Computed Tomography Metrics Research Articles

Body composition measurements and clinical outcomes in patients with resectable pancreatic adenocarcinoma – analysis from SWOG S1505

Sarcopenic obesity and muscle attenuation have been associated with survival in patients with borderline resectable and advanced pancreatic ductal adenocarcinoma (PDA); however, these relationships are unknown for patients with resectable PDA. This study examined the associations between skeletal muscle and adipose tissue as measured on baseline computed tomography (CT) and the overall survival (OS) of participants with resectable PDA in a secondary analysis of the Southwest Oncology Group S1505 clinical trial (identifier: NCT02562716). The S1505 phase II clinical trial enrolled patients with resectable PDA who were randomized to receive modified FOLFIRINOX or gemcitabine and nab-paclitaxel as perioperative chemotherapy, followed by surgical resection. Baseline axial CT images at the L3 level were analyzed with externally validated software, and measurements were recorded for skeletal muscle area and skeletal muscle density, visceral adipose tissue area (VATA) and density, and subcutaneous adipose tissue area and density. The relationships between CT metrics and OS were analyzed using Cox regression models, with adjustment for baseline participant characteristics. Of 98 eligible participants with available baseline abdominal CT, 8 were excluded because of imaging quality (eg, orthopedic hardware), resulting in 90 evaluable cases: 51 men (57.0%; mean age, 63.2 years [SD, 8.5]; mean body mass index [BMI], 29.3kg/m2 [SD, 6.4]), 80 White (89.0%), 6 Black (7.0%), and 4 unknown race (4.0%). Sarcopenia was present in 32 participants (35.9%), and sarcopenic obesity was present in 10 participants (11.2%). Univariable analyses for the 6 variables of interest indicated that the standardized mean difference (hazard ratio [HR], 0.75; 95% CI, 0.57-0.98; P=.04) was statistically significantly associated with OS. In models adjusted for sex, race, age, BMI, performance score, contrast use, sarcopenia, and sarcopenic obesity, VATA was statistically significantly associated with OS (HR, 1.58; 95% CI, 1.00-2.51; P=.05). No difference was observed in OS between participants according to sarcopenic obesity or sarcopenia categories. The median OS estimates were 25.1 months for participants without sarcopenic obesity, 18.6 months for participants with sarcopenic obesity, 23.6 months for participants without sarcopenia, and 27.9 months for participants with sarcopenia. This was the first study to systematically evaluate body composition parameters in a prospective multicenter trial of patients with resectable PDA who received perioperative chemotherapy. Visceral adipose tissue was associated with survival; however, there was no association between OS and sarcopenia or sarcopenic obesity. Further studies should evaluate these findings in more detail.

Qualitative and quantitative evaluation of computed tomography changes in adults with cystic fibrosis treated with elexacaftor-tezacaftor-ivacaftor: a retrospective observational study.

Introduction: The availability of highly effective triple cystic fibrosis transmembrane conductance regulator (CFTR) modulator combination therapy with elexacaftor-tezacaftor-ivacaftor (ETI) has improved pulmonary outcomes and quality of life of people with cystic fibrosis (pwCF). The aim of this study was to assess computed tomography (CT) changes under ETI visually with the Brody score and quantitatively with dedicated software, and to correlate CT measures with parameters of clinical response. Methods: Twenty two adult pwCF with two consecutive CT scans before and after ETI treatment initiation were retrospectively included. CT was assessed visually employing the Brody score and quantitatively by YACTA, a well-evaluated scientific software computing airway dimensions and lung parenchyma with wall percentage (WP), wall thickness (WT), lumen area (LA), bronchiectasis index (BI), lung volume and mean lung density (MLD) as parameters. Changes in CT metrics were evaluated and the visual and quantitative parameters were correlated with each other and with clinical changes in sweat chloride concentration, spirometry [percent predicted of forced expiratory volume in one second (ppFEV1)] and body mass index (BMI). Results: The mean (SD) Brody score improved with ETI [55 (12) vs. 38 (15); p < 0.001], incl. sub-scores for mucus plugging, peribronchial thickening, and parenchymal changes (all p < 0.001), but not for bronchiectasis (p = 0.281). Quantitatve WP (p < 0.001) and WT (p = 0.004) were reduced, conversely LA increased (p = 0.003), and BI improved (p = 0.012). Lung volume increased (p < 0.001), and MLD decreased (p < 0.001) through a reduction of ground glass opacity areas (p < 0.001). Changes of the Brody score correlated with those of quantitative parameters, exemplarily WT with the sub-score for mucus plugging (r = 0.730, p < 0.001) and peribronchial thickening (r = 0.552, p = 0.008). Changes of CT parameters correlated with those of clinical response parameters, in particular ppFEV1 with the Brody score (r = -0.606, p = 0.003) and with WT (r = -0.538, p = 0.010). Discussion: Morphological treatment response to ETI can be assessed using the Brody score as well as quantitative CT parameters. Changes in CT correlated with clinical improvements. The quantitative analysis with YACTA proved to be an objective, reproducible and simple method for monitoring lung disease, particularly with regard to future interventional clinical trials.

Weak to no correlation between quantitative high-resolution computed tomography metrics and lung function change in fibrotic diseases.

Identifying systemic sclerosis (SSc) and idiopathic pulmonary fibrosis (IPF) patients at risk of more rapid forced vital capacity (FVC) decline could improve trial design. The purpose of the present study was to explore the prognostic value of quantitative high-resolution computed tomography (HRCT) metrics derived by Imbio lung texture analysis (LTA) tool in predicting FVC slope. This retrospective study used data from patients who were not treated with investigational drugs with and without background antifibrotic therapies in tocilizumab phase 3 SSc, lebrikizumab phase 2 IPF, and zinpentraxin alfa phase 2 IPF studies conducted from 2015 to 2021. Controlled HRCT axial volumetric multidetector computed tomography scans were evaluated using the Imbio LTA tool. Associations between HRCT metrics and FVC slope were assessed through the Spearman correlation coefficient and adjusted R2 in a linear regression model adjusted by demographics and baseline clinical characteristics. A total of 271 SSc and IPF patients were analysed. Correlation coefficients of highest magnitude were observed in the SSc study between the extent of ground glass, normal volume, quantification of interstitial lung disease, reticular pattern, and FVC slope (-0.25, 0.28, -0.28, and -0.33, respectively), while the correlation coefficients observed in IPF studies were in general <0.2. The incremental prognostic value of the baseline HRCT metrics was marginal after adjusting baseline characteristics and was inconsistent across study arms. Data from the SSc and IPF studies suggested weak to no and inconsistent correlation between quantitative HRCT metrics derived by the Imbio LTA tool and FVC slope in the studied SSc and IPF population.

Quantitative CT Metrics Associated with Variability in the Diffusion Capacity of the Lung of Post-COVID-19 Patients with Minimal Residual Lung Lesions.

(1) Background: A reduction in the diffusion capacity of the lung for carbon monoxide is a prevalent longer-term consequence of COVID-19 infection. In patients who have zero or minimal residual radiological abnormalities in the lungs, it has been debated whether the cause was mainly due to a reduced alveolar volume or involved diffuse interstitial or vascular abnormalities. (2) Methods: We performed a cross-sectional study of 45 patients with either zero or minimal residual lesions in the lungs (total volume < 7 cc) at two months to one year post COVID-19 infection. There was considerable variability in the diffusion capacity of the lung for carbon monoxide, with 27% of the patients at less than 80% of the predicted reference. We investigated a set of independent variables that may affect the diffusion capacity of the lung, including demographic, pulmonary physiology and CT (computed tomography)-derived variables of vascular volume, parenchymal density and residual lesion volume. (3) Results: The leading three variables that contributed to the variability in the diffusion capacity of the lung for carbon monoxide were the alveolar volume, determined via pulmonary function tests, the blood vessel volume fraction, determined via CT, and the parenchymal radiodensity, also determined via CT. These factors explained 49% of the variance of the diffusion capacity, with p values of 0.031, 0.005 and 0.018, respectively, after adjusting for confounders. A multiple-regression model combining these three variables fit the measured values of the diffusion capacity, with R = 0.70 and p < 0.001. (4) Conclusions: The results are consistent with the notion that in some post-COVID-19 patients, after their pulmonary lesions resolve, diffuse changes in the vascular and parenchymal structures, in addition to a low alveolar volume, could be contributors to a lingering low diffusion capacity.

Artificial Intelligence in CT and MR Imaging for Oncological Applications.

Cancer care increasingly relies on imaging for patient management. The two most common cross-sectional imaging modalities in oncology are computed tomography (CT) and magnetic resonance imaging (MRI), which provide high-resolution anatomic and physiological imaging. Herewith is a summary of recent applications of rapidly advancing artificial intelligence (AI) in CT and MRI oncological imaging that addresses the benefits and challenges of the resultant opportunities with examples. Major challenges remain, such as how best to integrate AI developments into clinical radiology practice, the vigorous assessment of quantitative CT and MR imaging data accuracy, and reliability for clinical utility and research integrity in oncology. Such challenges necessitate an evaluation of the robustness of imaging biomarkers to be included in AI developments, a culture of data sharing, and the cooperation of knowledgeable academics with vendor scientists and companies operating in radiology and oncology fields. Herein, we will illustrate a few challenges and solutions of these efforts using novel methods for synthesizing different contrast modality images, auto-segmentation, and image reconstruction with examples from lung CT as well as abdome, pelvis, and head and neck MRI. The imaging community must embrace the need for quantitative CT and MRI metrics beyond lesion size measurement. AI methods for the extraction and longitudinal tracking of imaging metrics from registered lesions and understanding the tumor environment will be invaluable for interpreting disease status and treatment efficacy. This is an exciting time to work together to move the imaging field forward with narrow AI-specific tasks. New AI developments using CT and MRI datasets will be used to improve the personalized management of cancer patients.

Assessing Cast Aluminum Alloys with Computed Tomography Defect Metrics: A Gurson Porous Plasticity Approach

Aluminum alloys have inherent tendencies to produce casting defects caused by alloying or metal melt flow inside the mold. The traditional detection method for these defects includes reduced pressure tests, which assess metal quality in a destructive manner. This leaves a gap between metal quality assessments and tensile test correlations. Computed tomography (CT) scans offer crucial assistance in evaluating the internal quality of castings without damaging the structure. This provides a valuable opportunity to couple mechanical tests with numerical methods such as finite element analysis to predict the mechanical performance of the alloy. The present study aims to evaluate the internal quality of cast aluminum alloys using CT scans and to correlate the defect metrics obtained from CT scans with mechanical test results. The Gurson-type material model and finite element methodology have been used to validate the correlation studies. Therefore, we propose a more holistic approach to predicting the behavior of metals by coupling damage models with CT scans and mechanical tests. The study investigates several CT metrics such as the defect volume, total defect surface, biggest defect surface, and projected area of defects. The conclusion reveals that CT scans provide crucial assistance in evaluating the internal quality of castings, and CT defect metrics can be used to build correlations between mechanical tests and CT evaluations. The study also suggests that the concept of adjusted representative material yield parameter (ARMY) or computed representative material yield parameter (CRMY) can be used to correlate CT metrics with mechanical strength in cast materials and parts for a given aluminum alloy. Overall, the study proposes a more comprehensive methodology to assess the quality of cast aluminum alloys and couple the quality to mechanical performance.

Transverse Maxillary Deficiency Predicts Increased Upper Airway Collapsibility during Drug-Induced Sleep Endoscopy.

To examine the relationship between craniofacial skeletal anatomy and objective measures of pharyngeal collapse obtained during drug-induced sleep endoscopy. We hypothesized that transverse maxillary deficiency and an increased pharyngeal length will be associated with higher levels of pharyngeal collapsibility. Cross-sectional analysis in a prospective cohort. University Hospital. A cross-sectional analysis was conducted in a cohort of consecutive patients from the positive airway pressure(PAP) alternatives clinic who underwent computed tomography (CT) analysis and drug-induced sleep endoscopy for characterization of upper airway collapsibility. PAP titration was used to determine pharyngeal critical pressure (PCRIT ) and pharyngeal opening pressure (PhOP). CT metrics included: Transverse maxillary dimensions (interpremolar and intermolar distances) and pharyngeal length (posterior nasal spine to hyoid distance). The cohort (n = 103) of severe obstructive sleep apnea (Apnea and Hipopnea Index 32.1 ± 21.3 events/h) was predominantly male (71.8%), Caucasian (81.6%), middle-aged (54.4 ± 14.3 years), and obese (body mass index[BMI] = 30.0 ± 4.9 kg/m2 ). Reduced transverse maxillary dimensions were associated with higher PCRIT (intermolar distance: β [95% confidence interval, CI] = -.25 [-0.14, -0.36] cmH2 O/mm; p = .03) and PhOP (Interpremolar distance: β = -.25 [-0.14, -0.36] cmH2 O/mm; p = .02). Longer pharyngeal length was also associated with higher PCRIT (β = .11 [0.08, 0.14] cmH2 O/mm, p = .04) and PhOP (β [95% CI] = .06 [0.03, 0.09] cmH2 O/mm, p = .04). These associations persisted after adjustments for sex, age, height, and BMI. Our results further the concept that skeletal restriction in the transverse dimension and hyoid descent areassociated with elevations in pharyngeal collapsibility during sleep, suggesting a role of transverse deficiency in the pathogenesis of airway obstruction.

Diagnostic Value of Sarcopenia Computed Tomography Metrics for Older Patients with or without Cancers with Gastrointestinal Disorders.

The diagnostic utility of poor body composition measures in sarcopenia remains unclear. We hypothesize that the skeletal muscle gauge [combination of skeletal muscle index (SMI) and skeletal muscle density (SMD); SMG= SMI× SMD] would have significant diagnostic and predictive value in certain muscle regions and populations. Prospective cross-sectional study. We examined inpatients age ≥60years with or without cancer and with gastrointestinal disorders. We used computed tomography (CT) image metrics in the 12th thoracic (T12), third lumbar (L3), erector spinae muscle (ESM), and psoas muscle (PM) regions to establish correlations with the 2019 Asian Working Group for Sarcopenia Consensus and used receiver operating characteristic area under the curve (AUC) to compare differences between metrics. Associations between CT metrics and mortality were reported as relative risk after adjustments. We evaluated 385 patients (median age, 69.0years; 60.8% men) and found consistent trends in cancer (49.6%) and noncancer (50.4%) cohorts. SMG had a stronger correlation with muscle mass than SMD [mean rho: 0.68 (range, 0.59‒0.73) vs 0.39 (range, 0.28‒0.48); all P < .01] in T12, L3, and PM regions and a stronger correlation with muscle function than SMI [mean rho: 0.60 (range, 0.50‒0.77) vs 0.36 (range, 0.22‒0.58); all P < .05] in T12, ESM, and L3 regions. SMG outperformed SMI in diagnostic accuracy in all regions, particularly for L3 (AUC: 0.87‒0.88 vs 0.80‒0.82; both P < .05). PMG (PM gauge) and L3SMG did not differ, whereas EMG (ESM gauge) or T12SMG and L3SMG did (AUC: 0.80‒0.82 vs 0.87‒0.88; all P < .05). L3SMI, L3SMD, T12SMG, EMG, and PMG showed no association with 1-year cancer-related mortality after adjusting for confounders; however, L3SMG [relative risk= 0.92 (0.85‒0.99); P=.023) was. L3SMG covers all features of sarcopenia with more diagnostic value than other metrics, allowing a complete sarcopenia assessment with CT alone and not just in populations with cancer.

Association Between Pelvic Bone Computed Tomography-Derived Body Composition and Patient Outcomes in Older Adults With Proximal Femur Fracture.

To investigate the association between pelvic bone computed tomography (CT)-derived body composition and patient outcomes in older adult patients who underwent surgery for proximal femur fractures. We retrospectively identified consecutive patients aged ≥ 65 years who underwent pelvic bone CT and subsequent surgery for proximal femur fractures between July 2018 and September 2021. Eight CT metrics were calculated from the cross-sectional area and attenuation of the subcutaneous fat and muscle, including the thigh subcutaneous fat (TSF) index, TSF attenuation, thigh muscle (TM) index, TM attenuation, gluteus maximus (GM) index, GM attenuation, gluteus medius and minimus (Gmm) index, and Gmm attenuation. The patients were dichotomized using the median value of each metric. Multivariable Cox regression and logistic regression models were used to determine the association between CT metrics with overall survival (OS) and postsurgical intensive care unit (ICU) admission, respectively. A total of 372 patients (median age, 80.5 years; interquartile range, 76.0-85.0 years; 285 females) were included. TSF attenuation above the median (adjusted hazard ratio [HR], 2.39; 95% confidence interval [CI], 1.41-4.05), GM index below the median (adjusted HR, 2.63; 95% CI, 1.33-5.26), and Gmm index below the median (adjusted HR, 2.33; 95% CI, 1.12-4.55) were independently associated with shorter OS. TSF index (adjusted odds ratio [OR], 6.67; 95% CI, 3.13-14.29), GM index (adjusted OR, 3.45; 95% CI, 1.49-7.69), GM attenuation (adjusted OR, 2.33; 95% CI, 1.02-5.56), Gmm index (adjusted OR, 2.70; 95% CI, 1.22-5.88), and Gmm attenuation (adjusted OR, 2.22; 95% CI, 1.01-5.00) below the median were independently associated with ICU admission. In older adult patients who underwent surgery for proximal femur fracture, low muscle indices of the GM and gluteus medius/minimus obtained from their cross-sectional areas on preoperative pelvic bone CT were significant prognostic markers for predicting high mortality and postsurgical ICU admission.

Quantitative computed tomography predicts outcomes in idiopathic pulmonary fibrosis.

Prediction of disease course in patients with progressive pulmonary fibrosis remains challenging. The purpose of this study was to assess the prognostic value of lung fibrosis extent quantified at computed tomography (CT) using data-driven texture analysis (DTA) in a large cohort of well-characterized patients with idiopathic pulmonary fibrosis (IPF) enrolled in a national registry. This retrospective analysis included participants in the Australian IPF Registry with available CT between 2007 and 2016. CT scans were analysed using the DTA method to quantify the extent of lung fibrosis. Demographics, longitudinal pulmonary function and quantitative CT metrics were compared using descriptive statistics. Linear mixed models, and Cox analyses adjusted for age, gender, BMI, smoking history and treatment with anti-fibrotics were performed to assess the relationships between baseline DTA, pulmonary function metrics and outcomes. CT scans of 393 participants were analysed, 221 of which had available pulmonary function testing obtained within 90 days of CT. Linear mixed-effect modelling showed that baseline DTA score was significantly associated with annual rate of decline in forced vital capacity and diffusing capacity of carbon monoxide. In multivariable Cox proportional hazard models, greater extent of lung fibrosis was associated with poorer transplant-free survival (hazard ratio [HR] 1.20, p< 0.0001) and progression-free survival (HR 1.14, p< 0.0001). In a multi-centre observational registry of patients with IPF, the extent of fibrotic abnormality on baseline CT quantified using DTA is associated with outcomes independent of pulmonary function.

Impaired Ventilatory Efficiency, Dyspnea, and Exercise Intolerance in Chronic Obstructive Pulmonary Disease: Results from the CanCOLD Study.

Rationale: Impaired exercise ventilatory efficiency (high ventilatory requirements for CO2 [[Formula: see text]e/[Formula: see text]co2]) provides an indication of pulmonary gas exchange abnormalities in chronic obstructive pulmonary disease (COPD). Objectives: To determine 1) the association between high [Formula: see text]e/[Formula: see text]co2 and clinical outcomes (dyspnea and exercise capacity) and its relationship to lung function and structural radiographic abnormalities; and 2) its prevalence in a large population-based cohort. Methods: Participants were recruited randomly from the population and underwent clinical evaluation, pulmonary function, cardiopulmonary exercise testing, and chest computed tomography. Impaired exercise ventilatory efficiency was defined by a nadir [Formula: see text]e/[Formula: see text]co2 above the upper limit of normal (ULN), using population-based normative values. Measurements and Main Results: Participants included 445 never-smokers, 381 ever-smokers without airflow obstruction, 224 with Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1 COPD, and 200 with GOLD 2-4 COPD. Participants with [Formula: see text]e/[Formula: see text]co2 above the ULN were more likely to have activity-related dyspnea (Medical Research Council dyspnea scale ⩾ 2; odds ratio [5-95% confidence intervals], 1.77 [1.31 to 2.39]) and abnormally low peak [Formula: see text]o2 ([Formula: see text]o2peak below the lower limit of normal; odds ratio, 4.58 [3.06 to 6.86]). The Kco had a stronger correlation with nadir [Formula: see text]e/[Formula: see text]co2 (r = -0.38; P < 0.001) than other relevant lung function and computed tomography metrics. The prevalence of [Formula: see text]e/[Formula: see text]co2 above the ULN was 24% in COPD (similar in GOLD 1 and 2 through 4), which was greater than in never-smokers (13%) and ever-smokers (12%). Conclusions: [Formula: see text]e/[Formula: see text]co2 above the ULN was associated with greater dyspnea and low [Formula: see text]o2peak and was present in 24% of all participants with COPD, regardless of GOLD stage. The results show the importance of recognizing impaired exercise ventilatory efficiency as a potential contributor to dyspnea and exercise limitation, even in mild COPD.

Body composition measurements and overall survival in patients with resectable pancreatic adenocarcinoma receiving neoadjuvant chemotherapy: Analysis from SWOG S1505.

4131 Background: Sarcopenia and sarcopenic obesity have been associated with overall survival (OS) in patients (pts) with borderline resectable and advanced pancreatic ductal adenocarcinoma (PDA), but little is known about the effect of body composition on OS in pts with resectable PDA. We examined the relationship between skeletal muscle and adipose tissue measurements on baseline computed tomography (CT) and OS of pts with resectable PDA in a secondary analysis of SWOG S1505 (NCT02562716). Methods: SWOG S1505 enrolled pts with resectable PDA who were randomized to receive neoadjuvant FOLFIRINOX or gemcitabine-nab paclitaxel, followed by surgical resection. Baseline axial CT images at the L3 level were analyzed with externally validated software and measurements were recorded for skeletal muscle area (SMA), density (SMD) and index (SMI); visceral adipose tissue area (VATA) and density (VATD); and subcutaneous adipose tissue area (SATA) and density (SATD). Sarcopenia was defined as SMI &lt; 52 cm2/m2 for men and &lt; 39 cm2/m2 for women; sarcopenic obesity was defined as sarcopenia and a body mass index (BMI) &gt;30 kg/m2. The relationships between CT metrics and OS were analyzed using Cox regression models, with 95% CI. Statistical significance was defined as p &lt; 0.05. Results: Of 98 pts with available baseline abdominal CT, 8 were excluded for scan quality, resulting in 90 evaluable cases: 51 men (57%), 39 women (43%); mean age, 63.2 years, SD 8.5; mean BMI, 29.3 kg/m2, SD 6.4; 80 (89%) White, 6 (7%) Black, and 4 (4%) unknown. Sarcopenia was present in 32 (36%) and sarcopenic obesity in 10 (11%) patients. Univariable analyses for the variables of interest indicated VATA (HR 1.24; 0.97-1.60; p = 0.09) and SMD (HR 0.75; 0.57-0.98; p = 0.04) were associated with OS. Analyses adjusted for sex, race, age, BMI, performance score, contrast use, sarcopenia, and sarcopenic obesity showed VATA was associated with OS (HR 1.58; 1.0-2.51; p = 0.05). No significant difference in median OS was observed between pts with vs. without sarcopenia (OS 23.6 [19.3-NA] vs. 27.9 months [18.6-NA], respectively). Pts with vs. without sarcopenic obesity had lower median OS: 18.6 (14.7-NA) vs. 25.1 (10.5-46.0) months, respectively, but this difference was not statistically significant (HR 1.90, 95%CI 0.81-4.47, p = 0.14). Conclusions: This is one of the first studies to systematically evaluate body composition parameters in a prospective trial of patients with resectable PDA who received neoadjuvant chemotherapy. We found that visceral fat (VATA) is a prognostic marker in this population, but that sarcopenia may not be predictive in early PDA. Further studies to define the impact of longitudinal changes in body composition on individual outcomes may provide greater precision in predicting OS for subsets of pts with pancreatic cancer. Clinical trial information: NCT02562716.

Association of adipose tissue and skeletal muscle metrics with overall survival and postoperative complications in soft tissue sarcoma patients: an opportunistic study using computed tomography.

To determine the relationship between adipose tissue and skeletal muscle measurements on computed tomography (CT) and overall survival and major postoperative complications in patients with soft-tissue sarcoma (STS). The retrospective study included 137 STS patients (75 men, 62 women; mean age, 53 years, SD 17.7; mean BMI, 28.5, SD 6.6) who had abdominal CT exams. On a single CT image, at the L4 pedicle level, measurements of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and skeletal muscle area and attenuation were obtained using clinical PACS and specialized segmentation software. Clinical information was recorded, including STS characteristics (size, depth, grade, stage, and site), overall survival, and postoperative complications. The relationships between CT metrics and survival were analyzed using Cox proportional hazard models and those between CT metrics and postoperative complications using logistic regression models. There were 33 deaths and 41 major postoperative complications. Measured on clinical PACS, the psoas area (P=0.003), psoas index (P=0.006), psoas attenuation (P=0.011), and total muscle attenuation (P=0.023) were associated with overall survival. Using specialized software, psoas attenuation was also associated with overall survival (P=0.018). Adipose tissue metrics were not associated with survival or postoperative complications. In STS patients, CT-derived muscle size and attenuation are associated with overall survival. These prognostic biomarkers can be obtained using specialized segmentation software or routine clinical PACS.

CT based quantitative measures of the stability of fractured metastatically involved vertebrae treated with spine stereotactic body radiotherapy.

Mechanical instability secondary to vertebral metastases can lead to pathologic vertebral compression fracture (VCF) mechanical pain, neurological compromise, and the need for surgical stabilization. Stereotactic body radiation therapy (SBRT) as a treatment for spinal metastases is effective for pain and local tumor control, it has been associated with an increased risk of VCF. This study quantified computed tomography (CT) based stability measures in metastatic vertebrae with VCF treated with spine SBRT. It was hypothesized that semi-automated quantification of VCF based on CT metrics would be related to clinical outcomes. 128 SBRT treated spinal metastases patients were identified from a prospective database. Of these, 18 vertebral segments were identified with a VCF post-SBRT. A semi-automated system for quantifying VCF was developed based on CT imaging before and after SBRT. The system identified and segmented SBRT treated vertebral bodies, calculated stability metrics at single time points and changes over time. In the vertebrae that developed a new (n = 7) or progressive (n = 11) VCF following SBRT, the median time to VCF/VCF progression was 1.74months (range 0.53-7.79months). Fractured thoracolumbar vertebrae that went on to be stabilized (cemented and/or instrumented), had greater fractured vertebral body volume progression over time (12%) compared to those not stabilized (0.4%, p < 0.05). Neither the spinal instability neoplastic score (SINS) or any single timepoint stability metrics in post-hoc analyses correlated with future stabilization. This pilot study presents a quantitative semi-automated method assessing fractured thoracolumbar vertebrae based on CT. Increased fractured vertebral body volume progression post-SBRT was shown to predict those patients who were subsequently stabilized, motivating study of methods that assess temporal radiological changes toward augmenting existing clinical management in the metastatic spine.

Assessment of Orbital Computed Tomography (CT) Imaging Biomarkers in Patients with Thyroid Eye Disease.

To understand potential orbital biomarkers generated from computed tomography (CT) imaging in patients with thyroid eye disease. This is a retrospective cohort study. From a database of an ongoing thyroid eye disease research study at our institution, we identified 85 subjects who had both clinical examination and laboratory records supporting the diagnosis of thyroid eye disease and concurrent imaging prior to any medical or surgical intervention. Patients were excluded if imaging quality or type was not amenable to segmentation. The images of 170 orbits were analyzed with the developed automated segmentation tool. The main outcome measure was to cross 25 CT structural metrics for each eye with nine clinical markers using a Kendall rank correlation test to identify significant relationships. The Kendall rank correlation test between automatically calculated CT metrics and clinical data demonstrated numerous correlations. Extraocular rectus muscle metrics, such as the average diameter of the superior, medial, and lateral rectus muscles, showed a strong correlation (p < 0.05) with loss of visual acuity and presence of ocular motility defects. Hertel measurements demonstrated a strong correlation (p < 0.05) with volumetric measurements of the optic nerve and other orbital metrics such as the crowding index and proptosis. Optic neuropathy was strongly correlated (p < 0.05) with an increase in the maximum diameter of the superior muscle. This novel method of automated imaging metrics may provide objective, rapid clinical information. This data may be useful for appreciation of severity of thyroid eye disease and recognition of risk factors of visual impairment from dysthyroid optic neuropathy from CT imaging.

Spirometric assessment of emphysema presence and severity as measured by quantitative CT and CT-based radiomics in COPD

BackgroundThe mechanisms underlying airflow obstruction in COPD cannot be distinguished by standard spirometry. We ascertain whether mathematical modeling of airway biomechanical properties, as assessed from spirometry, could provide estimates of emphysema presence and severity, as quantified by computed tomography (CT) metrics and CT-based radiomics.MethodsWe quantified presence and severity of emphysema by standard CT metrics (VIDA) and co-registration analysis (ImbioLDA) of inspiratory-expiratory CT in 194 COPD patients who underwent pulmonary function testing. According to percentages of low attenuation area below − 950 Hounsfield Units (%LAA-950insp) patients were classified as having no emphysema (NE) with %LAA-950insp < 6, moderate emphysema (ME) with %LAA-950insp ≥ 6 and < 14, and severe emphysema (SE) with %LAA-950insp ≥ 14. We also obtained stratified clusters of emphysema CT features by an automated unsupervised radiomics approach (CALIPER). An emphysema severity index (ESI), derived from mathematical modeling of the maximum expiratory flow-volume curve descending limb, was compared with pulmonary function data and the three CT classifications of emphysema presence and severity as derived from CT metrics and radiomics.ResultsESI mean values and pulmonary function data differed significantly in the subgroups with different emphysema degree classified by VIDA, ImbioLDA and CALIPER (p < 0.001 by ANOVA). ESI differentiated NE from ME/SE CT-classified patients (sensitivity 0.80, specificity 0.85, AUC 0.86) and SE from ME CT-classified patients (sensitivity 0.82, specificity 0.87, AUC 0.88).ConclusionsPresence and severity of emphysema in patients with COPD, as quantified by CT metrics and radiomics can be estimated by mathematical modeling of airway function as derived from standard spirometry.

Association of low income with pulmonary disease progression in smokers with and without chronic obstructive pulmonary disease.

Low socioeconomic status has been associated with chronic obstructive pulmonary disease (COPD) but little is known about its impact on disease progression. We assessed the association of income to symptoms, pulmonary disease severity and progression in smokers with and without COPD.The COPDGene cohort of 4826 smokers who reported annual income in phase 2 was analysed. Those who reported annual income <USD 15 000 per year were “low-income” and the remainder “higher income”. Baseline demographics, symptoms, computed tomography (CT) imaging, and 5-year change in spirometry and CT metrics were characterised by group.The low income group was younger (55.7 versus 61.7, p<0.0001), had more current smokers (73% versus 36%, p<0.0001), higher rates of severe exacerbations (13% versus 7%, p<0.0001), more chronic bronchitis (22% versus 14%, p<0.0001), reduced access to preventative care and lower quality of life, but less emphysema (4.7% versus 6.2%, p<0.0001). After 5 years the low-income group had more smoking-related disease progression, without significant change in exacerbations or symptoms, than higher-income subjects. Low income was an independent predictor of decreasing forced expiratory volume in 1 s (FEV1) (p=0.001) and increased airway disease (p=0.007) after adjusting for baseline FEV1, age, sex, race, exposures and current smoking.Income disparity beyond the effects of race and current smoking is an important factor for disease progression. Worldwide, poverty and its consequences: associated respiratory exposures, limited healthcare access, and inadequate education about smoking risks, may exacerbate chronic lung disease.

Advanced quantitative methods in correlating sarcopenic muscle degeneration with lower extremity function biometrics and comorbidities.

Sarcopenic muscular degeneration has been consistently identified as an independent risk factor for mortality in aging populations. Recent investigations have realized the quantitative potential of computed tomography (CT) image analysis to describe skeletal muscle volume and composition; however, the optimum approach to assessing these data remains debated. Current literature reports average Hounsfield unit (HU) values and/or segmented soft tissue cross-sectional areas to investigate muscle quality. However, standardized methods for CT analyses and their utility as a comorbidity index remain undefined, and no existing studies compare these methods to the assessment of entire radiodensitometric distributions. The primary aim of this study was to present a comparison of nonlinear trimodal regression analysis (NTRA) parameters of entire radiodensitometric muscle distributions against extant CT metrics and their correlation with lower extremity function (LEF) biometrics (normal/fast gait speed, timed up-and-go, and isometric leg strength) and biochemical and nutritional parameters, such as total solubilized cholesterol (SCHOL) and body mass index (BMI). Data were obtained from 3,162 subjects, aged 66–96 years, from the population-based AGES-Reykjavik Study. 1-D k-means clustering was employed to discretize each biometric and comorbidity dataset into twelve subpopulations, in accordance with Sturges’ Formula for Class Selection. Dataset linear regressions were performed against eleven NTRA distribution parameters and standard CT analyses (fat/muscle cross-sectional area and average HU value). Parameters from NTRA and CT standards were analogously assembled by age and sex. Analysis of specific NTRA parameters with standard CT results showed linear correlation coefficients greater than 0.85, but multiple regression analysis of correlative NTRA parameters yielded a correlation coefficient of 0.99 (P<0.005). These results highlight the specificities of each muscle quality metric to LEF biometrics, SCHOL, and BMI, and particularly highlight the value of the connective tissue regime in this regard.

Quantitative Computed Tomography Metrics From the Transplanted Lung can Predict Forced Expiratory Volume in the First Second After Lung Transplantation.

Bronchiolitis obliterans syndrome after lung transplantation (LTx) manifests as a sustained decline in forced expiratory volume in the first second (FEV1). Quantitative computed tomography (QCT) metrics may predict FEV1 better than semiquantitative scores (SQSs), and the transplanted lung may provide better information than the native lung in unilateral LTx. Paired inspiratory-expiratory CT scans and pulmonary function testing of 178 LTx patients were analyzed retrospectively. SQS were graded (absent, mild, moderate, severe) for features including mosaic attenuation and bronchiectasis. QCT included lung volumes and air-trapping volumes, by lobe. Multivariate Pearson correlation and multivariate linear least squares regression analyses were performed. Multivariate linear least squares regression models using FEV1 as the outcome variable and SQS or QCT metrics as predictor variables demonstrated SQS to be a weak predictor of FEV1 (adjusted R, 0.114). QCT metrics were much stronger predictors of FEV1 (adjusted R, 0.654). QCT metrics demonstrated stronger correlation (r) with FEV1 than SQS. In bilateral LTx, whole lung volume difference (r=0.69), left lung volume difference (r=0.69), and right lung volume difference (r=0.65) were better than the sum of SQS (r=-0.54). Interestingly, in left LTx we obtained r=0.81, 0.86, 0.25, and -0.39, respectively. In right LTx, we obtained r=0.69, 0.49, 0.68, and -0.31, respectively. QCT metrics demonstrate stronger correlations with FEV1 and are better predictors of pulmonary function than SQS. SQS performs moderately well in bilateral LTx, but poorly on unilateral LTx. In unilateral LTx, QCT metrics from the transplanted lung are better predictors of FEV1 than QCT metrics from the nontransplanted lung.

Recent Advances in Computed Tomography Imaging in Chronic Obstructive Pulmonary Disease.

Lung imaging is increasingly being used to diagnose, quantify, and phenotype chronic obstructive pulmonary disease (COPD). Although spirometry is the gold standard for the diagnosis of COPD and for severity staging, the role of computed tomography (CT) imaging has expanded in both clinical practice and research. COPD is a heterogeneous disease with considerable variability in clinical features, radiographic disease, progression, and outcomes. Recent studies have examined the utility of CT imaging in enhancing diagnostic certainty, improving phenotyping, predicting disease progression and prognostication, selecting patients for intervention, and also in furthering our understanding of the complex pathophysiology of this disease. Multiple CT metrics show promise for use as imaging biomarkers in COPD.