scholarly journals Computed Tomography Features and Clinical Prognostic Characteristics of Hepatoid Adenocarcinoma of the Stomach

2021 ◽  
Vol 11 ◽  
Author(s):  
Wen-peng Huang ◽  
Li-ming Li ◽  
Jing Li ◽  
Jun-hui Yuan ◽  
Ping Hou ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Survival Time ◽  
Vascular Invasion ◽  
External Validation ◽  
Arterial Phase ◽  
Tumor Diameter ◽  
Hepatoid Adenocarcinoma ◽  
Factors Affecting ◽  
Ct Attenuation ◽  
Degree Of Differentiation

PurposeHepatoid adenocarcinoma of the stomach (HAS) is a highly malignant and aggressive tumor. The purpose of this study was to describe the clinical, computed tomography (CT), and prognostic features of HAS to increase the awareness of this entity and determine its distinguishing features from non-HAS tumors.MethodsThe CT features and clinical data of 47 patients in our hospital with pathologically documented HAS were retrospectively analyzed, and the relevant differences between pure HAS (pHAS) and mixed HAS (mHAS) were determined. In addition, 141 patients with non-HAS tumors in the same T stage in the same period were selected as the control group. The data were compared between the two groups, and factors affecting the prognosis of HAS were analyzed. In addition, we included 9 patients with HAS and 27 patients with non-HAS tumors from another center for external validation.ResultsThe patients in the HAS group were predominantly men (n = 33), and the tumor location was mostly the cardia or fundus (n = 27). Between the HAS and non-HAS groups, there were observed differences in terms of: sex, serum alpha-fetoprotein (AFP), carbohydrate antigen (CA)-125, and CA-724 levels; longest tumor diameter; degree of differentiation; vascular invasion; N stage, M stage, and tumor-node-metastasis (TNM) stage; thickest tumor diameter; plain CT attenuation; arterial-phase CT attenuation; CT attenuation between the venous and arterial phases; enhancement modes; and degrees of enhancement (all P < 0.05). In the data from another center for external validation, there were observed differences in terms of: age, degree of differentiation, vascular invasion, thickest tumor diameter, the ratio of arterial CT attenuation to CT attenuation of the abdominal aorta at the same level (RA), CT attenuation difference between the venous phase and arterial phase (HUv-a) (all P < 0.05). The results of the multivariate analysis revealed that the independent factors for differentiation were serum AFP level (P = 0.001), M stage (P = 0.038), and tumor enhancement on CT (P = 0.014). Among patients in the HAS group, 72.34% had pHAS and 27.66% had mHAS. The thickest tumor diameter and the longest short diameter of the metastatic lymph nodes of the mHAS group were on average 6.39 cm and 1.45 cm, respectively, which were larger than those in the pHAS group. The median progression-free survival time was 18.25 months in the HAS group, which was shorter than that in the non-HAS group (72.96 months; P = 0.001). The median overall survival time in the HAS group was 24.80 months, which was shorter than that in the non-HAS group (67.96 months; P = 0.001). The factors affecting the prognosis of HAS were M stage (P = 0.001), overall TNM stage (P = 0.048), presence of vascular cancer emboli (P = 0.040), and pHAS type (P = 0.046). Multifactorial analysis revealed that M stage (P = 0.027) and pHAS type (P = 0.009) were independent risk factors affecting the prognosis of HAS.ConclusionAlthough HAS is a rare clinical entity, it should be considered in the differential diagnosis of gastric tumors. Patients with HAS often have advanced-stage disease at presentation and a worse prognosis than patients with non-HAS tumors. CT findings, combined with laboratory results, can support the diagnosis of HAS. However, the final diagnosis needs to be confirmed with a histopathologic examination. If the postoperative pathologic findings reveal the mHAS type, a rapid clinical intervention and a detailed follow-up with CT are essential.

Pre-operative Diagnosis of Pancreatic Neuroendocrine Tumors with Endoscopic Ultrasonography and Computed Tomography in a Large Series

2016 ◽  
Vol 25 (3) ◽  
pp. 317-321 ◽  
Author(s):  
Raffaele Manta ◽  
Elisabetta Nardi ◽  
Nico Pagano ◽  
Claudio Ricci ◽  
Mariano Sica ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Neuroendocrine Tumors ◽  
Endoscopic Ultrasonography ◽  
Fine Needle Aspiration ◽  
Chromogranin A ◽  
Needle Aspiration ◽  
Large Series ◽  
Tumor Diameter ◽  
Pancreatic Neuroendocrine Tumors ◽  
Fine Needle

Background & Aims: Diagnosis of pancreatic neuroendocrine tumors (p-NETs) is frequently challenging. We describe a large series of patients with p-NETs in whom both pre-operative Computed Tomography (CT) and Endoscopic Ultrasonography (EUS) were performed. Methods: This was a retrospective analysis of prospectively collected sporadic p-NET cases. All patients underwent both standard multidetector CT study and EUS with fine-needle aspiration (FNA). The final histological diagnosis was achieved on a post-surgical specimen. Chromogranin A (CgA) levels were measured. Results: A total of 80 patients (mean age: 58 ± 14.2 years; males: 42) were enrolled. The diameter of functioning was significantly lower than that of non-functioning p-NETs (11.2 ± 8.5 mm vs 19.8 ± 12.2 mm; P = 0.0004). The CgA levels were more frequently elevated in non-functioning than functioning pNET patients (71.4% vs 46.9%; P = 0.049). Overall, the CT study detected the lesion in 51 (63.7%) cases, being negative in 26 (68.4%) patients with a tumor ≤10 mm, and in a further 3 (15%) cases with a tumor diameter ≤20 mm. CT overlooked the pancreatic lesion more frequently in patients with functioning than non-functioning p-NETs (46.5% vs 24.3%; P = 0.002). EUS allowed a more precise pre-operative tumor measurement, with an overall incorrect dimension in only 9 (11.2%) patients. Of note, the EUS-guided FNA suspected the neuroendocrine nature of tumor in all cases. Conclusions: Data of this large case series would suggest that the EUS should be included in the diagnostic work-up in all patients with a suspected p-NET, even when the CT study was negative for a primary lesion in the pancreas.– . Abbrevations: CgA: chromogranin A; EUS: Endoscopic Ultrasonography; FNA: fine-needle aspiration; p-NETs: pancreatic neuroendocrine tumors.

Individual Factors Affecting Computed Tomography Densitometry Measurements

2018 ◽  
Vol 2 (12) ◽  
Author(s):  
Kıyasettin Asil ◽  
Bora Kalaycıoğlu ◽  
Kamran Mahmutyazıcıoğlu
Keyword(s):  
Computed Tomography ◽  
Individual Factors ◽  
Factors Affecting

scholarly journals The Influence of Pre-Procedural Imaging and Cystic Duct Cholangiography on Endoscopic Transpapillary Gallbladder Drainage in Acute Cholecystitis

Diagnostics ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1286
Author(s):  
Junya Sato ◽  
Kazunari Nakahara ◽  
Yosuke Michikawa ◽  
Ryo Morita ◽  
Keigo Suetani ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Acute Cholecystitis ◽  
Cystic Duct ◽  
Magnetic Resonance Cholangiopancreatography ◽  
Procedure Time ◽  
Technical Success ◽  
Factors Affecting ◽  
Gallbladder Drainage ◽  
Procedural Evaluation ◽  
The Relationship

Endoscopic transpapillary gallbladder drainage (ETGBD) for acute cholecystitis is challenging. We evaluated the influence of pre-procedural imaging and cystic duct cholangiography on ETGBD. Patients who underwent ETGBD for acute cholecystitis were retrospectively examined. The rate of gallbladder contrast on cholangiography, the accuracy of cystic duct direction and location by computed tomography (CT) and magnetic resonance cholangiopancreatography (MRCP), and the relationship between pre-procedural imaging and the technical success of ETGBD were investigated. A total of 145 patients were enrolled in this study. Gallbladder contrast on cholangiography was observed in 29 patients. The accuracy of cystic duct direction and location (proximal or distal, right or left, and cranial or caudal) by CT were, respectively, 79%, 60%, and 58% by CT and 68%, 55%, and 58% by MRCP. Patients showing gallbladder contrast on cholangiography underwent ETGBD with a significantly shorter procedure time and a lower rate of cystic duct injury. No other factors affecting procedure time, technical success, and cystic duct injury were identified. Pre-procedural evaluation of cystic duct direction and location by CT or MRCP was difficult in patients with acute cholecystitis. Patients who showed gallbladder contrast on cholangiography showed a shorter procedure time and a lower rate of cystic duct injury.

Pediatric Minor Head Trauma: Factors Affecting the Anxiety of Parents

2021 ◽  
pp. 000992282110096
Author(s):  
Hasan Aldinc ◽  
Cem Gun ◽  
Serpil Yaylaci ◽  
Erol Barbur
Keyword(s):  
Computed Tomography ◽  
Head Trauma ◽  
Pediatric Patients ◽  
Positive Impact ◽  
Cranial Computed Tomography ◽  
Sufficient Information ◽  
Minor Head Trauma ◽  
Computed Tomography Imaging ◽  
Factors Affecting ◽  
X Ray

Managing the anxiety of the parents of pediatric patients with head trauma is challenging. This study aimed to examine the factors that affect anxiety levels of parents whose children were admitted to the emergency department with minor head trauma. In this prospective study, the parents of 663 consecutive pediatric patients were invited to answer a questionnaire. Parents of 600 children participated in the study. The parents who believed they were provided sufficient information and who were satisfied with the service received had significantly more improvement in anxiety-related questions. Cranial X-ray assessment had a significantly positive impact on the anxiety of the parents, whereas cranial computed tomography and neurosurgery consultation did not. In assessing pediatric minor head trauma, cranial computed tomography imaging and neurosurgery consultation should not be expected to relieve the anxiety of the parents. However, adequately informing them and providing satisfaction are the factors that could lead to improvement.

Automated Pancreas Segmentation And Volumetry Using Deep Neural Network On Computed Tomography

2021 ◽  
Author(s):  
Sang-Heon Lim ◽  
Young Jae Kim ◽  
Yeon-Ho Park ◽  
Doojin Kim ◽  
Kwang Gi Kim ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Deep Learning ◽  
Automatic Segmentation ◽  
External Validation ◽  
Three Dimensional ◽  
Semantic Segmentation ◽  
Quantitative Information ◽  
Similarity Coefficients ◽  
Internal Validation ◽  
Pancreas Segmentation

Abstract Pancreas segmentation is necessary for observing lesions, analyzing anatomical structures, and predicting patient prognosis. Therefore, various studies have designed segmentation models based on convolutional neural networks for pancreas segmentation. However, the deep learning approach is limited by a lack of data, and studies conducted on a large computed tomography dataset are scarce. Therefore, this study aims to perform deep-learning-based semantic segmentation on 1,006 participants and evaluate the automatic segmentation performance of the pancreas via four individual three-dimensional segmentation networks. In this study, we performed internal validation with 1,006 patients and external validation using the Cancer Imaging Archive (TCIA) pancreas dataset. We obtained mean precision, recall, and dice similarity coefficients of 0.869, 0.842, and 0.842, respectively, for internal validation via a relevant approach among the four deep learning networks. Using the external dataset, the deep learning network achieved mean precision, recall, and dice similarity coefficients of 0.779, 0.749, and 0.735, respectively. We expect that generalized deep-learning-based systems can assist clinical decisions by providing accurate pancreatic segmentation and quantitative information of the pancreas for abdominal computed tomography.

A Fully Automatic Deep Learning System for L3 Slice Selection and Body Composition Assessment on Abdominal Computed Tomography. (Preprint)

2021 ◽  
Author(s):  
Jiyeon Ha ◽  
Taeyong Park ◽  
Hong-Kyu Kim ◽  
Youngbin Shin ◽  
Yousun Ko ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Deep Learning ◽  
External Validation ◽  
Abdominal Muscle ◽  
Anatomic Variations ◽  
Success Rates ◽  
Technical Success ◽  
Segmentation Accuracy ◽  
Distance Difference ◽  
Fully Automatic

BACKGROUND As sarcopenia research has been gaining emphasis, the need for quantification of abdominal muscle on computed tomography (CT) is increasing. Thus, a fully automated system to select L3 slice and segment muscle in an end-to-end manner is demanding. OBJECTIVE We aimed to develop a deep learning model (DLM) to select the L3 slice with consideration of anatomic variations and to segment cross-sectional areas (CSAs) of abdominal muscle and fat. METHODS Our DLM, named L3SEG-net, was composed of a YOLOv3-based algorithm for selecting the L3 slice and a fully convolutional network (FCN)-based algorithm for segmentation. The YOLOv3-based algorithm was developed via supervised learning using a training dataset (n=922), and the FCN-based algorithm was transferred from prior work. Our L3SEG-net was validated with internal (n=496) and external validation (n=586) datasets. L3 slice selection accuracy was evaluated by the distance difference between ground truths and DLM-derived results. Technical success for L3 slice selection was defined when the distance difference was <10 mm. Overall segmentation accuracy was evaluated by CSA error. The influence of anatomic variations on DLM performance was evaluated. RESULTS In the internal and external validation datasets, the accuracy of automatic L3 slice selection was high, with mean distance differences of 3.7±8.4 mm and 4.1±8.3 mm, respectively, and with technical success rates of 93.1% and 92.3%, respectively. However, in the subgroup analysis of anatomic variations, the L3 slice selection accuracy decreased, with distance differences of 12.4±15.4 mm and 12.1±14.6 mm, respectively, and with technical success rates of 67.2% and 67.9%, respectively. The overall segmentation accuracy of abdominal muscle areas was excellent regardless of anatomic variation, with the CSA errors of 1.38–3.10 cm2. CONCLUSIONS A fully automatic system was developed for the selection of an exact axial CT slice at the L3 vertebral level and the segmentation of abdominal muscle areas.

scholarly journals Hepatocellular carcinoma in patients undergoing orthotopic liver transplantation: radiological findings with anatomopathological correlation in Brazil

2006 ◽  
Vol 43 (1) ◽  
pp. 24-29 ◽  
Author(s):  
Antônio Carlos Maciel ◽  
Carlos Thadeu Cerski ◽  
Roger Klein Moreira ◽  
Vinicius Labrea Resende ◽  
Maria Lúcia Zanotelli ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Hepatocellular Carcinoma ◽  
Liver Transplantation ◽  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Orthotopic Liver Transplantation ◽  
Imaging Techniques ◽  
Arterial Phase ◽  
Hepatitis C Virus Infection ◽  
Cirrhotic Patients

BACKGROUND: Hepatocellular carcinoma is one of the most common malignant tumors worldwide. Imaging techniques, specially computed tomography and ultrasound, are among the most useful diagnostic tools, although the accuracy of these methods may have a significant variability. AIMS: To determine the prevalence of hepatocellular carcinoma in cirrhotic patients undergoing orthotopic liver transplantation at "Santa Casa de Misericórdia" of Porto Alegre, RS, Brazil; to estimate the sensitivity of computed tomography and ultrasound in pretransplantation detection of hepatocellular carcinoma in this population; to correlate the radiological characteristics with anatomopathological findings. MATERIALS AND METHODS: Retrospective prevalence study. Population: adult, cirrhotic patients undergoing orthotopic liver transplantation from January 1990 to July 2003. Among the 292 transplanted patients, 31 cases of hepatocellular carcinoma were diagnosed, of which 29 were included in the study. Tumor characteristics in both ultrasound and computed tomography were compared to those observed in anatomopathological examination. RESULTS: Prevalence of hepatitis C virus infection among patients with diagnosis of hepatocellular carcinoma was 93.5%, and the prevalence of hepatocellular carcinoma among transplanted patients was 10.6%. The overall sensitivity of the imaging techniques was 70.3% for computed tomography and 72% for ultrasound. CONCLUSION: The prevalence of hepatocellular carcinoma at our institution, as well as the sensitivity of both ultrasound and computed tomography to detect such tumors at pretransplantation screening were similar to those found by other authors, while the prevalence of hepatitis C virus infection, the most common etiological agent for liver disease in our patients, is one of the highest ever reported in literature. Factors influencing hepatocellular carcinoma detection rates were: time from examination to liver transplantation; acquisition of computed tomography images during arterial phase; lesion size. Arterial phase proved to be the most useful part of computed tomography examination in this study.

scholarly journals Factors Affecting Radiation Dose in Computed Tomography Angiograms for Pulmonary Embolism: A Retrospective Cohort Study

2020 ◽  
Vol 10 ◽  
pp. 74
Author(s):  
Prashant Nagpal ◽  
Sarv Priya ◽  
Ali Eskandari ◽  
Aidan Mullan ◽  
Tanya Aggarwal ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Pulmonary Embolism ◽  
Radiation Dose ◽  
Care Center ◽  
Tertiary Care ◽  
Multivariate Logistic Regression Analysis ◽  
Factors Affecting ◽  
Model Based ◽  
Pulmonary Angiogram ◽  
The Mean

Objectives: Computed tomography pulmonary angiogram (CTPA) is one of the most commonly ordered and frequently overused tests. The purpose of this study was to evaluate the mean radiation dose to patients getting CTPA and to identify factors that are associated with higher dose. Material and Methods: This institutionally approved retrospective study included all patients who had a CTPA to rule out acute pulmonary embolism between 2016 and 2018 in a tertiary care center. Patient data (age, sex, body mass index [BMI], and patient location), CT scanner type, image reconstruction methodology, and radiation dose parameters (dose-length product [DLP]) were recorded. Effective dose estimates were obtained by multiplying DLP by conversion coefficient (0.014 mSv•mGy−1•cm−1). Multivariate logistic regression analysis was performed to determine the factors affecting the radiation dose. Results: There were 2342 patients (1099 men and 1243 women) with a mean age of 58.1 years (range 0.2–104.4 years) and BMI of 31.3 kg/m2 (range 12–91.5 kg/m2). The mean effective radiation dose was 5.512 mSv (median – 4.27 mSv; range 0.1–43.0 mSv). Patient factors, including BMI >25 kg/m2, male sex, age >18 years, and intensive care unit (ICU) location, were associated with significantly higher dose (P < 0.05). CT scanning using third generation dual-source scanner with model-based iterative reconstruction (IR) had significantly lower dose (mean: 4.90 mSv) versus single-source (64-slice) scanner with filtered back projection (mean: 9.29 mSv, P < 0.001). Conclusion: Patients with high BMI and ICU referrals are associated with high CT radiation dose. They are most likely to benefit by scanning on newer generation scanner using advance model-based IR techniques.

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