Quantitative imaging workshop XIX: Utilizing quantitative thoracic imaging to optimize population health final summary.

Lung cancer screening involves the use of thoracic CT for both detection and measurements of suspicious lung nodules to guide the screening management. Since lung cancer screening eligibility typically requires age over 50 years along with >20 pack-year tobacco exposure, thoracic CT scans also frequently reveal evidence for pulmonary emphysema as well as coronary artery calcification. These three thoracic diseases are collectively three of the leading causes of premature death across the world. Screening for the major thoracic diseases in this heavily tobacco-exposed cohort is broadening the focus of lung cancer screening to a more comprehensive health evaluation including discussing the relevance of screen-detected findings of the heart and lung parenchyma. The status and implications of these emerging issues were reviewed in a multidisciplinary workshop focused on the process of quantitative imaging in the lung cancer screening setting to guide the evolution of this important new area of public health.

Deteriorated bone microarchitecture caused by sympathetic overstimulation in pheochromocytoma and paraganglioma.

PURPOSE: Despite the potentially destructive effect of sympathetic activity on bone metabolism, its impact on bone microarchitecture, a key determinant of bone quality, has not been thoroughly investigated. This study aims to evaluate the impact of sympathetic activity on bone microarchitecture and bone strength in patients with pheochromocytoma and paraganglioma (PPGL). METHODS: A cross-sectional study was conducted in 38 PPGL patients (15 males and 23 females). Bone turnover markers serum procollagen type 1 N-terminal propeptide (P1NP) and ß-carboxy-terminal crosslinked telopeptide of type 1 collagen (ß-CTX) were measured. 24-h urinary adrenaline (24hUE) and 24-h urinary norepinephrine levels (24hUNE) were measured to indicate sympathetic activity. High-resolution peripheral quantitative computed tomography (HR-pQCT) was conducted to evaluate bone microarchitecture in PPGL patients and 76 age-, sex-matched healthy controls (30 males and 46 females). Areal bone mineral density (aBMD) was measured by dual-energy X-ray absorptiometry (DXA) simultaneously. RESULTS: PPGL patients had a higher level of ß-CTX. HR-pQCT assessment revealed that PPGL patients had notably thinner and more sparse trabecular bone (decreased trabecular number and thickness with increased trabecular separation), significantly decreased volume BMD (vBMD), and bone strength at both the radius and tibia compared with healthy controls. The deterioration of Tt.vBMD, Tb.Sp, and Tb.1/N.SD was more pronounced in postmenopausal patients compared with the premenopausal subjects. Moreover, subjects in the highest 24hUNE quartile (Q4) showed markedly lower Tb.N and higher Tb.Sp and Tb.1/N.SD at the tibia than those in the lowest quartile (Q1). Age-related bone loss was also exacerbated in PPGL patients to a certain extent. CONCLUSIONS: PPGL patients had significantly deteriorated bone microarchitecture and strength, especially in the trabecular bone, with an increased bone resorption rate. Our findings provide clinical evidence that sympathetic overstimulation may serve as a secondary cause of osteoporosis, especially in subjects with increased sympathetic activity.

GOLD-Grade Specific Disease Characterization and Phenotyping of COPD Using Quantitative Computed Tomography in the Nationwide COSYCONET Multicenter Trial in Germany.

INTRODUCTION: The aim of this study was to apply quantitative computed tomography (QCT) for GOLD-grade specific disease characterization and phenotyping of air-trapping, emphysema, and airway abnormalities in patients with chronic obstructive pulmonary disease (COPD) from a nationwide cohort study. METHODS: As part of the COSYCONET multicenter study, standardized CT in ex- and inspiration, lung function assessment (FEV1/FVC), and clinical scores (BODE index) were prospectively acquired in 525 patients (192 women, 327 men, aged 65.7 ± 8.5 years) at risk for COPD and at GOLD1-4. QCT parameters such as total lung volume (TLV), emphysema index (EI), parametric response mapping (PRM) for emphysema (PRMEmph) and functional small airway disease (PRMfSAD), total airway volume (TAV), wall percentage (WP), and total diameter (TD) were computed using automated software. RESULTS: TLV, EI, PRMfSAD, and PRMEmph increased incrementally with each GOLD grade (p < 0.001). Aggregated WP5-10 of subsegmental airways was higher from GOLD1 to GOLD3 and lower again at GOLD4 (p < 0.001), whereas TD5-10 was significantly dilated only in GOLD4 (p < 0.001). Fifty-eight patients were phenotyped as "non-airway non-emphysema type," 202 as "airway type," 96 as "emphysema type," and 169 as "mixed type." FEV1/FVC was best in "non-airway non-emphysema type" compared to other phenotypes, while "mixed type" had worst FEV1/FVC (p < 0.001). BODE index was 0.56 ± 0.72 in the "non-airway non-emphysema type" and highest with 2.55 ± 1.77 in "mixed type" (p < 0.001). CONCLUSION: QCT demonstrates increasing hyperinflation and emphysema depending on the GOLD grade, while airway wall thickening increases until GOLD3 and airway dilatation occur in GOLD4. QCT identifies four disease phenotypes with implications for lung function and prognosis.

Quantitative CT analysis of idiopathic pulmonary fibrosis and correlation with lung function study.

BACKGROUND: Idiopathic Pulmonary Fibrosis (IPF) is a progressive fibrotic lung disease. However, the field of quantitative CT scan analysis in conjunction with pulmonary function test for IPF patients remains relatively understudied. In this study, we evaluated the diagnostic value of features derived high-resolution computed tomography (HRCT) for patients with IPF and correlated them with pulmonary function tests. METHODS: We retrospectively analyzed the chest HRCT images and pulmonary function test results of 52 patients with IPF during the same period (1 week) and selected 52 healthy individuals, matched for sex, age, and body mass index (BMI) and with normal chest HRCT as controls. HRCT scans were performed using a Philips 256-row Brilliance iCT scanner with standardized parameters. Lung function tests were performed using a Jaeger volumetric tracer for forced vital capacity (FVC), total lung capacity (TLC), forced expiratory volume in first second (FEV1), FEV1/FVC, carbon monoxide diffusing capacity (DLCO), and maximum ventilation volume (MVV) metrics. CT quantitative analysis, including tissue segmentation and threshold-based quantification of lung abnormalities, was performed using 3D-Slicer software to calculate the percentage of normal lung areas (NL%), percentage of ground-glass opacity areas (GGO%), percentage of fibrotic area (F%) and abnormal lesion area percentage (AA%). Semi-quantitative analyses were performed by two experienced radiologists to assess disease progression. The aortic-to-sternal distance (ASD) was measured on axial images as a standardized parameter. Spearman or Pearson correlation analysis and multivariate stepwise linear regression were used to analyze the relationship between the data in each group, and the ROC curve was used to determine the optimal quantitative CT metrics for identifying IPF and controls. RESULTS: ROC curve analysis showed that F% distinguished the IPF patient group from the control group with the largest area under the curve (AUC) of 0.962 (95% confidence interval: 0.85-0.96). Additionally, with F% = 4.05% as the threshold, the Youden's J statistic was 0.827, with a sensitivity of 92.3% and a specificity of 90.4%. The ASD was significantly lower in the late stage of progression than in the early stage (t = 5.691, P < 0.001), with a mean reduction of 2.45% per month. Quantitative CT indices correlated with all pulmonary function parameters except FEV1/FVC, with the highest correlation coefficients observed for F% and TLC%, FEV1%, FVC%, MVV% (r = - 0.571, - 0.520, - 0.521, - 0.555, respectively, all P-values < 0.001), and GGO% was significantly correlated with DLCO% (r = - 0.600, P < 0.001). Multiple stepwise linear regression analysis showed that F% was the best predictor of TLC%, FEV1%, FVC%, and MVV% (R2 = 0.301, 0.301, 0.300, and 0.302, respectively, all P-values < 0.001), and GGO% was the best predictor of DLCO% (R2 = 0.360, P < 0.001). CONCLUSIONS: Quantitative CT analysis can be used to diagnose IPF and assess lung function impairment. A decrease in the ASD may indicate disease progression.

Effectiveness of opportunistic osteoporosis screening on chest CT using the DCNN model.

OBJECTIVE: To develop and evaluate a deep learning model based on chest CT that achieves favorable performance on opportunistic osteoporosis screening using the lumbar 1 + lumbar 2 vertebral bodies fusion feature images, and explore the feasibility and effectiveness of the model based on the lumbar 1 vertebral body alone. MATERIALS AND METHODS: The chest CT images of 1048 health check subjects from January 2021 to June were retrospectively collected as the internal dataset (the segmentation model: 548 for training, 100 for tuning and 400 for test. The classification model: 530 for training, 100 for validation and 418 for test set). The subjects were divided into three categories according to the quantitative CT measurements, namely, normal, osteopenia and osteoporosis. First, a deep learning-based segmentation model was constructed, and the dice similarity coefficient(DSC) was used to compare the consistency between the model and manual labelling. Then, two classification models were established, namely, (i) model 1 (fusion feature construction of lumbar vertebral bodies 1 and 2) and (ii) model 2 (feature construction of lumbar 1 alone). Receiver operating characteristic curves were used to evaluate the diagnostic efficacy of the models, and the Delong test was used to compare the areas under the curve. RESULTS: When the number of images in the training set was 300, the DSC value was 0.951 ± 0.030 in the test set. The results showed that the model 1 diagnosing normal, osteopenia and osteoporosis achieved an AUC of 0.990, 0.952 and 0.980; the model 2 diagnosing normal, osteopenia and osteoporosis achieved an AUC of 0.983, 0.940 and 0.978. The Delong test showed that there was no significant difference in area under the curve (AUC) values between the osteopenia group and osteoporosis group (P = 0.210, 0.546), while the AUC value of normal model 2 was higher than that of model 1 (0.990 vs. 0.983, P = 0.033). CONCLUSION: This study proposed a chest CT deep learning model that achieves favorable performance on opportunistic osteoporosis screening using the lumbar 1 + lumbar 2 vertebral bodies fusion feature images. We further constructed the comparable model based on the lumbar 1 vertebra alone which can shorten the scan length, reduce the radiation dose received by patients, and reduce the training cost of technologists.

Quantitative CT lumbar spine BMD cutpoint value for classifying osteoporosis among older East Asian women should be lower than the value for Caucasians.

For Caucasian women, the QCT (quantitative CT) lumbar spine (LS) bone mineral density (BMD) cutpoint value for classifying osteoporosis is 80 mg/ml. At the age of approximate 78 years, US Caucasian women QCT LS BMD population mean is 80 mg/ml, while that of Chinese women and Japanese women is around 50 mg/ml. Correlation analyses show, for Chinese women and Japanese women, QCT LS BMD of 45 mg/ml corresponds to the dual-energy X-ray absorptiometry cutpoint value for classifying osteoporosis. For Chinese and Japanese women, if QCT LS BMD 80 mg/ml is used as the threshold to classify osteoporosis, then the specificity of classifying subjects with vertebral fragility fracture into the osteoporotic group is low, whereas threshold of 45 mg/ml approximately achieve a similar separation for women with and without vertebral fragility fracture as the reports for Caucasian women. Moreover, by using 80mg/ml as the cutpoint value, LS QCT leads to excessively high prevalence of osteoporosis for Chinese women, with the discordance between hip dual-energy X-ray absorptiometry and LS QCT measures far exceeding expectation. Considering the different bone properties and the much lower prevalence of fragility fractures in the East Asian women compared with Caucasians, we argue that the QCT cutpoint value for classifying osteoporosis among older East Asian women will be close to and no more than 50 mg/ml LS BMD. We suggest that it is also imperative the QCT osteoporosis classification criterion for East Asian male LS, and male and female hips be re-examined.

Quantitative CT lumbar spine BMD cutpoint value for classifying osteoporosis among older Chinese men can be the same as that of older Chinese women, both much lower than the value for Caucasians.

For older Caucasian women and men, the QCT (quantitative CT) lumbar spine (LS) bone mineral density (BMD) threshold for classifying osteoporosis is 80 mg/ml. It was recently proposed that, for older East Asian women, the QCT LS BMD value equivalent to the Caucasian women's threshold of 80 mg/mL is about 45∼50 mg/ml. For a data of 328 cases of Chinese men (age: 73.6 ± 4.4 years) who had QCT LS BMD and DXA LS BMD at the same time and with the DXA BMD value of ≤ 0.613 g/cm2 to classify osteoporosis, the corresponding QCT LS BMD threshold is 53 mg/ml. Osteoporotic-like vertebral fracture sum score (OLVFss) ≤ -2.5 has been proposed to diagnose osteoporosis. For 316 cases of Chinese men (age:73.7±4.5 years), OLVFss ≤ -2.5 defines an osteoporosis prevalence of 4.4%; to achieve this osteoporosis prevalence, the corresponding QCT LS BMD value is < 47.5 mg/ml. In the China Action on Spine and Hip Status study, a Genant grades 2/3 radiographic 'osteoporotic vertebral fracture' prevalence was 2.84% for Chinese men (total n = 1267, age: 62.77 ± 9.20 years); to achieve this osteoporosis prevalence, the corresponding BMD value was < 42.5 mg/ml. In a study of 357 Beijing older men, according to the clinical fragility fracture prevalence and femoral neck DXA T-score, the QCT LS BMD value to classify osteoporosis was between 39.45 mg/ml and 51.38 mg/ml. For older Chinese men (≥ 50 years), we recommend the cutpoint for the QCT LS BMD definition of osteoporosis to be 45∼50 mg/ml which is the same as the value for Chinese women.

Impact of scatter radiation on spectral quantification performance of first- and second-generation dual-layer spectral computed tomography.

OBJECTIVE: To assess the impact of scatter radiation on quantitative performance of first and second-generation dual-layer spectral computed tomography (DLCT) systems. METHOD: A phantom with two iodine inserts (1 and 2 mg/mL) configured to intentionally introduce high scattering conditions was scanned with a first- and second-generation DLCT. Collimation widths (maximum of 4 cm for first generation and 8 cm for second generation) and radiation dose levels were varied. To evaluate the performance of both systems, the mean CT numbers of virtual monoenergetic images (MonoEs) at different energies were calculated and compared to expected values. MonoEs at 50  versus 150 keV were plotted to assess material characterization of both DLCTs. Additionally, iodine concentrations were determined, plotted, and compared against expected values. For each experimental scenario, absolute errors were reported. RESULTS: An experimental setup, including a phantom design, was successfully implemented to simulate high scatter radiation imaging conditions. Both CT scanners illustrated high spectral accuracy for small collimation widths (1 and 2 cm). With increased collimation (4 cm), the second-generation DLCT outperformed the earlier DLCT system. Further, the spectral performance of the second-generation DLCT at an 8 cm collimation width was comparable to a 4 cm collimation on the first-generation DLCT. A comparison of the absolute errors between both systems at lower energy MonoEs illustrates that, for the same acquisition parameters, the second-generation DLCT generated results with decreased errors. Similarly, the maximum error in iodine quantification was less with second-generation DLCT (0.45  and 0.33 mg/mL for the first and second-generation DLCT, respectively). CONCLUSION: The implementation of a two-dimensional anti-scatter grid in the second-generation DLCT improves the spectral quantification performance. In the clinical routine, this improvement may enable additional clinical benefits, for example, in lung imaging.

Advances in Research on Application of Quantitative CT in Clinical Diagnosis and Treatment of Osteoporosis.

Quantitative CT (QCT) is a method of measuring bone mineral density (BMD) of human based on a CT machine,calibrated by QCT body model and analyzed by professional software.Compared with dual-energy X-ray absorptiometry,QCT can not only assess the cortical and cancellous BMD but also exclude the influences of osteophytes and aortic/vascular calcification,thus being capable of accurately reflecting patients' bone mass.In recent years,increasing studies on QCT and osteoporosis (OP) have been carried out,and the application of QCT in the diagnosis of OP,evaluation of vertebral bone conditions,prediction of fracture risks,and assessment of anti-OP treatment is garnering increasing attention from researchers at home and abroad.This article reviews the research progress in this field,aiming to provide a reference for the research on QCT in the diagnosis and treatment of OP.

Qualitative and quantitative imaging features of solid pancreas tumours in portal venous phase CT: are they useful in determining tumour type and grade?

Purpose: Solid pancreatic lesions might have overlapping findings in portal venous phase computed tomography (CT). In this study, we aimed to investigate the quantitative and qualitative imaging features of solid pancreas lesions based on subtype and grade. Material and methods: The study group consisted of 159 patients with solid pancreatic tumours detected after exclusion criteria. According to the pathology results, the patients were divided into 3 groups as PDAC (pancreatic ductal adenocarcinoma, n = 137), PNET (pancreatic neuroendocrine tumour, n = 15), and SC (sarcomatoid carcinoma, n = 7). PDAC and PNET lesions were evaluated in 3 subgroups according to grade. Results: There was no difference between the groups in terms of age, gender, tumour localisation, and internal structure (p = 0.23, p = 0.81, p = 0.19, and p = 0.94, respectively). Qualitative features significantly differed in terms of tumour margin feature, visual tumour density, presence of cystic component, and presence of necrosis (p = 0.01, p = 0.0001, p = 0.002, and p = 0.004, respectively). Tumour size, Tmden, Tmden/VPden, and Tmden/PanPden showed differences between groups (p = 0.0001, p = 0.002, p = 0.0001, p = 0.0001, respectively). The presence of cystic density in PDAC patients differed according to grade (p = 0.01). Conclusions: While ill-defined irregular margins, hypodense visual tumour density, no cystic component, low value of Tmden, and low ratios of Tmden/VPden and Tmden/PanPden indicate PDAC, regular margins, iso-or hyperdense visual tumour density, cystic component, high value of Tmden, and high ratios of Tmden/VPden and Tmden/PanPden indicate PNET. SC can be differentiated from them by containing necrosis and reaching larger sizes. The presence of a cystic component in PDAC patients indicates high grade.

CT imaging findings in lung transplant recipients with COVID-19.

OBJECTIVES: Our goal was to compare the chest computed tomography (CT) imaging findings of COVID-19 in lung transplant recipients (LTR) and a group of non-transplanted controls (NTC). METHODS: This retrospective study included 51 consecutive LTR hospitalized with COVID-19 from two centers. A total of 75 NTC were included for comparison. Images were classified regarding the standardized RSNA category, main pattern of lung attenuation, and longitudinal and axial distribution. Quantitative CT (QCT) analysis was performed to evaluate percentage of high attenuation areas (%HAA, threshold -250 to -700 HU). CT scoring was used to measure severity of parenchymal abnormalities. RESULTS: The imaging findings of COVID-19 in LTR were significantly different from controls regarding the RSNA classification and pattern of lung attenuation. LTR had a significantly higher proportion of patients with an indeterminate pattern on CT (0.31 vs. 0.11, p = 0.014). The most frequent pattern of attenuation in LTR was predominantly consolidation (0.39 vs. 0.22, p = 0.144) followed by a mixed pattern of ground-glass opacities (GGO) and consolidation (0.37 vs. 0.20, adjusted p = 0.102). On the other hand, the most common pattern in NTC was GGO predominant (0.58 vs. 0.24 of LTR, p = 0.001). LTR had significantly more severe parenchymal disease measured by CT score and %HAA by QCT (0.372 ± 0.08 vs. 0.148 ± 0.06, p < 0.001). CONCLUSION: The most frequent finding of COVID-19 in LTR is a predominant pattern of consolidation. Compared to NTC, LTR more frequently demonstrated an indeterminate pattern according to the RSNA classification and more extensive lung abnormalities on QCT and semi-quantitative scoring. KEY POINTS: • The most common CT finding of COVID-19 in LTR is a predominant pattern of consolidation followed by a mixed pattern of GGO and consolidation, while controls more often have a predominant pattern of GGO. • LTR more often presents with an indeterminate pattern of COVID-19 by RSNA classification than controls; therefore, molecular testing for COVID-19 is essential for LTR presenting with lower airway infection independently of imaging findings. • LTR had more extensive disease by semi-quantitative CT score and increased percentage areas of high attenuation on QCT.

Analysis of tissue lipidomics and computed tomography pulmonary fat attenuation volume (CTPFAV ) in idiopathic pulmonary fibrosis.

BACKGROUND AND OBJECTIVE: There is increasing interest in the role of lipids in processes that modulate lung fibrosis with evidence of lipid deposition in idiopathic pulmonary fibrosis (IPF) histological specimens. The aim of this study was to identify measurable markers of pulmonary lipid that may have utility as IPF biomarkers. STUDY DESIGN AND METHODS: IPF and control lung biopsy specimens were analysed using a unbiased lipidomic approach. Pulmonary fat attenuation volume (PFAV) was assessed on chest CT images (CTPFAV ) with 3D semi-automated lung density software. Aerated lung was semi-automatically segmented and CTPFAV calculated using a Hounsfield-unit (-40 to -200HU) threshold range expressed as a percentage of total lung volume. CTPFAV was compared to pulmonary function, serum lipids and qualitative CT fibrosis scores. RESULTS: There was a significant increase in total lipid content on histological analysis of IPF lung tissue (23.16 nmol/mg) compared to controls (18.66 mol/mg, p = 0.0317). The median CTPFAV in IPF was higher than controls (1.34% vs. 0.72%, p < 0.001) and CTPFAV correlated significantly with DLCO% predicted (R2 = 0.356, p < 0.0001) and FVC% predicted (R2 = 0.407, p < 0.0001) in patients with IPF. CTPFAV correlated with CT features of fibrosis; higher CTPFAV was associated with >10% reticulation (1.6% vs. 0.94%, p = 0.0017) and >10% honeycombing (1.87% vs. 1.12%, p = 0.0003). CTPFAV showed no correlation with serum lipids. CONCLUSION: CTPFAV is an easily quantifiable non-invasive measure of pulmonary lipids. In this pilot study, CTPFAV correlates with pulmonary function and radiological features of IPF and could function as a potential biomarker for IPF disease severity assessment.

Na-Cl Co-transporter (NCC) gene inactivation is associated with improved bone microstructure.

Gitelman syndrome (GS) is the disease model of the inactivation of thiazide-sensitive sodium chloride cotransporter (NCC), which is believed to benefit bone mass and reduce fracture risk. In this study, we found that GS patients have superior bone microarchitecture, which is associated with the disease status. Several decreased bone parameters with aging in healthy controls were reversed in GS patients to a certain extent. PURPOSE: To evaluate the impact of the inactivation of NCC on bone turnover and microarchitecture in Gitelman syndrome patients. METHODS: A cross-sectional study was conducted in 45 GS patients (25 males and 20 females). Serum procollagen type 1 N-terminal propeptide (P1NP), ß-carboxy-terminal crosslinked telopeptide of type 1 collagen (ß-CTX), and osteocalcin were measured. High-resolution peripheral quantitative computed tomography (HR-pQCT) was conducted to evaluate bone microarchitecture in GS patients and age- and sex-matched healthy controls. Areal bone mineral density (aBMD) was measured by dual-energy X-ray absorptiometry (DXA) simultaneously. RESULTS: GS patients had a relatively lower level of ß-CTX. aBMD at several skeletal sites was improved in GS patients. HR-pQCT assessment revealed that GS patients had slightly thinner but significantly more compact trabecular bone (increased trabecular number and decreased thickness), notably decreased cortical porosity, and increased volume BMD (vBMD) at both the radius and tibia compared with controls. The disease severity, represented as the relationship with the minimum level of magnesium during the course and standard base excess, was associated with bone microarchitecture parameters after adjusting for age, sex, and BMI. The decreased vBMD and Tb.BV/TV, and increased Tb.Sp and Ct.Po with aging, were reversed in GS patients to a certain extent. CONCLUSION: GS patients have superior bone microarchitecture, which suggests that the inactivation of NCC might be beneficial for avoiding osteoporosis.

The Effect of Region of Interest on Measurement of Bone Mineral Density of the Proximal Femur: Simulation Analysis Using CT Images.

While accurate measurement of bone mineral density (BMD) is essential in the diagnosis of osteoporosis and in evaluating the treatment of osteoporosis, it is unclear how region of interest (ROI) settings affect measurement of BMD at the total proximal femur region. In this study, we performed a simulation analysis to clarify the effect on BMD measurement of changing the ROI using hip computed tomography (CT) images of 75 females (mean age, 62.4 years). Digitally reconstructed radiographs of the proximal femur region were generated from CT images to calculate the change in BMD when the proximal boundary of the ROI was altered by 0-10 mm, and when the distal boundary of the ROI was altered by 0-30 mm. Further, changes in BMD were compared across BMD classification groups. A mean BMD increase of 0.62% was found for each 1-mm extension of the distal boundary. A mean BMD decrease of 0.18% was found for each 1-mm alteration of the proximal boundary. Comparing BMD classification groups, patients with osteoporosis and osteopenia demonstrated greater BMD changes than patients with normal BMD for the distal boundary (0.68%, 0.64%, and 0.54%, respectively) and patients with osteoporosis demonstrated greater BMD changes than patients with osteoporosis and normal BMD for the proximal boundary (0.37%, 0.13%, and 0.03%, respectively). In conclusion, our study found that a consistent ROI setting, especially on the distal boundary, is necessary for the accurate measurement of total proximal femur BMD. Based on the findings, we recommend confirming that the ROI setting shown on the BMD result form is consistent with changes in serial BMD.

Relationships between QUS and HR-pQCT, DXA, and bone turnover markers.

INTRODUCTION: Relationship of quantitative ultrasound (QUS) with high-resolution peripheral quantitative computed tomography (HR-pQCT), dual-energy X-ray absorptiometry (DXA), and bone-related biochemical markers was analyzed. MATERIALS AND METHODS: The subjects were 480 individuals. Speed of sound (SOS) was measured by calcaneal QUS. Volumetric bone mineral density (vBMD) and microarchitecture of trabecular and cortical bone in the distal radius and tibia were assessed by HR-pQCT. Areal bone mineral density (aBMD) in the lumbar spine and proximal femur were measured by DXA. TRACP-5b, P1NP, 25 (OH) vitamin D, and pentosidine were evaluated by biochemical tests. The correlation of each parameter was analyzed for all subjects and by sex and age group. RESULTS: QUS was moderately correlated with Tb.vBMD and Tb.BV/TV in the radius and tibia. No correlation was seen with Ct.vBMD or cortical porosity (Ct.Po). Although a correlation was seen with cortical thickness (Ct.Th) in the tibia in all subjects, no correlation was seen in women aged ≥ 60 years. QUS showed moderate correlations with aBMD in the proximal femur. Although moderate correlation was seen with aBMD in the lumbar spine in all subjects, no correlation was seen in subjects aged ≥ 60 years. No significant correlations were seen between QUS and biochemical markers. CONCLUSIONS: Moderate correlations were seen between QUS and Tb.vBMD and microarchitecture in the radius and tibia and aBMD of the proximal femur. On the other hand, practically no correlations were seen with Ct.vBMD or Ct.Po and the bone-related biochemical markers. Only in middle age, moderate correlations were seen with Ct.Th in the tibia and with aBMD of the lumbar spine.

Hepatic Steatosis: CT-Based Prevalence in Adults in China and the United States and Associations With Age, Sex, and Body Mass Index.

BACKGROUND. Calibrated CT fat fraction (FFCT) measurements derived from un-enhanced abdominal CT reliably reflect liver fat content, allowing large-scale population-level investigations of steatosis prevalence and associations. OBJECTIVE. The purpose of this study was to compare the prevalence of hepatic steatosis, as assessed by calibrated CT measurements, between population-based Chinese and U.S. cohorts, and to investigate in these populations the relationship of steatosis with age, sex, and body mass index (BMI). METHODS. This retrospective study included 3176 adults (1985 women and 1191 men) from seven Chinese provinces and 8748 adults (4834 women and 3914 men) from a single U.S. medical center, all drawn from previous studies. All participants were at least 40 years old and had undergone unenhanced abdominal CT in previous studies. Liver fat content measurements on CT were cross-calibrated to MRI proton density fat fraction measurements using phantoms and expressed as adjusted FFCT measurements. Mild, moderate, and severe steatosis were defined as adjusted FFCT of 5.0-14.9%, 15.0-24.9%, and 25.0% or more, respectively. The two cohorts were compared. RESULTS. In the Chinese and U.S. cohorts, the median adjusted FFCT for women was 4.7% and 4.8%, respectively, and that for men was 5.8% and 6.2%, respectively. In the Chinese and U.S. cohorts, steatosis prevalence for women was 46.3% and 48.7%, respectively, whereas that for men was 58.9% and 61.9%, respectively. Severe steatosis prevalence was 0.9% and 1.8% for women and 0.2% and 2.6% for men in the Chinese and U.S. cohorts, respectively. Adjusted FFCT did not vary across age decades among women or men in the Chinese cohort, although it increased across age decades among women and men in the U.S. cohort. Adjusted FFCT and BMI exhibited weak correlation (r = 0.312-0.431). Among participants with normal BMI, 36.8% and 38.5% of those in the Chinese and U.S. cohorts, respectively, had mild steatosis, and 3.0% and 1.5% of those in the Chinese and U.S. cohorts, respectively, had moderate or severe steatosis. Among U.S. participants with a BMI of 40.0 or greater, 17.7% had normal liver content. CONCLUSION. Steatosis and severe steatosis had higher prevalence in the U.S. cohort than in the Chinese cohort in both women and men. BMI did not reliably predict steatosis. CLINICAL IMPACT. The findings provide new information on the dependence of hepatic steatosis on age, sex, and BMI.

Quantitative Computed Tomography: What Clinical Questions Can it Answer in Chronic Lung Disease?

Quantitative computed tomography (QCT) has recently gained an important role in the functional assessment of chronic lung disease. Its capacity in diagnostic, staging, and prognostic evaluation in this setting is similar to that of traditional pulmonary function testing. Furthermore, it can demonstrate lung injury before the alteration of pulmonary function test parameters, and it enables the classification of disease phenotypes, contributing to the customization of therapy and performance of comparative studies without the intra- and inter-observer variation that occurs with qualitative analysis. In this review, we address technical issues with QCT analysis and demonstrate the ability of this modality to answer clinical questions encountered in daily practice in the management of patients with chronic lung disease.

Quantitative CT comparison between COVID-19 and mycoplasma pneumonia suspected as COVID-19: a longitudinal study.

OBJECTIVE: The purpose of this study was to compare imaging features between COVID-19 and mycoplasma pneumonia (MP). MATERIALS AND METHODS: The data of patients with mild COVID-19 and MP who underwent chest computed tomography (CT) examination from February 1, 2020 to April 17, 2020 were retrospectively analyzed. The Pneumonia-CT-LKM-PP model based on a deep learning algorithm was used to automatically quantify the number, volume, and involved lobes of pulmonary lesions, and longitudinal changes in quantitative parameters were assessed in three CT follow-ups. RESULTS: A total of 10 patients with mild COVID-19 and 13 patients with MP were included in this study. There was no difference in lymphocyte counts at baseline between the two groups (1.43 ± 0.45 vs. 1.44 ± 0.50, p = 0.279). C-reactive protein levels were significantly higher in MP group than in COVID-19 group (p < 0.05). The number, volume, and involved lobes of pulmonary lesions reached a peak in 7-14 days in the COVID-19 group, but there was no peak or declining trend over time in the MP group (p < 0.05). CONCLUSION: Based on the longitudinal changes of quantitative CT, pulmonary lesions peaked at 7-14 days in patients with COVID-19, and this may be useful to distinguish COVID-19 from MP and evaluate curative effects and prognosis.

Incubation period, clinical and lung CT features for early prediction of COVID-19 deterioration: development and internal verification of a risk model.

BACKGROUND: Most severe, critical, or mortal COVID-19 cases often had a relatively stable period before their status worsened. We developed a deterioration risk model of COVID-19 (DRM-COVID-19) to predict exacerbation risk and optimize disease management on admission. METHOD: We conducted a multicenter retrospective cohort study with 239 confirmed symptomatic COVID-19 patients. A combination of the least absolute shrinkage and selection operator (LASSO), change-in-estimate (CIE) screened out independent risk factors for the multivariate logistic regression model (DRM-COVID-19) from 44 variables, including epidemiological, demographic, clinical, and lung CT features. The compound study endpoint was progression to severe, critical, or mortal status. Additionally, the model's performance was evaluated for discrimination, accuracy, calibration, and clinical utility, through internal validation using bootstrap resampling (1000 times). We used a nomogram and a network platform for model visualization. RESULTS: In the cohort study, 62 cases reached the compound endpoint, including 42 severe, 18 critical, and two mortal cases. DRM-COVID-19 included six factors: dyspnea [odds ratio (OR) 4.89;confidence interval (95% CI) 1.53-15.80], incubation period (OR 0.83; 95% CI 0.68-0.99), number of comorbidities (OR 1.76; 95% CI 1.03-3.05), D-dimer (OR 7.05; 95% CI, 1.35-45.7), C-reactive protein (OR 1.06; 95% CI 1.02-1.1), and semi-quantitative CT score (OR 1.50; 95% CI 1.27-1.82). The model showed good fitting (Hosmer-Lemeshow goodness, X2(8) = 7.0194, P = 0.53), high discrimination (the area under the receiver operating characteristic curve, AUROC, 0.971; 95% CI, 0.949-0.992), precision (Brier score = 0.051) as well as excellent calibration and clinical benefits. The precision-recall (PR) curve showed excellent classification performance of the model (AUCPR = 0.934). We prepared a nomogram and a freely available online prediction platform ( https://deterioration-risk-model-of-covid-19.shinyapps.io/DRMapp/ ). CONCLUSION: We developed a predictive model, which includes the including incubation period along with clinical and lung CT features. The model presented satisfactory prediction and discrimination performance for COVID-19 patients who might progress from mild or moderate to severe or critical on admission, improving the clinical prognosis and optimizing the medical resources.

Biomechanical analysis of vertebral wedge deformity in elderly women with quantitative CT-based finite element analysis.

BACKGROUND: To explore the vertebral deformity angle (VD angle) of 1st lumbar vertebral body (L1) in elderly women, investigate the influence of VD on vertebral stiffness (VS) by biomechanical analysis using quantitative computed tomography-based finite element analysis (QCT-FEA). METHODS: Two hundred seventy eight participants were recruited, and underwent QCT scan. Measured VD angles of L1, and constructed QCT-FEA models of L1 with the minimum (0.59°), median (5.79°) and maximum (11.15°) VD angles, respectively. Loads in two directions were applied on the upper edge of L1 with a force of 700 N, and vertebral stiffness (VS) was defined as the ratio of 700 N and displacement at the superior reference point: (1) perpendicular to the upper edge of L1 (defined as VS-U); (2) perpendicular to the lower edge of L1(defined as VS-L). RESULTS: Age was very weak positively correlated with VD angle, moderate negatively correlated with vBMD, and moderate negatively correlated with VS (P < 0.05). VS-U was significantly different among three VD angles, so was VS-L (P < 0.001). VS-U was higher than VS-L in 5.79° and 11.15° VD angles (P < 0.05), however no difference in 0.59° VD angles (P > 0.10). CONCLUSIONS: VD angle of L1 was slightly increased with age and not correlated with vBMD, and VS was moderate negatively correlated with age, showing that the vertebral body was more likely to fracture with aging. VS-U and VS-L were gradually decreased with the increase of VD angle, and VS-L was lower than VS-U with the increase of VD angle, which showed that vertebral body was more prone to fracture when the load was perpendicular to the lower edge of the vertebral body as the VD angle increasing.