Quantitative Computed Tomography Measurements Research Articles

Bone density measurement in patients with spinal metastatic tumors using chest quantitative CT deep learning model

ObjectiveThis study aims to develop a deep learning model using the 3DResUNet architecture to predict vertebral volumetric bone mineral density (vBMD) from Quantitative Computed Tomography (QCT) scans in patients with spinal metastatic tumors, enhancing osteoporosis screening capabilities. Methods749 patients with spinal metastatic tumors underwent QCT vertebral vBMD measurements. The dataset was randomly split into training (599 cases) and test sets (150 cases). The 3DResUNet model was trained for vBMD classification and prediction using QCT images processed with automated bone segmentation and ROI extraction. ResultsThe deep learning model demonstrated strong performance with Spearman correlation coefficients of 0.923 (training set) and 0.918 (test set) between predicted and QCT-measured vBMD values. Bland-Altman analysis showed a slight bias of −1.42 mg/cm3 (training set) and −1.14 mg/cm3 (test set) between the model predictions and QCT measurements. The model achieved an area under the curve (AUC) of 0.977 (training set) and 0.966 (test set) for diagnosing Osteoporosis based on vBMD. ConclusionThe developed deep learning model using 3DResUNet effectively predicts vertebral vBMD from QCT scans in patients with spinal metastatic tumors. It provides accurate and automated vBMD measurements, potentially facilitating widespread osteoporosis screening in clinical practice, mainly where DXA availability is limited.

Artificial intelligence-assisted quantitative CT parameters in predicting the degree of risk of solitary pulmonary nodules

Introduction Artificial intelligence (AI) shows promise for evaluating solitary pulmonary nodules (SPNs) on computed tomography (CT). Accurately determining cancer invasiveness can guide treatment. We aimed to investigate quantitative CT parameters for invasiveness prediction. Methods Patients with stage 0–IB NSCLC after surgical resection were retrospectively analysed. Preoperative CTs were evaluated with specialized software for nodule segmentation and CT quantification. Pathology was the reference for invasiveness. Univariate and multivariate logistic regression assessed predictors of high-risk SPN. Results Three hundred and fifty-five SPN were included. On multivariate analysis, CT value mean and nodule type (ground glass opacity vs. solid) were independent predictors of high-risk SPN. The area under the curve (AUC) was 0.811 for identifying high-risk nodules. Conclusions Quantitative CT measures and nodule type correlated with invasiveness. Software-based CT assessment shows potential for noninvasive prediction to guide extent of resection. Further prospective validation is needed, including comparison with benign nodules.

MRI-based pedicle bone quality score: correlation to quantitative computed tomography bone mineral density and its role in quantitative assessment of osteoporosis

BACKGROUND CONTEXTBone quality in the pedicle region generally determines screw pullout strength, insertion torque, and vertebral body loading characteristics. Dual-energy X-ray absorptiometry (DEXA), as the gold standard for evaluating bone mineral density (BMD), cannot measure the BMD of specific parts, such as pedicle, and DEXA is limited in many ways. Recent studies have shown a correlation between the magnetic resonance imaging (MRI)-based vertebral bone quality (VBQ) score and BMD measured using DEXA or quantitative computed tomography (QCT). However, no studies have been reported on the MRI-based pedicle bone quality (PBQ) score. Moreover, few studies have investigated the relationship between MRI-based PBQ and osteoporosis. PURPOSETo create a new site-specific MRI-based PBQ assessment method and assess its diagnostic capacity in patients with normal BMD and osteopenia/osteoporosis. STUDY DESIGN/SETTINGA retrospective study. PATIENT SAMPLEA total of 156 patients underwent lumbar fusion surgery for chronic low back pain at our hospital between 2021 and 2022, with lumbar QCT and T1-weighted MRI performed before surgery. OUTCOME MEASURESCorrelation of the PBQ score with QCT BMD, and the association between the PBQ score and presence of osteopenia/osteoporosis. METHODSBMD of the lumbar was calculated as the mean BMD of the L1 and L2 vertebral bodies on the basis of asynchronous QCT measurements. The PBQ score, which is the average of the bone quality values of both pedicles on the basis of site-specific T1-weighted sagittal MRI images, was calculated by dividing the median signal intensity of the L1–L4 pedicles by the signal intensity of the cerebrospinal fluid at the L3 level. The interobserver reliability of the PBQ score was assessed using the intraclass correlation coefficient (ICC). A receiver operating characteristic curve was drawn, and the area under the curve (AUC) was calculated to assess the predictive performance of PBQ for osteoporosis. The PBQ score was compared with QCT BMD, as the gold standard, using Pearson correlation analysis. RESULTSIn total, 156 patients participated in this study, including 51 in the Normal BMD group and 105 in the osteopenia/osteoporosis group. The PBQ score in the osteopenia/osteoporosis group was significantly higher than that in the normal BMD group (3.19±0.55 vs. 2.84±0.51, p<.001). The VBQ and PBQ scores were calculated by 2 authors and were in good agreement (intraclass correlation coefficient=0.949 and 0.929, respectively). Pearson's test showed a significant negative correlation between PBQ and QCT BMD (r=−0.4887, p<.001). The optimal cutoff PBQ score to differentiate patients with osteopenia/osteoporosis from those with normal BMD was 3.160, with a sensitivity of 66.7%, specificity of 72.5%, and AUC of 0.776. The PBQ score correlated more strongly with QCT BMD (r=−0.4887) than VBQ (r=−0.4078). CONCLUSIONSIn this study, we propose a novel, MRI-based pedicle-specific bone quality score. This is the first study to investigate the relationship between the PBQ score and QCT BMD. The PBQ score showed diagnostic utility, differentiating between patients with osteopenia/osteoporosis and those with normal BMD (AUC=0.776), and the PBQ score correlated more strongly with QCT BMD than VBQ.

Determination of pulmonary vessel alteration in Chinese male smokers by quantitative computed tomography measurements: a retrospective study.

The blood volume of intraparenchymal vessels is reported to be increased in smokers. However, the blood volume can be affected by many confounders besides tobacco exposure. This study aimed to investigate the association between cigarette smoking and pulmonary blood volume after adjusting the related factors in a large cohort of Chinese males. In this retrospective study, male participants admitted to the First Affiliated Hospital of Xi'an Jiaotong University for annual health assessment between February 2017 and February 2018 were enrolled. All subjects underwent non-contrast chest computed tomography (CT) scans, and 152 subjects underwent a review CT scan 2-3 years later. A three-dimensional approach was employed to segment the lung and intrapulmonary vessels and quantitative CT (QCT) measurements, including lung volume (LV), intrapulmonary vessel volume (IPVV), low-attenuation area <-950 Hounsfield unit (LAA-950 and LAA-950%), and mean lung density (MLD). Linear regression was used to estimate the association between IPVV and the smoking index (SI). A paired t-test was used to compare the QCT parameters between the initial and follow-up CT scans. A total of 656 male participants were enrolled and classified into three subgroups: non-smokers (n=311), current smokers (n=267), and former smokers (n=78). The IPVV of current smokers (134.62±23.96 vs. 120.76±25.52 mL) and former smokers (130.79±25.13 vs. 120.76±25.52 mL) were significantly larger than that of non-smokers (P<0.05). A higher SI was associated with greater IPVV [non-standardized coefficient: 0.167, 95% confidence interval (CI): 0.086-0.248]. For current smokers, the IPVV of the follow-up scan significantly increased compared to its baseline scan (135.49±28.60 vs. 129.73±29.75 mL, t=-2.326, P=0.02), but for the non-smokers and former smokers, the IPVV of the follow-up scan did not increase or decrease compared to the baseline scan (P>0.05). Pulmonary vascular volumes detectable on non-contrast CT are associated with cigarette exposure, and smoking cessation may prevent pulmonary vasculature remodeling.

Fracture risk based on high-resolution peripheral quantitative computed tomography measures does not vary with age in older adults-the bone microarchitecture international consortium prospective cohort study.

Fracture risk increases with lower areal bone mineral density (aBMD); however, aBMD-related estimate of risk may decrease with age. This may depend on technical limitations of 2-dimensional (2D) dual energy X-ray absorptiometry (DXA) which are reduced with 3D high-resolution peripheral quantitative computed tomography (HR-pQCT). Our aim was to examine whether the predictive utility of HR-pQCT measures with fracture varies with age. We analyzed associations of HR-pQCT measures at the distal radius and distal tibia with two outcomes: incident fractures and major osteoporotic fractures. We censored follow-up time at first fracture, death, last contact or 8years after baseline. We estimated hazard ratios (HR) and 95%CI for the association between bone traits and fracture incidence across age quintiles. Among 6835 men and women (ages 40-96) with at least one valid baseline HR-pQCT scan who were followed prospectively for a median of 48.3months, 681 sustained fractures. After adjustment for confounders, bone parameters at both the radius and tibia were associated with higher fracture risk. The estimated HRs for fracture did not vary significantly across age quintiles for any HR-pQCT parameter measured at either the radius or tibia. In this large cohort, the homogeneity of the associations between the HR-pQCT measures and fracture risk across age groups persisted for all fractures and for major osteoporotic fractures. The patterns were similar regardless of the HR-pQCT measure, the type of fracture, or the statistical models. The stability of the associations between HR-pQCT measures and fracture over a broad age range shows that bone deficits or low volumetric density remain major determinants of fracture risk regardless of age group. The lower risk for fractures across measures of aBMD in older adults in other studies may be related to factors which interfere with DXA but not with HR-pQCT measures.

Assessment of whole-body and regional body fat using abdominal quantitative computed tomography in Chinese women and men

BackgroundBeing overweight or obese has become a serious public health concern, and accurate assessment of body composition is particularly important. More precise indicators of body fat composition include visceral adipose tissue (VAT) mass and total body fat percentage (TBF%). Study objectives included examining the relationships between abdominal fat mass, measured by quantitative computed tomography (QCT), and the whole-body and regional fat masses, measured by dual energy X-ray absorptiometry (DXA), as well as to derive equations for the prediction of TBF% using data obtained from multiple QCT slices.MethodsWhole-body and regional fat percentage were quantified using DXA in Chinese males (n = 68) and females (n = 71) between the ages of 24 and 88. All the participants also underwent abdominal QCT measurement, and their VAT mass and visceral fat volume (VFV) were assessed using QCT and DXA, respectively.ResultsDXA-derived TBF% closely correlated with QCT abdominal fat percentage (r = 0.89–0.93 in men and 0.76–0.88 in women). Stepwise regression showed that single-slice QCT data were the best predictors of DXA-derived TBF%, DXA android fat percentage and DXA gynoid fat percentage. Cross-validation analysis showed that TBF% and android fat percentage could be accurately predicted using QCT data in both sexes. There were close correlations between QCT-derived and DXA-derived VFV (r = 0.97 in men and 0.93 in women).ConclusionClinicians can assess the TBF% and android and gynoid fat percentages of Chinese women and men by analysing existing abdominal CT-derived data using the QCT technique.

Early Diagnosis of High-Risk Chronic Obstructive Pulmonary Disease Based on Quantitative High-Resolution Computed Tomography Measurements.

Quantitative computed tomography (QCT) techniques, focusing on airway anatomy and emphysema, may help to detect early structural changes of COPD disease. This retrospective study aims to identify high-risk COPD participants by using QCT measurements. We enrolled 140 participants from the Second Affiliated Hospital of Shenyang Medical College who completed inspiratory high-resolution CT scans, pulmonary function tests (PFTs), and clinical characteristics recorded. They were diagnosed Non-COPD by PFT value of FEV1/FVC >70% and divided into two groups according percentage predicted FEV1 (FEV1%), low-risk COPD group: FEV1% ≥ 95%, high-risk group: 80% < FEV1% < 95%. The QCT measurements were analyzed by the Student's t-test (or Mann-Whitney U-test) method. Then, feature candidates were identified using the LASSO method. Meanwhile, the correlation between QCT measurements and PFTs was assessed by the Spearman rank correlation test. Furthermore, support vector machine (SVM) was performed to identify high-risk COPD participants. The performance of the models was evaluated in terms of accuracy (ACC), sensitivity (SEN), specificity (SPE), F1-score, and area under the ROC curve (AUC), with p <0.05 considered statistically significant. The SVM based on QCT measurements achieved good performance in identifying high-risk COPD patients with 85.71% of ACC, 88.34% of SEN, 84.00% of SPE, 83.33% of F1-score, and 0.93 of AUC. Further, QCT measurements integration of clinical data improved the performance with an ACC of 90.48%. The emphysema index (%LAA-950) of left lower lung was negatively correlated with PFTs (P < 0.001). The airway anatomy indexes of lumen diameter (LD) were correlated with PFTs. QCT measurements combined with clinical information could provide an effective tool for an early diagnosis of high-risk COPD. The QCT indexes can be used to assess the pulmonary function status of high-risk COPD.

Cluster Analysis of World Trade Center Related Lower Airway Diseases.

Introduction: Cluster analysis can classify without a priori assumptions the heterogeneous chronic lower airway diseases found in former workers at the World Trade Center (WTC) disaster site. Methods: We selected the first available chest computed tomography scan with quantitative computed tomography measurements on 311 former WTC workers with complete clinical, and spirometric data from their closest surveillance visit. We performed a nonhierarchical iterative algorithm K-prototype cluster analysis, using gap measure. Results: A five-cluster solution was most satisfactory. Cluster 5 had the healthiest individuals. In cluster 4, smoking was most prevalent and intense but there was scant evidence of respiratory disease. Cluster 3 had symptomatic subjects with reduced forced vital capacity impairment (low FVC). Clusters 1 and 2 had less dyspneic subjects, but more functional and quantitative computed tomography evidence of chronic obstructive pulmonary disease (COPD) in cluster 1, or low FVC in cluster 2. Clusters 1 and 4 had the highest proportion of rapid first-second forced expiratory volume decliners. Conclusions: Cluster analysis confirms low FVC and COPD/pre-COPD as distinctive chronic lower airway disease phenotypes on long-term surveillance of the WTC workers.

Plasma metabolomics and quantitative interstitial abnormalities in ever-smokers

BackgroundQuantitative interstitial abnormalities (QIA) are an automated computed tomography (CT) finding of early parenchymal lung disease, associated with worse lung function, reduced exercise capacity, increased respiratory symptoms, and death. The metabolomic perturbations associated with QIA are not well known. We sought to identify plasma metabolites associated with QIA in smokers. We also sought to identify shared and differentiating metabolomics features between QIA and emphysema, another smoking-related advanced radiographic abnormality.MethodsIn 928 former and current smokers in the Genetic Epidemiology of COPD cohort, we measured QIA and emphysema using an automated local density histogram method and generated metabolite profiles from plasma samples using liquid chromatography–mass spectrometry (Metabolon). We assessed the associations between metabolite levels and QIA using multivariable linear regression models adjusted for age, sex, body mass index, smoking status, pack-years, and inhaled corticosteroid use, at a Benjamini–Hochberg False Discovery Rate p-value of ≤ 0.05. Using multinomial regression models adjusted for these covariates, we assessed the associations between metabolite levels and the following CT phenotypes: QIA-predominant, emphysema-predominant, combined-predominant, and neither- predominant. Pathway enrichment analyses were performed using MetaboAnalyst.ResultsWe found 85 metabolites significantly associated with QIA, with overrepresentation of the nicotinate and nicotinamide, histidine, starch and sucrose, pyrimidine, phosphatidylcholine, lysophospholipid, and sphingomyelin pathways. These included metabolites involved in inflammation and immune response, extracellular matrix remodeling, surfactant, and muscle cachexia. There were 75 metabolites significantly different between QIA-predominant and emphysema-predominant phenotypes, with overrepresentation of the phosphatidylethanolamine, nicotinate and nicotinamide, aminoacyl-tRNA, arginine, proline, alanine, aspartate, and glutamate pathways.ConclusionsMetabolomic correlates may lend insight to the biologic perturbations and pathways that underlie clinically meaningful quantitative CT measurements like QIA in smokers.

Short-term Precision Of High-resolution Peripheral Quantitative Computed Tomography Measures Of The Second Metatarsal Diaphysis

Short-term Precision Of High-resolution Peripheral Quantitative Computed Tomography Measures Of The Second Metatarsal Diaphysis

Repeatability of Pulmonary Quantitative Computed Tomography Measurements in Chronic Obstructive Pulmonary Disease.

Repeatability of Pulmonary Quantitative Computed Tomography Measurements in Chronic Obstructive Pulmonary Disease.

Quantifying emphysema in lung screening computed tomography with robust automated lobe segmentation.

Anatomy-based quantification of emphysema in a lung screening cohort has the potential to improve lung cancer risk stratification and risk communication. Segmenting lung lobes is an essential step in this analysis, but leading lobe segmentation algorithms have not been validated for lung screening computed tomography (CT). In this work, we develop an automated approach to lobar emphysema quantification and study its association with lung cancer incidence. We combine self-supervised training with level set regularization and finetuning with radiologist annotations on three datasets to develop a lobe segmentation algorithm that is robust for lung screening CT. Using this algorithm, we extract quantitative CT measures for a cohort () from the National Lung Screening Trial and analyze the multivariate association with lung cancer incidence. Our lobe segmentation approach achieved an external validation Dice of 0.93, significantly outperforming a leading algorithm at 0.90 (). The percentage of low attenuation volume in the right upper lobe was associated with increased lung cancer incidence (odds ratio: 1.97; 95% CI: [1.06, 3.66]) independent of risk factors and diagnosis of whole lung emphysema. Quantitative lobar emphysema improved the goodness-of-fit to lung cancer incidence (, ). We are the first to develop and validate an automated lobe segmentation algorithm that is robust to smoking-related pathology. We discover a quantitative risk factor, lending further evidence that regional emphysema is independently associated with increased lung cancer incidence. The algorithm is provided at https://github.com/MASILab/EmphysemaSeg.

Abdominal aortic calcification assessed on standard lateral lumbar radiographs as a screening tool for impaired bone status in spine surgery.

The aim of this study was to determine whether the presence of abdominal aortic calcification (AAC) can predict patient bone status, represented by volumetric bone mineral density (vBMD) assessed with quantitative computed tomography (QCT). Patients undergoing lumbar fusion surgery at a tertiary care center between 2014 and 2021, with a preoperative lumbar CT-scan and lateral lumbar radiographs were retrospectively reviewed. A semi-quantitative measurement method for AAC (AAC 4, 8 and 24) was performed. QCT measurements were made for L1 and L2. Patients were divided into two groups depending on whether AAC was present. A one-way analysis of covariance was conducted to adjust for age. A multiple linear regression model was used to test if age, sex, BMI, diabetes, hypertension, smoking and presence of AAC could predict the vBMD. A receiver operating characteristic (ROC) analysis was conducted for predicting impaired bone status. 267 patients with a median age of 65.1years and BMI of 29.8kg/m2 were analyzed, 59.6% of patients had AAC. The group comparison showed that vBMD was significantly lower in patients with the presence of AAC (97.8mg/cm3 vs. 121.5mg/cm3). Age (β = - 0.360; p < 0.001) and presence of AAC (β = -0.206; p = 0.005) significantly predict vBMD as independent variables. Impaired bone status could be discriminated using AAC 4, 8 and 24 (cut off value 0.5) with a sensitivity of 70.1% and a specificity of 60.2%. The presence of AAC may identify patients at risk for impaired bone status. Preoperative evaluation of standard lumbar radiographs could be used as a potential diagnostic tool in assessing bone status.

Age-related changes in lumbar bone mineral density measured using quantitative computed tomography in healthy female cynomolgus monkeys.

Cynomolgus monkeys are widely used in studies related to osteoporosis, and there is no evidence of age-related changes in volumetric bone mineral density (vBMD) measured using quantitative computed tomography (QCT) in nonhuman primates. This study aimed to describe changes in the characteristics of lumbar vBMD with age, to analyze the relationship between lumbar vBMD and body composition, and to investigate the precision of QCT measurements in healthy female cynomolgus monkeys. Age-related changes in lumbar vBMD were described using cubic regression models, and the accumulated bone loss rates (ABLR) of the lumbar spine were calculated. Spearman rank correlation and ridge regression analysis were used to investigate the relationship of the average lumbar vBMD and body components. Thirty animals were selected to analyze the short-term in vivo precision of the QCT measurements. The precision was expressed as the root-mean-square coefficient of variation (RMS-CV%) or root-mean-square standard deviation (RMS-SD). A total of 72 healthy female cynomolgus monkeys, aged 1-25 years, were included in this study. The average lumbar vBMD of female cynomolgus monkeys increased with age until the age of 10 years, around which it reached peak bone mass, with a relatively marked decline after the age of 13 years. The ABLRs of female cynomolgus monkeys in the premenopausal (13-19 years) and postmenopausal age groups (20-25 years) were -4.9% and -21.2%, respectively. Ridge regression analysis showed that age and subcutaneous adipose tissue (SAT) contributed positively to the average lumbar vBMD in animals aged ≤10 years, whereas in animals aged >10 years, age contributed negatively to lumbar vBMD. The RMS-CV% (RMS-SD) of the lumbar vBMD measured using QCT ranged from 0.47% to 1.60% (1.91-6.31 mg/cm3). Age-related changes in lumbar vBMD measured using QCT in healthy female monkeys showed similar trends to those in humans. Age and SAT may affect the lumbar vBMD in female cynomolgus monkeys. QCT revealed good precision in measuring the lumbar vBMD in female cynomolgus monkeys.

Causes, Diagnose and Treatment of Osteoporosis

Osteoporosis is a chronic degenerative bone disease that seriously affects human health. This study analyzes the causes of osteoporosis in detail, expounds the common diagnostic methods, and proposes some corresponding treatment programs. Dual Energy X-ray Absorptiometry has high accuracy, image quality improvement, fast speed, rich clinical applications, and is suitable for scientific research. Quantitative Computed tomography measures true volumetric bone mineral density using initial CT data. This method is not affected by obesity, hyperosteoplasia, vascular calcification and vertebral size. Osteoporosis has the primary and secondary causes, primary osteoporosis covers the osteoporosis when women go through menopause (Type I), and osteoporosis of senile (Type II), and secondary osteoporosis refers to osteoporosis caused by certain medical conditions or medications. Exercise can help patients treat osteoporosis, and drugs could help prevent falls help prevent fractures. However, the treatment effect of most osteoporosis patients is not satisfactory. To treat osteoporosis, only one drug "single-handedly" has limited efficacy, and to effectively combat osteoporosis, it is necessary to emphasize "multi-service combat".

CT-measured hernia parameters can predict component separation: a cross-sectional study from China.

Currently, there are no reliable preoperative methods for predicting component separation (CS) during incisional hernia repair. By quantitatively measuring preoperative computed tomography (CT) imaging, we aimed to assess the value of hernia defect size, abdominal wall muscle quality, and hernia volume in predicting CS. The data of 102 patients who underwent open Rives-Stoppa retro-muscular mesh repair for midline incisional hernia between January 2019 and March 2022 were retrospectively analyzed. The patients were divided into two groups: ''CS group'' patients who required CS to attempt fascial closure, and ''non-CS'' group patients who required only Rives-Stoppa retro-muscular release to achieve fascial closure. Hernia defect width, hernia defect angle, rectus width, abdominal wall muscle area and CT attenuation, hernia volume (HV), and abdominal cavity volume (ACV) were measured on CT images. The rectus width to defect width ratio (RDR), HV/ACV, and HV/peritoneal volume (PV; i.e., HV + ACV) were calculated. Differences between the indices of the two groups were compared. Logistic regression models were applied to analyze the relationships between the above CT parameters and CS. Receiver operator characteristic (ROC) curves were generated to evaluate the potential utility of CT parameters in predicting CS. Of the102 patients, 69 were in the non-CS group and 33 were in the CS group. Compared with the non-CS group, hernia defect width (P < 0.001), hernia defect angle (P < 0.001), and hernia volume (P < 0.001) were larger in the CS group, while RDR (P < 0.001) was smaller. The abdominal wall muscle area in the CS group was slightly greater than that in the non-CS group (P = 0.046), and there was no significant difference in the CT attenuation of the abdominal wall muscle between the two groups (P = 0.089). Multivariate logistic regression identified hernia defect width (OR 1.815, 95% CI 1.428-2.308, P < 0.001), RDR (OR 0.018, 95% CI 0.003-0.106, P < 0.001), hernia defect angle (OR 1.077, 95% CI 1.042-1.114, P < 0.001), hernia volume (OR 1.002, 95% CI 1.001-1.003, P < 0.001), and CT attenuation of abdominal wall muscle (OR 0.962, 95% CI 0.927-0.998, P = 0.037) as independent predictors of CS. Hernia defect width was the best predictor for CS, with a cut-off point of 9.2cm and an area under the curve (AUC) of 0.890. The AUCs of RDR, hernia defect angle, hernia volume, and abdominal wall muscle CT attenuation were 0.843, 0.812, 0.747, and 0.572, respectively. Quantitative CT measurements are of great value for preoperative prediction of CS. Hernia defect size, hernia volume, and the CT attenuation of abdominal wall muscle are all preoperative predictive indicators of CS.

Structural features on quantitative chest computed tomography of patients with maximal mid-expiratory flow impairment in a normal lung function population

BackgroundMaximal mid-expiratory flow (MMEF) is an earlier predictor of chronic obstructive pulmonary disease (COPD) development than forced expiratory volume in 1 s (FEV1). Changes of lung structure in patients with MMEF impairment only is still not clear. Therefore, this study aimed to investigate the structural features of patients with decreased MMEF by quantitative computed tomography (QCT) and develop a predictive model for predicting patients with reduced MMEF in normal lung function population.MethodsIn this study, 131 patients with normal spirometry results and available volumetric chest CT images were enrolled and divided into the reduced MMEF group (FEV1/forced expiratory vital capacity (FEV1/FVC) > 0.7, FEV1% predictive values (FEV1%pred) > 80%, MMEF%pred < 80%, n = 52) and the normal MMEF group (FEV1/FVC > 0.7, FEV1%pred > 80%, MMEF%pred ≥ 80%, n = 79). The emphysema, small airway disease and medium-size airway parameters were measured by a commercial software. The differences were investigated in clinical features, spirometrical parameters and QCT parameters between the two groups. A nomogram model was constructed based on the results of the multivariable logistic regression model. Spearman’s correlation coefficients were calculated between QCT measurements and spirometrical parameters.ResultsThere were more males in reduced MMEF group than normal group (P < 0.05). Lung parenchyma parameter (PRMEmph) and airway-related parameters (functional small airway disease (PRMfSAD), luminal area of fifth- and sixth- generation airway (LA5, LA6) were significantly different between the reduced MMEF group and the normal group (20.2 ± 17.4 vs 9.4 ± 6.7, 3.4 ± 3.5 vs 1.9 ± 2.0, 12.2 ± 2.5 vs 13.7 ± 3.4, 7.7 ± 2.4 vs 8.9 ± 2.8, respectively, all P < 0.01). After multivariable logistical regression, only sex (odds ratio [OR]: 2.777; 95% confidence interval [CI]:1.123–3.867), PRMfSAD (OR:1.102, 95%CI:1.045–1.162) and LA6 (OR:0.650, 95%CI:0.528–0.799) had significant differences between the two groups (P < 0.05) and a model incorporating with the three indicators was constructed (area under curve, 0.836). Correlation analysis showed MMEF%pred had mild to moderate correlation with airway-related measurements.ConclusionIn normal lung function population, patients with reduced MMEF have potential medium-size and small airway changes, and MMEF%pred is significantly associated with airway-related CT parameters. The nomogram incorporating with sex, PRMfSAD and LA6 has good predictive value and offers more objective evidences in a group with reduced MMEF.

Impact of Bronchiectasis on COPD Severity and Alpha-1 Antitrypsin Deficiency as a Risk Factor in Individuals with a Heavy Smoking History.

Bronchiectasis is common among those with heavy smoking histories, but risk factors for bronchiectasis, including alpha-1 antitrypsin deficiency, and its implications for COPD severity are uncharacterized in such individuals. To characterize the impact of bronchiectasis on COPD and explore alpha-1antitrypsin as a risk factor for bronchiectasis. SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) participants (N=914; ages 40-80 years; ≥20-pack-year smoking) had high-resolution computed tomography (CT) scans interpreted visually for bronchiectasis, based on airway dilation without fibrosis or cicatrization. We performed regression-based models of bronchiectasis with clinical outcomes and quantitative CT measures. We deeply sequenced the gene encoding -alpha-1 antitrypsin, SERPINA1, in 835 participants to test for rare variants, focusing on the PiZ genotype (Glu366Lys, rs28929474). We identified bronchiectasis in 365 (40%) participants, more frequently in women (45% versus 36%, p=0.0045), older participants (mean age=66[standard deviation (SD)=8.3] versus 64[SD=9.1] years, p=0.0083), and those with lower lung function (forced expiratory volume in 1 second [FEV1 ] percentage predicted=66%[SD=27] versus 77%[SD=25], p<0.0001; FEV1 to forced vital capacity [FVC] ratio=0.54[0.17] versus 0.63[SD=0.16], p<0.0001). Participants with bronchiectasis had greater emphysema (%voxels ≤-950 Hounsfield units, 11%[SD=12] versus 6.3%[SD=9], p<0.0001) and parametric response mapping functional small airways disease (26[SD=15] versus 19[SD=15], p<0.0001). Bronchiectasis was more frequent in the combined PiZZ and PiMZ genotype groups compared to those without PiZ, PiS, or other rare pathogenic variants (N=21 of 40 [52%] versus N=283 of 707[40%], odds ratio [OR]=1.97; 95% confidence interval [CI]=1.002, 3.90, p=0.049), an association attributed to White individuals (OR=1.98; 95%CI = 0.9956, 3.9; p=0.051). Bronchiectasis was common in those with heavy smoking histories and was associated with detrimental clinical and radiographic outcomes. Our findings support alpha-1antitrypsin guideline recommendations to screen for alpha-1 antitrypsin deficiency in an appropriate bronchiectasis subgroup with a significant smoking history.

Discordance in lumbar bone mineral density measurements by quantitative computed tomography and dual-energy X-ray absorptiometry in postmenopausal women: a prospective comparative study

Background ContextLevel-specific lumbar bone mineral density (BMD) evaluation of a single vertebral body can provide useful surgical planning and osteoporosis management information. Previous comparative studies have primarily focused on detecting spinal osteoporosis but not at specific levels. PurposeTo compare the detection rate of lumbar osteoporosis between quantitative computed tomography (QCT) and dual-energy X-ray absorptiometry (DXA); to explore and analyze the distribution models of QCT-derived BMD and DXA T-score at the specific levels; and to evaluate the diagnostic accuracy of level-specific BMD thresholds for the prediction of osteoporotic vertebral compression fracture (OVCF) in postmenopausal women. Study Design/SettingA comparative analysis of prospectively collected data comparing QCT-derived BMD with DXA T-score. Patient SampleA total of 296 postmenopausal women who were referred to the spine service of a single academic institution were enrolled. Outcome MeasuresQCT-derived BMD and DXA T-score at specific levels, with or without osteoporotic vertebral compression fracture. MethodsPostmenopausal women who underwent QCT and DXA within a week of admission from May 2019 to June 2022 were enrolled. The diagnostic criteria for osteoporosis recommended by the World Health Organization and the American College of Radiology were used for lumbar osteoporotic diagnosis. To evaluate differences in lumbar BMD measurements at specific levels, a threshold of T score=-2.5 and QCT-derived BMD = 80 mg/cm3 were used to categorize level-specific lumbar BMD into low and high BMD. Disagreements in BMD categorization between DXA and QCT were classified as a minor or major discordance based on the definition by Woodson. Data between QCT and DXA were visualized in a stacked bar plot and analyzed. Correlations between DXA and QCT at the specific levels were evaluated using Pearson's linear correlation and scatter plots. Curve fitting of BMD distribution, receiver operating characteristic (ROC) and area under the curve (AUC) for each single vertebral level was performed. ResultsOf the 296 patients, QCT diagnosed 61.1% as osteoporosis, 30.4% as osteopenia and 8.4% as normal. For those screened with DXA, 54.1% of the patients had osteoporosis, 29.4% had osteopenia and 16.6% had normal BMD. Diagnoses were concordant for 194 (65.5%) patients. Of the other 102 discordant patients, 5 (1.7%) were major and 97 (32.8%) were minor. Significant correlations in level-specific BMD between DXA and QCT were observed (p<.001), with Pearson's correlation coefficients ranging from 0.662 to 0.728. The correlation strength was in the order of L1 > L2 > L3 > L4. The low BMD detection rate for QCT was significantly higher than that for DXA at the L3 and L4 levels (65% vs. 47.9% and 68.1% vs 43.7, respectively, p<.001). Patients with OVCF showed significantly lower QCT-derived BMD (47.2 mg/cm3 vs. 83.2 mg/cm3, p<.001) and T-score (-3.39 vs. -1.98, p<.001) than those without OVCF. Among these patients, 82.8% (101/122) were diagnosed with osteoporosis by QCT measurement, while only 74.6% (91/122) were diagnosed by DXA. For discrimination between patients with and without OVCF, QCT-derived BMD showed better diagnosed performance (AUC range from 0.769 to 0.801) than DXA T-score (AUC range from 0.696 to 0.753). ConclusionQCT provided a more accurate evaluation of lumbar osteoporosis than DXA. The QCT-derived BMD measurements at a specific lumbar level have a high diagnostic performance for OVCF.

MRI-Based Score for Assessment of Bone Mineral Density in Operative Spine Patients.

Retrospective comparison. The aim was to determine whether a previously developed magnetic resonance imaging (MRI)-derived bone mineral density (BMD) scoring system can differentiate between healthy and osteoporotic vertebrae and to validate this scoring system against quantitative computed tomography measurements. BMD is an important preoperative consideration in spine surgery. Techniques to measure BMD are subject to falsely elevated values in the setting of spondylosis (dual-energy X-ray absorptiometry) or require significant exposure to radiation [quantitative computed tomography (QCT)]. Previous studies have shown that MRI may be utilized to measure bone quality using changes in the bone marrow signal observed on T1-weighted MRIs. Retrospective study of patients who underwent operative lumbar procedures at a single tertiary institution between 2016 and 2021 (n=61). Vertebral bone quality (VBQ) scores were measured by dividing the median signal intensities of L1-L4 by the signal intensity of cerebrospinal fluid on noncontrast T1W MRI. Demographic data, comorbidities, VBQ scores, and QCT-derived T scores and BMD of the lumbar spine were compared between healthy ( T score ≥-1; n=21), osteopenic (-2.5 < T score < -1; n=21), and osteoporotic ( T score ≤-2.5; n=19) cohorts using analysis of variance with post hoc Tukey test. Linear regression and receiver operating characteristic curve analyses were performed to assess the predictive value of VBQ scores. Pearson correlation test was used to evaluate the association between VBQ scores and QCT-derived measurements. VBQ differentiated between healthy and osteoporotic groups ( P =0.009). Receiver operating characteristic curve analysis revealed that a greater VBQ score was associated with presence of osteoporosis (area under the curve=0.754, P =0.006). Cutoff VBQ for osteoporosis was 2.6 (Youden index 0.484; sensitivity: 58%; specificity: 90%). VBQ scores weakly correlated with QCT-derived BMD ( P =0.03, r =-0.27) and T scores ( P =0.04, r =-0.26). This study attempted to further validate a previously developed MRI-based BMD scoring system against QCT-derived measurements. VBQ score was found to be a significant predictor of osteoporosis and could differentiate between healthy and osteoporotic vertebrae.