the same or more relevant information can be obtained. Magnetic resonance imaging (MRI) is comparable to CT with regard to the detection of most morphological changes in the CF lung. It is thought to be less sensitive to detect small airway disease. At the same time, MRI is superior to CT when it comes to the assessment of functional changes such as altered pulmonary perfusion. The recommendation is to further reduce radiation dose related to the use of CT and to use MRI in the follow-up of morphological changes where possible.