Pulmonary Functional Imaging: Part 1-State-of-the-Art Technical and Physiologic Underpinnings

Beyond Spirometry: Linking Wasted Ventilation to Exertional Dyspnea in the Initial Stages of COPD

Exertional dyspnea, a key complaint of patients with chronic obstructive pulmonary disease (COPD), ultimately reflects an increased inspiratory neural drive to breathe. In non-hypoxemic patients with largely preserved lung mechanics - as those in the initial stages of the disease - the heightened inspiratory neural drive is strongly associated with an exaggerated ventilatory response to metabolic demand. Several lines of evidence indicate that the so-called excess ventilation (high ventilation-CO2 output relationship) primarily reflects poor gas exchange efficiency, namely increased physiological dead space. Pulmonary function tests estimating the extension of the wasted ventilation and selected cardiopulmonary exercise testing variables can, therefore, shed unique light on the genesis of patients' out-of-proportion dyspnea. After a succinct overview of the basis of gas exchange efficiency in health and inefficiency in COPD, we discuss how wasted ventilation translates into exertional dyspnea in individual patients. We then outline what is currently known about the structural basis of wasted ventilation in "minor/trivial" COPD vis-à-vis the contribution of emphysema versus a potential impairment in lung perfusion across non-emphysematous lung. After summarizing some unanswered questions on the field, we propose that functional imaging be amalgamated with pulmonary function tests beyond spirometry to improve our understanding of this deeply neglected cause of exertional dyspnea. Advances in the field will depend on our ability to develop robust platforms for deeply phenotyping (structurally and functionally), the dyspneic patients showing unordinary high wasted ventilation despite relatively preserved FEV1.

Using the phase III slope of exhaled methane during a single breath DLCO test to assess ventilation heterogeneity

BACKGROUND

The Phase III slope from a single breath nitrogen washout test provides information about ventilation heterogeneity (VH) in the lungs.

PURPOSE

To determine if the Phase III slope from the exhaled tracer gas concentration during a standard, single breath DLCO test using rapid gas analysis provides similar information about VH.

BASIC PROCEDURES

Retrospective analysis of clinical pulmonary function laboratory data including spirometry, lung volumes, and DLCO. The normalized Phase III slope from the exhaled CH4 concentration (SnCH4) was compared among different patterns of physiologic abnormality and with VA/TLC as an indicator of VH.

MAIN FINDINGS

SnCH4 was the steepest in the group with "Obstruction and Low DLCO", with significant differences between this group and the "Normal", "Obstruction with Normal DLCO", "Mixed Obstruction and Restriction" and "Isolated Low DLCO" groups. SnCH4 was steeper in current and former smokers compared to non-smokers. Among the entire study sample, SnCH4 correlated with VA/TLC (Spearman rho = -0.56, p < 0.01) and remained a significant determinant of VA/TLC by regression modeling.

PRINCIPAL CONCLUSIONS

The SnCH4 derived from a standard, single breath DLCO test using rapid gas analysis varied among distinct patterns of physiologic abnormalities and was associated with VA/TLC as a measure of VH.

A Critical Analysis of the CFD-DEM Simulation of Pharmaceutical Aerosols Deposition in Upper Intra-Thoracic Airways: Considerations on Aerosol Transport and Deposition

The reliability and accuracy of numerical models and computer simulations to study aerosol deposition in the human respiratory system is investigated for a patient-specific tracheobronchial tree geometry. A computational fluid dynamics (CFD) model coupled with discrete elements methods (DEM) is used to predict the transport and deposition of the aerosol. The results are compared to experimental and numerical data available in the literature to study and quantify the impact of the modeling parameters and numerical assumptions. Even if the total deposition compares very well with the reference data, it is clear from the present work how local deposition results can depend significantly upon spatial discretization and boundary conditions adopted to represent the respiratory act. The modeling of turbulent fluctuations in the airflow is also found to impact the local deposition and, to a minor extent, the flow characteristics at the inlet of the computational domain. Using the CFD-DEM model, it was also possible to calculate the airflow and particles splitting at bifurcations, which were found to depart from the assumption of being equally distributed among branches adopted by some of the simplified deposition models. The results thus suggest the need for further studies towards improving the quantitative prediction of aerosol transport and deposition in the human airways.

Flow-Field Inference for Turbulent Exhale Flow Measurement

BACKGROUND

Vision-based pulmonary diagnostics present a unique approach for tracking and measuring natural breathing behaviors through remote imaging. While many existing methods correlate chest and diaphragm movements to respiratory behavior, we look at how the direct visualization of thermal CO2 exhale flow patterns can be tracked to directly measure expiratory flow.

METHODS

In this work, we present a novel method for isolating and extracting turbulent exhale flow signals from thermal image sequences through flow-field prediction and optical flow measurement. The objective of this work is to introduce a respiratory diagnostic tool that can be used to capture and quantify natural breathing, to identify and measure respiratory metrics such as breathing rate, flow, and volume. One of the primary contributions of this work is a method for capturing and measuring natural exhale behaviors that describe individualized pulmonary traits. By monitoring subtle individualized respiratory traits, we can perform secondary analysis to identify unique personalized signatures and abnormalities to gain insight into pulmonary function. In our study, we perform data acquisition within a clinical setting to train an inference model (FieldNet) that predicts flow-fields to quantify observed exhale behaviors over time.

RESULTS

Expiratory flow measurements capturing individualized flow signatures from our initial cohort demonstrate how the proposed flow field model can be used to isolate and analyze turbulent exhale behaviors and measure anomalous behavior.

CONCLUSIONS

Our results illustrate that detailed spatial flow analysis can contribute to unique signatures for identifying patient specific natural breathing behaviors and abnormality detection. This provides the first-step towards a non-contact respiratory technology that directly captures effort-independent behaviors based on the direct measurement of imaged CO2 exhaled airflow patterns.

Chest Magnetic Resonance Imaging: Advances and Clinical Care

Many promising study results as well as technical advances for chest magnetic resonance imaging (MRI) have demonstrated its academic and clinical potentials during the last few decades, although chest MRI has been used for relatively few clinical situations in routine clinical practice. However, the Fleischner Society as well as the Japanese Society of Magnetic Resonance in Medicine have published a few white papers to promote chest MRI in routine clinical practice. In this review, we present clinical evidence of the efficacy of chest MRI for 1) thoracic oncology and 2) pulmonary vascular diseases.

Pulmonary MRI with ultra-short TE using single- and dual-echo methods: comparison of capability for quantitative differentiation of non- or minimally invasive adenocarcinomas from other lung cancers with that of standard-dose thin-section CT

OBJECTIVE

The purpose of this study was thus to compare capabilities for quantitative differentiation of non- and minimally invasive adenocarcinomas from other of pulmonary MRIs with ultra-short TE (UTE) obtained with single- and dual-echo techniques (UTE-MRISingle and UTE-MRIDual) and thin-section CT for stage IA lung cancer patients.

METHODS

Ninety pathologically diagnosed stage IA lung cancer patients who underwent thin-section standard-dose CT, UTE-MRISingle, and UTE-MRIDual, surgical treatment and pathological examinations were included in this retrospective study. The largest dimension (Dlong), solid portion (solid Dlong), and consolidation/tumor (C/T) ratio of each nodule were assessed. Two-tailed Student's t-tests were performed to compare all indexes obtained with each method between non- and minimally invasive adenocarcinomas and other lung cancers. Receiver operating characteristic (ROC)-based positive tests were performed to determine all feasible threshold values for distinguishing non- or minimally invasive adenocarcinoma (MIA) from other lung cancers. Sensitivity, specificity, and accuracy were then compared by means of McNemar's test.

RESULTS

Each index showed significant differences between the two groups (p < 0.0001). Specificities and accuracies of solid Dlong for UTE-MRIDual2nd echo and CTMediastinal were significantly higher than those of solid Dlong for UTE-MRISingle and UTE-MRIDual1st echo and all C/T ratios except CTMediastinal (p < 0.05). Moreover, the specificities and accuracies of solid Dlong and C/T ratio were significantly higher than those of Dlong for each method (p < 0.05).

CONCLUSION

Pulmonary MRI with UTE is considered at least as valuable as thin-section CT for quantitative differentiation of non- and minimally invasive adenocarcinomas from other stage IA lung cancers.

CLINICAL RELEVANCE STATEMENT

Pulmonary MRI with UTE's capability for quantitative differentiation of non- and minimally invasive adenocarcinomas from other lung cancers in stage IA lung cancer patients is equal or superior to that of thin-section CT.

KEY POINTS

• Correlations were excellent for pathologically examined nodules with the largest dimensions (Dlong) and a solid component (solid Dlong) for all indexes (0.95 ≤ r ≤ 0.99, p < 0.0001). • Pathologically examined Dlong and solid Dlong obtained with all methods showed significant differences between non- and minimally invasive adenocarcinomas and other lung cancers (p < 0.0001). • Solid tumor components are most accurately measured by UTE-MRIDual2nd echo and CTMediastinal, whereas the ground-glass component is imaged by UTE-MRIDual1st echo and CTlung with high accuracy. UTE-MRIDual predicts tumor invasiveness with 100% sensitivity and 87.5% specificity at a C/T threshold of 0.5.

Lung Magnetic Resonance Imaging: Technical Advancements and Clinical Applications

ABSTRACT

Since lung magnetic resonance imaging (MRI) became clinically available, limited clinical utility has been suggested for applying MRI to lung diseases. Moreover, clinical applications of MRI for patients with lung diseases or thoracic oncology may vary from country to country due to clinical indications, type of health insurance, or number of MR units available. Because of this situation, members of the Fleischner Society and of the Japanese Society for Magnetic Resonance in Medicine have published new reports to provide appropriate clinical indications for lung MRI. This review article presents a brief history of lung MRI in terms of its technical aspects and major clinical indications, such as (1) what is currently available, (2) what is promising but requires further validation or evaluation, and (3) which developments warrant research-based evaluations in preclinical or patient studies. We hope this article will provide Investigative Radiology readers with further knowledge of the current status of lung MRI and will assist them with the application of appropriate protocols in routine clinical practice.

Automatic lung segmentation of magnetic resonance images: A new approach applied to healthy volunteers undergoing enhanced Deep-Inspiration-Breath-Hold for motion-mitigated 4D proton therapy of lung tumors

Background and purpose

Respiratory suppression techniques represent an effective motion mitigation strategy for 4D-irradiation of lung tumors with protons. A magnetic resonance imaging (MRI)-based study applied and analyzed methods for this purpose, including enhanced Deep-Inspiration-Breath-Hold (eDIBH). Twenty-one healthy volunteers (41-58 years) underwent thoracic MR scans in four imaging sessions containing two eDIBH-guided MRIs per session to simulate motion-dependent irradiation conditions. The automated MRI segmentation algorithm presented here was critical in determining the lung volumes (LVs) achieved during eDIBH.

Materials and methods

The study included 168 MRIs acquired under eDIBH conditions. The lung segmentation algorithm consisted of four analysis steps: (i) image preprocessing, (ii) MRI histogram analysis with thresholding, (iii) automatic segmentation, (iv) 3D-clustering. To validate the algorithm, 46 eDIBH-MRIs were manually contoured. Sørensen-Dice similarity coefficients (DSCs) and relative deviations of LVs were determined as similarity measures. Assessment of intrasessional and intersessional LV variations and their differences provided estimates of statistical and systematic errors.

Results

Lung segmentation time for 100 2D-MRI planes was ∼ 10 s. Compared to manual lung contouring, the median DSC was 0.94 with a lower 95 % confidence level (CL) of 0.92. The relative volume deviations yielded a median value of 0.059 and 95 % CLs of -0.013 and 0.13. Artifact-based volume errors, mainly of the trachea, were estimated. Estimated statistical and systematic errors ranged between 6 and 8 %.

Conclusions

The presented analytical algorithm is fast, precise, and readily available. The results are comparable to time-consuming, manual segmentations and other automatic segmentation approaches. Post-processing to remove image artifacts is under development.

Chest MRI and CT Predictors of 10-Year All-Cause Mortality in COPD

Pulmonary imaging measurements using magnetic resonance imaging (MRI) and computed tomography (CT) have the potential to deepen our understanding of chronic obstructive pulmonary disease (COPD) by measuring airway and parenchymal pathologic information that cannot be provided by spirometry. Currently, MRI and CT measurements are not included in mortality risk predictions, diagnosis, or COPD staging. We evaluated baseline pulmonary function, MRI and CT measurements alongside imaging texture-features to predict 10-year all-cause mortality in ex-smokers with (n = 93; 31 females; 70 ± 9years) and without (n = 69; 29 females, 69 ± 9years) COPD. CT airway and vessel measurements, helium-3 (3He) MRI ventilation defect percent (VDP) and apparent diffusion coefficients (ADC) were quantified. MRI and CT texture-features were extracted using PyRadiomics (version2.2.0). Associations between 10-year all-cause mortality and all clinical and imaging measurements were evaluated using multivariable regression model odds-ratios. Machine-learning predictive models for 10-year all-cause mortality were evaluated using area-under-receiver-operator-characteristic-curve (AUC), sensitivity and specificity analyses. DLCO (%pred) (HR = 0.955, 95%CI: 0.934-0.976, p < 0.001), MRI ADC (HR = 1.843, 95%CI: 1.260-2.871, p < 0.001), and CT informational-measure-of-correlation (HR = 3.546, 95% CI: 1.660-7.573, p = 0.001) were the strongest predictors of 10-year mortality. A machine-learning model trained on clinical, imaging, and imaging textures was the best predictive model (AUC = 0.82, sensitivity = 83%, specificity = 84%) and outperformed the solely clinical model (AUC = 0.76, sensitivity = 77%, specificity = 79%). In ex-smokers, regardless of COPD status, addition of CT and MR imaging texture measurements to clinical models provided unique prognostic information of mortality risk that can allow for better clinical management.Clinical Trial Registration: www.clinicaltrials.gov NCT02279329.

Lung functional imaging

Pulmonary functional imaging modalities such as computed tomography, magnetic resonance imaging and nuclear imaging can quantitatively assess regional lung functional parameters and their distributions. These include ventilation, perfusion, gas exchange at the microvascular level and biomechanical properties, among other variables. This review describes the rationale, strengths and limitations of the various imaging modalities employed for lung functional imaging. It also aims to explain some of the most commonly measured parameters of regional lung function. A brief review of evidence on the role and utility of lung functional imaging in early diagnosis, accurate lung functional characterisation, disease phenotyping and advancing the understanding of disease mechanisms in major respiratory disorders is provided.

Area-Detector Computed Tomography for Pulmonary Functional Imaging

An area-detector CT (ADCT) has a 320-detector row and can obtain isotropic volume data without helical scanning within an area of nearly 160 mm. The actual-perfusion CT data within this area can, thus, be obtained by means of continuous dynamic scanning for the qualitative or quantitative evaluation of regional perfusion within nodules, lymph nodes, or tumors. Moreover, this system can obtain CT data with not only helical but also step-and-shoot or wide-volume scanning for body CT imaging. ADCT also has the potential to use dual-energy CT and subtraction CT to enable contrast-enhanced visualization by means of not only iodine but also xenon or krypton for functional evaluations. Therefore, systems using ADCT may be able to function as a pulmonary functional imaging tool. This review is intended to help the reader understand, with study results published during the last a few decades, the basic or clinical evidence about (1) newly applied reconstruction methods for radiation dose reduction for functional ADCT, (2) morphology-based pulmonary functional imaging, (3) pulmonary perfusion evaluation, (4) ventilation assessment, and (5) biomechanical evaluation.

Advances for Pulmonary Functional Imaging: Dual-Energy Computed Tomography for Pulmonary Functional Imaging

Dual-energy computed tomography (DECT) can improve the differentiation of material by using two different X-ray energy spectra, and may provide new imaging techniques to diagnostic radiology to overcome the limitations of conventional CT in characterizing tissue. Some techniques have used dual-energy imaging, which mainly includes dual-sourced, rapid kVp switching, dual-layer detectors, and split-filter imaging. In iodine images, images of the lung's perfused blood volume (PBV) based on DECT have been applied in patients with pulmonary embolism to obtain both images of the PE occluding the pulmonary artery and the consequent perfusion defects in the lung's parenchyma. PBV images of the lung also have the potential to indicate the severity of PE, including chronic thromboembolic pulmonary hypertension. Virtual monochromatic imaging can improve the accuracy of diagnosing pulmonary vascular diseases by optimizing kiloelectronvolt settings for various purposes. Iodine images also could provide a new approach in the area of thoracic oncology, for example, for the characterization of pulmonary nodules and mediastinal lymph nodes. DECT-based lung ventilation imaging is also available with noble gases with high atomic numbers, such as xenon, which is similar to iodine. A ventilation map of the lung can be used to image various pulmonary diseases such as chronic obstructive pulmonary disease.

Volume-Controlled 19 F MR Ventilation Imaging of Fluorinated Gas

BACKGROUND

¹⁹ F MRI of inhaled gas tracers has developed into a promising tool for pulmonary diagnostics. Prior to clinical use, the intersession repeatability of acquired ventilation parameters must be quantified and maximized.

PURPOSE

To evaluate repeatability of static and dynamic ¹⁹ F ventilation parameters and correlation with predicted forced expiratory volume in 1 second (FEV₁ %pred) with and without inspiratory volume control.

STUDY TYPE

Prospective.

POPULATION

A total of 30 healthy subjects and 26 patients with chronic obstructive pulmonary disease (COPD).

FIELD STRENGTH/SEQUENCE

Three-dimensional (3D) gradient echo pulse sequence with golden-angle stack-of-stars k-space encoding at 1.5 T.

ASSESSMENT

All study participants underwent ¹⁹ F ventilation MRI over eight breaths with inspiratory volume control (w VC) and without inspiratory volume control (w/o VC), which was repeated within 1 week. Ventilated volume percentage (VVP), fractional ventilation (FV), and wash-in time (WI) were computed. Lung function testing was conducted on the first visit.

STATISTICAL TESTS

Correlation between imaging and FEV₁ %pred was measured using Pearson correlation coefficient (r). Differences in imaging parameters between first and second visit were analyzed using paired t-test. Repeatability was quantified using intraclass correlation coefficient (ICC) and coefficient of variation (CoV). Minimum detectable effect size (MDES) was calculated with a power analysis for study size n = 30 and a power of 0.8. All hypotheses were tested with a significance level of 5% two sided.

RESULTS

Strong and moderate linear correlations with FEV₁ %pred for COPD patients were found in almost all imaging parameters. The ICC w VC exceeds the ICC w/o VC for all imaging parameters. CoV was significantly lower w VC for initial VVP in COPD patients, FV, CoV FV, WI and standard deviation (SD) of WI. MDES of all imaging parameters were smaller w VC.

DATA CONCLUSION

¹⁹ F gas wash-in MRI with inspiratory volume control increases the correlation and repeatability of imaging parameters with lung function testing.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

State of the Art MR Imaging for Lung Cancer TNM Stage Evaluation

Since the Radiology Diagnostic Oncology Group (RDOG) report had been published in 1991, magnetic resonance (MR) imaging had limited clinical availability for thoracic malignancy, as well as pulmonary diseases. However, technical advancements in MR systems, such as sequence and reconstruction methods, and adjustments in the clinical protocol for gadolinium contrast media administration have provided fruitful results and validated the utility of MR imaging (MRI) for lung cancer evaluations. These techniques include: (1) contrast-enhanced MR angiography for T-factor evaluation, (2) short-time inversion recovery turbo spin-echo sequences as well as diffusion-weighted imaging (DWI) for N-factor assessment, and (3) whole-body MRI with and without DWI and with positron emission tomography fused with MRI for M-factor or TNM stage evaluation as well as for postoperative recurrence assessment of lung cancer or other thoracic tumors using 1.5 tesla (T) or 3T systems. According to these fruitful results, the Fleischner Society has changed its position to approve of MRI for lung or thoracic diseases. The purpose of this review is to analyze recent advances in lung MRI with a particular focus on lung cancer evaluation, clinical staging, and recurrence assessment evaluation.

Imaging Regional Airway Involvement of Asthma: Heterogeneity in Ventilation, Mucus Plugs and Remodeling

The imaging of asthma using chest computed tomography (CT) is well-established (Jarjour et al., Am J Respir Crit Care Med 185(4):356-62, 2012; Castro et al., J Allergy Clin Immunol 128:467-78, 2011). Moreover, recent advances in functional imaging of the lungs with advanced computer analysis of both CT and magnetic resonance images (MRI) of the lungs have begun to play a role in quantifying regional obstruction. Specifically, quantitative measurements of the airways for bronchial wall thickening, luminal narrowing and distortion, the amount of mucus plugging, parenchymal density, and ventilation defects that could contribute to the patient's disease course are instructive for the entire care team. In this chapter, we will review common imaging methods and findings that relate to the heterogeneity of asthma. This information can help to guide treatment decisions. We will discuss mucous plugging, quantitative assessment of bronchial wall thickening, delta lumen phenomenon, parenchymal low-density lung on CT, and ventilation defect percentage on MRI as metrics for assessing regional ventilatory dysfunction.

Lung function measurements in preclinical research: What has been done and where is it headed?

Due to the close interaction of lung morphology and functions, repeatable measurements of pulmonary function during longitudinal studies on lung pathophysiology and treatment efficacy have been a great area of interest for lung researchers. Spirometry, as a simple and quick procedure that depends on the maximal inspiration of the patient, is the most common lung function test in clinics that measures lung volumes against time. Similarly, in the preclinical area, plethysmography techniques offer lung functional parameters related to lung volumes. In the past few decades, many innovative techniques have been introduced for in vivo lung function measurements, while each one of these techniques has their own advantages and disadvantages. Before each experiment, depending on the sensitivity of the required pulmonary functional parameters, it should be decided whether an invasive or non-invasive approach is desired. On one hand, invasive techniques offer sensitive and specific readouts related to lung mechanics in anesthetized and tracheotomized animals at endpoints. On the other hand, non-invasive techniques allow repeatable lung function measurements in conscious, free-breathing animals with readouts related to the lung volumes. The biggest disadvantage of these standard techniques for lung function measurements is considering the lung as a single unit and providing only global readouts. However, recent advances in lung imaging modalities such as x-ray computed tomography and magnetic resonance imaging opened new doors toward obtaining both anatomical and functional information from the same scan session, without the requirement for any extra pulmonary functional measurements, in more regional and non-invasive manners. Consequently, a new field of study called pulmonary functional imaging was born which focuses on introducing new techniques for regional quantification of lung function non-invasively using imaging-based techniques. This narrative review provides first an overview of both invasive and non-invasive conventional methods for lung function measurements, mostly focused on small animals for preclinical research, including discussions about their advantages and disadvantages. Then, we focus on those newly developed, non-invasive, imaging-based techniques that can provide either global or regional lung functional readouts at multiple time-points.

Artificial intelligence in functional imaging of the lung

Artificial intelligence (AI) is transforming the way we perform advanced imaging. From high-resolution image reconstruction to predicting functional response from clinically acquired data, AI is promising to revolutionize clinical evaluation of lung performance, pushing the boundary in pulmonary functional imaging for patients suffering from respiratory conditions. In this review, we overview the current developments and expound on some of the encouraging new frontiers. We focus on the recent advances in machine learning and deep learning that enable reconstructing images, quantitating, and predicting functional responses of the lung. Finally, we shed light on the potential opportunities and challenges ahead in adopting AI for functional lung imaging in clinical settings.

PREFUL MRI Depicts Dual Bronchodilator Changes in COPD: A Retrospective Analysis of a Randomized Controlled Trial

Purpose

To assess whether dynamic ventilation and perfusion (Q) biomarkers derived by phase-resolved functional lung (PREFUL) MRI can measure treatment response to 14-day therapy with indacaterol-glycopyrronium (IND-GLY) and correlate to clinical outcomes including lung function, symptoms, and cardiac function in patients with chronic obstructive pulmonary disease (COPD), as determined by spirometry, body plethysmography, cardiac MRI, and dyspnea score measurements.

Materials and Methods

The cardiac left ventricular function in COPD (CLAIM) study enrolled patients aged 40 years or older with COPD, stable cardiovascular function, and hyperinflation (residual volume > 135% predicted). Dynamic MRI data of these patients were retrospectively analyzed using the PREFUL technique to assess the effect of 14-day IND-GLY treatment versus placebo on regional measurements of ventilation dynamics. After manual segmentation of the lung parenchyma, flow-volume loops of each voxel were correlated to an individualized reference flow-volume loop, creating a two-dimensional flow-volume loop correlation map (FVL-CM) as a measure of ventilation dynamics. Ventilation-perfusion match (VQM) was evaluated in combination with perfusion and regional ventilation (VQM_RVent) and with perfusion and the FVL-CM measurement (VQM_CM). For image and statistical analysis, the lung parenchyma was segmented as a region of interest by manually delineating the lung boundary and excluding the large (central) vessels for each section. Differences in ventilation, perfusion, and VQM between IND-GLY and placebo were compared using analysis of variance, with study treatment, patient, and period included as factors.

Results

Fifty patients (mean age, 64.3 years ± 7.65 [SD]; 35 men) were included in this analysis. IND-GLY significantly increased mean correlation as measured with FVL-CM versus that of placebo (least squares [LS] means treatment difference: 0.05 [95% CI: 0.03, 0.07]; P < .0001). Compared with placebo, IND-GLY increased mean Q (LS means treatment difference: 9.27 mL/min/100 mL [95% CI: 0.05, 18.49]; P = .049) and improved both VQM_CM and VQM_RVent (LS means treatment difference: 0.06 [95% CI: 0.03, 0.08]; P < .0001 and 0.05 [95% CI: 0.02, 0.08]; P = .001, respectively).

Conclusion

Regional ventilation dynamics and VQM measured by PREFUL MRI show treatment response in COPD.

Supplemental material is available for this article.

Clinical trial registration no. NTR6831

Keywords: MRI, COPD, Perfusion, Ventilation, Lung, Pulmonary

Published under a CC BY 4.0 license

Estimation of Nuclear Medicine Exposure Measures Based on Intelligent Computer Processing

This paper provides an in-depth discussion and analysis of the estimation of nuclear medicine exposure measurements using computerized intelligent processing. The focus is on the study of energy extraction algorithms to obtain a high energy resolution with the lowest possible ADC sampling rate and thus reduce the amount of data. This paper focuses on the direct pulse peak extraction algorithm, polynomial curve fitting algorithm, double exponential function curve fitting algorithm, and pulse area calculation algorithm. The detector output waveforms are obtained with an oscilloscope, and the analysis module is designed in MATLAB. Based on these algorithms, the data obtained from six different lower sampling rates are analyzed and compared with the results of the high sampling rate direct pulse peak extraction algorithm and the pulse area calculation algorithm, respectively. The correctness of the compartment model was checked, and the results were found to be realistic and reliable, which can be used for the analysis of internal exposure data in radiation occupational health management, estimation of internal exposure dose for nuclear emergency groups, and estimation of accidental internal exposure dose. The results of the compartment model of the respiratory tract and the compartment model of the digestive tract can be used to calculate the distribution and retention patterns of radionuclides and their compounds in the body, which can be used to assess the damage of radionuclide internal contamination and guide the implementation of medical treatment.

Total Lung and Lobar Quantitative Assessment Based on Paired Inspiratory-Expiratory Chest CT in Healthy Adults: Correlation with Pulmonary Ventilatory Function

Objective: To provide the quantitative volumetric data of the total lung and lobes in inspiration and expiration from healthy adults, and to explore the value of paired inspiratory–expiratory chest CT scan in pulmonary ventilatory function and further explore the influence of each lobe on ventilation. Methods: A total of 65 adults (29 males and 36 females) with normal clinical pulmonary function test (PFT) and paired inspiratory–expiratory chest CT scan were retrospectively enrolled. The inspiratory and expiratory volumetric indexes of the total lung (TL) and 5 lobes (left upper lobe [LUL], left lower lobe [LLL], right upper lobe [RUL], right middle lobe [RML], and right lower lobe [RLL]) were obtained by Philips IntelliSpace Portal image postprocessing workstation, including inspiratory lung volume (LV_in), expiratory lung volume (LV_ex), volume change (∆LV), and well-aerated lung volume (WAL, lung tissue with CT threshold between −950 and −750 HU in inspiratory scan). Spearman correlation analysis was used to explore the correlation between CT quantitative indexes of the total lung and ventilatory function indexes (including total lung capacity [TLC], residual volume [RV], and force vital capacity [FVC]). Multiple stepwise regression analysis was used to explore the influence of each lobe on ventilation. Results: At end-inspiratory phase, the LV_in-TL was 4664.6 (4282.7, 5916.2) mL, the WAL_TL was 4173 (3639.6, 5250.9) mL; both showed excellent correlation with TLC (LV_in-TL: r = 0.890, p < 0.001; WAL_TL: r = 0.879, p < 0.001). From multiple linear regression analysis with lobar CT indexes as variables, the LV_in and WAL of these two lobes, LLL and RUL, showed a significant relationship with TLC. At end-expiratory phase, the LV_ex-TL was 2325.2 (1969.7, 2722.5) mL with good correlation with RV (r = 0.811, p < 0.001), of which the LV_ex of RUL and RML had a significant relationship with RV. For the volumetric change within breathing, the ∆LV_TL was 2485.6 (2169.8, 3078.1) mL with good correlation with FVC (r = 0.719, p < 0.001), moreover, WAL_TL showed a better correlation with FVC (r = 0.817, p < 0.001) than that of ∆LV_TL. Likewise, there was also a strong association between ∆LV, WAL of these two lobes (LLL and RUL), and FVC. Conclusions: The quantitative indexes derived from paired inspiratory–expiratory chest CT could reflect the clinical pulmonary ventilatory function, LLL, and RUL give greater impact on ventilation. Thus, the pulmonary functional evaluation needs to be more precise and not limited to the total lung level.

Pulmonary Functional Imaging: Part 2-State-of-the-Art Clinical Applications and Opportunities for Improved Patient Care

Pulmonary functional imaging may be defined as the regional quantification of lung function by using primarily CT, MRI, and nuclear medicine techniques. The distribution of pulmonary physiologic parameters, including ventilation, perfusion, gas exchange, and biomechanics, can be noninvasively mapped and measured throughout the lungs. This information is not accessible by using conventional pulmonary function tests, which measure total lung function without viewing the regional distribution. The latter is important because of the heterogeneous distribution of virtually all lung disorders. Moreover, techniques such as hyperpolarized xenon 129 and helium 3 MRI can probe lung physiologic structure and microstructure at the level of the alveolar-air and alveolar-red blood cell interface, which is well beyond the spatial resolution of other clinical methods. The opportunities, challenges, and current stage of clinical deployment of pulmonary functional imaging are reviewed, including applications to chronic obstructive pulmonary disease, asthma, interstitial lung disease, pulmonary embolism, and pulmonary hypertension. Among the challenges to the deployment of pulmonary functional imaging in routine clinical practice are the need for further validation, establishment of normal values, standardization of imaging acquisition and analysis, and evidence of patient outcomes benefit. When these challenges are addressed, it is anticipated that pulmonary functional imaging will have an expanding role in the evaluation and management of patients with lung disease.