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1.
Artigo em Inglês | MEDLINE | ID: mdl-33684050

RESUMO

Automatic quantification of the left ventricle (LV) from cardiac magnetic resonance (CMR) images plays an important role in making the diagnosis procedure efficient, reliable, and alleviating the laborious reading work for physicians. Considerable efforts have been devoted to LV quantification using different strategies that include segmentation-based (SG) methods and the recent direct regression (DR) methods. Although both SG and DR methods have obtained great success for the task, a systematic platform to benchmark them remains absent because of differences in label information during model learning. In this paper, we conducted an unbiased evaluation and comparison of cardiac LV quantification methods that were submitted to the Left Ventricle Quantification (LVQuan) challenge, which was held in conjunction with the Statistical Atlases and Computational Modeling of the Heart (STACOM) workshop at the MICCAI 2018. The challenge was targeted at the quantification of 1) areas of LV cavity and myocardium, 2) dimensions of the LV cavity, 3) regional wall thicknesses (RWT), and 4) the cardiac phase, from mid-ventricle short-axis CMR images. First, we constructed a public quantification dataset Cardiac-DIG with ground truth labels for both the myocardium mask and these quantification targets across the entire cardiac cycle. Then, the key techniques employed by each submission were described. Next, quantitative validation of these submissions were conducted with the constructed dataset. The evaluation results revealed that both SG and DR methods can offer good LV quantification performance, even though DR methods do not require densely labeled masks for supervision. Among the 12 submissions, the DR method LDAMT offered the best performance, with a mean estimation error of 301 mm^2 for the two areas, 2.15 mm for the cavity dimensions, 2.03 mm for RWTs, and a 9.5% error rate for the cardiac phase classification. Three of the SG methods also delivered comparable performances. Finally, we discussed the advantages and disadvantages of SG and DR methods, as well as the unsolved problems in automatic cardiac quantification for clinical practice applications.

2.
Artigo em Inglês | MEDLINE | ID: mdl-33600328

RESUMO

Measurement of total-plaque-area (TPA) is important for determining long term risk for stroke and monitoring carotid plaque progression. Since delineation of carotid plaques is required, a deep learning method can provide automatic plaque segmentations and TPA measurements; however, it requires large datasets and manual annotations for training with unknown performance on new datasets. A UNet++ ensemble algorithm was proposed to segment plaques from 2D carotid ultrasound images, trained on three small datasets (n=33, 33, 34 subjects) and tested on 44 subjects from the SPARC dataset (n=144, London, Canada). The ensemble was also trained on the entire SPARC dataset and tested with a different dataset (n=497, Zhongnan Hospital, China). Algorithm and manual segmentations were compared using Dice-similarity-coefficient (DSC) and TPAs were compared using the difference (TPA), Pearson correlation coefficient (r), and Bland-Altman analyses. Segmentation variability was determined using the intra-class correlation coefficient (ICC) and coefficient-of-variation (CoV). For the 44 SPARC subjects, algorithm DSC was 83.3-85.7%, and algorithm TPAs were strongly correlated (r=0.985-0.988; p<0.001) with manual results with marginal biases (0.73-6.75) mm2 using the three training datasets. Algorithm ICC for TPAs (ICC=0.996) was similar to intra- and inter-observer manual results (ICC=0.977, 0.995). Algorithm CoV=6.98% for plaque areas was smaller than the inter-observer manual CoV (7.54%). For the Zhongnan dataset, DSC was 88.6%; algorithm and manual TPAs were strongly correlated (r=0.972, p<0.001) with TPA=-0.444.05 mm2 and ICC=0.985. The proposed algorithm trained on small datasets and segmented a different dataset without retraining with accuracy and precision that may be useful clinically and for research.

3.
Med Phys ; 2021 Jan 08.
Artigo em Inglês | MEDLINE | ID: mdl-33417726

RESUMO

PURPOSE: Cardiac relaxometry techniques, particularly T1 mapping, have recently gained clinical importance in various cardiac pathologies. Myocardial T1 and extracellular volume are usually calculated from manual identification of left ventricular epicardial and endocardial regions. This is a laborious process, particularly for large volume studies. Here we present a fully automated relaxometry framework (FASTR) for segmental analysis of T1 maps (both native and postcontrast) and partition coefficient (λ). METHODS: Patients (N = 11) were imaged postacute myocardial infarction on a 1.5T clinical scanner. The scan protocol involved CINE-SSFP imaging, native, and post-contrast T1 mapping using the Modified Look-Locker Inversion (MOLLI) recovery sequence. FASTR consisted of automatic myocardial segmentation of spatio-temporally coregistered CINE images as an initial guess, followed by refinement of the contours on the T1 maps to derive segmental T1 and λ. T1 and λ were then compared to those obtained from two trained expert observers. RESULTS: Robust endocardial and epicardial contours were achieved on T1 maps despite the presence of infarcted tissue. Relative to experts, FASTR resulted in myocardial Dice coefficients (native T1: 0.752 ± 0.041; postcontrast T1: 0.751 ± 0.057) that were comparable to interobserver Dice (native T1: 0.803 ± 0.045; postcontrast T1: 0.799 ± 0.054). There were strong correlations observed for T1 and λ derived from experts and FASTR (native T1: r = 0.83; postcontrast T1: r = 0.87; λ: r = 0.78; P < 0.0001), which were comparable to inter-expert correlation coefficients (native T1: r = 0.90; postcontrast T1: r = 0.93; λ: r = 0.80; P < 0.0001). CONCLUSIONS: Our fully automated framework, FASTR, can generate accurate myocardial segmentations for native and postcontrast MOLLI T1 analysis without the need for manual intervention. Such a design is appealing for high volume clinical protocols.

4.
Radiology ; : 202861, 2020 Dec 08.
Artigo em Inglês | MEDLINE | ID: mdl-33289613

RESUMO

Background Hyperpolarized noble gas MRI helps measure lung ventilation, but clinical translation remains limited. Free-breathing proton MRI may help quantify lung function using existing MRI systems without contrast material and may assist in providing information about ventilation not visible to the eye or easily extracted with segmentation methods. Purpose To explore the use of deep convolutional neural networks (DCNNs) to generate synthetic MRI ventilation scans from free-breathing MRI (deep learning [DL] ventilation MRI)-derived specific ventilation maps as a surrogate of noble gas MRI and to validate this approach across a wide range of lung diseases. Materials and Methods In this secondary analysis of prospective trials, 114 paired noble gas MRI and two-dimensional free-breathing MRI scans were obtained in healthy volunteers with no history of chronic or acute respiratory disease and in study participants with a range of different obstructive lung diseases, including asthma, bronchiectasis, chronic obstructive pulmonary disease, and non-small-cell lung cancer between September 2013 and April 2018 (ClinicalTrials.gov identifiers: NCT03169673, NCT02351141, NCT02263794, NCT02282202, NCT02279329, and NCT02002052). A U-Net-based DCNN model was trained to map free-breathing proton MRI to hyperpolarized helium 3 (3He) MRI ventilation and validated using a sixfold validation. During training, the DCNN ventilation maps were compared with noble gas MRI scans using the Pearson correlation coefficient (r) and mean absolute error. DCNN ventilation images were segmented for ventilation and ventilation defects and were compared with noble gas MRI scans using the Dice similarity coefficient (DSC). Relationships were evaluated with the Spearman correlation coefficient (rS). Results One hundred fourteen study participants (mean age, 56 years ± 15 [standard deviation]; 66 women) were evaluated. As compared with 3He MRI, DCNN model ventilation maps had a mean r value of 0.87 ± 0.08. The mean DSC for DL ventilation MRI and 3He MRI ventilation was 0.91 ± 0.07. The ventilation defect percentage for DL ventilation MRI was highly correlated with 3He MRI ventilation defect percentage (rS = 0.83, P < .001, mean bias = -2.0% ± 5). Both DL ventilation MRI (rS = -0.51, P < .001) and 3He MRI (rS = -0.61, P < .001) ventilation defect percentage were correlated with the forced expiratory volume in 1 second. The DCNN model required approximately 2 hours for training and approximately 1 second to generate a ventilation map. Conclusion In participants with diverse pulmonary pathologic findings, deep convolutional neural networks generated ventilation maps from free-breathing proton MRI trained with a hyperpolarized noble-gas MRI ventilation map data set. The maps showed correlation with noble gas MRI ventilation and pulmonary function measurements. © RSNA, 2020 See also the editorial by Vogel-Claussen in this issue.

5.
Magn Reson Med ; 2020 Nov 23.
Artigo em Inglês | MEDLINE | ID: mdl-33226667

RESUMO

PURPOSE: To develop an approach for automated quantification of myocardial infarct heterogeneity in late gadolinium enhancement (LGE) cardiac MRI. METHODS: We acquired 2D short-axis cine and 3D LGE in 10 pigs with myocardial infarct. The 2D cine myocardium was segmented and registered to the LGE images. LGE image signal intensities within the warped cine myocardium masks were analyzed to determine the thresholds of infarct core (IC) and gray zone (GZ) for the standard-deviation (SD) and full-width-at-halfmaximum (FWHM) methods. The initial IC, GZ, and IC + GZ segmentations were postprocessed using a normalized cut approach. Cine segmentation and cine-LGE registration accuracies were evaluated using dice similarity coefficient and average symmetric surface distance. Automated IC, GZ, and IC + GZ volumes were compared with manual results using Pearson correlation coefficient (r), Bland-Altman analyses, and intraclass correlation coefficient. RESULTS: For n = 87 slices containing scar, we achieved cine segmentation dice similarity coefficient = 0.87 ± 0.12, average symmetric surface distance = 0.94 ± 0.74 mm (epicardium), and 1.03 ± 0.82 mm (endocardium) in the scar region. For cine-LGE registration, dice similarity coefficient was 0.90 ± 0.06 and average symmetric surface distance was 0.72 ± 0.39 mm (epicardium) and 0.86 ± 0.53 mm (endocardium) in the scar region. For both SD and FWHM methods, automated IC, GZ, and IC + GZ volumes were strongly (r > 0.70) correlated with manual measurements, and the correlations were not significantly different from interobserver correlations (P > .05). The agreement between automated and manual scar volumes (intraclass correlation coefficient = 0.85-0.96) was similar to that between two observers (intraclass correlation coefficient = 0.81-0.99); automated scar segmentation errors were not significantly different from interobserver segmentation differences (P > .05). CONCLUSIONS: Our approach provides fully automated cine-LGE MRI registration and LGE myocardial infarct heterogeneity quantification in preclinical studies.

6.
IEEE Trans Med Imaging ; 39(9): 2844-2855, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32142426

RESUMO

Vessel-wall-volume (VWV) is an important three-dimensional ultrasound (3DUS) metric used in the assessment of carotid plaque burden and monitoring changes in carotid atherosclerosis in response to medical treatment. To generate the VWV measurement, we proposed an approach that combined a voxel-based fully convolution network (Voxel-FCN) and a continuous max-flow module to automatically segment the carotid media-adventitia (MAB) and lumen-intima boundaries (LIB) from 3DUS images. Voxel-FCN includes an encoder consisting of a general 3D CNN and a 3D pyramid pooling module to extract spatial and contextual information, and a decoder using a concatenating module with an attention mechanism to fuse multi-level features extracted by the encoder. A continuous max-flow algorithm is used to improve the coarse segmentation provided by the Voxel-FCN. Using 1007 3DUS images, our approach yielded a Dice-similarity-coefficient (DSC) of 93.2±3.0% for the MAB in the common carotid artery (CCA), and 91.9±5.0% in the bifurcation by comparing algorithm and expert manual segmentations. We achieved a DSC of 89.5±6.7% and 89.3±6.8% for the LIB in the CCA and the bifurcation respectively. The mean errors between the algorithm-and manually-generated VWVs were 0.2±51.2 mm3 for the CCA and -4.0±98.2 mm3 for the bifurcation. The algorithm segmentation accuracy was comparable to intra-observer manual segmentation but our approach required less than 1s, which will not alter the clinical work-flow as 10s is required to image one side of the neck. Therefore, we believe that the proposed method could be used clinically for generating VWV to monitor progression and regression of carotid plaques.

7.
Med Image Anal ; 61: 101636, 2020 04.
Artigo em Inglês | MEDLINE | ID: mdl-31972427

RESUMO

Cardiac magnetic resonance imaging (MRI) provides a wealth of imaging biomarkers for cardiovascular disease care and segmentation of cardiac structures is required as a first step in enumerating these biomarkers. Deep convolutional neural networks (CNNs) have demonstrated remarkable success in image segmentation but typically require large training datasets and provide suboptimal results that require further improvements. Here, we developed a way to enhance cardiac MRI multi-class segmentation by combining the strengths of CNN and interpretable machine learning algorithms. We developed a continuous kernel cut segmentation algorithm by integrating normalized cuts and continuous regularization in a unified framework. The high-order formulation was solved through upper bound relaxation and a continuous max-flow algorithm in an iterative manner using CNN predictions as inputs. We applied our approach to two representative cardiac MRI datasets across a wide range of cardiovascular pathologies. We comprehensively evaluated the performance of our approach for two CNNs trained with various small numbers of training cases, tested on the same and different datasets. Experimental results showed that our approach improved baseline CNN segmentation by a large margin, reduced CNN segmentation variability substantially, and achieved excellent segmentation accuracy with minimal extra computational cost. These results suggest that our approach provides a way to enhance the applicability of CNN by enabling the use of smaller training datasets and improving the segmentation accuracy and reproducibility for cardiac MRI segmentation in research and clinical patient care.

8.
Magn Reson Med ; 84(1): 416-426, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-31765497

RESUMO

PURPOSE: Multi-b diffusion-weighted hyperpolarized inhaled-gas MRI provides imaging biomarkers of terminal airspace enlargement including ADC and mean linear intercept (Lm ), but clinical translation has been limited because image acquisition requires relatively long or multiple breath-holds that are not well-tolerated by patients. Therefore, we aimed to accelerate single breath-hold 3D multi-b diffusion-weighted 129 Xe MRI, using k-space undersampling in imaging direction using a different undersampling pattern for different b-values combined with the stretched exponential model to generate maps of ventilation, apparent transverse relaxation time constant ( T 2 ∗ ), ADC, and Lm values in a single, short breath-hold; accelerated and non-accelerated measurements were directly compared. METHODS: We evaluated multi-b (0, 12, 20, 30, and 45.5 s/cm2 ) diffusion-weighted 129 Xe T 2 ∗ /ADC/morphometry estimates using acceleration factor (AF = 1 and 7) and multi-breath sampling in 3 volunteers (HV), and 6 participants with alpha-1 antitrypsin deficiency (AATD). RESULTS: For the HV subgroup, mean differences of 5%, 2%, and 8% were observed between fully sampled and undersampled k-space for ADC, Lm , and T 2 ∗ values, respectively. For the AATD subgroup, mean differences were 9%, 6%, and 12% between fully sampled and undersampled k-space for ADC, Lm and T 2 ∗ values, respectively. Although mean differences of 1% and 4.5% were observed between accelerated and multi-breath sampled ADC and Lm values, respectively, mean ADC/Lm estimates were not significantly different from corresponding mean ADCM /Lm M or mean ADCA /Lm A estimates (all P > 0.60 , A = undersampled and M = multi-breath sampled). CONCLUSIONS: Accelerated multi-b diffusion-weighted 129 Xe MRI is feasible at AF = 7 for generating pulmonary ADC and Lm in AATD and normal lung.

9.
Comput Intell Neurosci ; 2019: 2087132, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31885530

RESUMO

Long and tedious calibration time hinders the development of motor imagery- (MI-) based brain-computer interface (BCI). To tackle this problem, we use a limited labelled set and a relatively large unlabelled set from the same subject for training based on the transductive support vector machine (TSVM) framework. We first introduce an improved TSVM (ITSVM) method, in which a comprehensive feature of each sample consists of its common spatial patterns (CSP) feature and its geometric feature. Moreover, we use the concave-convex procedure (CCCP) to solve the optimization problem of TSVM under a new balancing constraint that can address the unknown distribution of the unlabelled set by considering various possible distributions. In addition, we propose an improved self-training TSVM (IST-TSVM) method that can iteratively perform CSP feature extraction and ITSVM classification using an expanded labelled set. Extensive experimental results on dataset IV-a from BCI competition III and dataset II-a from BCI competition IV show that our algorithms outperform the other competing algorithms, where the sizes and distributions of the labelled sets are variable. In particular, IST-TSVM provides average accuracies of 63.25% and 69.43% with the abovementioned two datasets, respectively, where only four positive labelled samples and sixteen negative labelled samples are used. Therefore, our algorithms can provide an alternative way to reduce the calibration time.


Assuntos
Interfaces Cérebro-Computador , Eletroencefalografia , Imaginação , Atividade Motora , Máquina de Vetores de Suporte , Encéfalo/fisiologia , Calibragem , Eletroencefalografia/métodos , , Mãos , Humanos , Imaginação/fisiologia , Modelos Teóricos , Atividade Motora/fisiologia , Processamento de Sinais Assistido por Computador , Fatores de Tempo , Língua
10.
Magn Reson Med ; 81(3): 2135-2146, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30362609

RESUMO

PURPOSE: To develop a rapid Fourier decomposition (FD) free-breathing pulmonary 1 H MRI (FDMRI) image processing and biomarker pipeline for research use. METHODS: We acquired MRI in 20 asthmatic subjects using a balanced steady-state free precession (bSSFP) sequence optimized for ventilation imaging. 2D 1 H MRI series were segmented by enforcing the spatial similarity between adjacent images and the right-to-left lung volume-ratio. The segmented lung series were co-registered using a coarse-to-fine deformable registration framework that used dual optimization techniques. All pairwise registrations were implemented in parallel and FD was performed to generate 2D ventilation-weighted maps and ventilation-defect-percent (VDP). Lung segmentation and registration accuracy were evaluated by comparing algorithm and manual lung-masks, deformed manual lung-masks, and fiducials in the moving and fixed images using Dice-similarity-coefficient (DSC), mean-absolute-distance (MAD), and target-registration-error (TRE). The relationship of FD-VDP and 3 He-VDP was evaluated using the Pearson-correlation-coefficient (r) and Bland Altman analysis. Algorithm reproducibility was evaluated using the coefficient-of-variation (CoV) and intra-class-correlation-coefficient (ICC) for segmentation, registration, and FD-VDP components. RESULTS: For lung segmentation, there was a DSC of 95 ± 1.5% and MAD of 2.3 ± 0.5 mm, and for registration there was a DSC of 97 ± 0.8%, MAD of 1.6 ± 0.4 mm and TRE of 3.6 ± 1.2 mm. Reproducibility for segmentation DSC (CoV/ICC = 0.5%/0.92), registration TRE (CoV/ICC = 0.4%/0.98), and FD-VDP (Cov/ICC = 3.9%/0.97) was high. The pipeline required 10 min/subject. FD-VDP was correlated with 3 He-VDP (r = 0.69, P < 0.001) although there was a bias toward lower FD-VDP (bias = -4.9%). CONCLUSIONS: We developed and evaluated a pipeline that provides a rapid and precise method for FDMRI ventilation maps.


Assuntos
Asma/diagnóstico por imagem , Pulmão/diagnóstico por imagem , Imagem por Ressonância Magnética/métodos , Respiração , Adulto , Algoritmos , Biomarcadores , Gráficos por Computador , Feminino , Análise de Fourier , Humanos , Processamento de Imagem Assistida por Computador , Masculino , Pessoa de Meia-Idade , Modelos Estatísticos , Linguagens de Programação , Reprodutibilidade dos Testes , Testes de Função Respiratória , Software
11.
J Magn Reson Imaging ; 49(6): 1713-1722, 2019 06.
Artigo em Inglês | MEDLINE | ID: mdl-30578587

RESUMO

BACKGROUND: Multi-b diffusion-weighted hyperpolarized-gas MRI measures pulmonary airspace-enlargement using apparent diffusion coefficients (ADCs) and mean-linear-intercepts (Lm ). PURPOSE: To develop single-breath 3D multi-b diffusion-weighted 3 He and 129 Xe MRI using k-space undersampling. Rapid, cost-efficient, single-breath acquisitions may facilitate clinical translation. STUDY TYPE: Prospective. SUBJECTS: We evaluated 12 participants, including nine subjects (mean age = 69 ± 9) who were included in the retrospective experiment and three chronic pulmonary obstruction disease (COPD) patients (mean age = 81 ± 6) who participated in the prospective study. FIELD STRENGTH: A whole-body 3 T 2D/3D fast gradient recall echo (FGRE) sequence. ASSESSMENT: Hyperpolarized 3 He/129 Xe MRI, spirometry, plethysmography computed tomography (CT). We evaluated 129 Xe ADC/morphometry estimates by retrospectively undersampling previously acquired fully sampled multibreath, multi-b diffusion-weighted data. Next, we prospectively evaluated the feasibility of accelerated (AF = 7) 3 He MRI static-ventilation/T2 * (extra short-TE, b = 0 image) and ADC/morphometry (five b-values) maps using a single gas-dose and 16-second breath-hold. To conservatively evaluate cost-improvement, we compared total costs of single vs. multiple 129 Xe doses. STATISTICAL TESTS: Multivariate analysis of variance, independent t-tests and voxel-by-voxel basis difference test. RESULTS: For the retrospectively undersampled 129 Xe data, a nonsignificant mean difference for ADC/Lm of 14%/12%, 12%/8%, and 11%/9% was observed (all, P > 0.4) between the fully sampled and accelerated data for the never-smoker, COPD, and alpha-1 antitrypsin deficiency (AATD) groups, respectively. The control never-smoker group had significantly lower ADC (P < 0.001) and Lm (P < 0.001) than the COPD/AATD group for both fully sampled and accelerated data. For the prospectively acquired 3 He MRI data, static-ventilation, T2 *, ADC, and morphometry maps were acquired using a single 16-second breath-hold scan and single gas dose. Accelerated imaging resulted in cost savings of ~$US 1000/patient, a conservative estimate based on 129 Xe MRI dose savings (single vs. five doses). DATA CONCLUSION: This is a proof-of-concept demonstration of accelerated (7×) morphometry that shows that less cost- and time-efficient multibreath methods that lead to variability and patient fatigue may be avoided in the future. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018.


Assuntos
Hélio , Imageamento Tridimensional/métodos , Isótopos , Imagem por Ressonância Magnética/métodos , Doença Pulmonar Obstrutiva Crônica/diagnóstico por imagem , Isótopos de Xenônio , Idoso , Idoso de 80 Anos ou mais , Difusão , Feminino , Gases , Humanos , Imageamento Tridimensional/economia , Imagem por Ressonância Magnética/economia , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Gases Nobres , Pletismografia , Estudo de Prova de Conceito , Estudos Prospectivos , Reprodutibilidade dos Testes , Estudos Retrospectivos , Espirometria , Tomografia Computadorizada por Raios X , Xenônio
12.
J Med Imaging (Bellingham) ; 5(2): 026002, 2018 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-29963580

RESUMO

We designed and generated pulmonary imaging biomarker pipelines to facilitate high-throughput research and point-of-care use in patients with chronic lung disease. Image processing modules and algorithm pipelines were embedded within a graphical user interface (based on the .NET framework) for pulmonary magnetic resonance imaging (MRI) and x-ray computed-tomography (CT) datasets. The software pipelines were generated using C++ and included: (1) inhaled He3/Xe129 MRI ventilation and apparent diffusion coefficients, (2) CT-MRI coregistration for lobar and segmental ventilation and perfusion measurements, (3) ultrashort echo-time H1 MRI proton density measurements, (4) free-breathing Fourier-decomposition H1 MRI ventilation/perfusion and free-breathing H1 MRI specific ventilation, (5) multivolume CT and MRI parametric response maps, and (6) MRI and CT texture analysis and radiomics. The image analysis framework was implemented on a desktop workstation/tablet to generate biomarkers of regional lung structure and function related to ventilation, perfusion, lung tissue texture, and integrity as well as multiparametric measures of gas trapping and airspace enlargement. All biomarkers were generated within 10 min with measurement reproducibility consistent with clinical and research requirements. The resultant pulmonary imaging biomarker pipeline provides real-time and automated lung imaging measurements for point-of-care and high-throughput research.

13.
J Appl Physiol (1985) ; 125(1): 73-85, 2018 07 01.
Artigo em Inglês | MEDLINE | ID: mdl-29543132

RESUMO

Ventilation heterogeneity is a hallmark finding in obstructive lung disease and may be evaluated using a variety of methods, including multiple-breath gas washout and pulmonary imaging. Such methods provide an opportunity to better understand the relationships between structural and functional abnormalities in the lungs, and their relationships with important clinical outcomes. We measured ventilation heterogeneity and respiratory impedance in 100 subjects [50 patients with asthma, 22 ex-smokers, and 28 patients with chronic obstructive pulmonary disease (COPD)] using oscillometry and hyperpolarized 3He magnetic resonance imaging (MRI) and determined their relationships with quality of life scores and disease control/exacerbations. We also coregistered MRI ventilation maps to a computational airway tree model to generate patient-specific respiratory impedance predictions for comparison with experimental measurements. In COPD and asthma patients, respectively, forced oscillation technique (FOT)-derived peripheral resistance (5-19 Hz) and MRI ventilation defect percentage (VDP) were significantly related to quality of life (FOT: COPD ρ = 0.4, P = 0.004; asthma ρ = -0.3, P = 0.04; VDP: COPD ρ = 0.6, P = 0.003; asthma ρ = -0.3, P = 0.04). Patients with poorly controlled asthma (Asthmatic Control Questionnaire >2) had significantly increased resistance (5 Hz: P = 0.01; 5-19 Hz: P = 0.006) and reactance (5 Hz: P = 0.03). FOT-derived peripheral resistance (5-19 Hz) was significantly related to VDP in patients with asthma and COPD patients (asthma: ρ = 0.5, P < 0.001; COPD: ρ = 0.5, P = 0.01), whereas total respiratory impedance was related to VDP only in patients with asthma (resistance 5 Hz: ρ = 0.3, P = 0.02; reactance 5 Hz: ρ = -0.5, P < 0.001). Model-predicted and FOT-measured reactance (5 Hz) were correlated in patients with asthma (ρ = 0.5, P = 0.001), whereas in COPD patients, model-predicted and FOT-measured resistance (5-19 Hz) were correlated (ρ = 0.5, P = 0.004). In summary, in patients with asthma and COPD patients, we observed significant, independent relationships for FOT-measured impedance and MRI ventilation heterogeneity measurements with one another and with quality of life scores. NEW & NOTEWORTHY In 100 patients, including patients with asthma and ex-smokers, 3He MRI ventilation heterogeneity and respiratory system impedance were correlated and both were independently related to quality of life scores and asthma control. These findings demonstrated the critical relationships between respiratory system impedance and ventilation heterogeneity and their role in determining quality of life and disease control. These observations underscore the dominant role that abnormalities in the lung periphery play in ventilation heterogeneity that results in patients' symptoms.


Assuntos
Pulmão/fisiopatologia , Doença Pulmonar Obstrutiva Crônica/fisiopatologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Resistência das Vias Respiratórias/fisiologia , Asma/fisiopatologia , Feminino , Volume Expiratório Forçado/fisiologia , Humanos , Imagem por Ressonância Magnética/métodos , Masculino , Pessoa de Meia-Idade , Oscilometria/métodos , Qualidade de Vida , Respiração , Testes de Função Respiratória/métodos , Espirometria/métodos , Adulto Jovem
14.
Radiology ; 287(2): 693-704, 2018 05.
Artigo em Inglês | MEDLINE | ID: mdl-29470939

RESUMO

Purpose To measure regional specific ventilation with free-breathing hydrogen 1 (1H) magnetic resonance (MR) imaging without exogenous contrast material and to investigate correlations with hyperpolarized helium 3 (3He) MR imaging and pulmonary function test measurements in healthy volunteers and patients with asthma. Materials and Methods Subjects underwent free-breathing 1H and static breath-hold hyperpolarized 3He MR imaging as well as spirometry and plethysmography; participants were consecutively recruited between January and June 2017. Free-breathing 1H MR imaging was performed with an optimized balanced steady-state free-precession sequence; images were retrospectively grouped into tidal inspiration or tidal expiration volumes with exponentially weighted phase interpolation. MR imaging volumes were coregistered by using optical flow deformable registration to generate 1H MR imaging-derived specific ventilation maps. Hyperpolarized 3He MR imaging- and 1H MR imaging-derived specific ventilation maps were coregistered to quantify regional specific ventilation within hyperpolarized 3He MR imaging ventilation masks. Differences between groups were determined with the Mann-Whitney test and relationships were determined with Spearman (ρ) correlation coefficients. Statistical analyses were performed with software. Results Thirty subjects (median age: 50 years; interquartile range [IQR]: 30 years), including 23 with asthma and seven healthy volunteers, were evaluated. Both 1H MR imaging-derived specific ventilation and hyperpolarized 3He MR imaging-derived ventilation percentage were significantly greater in healthy volunteers than in patients with asthma (specific ventilation: 0.14 [IQR: 0.05] vs 0.08 [IQR: 0.06], respectively, P < .0001; ventilation percentage: 99% [IQR: 1%] vs 94% [IQR: 5%], P < .0001). For all subjects, 1H MR imaging-derived specific ventilation correlated with plethysmography-derived specific ventilation (ρ = 0.54, P = .002) and hyperpolarized 3He MR imaging-derived ventilation percentage (ρ = 0.67, P < .0001) as well as with forced expiratory volume in 1 second (FEV1) (ρ = 0.65, P = .0001), ratio of FEV1 to forced vital capacity (ρ = 0.75, P < .0001), ratio of residual volume to total lung capacity (ρ = -0.68, P < .0001), and airway resistance (ρ = -0.51, P = .004). 1H MR imaging-derived specific ventilation was significantly greater in the gravitational-dependent versus nondependent lung in healthy subjects (P = .02) but not in patients with asthma (P = .1). In patients with asthma, coregistered 1H MR imaging specific ventilation and hyperpolarized 3He MR imaging maps showed that specific ventilation was diminished in corresponding 3He MR imaging ventilation defects (0.05 ± 0.04) compared with well-ventilated regions (0.09 ± 0.05) (P < .0001). Conclusion 1H MR imaging-derived specific ventilation correlated with plethysmography-derived specific ventilation and ventilation defects seen by using hyperpolarized 3He MR imaging. © RSNA, 2018 Online supplemental material is available for this article.


Assuntos
Asma/fisiopatologia , Imagem por Ressonância Magnética , Respiração , Adulto , Idoso , Idoso de 80 Anos ou mais , Asma/diagnóstico por imagem , Asma/metabolismo , Feminino , Voluntários Saudáveis , Hélio/metabolismo , Humanos , Hidrogênio/metabolismo , Interpretação de Imagem Assistida por Computador , Medidas de Volume Pulmonar , Masculino , Pessoa de Meia-Idade , Estudo de Prova de Conceito , Troca Gasosa Pulmonar , Reprodutibilidade dos Testes , Testes de Função Respiratória , Estudos Retrospectivos , Adulto Jovem
15.
Acad Radiol ; 24(10): 1268-1276, 2017 10.
Artigo em Inglês | MEDLINE | ID: mdl-28551402

RESUMO

RATIONALE AND OBJECTIVES: Ventilation heterogeneity is a hallmark feature of asthma. Our objective was to evaluate ventilation heterogeneity in patients with severe asthma, both pre- and post-salbutamol, as well as post-methacholine (MCh) challenge using the lung clearance index, free-breathing pulmonary 1H magnetic resonance imaging (FDMRI), and inhaled-gas MRI ventilation defect percent (VDP). MATERIALS AND METHODS: Sixteen severe asthmatics (49 ± 10 years) provided written informed consent to an ethics board-approved protocol. Spirometry, plethysmography, and multiple breath nitrogen washout to measure the lung clearance index were performed during a single visit within 15 minutes of MRI. Inhaled-gas MRI and FDMRI were performed pre- and post-bronchodilator to generate VDP. For asthmatics with forced expiratory volume in 1 second (FEV1) >70%predicted, MRI was also performed before and after MCh challenge. Wilcoxon signed-rank tests, Spearman correlations, and a repeated-measures analysis of variance were performed. RESULTS: Hyperpolarized 3He (P = .02) and FDMRI (P = .02) VDP significantly improved post-salbutamol and for four asthmatics who could perform MCh (n = 4). 3He and FDMRI VDP significantly increased at the provocative concentration of MCh, resulting in a 20% decrease in FEV1 (PC20) and decreased post-bronchodilator (P = .02), with a significant difference between methods (P = .01). FDMRI VDP was moderately correlated with 3He VDP (ρ = .61, P = .01), but underestimated VDP relative to 3He VDP (-6 ± 9%). Whereas 3He MRI VDP was significantly correlated with the lung clearance index, FDMRI was not (ρ = .49, P = .06). CONCLUSIONS: FDMRI VDP generated in free-breathing asthmatic patients was correlated with static inspiratory breath-hold 3He MRI VDP but underestimated VDP relative to 3He MRI VDP. Although less sensitive to salbutamol and MCh, FDMRI VDP may be considered for asthma patient evaluations at centers without inhaled-gas MRI.


Assuntos
Asma/diagnóstico por imagem , Asma/fisiopatologia , Pulmão/diagnóstico por imagem , Pulmão/fisiopatologia , Imagem por Ressonância Magnética/métodos , Adulto , Albuterol/uso terapêutico , Asma/tratamento farmacológico , Broncoconstritores , Broncodilatadores/uso terapêutico , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Masculino , Cloreto de Metacolina , Pessoa de Meia-Idade , Pletismografia/métodos , Respiração , Testes de Função Respiratória , Espirometria/métodos
16.
Med Phys ; 44(5): 1718-1733, 2017 May.
Artigo em Inglês | MEDLINE | ID: mdl-28206676

RESUMO

PURPOSE: Recent pulmonary imaging research has revealed that in patients with chronic obstructive pulmonary disease (COPD) and asthma, structural and functional abnormalities are spatially heterogeneous. This novel information may help optimize treatment in individual patients, monitor interventional efficacy, and develop new treatments. Moreover, by automating the measurement of regional biomarkers for the 19 different anatomical lung segments, there is an opportunity to embed imaging biomarkers into clinically acceptable clinical workflows and improve lung disease clinical care. Therefore, to exploit the regional structure-function information provided by thoracic imaging, and as a first step toward this goal, our objective was to develop a fully automated registration pipeline for thoracic x-ray computed tomography (CT) and inhaled gas functional magnetic resonance imaging (MRI) whole lung and segmental structure-function biomarkers. METHODS: Thirty-five patients including 15 severe, poorly controlled asthmatics and 20 COPD patients [classified according to the global initiative for chronic obstructive lung disease (GOLD) criteria)] provided written informed consent to a study protocol approved by Health Canada and underwent pulmonary function tests, MRI, and CT during a single 2-hour visit. Using this diverse patient dataset, we developed and evaluated a joint deformable registration approach to simultaneously coregister CT with both 1 H and 3 He MRI by enforcing the similarity of the deformation fields from the two individual registrations. We derived a simpler model that was equivalent to the original challenging optimization problem through variational analysis and the simpler model gave rise to an efficient numerical solver that was parallelized on a graphics processing unit. The coregistered CT-3 He MRI and whole lung/segmental lung masks were used to generate whole lung and segmental 3 He MRI ventilation defect percent (VDP). To estimate fiducial localization reproducibility, a single observer manually identified 109 pairs of CT and 3 He MRI fiducials for 35 patient images on five separate occasions and determined the fiducial localization error (FLE). CT-3 He MRI registration accuracy was evaluated using the target registration error (TRE). Whole lung VDP generated using the algorithm was compared with VDP generated using a previously validated semiautomated approach and computational efficiency was evaluated using run time. RESULTS: In 35 patients including 15 with severe asthma and 20 with COPD, mean forced expiratory volume in 1 s (FEV1 ) was 63±24%pred and FEV1 /forced vital capacity (FVC) was 54 ± 17%. FLE was 0.16 mm and 0.34 mm for 3 He MRI and CT, respectively. TRE was 4.5 ± 2.0 mm, 4.0 ± 1.7 mm, 4.8 ± 2.3 mm for asthma, COPD GOLD II, and GOLD III groups, respectively, with a mean of 4.4 ± 2.0 mm for the entire dataset. TRE was significantly improved for joint CT-1 H/3 He MRI registration compared with CT-1 H MRI rigid registration (P < 0.0001). Whole lung VDP generated using the pipeline was not significantly different (P = 0.37) compared to a semiautomated method with which it was strongly correlated (r = 0.93, P < 0.0001). The fully automated pipeline required 11 ± 0.4 min to generate whole lung and segmental VDP. CONCLUSIONS: For a diverse group of patients with COPD and asthma, whole lung and segmental VDP was measured using an automated lung image analysis pipeline which provides a way to incorporate lung functional biomarkers into clinical research and patient care.


Assuntos
Imagem por Ressonância Magnética , Doença Pulmonar Obstrutiva Crônica/diagnóstico por imagem , Tomografia Computadorizada por Raios X , Canadá , Hélio , Humanos , Masculino , Reprodutibilidade dos Testes
17.
Acad Radiol ; 24(1): 4-12, 2017 01.
Artigo em Inglês | MEDLINE | ID: mdl-27717759

RESUMO

RATIONALE AND OBJECTIVES: Evidence-based treatment and management for patients with bronchiectasis remain challenging. There is a need for regional disease measurements as focal distribution of disease is common. Our objective was to evaluate the ability of magnetic resonance imaging (MRI) to detect regional ventilation impairment and response to airway clearance therapy (ACT) in patients with noncystic fibrosis (CF) bronchiectasis, providing a new way to objectively and regionally evaluate response to therapy. MATERIALS AND METHODS: Fifteen participants with non-CF bronchiectasis and 15 age-matched healthy volunteers provided written informed consent to an ethics board-approved Health Insurance Portability and Accountability Act-compliant protocol and underwent spirometry, plethysmography, computed tomography (CT), and hyperpolarized 3He MRI. Bronchiectasis patients also completed a Six-Minute Walk Test, the St. George's Respiratory questionnaire, and Patient Evaluation Questionnaire (PEQ), and returned for a follow-up visit after 3 weeks of daily oscillatory positive expiratory pressure use. CT evidence of bronchiectasis was qualitatively reported by lobe, and MRI ventilation defect percent (VDP) was measured for the entire lung and individual lobes. RESULTS: CT evidence of bronchiectasis and abnormal VDP (14 ± 7%) was observed for all bronchiectasis patients and no healthy volunteers. There was CT evidence of bronchiectasis in all lobes for 3 patients and in 3 ± 1 lobes (range = 1-4) for 12 patients. VDP in lobes with CT evidence of bronchiectasis (19 ± 12%) was significantly higher than in lobes without CT evidence of bronchiectasis (8 ± 5%, P = .001). For patients, VDP in lung lobes with (P < .0001) and without CT evidence of bronchiectasis (P = .006) was higher than in healthy volunteers (3 ± 1%). For all patients, mean PEQ-ease-bringing-up-sputum (P = .048) and PEQ-patient-global-assessment (P = .01) were significantly improved post-oscillatory positive expiratory pressure. An improvement in regional VDP greater than the minimum clinical important difference was observed for 8 of the 14 patients evaluated. CONCLUSIONS: There was CT and MRI evidence of structure-function abnormalities in patients with bronchiectasis; in approximately half, there was evidence of ventilation improvements after airway clearance therapy.


Assuntos
Bronquiectasia/patologia , Doença Pulmonar Obstrutiva Crônica/patologia , Idoso , Idoso de 80 Anos ou mais , Bronquiectasia/fisiopatologia , Bronquiectasia/terapia , Estudos de Casos e Controles , Expiração/fisiologia , Feminino , Volume Expiratório Forçado/fisiologia , Humanos , Pulmão/fisiopatologia , Imagem por Ressonância Magnética/métodos , Masculino , Pessoa de Meia-Idade , Pletismografia/métodos , Doença Pulmonar Obstrutiva Crônica/fisiopatologia , Doença Pulmonar Obstrutiva Crônica/terapia , Respiração , Espirometria/métodos , Inquéritos e Questionários , Tomografia Computadorizada por Raios X/métodos , Capacidade Vital/fisiologia
18.
J Magn Reson Imaging ; 45(4): 1204-1215, 2017 04.
Artigo em Inglês | MEDLINE | ID: mdl-27731948

RESUMO

PURPOSE: To develop and assess ultrashort echo-time (UTE) magnetic resonance imaging (MRI) biomarkers of lung function in asthma patients. MATERIALS AND METHODS: Thirty participants including 13 healthy volunteers and 17 asthmatics provided written informed consent to UTE and pulmonary function tests in addition to hyperpolarized-noble-gas 3T MRI and computed tomography (CT) for asthmatics only. The difference in MRI signal-intensity (SI) across four lung volumes (full-expiration, functional-residual-capacity [FRC], FRC+1L, and full-inspiration) was determined on a voxel-by-voxel basis to generate dynamic proton-density (DPD) maps. MRI ventilation-defect-percent (VDP), UTE SI, and DPD values as well as CT radiodensity were determined for whole lung and individual lobes. RESULTS: Mean SI at full-expiration (P < 0.01), FRC (P < 0.05), and DPD (P < 0.01) were greater in healthy volunteers compared to asthmatics. In asthmatics, UTE SI at full-expiration and DPD were correlated with FEV1 /FVC (SI r = 0.73/P = 0.002; DPD r = 0.75/P = 0.003), RV/TLC (SI r = -0.57/P = 0.02), or RV (DPD r = -0.62/P = 0.02), CT radiodensity (SI r = 0.83/P = 0.006; DPD r = 0.71/P = 0.01), and lobar VDP (SI rs = -0.33/P = 0.02; DPD rs = -0.47/P = 0.01). CONCLUSION: In patients with asthma, UTE SI and dynamic proton-density were related to pulmonary function measurements, whole lung and lobar VDP, as well as CT radiodensity. Thus, UTE MRI biomarkers may reflect ventilation heterogeneity and/or gas-trapping in asthmatics using conventional equipment, making this approach potentially amenable for clinical use. LEVEL OF EVIDENCE: 2 J. Magn. Reson. Imaging 2017;45:1204-1215.


Assuntos
Asma/fisiopatologia , Interpretação de Imagem Assistida por Computador/métodos , Processamento de Imagem Assistida por Computador/métodos , Pulmão/diagnóstico por imagem , Pulmão/fisiopatologia , Imagem por Ressonância Magnética/métodos , Adulto , Biomarcadores , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Testes de Função Respiratória
19.
Eur Respir J ; 48(2): 370-9, 2016 08.
Artigo em Inglês | MEDLINE | ID: mdl-27174885

RESUMO

In asthma patients, magnetic resonance imaging (MRI) and the lung clearance index (LCI) have revealed persistent ventilation heterogeneity, although its relationship to asthma control is not well understood. Therefore, our goal was to explore the relationship of MRI ventilation defects and the LCI with asthma control and quality of life in patients with severe, poorly controlled asthma.18 patients with severe, poorly controlled asthma (mean±sd 46±12 years, six males/12 females) provided written informed consent to an ethics board approved protocol, and underwent spirometry, LCI and (3)He MRI during a single 2-h visit. Asthma control and quality of life were evaluated using the Asthma Control Questionnaire (ACQ) and Asthma Quality of Life Questionnaire (AQLQ). Ventilation heterogeneity was quantified using the LCI and (3)He MRI ventilation defect percent (VDP).All participants reported poorly controlled disease (mean±sd ACQ score=2.3±0.9) and highly heterogeneous ventilation (mean±sd VDP=12±11% and LCI=10.5±3.0). While VDP and LCI were strongly correlated (r=0.86, p<0.0001), in a multivariate model that included forced expiratory volume in 1 s, VDP and LCI, VDP was the only independent predictor of asthma control (R(2)=0.38, p=0.01). There was also a significantly worse VDP, but not LCI in asthma patients with an ACQ score >2 (p=0.04) and AQLQ score <5 (p=0.04), and a trend towards worse VDP (p=0.053), but not LCI in asthma patients reporting ≥1 exacerbation in the past 6 months.In patients with poorly controlled, severe asthma MRI ventilation, but not LCI was significantly worse in those with worse ACQ and AQLQ.


Assuntos
Asma/fisiopatologia , Pulmão/diagnóstico por imagem , Respiração , Adolescente , Adulto , Idoso , Brônquios/patologia , Progressão da Doença , Feminino , Volume Expiratório Forçado , Humanos , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Qualidade de Vida , Espirometria , Inquéritos e Questionários , Adulto Jovem
20.
J Thorac Dis ; 8(3): E204-7, 2016 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-27076971
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