CT Features Research Articles

Assessment of high-risk gastroesophageal varices in cirrhotic patients using quantitative parameters from dual-source dual-energy CT.

To investigate the clinical value of dual-source dual-energy CT (dsDECT) quantitative parameters in evaluating hemodynamics and predicting high-risk gastroesophageal varices in cirrhotic patients. 98 consecutive patients were collected in this prospectively study and all patients underwent an abdominal triple-phase contrasted-enhanced examination with dsDECT. Iodine concentration (IC) and normalized iodine concentration (NIC) of the liver parenchyma, spleen parenchyma and aorta at different phases were recorded, and arterial iodine fraction (AIF), iodine washout rate (IWR), and extracellular volume (ECV) were calculated. Using upper gastrointestinal endoscopy as the reference standard, patients who met the inclusion and exclusion criteria were divided into groups with varices need treatment (VNT) and non-VNT. The clinical characteristics, traditional CT features and quantitative dsDECT parameters were compared between the VNT group and the non-VNT group using univariate analysis. The binary logistics analysis was used to build a model for diagnosing VNT. The receiver operating characteristic (ROC) curve was used for analysis and the DeLong test was used to compare different ROC curves. Finally, 57 patients were included in this study. Univariate analysis showed statistically significant differences in NIC of the liver at the portal venous phase (NIC-LPVP), IWR of the liver (IWR-L) and spleen volume between the VNT group and the non-VNT group (p < 0.05). The mixed-CT model was built by binary logistics analysis. The ROC curves of NIC-LPVP, IWR-L, spleen volume and the mixed-CT model were statistically significant (p < 0.05) for predicting VNT in cirrhotic patients, among which the area under the ROC curve of the mixed-CT model was the highest. Dual-source dual-energy CT has added clinical value in evaluating hepatic hemodynamics and diagnosing VNT in patients with liver cirrhosis.

The Utility of Cardiac Computed Tomographic Angiography in Differentiating Between Papillary Fibroelastoma, Infective Endocarditis, and Degeneration of the Aortic Valve

Purpose Cardiac computed tomography angiography (CCTA) has significantly advanced the visualization of cardiac structures, particularly valves. We assessed the diagnostic performance of CCTA in diagnosing the most common disorders affecting the aortic valves requiring surgery—papillary fibroelastoma, infective endocarditis, and degeneration. Methods This retrospective study included patients who underwent aortic valve resection between 2016 and 2023 and had a preceding CCTA. Pathologic diagnoses were categorized into the following 3 groups: papillary fibroelastoma, infective endocarditis, and degeneration. Each case was independently evaluated by 3 cardiac-trained radiologists. Results The study group consisted of 50 patients with aortic valvular disorder—14 papillary fibroelastoma, 13 endocarditis, and 23 degeneration. Diagnostic accuracy varied from 70% to 74% among the 3 readers, with a pooled accuracy of 71% and consensus accuracy of 76%. Most errors involved small (≤7 mm) papillary fibroelastomas. Both papillary fibroelastomas and endocarditis-related vegetations typically presented with nodules on CT; however, nodule stalks were only observed with papillary fibroelastomas. Echocardiography aided in distinguishing between the disorders by detecting leaflet perforation and aortic regurgitation in cases of infective endocarditis. Conclusions This study evaluated cardiac CTA for noninvasive characterization of aortic valvular disorders prior to resection. Reader accuracy ranged from 70% to 74%, improving to 76% with consensus interpretations. Small papillary fibroelastomas (≤7 mm) and overlapping imaging features, such as nodular lesions and leaflet thickening, were diagnostic challenges. Greater awareness of these CT characteristics is essential for accurate diagnosis and clinical management.

Infantile Sinonasal Tract Myxomas with Orbital Involvement: Presentation of Two Cases and Comprehensive Literature Review

Objective: Our aim is to present two cases of infantile sinonasal tract myxoma with orbital involvement and conduct a comprehensive literature review of the topic. We aim to provide a summary of the presentation of infantile sinonasal tract myxomas to effectively aid clinicians in considering this rare entity as a potential diagnosis. Methods: We present a case series and a retrospective review of the published literature in the English language. A search was conducted between 1945 and 2023 on sinonasal myxoma. Cases of infantile (&lt;3 years) sinonasal myxoma in the literature were reported as well as two cases of our own. Data was collected from each of the identified articles on the age of presentation, sex, initial presentation, tumor location, imaging, pathology, and treatment. Results: Forty-eight cases of sinonasal myxoma in children &lt;3 years of age were identified. These cases had a slight male preponderance (F:M, 1:1.39) and an average age of diagnosis of sixteen months. Of the cases included, the majority involved the maxilla and maxillary sinuses (83.3%) and commonly presented with a painless slow-growing mass in the region of the tumor. Characteristic CT findings are homogenous solid masses with heterogeneous contrast enhancement. On MRI, these lesions appear hypointense on T1 with highly variable contrast enhancement and hyperintense on T2. Conclusions: We present two cases of infantile sinonasal myxoma with secondary orbital involvement followed by a major review. Treatment of these cases with surgical excision (confirmed clear margins) provided 0% rates of recurrence in the reported cases. Due to the rarity of these tumors and recent histological reclassification, a comprehensive review of this condition will assist clinicians in their management of it.

High Diagnostic Accuracy of Arterial Phase CT in Differentiating Pheochromocytoma in Good/Poor Washout Adrenal Masses

Abstract Introduction Differentiating pheochromocytomas from other adrenal masses based on CT characteristics remains challenging, particularly in lipid-poor lesions with variable washout patterns. This study evaluated CT features for distinguishing pheochromocytomas in good and poor washout sub-cohorts. Methods We prospectively analyzed 72 patients with unilateral lipid-poor adrenal masses. CT protocol included basal, bolus-tracked arterial, early venous (45 seconds post-arterial), and delayed (15 minutes post-arterial) phases. Masses were categorized into good and poor washout groups. Histopathology provided the final diagnosis. CT characteristics and calculated indices were compared between pheochromocytomas and other masses in each washout category. Results The cohort included pheochromocytomas (n=35), adrenocortical carcinoma (ACC, n=15), lipid-poor adenomas (n=13), and metastatic infiltration/infection (n=9). In the good washout group, pheochromocytomas (n=15) showed larger diameters (6.00 vs. 3.45 cm, p=0.001), higher necrosis frequency (73.3% vs. 30%, p=0.049), and greater arterial attenuation (173.2 vs. 74.5 HU, p&amp;lt;0.001) compared to adenomas (n=9). Arterial attenuation provided a high discriminatory value (AUC: 0.967), with 100% sensitivity at 87.6 HU and 100% specificity at 139.9 HU. In the poor washout group, pheochromocytomas (n=20) exhibited higher arterial attenuation (99.2 vs. 59.2 HU, p&amp;lt;0.001; AUC: 0.844) compared to ACC (n=14), metastatic infiltration (n=9), and adenomas (n=4), with 85% sensitivity and 78% specificity at 73.3 HU. Normetanephrine-secreting/non-secretory pheochromocytomas showed higher arterial enhancement than metanephrine-secreting ones (132.0 vs. 90.5 HU, p=0.020) within the poor washout group. Conclusion Arterial phase attenuation on CT has good diagnostic accuracy for differentiating pheochromocytomas from other adrenal masses in both good and poor washout categories, potentially guiding hormonal workup.

Secondary organising pneumonia associated to COVID-19 infection in patients with central nervous system inflammatory demyelinating diseases treated with anti-CD20 therapies.

Organizing pneumonia (OP), an interstitial lung disease, has been observed in patients with inflammatory demyelinating diseases (IDDs) treated with anti-CD20, particularly after COVID-19, but data are limited. To provide a detailed characterization of COVID-19-associated OP in IDD patients treated with anti-CD20. Bi-centric retrospective cohort study including patients with multiple sclerosis (MS), aquaporin-4-positive neuromyelitis optica spectrum disorder (AQP4 + NMOSD), and myelin oligodendrocyte glycoprotein antibody disease (MOGAD) who received anti-CD20 and were diagnosed with COVID-19-associated OP between March 2020 and October 2023. Nineteen patients were included (mean age 46.8 years; 52.6% female; 63% rituximab, 37% ocrelizumab). Sixteen had MS, two MOGAD, and one AQP4 + NMOSD. Intermittent fever was the predominant symptom. Hospitalization occurred in all but one patient, without fatalities. Chest CT consistently showed OP patterns. Thirteen patients had positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR in bronchoalveolar lavage. Treatments included corticosteroids, antivirals, monoclonal antibodies, and convalescent plasma. Fourteen patients postponed infusions; nine resumed post-recovery (median 11.9 months), two switched due to hypogammaglobulinemia, and three stopped. After a mean follow-up of 1.5 years, lung abnormalities and clinical manifestations resolved in 18 patients; however, 13 experienced long-COVID. In anti-CD20-treated patients with recurrent fever and distinctive CT features, COVID-19-associated OP should be considered.

Association between duration of phenoxybenzamine use and postoperative delirium in suspected adrenal pheochromocytoma: a retrospective cohort study

BackgroundAt present, the available evidence regarding the relationship between duration of phenoxybenzamine use and postoperative delirium is inadequate in suspected adrenal pheochromocytoma.ObjectiveTo understand how changes in the duration of phenoxybenzamine use may affect postoperative delirium. The secondary objective of this study is to explore how the duration of phenoxybenzamine use may jointly influence postoperative delirium together with other interacting variables.MethodsWe conducted a retrospective cohort study involving 527 participants with a preoperative diagnosis of suspected pheochromocytoma. CT characteristics, preoperative preparation, intraoperative infusion, estimated bleeding, use of intraoperative vasoactive drugs, and outcomes were obtained from all participants. Logistic regression and interaction effects were utilized to substantiate the research objectives.ResultsA total of 108 (20.5%) developed postoperative delirium, which was seen in 37 (18.0%) in the pheochromocytoma group and 71 (22.0%) in the non-pheochromocytoma group. The incidence of postoperative delirium showed no statistically significant differences in the two groups. A positive association between the duration of phenoxybenzamine use and the risk of postoperative delirium was observed (OR = 1.05, 95%CI = 1.03–1.08, p &amp;lt; 0.01), independent of confounders. The relationship between the duration of phenoxybenzamine use and postoperative delirium differed according to the presence or absence of pheochromocytoma, suggesting an interactive effect (p &amp;lt; 0.05).ConclusionThis study highlights the influence of inappropriate duration of phenoxybenzamine use on the risk of incident postoperative delirium, independent of confounders. The effect of duration of phenoxybenzamine use causes a further increase in the risk of postoperative delirium, especially in non-pheochromocytomas.

Imaging and clinical manifestations of hematogenous dissemination in melioidosis

BackgroundAlthough there is a high incidence of hematogenous infections in melioidosis, a tropical infectious disease, there are few systematic analyses of hematogenous melioidosis in imaging articles. A comprehensive clinical and imaging evaluation of hematogenous melioidosis be conducted in order to achieve early diagnosis of the disease.Materials and methodsWe conducted an analysis of 111 cases of melioidosis diagnosed by bacteriological culture between August 2001 and September 2022. The analysis focused on observing the main manifestations of chest imaging and clinical data, including nodules, cavities, consolidation, ground glass opacity(GGO), pleural effusion, centrilobular nodules, and temperature, leucocyte count, diabetes, etc. Our study involved univariate and multivariate analyses to identify significant diagnostic variables and risk predictive factors.ResultsA total of 71.2% (79/111) of melioidosis cases were caused by hematogenous infection, and the most common organ involved was the lungs (88.5%, 100/113). The incidence of sepsis in patients with lung abnormalities was high (73%, 73/100), and the mortality rate of septic shock was 22% (22/100). Univariate analysis showed that the radiologic signs of blood culture-positive cases were more likely to have bilateral pulmonary and subpleural nodules (p = 0.003), bilateral GGO (p = 0.001), bilateral hydrothorax (p = 0.011). The multivariate analysis revealed a significant improvement in the area under the receiver operating characteristic curve (AUC) when comparing the model that included both clinical and radiologic variables to the model with clinical variables alone. The AUC increased from 0.818 to 0.932 (p = 0.012). The most important variables in the logistic regression with backward elimination were found to be nodule, GGO, and diabetes.ConclusionThe combination of CT features and clinical variables provided a valuable and timely warning for blood borne infectious melioidosis.

Identification of gunshot entry wounds using hyperdense rim sign on post-mortem computed tomography.

Post-mortem computed tomography (PMCT) is an increasingly utilized tool in forensic medicine for evaluating head gunshot injuries. Vault bevelling sign, when present, provides information regarding entry and exit wounds; when absent, identifying wound type on PMCT remains challenging. A cutaneous hyperdense ring, described in an animal study by Junno et al. (2022), may be indicative of contact shots. We hypothesized that it could also be observed in human gunshot injuries. Our study evaluates the reliability of the cutaneous hyperdense rim sign for identifying entry gunshot wounds in PMCT. After excluding complex and mucosal wounds, two operators retrospectively evaluated 64 gunshot wounds (30 entry and 34 exit wounds) in 34 head PMCT cases (2018-2022). Gold standard for wound type determination was the autopsy report. The hyperdense rim sign was defined as at least two-thirds of a continuous cutaneous hyperdense circle on a multiplanar reconstruction of cutaneous tissue tangent to the wound. The hyperdense rim sign demonstrated a specificity of 97% (95% CI: 85-100%) and a sensitivity of 63% (95% CI: 44-80%) for identifying entry wounds. Moreover, in 16 external examination reports where the presence of powder residues or bullet wipe at entry wound was explicitly mentioned, a positive association was observed between hyperdense rim sign and the presence of these elements (p = 0.018). These findings suggest that the hyperdense rim sign, when present, may be a valuable tool for entry wound determination in gunshot injuries, interpreted in conjunction with other CT and autopsy features.

Machine learning techniques for diagnosis of rare diseases from medical images

Introduction/Background: Rare diseases are life-threatening or chronically debilitating conditions that affect a small percentage of the population. Early and accurate diagnosis of rare diseases is challenging due to their complexity and limited understanding. Conventional diagnostic methods are often inadequate, time-consuming, and expensive. Machine learning (ML) has emerged as a promising technique for the analysis of medical images to support the diagnosis of various diseases including rare disorders. ML algorithms can learn complex patterns from large medical imaging datasets to aid clinicians in disease diagnosis, prognosis, and detection of complications. Materials and Methods: A structured search was conducted in electronic databases, including PubMed, Scopus, Web of Science, and Google Scholar to identify peer-reviewed articles published between 2013 to 2023 related to ML-based diagnosis of rare diseases from medical images. A total of 187 articles were identified after removing duplicates. The titles and abstracts of retrieved articles were screened to determine their relevance based on the research objective. Finally, 51 full-text articles were selected for the final review. The key data extracted from selected studies included diseases, imaging modalities, ML algorithms, performance metrics, datasets, and limitations. Results: Most studies evaluated deep learning-based ML techniques, with convolutional neural networks (CNN) being the most applied algorithm. CNNs were mainly used to classify rare diseases based on specific imaging features in X-rays, CT, and MRI scans. Diseases frequently investigated included cardiovascular, neurological, and rare genetic disorders. Publicly available datasets such as Deep Lesion, MSD, and ChestX-ray14 were commonly utilized. Most studies reported high classification accuracy ranging from 80-95% on test datasets. However, limited generalizability due to small private datasets and lack of external validation were limitations. Discussion: The results demonstrate the potential of deep learning for the image-based diagnosis of rare diseases. Features learned from large imaging data sets enabled CNNs to distinguish subtle abnormalities. Hybrid models combining CNNs with other techniques like recurrent neural networks further improved performance. Overall, ML showed promise as a decision support tool. However, more multi-center validation studies are needed using larger and diverse datasets before clinical adoption. Standardization of performance metrics and reporting is also required to establish reliability and generalizability. Conclusion: This comprehensive review provided insights into ongoing research applying ML to medical images for rare disease diagnosis. While initial results are encouraging, further work is still necessary before ML can be reliably used in clinical decision making. Larger collaborative efforts and open-source datasets are needed to advance the field. Standardization of ML frameworks can also promote reproducible research and comparison of different methodologies.

Marked osteopenia as a CT feature of confirmed multiple myeloma in a dog

AbstractA 6‐year‐old, female, spayed Airedale terrier, presented with a 7‐day history of right pelvic limb lameness and a 2‐day history of gingival bleeding and melaena. A mild bi‐cytopenia had been reported 2 years before during a regular check‐up, and this was still present a week before referral. A computed tomographic study of the thorax and abdomen showed marked osteopenia and multifocal coalescent areas of geographic osteolysis affecting predominantly the axial skeleton with concurrent pathological rib fractures. Bone marrow cytology and histopathology were compatible with multiple myeloma given an increased numbers of plasma cells (&gt;70%). To the authors’ knowledge, this is the first reported case of marked generalised osteopenia detected as a computed tomography imaging feature of multiple myeloma.

Clinical and CT characteristics for predicting lymph node metastasis in patients with synchronous multiple primary lung adenocarcinoma

PurposeThis study aims to investigate the risk factors for lymph node metastasis (LNM) in synchronous multiple primary lung cancer (sMPLC) using clinical and CT features, and to offer guidance for preoperative LNM prediction and lymph node (LN) resection strategy.Materials and methodsA retrospective analysis was conducted on the clinical data and CT features of patients diagnosed with sMPLC at the Third Affiliated Hospital of Kunming Medical University from January 1, 2018 to December 31, 2022. Patients were classified into two groups: the LNM group and the non-LNM (n-LNM) group. The study utilized univariate analysis to examine the disparities in clinical data and CT features between the two groups. Additionally, multivariate analysis was employed to discover the independent risk variables for LNM. The diagnostic efficacy of various parameters was evaluated using the receiver operating characteristic (ROC) curve.ResultsAmong the 688 patients included in this study, 59 exhibited LNM. Univariate analysis revealed significant differences between the LNM and n-LNM groups in terms of gender, smoking history, CYFRA21-1 level, CEA level, NSE level, lesion type, total lesion diameter, main lesion diameter, spiculation sign, lobulation sign, cavity sign, and pleural traction sign. Logistic regression identified CEA level (OR = 1.042, 95%CI: 1.009-1.075), lesion type (OR = 9.683, 95%CI: 3.485-26.902), and main lesion diameter (OR = 1.677, 95%CI: 1.347-2.089) as independent predictors of LNM. The regression equation for the joint prediction was as follows: logit(p)= -7.569+0.041*CEA level +2.270* lesion type +0.517* main lesion diameter.ROC curve analysis showed that the AUC for CEA level was 0.765 (95% CI, 0.694–0.836), for lesion type was 0.794 (95% CI, 0.751–0.838), for main lesion diameter was 0.830 (95% CI, 0.784–0.875), and for the combine predict model was 0.895 (95% CI, 0.863–0.928).ConclusionThe combination of clinical and imaging features can better predict the status of LNM of sMPLC, and the prediction efficiency is significantly higher than that of each factor alone, and can provide a basis for lymph node management decision.

Synergizing traditional CT imaging with radiomics: a novel model for preoperative diagnosis of gastric neuroendocrine and mixed adenoneuroendocrine carcinoma.

To develop diagnostic models for differentiating gastric neuroendocrine carcinoma (g-NEC) and gastric mixed adeno-neuroendocrine carcinoma (g-MANEC) from gastric adenocarcinoma (g-ADC) based on traditional contrast enhanced CT imaging features and radiomics features. We retrospectively analyzed 90 g-(MA)NEC (g-MANEC and g-NEC) patients matched 1:1 by T-stage with 90 g-ADC patients. Traditional CT features were analyzed using univariable and multivariable logistic regression. Tumor segmentation and radiomics features extraction were performed with Slicer and PyRadiomics. Feature selection was conducted through univariable analysis, correlation analysis, LASSO, and multivariable stepwise logistic. The combined model incorporated clinical and radiomics predictors. Diagnostic performance was assessed with ROC curves and DeLong's test. The models' diagnostic efficacy was further validated in subgroup of g-NEC vs. g-ADC and g-MANEC vs. g-ADC cases. Tumor necrosis and lymph node metastasis were independent predictors for differentiating g-(MA)NEC from g-ADC (P < 0.05). The clinical model's AUC was 0.700 (training) and 0.667(validation). Five radiomics features were retained, with the radiomics model showing AUC of 0.809 (training) and 0.802 (validation). The combined model's AUCs were 0.853 (training) and 0.812 (validation), significantly outperforming the clinical model (P < 0.05). Subgroup analysis revealed that the combined model exhibited acceptable performance in differentiating g-NEC from g-ADC and g-MANEC from g-ADC, with AUCof0.887 and 0.823 in the training cohort and 0.852 and 0.762 in the validation cohort. A combined model based on traditional CT imaging and radiomic features provides a non-invasive and effective preoperative diagnostic method for differentiating g-(MA)NEC from g-ADC.

Characterization of exclusive rib lesions detected by [68Ga]Ga-PSMA-11 PET/CT.

The objective of this study was to characterize exclusive costal lesions detected by 68Gallium-labelled prostate-specific membrane antigen ([68Ga]Ga-PSMA-11) PET/computed tomography (CT) at initial staging or biochemical recurrence (BCR) in prostate cancer (PCa) patients, and to identify clinical and/or PET/CT criteria associated with benign and malignant lesions. We retrospectively identified 54 patients with PCa who underwent [68Ga]Ga-PSMA-11 PET/CT for initial staging (N = 39) or BCR (N = 15) and whose reports described rib lesions, at the exclusion of any other lesions, whether doubtful, suspicious, or established. Posttherapy prostate-specific antigen (PSA) levels were used to determine whether those lesions were benign or malignant. Each patient's prostate-specific membrane antigen PET/CT report was classified as true positive, true negative, false positive, or false negative based on the posttherapy PSA level. We then assessed whether any clinical and/or PET/CT criteria could help differentiate benign from malignant lesions, and if any criteria were misleading. Among the 54 patients, 46 (85.2%) had 64 benign costal lesions, and eight (14.8%) had 10 malignant lesions. PET/CT reports indicated rib lesions as benign/equivocal in 38/54 (55.6%) patients and malignant in 16/54 (29.6%). Benign features on CT were the only parameter significantly associated with the final diagnosis. Factors such as patient age, maximum standardized uptake value of lesions, lesion dispersion, and malignant features described on CT were found to be misleading when deciding the malignant or benign status. Most exclusive costal lesions detected by [68Ga]Ga-PSMA-11 PET/CT are benign. Apart from specific benign CT features, no clinical or PET/CT criteria reliably differentiate benign from malignant costal lesions.

CT Features of Fibrous Dysplasia

CT Features of Fibrous Dysplasia

Dual Sulfone-Bridged Triphenylamine Heteroaromatics for High-Performance Blue Organic Electroluminescence.

Polycyclic heteroaromatics (PHAs) are a highly versatile class of functional materials, especially applicable as efficient luminophores in organic light-emitting diodes (OLEDs). Those constructed by tethered phenyl surrounding the main group center attract extensive attention due to their excellent OLED device performance. However, the development of such a class of emitters is often limited to boron, nitrogen-doped π-conjugated heterocycles. Herein, we proposed a novel kind of blue emitter by constructing a donor-acceptor molecular configuration, utilizing a dual sulfone-bridged triphenylamine (BTPO) core and mono/di-diphenylamine (DPA) substituents. The twisted D-A molecular structures and appropriate donor strength facilitate the effective separation of natural transition orbitals, endowing the emitters with charge-transfer dominant hybridized local and charge-transfer characteristics for the excited states. Both BTPO-DPA and BTPO-2DPA own small S1-T1 splitting energy, thus demonstrating blue thermally activated delayed fluorescence. The more symmetrical structure and enhanced CT features brought by additional DPA moiety confer BTPO-2DPA with a shorter delayed fluorescence lifetime, a higher fluorescence quantum yield and narrower emission. Therefore, BTPO-2DPA based OLED devices exhibit superior blue electroluminescence performance, with external quantum efficiencies reaching 12.31 %.

CT and MRI of pancreatic cystic lesions: tricks of the trade

PurposeTo describe CT and MRI findings of pancreatic cystic lesions.BackgroundThe growing use of ultrasound, CT and MRI has led to increasing incidental detection of pancreatic cystic lesions. These lesions range from benign entities (e.g., acute necrotic collection) to potentially malignant neoplasms (e.g., IPMN) and malignant neoplasms (e.g., ductal adenocarcinoma). CT and MRI can help to differentiate pancreatic cystic lesions.FindingsPancreatic cystic lesions neoplasms often have pathognomonic CT and MRI characteristics. It is important to consider size, number of cysts, septa, the relationship with the main pancreatic duct, internal nodules and wall enhancement. Guidelines from different societies have been developed to promote and standardize the management and follow-up of pancreatic cystic lesions.ConclusionCT and MRI play a crucial role in the detection and characterization of pancreatic cystic lesions.

Comparison of computed tomography findings between perianal tumors originating from the anal sacs and perianal glands in dogs.

Tumors originating from the anal sacs and perianal glands are common tumors of the perianal region. However, differentiation of perianal tumors based on CT findings remains challenging because perianal tumors can show overlapping CT characteristics. Therefore, this retrospective, multi-institutional study aimed to identify the CT findings that can differentiate between tumors originating from the anal sacs and perianal glands in canines. Twenty dogs were included, with nine apocrine gland anal sac adenocarcinomas (AGASACAs), six perianal gland adenomas, three perianal gland carcinomas, and two perianal gland epitheliomas. The tumor CT features included the tumor growth pattern, tumor shape, cystic changes within the tumor, contrast enhancement pattern, displacement of the anus, and identification of the anal sacs. The prevalences of suspected metastatic lymphadenopathy of the iliosacral lymph centers and lung metastases were evaluated. The tumor volumes and values normalized to body weight were also assessed. The tumor growth patterns differed significantly between AGASACAs and perianal gland tumors. AGASACAs mostly showed unilateral growth, whereas perianal gland tumors mostly exhibited bilateral growth. CT features, except for the tumor growth pattern, failed to show significant differences between tumors arising from the anal sacs and those arising from the perianal glands. Although histopathological diagnosis remains the gold standard, this study's findings suggest that CT analysis of tumor growth patterns may help differentiate AGASACAs from perianal gland tumors.

CT and MRI radiographic characteristics of seminal vesicle cysts

PurposeSeminal vesicle cysts are relatively uncommon benign lesions. Early and accurate diagnosis is crucial for guiding appropriate management strategies. The purpose of this study was to investigate the radiographic characteristics of seminal vesicle cysts in order to enhance the diagnostic proficiency of radiologists. MethodsWe conduct a comprehensive descriptive analysis of the CT and MRI findings pertaining to 15 patients with seminal vesicle cyst, complemented by a brief literature review. ResultThe mean age of 15 patients with seminal vesicle cyst was 57.53 ± 17.0 years. Among these patients, 53.33% (8/15) were incidentally detected, while 40% (6/15) presented with symptoms of abdominal or pelvic pain. One patient exhibited hematospermia. In 86.67% (13/15) of cases, the cysts were unilateral, while the remaining 13.33% (2/15) were bilateral. Radiological assessment comprised CT scans for 7 patients, MRI scans for 12 patients, and a combination of both modalities for 4 patients. Imaging characteristics revealed 11 cases of unilocular cysts and 4 cases of multilocular cysts, with the largest measuring approximately 16.0 × 9.8 cm. CT imaging distinctly demonstrated punctate or nodular calcification along the cyst wall in 3 cases. MRI, on the other hand, facilitated the visualization of cystic contents, including mucinous protein in 9 cases and hemorrhagic components in 2 cases. ConclusionThe radiographic manifestations of seminal vesicle cysts exhibit distinct characteristics, CT and MRI imaging modalities are instrumental in facilitating their accurate diagnosis.

Computed tomography of acute orbital trauma in children: a retrospective study

INTRODUCTION: Orbital injuries account for 36 to 64% of all blunt trauma to the facial bones. Diagnosis of orbital wall fractures is carried out using conventional radiography in several projections and computed tomography; magnetic resonance imaging is less commonly used. Often, due to the small displacement of orbital bone fragments, X-ray diagnosis is difficult. Multislice CT with reconstruction of sagittal, coronal projections and 3D in the bone window in such cases is the best visualization method. However, there are still no clear indications for the use of each method and there is no complete view of the CT characteristics of orbital damage.OBJECTIVE: To study the diagnostic value of computed tomography of orbital fractures in pediatric patients with acute trauma.MATERIAL AND METHODS: Retro- and prospectively analyzed the results of CT scans of 94 patients with facial fractures from 01/01/2023 to 09/01/2023 to assess combined orbital injuries. Orbital fractures were detected in 63 children (67.0%). There were 44 boys (69.84%), 19 girls (30.15%) aged from 7 months to 17 years 10 months (average age 10.3). Statistics: For statistical analysis, the method of calculating the nominal correlation using the Kramer coefficient (V) using the IBM SPSS Statistics software package was used.RESULTS: Concomitant injury was observed in 30 (47.6%); isolated 33 (52.36%). The number and frequency of fractures observed were as follows: superior wall of the orbit — 39 (61.9%); zygomatic complex — 19 (30.1%); lower wall of the orbit — 43 (68.2%); nasal bone — 17 (26.9%); lower jaw — 6 (9.5%); medial wall of the orbit — 28 (44.4%); upper jaw — 27 (42.8%); alveolar process — 6 (9.5%); isolated zygomatic arch — 14 (22.2%); Le Fort type I — 1 (1.5%); Le Fort type II — 2 (3.1%); and Le Fort type III — 0 (0%). Orbital hematomas were found in 25 patients (39.6%). It was revealed a strong correlation between the presence of contiguous skull fractures and multiple skull fractures (V=0.878, p&lt;0.001), frontal sinus fractures and frontal sinus hemosinus (V=0.69, p&lt;0.001).CONCLUSION: Orbital fractures are a frequent type of facial fracture occurring in children with blunt isolated and combined trauma. In children with blunt trauma, head CT combined with clinical examination is currently the optimal tool for diagnosing clinically significant orbital injuries. There is a strong correlation between orbital hematomas and orbital vault fractures, orbital hematomas and lattice fractures, adjacent skull and orbital vault fractures, and adjacent skull and lattice fractures. CT examination should include multiplanar (in coronal and sagittal planes) and 3D reconstructions, which help to assess the extent of the fracture, the presence of diastasis, the degree of muscle impingement. Based on the data obtained, the clinician determines the need for surgical intervention.

Prediction of benign and malignant ground glass pulmonary nodules based on multi-feature fusion of attention mechanism.

The purpose of this study was to develop and validate a new feature fusion algorithm to improve the classification performance of benign and malignant ground-glass nodules (GGNs) based on deep learning. We retrospectively collected 385 cases of GGNs confirmed by surgical pathology from three hospitals. We utilized 239 GGNs from Hospital 1 as the training and internal validation set, and 115 and 31 GGNs from Hospital 2 and Hospital 3, respectively, as external test sets 1 and 2. Among these GGNs, 172 were benign and 203 were malignant. First, we evaluated clinical and morphological features of GGNs at baseline chest CT and simultaneously extracted whole-lung radiomics features. Then, deep convolutional neural networks (CNNs) and backpropagation neural networks (BPNNs) were applied to extract deep features from whole-lung CT images, clinical, morphological features, and whole-lung radiomics features separately. Finally, we integrated these four types of deep features using an attention mechanism. Multiple metrics were employed to evaluate the predictive performance of the model. The deep learning model integrating clinical, morphological, radiomics and whole lung CT image features with attention mechanism (CMRI-AM) achieved the best performance, with area under the curve (AUC) values of 0.941 (95% CI: 0.898-0.972), 0.861 (95% CI: 0.823-0.882), and 0.906 (95% CI: 0.878-0.932) on the internal validation set, external test set 1, and external test set 2, respectively. The AUC differences between the CMRI-AM model and other feature combination models were statistically significant in all three groups (all p<0.05). Our experimental results demonstrated that (1) applying attention mechanism to fuse whole-lung CT images, radiomics features, clinical, and morphological features is feasible, (2) clinical, morphological, and radiomics features provide supplementary information for the classification of benign and malignant GGNs based on CT images, and (3) utilizing baseline whole-lung CT features to predict the benign and malignant of GGNs is an effective method. Therefore, optimizing the fusion of baseline whole-lung CT features can effectively improve the classification performance of GGNs.