Qualitative and quantitative assessment of smoking-related lung disease: effect of iterative reconstruction on low-dose computed tomographic examinations

The Use of CT Densitometry for the Assessment of Emphysema in Clinical Trials: A Position Paper from the Fleischner Society

Emphysema's significant morbidity and mortality underscore the need for reliable outcome metrics in clinical trials. However, commonly accepted COPD outcome measures do not adequately capture emphysema severity or progression. Computed tomography (CT) metrics have been validated as accurate indicators of pathological emphysema and predictors of COPD progression, exacerbations, and mortality. This Position Paper reviews the evidence supporting CT densitometry as a biomarker for emphysema, establishes implementation standards, and highlights areas for future research. A systematic literature review addressed three key questions: whether CT densitometry can be used as a diagnostic biomarker of emphysema, whether CT densitometry can be used as prognostic biomarker, and whether longitudinal change in densitometry can be used as a disease progression monitoring biomarker. Emphysema metrics, such as the percentage of low attenuation areas (LAA-950), are validated, highly reproducible diagnostic and prognostic biomarkers. Volume-adjusted lung density is recommended for disease monitoring. Both metrics demonstrate a scan-rescan intra-class correlation coefficient of 0.99 with proper technique. The paper also discusses relevant CT physics, techniques, and sources of variation, including technical factors, physiological changes, and software analysis. Key recommendations for clinical trials include using standardized CT techniques, proper subject selection, and longitudinal evaluation with volume-adjusted lung density.

Deep Learning-Based Kernel Adaptation Enhances Quantification of Emphysema on Low-Dose Chest CT for Predicting Long-Term Mortality

OBJECTIVES

The aim of this study was to ascertain the predictive value of quantifying emphysema using low-dose computed tomography (LDCT) post deep learning-based kernel adaptation on long-term mortality.

MATERIALS AND METHODS

This retrospective study investigated LDCTs obtained from asymptomatic individuals aged 60 years or older during health checkups between February 2009 and December 2016. These LDCTs were reconstructed using a 1- or 1.25-mm slice thickness alongside high-frequency kernels. A deep learning algorithm, capable of generating CT images that resemble standard-dose and low-frequency kernel images, was applied to these LDCTs. To quantify emphysema, the lung volume percentage with an attenuation value less than or equal to -950 Hounsfield units (LAA-950) was gauged before and after kernel adaptation. Low-dose chest CTs with LAA-950 exceeding 6% were deemed emphysema-positive according to the Fleischner Society statement. Survival data were sourced from the National Registry Database at the close of 2021. The risk of nonaccidental death, excluding causes such as injury or poisoning, was explored according to the emphysema quantification results using multivariate Cox proportional hazards models.

RESULTS

The study comprised 5178 participants (mean age ± SD, 66 ± 3 years; 3110 males). The median LAA-950 (18.2% vs 2.6%) and the proportion of LDCTs with LAA-950 exceeding 6% (96.3% vs 39.3%) saw a significant decline after kernel adaptation. There was no association between emphysema quantification before kernel adaptation and the risk of nonaccidental death. Nevertheless, after kernel adaptation, higher LAA-950 (hazards ratio for 1% increase, 1.01; P = 0.045) and LAA-950 exceeding 6% (hazards ratio, 1.36; P = 0.008) emerged as independent predictors of nonaccidental death, upon adjusting for age, sex, and smoking status.

CONCLUSIONS

The application of deep learning for kernel adaptation proves instrumental in quantifying pulmonary emphysema on LDCTs, establishing itself as a potential predictive tool for long-term nonaccidental mortality in asymptomatic individuals.

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.

A Challenge for Emphysema Quantification Using a Deep Learning Algorithm With Low-dose Chest Computed Tomography

PURPOSE

We aimed to identify clinically relevant deep learning algorithms for emphysema quantification using low-dose chest computed tomography (LDCT) through an invitation-based competition.

MATERIALS AND METHODS

The Korean Society of Imaging Informatics in Medicine (KSIIM) organized a challenge for emphysema quantification between November 24, 2020 and January 26, 2021. Seven invited research teams participated in this challenge. In total, 558 pairs of computed tomography (CT) scans (468 pairs for the training set, and 90 pairs for the test set) from 9 hospitals were collected retrospectively or prospectively. CT acquisition followed the hospitals' protocols to reflect the real-world clinical setting. Using the training set, each team developed an algorithm that generated converted LDCT by changing the pixel values of LDCT to simulate those of standard-dose CT (SDCT). The agreement between SDCT and LDCT was evaluated using the intraclass correlation coefficient (ICC; 2-way random effects, absolute agreement, and single rater) for the percentage of low-attenuated area below -950 HU (LAA-950 HU), κ value for emphysema categorization (LAA-950 HU, <5%, 5% to 10%, and ≥10%) and cosine similarity of LAA-950 HU.

RESULTS

The mean LAA-950 HU of the test set was 14.2%±10.5% for SDCT, 25.4%±10.2% for unconverted LDCT, and 12.9%±10.4%, 11.7%±10.8%, and 12.4%±10.5% for converted LDCT (top 3 teams). The agreement between the SDCT and converted LDCT of the first-place team was 0.94 (95% confidence interval: 0.90, 0.97) for ICC, 0.71 (95% confidence interval: 0.58, 0.84) for categorical agreement, and 0.97 (interquartile range: 0.94 to 0.99) for cosine similarity.

CONCLUSIONS

Emphysema quantification with LDCT was feasible through deep learning-based CT conversion strategies.

Optimization of pulmonary emphysema quantification on CT scans of COPD patients using hybrid iterative and post processing techniques: correlation with pulmonary function tests

Objectives

The aim of this study was to assess the effect of hybrid iterative reconstruction and post processing on emphysema quantification in low-dose CT scans of COPD patients using pulmonary function tests (PFT) as a reference.

Methods

CT scans of 23 COPD patients diagnosed with GOLD I or higher were reconstructed with iDose⁴ level 1 to 7 in IntelliSpace Portal (ISP) 6 and 7. ISP7 was used with and without specific denoising filter for COPD. The extent of emphysema was measured as percentage of lung voxels with attenuation < − 950 Hounsfield units (%LAA-950). The correlation between %LAA-950 and PFT, age, BMI, pack years, and the Clinical COPD Questionnaire (CCQ) and Medical Research Council dyspnea scale (MRC) was determined.

Results

Denoising significantly reduced %LAA-950 as was demonstrated by lower %LAA-950 in ISP7 with denoising filter and a significant reduction in %LAA-950 with higher iDose⁴ levels. All PFT except forced vital capacity (FVC) were significantly inversely correlated with %LAA-950. There was a trend toward a stronger correlation at higher iDose⁴ levels. %LAA-950 was also significantly correlated with BMI, GOLD class, and CCQ scores.

Conclusions

Our study showed that hybrid iterative reconstruction and use of post processing denoising can optimize the use of emphysema quantification in CT scans as a complimentary diagnostic tool to stage COPD in addition to PFT.

Variability of CT Airways Measurements in COPD Patients Between Morning and Afternoon: Comparisons to Variability of Spirometric Measurements

RATIONALE AND OBJECTIVES

Computed tomography (CT) airways measurements can be used as surrogates to spirometric measurements for assessing bronchodilation in a particular patient with chronic obstructive pulmonary disease. Although spirometric measurements show variations within the opening hours of a hospital department, we aimed to compare the variability of CT airways measurements between morning and afternoon in patients with chronic obstructive pulmonary disease to that of spirometric measurements.

MATERIALS AND METHODS

Twenty patients had pulmonary function tests and CT around 8 am and 4 pm. Luminal area (LA) and wall thickness (WT) of third and fourth generation airways were measured twice by three readers. The percentage of airway area occupied by the wall (WA%) and the square root of wall area at an internal perimeter of 10 mm (√WAPi10) were calculated. The effects of examination time, reader, and measurement session on CT airways measurements were assessed, and the variability of these measurements was compared to that of spirometric measurements.

RESULTS

Variability of LA^3rd and LA^4th was greater than that of spirometric measurements (P values ranging from <.001 to .033). There was no examination time effect on √WAPi10, WT^3rd, LA^4th, or WA%^4th (P values ranging from .102 to .712). There was a reader effect on all CT airways measurements (P values ranging from <.001 to .028), except in WT^3rd (P> .999). There was no effect of measurement session on any CT airway measurement (P values ranging from .535 to >.999).

CONCLUSION

As the variability of LA^3rd and LA^4th is greater than that of spirometric measurements, clinical studies should include cohorts with larger numbers of patients when considering LA than when considering spirometric measurements as end points.

Reduced dose CT with model-based iterative reconstruction compared to standard dose CT of the chest, abdomen, and pelvis in oncology patients: intra-individual comparison study on image quality and lesion conspicuity

PURPOSE

To compare image quality and lesion conspicuity of reduced dose (RD) CT with model-based iterative reconstruction (MBIR) compared to standard dose (SD) CT in patients undergoing oncological follow-up imaging.

METHODS

Forty-four cancer patients who had a staging SD CT within 12 months were prospectively included to undergo a weight-based RD CT with MBIR. Radiation dose was recorded and tissue attenuation and image noise of four tissue types were measured. Reproducibility of target lesion size measurements of up to 5 target lesions per patient were analyzed. Subjective image quality was evaluated for three readers independently utilizing 4- or 5-point Likert scales.

RESULTS

Median radiation dose reduction was 46% using RD CT (P < 0.01). Median image noise across all measured tissue types was lower (P < 0.01) in RD CT. Subjective image quality for RD CT was higher (P < 0.01) in regard to image noise and overall image quality; however, there was no statistically significant difference regarding image sharpness (P = 0.59). There were subjectively more artifacts on RD CT (P < 0.01). Lesion conspicuity was subjectively better in RD CT (P < 0.01). Repeated target lesion size measurements were highly reproducible both on SD CT (ICC = 0.987) and RD CT (ICC = 0.97).

CONCLUSIONS

RD CT imaging with MBIR provides diagnostic imaging quality and comparable lesion conspicuity on follow-up exams while allowing dose reduction by a median of 46% compared to SD CT imaging.

The effects of iterative reconstruction and kernel selection on quantitative computed tomography measures of lung density

PURPOSE

To determine the effects of iterative reconstruction (IR) and high-frequency kernels on quantitative computed tomography (qCT) density measures at reduced X-ray dose.

MATERIALS AND METHODS

The COPDGene 2 Phantom (CTP 698, The Phantom Laboratory, Salem, NY) with four embedded lung mimicking foam densities (12lb, 20lb, and 4lb), as well as water, air, and acrylic reference inserts, was imaged using a GE 64 slice CT750 HD scanner in helical mode with four current-time products ranging from 12 to 100 mAs. The raw acquired data were reconstructed using standard (STD - low frequency) and Bone (high frequency) kernels with filtered back projection (FBP), 100% ASiR, and Veo reconstruction algorithms. The reference density inserts were manually segmented using Slicer3D (www.slicer.org), and the mean, standard deviation, and histograms of the segmented regions were generated using Fiji (http://fiji.sc/Fiji) for each reconstruction. Measurements of threshold values placed on the cumulative frequency distribution of voxels determined by these measured histograms at 5%, PD5_phant , and 15%, PD15_phant , (analogous to the relative area below -950 HU (RA-950) and percent density 15 (PD15) in human lung emphysema quantification, respectively), were also performed.

RESULTS

The use of high-resolution kernels in conjunction with ASiR and Veo did not significantly affect the mean Hounsfield units (HU) of each of the density standards (< 4 HU deviation) and current-time products within the phantom when compared with the STD+FBP reconstruction conventionally used in clinical applications. A truncation of the scanner reported HU values at -1024 that shifts the mean toward more positive values was found to cause a systematic error in lower attenuating regions. Use of IR drove convergence toward the mean of measured histograms (~100-137% increase in the number measured voxels at the mean of the histogram), while the combination of Bone+ASiR preserved the standard deviation of HU values about the mean compared to STD+FBP, with the added effect of improved spatial resolution and accuracy in airway measures. PD5_phant and PD15_phant were most similar between the Bone+ASiR and STD+FBP in all regions except those affected by the -1024 truncation artifact.

CONCLUSIONS

Extension of the scanner reportable HU values below the present limit of -1024 will mitigate discrepancies found in qCT lung densitometry in low-density regions. The density histogram became more sharply peaked, and standard deviation was reduced for IR, directly effecting density thresholds, PD5_phant and PD15_phant, placed on the cumulative frequency distribution of each region in the phantom, which serve as analogs to RA-950 and PD15 typically used in lung density quantitation. The combination of high-frequency kernels (Bone) with ASiR mitigates this effect and preserves density measures derived from the image histogram. Moreover, previous studies have shown improved accuracy of qCT airway measures of wall thickness (WT) and wall area percentage (WA%) when using high-frequency kernels in combination with ASiR to better represent airway walls. The results therefore suggest an IR approach for accurate assessment of airway and parenchymal density measures in the lungs.

CT pulmonary angiography using different noise index values with an iterative reconstruction algorithm and dual energy CT imaging using different body mass indices: Image quality and radiation dose

OBJECTIVE

To investigate the differences in imaging quality and radiation dose in CT pulmonary angiography (CTPA) by using fast-kV switching dual energy CT imaging and 3D Smart mA modulation at different body mass indices (BMIs) and at different noise index (NI) values with an adaptive statistical iterative reconstruction (ASIR) algorithm.

METHODS

Four hundred patients who underwent CTPA were equally divided into two groups: A (18.5 kg/m2 ≦ BMI <24.9 kg/m2) and B (24.9 kg/m2 ≦ BMI ≦ 4.9 kg/m2). The groups were randomly subdivided into four subgroups (n = 50): A1-A4 and B1-B4. The patients in subgroups A1 and B1 underwent fast-kV switching dual energy CT imaging. The other patients underwent 3D Smart mA modulation with the ASIR algorithm at NI values 26, 36, and 46 for A2/B2, A3/B3, and A4/B4, respectively. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of all images were calculated after CTPA. Images were then subjectively evaluated using a 5-point scale. The volume CT dose index and dose-length product (DLP) were recorded and their means calculated. The DLP was converted to the effective dose (ED).

RESULTS

In group A, the SNR, CNR, and subjective image scores showed no statistical differences (P > 0.05). The ED in subgroup A4 was 67.12% and 31.53% lower than that in A1 and A2, respectively. In group B, the variables showed no significant differences between the subgroups B3, B1, and B2 (P > 0.05). The ED in subgroup B3 was 50.12% and 35.95% lower than that in B1 and B2, respectively.

CONCLUSIONS

Setting different NI values according to BMIs and applying the ASIR algorithm can more effectively reduce the radiation dose in CTPA than in fast-kV switching dual energy CT, while maintaining image quality. Imaging may be performed at NI = 46 in patients with lower BMI (group A) and at NI = 36 in patients with higher BMI (group B).

CT Pulmonary Angiography Using Automatic Tube Current Modulation Combination with Different Noise Index with Iterative Reconstruction Algorithm in Different Body Mass Index: Image Quality and Radiation Dose

RATIONALE AND OBJECTIVES

This study aimed to determine the appropriate body mass index (BMI)-dependent noise index (NI) setting in computed tomography pulmonary angiography (CTPA) with automatic tube current modulation with adaptive statistical iterative reconstruction (ASiR).

MATERIALS AND METHODS

A total of 480 patients who had a CTPA were divided into group A (18.5 kg/m² ≤ BMI < 25 kg/m²), group B (25 kg/m² ≤ BMI < 30 kg/m²), and group C (BMI ≥ 30 kg/m²), according to their BMI values; each group had 160 patients. The three groups were further randomly divided into four subgroups: A1, A2, A3, A4; B1, B2, B3, B4; and C1, C2, C3, C4, with corresponding NI values of 26, 36, 40, and 46, respectively. All images were restructured with the ASiR algorithm, and the images with the lowest NI (26 Hounsfield units) in each group were used as reference standard. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) for the pulmonary artery of each group were calculated. Subjective image quality was evaluated using a five-score method by two independent radiologists. The CT dose index of volume and dose-length product were recorded and were converted to effective dose (ED). SNR and CNR in the group A, B, and C subgroups were compared to repeated measures analysis of variance, and the subjective score, Volumetric CT dose index of volume, dose-length product, and ED were compared to one-way analysis of variance.

RESULTS

For groups A and B, the SNR, CNR, and subjective scores of the images in their subgroups showed no statistical differences (P >.05). The ED in subgroups A4 and B4 was significantly lower than that in subgroups A1 (by 33.24%) and B1 (by 34.47%) (P <.01). For group C, there was no significant difference in the SNR, CNR, and the subjective image scores between subgroups C3 and C1 (P >.05). The ED in subgroup C3 was significantly lower than the ED in subgroup C1 (by 47.75%) (P <.01) CONCLUSIONS: Patient BMI-dependent NI settings that are higher than the recommended value may be used in CTPA with automatic tube current modulation and ASiR to effectively reduce radiation dose while maintaining diagnostic image quality.

Findings on Thoracic Computed Tomography Scans and Respiratory Outcomes in Persons with and without Chronic Obstructive Pulmonary Disease: A Population-Based Cohort Study

BACKGROUND

Thoracic computed tomography (CT) scans are widely performed in clinical practice, often leading to detection of airway or parenchymal abnormalities in asymptomatic or minimally symptomatic individuals. However, clinical relevance of CT abnormalities is uncertain in the general population.

METHODS

We evaluated data from 1361 participants aged ≥40 years from a Canadian prospective cohort comprising 408 healthy never-smokers, 502 healthy ever-smokers, and 451 individuals with spirometric evidence of chronic obstructive pulmonary disease (COPD) who had thoracic CT scans. CT images of subjects were visually scored for respiratory bronchiolitis(RB), emphysema(E), bronchial-wall thickening(BWT), expiratory air-trapping(AT), and bronchiectasis(B). Multivariable logistic regression models were used to assess associations of CT features with respiratory symptoms, dyspnea, health status as determined by COPD assessment test, and risk of clinically significant exacerbations during 12 months follow-up.

RESULTS

About 11% of life-time never-smokers demonstrated emphysema on CT scans. Prevalence increased to 30% among smokers with normal lung function and 36%, 50%, and 57% among individuals with mild, moderate or severe/very severe COPD, respectively. Presence of emphysema on CT was associated with chronic cough (OR,2.11; 95%CI,1.4-3.18); chronic phlegm production (OR,1.87; 95% CI,1.27-2.76); wheeze (OR,1.61; 95% CI,1.05-2.48); dyspnoea (OR,2.90; 95% CI,1.41-5.98); CAT score≥10(OR,2.17; 95%CI,1.42-3.30) and risk of ≥2 exacerbations over 12 months (OR,2.17; 95% CI, 1.42-3.0).

CONCLUSIONS

Burden of thoracic CT abnormalities is high among Canadians ≥40 years of age, including never-smokers and smokers with normal lung function. Detection of emphysema on CT scans is associated with pulmonary symptoms and increased risk of exacerbations, independent of smoking or lung function.

Computed Tomography and Magnetic Resonance Imaging for Longitudinal Characterization of Lung Structure Changes in a Yucatan Miniature Pig Silicosis Model

Medical imaging is a rapidly advancing field enabling the repeated, noninvasive assessment of physiological structure and function. These beneficial characteristics can supplement studies in swine by mirroring the clinical functions of detection, diagnosis, and monitoring in humans. In addition, swine may serve as a human surrogate, facilitating the development and comparison of new imaging protocols for translation to humans. This study presents methods for pulmonary imaging developed for monitoring pulmonary disease initiation and progression in a pig exposure model with computed tomography and magnetic resonance imaging. In particular, a focus was placed on systematic processes, including positioning, image acquisition, and structured reporting to monitor longitudinal change. The image-based monitoring procedure was applied to 6 Yucatan miniature pigs. A subset of animals (n= 3) were injected with crystalline silica into the apical bronchial tree to induce silicosis. The methodology provided longitudinal monitoring and evidence of progressive lung disease while simultaneously allowing for a cross-modality comparative study highlighting the practical application of medical image data collection in swine. The integration of multimodality imaging with structured reporting allows for cross comparison of modalities, refinement of CT and MRI protocols, and consistently monitors potential areas of interest for guided biopsy and/or necropsy.

Association of incidental emphysema with annual lung function decline and future development of airflow limitation

Objectives

Emphysema is one of the prognostic factors for rapid lung function decline in patients with COPD, but the impact of incidentally detected emphysema on population without spirometric abnormalities has not been evaluated. This study aimed to determine whether emphysema detected upon computed tomography (CT) screening would accelerate the rate of lung function decline and influence the possibility of future development of airflow limitation in a population without spirometric abnormalities.

Materials and methods

Subjects who participated in a routine screening for health checkup and follow-up pulmonary function tests for at least 3 years between 2004 and 2010 were retrospectively enrolled. The percentage of low-attenuation area below −950 Hounsfield units (%LAA₋₉₅₀) was calculated automatically. A calculated value of %LAA₋₉₅₀ that exceeded 10% was defined as emphysema. Adjusted annual lung function decline was analyzed using random-slope, random-intercept mixed linear regression models.

Results

A total of 628 healthy subjects within the normal range of spriometric values were included. Multivariable analysis showed that the emphysema group exhibited a faster decline in forced vital capacity (−33.9 versus −18.8 mL/year; P=0.02). Emphysema was not associated with the development of airflow limitation during follow-up.

Conclusion

Incidental emphysema quantified using CT scan was significantly associated with a more rapid decline in forced vital capacity in the population with normative spirometric values. However, an association between emphysema and future development of airflow limitation was not observed.

Application of computed tomography virtual noncontrast spectral imaging in evaluation of hepatic metastases: a preliminary study

Objective:

The objective was to qualitatively and quantitatively evaluate hepatic metastases using computed tomography (CT) virtual noncontrast (VNC) spectral imaging in a retrospective analysis.

Methods:

Forty hepatic metastases patients underwent CT scans including the conventional true noncontrast (TNC) and the tri-phasic contrast-enhanced dual energy spectral scans in the hepatic arterial, portal venous, and equilibrium phases. The tri-phasic spectral CT images were used to obtain three groups of VNC images including in the arterial (VNCa), venous (VNCv), and equilibrium (VNCe) phase by the material decomposition process using water and iodine as a base material pair. The image quality and the contrast-to-noise ratio (CNR) of metastasis of the four groups were compared with ANOVA analysis. The metastasis detection rates with the four nonenhanced image groups were calculated and compared using the Chi-square test.

Results:

There were no significant differences in image quality among TNC, VNCa and VNCv images (P > 0.05). The quality of VNCe images was significantly worse than that of other three groups (P < 0.05). The mean CNR of metastasis in the TNC and VNCs images was 1.86, 2.42, 1.92, and 1.94, respectively; the mean CNR of metastasis in VNCa images was significantly higher than that in other three groups (P < 0.05), while no statistically significant difference was observed among VNCv, VNCe and TNC images (P > 0.05). The metastasis detection rate of the four nonenhanced groups with no statistically significant difference (P > 0.05).

Conclusions:

The quality of VNCa and VNCv images is identical to that of TNC images, and the metastasis detection rate in VNC images is similar to that in TNC images. VNC images obtained from arterial phase show metastases more clearly. Thus, VNCa imaging may be a surrogate to TNC imaging in hepatic metastasis diagnosis.