Value Of Computed Tomography Research Articles

The efficacy of clinicopathological and imaging features in differentiating benign from malignant parotid micro- and minitumors: a retrospective analysis

ObjectiveTo compare clinicopathological and imaging and features of micro- and minitumors of the parotid gland and provide a reference for preoperative prediction of benign vs. malignant status. Study DesignPatients with parotid gland tumors treated surgically were selected. Relevant clinicopathological and imaging data were collected for patients with maximum tumor diameters ≤ 20 mm on preoperative computed tomography (CT). The lesions were divided into two groups, microtumors and minitumors, based on maximum tumor diameter. CT imaging features of benign and malignant tumors were compared through binary logistic regression analysis. ResultsMicrotumors and minitumors were categorized by maximum diameters < 10 mm (n = 74) and 10-20 mm (n = 611), respectively. Benign and malignant minitumors exhibited significant differences in boundary, tumor density, margin morphology, spiculation margin, and CT values in the plain and arterial phase (P < 0.05), resembling those found in typical malignant parotid gland tumors. However, no significant differences were observed between benign and malignant microtumors. Logistic regression analysis identified boundary, margin morphology, and spiculation margin as independent predictors of malignancy. The prediction model excelled in identifying benign lesions but was less successful in identifying malignancies. ConclusionParotid gland minitumors had imaging features similar to typical larger malignant tumors. Active exclusion of the malignant risk and early surgical treatment is recommended for these tumors. Statement of Clinical RelevanceThis study analyzed the clinicopathological and imaging features of micro- and minitumors of the parotid gland to provide a reference for preoperative prediction and treatment. Active exclusion of malignant risk and early surgical treatment is recommended for small parotid tumors.

Optimization of Routine Pediatric Computed Tomography Examinations in Hawassa City, Sidama Regional State, Ethiopia

Computed tomography (CT) has considerable impact in patient care. However, it is the most irradiating medical imaging technique in diagnostic radiology department. Optimization of pediatric CT is not well-practiced in developing countries. Protocols for some age groups were missed, and scan parameters are not adapted to the patient body size and age group. Furthermore, there are no established diagnostic reference levels to enhance dose optimization for pediatric patients at the local, regional, and national levels. Therefore, this study aimed to assess the optimization of routine pediatric CT examinations in Hawassa city, Ethiopia. A total of 360 pediatric dose records were reviewed for routine pediatric CT performed between January 1st, 2021 - May 30th, 2022. The data were analyzed using the statistical package for social science version 25 software. The Local Diagnostic Reference Levels (LDRLs) were established at the 75th percentile of CT dose quantities. The average KVp, mAs, and scan length used for pediatric head, chest, and abdomen CT were (112.8, 260.6, and 19.8), (112.9, 64.7, and 31.5), and (113.3, 79.4, and 32.9) respectively. The range of the established LDRLs in terms of volumetric CT dose index for the head, chest, and abdomen CT were (31.5 to 47, 2.3 to 6.1, 1.7 to 4.7) mGy. Whereas the range in terms of dose length product per scan for the head, chest, and abdomen CT were (723.4 to 1126.7, 55.9 to 258.9, and 38.1 to 242.5) mGy cm respectively. The obtained results show that the LDRLs for volumetric CT does index for head and chest CT were equivalent to the international studies. Whereas the local DRLs in terms of dose length product per scan were higher than the reports other studies except in Japan where the values for chest CT were comparable to the results of this study. Finally, the findings suggested that non-optimized pediatric head and chest CT were performed across all age groups.

A Retrospective Analysis of the Computed Tomography Findings and Diagnosis of 53 Cases of Elastofibroma in the Infrascapular Region.

In this work, we have used histopathology as the gold standard for the diagnosis, calculated the sensitivity and positive predictive value (PPV) of computed tomography (CT), and analyzed the CT and clinical characteristics of pathologically proven elastofibromas. A systematic retrospective analysis was performed on all patients with infrascapular lesions who were treated in the hospital from 2006 to 2018. CT and histopathological examinations were performed for all cases, and the CT sensitivity and PPV for the diagnosis of elastofibroma were calculated. 12 of 53 cases (20 lesions) underwent enhanced CT scan after CT plain scan, and the related clinical and CT features of elastofibromas have been discussed. Of the 54 patients treated during the study, CT diagnosis was consistent with histopathology in 53 cases. One was a false-positive patient. The PPV and sensitivity of the CT in the diagnosis of elastofibroma were 93.3% (95% CI 68.0%-99.8%) and 100%, respectively. The CT values of 12 patients with 20 lesions on plain and enhanced scans were statistically significant (P=0.001). The prevalence of elastofibromas in males and females was statistically significant (P=.000). There was no statistically significant difference in the incidence of left and right elastofibromas (P=0.752). There was no significant difference in the volume of left and right lesions (P=0.209) and the volume of elastofibromas between males and females (P=.474). CT is the most practical tool for the evaluation of elastofibromas in the infrascapular region.

Dynamic deformation and meso-structure of coarse-grained saline soil under cyclic loading with freeze-thaw cycles

The cumulative deformation properties of subgrade soil under cyclic traffic loads are critical for optimizing pavement structure design and ensuring long-term highway structural performance. This study aims to investigate the coupling effect of freeze-thaw cycles and cyclic loads on the cumulative deformation behaviors and meso-structure of coarse-grained saline soil (CGSS) subgrade filling in high-cold areas. Dynamic triaxial tests and computed tomography (CT) scanning were conducted to analyze the CGSS under different working conditions. The research focused on the dynamic deformation development and damage evolution under varying freeze-thaw cycles and load amplitudes. The research results show that the cumulative deformation behavior of CGSS under cyclic loading is relatively sensitive to the freeze-thaw process. The cumulative dynamic strain increases as the freeze-thaw cycles, with a critical freeze-thaw cycle number of five. The stable cumulative dynamic strain curve exhibits clear three-stage characteristics when plotted in semi-log coordination, with critical loading cycles at 20 and 1,000. After 10–100 loading cycles, the cumulative strain curve quickly shows failure. The CGSS’s low density and pore regions greatly increase after a freeze-thaw cycle. The rise in dynamic stress amplitude notably affects the bonding between soil particles and crystalline salts. The coupling effect of the freeze-thaw cycle and dynamic activity exacerbates the deterioration of soil structure, resulting in variations in CT values within the scanning layer in the final state.

Maxillary bone healing and CT value after Le Fort I osteotomy using absorbable plate system: A retrospective study

This study aimed to evaluate maxillary bone healing and computed tomography (CT) values after Le Fort I osteotomy with sagittal split ramus osteotomy in patients with class II and III malocclusion. Four absorbable plates and screws were used to fix the maxillary segments in all patients. For 112 sides (58 patients), the bone defect areas at the anterior and posterior sites between the maxillary segments were measured using 3-dimensional CT views reconstructed over a constant CT value at 1 week and 1 year postoperatively. Subsequently, CT values at the upper, middle, and lower sites around the osteotomy line in the medial, middle, and lateral regions were measured. The bone defect area after 1 year increased at the anterior site in class III and at both the anterior and posterior sites in class II (P < 0.05). This study suggests that the increase in bone defect area was affected by lower CT values at the middle site of the middle and lateral regions in class II, and that bony defects between fragments in the maxilla could partially remain in both classes II and III within 1 year after Le Fort I osteotomy.

Value of the Air Bronchogram Sign and Other Computed Tomography Findings in the Early Diagnosis of Lung Adenocarcinoma.

The present study aims to explore the application value of the air bronchogram (AB) sign and other computed tomography (CT) signs in the early diagnosis of lung adenocarcinoma (LUAD). The pathological information and CT images of 130 patients diagnosed with N 0 and M 0 solitary pulmonary nodules (diameter ≤3 cm) and treated with surgical resection in our hospital between June 2021 and June 2022 were analyzed. The patients were divided into the benign pulmonary nodule (BPN) group (14 cases), the AIS group (30 cases), the MIA group (10 cases), and the IAC group (76 cases). Among the 116 patients with AIS and LUAD, 96 showed an AB sign. Among the 14 patients with BPN, only 4 patients showed an AB sign. The average CT value and maximum diameter were significantly higher in the IAC group than in the AIS and MIA groups. In the BPN group, 5 patients had an average CT value of >80 HU. Among all LUAD-based groups, there was only 1 patient with a CT value of >60 HU. The identification of the AB sign based on CT imaging facilitates the differentiation between benign and malignant nodules. The CT value and maximum diameter of pulmonary adenocarcinoma nodules increase with the increase of the malignancy degree. The nodule type, CT value, and maximum diameter are useful for predicting the pathological type and prognosis. If the average CT value of pulmonary nodules is >80 HU, LUAD may be excluded.

Preoperative differentiation of gastric schwannomas and gastrointestinal stromal tumors based on computed tomography: a retrospective multicenter observational study.

Gastric schwannoma is a rare benign tumor accounting for only 1-2% of alimentary tract mesenchymal tumors. Owing to their low incidence rate, most cases are misdiagnosed as gastrointestinal stromal tumors (GISTs), especially tumors with a diameter of less than 5 cm. Therefore, this study aimed to develop and validate a diagnostic nomogram based on computed tomography (CT) imaging features for the preoperative prediction of gastric schwannomas and GISTs (diameters = 2-5 cm). Gastric schwannomas in 47 patients and GISTs in 230 patients were confirmed by surgical pathology. Thirty-four patients with gastric schwannomas and 167 with GISTs admitted between June 2009 and August 2022 at Hospital 1 were retrospectively analyzed as the test and training sets, respectively. Seventy-six patients (13 with gastric schwannomas and 63 with GISTs) were included in the external validation set (June 2017 to September 2022 at Hospital 2). The independent factors for differentiating gastric schwannomas from GISTs were obtained by multivariate logistic regression analysis, and a corresponding nomogram model was established. The accuracy of the nomogram was evaluated using receiver operating characteristic and calibration curves. Logistic regression analysis showed that the growth pattern (odds ratio [OR] 3.626; 95% confidence interval [CI] 1.105-11.900), absence of necrosis (OR 4.752; 95% CI 1.464-15.424), presence of tumor-associated lymph nodes (OR 23.978; 95% CI 6.499-88.466), the difference between CT values during the portal and arterial phases (OR 1.117; 95% CI 1.042-1.198), and the difference between CT values during the delayed and portal phases (OR 1.159; 95% CI 1.080-1.245) were independent factors in differentiating gastric schwannoma from GIST. The resulting individualized prediction nomogram showed good discrimination in the training (area under the curve [AUC], 0.937; 95% CI, 0.900-0.973) and validation (AUC, 0.921; 95% CI, 0.830-1.000) datasets. The calibration curve showed that the probability of gastric schwannomas predicted using the nomogram agreed well with the actual value. The proposed nomogram model based on CT imaging features can be used to differentiate gastric schwannoma from GIST before surgery.

Comparison of ureteral stone measurements for predicting the efficacy of a single session of extracorporeal shockwave lithotripsy: one-, two-, and three-dimensional computed tomography measurements.

The objective of this study was to compare the value of one-, two- and three-dimensional computed tomography (CT) measurements for predicting the efficacy of a single session of extracorporeal shock wave lithotripsy (ESWL) in patients with a single ureteral stone. A total of 165 patients were included based on the inclusion and exclusion criteria. Different models were constructed using a combination of patients' clinical data and measurements obtained by manual sketching and automated extraction software. Multivariate logistic regression was used to develop the models. Receiver operating characteristic curves were used to assess the performance of the models. There was good interobserver agreement for all measurements in different dimensions (P < 0.001). We also found that hydronephrosis, the largest diameter, the largest area, volume, and mean CT value were significantly greater in the failure group than in the success group (P < 0.01). Furthermore, all sizes and CT measurement values were found to be independent predictors for predicting efficacy after one session of ESWL (P < 0.05). In addition, the multivariate logistic analysis showed that the area under the curve (AUC) for two-dimensional and three-dimensional measurements was superior to that of one-dimensional measurement (P < 0.01). However, when size alone was included as a measurable predictor, there was no significant difference in the AUC among the one-, two-, and three-dimensional measurements (P > 0.05). In summary, after adjusting for clinical data, two- and three-dimensional measurements combining ureteral stone size and CT values were found to be the best predictors of ESWL efficacy, and software-based three-dimensional measurements should be considered to avoid interobserver variability in clinical practice.

The agreement of different techniques for muscle measurement in diagnosing sarcopenia: a systematic review and meta-analysis.

The measurement or estimation of muscle mass plays an important role in the diagnosis of sarcopenia. Beside dual-energy X-ray absorptiometry (DXA), several modalities, including bioelectrical impedance analysis (BIA), ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI), have helped to provide imaging or electrical biomarkers for muscle mass. This study was aimed at summarizing the diagnostic performance of different techniques on muscle assessment for sarcopenia. Studies on the assessment of muscle mass by different techniques (compared with DXA), published from inception to 12 October, 2023 were retrieved from 4 electronic databases: the Cochrane Library, Embase, PubMed, and Web of Science. The quality assessment of included studies was conducted using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). The sensitivity, specificity, Cohen's kappa coefficient (κ), and Pearson correlation coefficient (r) with 95% confidence intervals (CIs) were pooled and presented via forest plots. The area under the curve (AUC) with 95% CI was pooled and presented via summary receiver operating characteristic (sROC) curve. A total of 28 studies involving 4,926 participants were included. Compared with DXA, the pooled sensitivity and specificity, AUC, and Cohen's κ were 0.79 (95% CI: 0.71-0.86, P<0.001), 0.95 (95% CI: 0.82-0.99, P<0.001), and 0.88 (95% CI: 0.85-0.90), and 0.61 (95% CI: 0.51-0.72) for BIA. The pooled r value between DXA and BIA or US or MRI was 0.94 (95% CI: 0.92-0.96, P<0.001), 0.69 (95% CI: 0.54-0.80, P<0.001), and 0.96 (95% CI: 0.95-0.97, P=0.21), respectively. No qualified original study in relation to CT was included. BIA, US, and MRI would provide acceptable diagnostic accuracy for sarcopenia by evaluating muscle mass in terms of sensitivity, specificity, accuracy, and their higher correlations with DXA. Further investigation is required to elucidate the value of CT in diagnosing sarcopenia.

Value of CT Quantitative Parameters in Prediction of Pathological Types of Lung Ground Glass Nodules

The pathological types of lung ground glass nodules (GGNs) show great significance to the clinical treatment. This study was aimed to predict pathological types of GGNs based on computed tomography (CT) quantitative parameters. 389 GGNs confirmed by postoperative pathology were selected, including 138 cases of precursor glandular lesions [atypical adenomatous hyperplasia (AAH) and adenocarcinoma in situ (AIS)], 109 cases of microinvasive adenocarcinoma (MIA) and 142 cases of invasive adenocarcinoma (IAC). The morphological characteristics of nodules were evaluated subjectively by radiologist, as well as artificial intelligence (AI). In the subjective CT signs, the maximum diameter of nodule and the frequency of spiculation, lobulation and pleural traction increased from AAH+AIS, MIA to IAC. In the AI quantitative parameters, parameters related to size and CT value, proportion of solid component, energy and entropy increased from AAH+AIS, MIA to IAC. There was no significant difference between AI quantitative parameters and the subjective CT signs for distinguishing the pathological types of GGNs. AI quantitative parameters were valuable in distinguishing the pathological types of GGNs.

Dosimetric evaluation in Helical TomoTherapy for lung SBRT using Monte Carlo-based independent dose verification software.

To elucidate the dosimetric errors caused by a model-based algorithm in lung stereotactic body radiation therapy (SBRT) with Helical TomoTherapy (HT) using Monte Carlo (MC)-based dose verification software. For 38 plans of lung SBRT, the dose calculation accuracy of a treatment planning system (TPS) of HT was compared with the results of DoseCHECK, the commercial MC-based independent verification software. The following indices were extracted to evaluate the correlation of dosimetric errors: (1) target volume, (2) average computed tomography (CT) value of the planning target volume (PTV) margin, and (3) average CT value of surrounding 2-mm area of the PTV (PTV ring). Receiver operating characteristic (ROC) analyses determined the threshold for 5% of differences in PTV D95%. Then, the 38 plans were classified into two groups using the cutoff values of ROC analysis for these three indices. Dosimetric differences between groups were statistically compared using the Mann-Whitney U test. TPS of HT overestimated by more than 5% in the PTV D95% in 16 of 38 plans. The PTV ring showed the strongest correlation with dosimetric differences. The cutoff value for the target volume, the PTV margin, and the PTV ring was 14.7 cc, -754 HU, and -708 HU, respectively. The area under the curve (AUC) for the target volume, the PTV margin, and the PTV ring were 0.835, 0.878, and 0.932, respectively. Dosimetric errors more than 5% were observed when the PTV volume was less than 15 cc or when the CT value around the target was less than -700 HU. The TPS of HT might overestimate the PTV dose by more than 5% if any the three indices in this study were below threshold. Therefore, independent verification with an MC-based algorithm should be strongly recommended for lung SBRT in HT.

Reducing image artifacts in sparse projection CT using conditional generative adversarial networks

Reducing the amount of projection data in computed tomography (CT), specifically sparse-view CT, can reduce exposure dose; however, image artifacts can occur. We quantitatively evaluated the effects of conditional generative adversarial networks (CGAN) on image quality restoration for sparse-view CT using simulated sparse projection images and compared them with autoencoder (AE) and U-Net models. The AE, U-Net, and CGAN models were trained using pairs of artifacts and original images; 90% of patient cases were used for training and the remaining for evaluation. Restoration of CT values was evaluated using mean error (ME) and mean absolute error (MAE). The image quality was evaluated using structural image similarity (SSIM) and peak signal-to-noise ratio (PSNR). Image quality improved in all sparse projection data; however, slight deformation in tumor and spine regions was observed, with a dispersed projection of over 5°. Some hallucination regions were observed in the CGAN results. Image resolution decreased, and blurring occurred in AE and U-Net; therefore, large deviations in ME and MAE were observed in lung and air regions, and the SSIM and PSNR results were degraded. The CGAN model achieved accurate CT value restoration and improved SSIM and PSNR compared to AE and U-Net models.

A 4D-CBCT correction network based on contrastive learning for dose calculation in lung cancer

ObjectiveThis study aimed to present a deep-learning network called contrastive learning-based cycle generative adversarial networks (CLCGAN) to mitigate streak artifacts and correct the CT value in four-dimensional cone beam computed tomography (4D-CBCT) for dose calculation in lung cancer patients.Methods4D-CBCT and 4D computed tomography (CT) of 20 patients with locally advanced non-small cell lung cancer were used to paired train the deep-learning model. The lung tumors were located in the right upper lobe, right lower lobe, left upper lobe, and left lower lobe, or in the mediastinum. Additionally, five patients to create 4D synthetic computed tomography (sCT) for test. Using the 4D-CT as the ground truth, the quality of the 4D-sCT images was evaluated by quantitative and qualitative assessment methods. The correction of CT values was evaluated holistically and locally. To further validate the accuracy of the dose calculations, we compared the dose distributions and calculations of 4D-CBCT and 4D-sCT with those of 4D-CT.ResultsThe structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) of the 4D-sCT increased from 87% and 22.31 dB to 98% and 29.15 dB, respectively. Compared with cycle consistent generative adversarial networks, CLCGAN enhanced SSIM and PSNR by 1.1% (p < 0.01) and 0.42% (p < 0.01). Furthermore, CLCGAN significantly decreased the absolute mean differences of CT value in lungs, bones, and soft tissues. The dose calculation results revealed a significant improvement in 4D-sCT compared to 4D-CBCT. CLCGAN was the most accurate in dose calculations for left lung (V5Gy), right lung (V5Gy), right lung (V20Gy), PTV (D98%), and spinal cord (D2%), with the relative dose difference were reduced by 6.84%, 3.84%, 1.46%, 0.86%, 3.32% compared to 4D-CBCT.ConclusionsBased on the satisfactory results obtained in terms of image quality, CT value measurement, it can be concluded that CLCGAN-based corrected 4D-CBCT can be utilized for dose calculation in lung cancer.

Ultrasound Evaluation of Sarcopenia in Patients with Hepatocellular Carcinoma: A Faster and Easier Way to Detect Patients at Risk.

The condition of sarcopenia, defined as a progressive loss of musculoskeletal mass and muscular strength, is very common in patients with hepatocellular carcinoma (HCC) and presents a remarkable association with its prognosis. Thus, the early identification of sarcopenic patients represents one of the potential new approaches in the global assessment of HCC, and there is increasing interest regarding the potential therapeutic implications of this condition. The gold standard for the quantification of muscle mass is magnetic resonance imaging (MRI) or computed tomography (CT), but these techniques are not always feasible because of the high-cost equipment needed. A new possibility in sarcopenia identification could be muscle ultrasound examination. The measurement of specific parameters such as the muscle thickness, muscular fascicles length or pennation angle has shown a good correlation with CT or MRI values and a good diagnostic accuracy in the detection of sarcopenia. Recently, these results were also confirmed specifically in patients with chronic liver disease. This review summarizes the role of imaging for the diagnosis of sarcopenia in patients with HCC, focusing on the advantages and disadvantages of the diagnostic techniques currently validated for this aim and the future perspectives for the identification of this condition.

The role of computed tomography angiography in assessing the correlation between properties of coronary atherosclerotic plaque and blood lipids.

Coronary atherosclerotic heart disease (CAHD) is the leading cause of death in developed countries. This study aimed to explore the correlation between the properties of coronary atherosclerotic plaque and blood lipids using computed tomography angiography (CTA). A total of 83 patients with coronary heart disease were included in this study (males: 50; females: 33; average age: [59 ± 8] years old). They were classified into the stable angina group and unstable angina group. Atherosclerotic plaques were classified as fatty plaques (soft plaques), fibrous plaques, and calcified plaques based on the computed tomography (CT) values. SPSS 17.0 statistical software was used to analyze the correlation between the properties of angina and the CT values of atherosclerotic plaques, blood lipids, and plaque properties, and then compared between the stable and unstable angina groups. There were statistically significant differences in plaque properties between the stable and unstable angina groups (P< 0.001). During CTA examination, we found statistically significant differences in the CT density values of atherosclerotic plaques between the stable and unstable angina groups (P< 0.001). There were statistically significant differences between the properties of angina and the level of blood lipids (P< 0.05). Anginal properties negatively correlated with calcified plaques and positively correlated with non-calcified plaques. Calcified plaques negatively correlated with total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG), and positively correlated with high-density lipoprotein cholesterol (HDL-C). Non-calcified plaques negatively correlated with HDL-C and positively correlated with TC, LDL-C, and TG.

CT-based screening of sarcopenia and its role in cachexia syndrome in pancreatic cancer.

Since computed tomography (CT) is a part of standard diagnostic protocol in pancreatic ductal adenocarcinoma (PDAC), we have evaluated the value of CT for sarcopenia screening in patients with PDAC, intending to expand the diagnostic value of tomographic studies. In our study, we included 177 patients with available CT images. Two groups were formed: Group 1 consisted of 117 patients with PDAC in various locations and stages and Group 2, or the control group, consisted of 60 "nominally healthy" patients with other somatic non-oncological diseases. The body mass index (BMI) was defined as a ratio of patient's weight to the square of their height (kg/m2). CT-based body composition analysis was performed using commercially available software with evaluation of sarcopenia using skeletal muscle index (SMI, cm2/m2). Based on the SMI values, sarcopenia was found in 67.5% of patients (79 out of 117) in the first patient group. It was found more frequently in males (42 out of 56; 75%) than in females (37 out of 61; 60.6%). Additionally, we observed a decrease in muscle mass (hidden sarcopenia) in 79.7% in patients with a normal BMI. Even in overweight patients, sarcopenia was found in 50% (sarcopenic obesity). In patients with reduced BMI sarcopenia was found in all cases (100%). Statistically significant difference of SMI between two groups was revealed for both sexes (p = 0,0001), with no significant difference between groups in BMI. BMI is an inaccurate value for the assessment of body composition as it does not reflect in the details the human body structure. As SMI may correlate with the prognosis, decreased muscle mass- especially "hidden" sarcopenia or sarcopenic obesity- should be reported. The use of CT-based evaluation of sarcopenia and sarcopenic obesity will allow for a better treatment response assessment in patients with cancer cachexia.

Diagnostic accuracy of thoracic CT to differentiate transudative from exudative pleural effusion prior to thoracentesis.

Computed tomography (CT) scan is commonly performed for pleural effusion diagnostis in the clinic. However, there are limited data assessing the accuracy of thoracic CT for the separation of transudative from exudative effusions. The study aimed to determine the diagnostic value of thoracic CT in distinguishing transudates from exudates in patients with pleural effusion. This is a two-center retrospective analysis of patients with pleural effusion, a total of 209 patients were included from The First Affiliated Hospital of Henan University of Science and Technology as the derivation cohort (Luoyang cohort), and 195 patients from the First Affiliated Hospital of Zhengzhou University as the validation cohort (Zhengzhou cohort). Patients who underwent thoracic CT scan followed by diagnostic thoracentesis were enrolled. The optimal cut-points of CT value in pleural fluid (PF) and PF to blood CT value ratio for predicting a transudative vs. exudative pleural effusions were determined in the derivation cohort and further verified in the validation cohort. In the Derivation (Luoyang) cohort, patients with exudates had significantly higher CT value [13.01 (10.01-16.11) vs. 4.89 (2.31-9.83) HU] and PF to blood CT value ratio [0.37 (0.27-0.53) vs. 0.16 (0.07-0.26)] than those with transudates. With a cut-off value of 10.81 HU, the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of CT value were 0.85, 88.89%, 68.90%, 43.96%, and 95.76%, respectively. The optimum cut-value for PF to blood CT value ratio was 0.27 with AUC of 0.86, yielding a sensitivity of 61.11%, specificity of 86.36%, PPV of 78.57%, and NPV of 73.08%. These were further verified in the Validation (Zhengzhou) cohort. CT value and PF to blood CT value ratio showed good differential abilities in predicting transudates from exudates, which may help to avoid unnecessary thoracentesis.

Histograms of computed tomography values in differential diagnosis of benign and malignant osteogenic lesions.

The use of histogram analysis of computed tomography (CT) values is a potential method for differentiating between benign osteoblastic lesions (BOLs) and malignant osteoblastic lesions (MOLs). To explore the diagnostic efficacy of histogram analysis in accurately distinguishing between BOLs and MOLs based on CT values. A total of 25 BOLs and 25 MOLs, which were confirmed through pathology or imaging follow-up, were included in this study. FireVoxel software was used to process the lesions and obtain various histogram parameters, including mean value, standard deviation, variance, coefficient of variation, skewness, kurtosis, entropy value, and percentiles ranging from 1st to 99th. Statistical tests, such as two independent-sample t-tests and the Mann-Whitney U test with Bonferroni correction, were employed to compare the differences in histogram parameters between BOLs and MOLs. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic efficacy of each parameter. Significant differences were observed in several histogram parameters between BOLs and MOLs, including the mean value, coefficient of variation, skewness, and various percentiles. Notably, the 25th percentile demonstrated the highest diagnostic efficacy, as indicated by the largest area under the curve in the ROC curve analysis. Histogram analysis of CT values provides valuable diagnostic information for accurately differentiating between BOLs and MOLs. Among the different parameters, the 25th percentile parameter proves to be the most effective in this discrimination process.

Clinical and non-contrast computed tomography characteristics and disease development in patients with benign pulmonary subsolid nodules with a solid component ≤ 5 mm

ObjectivesTo evaluate the clinical and non-contrast computed tomography (CT) features of patients with benign pulmonary subsolid nodules (SSNs) with a solid component ≤ 5 mm and their development trends via follow-up CT.MethodsWe retrospectively collected 436 data from patients who had SSNs with a solid component ≤ 5 mm, including 69 with absorbable benign SSNs (AB-SSNs), 70 with nonabsorbable benign SSNs (NB-SSNs), and 297 with malignant SSNs (M-SSNs). Models 1, 2, and 3 for distinguishing the different types of SSNs were then developed and validated.ResultsPatients with AB-SSNs were younger and exhibited respiratory symptoms more frequently than those with M-SSNs. The frequency of nodules detected during follow-up CT was in the following order: AB-SSNs > NB-SSNs > M-SSNs. NB-SSNs were smaller than M-SSNs, and ill-defined margins were more frequent in AB-SSNs than in NB-SSNs and M-SSNs. Benign SSNs exhibited irregular shape, target sign, and lower CT values more frequently compared to M-SSNs, whereas the latter demonstrated bubble lucency more commonly compared to the former. Furthermore, AB-SSNs showed more thickened interlobular septa and satellite lesions than M-SSNs and M-SSNs had more pleural retraction than AB-SSNs (all p < 0.017). The three models had AUCs ranging 0.748–0.920 and 0.790–0.912 in the training and external validation cohorts, respectively. A follow-up CT showed nodule progression in four benign SSNs.ConclusionsThe three SSN types have different clinical and imaging characteristics, with some benign SSNs progressing to resemble malignancy.Critical relevance statementA good understanding of the imaging features and development trends of benign SSNs may help reduce unnecessary follow-up or interventions. This retrospective study explores the CT characteristics of benign SSNs with a solid component ≤ 5 mm by comparing AB-SSNs, NB-SSNs, and M-SSNs and delineates their development trends via follow-up CT.Key points1. Different subsolid nodule types exhibit distinct clinical and imaging features.2. A miniscule number of benign subsolid nodules can progress to resemble malignancy.3. Knowing the clinical and imaging features and development trends of benign subsolid nodules can improve management.Graphical

Assessing the effect of scanning parameter on the size and density of pulmonary nodules: a phantom study

BackgroundLung cancer remains a leading cause of death among cancer patients. Computed tomography (CT) plays a key role in lung cancer screening. Previous studies have not adequately quantified the effect of scanning protocols on the detected tumor size. The aim of this study was to assess the effect of various CT scanning parameters on tumor size and densitometry based on a phantom study and to investigate the optimal energy and mA image quality for screening assessment.MethodsWe proposed a new model using the LUNGMAN N1 phantom multipurpose anthropomorphic chest phantom (diameters: 8, 10, and 12 mm; CT values: − 100, − 630, and − 800 HU) to evaluate the influence of changes in tube voltage and tube current on the size and density of pulmonary nodules. In the LUNGMAN N1 model, three types of simulated lung nodules representing solid tumors of different sizes were used. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were used to evaluate the image quality of each scanning combination. The consistency between the calculated results based on segmentation from two physicists was evaluated using the interclass correlation coefficient (ICC).ResultsIn terms of nodule size, the longest diameters of ground-glass nodules (GGNs) were closest to the ground truth on the images measured at 100 kVp tube voltage, and the longest diameters of solid nodules were closest to the ground truth on the images measured at 80 kVp tube voltage. In respect to density, the CT values of GGNs and solid nodules were closest to the ground truth when measured at 80 kVp and 100 kVp tube voltage, respectively. The overall agreement demonstrates that the measurements were consistent between the two physicists.ConclusionsOur proposed model demonstrated that a combination of 80 kVp and 140 mA scans was preferred for measuring the size of the solid nodules, and a combination of 100 kVp and 100 mA scans was preferred for measuring the size of the GGNs when performing lung cancer screening. The CT values at 80 kVp and 100 kVp were preferred for the measurement of GGNs and solid nodules, respectively, which were closest to the true CT values of the nodules. Therefore, the combination of scanning parameters should be selected for different types of nodules to obtain more accurate nodal data.