Precontrast Computed Tomography Research Articles

CT imaging analysis differentiating papillary renal neoplasm with reverse polarity from papillary renal cell carcinoma: combined with a radiomics model.

To assess the computed tomography (CT) findings of papillary renal neoplasm with reverse polarity (PRNRP) and develop a radiomics-based model to distinguish PRNRPs from papillary renal cell carcinomas (PRCCs). We analyzed 31 PRNRPs and 68 PRCCs using preoperative kidney CT. We evaluated CT features that could discriminate PRNRPs from PRCCs. A radiomics signature was constructed using features selected through a least absolute shrinkage and selection operator algorithm. A radiomics-based model incorporating a radiomics signature and subjective CT parameters using multivariate logistic regression was developed. The diagnostic performance of the CT parameters, radiomics model, and their combination was evaluated using the area under the curve (AUC). Most of PRNRPs had a round shape (93.5%), well-defined margin (100%), and persistent enhancement (77.4%). Compared with PRCC, PRNRPs exhibited distinct CT features including small size (16.7 vs. 37.7mm, P < 0.001), heterogeneity (64.5 vs. 32.4%, P = 0.004), enhancing dot sign (16.1 vs. 1.5%, P = 0.001), and high attenuation in pre-contrast CT (44.2 vs. 35.5 HU, P = 0.003). Multivariate analysis revealed smaller mass size (odds ratio [OR]: 0.9; 95% confidence interval [CI] 0.9-1.0, P = 0.013), heterogeneity (OR: 8.8; 95% CI 1.9-41.4, P = 0.006), and higher attenuation in pre-contrast CT (OR: 1.1; 95% CI 1.0-1.2, P = 0.011) as significant independent factors for identifying PRNRPs. The diagnostic performance of the combination model was excellent (AUC: 0.923). Smaller tumor size, heterogeneity, and higher attenuation in pre-contrast CT were more closely associated with PRNRPs than with PRCCs. Though the retrospective design, small sample size, and single-center data of this study may affect the generalizability of the findings, combining subjective CT features with a radiomics model is beneficial for distinguishing PRNRPs from PRCCs.

Renal Lesions with Low-level Enhancement on Contrast-enhanced CT Promotes Early Detection of Drug-induced Kidney Injury in Patients Administered Anticancer Drugs.

Some patients with cancer-administered anti-cancer drugs may develop renal lesions with low-level enhancement on follow-up abdominal computed tomography (CT). To explore the clinical significance of renal lesions with low-level enhancement on CT after exposure to anti-cancer drugs. Medical records of patients with cancer who developed renal lesions on CT after exposure to anti-cancer drugs were retrospectively reviewed. Renal lesions were scored according to the extent of involvement, CT attenuation values of lesions and normal parenchyma were measured on precontrast CT and three phases of contrast-enhanced CT, and changes in serum creatinine (SCr) from one week before exposure to drugs to one week before and after the appearance of renal lesions were recorded. This study included 54 patients (86 lesions). Lesions were slightly lower density on pre-contrast CT, and less enhancing than normal renal parenchyma, especially in the delayed phase. Lesions were wedge-shaped, and involved the renal pyramid and associated renal cortex, as well as, were single or multiple, and occurred in the unilateral or bilateral kidneys. There were patchy and cord-like shadows of increased density in adjacent perirenal adipose tissue. During follow-up, lesions disappeared in 15 patients and persisted in 39 patients without significant progression. There were significant differences in renal lesions and normal renal parenchyma CT attenuation values in each phase of contrast-enhanced CT. Change in SCr level was significantly positively correlated with lesion score. Renal lesions with low-level enhancement on CT suggest early drug-induced kidney injury. These findings will inform clinical decision-making.

A deep learning model for automated kidney calculi detection on non-contrast computed tomography scans in dogs.

Nephrolithiasis is one of the most common urinary disorders in dogs. Although a majority of kidney calculi are non-obstructive and are likely to be asymptomatic, they can lead to parenchymal loss and obstruction as they progress. Thus, early diagnosis of kidney calculi is important for patient monitoring and better prognosis. However, detecting kidney calculi and monitoring changes in the sizes of the calculi from computed tomography (CT) images is time-consuming for clinicians. This study, in a first of its kind, aims to develop a deep learning model for automatic kidney calculi detection using pre-contrast CT images of dogs. A total of 34,655 transverseimage slices obtained from 76 dogs with kidney calculi were used to develop the deep learning model. Because of the differences in kidney location and calculi sizes in dogs compared to humans, several processing methods were used. The first stage of the models, based on the Attention U-Net (AttUNet), was designed to detect the kidney for the coarse feature map. Five different models-AttUNet, UTNet, TransUNet, SwinUNet, and RBCANet-were used in the second stage to detect the calculi in the kidneys, and the performance of the models was evaluated. Compared with a previously developed model, all the models developed in this study yielded better dice similarity coefficients (DSCs) for the automatic segmentation of the kidney. To detect kidney calculi, RBCANet and SwinUNet yielded the best DSC, which was 0.74. In conclusion, the deep learning model developed in this study can be useful for the automated detection of kidney calculi.

Dual-energy CT for gastrointestinal bleeding.

Dual-energy computed tomography (DECT) can be used for various types of analyses, including iodine quantification, and its usefulness in diagnosing gastrointestinal diseases has been reported. This pictorial review describes the use of DECT in the diagnosis of gastrointestinal bleeding. Virtual non-contrast computed tomography (CT) is available in DECT and can be used as a substitute for pre-contrast CT in the case of gastrointestinal haemorrhage. The omission of pre-contrast CT can reduce radiation exposure by approximately 30%. A low-keV virtual monochromatic X-ray image (VMI) can increase the contrast of iodine, and iodine maps can provide better visibility of extravasation. These analytical images can provide a diagnosis with a high degree of confidence. In addition, the low-keV VMI clearly illustrates the vascular structure, which may be useful for improving the visibility of vascular lesions and for confirming the arterial anatomy before embolisation. Considering that these analytical images are created on the basis of contrast-enhanced CT, the positional information of organs is entirely identical, thus allowing the comparison of images regardless of intestinal peristalsis or body motion. In conclusion, the analytical images of DECT can solve the problems of conventional protocols, and DECT is considered useful in the imaging diagnosis of gastrointestinal bleeding.

Evaluation of the Practice of Performing Abdominal CT Scan with Manually Administered Fixed Dose of Contrast in Achieving Adequate Hepatic Enhancement: An Institutional-Based Cross-Sectional Study.

Intravenous (IV) iodine-based contrast agents are administered during computed tomography (CT) examination to enhance the density differences between lesions and surrounding parenchyma, which is important for lesion characterization, and to demonstrate vascular anatomy and vessel patency. Quality of contrast enhancement has a significant influence on diagnostic interpretation and subsequent management. In this study, we assessed the quality of portal venous phase abdominal CT scans performed with a manual injection of a fixed dose of contrast, which is the routine practice at Tikur Anbessa Specialized Hospital (TASH). The effect of age and sex was also assessed. A hospital-based retrospective review was performed to identify patients who have had a precontrast and postcontrast abdominal CT scan from November 4, 2020, to September 30, 2022. All patients with abdominal CT scans having precontrast and portal venous phase scans were included in the study. All CT scans were reviewed by the principal investigator and the quality of contrast enhancement was assessed. In this study, there were a total of 379 patients. The mean hepatic attenuations in precontrast and portal venous phase scans were 59.05 ± 6.69 HU and 103.73 ± 12.84 HU. The proportion of scans with less than 50 HU enhancement was 68% (n = 258). There was a significant association between age and sex with contrast enhancement. The hepatic contrast enhancement pattern of abdominal CT scan at the study institution reveals a concerning degree of image quality. This is evidenced by the high number of suboptimal contrast enhancement indices and the highly variable enhancement patterns across different patients. This can have a negative impact on the diagnostic performance of CT imaging and can adversely affect the management. Furthermore, both sex and age affect the pattern of enhancement.

Prognostic Value of Artificial Intelligence-Driven, Computed Tomography-Based, Volumetric Assessment of the Volume and Density of Muscle in Patients With Colon Cancer.

The prognostic value of the volume and density of skeletal muscles in the abdominal waist of patients with colon cancer remains unclear. This study aimed to investigate the association between the automated computed tomography (CT)-based volume and density of the muscle in the abdominal waist and survival outcomes in patients with colon cancer. We retrospectively evaluated 474 patients with colon cancer who underwent surgery with curative intent between January 2010 and October 2017. Volumetric skeletal muscle index and muscular density were measured at the abdominal waist using artificial intelligence (AI)-based volumetric segmentation of body composition on preoperative pre-contrast CT images. Patients were grouped based on their skeletal muscle index (sarcopenia vs. not) and muscular density (myosteatosis vs. not) values and combinations (normal, sarcopenia alone, myosteatosis alone, and combined sarcopenia and myosteatosis). Postsurgical disease-free survival (DFS) and overall survival (OS) were analyzed using univariable and multivariable analyses, including multivariable Cox proportional hazard regression. Univariable analysis showed that DFS and OS were significantly worse for the sarcopenia group than for the non-sarcopenia group (P = 0.044 and P = 0.003, respectively, by log-rank test) and for the myosteatosis group than for the non-myosteatosis group (P < 0.001 by log-rank test for all). In the multivariable analysis, the myosteatotic muscle type was associated with worse DFS (adjusted hazard ratio [aHR], 1.89 [95% confidence interval, 1.25-2.86]; P = 0.003) and OS (aHR, 1.90 [95% confidence interval, 1.84-3.04]; P = 0.008) than the normal muscle type. The combined muscle type showed worse OS than the normal muscle type (aHR, 1.95 [95% confidence interval, 1.08-3.54]; P = 0.027). Preoperative volumetric sarcopenia and myosteatosis, automatically assessed from pre-contrast CT scans using AI-based software, adversely affect survival outcomes in patients with colon cancer.

Predicting the efficacy of immune checkpoint inhibitors monotherapy in advanced non-small cell lung cancer: a machine learning method based on multidimensional data.

Immunotherapy has improved the prognosis of patients with advanced non-small cell lung cancer (NSCLC), but only a small subset of patients achieved clinical benefit. The purpose of our study was to integrate multidimensional data using a machine learning method to predict the therapeutic efficacy of immune checkpoint inhibitors (ICIs) monotherapy in patients with advanced NSCLC. We retrospectively enrolled 112 patients with stage IIIB-IV NSCLC receiving ICIs monotherapy. The random forest (RF) algorithm was used to establish efficacy prediction models based on five different input datasets, including precontrast computed tomography (CT) radiomic data, postcontrast CT radiomic data, a combination of the two CT radiomic data, clinical data, and a combination of radiomic and clinical data. The 5-fold cross-validation was used to train and test the random forest classifier. The performance of the models was assessed according to the area under the curve (AUC) in the receiver operating characteristic curve. Survival analysis was performed to determine the difference in progression-free survival (PFS) between the two groups with the prediction label generated by the combined model. The radiomic model based on the combination of precontrast and postcontrast CT radiomic features and the clinical model produced an AUC of 0.92±0.04 and 0.89±0.03, respectively. By integrating radiomic and clinical features together, the combined model had the best performance with an AUC of 0.94±0.02. The survival analysis showed that the two groups had significantly different PFS times (p<0.0001). The baseline multidimensional data including CT radiomic and multiple clinical features were valuable in predicting the efficacy of ICIs monotherapy in patients with advanced NSCLC.

Clinical indication diagnostic reference level (DRLCI) and post-optimization image quality for Adult Computed Tomography Examinations in Enugu, south eastern Nigeria

This work established Clinical Diagnostic Reference levels (DRLci) for adult Computed Tomography (CT) examination and its application in the practice of medical imaging and Radiology. We also assessed post-optimization image quality as a panacea for dose optimization. The study was a prospective study conducted in five centres in Enugu, Nigeria with ethical certificate no NHREC/05/01/2008B-FWA00002485-1RB00002323. Dose values and technical parameters were obtained using International Commission on Radiological Protection (ICRP) Publication 135.Protocols were used as specified in Siemens machine for helical pre and post contrast CT examination. Scan parameters such as Field of view, pitch, rotation time, tube output, Kv, mAs and slice thickness were documented. Quality control checks were carried out on the machines. Adult patients from 18 years and above that presented to for CT investigation of the head, chest or abdomen from November 2018 to April 2021 were included in the study. A total of 2490 patients with distribution 1200 brain scans (48.2%), 420 chest scans (16.9%) and 870 abdominal scans (34.9%) were studied from the 5 participating centres (one public and four private CT centres). The distribution were as follows: Head - CVA (300), Trauma (300), Metastasis/abscess (300), Infection (180), Seizure (120). Chest - Lung disease (240), Lung cancer/mass (180). Abdomen/Pelvis - Abdominal cancer/metastasis (120), Abdominal mass (300), Liver disease (240), Urography (210). The adult patient's weight was 50 ± 10 kg. Objective image quality assessment was carried out via signal to noise ratio (SNR) analysis prior to data collection. Pearson correlation was used to compare the mean dose quantities, age and sex. Dose values for CT centres and between previous literatures were determined using student t-test at 0.05 level of significance. 476(39.7%) were females and 724(60.3%) were males. Out of the 420 patients that underwent the chest scan, 204(48.6%) were females and 216(51.4%) were males. For the Abdomen/Pelvis scan with 870 patients, 411(47.2%) were females and 459(52.8%) were males. For head CT, the CTDIvol for trauma, CVA, metastasis, infection and seizure are 43, 43, 43, 34 and 28 mGy respectively. Their corresponding DLP includes; 907, 879, 1689, 969, 995 mGy cm. In the chest, the CTDI for lung disease and mass are 13 and 13 mGy. Their corresponding DLP includes; 763 and 1531 mGy cm. In the abdomen, the CTDIvol for liver disease, malignancy, mass and urography are 16, 12, 16, and 15 mGy. Their corresponding DLP includes; 2723, 2011, 2011, 2047 mGy cm.The CTDIvol values in this study for head, chest and abdomen/pelvis region are below the European commission value (1999) with a p value of 0.024, 0.018, and 0.000 respectively All the images were accepted by the radiologist and has comparable signal to noise ratio (SNR) dose reduction from the optimization process. Almost all the centres have their dose value below the estimated DRL for Enugu and up to 50% dose reduction. Clinical indications DRL for 10 common clinical indications in CT examination were established. The study showed wide variations in patient dose between hospitals and even between identical scanners for different clinical indications. Clinical Indication DRLs developed for pre and post contrast studies are useful for dose optimization.

Pre-contrast CT calcium score correlation with significant risk factors for coronary artery disease

Computed Tomography (CT) scan is one of the most widely used methods for evaluating the pre-contrast CT calcium scoring. This study aims to assess the correlation of pre-contrast CT calcium scoring with major risk factors for coronary artery disease (CAD). A descriptive study was conducted from Oct 2021 to Jan 2022 and included 109 patients. The mean age of the patients was 54.5 ± 14.1 (range 40–79) years old. The spreadsheet was used to gather the data via Picture Archive and Communication System (PACS) from the radiology department of King Salman Specialist Hospital, Hail (KSSHH). The study showed the percentage of male and female patients were 41.0% and 59.0%, respectively. More than zero calcium score among males was found to be 67.0%, whereas among females, it was at least 50.0%. The male group of 60–79 years old was found to be the most effected age group with more than zero calcium, while the female age group of 70–79 years showed the same zero calcium score. The percentage of calcium prevalence (score >0) in coronary arteries is affected by a number of risk factors. Coronary artery calcium (CAC) has emerged as a consistent means for assessing the risk of primary cardiovascular outcomes, especially for asymptomatic people. This study showed that the patient group with more than one risk factor for coronary heart disease had no evidence of calcium scoring. Study recommends to enlarge sample size in the coming future studies and to perform calcium scoring using CT scan before computed tomography angiofraphy (CTA).

Clinical value of deep vein thrombosis density on pre-contrast and post-contrast lower-extremity CT for prediction of pulmonary thromboembolism.

There was a lack of studies assessing the relationship between deep vein thrombosis (DVT) Hounsfield unit (HU) density and pulmonary thromboembolism (PTE). To evaluate the clinical value of DVT density measured on pre- and post-contrast lower-extremity computed tomography (CT) for the prediction of PTE. From 2017 to 2021, patients who underwent pulmonary CT angiography within one week after diagnosis of DVT on lower-extremity CT were included in this retrospective study. Then, the patients without PTE were included in "DVT group" and those with both DVT and PTE were included in the "DVT-PTE group." The DVT HU density was measured by drawing free-hand region of interests (ROIs) within the thrombus at the most proximal filling defect level. A receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of DVT density for the risk of PTE. This study included a total of 94 patients (DVT group: n=56; DVT-PTE group: m=38). DVT density was significantly higher in the DVT-PTE group than the DVT group in both pre-contrast (53.5 ± 6.2 HU vs. 44.1 ± 7.9 HU; P < 0.001) and post-contrast CT (67.0 ± 8.6 HU vs. 57.1 ± 10.6 HU; P < 0.001). ROC analysis revealed that the area under curve, sensitivity, and specificity for predicting the risk of PTE were 0.739, 71.1%, and 64.2%, respectively, at a DVT density cutoff of 48.2 HU on pre-contrast CT and were 0.779, 73.7%, and 69.6% at a DVT density cutoff of 61.8 HU on post-contrast CT. The DVT density on both pre- and post-contrast CT could be a predictive factor of PTE.

Distinguishing between metastatic and benign adrenal masses in patients with extra-adrenal malignancies.

Background and ObjectivesThe adrenal gland is a common organ involved in metastasis. This study aimed to compare adrenal metastases (AMs) and adrenal benign masses (ABMs) of patients with extra-adrenal malignancies during the staging or follow-up.MethodsWe retrospectively collected data from 120 patients with AMs and 87 patients with ABMs. The clinical characteristics, imaging features, pathology, and treatment regimes were analyzed.ResultsThe most common types of extra-adrenal malignancies in patients with ABMs included thyroid, kidney, and gynecological cancers. On the other hand, lung and kidney cancers and lymphoma were the most frequent primary cancers of AMs. The age and incidence of symptoms were significantly higher in patients with AM. Radiological analysis showed that AMs tended to have larger tumor sizes and higher attenuation values than ABMs on pre-contrast computed tomography (CT). The diagnostic accuracy of positron emission tomography-CT for AM was 94.1%. An adrenal biopsy had a diagnostic accuracy of 92.5%. A multivariate logistic regression model demonstrated that the origins of extra-adrenal malignancies, the enhancement pattern, and attenuation values in pre-contrast CT were independent predictors of AMs. The sensitivity and specificity of this predictive model of combination was 92.5% and 74.1%, respectively.ConclusionsThe differential diagnosis between AMs and ABMs is extremely important. The combination of origin of first malignancy, enhancement pattern and CT value in non-enhanced phase is a valuable model for predicting AMs.

Transient Small Bowel Angio-oedema Secondary to Intravenous Iodinated Contrast Medium

We report the clinical profile and computed tomography (CT) findings of a rare case of transient angio-edema of the small bowel following intravenous administration of non-ionic iodinated contrast material in a 36-year-old woman. The pre-contrast CT showed normal small bowel and large bowel wall thickness. Findings included long segment, circumferential bowel wall thickening involving the duodenum, jejunum, and almost the entire ileum on CT scan obtained following the intravenous contrast material injection. The large bowel wall appeared normal in post contrast images also. There was no mesenteric fat stranding, ascites or significant lymphadenopathy. This entity, like most contrast-induced adverse reactions, has a favorable clinical outcome with aggressive clinical monitoring and supportive measures.

CT-Based Radiomics Nomogram for Differentiation of Anterior Mediastinal Thymic Cyst From Thymic Epithelial Tumor.

ObjectivesThis study aimed to distinguish preoperatively anterior mediastinal thymic cysts from thymic epithelial tumors via a computed tomography (CT)-based radiomics nomogram.MethodsThis study analyzed 74 samples of thymic cysts and 116 samples of thymic epithelial tumors as confirmed by pathology examination that were collected from January 2014 to December 2020. Among the patients, 151 cases (scanned at CT 1) were selected as the training cohort, and 39 cases (scanned at CT 2 and 3) served as the validation cohort. Radiomics features were extracted from pre-contrast CT images. Key features were selected by SelectKBest and least absolute shrinkage and selection operator and then used to build a radiomics signature (Rad-score). The radiomics nomogram developed herein via multivariate logistic regression analysis incorporated clinical factors, conventional CT findings, and Rad-score. Its performance in distinguishing the samples of thymic cysts from those of thymic epithelial tumors was assessed via discrimination, calibration curve, and decision curve analysis (DCA).ResultsThe radiomics nomogram, which incorporated 16 radiomics features and 3 conventional CT findings, including lesion edge, lobulation, and CT value, performed better than Rad-score, conventional CT model, and the clinical judgment by radiologists in distinguishing thymic cysts from thymic epithelial tumors. The area under the receiver operating characteristic (ROC) curve of the nomogram was 0.980 [95% confidence interval (CI), 0.963–0.993] in the training cohort and 0.992 (95% CI, 0.969–1.000) in the validation cohort. The calibration curve and the results of DCA indicated that the nomogram has good consistency and valuable clinical utility.ConclusionThe CT-based radiomics nomogram presented herein may serve as an effective and convenient tool for differentiating thymic cysts from thymic epithelial tumors. Thus, it may aid in clinical decision-making.

Relation of Serum Albumin Levels to Myocardial Extracellular Volume in Patients With Severe Aortic Stenosis

Severe aortic stenosis (AS) is often characterized by myocardial interstitial fibrosis. Myocardial interstitial fibrosis, classically measured by magnetic resonance imaging, was also shown to be accurately measured by computed tomography (CT)-derived extracellular volume fraction (ECVF). Serum albumin (SA) level (g/dl) has been shown to correlate with ECVF among patients with heart failure and preserved ejection fraction. Our objective was to evaluate the association between SA and ECVF among patients with severe symptomatic AS. Patients with symptomatic severe AS who were evaluated as candidates for intervention between 2016 and 2018 were enrolled prospectively. All patients underwent precontrast and postcontrast CT for estimating myocardial ECVF. Valid ambulatory SA within 6 weeks of the cardiac CT were obtained and classified as (tertiles) <3.8, 3.8 to 4.19, and ≥4.2 g/dl. Patients with acute systemic illness at the time of the albumin test were excluded. The study included 68 patients, mean age 81 ± 6 years, 53% women. Patients with lower SA were more likely to have chronic renal failure, previous percutaneous coronary interventions, and a reduced functional class. The mean ECVF (%) in the study cohort was 41 ± 12%, significantly higher among the patients in the lower SA level groups (50 ± 12% vs 38 ± 7% vs 33 ± 9% in the <3.8 g/dl, 3.8 to 4.19 g/dl and ≥4.2 g/dl groups respectively, p for trend <0.001). A statistically significant inverse correlation was found between SA levels and ECVF (r -0.7, p <0.001). Multivariable analysis showed significant independent association between low SA and ECVF. In conclusion, the SA level is inversely associated with CT-derived ECVF in patients with severe AS.

A comparative study between high-definition volumetric imaging computed tomography and multi-slice computed tomography in the detection of acute thoraco-lumbar disc extrusions in dogs

Computed tomography (CT) is commonly used to image intervertebral disc extrusion (IVDE) in dogs. The current gold standard for CT imaging is the use of multi-slice CT (MS CT) units. Smaller high-definition volumetric imaging (HDVI) mobile CT has been marketed for veterinary practice. This unit is described as an advanced flat panel. The goal of this manuscript was to evaluate the ability of the HDVI CT in detecting IVDE without the need for CT myelography, compared with the detection of acute disc extrusions with a MS CT without the need for MS CT myelogram. Retrospective blinded analyses of 219 dogs presented for thoraco-lumbar IVDE that had a HDVI CT (n = 123) or MS CT (n = 96) were performed at a single referral hospital. A total of 123 cases had HDVI CT scans with surgically confirmed IVDE. The IVDE was identified in 88/123 (72%) dogs on pre-contrast HDVI CT. The remaining 35/128 (28%) cases required a HDVI CT myelogram to identify the IVDE. Ninety-six cases had MS CT scans with surgically confirmed IVDE. The IVDE was identified in 78/96 (81%) dogs on the pre-contrast MS CT. The remaining 18/96 (19%) cases had a MS CT myelogram to identify the IVDE. Multi-slice CT detected IVDE significantly more than HDVI CT (p = 0.032). This study showed that the ability of HDVI CT for detecting IVDE is lower than that of MS CT. The HDVI CT system may be useful in smaller referral practices, with a lower case load where space is limited.

Effect of image quality on myocardial extracellular volume quantification using cardiac computed tomography: a phantom study.

The image quality directly affects the accuracy of computed tomography (CT) extracellular volume (ECV) quantification. To investigate the effects of image quality and acquisition protocol on the accuracy of ECV quantification. One-volume scans were performed on a 320-row multidetector CT volume scanner using a multi-energy CT phantom. To simulate the blood pool and myocardium, solid rods representing blood and soft tissue were used in precontrast CT. Moreover, the solid rods including different iodine concentrations were used in postcontrast CT. The tube voltage was set at 120 kVp, and the tube current was changed from 750 mA (100% dose) to 190 mA (25% dose). All images underwent full- and half-scan reconstructions based on model-based iterative reconstruction. The ECV was calculated from the CT numbers between pre- and postcontrast. The mean ECV with full- and half-scan reconstructions at the central portion was 0.275 at 100% scan dose to 0.271 at 25% scan dose and 0.276 at 100% scan dose to 0.269 at 25% scan dose. Compared with that in the 100% scan dose, the variation in each ECV increased with decreasing radiation dose. The ECV at the center of the image along the z-axis had lower variation than that at outer portion of the images. On the reconstruction algorithm, there was no statistical difference in ECVs with full- and half-scan reconstructions. For stable ECV quantifications, excessive radiation dose reduction may be inappropriate, and it is better to consider the variations in ECV values depending on the slice location.

CT imaging features of the normal parathyroid gland in the dog.

Aim of our prospective pilot study was to assess the feasibility of computed tomography (CT) to visualize the normal parathyroid gland in dogs and provide a description of its CT appearance. A total of 25 dogs, which received CT imaging including the neck region for diseases unrelated to the thyroid or parathyroid glands, were enrolled. Inclusion criteria were a normal physical examination, an unremarkable complete blood count and serum chemistry profile. Pre and post contrast CT images were acquired using a 16-slice helical scanner with an 18 cm field of view, 1 mm slice thickness and a 512 × 512 matrix. Post contrast images were obtained 30-45 seconds following contrast medium injection (early venous phase). CT-images were independently reviewed by 2 radiologists. Visibility of the parathyroid gland was recorded and inter-observer agreement was calculated. For all visualized parathyroid glands the following parameters were assessed: size, density in Hounsfield units (HU) on pre and post contrast images, density of the thyroid gland and border definition (excellent, moderate, poor). Only 20 respectively 25 parathyroid glands could be visualized by the 2 observers. The number did not vary between pre and post contrast images. The inter-observer agreement for the identification was fair (κ = 0.40). Length, width and height (mean ± standard deviation) of the parathyroid gland were 4.2 × 2.5 × 2.9 mm ± 1.3 × 0.8 × 1.0 mm. The density was 39.7 ± 20.6 HU on pre contrast images and 103.1 ± 47.1 HU on post contrast images, thus the organ was hypoattenuating compared to the thyroid gland on pre (166.7 ± 34.3 HU) and post contrast (234.0 ± 60.1 HU) images. This study offers the first description of the CT appearance of the presumed normal canine parathyroid gland. However, the overall visibility was poor. Despite the overall poor visibility of the parathyroid gland it was occasionally visible and its CT dimensions were larger as described for ultrasound in this group of dogs, which showed no clinical signs of hyperparathyroidism. Thus, visibility of the parathyroid gland on CT may not necessarily imply parathyroid disease. However, further research is necessary.

CT Image-Based Texture Analysis to Predict Microvascular Invasion in Primary Hepatocellular Carcinoma.

The objective of this study was to determine the clinical value of computed tomography (CT) image-based texture analysis in predicting microvascular invasion of primary hepatocellular carcinoma (HCC). CT images of patients with HCC from May 2017 to May 2019 confirmed by surgery and histopathology were retrospectively analyzed. Image features including tumor margin, tumor capsule, peritumoral enhancement, hypoattenuating halo, intratumoral arteries, and tumor-liver differences were assessed. All patients were divided into microvascular invasion (MVI)-negative group (n = 34) and MVI-positive group (n = 68). Preoperative CT images were further imported into MaZda software, where the regions of interest of the lesions were manually delineated. Texture features of lesions based on pre-contrast, arterial, portal, and equilibrium phase CT images were extracted. Thirty optimal texture parameters were selected from each phase by Fisher's coefficient (Fisher), classification error probability combined with average correlation coefficient (POE+ACC), and mutual information (MI). Finally, receiver operating characteristic curve analysis was performed. The results showed that the Edmonson-Steiner grades, tumor size, tumor margin, and intratumoral artery characteristics were significantly different between the two groups (P = 0.012, < 0.001, < 0.001, = 0.003, respectively). There were 58 parameters with significant differences between the MVI-negative and MVI-positive groups (P < 0.001 for all). Among them, 12, 14, 17, and 15 parameters were derived from the pre-contrast phase, arterial phase, portal phase, and equilibrium phase respectively. According to the ROC analysis, optimal texture parameters based on the pre-contrast, arterial, portal, and equilibrium phases were 135dr_GLevNonU (AUC, 0.766; the cutoff value, 1055.00), Vertl_RLNonUni (AUC, 0.764; the cutoff value, 5974.38), 45dgr_GLevNonU (AUC, 0.762; the cutoff value, 924.34), and Vertl_RLNonUni (AUC, 0.754; the cutoff value, 4868.80), respectively. Texture analysis of preoperative CT images may be used as a non-invasive method to predict microvascular invasion in patients with primary hepatocellular carcinomas, and further to guide the treatment and evaluate prognosis. The most valuable parameters were derived from the gray-level run-length matrix.

Evaluate the Differences in CT Features and Serum IgG4 Levels between Lymphoma and Immunoglobulin G4-Related Disease of the Orbit.

Background: Benign immunoglobulin G4 (IgG4)-related orbital disease (IgG4-ROD)—characterized as tumors mimicking malignant orbital lymphoma (OL)—responds well to steroids, instead of chemotherapy, radiotherapy and/or surgery of OL. The objective of this study was to report the differences in computed tomography (CT) features and- serum IgG4 levels of IgG4-ROD and OL. Methods: This study retrieved records for patients with OL and IgG4-ROD from a pathology database during an eight-year-and-five-month period. We assessed the differences between 16 OL patients with 27 lesions and nine IgG4-ROD patients with 20 lesions according to prebiopsy CT features of lesions and prebiopsy serum IgG4 levels and immunoglobulin G (IgG) levels This study also established the receiver-operating curves (ROC) of precontrast and postcontrast CT Hounsfield unit scales (CTHU), serum IgG4 levels, serum IgG levels and their ratios. Results: Significantly related to IgG4-ROD (all p < 0.05) were the presence of lesions with regular borders, presence of multiple lesions—involving both lacrimal glands on CT scans—higher median values of postcontrast CTHU, postcontrast CTHU/precontrast CTHU ratios, serum IgG4 levels and serum IgG4/IgG level ratios. Compared to postcontrast CTHU, serum IgG4 levels had a larger area under the ROC curve (0.847 [95% confidence interval (CI): 0.674–1.000, p = 0.005] vs. 0.766 [95% CI: 0.615–0.917, p = 0.002]), higher sensitivity (0.889 [95% CI: 0.518–0.997] vs. 0.75 [95% CI: 0.509–0.913]), higher specificity (0.813 [95% CI: 0.544–0.960] vs. 0.778 [95% CI: 0.578–0.914]) and a higher cutoff value (≥132.5 mg/dL [milligrams per deciliter] vs. ≥89.5). Conclusions: IgG4-ROD showed distinct CT features and elevated serum IgG4 (≥132.5 mg/dL), which could help distinguish IgG4-ROD from OL.

Combined Assessment of Pulmonary Ventilation and Perfusion with Single-Energy Computed Tomography and Image Processing

To establish a proof-of-principle for combined assessment of pulmonary ventilation and perfusion using single-energy computed tomography (CT) and image processing/analysis (denoted as single-energy CT ventilation/perfusion imaging). Breath-hold CT scans were acquired at end-expiration and end-inspiration before injection of iodinated contrast agents, and repeated at end-inspiration after contrast injection for 17 canines (8 normal and 9 diseased lung subjects). Ventilation images were calculated with deformable image registration to map the end-expiratory and end-inspiratory CT images and quantitative analysis for regional volume changes as surrogates for ventilation. Perfusion images were calculated by subtracting the end-inspiratory precontrast CT from the deformably registered end-inspiratory postcontrast CT, yielding a map of regional Hounsfield unit enhancement as a surrogate for perfusion. Ventilation-perfusion matching, spatial heterogeneity, and gravitationally directed gradients were compared between two groups using a Wilcoxon rank-sum test. The normal group had significantly higher Dice similarity coefficients for spatial overlap of segmented functional volumes between ventilation and perfusion (median 0.40 vs. 0.33, p = 0.05), suggesting stronger ventilation-perfusion matching. The normal group also had greater Spearman's correlation coefficients based on 16 regions of interest (median 0.58 vs. 0.40, p = 0.09). The coefficients of variation were comparable (median, ventilation 0.71 vs. 0.91, p = 0.60; perfusion 0.63 vs. 0.75, p = 0.27). The linear regression slopes of gravitationally directed gradient were also comparable for ventilation (median, ventilation -0.26 vs. -0.18, p = 0.19; perfusion -0.17 vs. -0.06, p = 0.11). These findings provide proof-of-principle for single-energy CT ventilation/perfusion imaging.