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Abstract Objective It was aimed to compare visceral adiposity index (VAI) levels in patients with normal bone mineral density (BMD), osteopenia, and osteoporosis. Methods One hundred twenty postmenopausal women (40 with normal BMD, 40 with osteopenia, and 40 with osteoporosis) between the ages of 50 to 70 years were included in the study. For females, the VAI was calculated using the formula (waist circumference [WC]/[36.58 + (1.89 x body mass index (BMI))]) x (1.52/High-density lipoprotein [HDL]-cholesterol [mmol/L]) x (triglyceride [TG]/0.81 [mmol/L]). Results The time of menopause from the beginning was similar in all groups. Waist circumference was found to be higher in those with normal BMD than in the osteopenic and osteoporotic groups (p = 0.018 and p < 0.001, respectively), and it was also higher in the osteopenic group than in the osteoporotic group (p = 0.003). Height and body weight, BMI, blood pressure, insulin, glucose, HDL-cholesterol, and homeostasis model assessment-insulin resistance (HOMA-IR) levels were similar in all groups. Triglyceride levels were found to be higher in the normal BMD group, compared with the osteoporotic group (p = 0.005). The level of VAI was detected as higher in those with normal BMD, compared with the women with osteoporosis (p = 0.002). Additionally, the correlation analysis showed a positive correlation between dual-energy X-ray absorptiometry (DXA) spine T-scores, WC, VAI, and a negative correlation between DXA spine T-scores and age. Conclusion In our study, we found higher VAI levels in those with normal BMD, compared with women with osteoporosis. We consider that further studies with a larger sample size will be beneficial in elucidating the entity.
Resumo Objetivo O objetivo foi comparar os níveis de índice de adiposidade visceral (IVA) em pacientes com densidade mineral óssea (DMO) normal osteopenia e osteoporose. Métodos Cento e vinte mulheres na pós-menopausa (40 com DMO normal 40 com osteopenia e 40 com osteoporose) com idades entre 50 e 70 anos foram incluídas no estudo. Para o sexo feminino o VAI foi calculado pela fórmula (circunferência da cintura [CC]/[36 58 + (1 89 x índice de massa corporal (IMC))]) x (1 52/lipoproteína de alta densidade [HDL]-colesterol [mmol/L]) x (triglicerídeo [TG]/0 81 [mmol/L]). Resultados O tempo de menopausa desde o início foi semelhante em todos os grupos. A circunferência da cintura foi maior naqueles com DMO normal do que nos grupos osteopênicos e osteoporóticos (p = 0 018 e p < 0 001 respectivamente) e também foi maior no grupo osteopênico do que no grupo osteoporótico (p = 0 003) . Altura e peso corporal IMC pressão arterial insulina glicose HDL-colesterol e os níveis de avaliação do modelo de homeostase-resistência à insulina (HOMA-IR) foram semelhantes em todos os grupos. Os níveis de triglicerídeos foram maiores no grupo DMO normal em comparação com o grupo osteoporótico (p = 0 005). O nível de VAI foi detectado como maior naquelas com DMO normal em comparação com as mulheres com osteoporose (p = 0 002). Além disso a análise de correlação mostrou uma correlação positiva entre a absorciometria de raios-X de dupla energia (DXA) nas pontuações T da coluna CC VAI e uma correlação negativa entre as pontuações T da coluna DXA e a idade. Conclusão Em nosso estudo encontramos níveis mais elevados de VAI naquelas com DMO normal em comparação com mulheres com osteoporose. Consideramos que novos estudos com maior tamanho amostral serão benéficos na elucidação da entidade.
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Humans , Female , Middle Aged , Aged , Osteoporosis , Bone Diseases, Metabolic , Adiposity , ObesityABSTRACT
ABSTRACT Objective: This study aimed to determine the differences in body fat distribution and central obesity indicators using dual-energy X-ray absorptiometry (DXA), adiposity indices, and anthropometric indices between women with and without polycystic ovary syndrome (PCOS). Materials and methods: Clinical and laboratory examination history, including transvaginal ultrasound, fasting blood samples, anthropometric measurements, and DXA scans were conducted in 179 women with PCOS (PCOS group) and 100 without PCOS (non-PCOS group). The volunteers were grouped by body mass index (BMI): normal (18-24.9 kg/m2), overweight (25-29.9 kg/m2), or obese (>30 kg/m2). The visceral adiposity index (VAI) and lipid accumulation product (LAP) were calculated, regions of interest (ROIs) were determined, and the fat mass index (FMI) was calculated using DXA. Results: VAI, LAP, ROIs, FMI, and adiposity indices by DXA were higher in women with PCOS and normal BMI. In both PCOS and non-PCOS groups, the ROIs progressively increased from normal BMI to overweight and obese, and from overweight to obese. Obese women with PCOS showed high trunk fat mass. However, obesity was not able to modify these trunk/periphery fat ratios in PCOS from overweight to higher BMI. These variables were associated with the incidence of PCOS. Conclusion: In women with PCOS and normal BMI, both DXA and the adiposity indices, VAI and LAP, are more sensitive methods to evaluate total body fat and fat accumulation in the central abdominal region. It was also observed that as BMI increased, the differences in measurements between women with and without PCOS decreased.
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Objective:To evaluate the effects of split-filter dual-energy CT (SF-DECT) in improving image quality at low doses in the process of abdominal examinations for children.Methods:A preliminary study was conducted using child phantoms. Furthermore, 20 children aged 4-6 years were recruited prospectively for clinical validation from June 2020 to December 2020. Conventional single-energy CT (SECT) and SF-DECT were employed to scan the abdominal areas of the phantoms and children. Then, the CT values, image noise, contrast to noise ratios (CNRs), and image subjective scores of SF-DECT and SECT were compared under various doses (1, 2, 3, and 4 mGy).Results:For the phantoms under doses of 3 and 4 mGy, SF-DECT decreased the image noise by 18.9% and 23.6%, respectively, and increased the liver and kidney CNRs (CNR liv and CNR kid) by 12.8% and 31.9% at most, respectively, compared to SECT ( Z = 3.00, 5.17, P < 0.001). For children, SF-DECT decreased image noise ( Z = 4.64, P < 0.001) and increased CNR liv and CNR kid ( Z = 3.78, 3.39, P < 0.001). For both the phantoms and the children, the subjective scores of images scanned using the SF-DECT were higher than those scanned using the SECT ( Z = 1.96-3.80, P < 0.05). Conclusions:Compared with SECT, SF-DECT can improve the quality of children′s abdominal images. This technique has a certain prospect of optimizing abdominal CT for children. However, it is necessary to conduct in-depth clinical research to verify the result.
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Objective To analyze the pulmonary perfusion defect index (PPDI) of dual-energy computed tomography (CT) and pulmonary artery obstruction index (PAOI) of conventional CT angiography, and to investigate the clinical application value of dual-energy CT perfusion imaging in the examination of patients with acute pulmonary embolism. Methods A retrospective study was conducted on 21 patients diagnosed with acute pulmonary embolism in Weifang People's Hospital from January 1, 2022 to December 31, 2022. PPDI, PAOI, and maximum plasma D-dimer concentration (mg/L) were calculated. According to the 2019 ESC Guidelines, the patients were divided into low-risk group (n = 8) and medium-risk group (n = 12). The Mann-Whitney U test was used for between-group comparisons. The Spearman’s rank correlation coefficient was used to analyze the correlations between PAOI, PPDI, and plasma D-dimer concentration. Results The PPDI, PAOI, and D-dimer values in the low-risk group were 3.33 (2.09, 4.58), 5.00 (3.13, 5.00), and 0.67 (0.52, 0.79), respectively. The PPDI, PAOI, and D-dimer values in the middle-risk group were 8.34 (5.42, 12.50), 12.50 (8.13, 15.00), and 1.18 (0.86, 2.87), respectively. The Z-values of comparison between the two groups were −3.092, −3.650, and −3.318, respectively (all P < 0.05). There were significant differences in PPDI, PAOI, and D-dimer between the low-risk and middle-risk groups (P < 0.05). Positive correlations were observed between PPDI and PAOI, between PPDI and D-dimer, and between PAOI and D-dimer (rs = 0.869, 0.918, 0.909, all P < 0.05). Conclusion Both PPDI and PAOI can be used for the clinical examination of patients with acute pulmonary embolism and evaluation of the severity of the disease. Compared with conventional CT, dual-energy CT perfusion imaging is more efficient in the diagnosis of acute pulmonary embolism, and facilitates accurate clinical treatment.
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The incidence and recurrence rates of urinary stone diseases have remained high recently, and stone analysis is of great significance for further understanding of the pathophysiological processes of urinary stones and to develop effective prevention strategies and precise treatment. Imaging evaluation is the main method of preoperative stone analysis, and dual-energy CT has shown its potential in identifying common main components of stones. The emergence of photon counting spectral CT is expected to achieve accurate analysis of stone components at the pixel level. The intraoperative stone analysis mainly relies on the automatic recognition of endoscopic images, and using machine learning algorithms can more reliably predict common stone composition. It is of great significance for stone analysis and assessment of metabolic causes by introducing morpho-constitutional classification (MCC)and observing and describing the papillary renal lesions during operation. This article reviews the progress of preoperative and intraoperative stone analysis, in order to improve clinicians' understanding of the importance of stone analysis, and provide a direction for further clinical research.
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ABSTRACT Trabecular bone score (TBS) is an indirect and noninvasive measure of bone quality. A low TBS indicates degraded bone microarchitecture, predicts osteoporotic fracture, and is partially independent of clinical risk factors and bone mineral density (BMD). There is substantial evidence supporting the use of TBS to assess vertebral, hip, and major osteoporotic fracture risk in postmenopausal women, as well as to assess hip and major osteoporotic fracture risk in men aged > 50 years. TBS complements BMD information and can be used to adjust the FRAX (Fracture Risk Assessment) score to improve risk stratification. While TBS should not be used to monitor antiresorptive therapy, it may be potentially useful for monitoring anabolic therapy. There is also a growing body of evidence indicating that TBS is particularly useful as an adjunct to BMD for fracture risk assessment in conditions associated with increased fracture risk, such as type-2 diabetes, chronic corticosteroid excess, and other conditions wherein BMD readings are often misleading. The interference of abdominal soft tissue thickness (STT) on TBS should also be considered when interpreting these findings because image noise can impact TBS evaluation. A new TBS software version based on an algorithm that accounts for STT rather than BMI seems to correct this technical limitation and is under development. In this paper, we review the current state of TBS, its technical aspects, and its evolving role in the assessment and management of several clinical conditions.
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Abstract Objective Population-level monitoring of body composition requires accurate, biologically-relevant, yet feasible methods for estimating percent body fat (%BF). The aim of this study was to develop and cross-validate an equation for %BF from Body Mass Index (BMI), age, and sex among children with intellectual disability (ID). This study further aimed to examine the performance of an existing BMI-based equation (Deurenberg equation) for %BF in children with ID. Method Participants were 107 children (63 boys; aged 6-15 years) with ID randomly allocated to development (n= 81) and cross-validation (n= 26) samples. Dual-Energy X-Ray Absorptiometry provided the criterion %BF. Results The model including BMI, age, and sex (0 = male; 1 = female) had a significant goodness-of-fit in determining %BF (p< 0.001; R2= 0.69; SEE =5.68%). The equation was: %BF = - 15.416 + (1.394 × BMI) + (4.538 × age) - (0.262 × age2) + (5.489 × sex). The equation was cross-validated in the separate sample based on (i) strong correlation (r = 0.82; p< 0.001) and non-significant differences between actual and predicted %BF (28.6 ± 9.6% and 30.1 ± 7.1%, respectively); (ii) mean absolute error (MAE) = 4.4%; and (iii) reasonable %BF estimations in Bland-Altman plot (mean: 1.48%; 95% CI: 12.5, -9.6). The Deurenberg equation had a large %BF underestimation (mean: -7.1%; 95% CI: 5.3, -19.5), significant difference between actual and estimated %BF (28.6 ± 9.7% and 21.5 ± 7.0%, respectively; p< 0.001), and MAE = 8.1%. Conclusions The developed equation with BMI, sex, and age provides valid %BF estimates for facilitating population-level body fat screening among children with ID.
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Objective:To investigate the application value of artificial intelligence in dual-source CT coronary angiography.Methods:The imaging data of 50 patients with coronary artery diseases who received treatment in Benxi Central Hospital from January to December 2021 were retrospectively analyzed. All patients underwent coronary computed tomography angiography examination and coronary arteriography. Coronary computed tomography angiography images were uploaded to the post-processing workstation and post-processed and analyzed by two radiologists. At the same time, the images were also post-processed by AI software and diagnosis reports were generated. In terms of coronary artery stenosis, the diagnostic results provided by AI software were compared with coronary angiography results. In terms of myocardial bridging, the diagnostic results provided by AI software were compared with radiologist's diagnosis. The accuracy of AI software was judged.Results:In the diagnosis of coronary artery stenosis, the sensitivity, specificity, positive predictive value and the negative predictive value of AI software were 93.22%, 81.32%, 76.39% and 94.87% respectively. These were well consistent with coronary arteriography results (Kappa = 0.71, P < 0.001). In the diagnosis of myocardial bridging, the sensitivity, specificity, positive predictive value and the negative predictive value of AI software were 30.77%, 81.45%, 25.81% and 84.87% respectively. These were poorly consistent with radiologists' diagnostic results (Kappa = 0.11, P = 0.162). Conclusion:AI-based dual-source CT coronary angiography is of high value in the diagnosis of coronary artery stenosis, but it is of low value in the diagnosis of myocardial bridging.
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Dual-energy X-ray absorptiometry(DXA) has been widely used for more than 30 years with continuous technological innovations, which makes DXA a reliable and feasible tool for clinical use. In addition to the measurement of bone mineral density for osteoporosis, DXA has a variety of applications, such as vertebral fracture analysis, grading of abdominal aortic calcifications, atypical femur fracture, trabecular bone score, hip structures analysis, finite element analysis and body composition etc. This review is aimed to provide updates on aforementioned application.
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Objective:To compare the consistency between bioelectrical impedance analysis(BIA)and dual-energy X-ray absorptiometry(DXA)in skeletal muscle mass assessment in elderly patients with advanced chronic kidney disease(CKD), and to provide a basis for accurate clinical diagnosis of sarcopenia.Methods:Elderly patients with advanced CKD at the Department of Nephrology of Shanghai Sixth People's Hospital were included.Parameters for physical performance included handgrip strength and gait speed, and body muscle mass was measured by DXA and multifrequency BIA.The consistency between the two methods was assessed by the intraclass correlation coefficient, Bland-Altman analysis and kappa coefficient test.Results:This study included 67 elderly patients with advanced CKD with a mean age of(70.7±6.1)years and an average BMI of(24.6±3.5)kg/m 2.The proportion of enrolled male patients was 61.2% and the mean estimated glomerular filtration rate was(27.7±12.7)ml·min -1·1.73m -2.The intraclass correlation coefficients of muscle mass and appendicular skeletal-muscle mass index(ASMI)measured by BIA and DXA ranged from 0.81 to 0.90.Bland-Altman analysis showed that BIA overestimated muscle mass against DXA, and the mean difference in ASMI was(0.44±0.13)kg/m 2.In addition, there was a moderate agreement between the two measurement methods for determining muscle loss(Kappa=0.47). Conclusions:BIA and DXA offer a fair level of consistency in the assessment of muscle mass in elderly patients with advanced CKD.However, compared with DXA, BIA overestimates muscle mass in elderly patients with CKD.
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Objective:To analyze the effects of two decomposition algorithms of dual-energy cone beam CT (DECBCT) (direct decomposition and iterative decomposition) on the image quality and material decomposition accuracy of different sizes of phantoms.Methods:Different sizes of imaging parts of patients were simulated using the combination of CatPhan604 phantoms and customized annuluses. CBCT with high energy of 140 kVp and low energy of 100 kVp were acquired using the Varian Edge CBCT system. Then the material decomposition of DECBCT images was performed using the two algorithms. The electron density (ED) and contrast-to-noise ratio (CNR) of each material in the CTP682 module were calculated. They were used to assess the decomposition accuracy and image quality of the two algorithms.Results:Based on the values in the Catphan604 manual, both algorithms have high ED accuracy. Only the ED accuracy of four materials of the smallest sized phantom showed statistical difference ( z = -4.21, 4.30, 2.87, 5.45, P < 0.05), but the average relative error was less than 1%. The CNR of the iterative decomposition algorithm was significantly higher than that of the direct decomposition, increasing by 51.8%-703.47%. The increase in the phantom size significantly reduced the accuracy of ED, and the increased amplitude of the relative error was up to a maximum of 2.52%. The large phantom size also reduced the image quality of iterative decomposition, and the decreased amplitude of CNR was up to a maximum of 39.71. Conclusions:Compared with the direct decomposition, the iterative decomposition algorithm can significantly reduce the image noise and improve the contrast without losing the accuracy of electron density in the DECBCT construction of different sizes of phantoms.
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Objective:To analyze the value of dual energy CT parameters combined with serum procollagen Ⅰ N-terminal propeptide (PⅠNP) and beta C-terminal cross-linked telopeptide of type Ⅰ collagen (β-CTX) in differential diagnosis of spinal bone metastasis from lung cancer and myeloma.Methods:The clinical data of 54 patients with spinal bone metastasis from lung cancer and 50 patients with myeloma in Jincheng People′s Hospital from October 2019 to March 2021 were analyzed retrospectively. All patients were examined by dual energy CT on the day of admission, and the CT values at the energy levels of 40 to 80 keV (energy interval of 10 keV) were recorded. The serum PⅠNP and β-CTX levels were detected by chemiluminescent assay before treatment. The pathological examination results were taken as gold standard, and the CT values at the energy levels of 40 to 80 keV by dual energy CT and serum PⅠNP and β-CTX levels were compared between 2 groups. Receiver operating characteristic (ROC) curve was used to analyze the differential diagnosis value of the CT values at the energy levels of 40 to 80 keV, serum PⅠNP and β-CTX levels alone and combination.Results:The CT values at the energy levels of 40 to 80 keV by dual energy CT and serum PⅠNP and β-CTX levels in patients with spinal bone metastasis from lung cancer were significantly higher than those in patients with myeloma: 79.86 (61.20, 116.32) HU vs. 58.29 (46.92, 64.03) HU, 64.48 (50.27, 90.08) HU vs. 45.78 (38.59, 56.75) HU, 57.35 (43.31, 78.04) HU vs. 43.62 (36.91, 54.06) HU, 52.05 (42.98, 75.79) HU vs. 41.26 (32.84, 51.76) HU, 45.52 (38.55, 63.59) HU vs. 36.68 (28.72, 49.83) HU, 66.35 (31.15, 81.97) μg/L vs. 31.38 (27.76, 34.50) μg/L and 0.61 (0.48, 0.67) μg/L vs. 0.49 (0.47, 0.52) μg/L, and there were statistical differences ( P<0.05 or <0.01). ROC curve analysis result showed that the sensitivity of the combination of the CT values at the energy levels of 40 to 80 keV by dual energy CT was higher than those alone (83.33% vs. 59.26%, 61.11%, 62.96%, 64.81% and 66.67), the area under the curve (AUC) was also higher than those alone (0.882 vs. 0.798, 0.811, 0.817, 0.801 and 0.773), and there were statistical differences ( P<0.01 or <0.05); the sensitivity of the combination of serum PⅠNP and β-CTX levels was higher than those alone (81.48% vs. 57.41% and 62.96%), the AUC was higher than those alone (0.829 vs. 0.753 and 0.729), and there were statistical differences ( P<0.01 or <0.05); the sensitivity of all indexes combined in the differential diagnosis of spinal bone metastasis from lung cancer and myeloma was higher than those of the combination of the CT values at the energy levels of 40 to 80 keV by dual energy CT, the combination of serum PⅠNP and β-CTX levels (98.15% vs. 83.33% and 81.48%), the same as AUC (0.976 vs. 0.882 and 0.829), and there were statistical differences ( P<0.01); there were no significant differences in the specificity of each index alone and combination ( P>0.05). Conclusions:Compared with myeloma, the CT values at the energy levels of 40 to 80 keV by dual energy CT, serum PⅠNP and β-CTX levels in patients with spinal bone metastasis from lung cancer are increased, and the combination of the above indexes has ideal value in differential diagnosis of the two diseases.
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Objective:To investigate the application value of dual-energy CT in the differential diagnosis of lung metastases and benign nodules in breast cancer.Methods:The data of 96 patients with pathology-confirmed breast cancer at the Fifth Affiliated Hospital of Wenzhou Medical University from March 2017 to June 2021 were analyzed retrospectively. All patients received dual-energy chest CT scans within 2 weeks before surgery. All 96 patients were female, aged 31-84 (56±12) years. A total of 207 pulmonary nodules from 96 patients were classified into 81 lung metastases and 126 benign nodules according to pathological findings. Conventional CT features [longest diameter, boundary, location and CT value difference between arterial and venous phases (ΔCT) of nodules] and dual-energy CT parameters [standardized iodine concentration (NIC), slope of energy spectrum (λ HU) and normalized effective atomic number (nZ eff) in arterial and venous phases] were analyzed and measured. The χ 2 test, independent samples t test and Kruskal-Wallis rank-sum test were used to analyze the differences of conventional CT features and dual-energy CT parameters between lung metastases and benign nodules. First, the least shrinkage and selection operator (LASSO) regression method was used to screen conventional CT features and dual-energy CT parameters, and then logistic regression analysis was performed to screen out independent risk factors for lung metastases. Receiver operating characteristic (ROC) curves were used to evaluate the efficacy of CT parameters alone and logistic model in differentiating lung metastases from benign lung nodules. Results:There were statistically significant differences between lung metastases and benign nodules in longest diameter, ?CT, NIC, λ HU and nZ eff in arterial and venous phases (all P<0.05). LASSO regression and binary logistic regression analysis showed that the venous phase λ HU (OR=59.413, 95%CI 14.233-248.002, P<0.001) and the venous phase nZ eff (OR=4.508, 95%CI 2.787-7.290, P<0.001) were independent risk factors for predicting lung metastases. Among them, the venous phase λ HU had the highest diagnostic efficiency, with an area under curve (AUC) of 0.794 and an accuracy of 74.88%. The AUC of the logistic model constructed by combining the venous phase λ HU and the venous phase nZ eff could reach 0.958, and the accuracy was improved to 92.27%, which was significantly higher than the efficacy of the two alone ( Z=6.02, 9.54, all P<0.001). Conclusion:Dual-energy CT has great application value in the identification of lung metastases and benign nodules in patients with breast cancer, especially when combined with venous phase λ HU and venous phase nZ eff, the diagnostic efficiency is further improved.
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RESUMEN En diciembre de 2019 se informaron casos de una neumonía grave en la ciudad de Wuhan, China. En enero de 2020 fue identificado el nuevo virus, SARS-CoV-2, que producía esta enfermedad altamente contagiosa denominada COVID-19, y alcanzó nivel de epidemia en marzo de ese propio año. Existe un protocolo establecido para su diagnóstico, donde se encuentran los estudios de imagen, entre ellas la tomografía de tórax con técnica de energía dual. Las características de los hallazgos anatómicos pulmonares y vasculares en las imágenes tomográficas de pacientes con COVID-19, su distribución, y la relación con el tiempo transcurrido desde el inicio de los síntomas, juegan un papel importante en el control y tratamiento de esta enfermedad, lo que refleja el valor diagnóstico de esta técnica.
ABSTRACT In December 2019 some cases of a severe pneumonia were reported in the city of Wuhan, China. In January 2020, the new virus, SARS-CoV-2, which produced this highly contagious disease called COVID-19, was identified and it reached epidemic level in March 2020. There is an established protocol for its diagnosis, which includes imaging studies, including chest dual energy computed tomography. The characteristics of pulmonary and vascular anatomical findings in tomographic images of patients with COVID-19, their distribution, and their relationship with the time elapsed since the onset of symptoms, play an important role in the control and treatment of this disease, reflecting the diagnostic value of this technique.
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Abstract Objectives: To investigate the diagnostic performance of single-source dual-energy computed tomography (DECT) based on gemstone spectral imaging technology (including Discovery CT750HD and Revolution CT) in patients with suspected feet/ankles gouty arthritis, and evaluate the urate deposition with a novel semi-quantitative DECT scoring system. Methods: A total of 196 patients were consecutively included. Feet and ankles were evaluated in all patients by single-source DECT scan. The 2015 EULAR/ACR criteria were used as the reference for the diagnosis of gout. The sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of DECT for the diagnosis of gout in the early (≤1 year), middle (1-3 years), and late (> 3 years) disease durations were calculated. Besides, a novel semi-quantitative DECT scoring system was assessed for the measurement of urate deposition, and the correlation between the scores and the clinical and serological data were also evaluated. Moreover, the influences of artifacts on the diagnostic performance of DECT were also determined. Results: The sensitivity, specificity, and AUC of DECT in 196 patients were 38.10, 96.43%, and 0.673 in the early-stage group; 62.96, 100.00%, and 0.815 in the middle-stage group; and 77.55, 87.50%, and 0.825 in the late-stage group, respectively. The overall diagnostic accuracies in the AUC of DECT (Discovery CT750HD and Revolution CT) in the middle and late stages of gout were higher than that in the early stage of gout. Besides, the monosodium urate crystals were deposited on the first metatarsophalangeal joints and ankles/midfeet. Age, the presence of tophus, bone erosion, and disease duration considerably affected the total urate score. No statistical difference in the positive detection of nail artifact, skin artifact, vascular calcification, and noise artifact was found between the case and control groups. Conclusion: DECT (Discovery CT750HD and Revolution CT) showed promising diagnostic accuracy for the detection of urate crystal deposition in gout but had limited diagnostic sensitivity for short-stage gout. Longer disease duration, the presence of tophus, and bone erosion were associated with the urate crystal score system. The artifacts do not remarkably affect the diagnostic performance of DECT in gout.
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Abstract Objectives: To investigate the frequency of monosodium urate (MSU) crystal deposits on dual-energy computed tomography (DECT) in patients with clinical diagnosis of gout and the factors associated MSU crystal positivity. Methods: This study was conducted in patients with clinical diagnosis of gout who underwent DECT. Clinical features were compared between patients with positive and those with negative DECT results. A logistic regression analysis was performed to determine the factors associated with MSU crystal positivity on DECT. Results: A total of 148 patients with clinical diagnosis of gout were included, and MSU crystal deposition on DECT was observed in 64 patients (43.3%). The patients with positive DECT results were more likely to have renal insufficiency, longer disease duration, and higher serum urate level than those with negative. In the multivariable analysis, first gout attack (odds ratio 0.462; 95% confidence interval 0.229-0.931, p = 0.031) was associated with a less likely MSU crystal deposit-positive DECT result. In the subgroup analysis of patients with first attack, serum urate level > 8 mg/dL was associated with DECT positivity. Conclusion: Of the patients with clinical diagnosis of gout, those with renal insufficiency, longer disease duration, and high serum urate level were more likely to be positive of gout on DECT. First gout attack was associated with less likely to be positive for MSU crystal on DECT. Thus, performing DECT scan in the selected patients who had characteristics that highly probability of DECT positivity could increase positive predictive value.
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Virtual monochromatic images (VMI) that reconstructed on dual-energy computed tomography (DECT) have further application prospects in radiotherapy, and there is still a lack of clinical dose verification. In this study, GE Revolution CT scanner was used to perform conventional imaging and gemstone spectral imaging on the simulated head and body phantom. The CT images were imported to radiotherapy treatment planning system (TPS), and the same treatment plans were transplanted to compare the CT value and the dose distribution. The results show that the VMI can be imported into TPS for CT value-relative electron density conversion and dose calculation. Compared to conventional images, the VMI varies from 70 to 140 keV, has little difference in dose distribution of 6 MV photon treatment plan.
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Electrons , Phantoms, Imaging , Tomography Scanners, X-Ray Computed , Tomography, X-Ray ComputedABSTRACT
Objective:To investigate the feasibility of predicting lateral cervical lymph node metastasis (LLNM) in patients with papillary thyroid carcinoma (PTC) based on the nomogram constructed by dual-energy CT data.Methods:In total 417 patients with PTC confirmed by pathology in Tianjin First Central Hospital from January 2015 to December 2018 were retrospectively analyzed as a training group. Internal validation was conducted, including 139 patients in the LLNM group and 278 patients in the non-LLNM group. A total of 169 PTC patients from January 2019 to June 2020 were included as an external validation group, including 58 patients in the LLNM group and 111 patients in the non-LLNM group. The morphological characteristics of the primary thyroid lesions on dual-energy CT iodine maps were analyzed, including tumor location, maximum diameter, calcification, and extrathyroidal extension (ETE). Iodine concentration (IC) of the PTC parenchyma and the internal carotid artery on the same level in the arterial and venous phases were measured, and normalized iodine concentration (NIC) was calculated. The independent risk factors for LLNM were obtained by univariate and multivariate logistic regression analysis. Base on the results, a prediction model was constructed and expressed in the form of a nomogram. The internal and external validation of the model was carried out using ROC curve.Results:Multivariate binary logistic regression analysis showed that the lesion location in the upper polar of the thyroid, the presence of ETE, IC in arterial phase>2.9 mg/ml, IC in the venous phase>3.2 mg/ml, and NIC in the arterial phase>0.21 were independent risk factors for LLNM prediction. The nomogram based on the above factors was constructed with an area under the ROC curve (AUC) of 0.895 (95%CI 0.862-0.923). With a cut-off value of 0.79, the sensitivity and specificity were 86.3% and 75.2%, respectively. As for the external validation group, the AUC of the model was 0.887 (95%CI 0.830-0.931), with the sensitivity of 82.8%, and the specificity of 81.1%.Conclusion:The application values of the nomogram model based on dual-energy CT data in preoperative evaluation of the possibility of LLNM of PTC patients has been verified. The model constructed in this study might be helpful with the individualized treatment in a certain degree.
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Objective:To explore the application value of single source dual energy CT (DECT) scanning technique in improving the image quality of the pancreas.Methods:Imaging data of 21 patients with normal pancreas and 36 patients with pancreas related diseases in the First Affiliated Hospital of Naval Medical University from July 2021 to August 2021 were collected. All the patients first underwent multi-slice CT (MDCT) scan with no-contrast, and then dynamic enhanced MDCT scan. And the DECT scan was used in the delay period. Virtual single energy images (VMI, 40~100keV) of normal pancreas and mixed energy images of pancreatic lesions (PI, 80 and 140kVp) were obtained. The regions of interest (ROI) of fat on abdominal wall, normal pancreas and abdominal aorta were delineated, the CT values and standard deviation (SD) of each ROI were measured and recorded, and the pancreatic signal-to-noise ratio (SNR) and contrast-to-noise ratio (SNR) of each energy image were calculated. The objective index and subjective score of VMI(40-100keV) and PI (80kVp and 140kVp) with iodine (water) base map and VMI best CNR were compared between groups. The correlation between VMI(40-100keV) and PI(80, 140kVp) with iodine (water) base map and VMIbest CNR was analyzed by univariate regression.Results:In VMI(40-100keV) of normal pancreas, the highest SNR value was VMI best CNR and iodine (water) base map, and the highest CNR values were VMI 60keV and iodine (water) base map. There were significant differences on SNR and CNR values between different energy VMI and iodine (water) base map ( P<0.05). Among the four images of PI 80kVp, PI 140kVp, VMI best CNR and iodine (water) base map for pancreatic lesions, the SNR and CNR values of iodine (water) base map were the highest. The SNR and CNR values of VMI best CNR were higher than those of PI 80kVp, and the differences were statistically significant ( P<0.05). The lesion significance and edge sharpness score of iodine (water) base map was the highest, which was better than other groups; the lesion significance and edge sharpness score of VMI best CNR was better than PI 140kVp, and the differences were statistically significant ( P<0.05). The results of univariate regression analysis showed that the SNR values of PI 80kVp, PI 140kVp and VMI best CNR for pancreatic lesions were positively correlated with those of the iodine (water) base map ( P<0.05), the CNR values of PI 140kVp and VMI best CNR images were positively correlated with the iodine (water) base map ( P<0.05), and the SNR and CNR values of PI 140kVp were positively correlated with VMI best CNR ( P<0.05). Conclusions:VMI with different energy and iodine (water) base maps can be obtained by single source DECT enhanced scanning of pancreas related diseases. The VMI best CNR was the best among all VMIs, while the SNR and CNR values of iodine (water) base maps were the highest in all images. The VMI best CNR and iodine (water) base maps can improve the image quality of pancreas related diseases.
ABSTRACT
Background: Equations for the evaluation of fat-free mass (FFM) and fat mass (FM) with Bioelectrical impedance analysis (BIA) were formulated in Caucasian populations. International recommendations suggest that population-specific equations should be formulated. Aim: To validate an equation previously formulated in Chileans adults and compare it to a new equation generated on an independent sample. Material and Methods: In 108 adult volunteers aged 38.1±14.1 years (44% males), with a body mass index (BMI) of 25.1± 4.1 kg/m2, body composition was measured by BIA (Bodystat) and dual X-ray absorptiometry (DXA: Lunar Prodigy). Body composition estimated using Schifferli equation and BIA were compared with DEXA, by the Bland-Altman method and simple linear regression. Results: FFM and FM measured by DXA were 45.2 ± 9.8 kg and 29.6 ± 11.7 % respectively. Resistance was 467.7 ± 76.3 ohm. Schifferli equation and BIA significantly overestimated FFM by 7.3 and 7.4 kg, respectively. The error was higher for high levels of FFM (slope β < 1, p < 0.01). Both equations underestimated FM measured by DXA (averages of 7.5 and 7.8%, respectively, p < 0.01), without a differential bias for Schifferli equation, but with a bias in low levels of FM measured with BIA (slope β < 1, p < 0.01). Estimation biases could be eliminated using the regression coefficients. Conclusions: Both equations behave similarly and have biases, although less with Schifferli. Statistically correcting for biases, the new adjusted equations provide clinically valid estimates of FFM and FM. Equations should not only be population-specific, but also device-specific.