Feasibility of free breathing Lung MRI for Radiotherapy using non-Cartesian k-space acquisition schemes

The use of PET/MRI in radiotherapy

Positron emission tomography/magnetic resonance imaging (PET/MRI) is a hybrid imaging technique that quantitatively combines the metabolic and functional data from positron emission tomography (PET) with anatomical and physiological information from MRI. As PET/MRI technology has advanced, its applications in cancer care have expanded. Recent studies have demonstrated that PET/MRI provides unique advantages in the field of radiotherapy and has become invaluable in guiding precision radiotherapy techniques. This review discusses the rationale and clinical evidence supporting the use of PET/MRI for radiation positioning, target delineation, efficacy evaluation, and patient surveillance.Critical relevance statement This article critically assesses the transformative role of PET/MRI in advancing precision radiotherapy, providing essential insights into improved radiation positioning, target delineation, efficacy evaluation, and patient surveillance in clinical radiology practice.Key points• The emergence of PET/MRI will be a key bridge for precise radiotherapy.• PET/MRI has unique advantages in the whole process of radiotherapy.• New tracers and nanoparticle probes will broaden the use of PET/MRI in radiation.• PET/MRI will be utilized more frequently for radiotherapy.

From Pixels to Pathology: Employing Computer Vision to Decode Chest Diseases in Medical Images

Radiology has been a pioneer in the healthcare industry's digital transformation, incorporating digital imaging systems like picture archiving and communication system (PACS) and teleradiology over the past thirty years. This shift has reshaped radiology services, positioning the field at a crucial junction for potential evolution into an integrated diagnostic service through artificial intelligence and machine learning. These technologies offer advanced tools for radiology's transformation. The radiology community has advanced computer-aided diagnosis (CAD) tools using machine learning techniques, notably deep learning convolutional neural networks (CNNs), for medical image pattern recognition. However, the integration of CAD tools into clinical practice has been hindered by challenges in workflow integration, unclear business models, and limited clinical benefits, despite development dating back to the 1990s. This comprehensive review focuses on detecting chest-related diseases through techniques like chest X-rays (CXRs), magnetic resonance imaging (MRI), nuclear medicine, and computed tomography (CT) scans. It examines the utilization of computer-aided programs by researchers for disease detection, addressing key areas: the role of computer-aided programs in disease detection advancement, recent developments in MRI, CXR, radioactive tracers, and CT scans for chest disease identification, research gaps for more effective development, and the incorporation of machine learning programs into diagnostic tools.

Multi-parametric MRI for radiotherapy simulation

Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.

Motion compensated self supervised deep learning for highly accelerated 3D ultrashort Echo time pulmonary MRI

PURPOSE

To investigate motion compensated, self-supervised, model based deep learning (MBDL) as a method to reconstruct free breathing, 3D pulmonary UTE acquisitions.

THEORY AND METHODS

A self-supervised eXtra dimension MBDL architecture (XD-MBDL) was developed that combined respiratory states to reconstruct a single high-quality 3D image. Non-rigid motion fields were incorporated into this architecture by estimating motion fields from a lower resolution motion resolved (XD-GRASP) reconstruction. Motion compensated XD-MBDL was evaluated on lung UTE datasets with and without contrast and compared to constrained reconstructions and variants of self-supervised MBDL that do not account for dynamic respiratory states or leverage motion correction.

RESULTS

Images reconstructed using XD-MBDL demonstrate improved image quality as measured by apparent SNR (aSNR), contrast to noise ratio (CNR), and visual assessment relative to self-supervised MBDL approaches that do not account for dynamic respiratory states, XD-GRASP and a recently proposed motion compensated iterative reconstruction strategy (iMoCo). Additionally, XD-MBDL reduced reconstruction time relative to both XD-GRASP and iMoCo.

CONCLUSION

A method was developed to allow self-supervised MBDL to combine multiple respiratory states to reconstruct a single image. This method was combined with graphics processing unit (GPU)-based image registration to further improve reconstruction quality. This approach showed promising results reconstructing a user-selected respiratory phase from free breathing 3D pulmonary UTE acquisitions.

Deep learning for improving ZTE MRI images in free breathing

INTRODUCTION

Despite a growing interest in lung MRI, its broader use in a clinical setting remains challenging. Several factors limit the image quality of lung MRI, such as the extremely short T2 and T2* relaxation times of the lung parenchyma and cardiac and breathing motion. Zero Echo Time (ZTE) sequences are sensitive to short T2 and T2* species paving the way to improved "CT-like" MR images. To overcome this limitation, a retrospective respiratory gated version of ZTE (ZTE4D) which can obtain images in 16 different respiratory phases during free breathing was developed. Initial performance of ZTE4D have shown motion artifacts. To improve image quality, deep learning with fully convolutional neural networks (FCNNs) has been proposed. CNNs has been widely used for MR imaging, but it has not been used for improving free-breathing lung imaging yet. Our proposed pipeline facilitates the clinical work with patients showing difficulties/uncapable to perform breath-holding, or when the different gating techniques are not efficient due to the irregular respiratory pace.

MATERIALS AND METHODS

After signed informed consent and IRB approval, ZTE4D free breathing and breath-hold ZTE3D images were obtained from 10 healthy volunteers on a 1.5 T MRI scanner (GE Healthcare Signa Artist, Waukesha, WI). ZTE4D acquisition captured all 16 phases of the respiratory cycle. For the ZTE breath-hold, the subjects were instructed to hold their breath in 5 different inflation levels ranging from full expiration to full inspiration. The training dataset consisting of ZTE-BH images of 10 volunteers was split into 8 volunteers for training, 1 for validation and 1 for testing. In total 800 ZTE breath-hold images were constructed by adding Gaussian noise and performing image transformations (translations, rotations) to imitate the effect of motion in the respiratory cycle, and blurring from varying diaphragm positions, as it appears for ZTE4D. These sets were used to train a FCNN model to remove the artificially added noise and transformations from the ZTE breath-hold images and reproduce the original quality of the images. Mean squared error (MSE) was used as loss function. The remaining 2 healthy volunteer's ZTE4D images were used to test the model and qualitatively assess the predicted images.

RESULTS

Our model obtained a MSE of 0.09% on the training set and 0.135% on the validation set. When tested on unseen data the predicted images from our model improved the contrast of the pulmonary parenchyma against air filled regions (airways or air trapping). The SNR of the lung parenchyma was quantitatively improved by a factor of 1.98 and the CNR lung- blood, which is indicating the visibility of the intrapulmonary vessels, was improved by 4.2%. Our network was able to reduce ghosting artifacts, such as diaphragm movement and blurring, and enhancing image quality.

DISCUSSION

Free-breathing 3D and 4D lung imaging with MRI is feasible, however its quality is not yet acceptable for clinical use. This can be improved with deep learning techniques. Our FCNN improves the visual image quality and reduces artifacts of free-breathing ZTE4D. Our main goal was rather to remove ghosting artifacts from the ZTE4D images, to improve diagnostic quality of the images. As main results of the network, diaphragm contour increased with sharper edges by visual inspection and less blurring of the anatomical structures and lung parenchyma.

CONCLUSION

With FCNNs, image quality of free breathing ZTE4D lung MRI can be improved and enable better visualization of the lung parenchyma in different respiratory phases.

Real-time radial reconstruction with domain transform manifold learning for MRI-guided radiotherapy

BACKGROUND

MRI-guidance techniques that dynamically adapt radiation beams to follow tumor motion in real time will lead to more accurate cancer treatments and reduced collateral healthy tissue damage. The gold-standard for reconstruction of undersampled MR data is compressed sensing (CS) which is computationally slow and limits the rate that images can be available for real-time adaptation.

PURPOSE

Once trained, neural networks can be used to accurately reconstruct raw MRI data with minimal latency. Here, we test the suitability of deep-learning-based image reconstruction for real-time tracking applications on MRI-Linacs.

METHODS

We use automated transform by manifold approximation (AUTOMAP), a generalized framework that maps raw MR signal to the target image domain, to rapidly reconstruct images from undersampled radial k-space data. The AUTOMAP neural network was trained to reconstruct images from a golden-angle radial acquisition, a benchmark for motion-sensitive imaging, on lung cancer patient data and generic images from ImageNet. Model training was subsequently augmented with motion-encoded k-space data derived from videos in the YouTube-8M dataset to encourage motion robust reconstruction.

RESULTS

AUTOMAP models fine-tuned on retrospectively acquired lung cancer patient data reconstructed radial k-space with equivalent accuracy to CS but with much shorter processing times. Validation of motion-trained models with a virtual dynamic lung tumor phantom showed that the generalized motion properties learned from YouTube lead to improved target tracking accuracy.

CONCLUSION

AUTOMAP can achieve real-time, accurate reconstruction of radial data. These findings imply that neural-network-based reconstruction is potentially superior to alternative approaches for real-time image guidance applications.

Differential value of diffusion kurtosis imaging and intravoxel incoherent motion in benign and malignant solitary pulmonary lesions

Objective

To investigate the diagnostic value of diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) whole-lesion histogram parameters in differentiating benign and malignant solitary pulmonary lesions (SPLs).

Materials and Methods

Patients with SPLs detected by chest CT examination and with further routine MRI, DKI and IVIM-DWI functional sequence scanning data were recruited. According to the pathological results, SPLs were divided into a benign group and a malignant group. Independent samples t tests (normal distribution) or Mann‒Whitney U tests (nonnormal distribution) were used to compare the differences in DKI (Dk, K), IVIM (D, D*, f) and ADC whole-lesion histogram parameters between the benign and malignant SPL groups. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficiency of the histogram parameters and determine the optimal threshold. The area under the curve (AUC) of each histogram parameter was compared by the DeLong method. Spearman rank correlation was used to analyze the correlation between histogram parameters and malignant SPLs.

Results

Most of the histogram parameters for diffusion-related values (Dk, D, ADC) of malignant SPLs were significantly lower than those of benign SPLs, while most of the histogram parameters for the K value of malignant SPLs were significantly higher than those of benign SPLs. DKI (Dk, K), IVIM (D) and ADC were effective in differentiating benign and malignant SPLs and combined with multiple parameters of the whole-lesion histogram for the D value, had the highest diagnostic efficiency, with an AUC of 0.967, a sensitivity of 90.00% and a specificity of 94.03%. Most of the histogram parameters for the Dk, D and ADC values were negatively correlated with malignant SPLs, while most of the histogram parameters for the K value were positively correlated with malignant SPLs.

Conclusions

DKI (Dk, K) and IVIM (D) whole-lesion histogram parameters can noninvasively distinguish benign and malignant SPLs, and the diagnostic performance is better than that of DWI. Moreover, they can provide additional information on SPL microstructure, which has important significance for guiding clinical individualized precision diagnosis and treatment and has potential clinical application value.

Lung Nodules Missed in Initial Staging of Breast Cancer Patients in PET/MRI-Clinically Relevant?

Simple Summary

Image-based primary staging in women with newly-diagnosed breast cancer is important to exclude distant metastases, which affect up to 10% of women. The increasing implementation of [¹⁸F]FDG-PET/MRI as a radiation-saving primary staging tool bears the risk of missing lung nodules. Thus, chest CT serves as the diagnostic of choice for the detection and classification of pulmonary nodules. The aim of this study was the evaluation of the clinical relevance of missed lung nodules at initial staging of breast cancer patients in [¹⁸F]FDG-PET/MRI compared with CT. We demonstrated in an homogeneous population of 152 patients that all patients with newly-diagnosed breast cancer and clinically-relevant lung nodules were detected at initial [¹⁸F]FDG-PET/MRI staging. However, due to the lower sensitivity of MRI in detecting lung nodules, a small proportion of clinically-relevant lung nodules were missed. Thus, a supplemental low-dose chest CT after neoadjuvant therapy should be considered for backup.

Abstract

Purpose: The evaluation of the clinical relevance of missed lung nodules at initial staging of breast cancer patients in [¹⁸F]FDG-PET/MRI compared with CT. Methods: A total of 152 patients underwent an initial whole-body [¹⁸F]FDG-PET/MRI and a thoracoabdominal CT for staging. Presence, size, shape and location for each lung nodule in [¹⁸F]FDG-PET/MRI was noted. The reference standard was established by taking initial CT and follow-up imaging into account (a two-step approach) to identify clinically-relevant lung nodules. Patient-based and lesion-based data analysis was performed. Results: No patient with clinically-relevant lung nodules was missed on a patient-based analysis with MRI VIBE, while 1/84 females was missed with MRI HASTE (1%). Lesion-based analysis revealed 4/96 (4%, VIBE) and 8/138 (6%, HASTE) missed clinically-relevant lung nodules. The average size of missed lung nodules was 3.2 mm ± 1.2 mm (VIBE) and 3.6 mm ± 1.4 mm (HASTE) and the predominant location was in the left lower quadrant and close to the hilum. Conclusion: All patients with newly-diagnosed breast cancer and clinically-relevant lung nodules were detected at initial [¹⁸F]FDG-PET/MRI staging. However, due to the lower sensitivity in detecting lung nodules, a small proportion of clinically-relevant lung nodules were missed. Thus, supplemental low-dose chest CT after neoadjuvant therapy should be considered for backup.

Dynamic imaging using motion-compensated smoothness regularization on manifolds (MoCo-SToRM)

Objective. We introduce an unsupervised motion-compensated reconstruction scheme for high-resolution free-breathing pulmonary magnetic resonance imaging.Approach. We model the image frames in the time series as the deformed version of the 3D template image volume. We assume the deformation maps to be points on a smooth manifold in high-dimensional space. Specifically, we model the deformation map at each time instant as the output of a CNN-based generator that has the same weight for all time-frames, driven by a low-dimensional latent vector. The time series of latent vectors account for the dynamics in the dataset, including respiratory motion and bulk motion. The template image volume, the parameters of the generator, and the latent vectors are learned directly from the k-t space data in an unsupervised fashion.Main results. Our experimental results show improved reconstructions compared to state-of-the-art methods, especially in the context of bulk motion during the scans.Significance. The proposed unsupervised motion-compensated scheme jointly estimates the latent vectors that capture the motion dynamics, the corresponding deformation maps, and the reconstructed motion-compensated images from the raw k-t space data of each subject. Unlike current motion-resolved strategies, the proposed scheme is more robust to bulk motion events during the scan.

Development and validation of MRI-based radiomics signatures models for prediction of disease-free survival and overall survival in patients with esophageal squamous cell carcinoma

OBJECTIVES

To develop and validate an optimal model based on the 1-mm-isotropic-3D contrast-enhanced StarVIBE MRI sequence combined with clinical risk factors for predicting survival in patients with esophageal squamous cell carcinoma (ESCC).

METHODS

Patients with ESCC at our institution from 2015 to 2017 participated in this retrospective study based on prospectively acquired data, and were randomly assigned to training and validation groups at a ratio of 7:3. Random survival forest (RSF) and variable hunting methods were used to screen for radiomics features and LASSO-Cox regression analysis was used to build three models, including clinical only, radiomics only and combined clinical and radiomics models, which were evaluated by concordance index (CI) and calibration curve. Nomograms and decision curve analysis (DCA) were used to display intuitive prediction information.

RESULTS

Seven radiomics features were selected from 434 patients, combined with clinical features that were statistically significant to construct the predictive models of disease-free survival (DFS) and overall survival (OS). The combined model showed the highest performance in both training and validation groups for predicting DFS ([CI], 0.714, 0.729) and OS ([CI], 0.730, 0.712). DCA showed that the net benefit of the combined model and of the clinical model is significantly greater than that of the radiomics model alone at different threshold probabilities.

CONCLUSIONS

We demonstrated that a combined predictive model based on MR Rad-S and clinical risk factors had better predictive efficacy than the radiomics models alone for patients with ESCC.

KEY POINTS

• Magnetic resonance-based radiomics features combined with clinical risk factors can predict survival in patients with ESCC. • The radiomics nomogram can be used clinically to predict patient recurrence, DFS, and OS. • Magnetic resonance imaging is highly reproducible in visualizing lesions and contouring the whole tumor.

Free-breathing 3D Stack of Stars GRE (StarVIBE) sequence for detecting pulmonary nodules in 18F-FDG PET/MRI

BACKGROUND

The free-breathing T1-weighted 3D Stack of Stars GRE (StarVIBE) MR sequence potentially reduces artifacts in chest MRI. The purpose of this study was to evaluate StarVIBE for the detection of pulmonary nodules in ¹⁸F-FDG PET/MRI.

MATERIAL AND METHODS

In this retrospective analysis, conducted on a prospective clinical trial cohort, 88 consecutive women with newly diagnosed breast cancer underwent both contrast-enhanced whole-body ¹⁸F-FDG PET/MRI and computed tomography (CT). Patients' chests were examined on CT as well as on StarVIBE and conventional T1-weighted VIBE and T2-weighted HASTE MR sequences, with CT serving as the reference standard. Presence, size, and location of all detectable lung nodules were assessed. Wilcoxon test was applied to compare nodule features and Pearson's, and Spearman's correlation coefficients were calculated.

RESULTS

Out of 65 lung nodules detected in 36 patients with CT (3.7 ± 1.4 mm), StarVIBE was able to detect 31 (47.7%), VIBE 26 (40%) and HASTE 11 (16.8%), respectively. Overall, CT showed a significantly higher detectability than all MRI sequences combined (65 vs. 36, difference 44.6%, p < 0.001). The VIBE showed a significantly better detection rate than the HASTE (23.1%, p = 0.001). Detection rates between StarVIBE and VIBE did not significantly differ (7.7%, p = 0.27), but the StarVIBE showed a significant advantage detecting centrally located pulmonary nodules (66.7% vs. 16.7%, p = 0.031). There was a strong correlation in nodule size between CT and MRI sequences (HASTE: ρ = 0.80, p = 0.003; VIBE: ρ = 0.77, p < 0.001; StarVIBE: ρ = 0.78, p < 0.001). Mean image quality was rated as good to excellent for CT and MRI sequences.

CONCLUSION

The overall lung nodule detection rate of StarVIBE was slightly, but not significantly, higher than conventional T1w VIBE and significantly higher than T2w HASTE. Detectability of centrally located nodules is better with StarVIBE than with VIBE. Nevertheless, all MRI analyses demonstrated considerably lower detection rates for small lung nodules, when compared to CT.

Applying Compressed Sensing Volumetric Interpolated Breath-Hold Examination and Spiral Ultrashort Echo Time Sequences for Lung Nodule Detection in MRI

This prospective study aimed to investigate the ability of spiral ultrashort echo time (UTE) and compressed sensing volumetric interpolated breath-hold examination (CS-VIBE) sequences in magnetic resonance imaging (MRI) compared to conventional VIBE and chest computed tomography (CT) in terms of image quality and small nodule detection. Patients with small lung nodules scheduled for video-assisted thoracoscopic surgery (VATS) for lung wedge resection were prospectively enrolled. Each patient underwent non-contrast chest CT and non-contrast MRI on the same day prior to thoracic surgery. The chest CT was performed to obtain a standard reference for nodule size, location, and morphology. The chest MRI included breath-hold conventional VIBE and CS-VIBE with scanning durations of 11 and 13 s, respectively, and free-breathing spiral UTE for 3.5–5 min. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and normal structure visualizations were measured to evaluate MRI quality. Nodule detection sensitivity was evaluated on a lobe-by-lobe basis. Inter-reader and inter-modality reliability analyses were performed using the Cohen κ statistic and the nodule size comparison was performed using Bland–Altman plots. Among 96 pulmonary nodules requiring surgery, the average nodule diameter was 7.7 ± 3.9 mm (range: 4–20 mm); of the 73 resected nodules, most were invasive cancer (74%) or pre-invasive carcinoma in situ (15%). Both spiral UTE and CS-VIBE images achieved significantly higher overall image quality scores, SNRs, and CNRs than conventional VIBE. Spiral UTE (81%) and CS-VIBE (83%) achieved a higher lung nodule detection rate than conventional VIBE (53%). Specifically, the nodule detection rate for spiral UTE and CS-VIBE reached 95% and 100% for nodules >8 and >10 mm, respectively. A 90% detection rate was achieved for nodules of all sizes with a part-solid or solid morphology. Spiral UTE and CS-VIBE under-estimated the nodule size by 0.2 ± 1.4 mm with 95% limits of agreement from −2.6 to 2.9 mm and by 0.2 ± 1.7 mm with 95% limits of agreement from −3.3 to 3.5 mm, respectively, compared to the reference CT. In conclusion, chest CT remains the gold standard for lung nodule detection due to its high image resolutions. Both spiral UTE and CS-VIBE MRI could detect small lung nodules requiring surgery and could be considered a potential alternative to chest CT; however, their clinical application requires further investigation.

Free-breathing radial 3D fat-suppressed T1-weighted gradient echo (r-VIBE) sequence for assessment of pulmonary lesions: a prospective comparison of CT and MRI

Purpose

To determine whether the pulmonary MR imaging with free-breathing radial 3D fat-suppressed T1-weighted gradient echo (r-VIBE) sequence can detect lung lesions and display lesion profiles with an accuracy comparable to that of computed tomography (CT), which is the reference standard in this study.

Population

Sixty-three consecutive patients were prospectively enrolled between October, 2016 and March, 2017. All the patients received both 3T MRI scanning with a free-breathing r-VIBE sequence and chest standard CT. Morphologic features of lesions were evaluated by two radiologists with a 5-point system. Chest standard CT were used as reference standard. Weighted kappa analysis and chi-squared test were used to determine both inter-observer agreement and inter-method agreement.

Results

A total of 210 solid pulmonary nodules or masses and 1 ground-glass nodule were detected by CT. Compared to CT, r-VIBE correctly detected 95.7% of pulmonary nodules, including 100% of detection rate with diameter greater than 6 mm, 92.3% of pulmonary nodules with diameter between 4 and 6 mm, and 83.3% of pulmonary nodules with diameter less than 4 mm The inter-method agreements between r-VIBE and standard-dose CT were either “substantial” or “excellent” in the evaluation of following features of pulmonary nodules with diameter more than 10mm: including lobulation, spiculation, convergence of vessels, bubble-like attenuation, cavitation and mediastinal lymph node enlargement (0.605≤K≤1.000; P<0.0001). However, K values for inter-method agreements were significant but “moderate” or “poor” for evaluating pleural tag, halo, and calcification (0.355≤ K≤0.451; P<0.0001).

Conclusion

The use of pulmonary MR imaging with r-VIBE showed high detection rate of pulmonary nodules and inter-method agreement with CT. It is also useful for nodule morphologic assessment.

Detection of lung lesions in breath-hold VIBE and free-breathing Spiral VIBE MRI compared to CT

BACKGROUND

Detection of pulmonary nodules in MRI requires fast imaging strategies without respiratory motion impairment, such as single-breath-hold Cartesian VIBE. As patients with pulmonary diseases have limited breath-hold capacities, this study investigates the clinical feasibility of non-Cartesian Spiral VIBE under free-breathing compared to CT as the gold standard.

METHODS

Prospective analysis of 27 oncological patients examined in PET/CT and PET/MR. A novel motion-robust 3D ultrashort-echo-time (UTE) MR sequence was evaluated in comparison with CT and conventional breath-hold MR. CT scans were performed under breath-hold in end-expiratory and end-inspiratory position (CT ex, CT in). MR data was acquired with non-contrast-enhanced breath-hold Cartesian VIBE followed by a free-breathing 3D UTE Spiral VIBE. Impact of respiratory motion on pulmonary evaluation was investigated by two readers in Cartesian VIBE, followed by UTE Spiral VIBE and CT ex and the reference standard of CT in. Diagnostic accuracy was calculated, and visual image quality assessed.

RESULTS

Higher detection rate and sensitivity of pulmonary nodules in free-breathing UTE Spiral VIBE in comparison with breath-hold Cartesian VIBE were found for lesions > 10 mm (UTE Spiral VIBE/VIBE/CT ex): 93%/54%/100%; Lesions 5-10 mm: 67%/25%/ 92%; Lesions < 5 mm: 11%/11%/78%. Lobe-based analysis revealed sensitivities and specificities of 64%/96%/41% and 96%/93%/100% for UTE Spiral VIBE/VIBE/CT ex.

CONCLUSION

Free-breathing UTE Spiral VIBE indicates higher sensitivity for detection of pulmonary nodules than breath-hold Cartesian VIBE and is a promising but time-consuming approach. However, sensitivity and specificity of inspiratory CT remain superior in comparison and should be preferred for detection of pulmonary lesions.

Dynamic contrast-enhanced magnetic resonance imaging of the lung reveals important pathobiology in idiopathic pulmonary fibrosis

Introduction

Evidence suggests that abnormalities occur in the lung microvasculature in idiopathic pulmonary fibrosis (IPF). We hypothesised that dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) could detect alterations in permeability, perfusion and extracellular extravascular volume in IPF, thus providing in vivo regional functional information not otherwise available.

Methods

Healthy controls and IPF subjects underwent DCE-MRI of the thorax using a dynamic volumetric radial sampling sequence and administration of gadoterate meglumine at a dose of 0.1 mmol·kg⁻¹ at 2 mL·s⁻¹. Model-free analysis of signal intensity versus time curves in regions of interest from a lower, middle and upper axial plane, a posterior coronal plane and the whole lung yielded parameters reflective of perfusion and permeability (peak enhancement and rate of contrast arrival (k_washin)) and the extracellular extravascular space (rate of contrast clearance (k_washout)). These imaging parameters were compared between IPF and healthy control subjects, and between fast/slow IPF progressors.

Results

IPF subjects (n=16, 56% male, age (range) 67.5 (60–79) years) had significantly reduced peak enhancement and slower k_washin in all measured lung regions compared to the healthy volunteers (n=17, 65% male, age (range) 58 (51–63) years) on unadjusted analyses consistent with microvascular alterations. k_washout, as a measure of the extravascular extracellular space, was significantly slower in the lower lung and posterior coronal regions in the IPF subjects consistent with an increased extravascular extracellular space. All estimates were attenuated after adjusting for age. Similar trends were observed, but only the associations with k_washin in certain lung regions remained statistically significant. Among IPF subjects, k_washout rates nearly perfectly discriminated between those with rapidly progressive disease versus those with stable/slowly progressive disease.

Conclusions

DCE-MRI detects changes in the microvasculature and extravascular extracellular space in IPF, thus providing in vivo regional functional information.

Dynamic contrast-enhanced MRI demonstrates important in vivo lung regional microvascular and extravascular extracellular differences between IPF patients and healthy controls. These results signify IPF pathobiology and may have prognostic significance.https://bit.ly/3l14SWM

Radiomics nomogram analysis of T2-fBLADE-TSE in pulmonary nodules evaluation

OBJECTIVES

To develop and validate a radiomics nomogram for differentiating between malignant pulmonary nodules and benign nodules.

METHODS

56 benign and 51 malignant nodules from 96 patients were analyzed using manual segmentation of the T2-fBLADE-TSE, while the nodules signal intensity (SIlesion), lesion muscle ratio (LMR) and nodule size were all measured and recorded. The maximum relevance and minimum redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) were used to select nonzero coefficients and develop the model in pulmonary nodules diagnosis. The radiomics nomogram was also developed. The clinical prediction value was determined by the decision curve analysis (DCA).

RESULTS

The nodule size, SIlesion and LMR of the benign group were 1.78 ± 0.57 cm, 227.50 ± 81.39 and 2.40 ± 1.27 respectively, in contrast to the 2.00 ± 0.64 cm, 232.87 ± 82.21 and 2.17 ± 0.91, respectively, in the malignant group (P = 0.09, 0.60 and 0.579). A total of 13 radiomics features were retained. The Rad-score of the benign nodules group was lower than that of the malignant nodules group (P < 0.001 & 0.049, training & test set). The AUC of radiomics signature for nodules diagnosis was 0.82 (95% CI, 0.73-0.91) in the training set and 0.71 (95% CI, 0.51-0.90) in the test set. A nomogram, consisting of 13 radiomics features and nodule size, produced good prediction in the training set (AUC, 0.82; 95% CI, 0.73-0.91), which was significantly better than that of T2-based quantitative parameters (AUC, 0.62; 95% CI, 0.50-0.75, P = 0.003). In the test set, the performance of radiomics nomogram (AUC, 0.70; 95% CI, 0.51-0.90) was also better than that of T2-based quantitative parameters (AUC, 0.46; 95% CI, 0.25-0.67) (P = 0.145). The DCA showed that radiomics nomogram and T2-based quantitative parameter had overall net benefits, while the performance of nomogram was better.

CONCLUSION

We constructed and validated a T2-fBLADE-TSE-based radiomics nomogram that can help to differentiate between malignant pulmonary nodules and benign nodules.

Detecting small pulmonary nodules with spiral ultrashort echo time sequences in 1.5 T MRI

OBJECTIVE

This study investigated ultrashort echo time (UTE) sequences in 1.5 T magnetic resonance imaging (MRI) for small lung nodule detection.

MATERIALS AND METHODS

A total of 120 patients with 165 small lung nodules before video-associated thoracoscopic resection were enrolled. MRI sequences included conventional volumetric interpolated breath-hold examination (VIBE, scan time 16 s), spiral UTE (TE 0.05 ms) with free-breathing (scan time 3.5-5 min), and breath-hold sequences (scan time 20 s). Chest CT provided a standard reference for nodule size and morphology. Nodule detection sensitivity was evaluated on a lobe-by-lobe basis.

RESULTS

The nodule detection rate was significantly higher in spiral UTE free-breathing (> 78%, p < 0.05) and breath-hold sequences (> 75%, p < 0.05) compared with conventional VIBE (> 55%), reaching 100% when nodule size was > 16 mm, and reaching 95% when nodules were in solid morphology, regardless of size. The inter-sequence reliability between free-breathing and breath-hold spiral UTE was good (κ > 0.80). Inter-reader agreement was also high (κ > 0.77) for spiral UTE sequences. Nodule size measurements were consistent between CT and spiral UTE MRI, with a minimal bias up to 0.2 mm.

DISCUSSION

Spiral UTE sequences detect small lung nodules that warrant surgery, offers realistic scan times for clinical work, and could be implemented as part of routine lung MRI.

A review of the role of MRI in diagnosis and treatment of early stage lung cancer

Despite magnetic resonance imaging (MRI) being a mainstay in the oncologic care for many disease sites, it has not routinely been used in early lung cancer diagnosis, staging, and treatment. While MRI provides improved soft tissue contrast compared to computed tomography (CT), an advantage in multiple organs, the physical properties of the lungs and mediastinum create unique challenges for lung MRI. Although multi-detector CT remains the gold standard for lung imaging, advances in MRI technology have led to its increased clinical relevance in evaluating early stage lung cancer. Even though positron emission tomography is used more frequently in this context, functional MR imaging, including diffusion-weighted MRI and dynamic contrast-enhanced MRI, are emerging as useful modalities for both diagnosis and evaluation of treatment response for lung cancer. In parallel with these advances, the development of combined MRI and linear accelerator devices (MR-linacs), has spurred the integration of MRI into radiation treatment delivery in the form of MR-guided radiotherapy (MRgRT). Despite challenges for MRgRT in early stage lung cancer radiotherapy, early data utilizing MR-linacs shows potential for the treatment of early lung cancer. In both diagnosis and treatment, MRI is a promising modality for imaging early lung cancer.

Feasibility of pulmonary MRI for nodule detection in comparison to computed tomography

Background

To assess the feasibility of various magnetic resonance imaging (MRI) sequences for the detection of pulmonary nodules by comparing the detection rate of computed tomography (CT).

Methods

Forty-two patients with pulmonary nodules detected by multi-slice CT (MSCT) were prospectively enrolled in the present study between November 2016 and February 2017. Chest MRI was acquired within 24 h of CT. The MRI protocol included free-breathing radial VIBE (r-VIBE) and a conventional breathhold T1-weighted VIBE (C-VIBE) were analyzed by two independent radiologists. Both detection and morphology results of each MRI image were recorded. Subjective image evaluation in terms of overall nodule morphology on the MRI images was carried out using the 4-point scoring criteria. The MRI results were compared with those from CT, with the results of MSCT serving as the reference standard.

Results

Two hundred and fifty-eight solid pulmonary nodules in 42 patients were detected by CT. The r-VIBE correctly detected 94% of the pulmonary nodules as compared with CT. The detection rate increased to 100% for lesions ≥6 mm. The C-VIBE had a lower overall detection rate (64.3%) of pulmonary nodules. The difference in the subjective image evaluation scores between the two sequences was statistically significant (p < 0.001).

Conclusion

Significantly increased detection rates were obtained with free-breathing r-VIBE as compared with C-VIBE for the detection of pulmonary nodules and also provided more information when evaluating the nodules as compared with C-VIBE.

A pilot study of native T1-mapping for focal pulmonary lesions in 3.0 T magnetic resonance imaging: size estimation and differential diagnosis

Background

To investigate the accuracy of size estimation and potential diagnosis efficacy of native T1-mapping in focal pulmonary lesion, compared to T1-star 3D-volumetric interpolated breath-hold sequence (VIBE), T2-fBLADE turbo-spin echo (TSE), and computed tomography (CT).

Methods

Thirty-nine patients with CT-detected focal pulmonary lesions underwent thoracic 3.0-T magnetic resonance imaging (MRI) using axial free-breathing 3D T1-star VIBE, respiratory triggered T2-fBLADE TSE, breath-hold T1-Turbo fast low angle shot (FLASH) and T1-FLASH 3D. Native T1-mapping images were generated by T1-FLASH 3D with B1-filed correction by T1-Turbo FLASH. The intraclass correlation coefficient (ICC) and Bland-Altman plots were used to evaluate intra-observer agreement and inter-method reliability of diameter measurements. Native T1-values were measured and compared among the malignancy, tuberculosis, non-tuberculosis benign groups using Mann-Whitney U tests.

Results

Forty-five focal pulmonary lesions were displayed by CT, native T1-mapping, T1-star VIBE, and T2-fBLADE TSE. T1-mapping-based diameter measurements yielded an intra-observer ICC of 0.995. Additionally, inter-method measurements were highly consistent (T1-mapping & T1-star VIBE: ICC 0.982, T1-mapping & T2-fBLADE TSE: ICC 0.978, T1-mapping & CT: ICC 0.972). For lesions <3.00 cm, T1-mapping intra-observer (ICC 0.982) and inter-method diameter measurements were also highly consistent (T1-mapping & CT: ICC 0.823). Native T1-values of malignant tumors were lower than those of the non-tuberculosis benign lesions (P=0.003). Native T1-values of tuberculosis were lower than those of the non-tuberculosis benign lesions (P=0.002). Native T1-values showed no statistically significant differences between malignant tumors and tuberculosis (P=0.059).

Conclusions

Native T1-mapping enable accurate and reliable diameter measurement. Native T1-values potentially differentiate malignant tumors or tuberculosis from non-tuberculosis benign lesions.

Clinical Implementation of a Free-Breathing, Motion-Robust Dynamic Contrast-Enhanced MRI Protocol to Evaluate Pleural Tumors

OBJECTIVE. The purpose of this study was to develop a motion insensitive clinical dynamic contrast-enhanced MRI (DCE-MRI) protocol to assess the response of pleural tumors in clinical trials. MATERIALS AND METHODS. Thirty-two patients with pleura-based lesions were administered contrast material and imaged with gradient-recalled echo DCE-MRI sequence variants: either a traditional cartesian k-space acquisition (FLASH), a time-resolved imaging with stochastic trajectories acquisition (TWIST), or a radial stack-of-stars acquisition (radial) sequence in addition to other standard-of-care imaging sequences. Each image acquisition's sensitivity to motion was evaluated by comparing the motion of the thoracic border in 3D throughout the acquisition. One-way ANOVA was used to compare the image quality between different acquisitions. The 95% CIs were calculated for mean thoracic border displacement. The effects of motion on kinetic parameter estimation were explored with simulations according to clinically acquired data. RESULTS. Radial was the most motion-robust sequence with subvoxel mean displacement in the superior-inferior direction (0.4 ± 1.2 [SD] mm). FLASH showed intermediate displacement (4.6 ± 2.0 mm), whereas TWIST was most sensitive to motion (6.4 ± 3.4 mm). Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the images acquired with the radial sequence were on par or better than the FLASH and TWIST sequences when reconstructed with an improved density compensation algorithm. Simulations showed that motion on scans showing pleural-based lesions can lead to markedly inaccurate kinetic parameter estimation and inappropriate kinetic model convergence within a nested model analysis. CONCLUSION. A practical radial k-space trajectory sequence that provides motion-insensitive pharmacokinetic parameters was incorporated as part of the DCE-MRI protocol of pleural tumors. Validation and usefulness in clinical trials assessing response to therapy is needed.

Proton MRI of the Lung: How to Tame Scarce Protons and Fast Signal Decay

Pulmonary proton MRI techniques offer the unique possibility of assessing lung function and structure without the requirement for hyperpolarization or dedicated hardware, which is mandatory for multinuclear acquisition. Five popular approaches are presented and discussed in this review: 1) oxygen enhanced (OE)-MRI; 2) arterial spin labeling (ASL); 3) Fourier decomposition (FD) MRI and other related methods including self-gated noncontrast-enhanced functional lung (SENCEFUL) MR and phase-resolved functional lung (PREFUL) imaging; 4) dynamic contrast-enhanced (DCE) MRI; and 5) ultrashort TE (UTE) MRI. While DCE MRI is the most established and well-studied perfusion measurement, FD MRI offers a free-breathing test without any contrast agent and is predestined for application in patients with renal failure or with low compliance. Additionally, FD MRI and related methods like PREFUL and SENCEFUL can act as an ionizing radiation-free V/Q scan, since ventilation and perfusion information is acquired simultaneously during one scan. For OE-MRI, different concentrations of oxygen are applied via a facemask to assess the regional change in T₁ , which is caused by the paramagnetic property of oxygen. Since this change is governed by a combination of ventilation, diffusion, and perfusion, a compound functional measurement can be achieved with OE-MRI. The known problem of fast T₂ * decay of the lung parenchyma leading to a low signal-to-noise ratio is bypassed by the UTE acquisition strategy. Computed tomography (CT)-like images allow the assessment of lung structure with high spatial resolution without ionizing radiation. Despite these different branches of proton MRI, common trends are evident among pulmonary proton MRI: 1) free-breathing acquisition with self-gating; 2) application of UTE to preserve a stronger parenchymal signal; and 3) transition from 2D to 3D acquisition. On that note, there is a visible convergence of the different methods and it is not difficult to imagine that future methods will combine different aspects of the presented methods.

Free-breathing dynamic contrast-enhanced magnetic resonance of interstitial lung fibrosis

PURPOSE

Computed tomography (CT) imaging is the standard to assess interstitial lung disease. Magnetic resonance (MR) is potentially advantageous due to superior tissue characterization and better assessment of blood flow dynamics. This study aimed to evaluate idiopathic pulmonary fibrosis (IPF) using prototype 4D Stack of Stars GRE (StarVIBE) MR and compare it to CT.

METHOD

This IRB-approved prospective study included 13 patients [5F:8M; average age 66 ± 8.1 years] with pulmonary fibrosis, and 12 healthy controls [3F:9M; average age 55 ± 3.6 years]. MR of the chest included noncontrast steady-state free precession imaging (SSFP) and free-breathing 4D StarVIBE sequence with intravenous contrast administration up to 160 s. The images were assessed for quality and artifacts. The image resolution was evaluated based on the visibility of the smallest bronchi, vessels, lymph nodes, and pleural fissures. Independent assessment of reticulation, ground-glass opacity, and traction bronchiectasis was performed and compared to CT.

RESULTS

The StarVIBE images had fewer artifacts and higher spatial resolution. The findings associated with IPF were significantly better seen with StarVIBE, with superior CT correlation.

CONCLUSION

Contrast-enhanced free-breathing StarVIBE MR can generate high quality images with good correlation to CT in patients with IPF, and with high spatial and temporal resolution to generate rapid sequential dynamic images.

3T magnetic resonance for evaluation of adult pulmonary tuberculosis

OBJECTIVES

To evaluate image quality and detection rate of four 3T magnetic resonance imaging (MRI) sequences and MRI performances in pulmonary tuberculosis (TB) when compared to computed tomography (CT).

METHODS

Forty patients with pulmonary tuberculosis separately underwent CT and 3T-MRI with T1-weighted free-breathing star-volumetric interpolated breath-hold examination (Star-VIBE) and standard VIBE, T2-weighted two-dimensional fast BLADE turbo spin-echo (2D-fBLADE TSE) and three-dimensional isotropic turbo spin-echo (3D-SPACE). Four MRI sequences were compared in terms of detection rate and image quality, which consisted of signal to noise ratio (SNR), contrast to noise ratio (CNR) and 5-point scoring scale. The total sensitivity was also compared between CT and MRI. Inter-observer agreement on 5-point scoring scale was calculated by Cohen's kappa (k). SNR, CNR and 5-point scoring scale were compared using two-tailed pared t-test. Using CT as a reference, the MRI detection rate of pulmonary abnormality was evaluated by Pearson's Chi-square test. Furthermore, the sizes of the nodules (≥5 mm) were compared using intraclass correlation coefficient.

RESULTS

In this study, Free-breathing Star-VIBE had significantly better SNR and identical CNR compared with standard VIBE. 2D-fBLADE TSE had statistically higher SNR but uniform or inferior CNR compared with 3D-SPACE. Inter-observers showed excellent agreement on 5-point scoring scale. The average score of Star-VIBE and VIBE had no difference. The average score of 2D-fBLADE TSE was higher than 3D-SPACE. There were no statistical differences in the detection rates of non-calcified parenchymal lesions between Star-VIBE and standard VIBE, 2D-fBALDE TSE and 3D-SPACE. MRI is comparable to CT in detecting consolidation, cavity, non-calcified nodules of ≥5 mm and tree-in-bud signs compared to CT. MRI detected non-calcified nodules of ＜5 mm, 5-10 mm, ≥10 mm and calcified nodules with sensitivity of 69.6%, 90.6%, 100% and 89.5% respectively. In addition, the sizes of the nodules (≥5 mm) had statistical consistency. MRI is more sensitive in detecting caseous necrosis, liquefaction, active cavity, abnormalities of lymph nodes and pleura.

CONCLUSIONS

T1-weighted free-breathing Star-VIBE and T2-weighted 2D-fBLADE TSE, both with satisfactory image quality, are suitable for patients with pulmonary TB who need long-term follow-ups in clinical routine, especially for children, young women and pregnant women.

Improving dynamic contrast-enhanced MRI of the lung using motion-weighted sparse reconstruction: Initial experiences in patients

PURPOSE

The purpose of this study was to evaluate the performance of motion-weighted Golden-angle RAdial Sparse Parallel MRI (motion-weighted GRASP) for free-breathing dynamic contrast-enhanced MRI (DCE-MRI) of the lung.

METHODS

Motion-weighted GRASP incorporates a soft-gating motion compensation algorithm into standard GRASP reconstruction, so that motion-corrupted motion k-space (e.g., k-space acquired in inspiratory phases) contributes less to the final reconstructed images. Lung MR data from 20 patients (mean age = 57.9 ± 13.5) with known pulmonary lesions were retrospectively collected for this study. Each subject underwent a free-breathing DCE-MR scan using a fat-statured T₁-weighted stack-of-stars golden-angle radial sequence and a post-contrast breath-hold MR scan using a Cartesian volumetric-interpolated imaging sequence (BH-VIBE). Each radial dataset was reconstructed using GRASP without motion compensation and motion-weighted GRASP. All MR images were visually evaluated by two experienced radiologists blinded to reconstruction and acquisition schemes independently. In addition, the influence of motion-weighted reconstruction on dynamic contrast-enhancement patterns was also investigated.

RESULTS

For image quality assessment, motion-weighted GRASP received significantly higher visual scores than GRASP (P < 0.05) for overall image quality (3.68 vs. 3.39), lesion conspicuity (3.54 vs. 3.18) and overall artifact level (3.53 vs. 3.15). There was no significant difference (P > 0.05) between the breath-hold BH-VIBE and motion-weighted GRASP images. For assessment of temporal fidelity, motion-weighted GRASP maintained a good agreement with respect to GRASP.

CONCLUSION

Motion-weighted GRASP achieved better reconstruction performance in free-breathing DCE-MRI of the lung compared to standard GRASP, and it may enable improved assessment of pulmonary lesions.

A fast volumetric 4D-MRI with sub-second frame rate for abdominal motion monitoring and characterization in MRI-guided radiotherapy

Background

To propose a fast volumetric 4D-MRI based on 3D pulse sequence acquisition for abdominal motion monitoring and characterization in MRI-guided radiotherapy (MRgRT).

Methods

A 3D spoiled gradient echo sequence volumetric interpolated breath-hold examination (VIBE) [repetition time/echo time (TR/TE) =0.53/1.57 ms, flip-angle =5°, receiver bandwidth (RBW) =1,400 Hz/voxel] based 4D-MRI acquisition, accelerated by 4-fold controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA), named CAIPIRINHA-VIBE 4D-MRI, was implemented on a 1.5T MRI simulator (MR-sim) and applied for abdominal imaging of nine healthy volunteers under free breathing. One hundred and forty-four dynamics of the entire abdomen volume (56 slices), in total 8,064 (144×56) images with a voxel size of 2.7×2.7×4.0 mm³, were acquired in 89 s for 4D-MRI. This CAIPIRINHA-VIBE 4D-MRI was qualitatively compared with a 2D half-Fourier acquisition single-shot turbo spin-echo (2D-HASTE) based 4D-MRI. The motions of liver dome, kidney and spleen were analyzed using the CAIPIRINHA-VIBE 4D-MRI data. The kidney motion was quantitatively characterized in terms of motion range and the correlations between left and right kidneys.

Results

CAIPIRINHA-VIBE 4D-MRI was successfully conducted in all subjects. CAIPIRINHA-VIBE 4D-MRI exhibited much higher effective volumetric temporal resolution (0.615 vs. ~5 s/volume) and better reconstructed volume consistency than 2D-HASTE 4D-MRI. CAIPIRINHA-VIBE 4D-MRI was able to characterize the respiratory motion of abdominal organs simultaneously in three orthogonal directions, and could potentially be used for whole abdomen deformable motion tracking. Renal motion range was most pronounced in superior-inferior (SI) direction (L: 10.03±2.65 mm; R: 10.38±2.80 mm), significantly larger (P<0.001) than that in anterior-posterior (AP) and the least in left-right (LR) directions. Right kidney had significantly larger mobility (4.18±2.19 vs. 2.32±1.34 mm, P=0.045) than left kidney in AP, but not in LR and SI directions. The Pearson correlation coefficients r between left and right kidney motion were 0.5063 (P=0.164), 0.6624 (P=0.052) and 0.5752 (P=0.105) in LR, AP and SI correspondingly. The correlation of renal motion in SI and AP was found significant in right kidney (r=0.843, P=0.004) but not in left kidney (r=0.467, P=0.205).

Conclusions

A fast volumetric 4D-MRI was implemented for abdominal motion monitoring in MRgRT. A sub-second volumetric temporal resolution of 0.615 s, covering the entire abdomen, was demonstrated for respiratory motion monitoring and characterization. This technique holds potentials for MRgRT applications.

Comparison of four dimensional computed tomography and magnetic resonance imaging in abdominal radiotherapy planning

Background and Purpose

Four-dimensional (4D) computed tomography (CT) is widely used in radiotherapy (RT) planning and remains the current standard for motion evaluation. We assess a 4D magnetic resonance imaging (MRI) sequence in terms of motion and image quality in a phantom, healthy volunteers and patients undergoing RT.

Materials and Methods

The 4D-MRI sequence is a prototype T1-weighted 3D gradient echo with radial acquisition with self-gating. The accuracy of the 4D-MRI respiratory sorting based method was assessed using a MRI-CT compatible respiratory simulation phantom. In volunteers, abdominal viscera were evaluated for artefact, noise, structure delineation and overall image quality using a previously published four-point scoring system. In patients undergoing abdominal RT, the tumour (or a surrogate) was utilized to assess the range of motion on both 4D-CT and 4D-MRI. Furthermore, imaging quality was evaluated for both 4D-CT and 4D-MRI.

Results

In phantom studies 4D-MRI demonstrated amplitude of motion error of less than 0.2 mm for five, seven and ten bins. 4D-MRI provided excellent image quality for liver, kidney and pancreas. In patients, the median amplitude of motion seen on 4D-CT and 4D-MRI was 11.2 mm (range 2.8–20.3 mm) and 10.1 mm (range 0.7–20.7 mm) respectively. The median difference in amplitude between 4D-CT and 4D-MRI was −0.6 mm (range −3.4–5.2 mm). 4D-MRI demonstrated superior edge detection (median score 3 versus 1) and overall image quality (median score 2 versus 1) compared to 4D-CT.

Conclusions

The prototype 4D-MRI sequence demonstrated promising results and may be used in abdominal targeting, motion gating, and towards implementing MRI-based adaptive RT.

Simultaneous Evaluation of Lung Anatomy and Ventilation Using 4D Respiratory-Motion-Resolved Ultrashort Echo Time Sparse MRI

BACKGROUND

Computed tomography (CT) and spirometry are the current standard methods for assessing lung anatomy and pulmonary ventilation, respectively. However, CT provides limited ventilation information and spirometry only provides global measures of lung ventilation. Thus, a method that can enable simultaneous examination of lung anatomy and ventilation is of clinical interest.

PURPOSE

To develop and test a 4D respiratory-resolved sparse lung MRI (XD-UTE: eXtra-Dimensional Ultrashort TE imaging) approach for simultaneous evaluation of lung anatomy and pulmonary ventilation.

STUDY TYPE

Prospective.

POPULATION

In all, 23 subjects (11 volunteers and 12 patients, mean age = 63.6 ± 8.4).

FIELD STRENGTH/SEQUENCE

3T MR; a prototype 3D golden-angle radial UTE sequence, a Cartesian breath-hold volumetric-interpolated examination (BH-VIBE) sequence.

ASSESSMENT

All subjects were scanned using the 3D golden-angle radial UTE sequence during normal breathing. Ten subjects underwent an additional scan during alternating normal and deep breathing. Respiratory-motion-resolved sparse reconstruction was performed for all the acquired data to generate dynamic normal-breathing or deep-breathing image series. For comparison, BH-VIBE was performed in 12 subjects. Lung images were visually scored by three experienced chest radiologists and were analyzed by two observers who segmented the left and right lung to derive ventilation parameters in comparison with spirometry.

STATISTICAL TESTS

Nonparametric paired two-tailed Wilcoxon signed-rank test; intraclass correlation coefficient, Pearson correlation coefficient.

RESULTS

XD-UTE achieved significantly improved image quality compared both with Cartesian BH-VIBE and radial reconstruction without motion compensation (P < 0.05). The global ventilation parameters (a sum of the left and right lung measures) were in good correlation with spirometry in the same subjects (correlation coefficient = 0.724). There were excellent correlations between the results obtained by two observers (intraclass correlation coefficient ranged from 0.8855-0.9995).

DATA CONCLUSION

Simultaneous evaluation of lung anatomy and ventilation using XD-UTE is demonstrated, which have shown good potential for improved diagnosis and management of patients with heterogeneous lung diseases.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:411-422.

3D ultrashort echo time MRI of the lung using stack-of-spirals and spherical k-Space coverages: Evaluation in healthy volunteers and parenchymal diseases

BACKGROUND

Ultrashort echo time (UTE) has been shown to improve lung MRI quality in three dimensions. The evaluation of 3D-UTE stack-of-spirals VIBE (3D-USV) sequence for parenchymal diseases and a comparison of performance with that of a spherical mode of acquisition is needed.

PURPOSE

To assess MRI quality using a prototypical 3D-USV sequence and to compare performance with that of a spherical acquisition using Pointwise Encoding Time Reduction with Radial Acquisition (PETRA).

STUDY TYPE

Monocenter, prospective.

POPULATION

Twelve healthy volunteers and 32 adult patients with either cystic fibrosis (CF; n = 16) or interstitial lung disease (ILD; n = 16).

FIELD STRENGTH/SEQUENCE

Both free-breathing 3D-USV and PETRA were completed at 1.5T.

ASSESSMENT

In healthy volunteers, visual analysis of imaging quality was scored using a Likert scale. Quantitative evaluation of apparent signal ratio (Sr) and contrast ratio (Cr) was measured. Patients with CF and ILD completed both computed tomography (CT) and MRI. Depiction of structural alterations was assessed using dedicated clinical scores. All evaluations were done in consensus by two readers.

STATISTICAL TESTS

Comparison of means was assessed using the Wilcoxon signed rank test. Concordance and agreement between CT and MRI were assessed using the intraclass correlation coefficient (ICC) and kappa test.

RESULTS

In controls, 3D-USV yielded lower artifacts owing to better automatic respiratory synchronization than PETRA (P < 0.001). However, Sr and Cr of 3D-USV were found significantly lower by 2.25- and 2.36-fold, respectively (P < 0.001). In patients, 3D-USV and PETRA showed comparable performances to assess airway severity in CF (Bhalla score, ICC = 0.89 and ICC = 0.92, respectively) and presence of structural alterations in ILD such as honeycombing (kappa = 0.68 and kappa = 0.69, respectively).

DATA CONCLUSION

3D-USV enables high-resolution morphological imaging of the lung without need of an external device to compensate respiratory motions. Automation and robustness of the method may facilitate clinical application for both airway and interstitial lung investigations.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;48:1489-1497.

Free-breathing ultrashort echo time lung magnetic resonance imaging using stack-of-spirals acquisition: A feasibility study in oncology patients

OBJECTIVES

To investigate the diagnostic accuracy of lung magnetic resonance imaging (MRI) with a free-breathing three-dimensional ultrashort echo time spoiled gradient echo sequence using a stack-of-spirals acquisition (spiral 3D UTE) for pulmonary nodule detection at 3 T in oncology patients.

METHODS

The institutional review board approved this retrospective study. Between June and September of 2017, 32 oncology patients underwent both free-breathing spiral 3D UTE of the lungs and thin-section chest computed tomography (CT) for pulmonary metastasis workups. Semiquantitative analyses of the visible pulmonary vessels, bronchi, mediastinum, and overall image quality on spiral 3D UTE were assessed by two reviewers; CT was used as the reference standard. The probability of nodule presence also was assessed.

RESULTS

The mean acquisition duration of the spiral 3D UTE was 327 s (range, 300-465 s). The pulmonary vessels and bronchi were visible nearly consistently up to the sub-sub-segmental branch levels on spiral 3D UTE (96.9% [31/32] and 90.6% [29/32], respectively). >90% of the spiral 3D UTE images had an acceptable or good mediastinal evaluation; >80% had good or excellent overall image quality. Fifty nodules (6.1 ± 5.9 mm) were identified in 13 patients on CT; the overall nodule detection rate of spiral 3D UTE was 86% (43/50). All 20 nodules ≥ 5 mm in diameter were identified on spiral 3D UTE (100%).

CONCLUSIONS

Free-breathing spiral 3D UTE had high sensitivity for the detection of pulmonary nodules, a reasonable scan duration, and acceptable image quality, which may make it a potential alternative to CT for oncology patients.