Average Computed Tomography Value Research Articles

Fully automated measurement of noise, signal-to-noise ratio, and contrast-to-noise ratio on chest CT images: feasibility and efficiency.

Rapid and accurate measurement of computed tomography (CT) image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) is a clinical challenge. To explore the feasibility of intelligent measurement of chest CT image noise, SNR, and CNR. A total of 300 chest CT scans were included in the study, which was divided into research dataset, internal test dataset, and external test dataset. Based on the research dataset, automatically segment and measure the average CT values and standard deviation (SD) of CT values for background air and lung field under different thresholds to obtain noise, SNR, and CNR results. Using the results of manual measurements as the reference standard, we determine the optimal threshold with the highest consistency. Using internal and external test datasets, validate the consistency of automated measurements of noise, SNR, and CNR at the optimal CT threshold with reference standards. With background air set at -900 HU and lung field at -800 HU as thresholds, the automated measurements of noise, SNR, and CNR demonstrate the highest consistency with the reference standards. At the optimal threshold, the noise, SNR, and CNR measured automatically on both the internal (intraclass correlation coefficient [ICC] = 0.85-0.96) and external (ICC = 0.75-0.85) test datasets exhibit high consistency with their respective reference standards. The method we explored can intelligently measure the noise, SNR, and CNR of chest CT images, exhibits high consistency with radiologists, and offers a novel tool for image quality evaluation and analysis.

Osteoporosis screening using QCT-based cutoff value of Hounsfield units in patients with degenerative lumbar diseases.

In patients with degenerative lumbar diseases, we aimed to establish the cutoff value of Hounsfield units (HU) for osteoporosis screening on the basis of the relationship between computed tomography (CT) HU value and volume bone mineral density (BMD) measured by quantitative computed tomography (QCT). A total of 136 patients aged ≥ 50years with degenerative lumbar diseases were retrospectively included. Their QCT-BMD of L1-2 were recorded, and the CT values of L1-2 were measured with the same CT images of QCT. The degree of bone loss was evaluated with the criteria based on QCT-BMD: cutoff value of 80mg/cm3 for osteoporosis and cutoff value of 120mg/cm3 for osteopenia. The cutoff of CT value was acquired according to the linear regression equation between CT value and QCT-BMD. The rate of osteoporosis, osteopenia, normal BMD was 33.8% (46/136), 51.5% (70/136), and 14.7% (20/136), respectively. The Pearson correlation coefficients between CT value and QCT-BMD were over 0.9 (P < 0.05). The cutoff of average CT value of L1-2 was calculated and adjusted to 110HU for osteoporosis and 160HU for osteopenia according the equation: average QCT-BMD of L1-2 = 0.76✕average CT value of L1-2-0.46 (R2 = 0.931, P < 0.001). Cutoff value of 110HU was 91.2% (42/46) sensitive and 88.9% (80/90) specific for identifying osteoporosis. The cutoff value of 160HU was 95.0% (19/20) sensitive and 96.6% (112/116) specific for distinguishing normal BMD from abnormal BMD (osteoporosis and osteopenia). The CT value is effective in osteoporosis screening, and the QCT-based cutoff value is 110 HU for osteoporosis and 160 HU for osteopenia in the patients with degenerative lumbar disease.

Correlation between type 2 diabetes mellitus remission and intrapancreatic fat deposition.

Intrapancreatic fat deposition (IPFD) exerts a significant negative impact on patients with type 2 diabetes mellitus (T2DM), accelerates disease deterioration, and may lead to impaired β-cell quality and function. To investigate the correlation between T2DM remission and IPFD. We enrolled 80 abdominally obese patients with T2DM admitted to our institution from January 2019 to October 2023, including 40 patients with weight loss-induced T2DM remission (research group) and 40 patients with short-term intensive insulin therapy-induced T2DM remission (control group). We comparatively analyzed improvements in IPFD [differential computed tomography (CT) values of the spleen and pancreas and average CT value of the pancreas]; levels of fasting blood glucose (FBG), 2-h postprandial blood glucose (2hPBG), and insulin; and homeostasis model assessment of insulin resistance (HOMA-IR) scores. Correlation analysis was performed to explore the association between T2DM remission and IPFD. After treatment, the differential CT values of the spleen and pancreas, FBG, 2hPBG, and HOMA-IR in the research group were significantly lower than those before treatment and in the control group, and the average CT value of the pancreas and insulin levels were significantly higher. Correlation analysis revealed that the greater the T2DM remission, the lower the amount of IPFD. T2DM remission and IPFD are inversely correlated.

Development and validation of a risk prediction model for invasiveness of pure ground-glass nodules based on a systematic review and meta-analysis

BackgroundAssessing the aggressiveness of pure ground glass nodules early on significantly aids in making informed clinical decisions.ObjectiveDeveloping a predictive model to assess the aggressiveness of pure ground glass nodules in lung adenocarcinoma is the study’s goal.MethodsA comprehensive search for studies on the relationship between computed tomography(CT) characteristics and the aggressiveness of pure ground glass nodules was conducted using databases such as PubMed, Embase, Web of Science, Cochrane Library, Scopus, Wanfang, CNKI, VIP, and CBM, up to December 20, 2023. Two independent researchers were responsible for screening literature, extracting data, and assessing the quality of the studies. Meta-analysis was performed using Stata 16.0, with the training data derived from this analysis. To identify publication bias, Funnel plots and Egger tests and Begg test were employed. This meta-analysis facilitated the creation of a risk prediction model for invasive adenocarcinoma in pure ground glass nodules. Data on clinical presentation and CT imaging features of patients treated surgically for these nodules at the Third Affiliated Hospital of Kunming Medical University, from September 2020 to September 2023, were compiled and scrutinized using specific inclusion and exclusion criteria. The model’s effectiveness for predicting invasive adenocarcinoma risk in pure ground glass nodules was validated using ROC curves, calibration curves, and decision analysis curves.ResultsIn this analysis, 17 studies were incorporated. Key variables included in the model were the largest diameter of the lesion, average CT value, presence of pleural traction, and spiculation. The derived formula from the meta-analysis was: 1.16×the largest lesion diameter + 0.01 × the average CT value + 0.66 × pleural traction + 0.44 × spiculation. This model underwent validation using an external set of 512 pure ground glass nodules, demonstrating good diagnostic performance with an ROC curve area of 0.880 (95% CI: 0.852–0.909). The calibration curve indicated accurate predictions, and the decision analysis curve suggested high clinical applicability of the model.ConclusionWe established a predictive model for determining the invasiveness of pure ground-glass nodules, incorporating four key radiological indicators. This model is both straightforward and effective for identifying patients with a high likelihood of invasive adenocarcinoma.

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.

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.

Sub-calcaneal plantar fat pad assessment using dual-energy computed tomography: First experience in the diabetic foot

BackgroundThis study assessed the use of dual-energy computed tomography (CT) to evaluate sub-calcaneal plantar fat pad changes in people with diabetic neuropathy. MethodsDual-energy CT scans of people with diabetic neuropathy and non-diabetic controls were retrospectively included. Average CT values (in Hounsfield Units) and thickness (in centimeters) of the sub-calcaneal plantar fat pad were measured in mono-energetic images at two energy levels (40 keV and 70 keV). The CT values measured in patients with diabetic neuropathy were correlated to barefoot plantar pressure measurements performed during walking in a clinical setting. FindingsForty-five dual-energy CT scans of people with diabetic neuropathy and eleven DECT scans of non-diabetic controls were included. Mean sub-calcaneal plantar fat pad thickness did not significantly differ between groups (diabetes group 1.20 ± 0.34 cm vs. control group 1.21 ± 0.28 cm, P = 0.585). CT values at both 40 keV (−34.7 ± 48.7 HU vs. −76.0 ± 42.8 HU, P = 0.013) and 70 keV (−11.2 ± 30.8 HU vs. -36.3 ± 27.2 HU, P = 0.017) were significantly higher in the diabetes group compared to controls, thus contained less fatty tissue. This elevation was most apparent in patients with Type 1 diabetes. CT values positively correlated with the mean peak plantar pressure. InterpretationDual-energy CT was able to detect changes in the plantar fat pad of people with diabetic neuropathy.

Synthetic high-energy computed tomography image via a Wasserstein generative adversarial network with the convolutional block attention module.

Computed tomography (CT) is now universally applied into clinical practice with its non-invasive quality and reliability for lesion detection, which highly improves the diagnostic accuracy of patients with systemic diseases. Although low-dose CT reduces X-ray radiation dose and harm to the human body, it inevitably produces noise and artifacts that are detrimental to information acquisition and medical diagnosis for CT images. This paper proposes a Wasserstein generative adversarial network (WGAN) with a convolutional block attention module (CBAM) to realize a method of directly synthesizing high-energy CT (HECT) images through low-energy scanning, which greatly reduces X-ray radiation from high-energy scanning. Specifically, our proposed generator structure in WGAN consists of Visual Geometry Group Network (Vgg16), 9 residual blocks, upsampling and CBAM, a subsequent attention block. The convolutional block attention module is integrated into the generator for improving the denoising ability of the network as verified by our ablation comparison experiments. Experimental results of the generator attention module ablation comparison indicate an optimization boost to the overall generator model, obtaining the synthesized high-energy CT with the best metric and denoising effect. In different methods comparison experiments, it can be clearly observed that our proposed method is superior in the peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM) and most of the statistics (average CT value and its standard deviation) compared to other methods. Because P<0.05, the samples are significantly different. The data distribution at the pixel level between the images synthesized by the method in this paper and the high-energy CT images is also most similar. Experimental results indicate that CBAM is able to suppress the noise and artifacts effectively and suggest that the image synthesized by the proposed method is closest to the high-energy CT image in terms of visual perception and objective evaluation metrics.

Growth Regularity of Pulmonary Ground Glass Nodules Based on 3D Reconstruction Technology

Since the popularization of computed tomography (CT) technology, the detection rate of pulmonary ground glass nodules (GGNs) with imaging follow-up as the main management method has increased significantly. The purpose of this study is to quantitatively analyze the changes of pulmonary GGNs during the follow-up process with three-dimensional reconstruction technology, explore the natural progression of pulmonary GGNs, and provide effective basis for clinical guidance for patients to conduct reasonable management of nodules. A total of 115 cases of pulmonary GGNs with regular follow-up in the Combined Outpatient Department of Zhoushan Hospital from March 2015 to November 2022 were enrolled. Quantitative imaging features of nodules were extracted by semi-automatic segmentation of 3D Slicer software to evaluate the growth of nodules and clinical intervention during follow-up. The average baseline age of the patients was (56.9±10.1) yr. The mean follow-up time was (48.8±18.9) months. The two-dimensional diameter of baseline CT scan was (7.9±2.9) mm, and the maximum three-dimensional diameter was (10.1±3.4) mm. The two-dimensional diameter of the last CT scan was (9.9±4.7) mm, and the maximum three-dimensional diameter was (11.4±5.1) mm. A total of 27 cases (23.5%) showed an increase during follow-up, with a median volume doubling time of 822 days and a median mass doubling time of 1,007 days. 32 cases were surgically resected, including 6 cases of invasive adenocarcinoma (IAC), 16 cases of minimally invasive adenocarcinoma (MIA), 8 cases of adenocarcinoma in situ (AIS) and 2 cases of atypical adenomatous hyperplasia (AAH). Five nodules underwent surgical intervention due to the progression of two-dimensional diameter, which was pathologically confirmed as pre-invasive lesions, but their three-dimensional maximum diameter showed no significant change. Nodular morphology, lobulated sign, spiculated sign and vacuole signs all promoted the growth of nodules in univariate analysis. There were significant differences in age, baseline diameter, mean CT value, median CT value, 10% and 90% percentile CT number between the growth group and the stable group (P<0.05). Multivariate Logistic regression analysis showed that age and average CT value were risk factors for nodule growth (P<0.05). Receiver-operating characteristic (ROC) curve analysis results indicated that the age ≥63 years old, the baseline three-dimensional maximum diameter ≥9.2 mm, and the average CT value ≥-507.8 HU were more likely to accelerate the growth of GGNs. The maximum three-dimensional diameter ≥14.4 mm and the average CT value ≥-495.7 HU may be a higher malignant probability. GGNs show an inert growth process, and the use of three-dimensional measurements during follow-up is of greater significance. For persistent glass grinding nodules ≥63 years old, the baseline three-dimensional maximum diameter ≥9.2 mm, and the average CT value ≥-507.8 HU are more likely to increase. However, most nodules still have good prognosis after progression, and long-term follow-up is safe.

Artificial intelligence-based radiomics for the prediction of nodal metastasis in early-stage lung cancer

We aimed to investigate the value of computed tomography (CT)-based radiomics with artificial intelligence (AI) in predicting pathological lymph node metastasis (pN) in patients with clinical stage 0–IA non-small cell lung cancer (c-stage 0–IA NSCLC). This study enrolled 720 patients who underwent complete surgical resection for c-stage 0–IA NSCLC, and were assigned to the derivation and validation cohorts. Using the AI software Beta Version (Fujifilm Corporation, Japan), 39 AI imaging factors, including 17 factors from the AI ground-glass nodule analysis and 22 radiomics features from nodule characterization analysis, were extracted to identify factors associated with pN. Multivariate analysis showed that clinical stage IA3 (p = 0.028), solid-part size (p < 0.001), and average solid CT value (p = 0.033) were independently associated with pN. The receiver operating characteristic analysis showed that the area under the curve and optimal cut-off values of the average solid CT value relevant to pN were 0.761 and -103 Hounsfield units, and the threshold provided sensitivity, specificity, and negative predictive values of 69%, 65%, and 94% in the entire cohort, respectively. Measuring the average solid-CT value of tumors for pN may have broad applications such as guiding individualized surgical approaches and postoperative treatment.

Special Computed Tomography Imaging Features of Thymic Cyst.

Objective To explore the features and diagnostic value of computed tomography (CT) imaging in cases of thymic cysts. Methods A total of 24 cases of the thymic cysts (confirmed by postoperative pathology) were retrospectively analyzed. The location, morphology, and density of the thymic cysts were summarized, and the changes in CT value of the region of interest (ROI) in the thymic cysts between noncontrast enhanced and enhanced chest scans were compared and classified. Results The average long-axis dimension was 17.50 ± 6.00 mm, the CT value range across the 24 cases was 5–81 HU, and the average CT value of the noncontrast enhanced scans was 39.75 ± 20.66 HU. The CT value in the noncontrast enhanced scan was >20 HU in 79% of the sample cases. The CT value in the ROI of the thymic cysts under enhanced scan showed a significant decrease in 15 cases, a significant increase in 5 cases, and an insignificant change in 4 cases. Conclusion The CT values of the thymic cysts in the enhanced scans were generally lower than in the noncontrast enhanced scans, which might be a valuable finding for thymic cysts diagnosis.

Correlation of computed tomography quantitative parameters with tumor invasion and Ki-67 expression in early lung adenocarcinoma.

The purpose of the study is to investigate the correlation of computed tomography (CT) quantitative parameters with tumor invasion and Ki-67 expression in early lung adenocarcinoma.The study involved 141 lesions in 141 patients with early lung adenocarcinoma. According to the degree of tumor invasion, the lesions were assigned into (adenocarcinoma in situ + minimally invasive adenocarcinoma) group and invasive adenocarcinoma (IAC) group. Artificial intelligence-assisted diagnostic software was used to automatically outline the lesions and extract corresponding quantitative parameters on CT images. Statistical analysis was performed to explore the correlation of these parameters with tumor invasion and Ki-67 expression.The results of logistic regression analysis showed that the short diameter of the lesion and the average CT value were independent predictors of IAC. Receiver operating characteristic curve analysis identified the average CT value as an independent predictor of IAC with the best performance, with the area under the receiver operating characteristic curve of 0.893 (P < .001), and the threshold of –450 HU. Besides, the predicted probability of logistic regression analysis model was detected to have the area under the curve of 0.931 (P < .001). The results of Spearman correlation analysis showed that the expression level of Ki-67 had the highest correlation with the average CT value of the lesion (r = 0.403, P < .001).The short diameter of the lesion and the average CT value are independent predictors of IAC, and the average CT value is significantly positively correlated with the expression of tumor Ki-67.

Virtual Autopsy Morphological Features of Drowning.

To explore the application value of virtual autopsy to obtain key evidence information on drowned corpses and its application value of virtual autopsy in the diagnosis of drowning. In this study, 7 corpses were selected as the research objects. The image data of corpses were collected by computed tomography (CT) before conventional autopsy. The characteristics of corpses were observed through image reading, combined with virtual measurement indexes, and compared with 15 non-drowned corpses. The postmortem CT of drowning showed the more fluid in respiratory tract than the non-drowning, and ground-glass opacities in the lung. The statistical volume of fluid in the sinus (maxillary sinus and sphenoid sinus) was (10.24±4.70) mL in drowning cases and (2.02±2.45) mL in non-drowning cases. The average CT value of fluid in the sinus, left atrial blood and gastric contents in drowning cases were (15.91±17.20), (52.57±9.24) and (10.33±12.81) HU, respectively, which were lower than those in non-drowning cases (P<0.05). The comprehensive consideration of multiple characteristic image manifestations and the virtual measurement indexes are helpful to the forensic pathological diagnosis of drowning. Virtual autopsy can be used as an auxiliary method in the forensic diagnosis of drowning.

CT-Assisted Improvements in the Accuracy of the Intraoperative Frozen Section Examination of Ground-Glass Density Nodules.

Objectives The intraoperative frozen section examination (IFSE) of pulmonary ground-glass density nodules (GGNs) is a great challenge. In the present study, through comparing the correlation between the computed tomography (CT) findings and pathological diagnosis of GGNs, the CT features as independent risk factors affecting the examination were defined, and their value in the rapid intraoperative examination of GGNs was explored. Methods The relevant clinical data of 90 patients with GGNs on CT were collected, and all CT findings of GGNs, including the maximum transverse diameter, average CT value, spiculation, solid component, vascular sign, air sign, bronchus sign, lobulation, and pleural indentation, were recorded. All the cases received thoracoscopic surgery, and final pathological results were obtained. The cases were divided into three groups on the basis of pathological diagnosis: benign/atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS)/microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC). The CT findings were analyzed statistically, the independent risk factors were identified through the intergroup bivariate logistic regression analysis on variables with statistically significant differences, and a receiver operating curve (ROC) was plotted to establish a logistic regression model for diagnosing GGNs. A retrospective analysis was conducted on the coincidence rate of the rapid intraoperative and routine postoperative pathological examinations of the 90 cases with GGNs. The relevant clinical data of 49 cases with GGNs were collected. Conventional rapid intraoperative examination and CT-assisted rapid intraoperative examination were performed, and their coincidence rates with routine postoperative pathological examinations were compared. Results No statistical differences in the onset age, gender, smoking history, and family history of malignant tumors were found among cases with GGNs in the identification of benign/AAH, AIS/MIA, and IAC (P = 0.158, P = 0.947, P = 0.746, P = 0.566). No statistically significant difference was found among the three groups in terms of CT findings, such as lobulation, bronchus sign, pleural indentation, spiculation, vascular sign, and solid component (P > 0.05). The air sign, the maximum transverse diameter of GGNs, and average CT value showed statistically significant differences among the groups (P < 0.001, P < 0.05, P < 0.001). Bivariate logistic regression analysis was performed on three risk factors, and the predicted probability value was obtained. A ROC curve was plotted by using the maximum transverse diameter as a predictor for analysis between the groups with benign/AAH and AIS/MIA, and the results demonstrated that the area under the curve (AUC) was 0.692. A ROC curve was plotted by using the predicted probability value, maximum transverse diameter, and average CT value as predictors for distinguishing between the groups with AIS/MIA and IAC, and the results showed that the AUC values of the predicted probability value, maximum transverse diameter, and CT value were 0.920, 0.816, and 0.772, respectively. A regression model [Logit (P) = 2.304 − 2.689X1 + 0.302X2 + 0.011X3] was established to identify GGNs as IAC, obtaining AUC values of up to 0.920 for the groups with AIS/MIA and IAC, the sensitivity of 0.821, and the specificity of 0.894. The coincidence rate of rapid intraoperative and routine postoperative pathological examinations taken for modeling was 79.3%, that of conventional IFSE and postoperative pathological examination in prospective studies was 83.7%, and that of CT-assisted rapid intraoperative and postoperative pathological examinations was 98.0%. The former two were statistically different from the last one (P = 0.003 and P = 0.031, respectively). Conclusion The air sign, maximum transverse diameter, and average CT value of the CT findings of GGNs had superior capabilities to enhance the pathologic classification of GGNs. The auxiliary function of the comprehensive multifactor analysis of GGNs was better than that of single-factor analysis. CT-assisted diagnosis can improve the accuracy of rapid intraoperative examination, thereby increasing the accuracy of the selection of operative approaches in clinical practice.

Correlation of CT Values and Bone Mineral Density in Elderly Chinese Patients with Proximal Humeral Fractures.

ObjectiveTo investigate the correlation between computed tomography (CT) values and bone mineral density (BMD) in elderly Chinese patients with proximal humeral fractures.MethodsThis was a single‐center retrospective study involving 166 elderly patients with proximal humeral fractures between January and June 2015 in our hospital. Following the inclusion and exclusion criteria, 89 patients were finally enrolled in this study. The spiral CT scanning was performed on these patients, and the CT images were obtained by using MIMICS software. The CT values in axial, coronal, and sagittal images of healthy proximal humeri were measured using a circular region of interest (ROI) by Image J. The bone mineral density (BMD) of the lumbar spine and femoral neck was measured using dual‐energy X‐ray absorptiometry (DXA). Spearman rank correlation methods were used for analysis of the association between the proximal humerus average CT value (CTMean) and the lumbar spine as well as femoral neck BMD in patients with proximal humeral fractures, or osteoporotic patients.ResultsAmong the included 89 patients, there were 26 males and 63 females, 69% and 84% of whom were diagnosed with osteoporosis, respectively. The lumbar spine and femoral neck BMD and the CTMean of the proximal humerus were higher in males than females with proximal humeral fractures (P < 0.05). This gender difference was also found in the osteoporotic patient population (P < 0.05). The Spearman rank correlation method showed that the lumbar spine and femoral neck BMD was closely related to the proximal humeral CTMean in males (r = 0.877, P = 0.000; r = 0.832, P = 0.000; respectively) and females (r = 0.806, P = 0.000; r = 0.616, P = 0.000; respectively) with proximal humeral fractures, as well as osteoporotic male (r = 0.745, P = 0.000; r = 0.575, P = 0.000; respectively) and female (r = 0.613, P = 0.000; r = 0.629, P = 0.000; respectively) patients.ConclusionsThe CT value of the proximal humerus is a rapid and accurate method by which bone quality can be assessed in elderly patients with proximal humeral fractures. Moreover, the CT value of the proximal humerus is an alternative measurement of BMD that can guide surgeons in selecting the appropriate internal fixation material.

Radiomics nomogram: A noninvasive tool for preoperative evaluation of the invasiveness of pulmonary adenocarcinomas manifesting as ground-glass nodules

In this study, we aimed to establish a radiomics nomogram that noninvasively evaluates the invasiveness of pulmonary adenocarcinomas manifesting as ground-glass nodules (GGNs). Computed tomography (CT) images of 509 patients manifesting as GGNs were collected: 70% of cases were included in the training cohort and 30% in the validation cohort. The Max-Relevance and Min-Redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) algorithm were used to select the radiomics features and construct a radiomics signature. Univariate and multivariate logistic regression were used to select the invasiveness-related clinical and CT morphological predictors. Age, smoking history, long diameter, and average CT value were retained as independent predictors of GGN invasiveness. A radiomics nomogram was established by integrating clinical and CT morphological features with the radiomics signature. The radiomics nomogram showed good predictive ability in the training set (area under the curve [AUC], 0.940; 95% confidence interval [CI], 0.916–0.964) and validation set (AUC, 0.946; 95% CI, 0.907–0.986). This radiomics nomogram may serve as a noninvasive and accurate predictive tool to determine the invasiveness of GGNs prior to surgery and assist clinicians in creating personalized treatment strategies.

Quantitative Analysis of the Deltoid Ligament Degradation in Chronic Ankle Instability Patients using the CT Value

Category:Ankle; OtherIntroduction/Purpose:Chronic lateral ankle instability (CLAI) that is developed after multiple lateral ankle ligament injury lead to ankle osteoarthritis. Although isolated deltoid ligament injury is rare compared to lateral ankle ligament injury, deltoid ligament tear, especially deep posterior tibiotalar ligament (PTT) can be observed arthroscopically in CLAI patients. Unphysiological loading of the ankle joint with CLAI might cause degradation of the deltoid ligament. This study aimed to investigate image findings of the deltoid ligament using computed tomography (CT) value for quantitative analysis of degenerative ligament changes in CLAI patients.Methods:Among the enrolled patients who underwent ankle magnetic resonance imaging (MRI) and CT scans of the ankle, this retrospective analysis included 24 ankles without ankle osteoarthritis, osteochondral lesion of the talus (OLT), flatfoot and ankle fractures (14 males and 10 females; mean age, 42.8 years) as a control group, and 14 CLAI ankles without OLT (7 males and 7 females; mean age, 31.1 years) as CLAI group. The CT scans were performed using a 64-slice multidetector row CT. Deep PTT was detected on coronal T2-weighted MR images. Both the coronal MR and CT images were matched for analysis, then average CT values were measured using the region of interest that was applied to the detected area of deep PTT on the CT images.Spearman’s correlation coefficient was used to evaluate the correlation between age and CT value in the control group.Results:The strong negative correlation was identified between age and CT value in the control group (Spearman ρ= -0.88; p< 0.001). The CT value of the deep PTT are degraded with aging. Mean CT value of deep PTT in participants under 60 years old were 79.9 HU (95% CI, 75.1-84.8) in the control group (18 ankles), and 66.5 HU (95% CI, 58.6-74.5) in the CLAI group (14 ankles) (Welch’s t test; p = 0.005).Conclusion:MRI techniques and protocols recently have been developed, however, some limitations remain such as a quantitative evaluation of the ligament. Our findings suggest that the CLAI can lead to degradation of the deltoid ligament via an overloading of medial ankle structures. Additionally, CT values should be useful for quantitatively evaluating ligament status including degenerative changes.

Generation of Virtual Non-Contrast CT From Intravenous Enhanced CT in Radiotherapy Using Convolutional Neural Networks.

Objective: To generate virtual non-contrast (VNC) computed tomography (CT) from intravenous enhanced CT through convolutional neural networks (CNN) and compare calculated dose among enhanced CT, VNC, and real non-contrast scanning.Method: 50 patients who accepted non-contrast and enhanced CT scanning before and after intravenous contrast agent injections were selected, and two sets of CT images were registered. A total of 40 and 10 groups were used as training and test datasets, respectively. The U-Net architecture was applied to learn the relationship between the enhanced and non-contrast CT. VNC images were generated in the test through the trained U-Net. The CT values of non-contrast, enhanced and VNC CT images were compared. The radiotherapy treatment plans for esophageal cancer were designed, and dose calculation was performed. Dose distributions in the three image sets were compared.Results: The mean absolute error of CT values between enhanced and non-contrast CT reached 32.3 ± 2.6 HU, and that between VNC and non-contrast CT totaled 6.7 ± 1.3 HU. The average CT values in enhanced CT of great vessels, heart, lungs, liver, and spinal cord were all significantly higher than those of non-contrast CT (p < 0.05), with the differences reaching 97, 83, 42, 40, and 10 HU, respectively. The average CT values of the organs in VNC CT showed no significant differences from those in non-contrast CT. The relative dose differences of the enhanced and non-contrast CT were −1.2, −1.3, −2.1, and −1.5% in the comparison of mean doses of planned target volume, heart, great vessels, and lungs, respectively. The mean dose calculated by VNC CT showed no significant difference from that by non-contrast CT. The average γ passing rate (2%, 2 mm) of VNC CT image was significantly higher than that of enhanced CT image (0.996 vs. 0.973, p < 0.05).Conclusion: Designing a treatment plan based on enhanced CT will enlarge the dose calculation uncertainty in radiotherapy. This paper proposed the generation of VNC CT images from enhanced CT images based on U-Net architecture. The dose calculated through VNC CT images was identical with that obtained through real non-contrast CT.

Assessment of Clinical Stage IA Lung Adenocarcinoma with pN1/N2 Metastasis Using CT Quantitative Texture Analysis.

ObjectiveTo explore the application of texture analysis basing on computed tomography (CT) images in predicting lymph-node metastasis in patients with clinical stage IA lung adenocarcinoma.MethodsIn total, 256 patients with clinical stage IA lung adenocarcinoma who had underwentgone preoperative CT examinations were enrolled. A total of 25 texture features using MaZda (version 4.6) software and conventional radiological features were extracted from raw CT data sets. Based on surgical results, patients were stratified into lymph node metastasis–positive and –negative groups. Independent-sample t-tests and Mann–Whitney U tests were used to compare continuous variables between the groups. Continuity-correction and χ2 tests were used for categorical variable comparison. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of lymph-node metastasis.ResultsIn total, 256 clinical stage IA lung adenocarcinoma cases were proved by pathology: 39 (15.23%) cases with lymph-node metastasis (14 N1a, seven N1b, six N2a1, ten N2a2, and two N2b) and 217 (84.77%) cases without lymph-node metastasis. Univariate and multivariate logistic regression analyses demonstrated that total volume (OR 3.777, p=0.015), average CT value of whole tumor (OR 16.271, p<0.001), three texture parameters (mean OR 8.473, p<0.001; skewness OR 6.393, p=0.001; and entropy OR 0.343, p=0.049) were independent factors associated with lymph-node status. As such, early-stage lung adenocarcinoma with higher total volume (>4.05 cm3), average CT value of whole tumor (>–70 HU), mean (>133.79), entropy (>1.98), and lower skewness (≤0.02) pointed to positive lymph-node metastasis.ConclusionTexture parameters were independent factors associated with lymph-node status in clinical stage IA lung adenocarcinoma.

The effects of 1α,25-dihydroxyvitamin D3 on alveolar repair and bone mass in adiponectin-deficient mice

Chronic obstructive pulmonary disease (COPD) is a major cause of death worldwide. However, no drugs can regenerate lung tissue in COPD patients, and differentiation-inducing drugs that can effectively treat damaged alveoli are needed. In addition, the presence of systemic comorbidities is also considered problematic. Our previous study revealed that a retinoic acid derivative improved emphysema in elastase-induced COPD model mice at a dose of 1.0 mg/kg, whereas 1α,25-dihydroxyvitamin D3 (1,25(OH)2D3) showed an emphysema-improving effect in the same model at 0.1 μg/kg. Elastase-induced COPD model mice do not exhibit a systemic disease state, so evaluation in a model that better reflects the human disease state is considered necessary. To solve this problem, we focused on the adiponectin-deficient mouse and examined the effects of 1,25(OH)2D3 on alveolar regeneration. Fifty-week-old adiponectin-deficient mice were treated with 1,25(OH)2D3 (0.1 μg/kg) twice a week, for 30 weeks. The effects of pulmonary administration on alveolar repair were evaluated according to the distance between alveolar walls (Lm values) and computed tomography (CT) parameters. Bone density was evaluated based on CT. The administration of 1,25(OH)2D3 was confirmed to show a significant therapeutic effect. The Lm values in the control and 1,25(OH)2D3-treated groups were 98 ± 4 μm and 63 ± 1 μm, respectively. However, on CT, the average CT value and % of low attenuation area showed no significant change. In adiponectin-deficient mice, the reduction of bone density (cortical, spongy, and total bone), which is a systemic symptom of COPD, was significantly suppressed by 1,25(OH)2D3 at 80 weeks of age. The present study suggests that 1,25(OH)2D3 could be a potential candidate drug that may provide a radical cure for the lung disease and comorbidities of COPD patients. This work can lead to the development drugs that may provide a radical cure for COPD.