Contrast-enhanced Abdominal Computed Tomography Scan Research Articles

Deep learning image reconstruction algorithms in low-dose radiation abdominal computed tomography: assessment of image quality and lesion diagnostic confidence.

The image quality of computed tomography (CT) can be adversely affected by a low radiation dose, and reconstruction algorithms of an appropriate level may be useful in reducing this impact. Eight sets of CT images of a phantom were reconstructed with filtered back projection (FBP); adaptive statistical iterative reconstruction-Veo (ASiR-V) at 30% (AV-30), 50% (AV-50), 80% (AV-80), and 100% (AV-100); and deep learning image reconstruction (DLIR) at low (DL-L), medium (DL-M), and high (DL-H) levels. The noise power spectrum (NPS) and task transfer function (TTF) were measured. Thirty consecutive patients underwent low-dose radiation contrast-enhanced abdominal CT scans that were reconstructed using FBP, AV-30, AV-50, AV-80, and AV-100, and three levels of DLIR. The standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) of the hepatic parenchyma and paraspinal muscle were evaluated. Two radiologists assessed the subjective image quality and lesion diagnostic confidence using a 5-point Likert scale. In the phantom study, both a higher DLIR and ASiR-V strength and a higher radiation dose led less noise. The NPS peak and average spatial frequency of the DLIR algorithms were closer to those of FBP, as the tube current increased and declined as the level of ASiR-V and DLIR strengthened. The NPS average spatial frequency of DL-L were higher than those of AISR-V. In clinical studies, AV-30 demonstrated a higher SD and lower SNR and CNR compared to DL-M and DL-H (P<0.05). For qualitative assessment, DL-M produced the highest qualitative image quality scores, with the exception of overall image noise (P<0.05). The NPS peak, average spatial frequency, and SD were the highest and the SNR, CNR, and subjective scores were the lowest with FBP. Compared with FBP and ASiR-V, DLIR provided better image quality and noise texture both in the phantom and clinical studies, and DL-M maintained the best image quality and lesion diagnostic confidence in low-dose radiation abdominal CT.

Deep Learning to Detect Pancreatic Cystic Lesions on Abdominal Computed Tomography Scans: Development and Validation Study.

Pancreatic cystic lesions (PCLs) are frequent and underreported incidental findings on computed tomography (CT) scans and can evolve to pancreatic cancer-the most lethal cancer, with less than 5 months of life expectancy. The aim of this study was to develop and validate an artificial deep neural network (attention gate U-Net, also named "AGNet") for automated detection of PCLs. This kind of technology can help radiologists to cope with an increasing demand of cross-sectional imaging tests and increase the number of PCLs incidentally detected, thus increasing the early detection of pancreatic cancer. We adapted and evaluated an algorithm based on an attention gate U-Net architecture for automated detection of PCL on CTs. A total of 335 abdominal CTs with PCLs and control cases were manually segmented in 3D by 2 radiologists with over 10 years of experience in consensus with a board-certified radiologist specialized in abdominal radiology. This information was used to train a neural network for segmentation followed by a postprocessing pipeline that filtered the results of the network and applied some physical constraints, such as the expected position of the pancreas, to minimize the number of false positives. Of 335 studies included in this study, 297 had a PCL, including serous cystadenoma, intraductal pseudopapillary mucinous neoplasia, mucinous cystic neoplasm, and pseudocysts . The Shannon Index of the chosen data set was 0.991 with an evenness of 0.902. The mean sensitivity obtained in the detection of these lesions was 93.1% (SD 0.1%), and the specificity was 81.8% (SD 0.1%). This study shows a good performance of an automated artificial deep neural network in the detection of PCL on both noncontrast- and contrast-enhanced abdominal CT scans.

Transarterial Embolization of Ruptured Pancreaticoduodenal Artery Pseudoaneurysm Related to Chronic Pancreatitis

We presented a 67-year-old woman with lightheadedness, diaphoresis, and acute epigastric and right hypochondrium pain, with a past medical history including stage 2 essential hypertension, chronic ischemic cardiomyopathy, and class 1 obesity. An abdominal contrast-enhanced CT scan showed an extensive hematoma (3 × 4 cm2 in size) located intra-abdominally, adjacent to the duodenojejunal area, with hyperdensity around the duodenum, positioned inferior to the pancreas (30-59 HU). Moreover, the CT scan also revealed an enhancing lesion as a pseudoaneurysm of the inferior pancreaticoduodenal artery, measuring 5 × 8 × 8 mm3 with active bleeding and associated hematoma. Following these investigations of the abdominal area, a decision was made to proceed with an endovascular intervention within the interventional radiology department. With the patient under conscious sedation, via a right common femoral artery approach, the superior mesenteric artery was catheterized. While injecting the contrast agent to obtain a better working projection, the pseudoaneurysm ruptured, and acute extravasation of the contrast agent was noted, followed by injection of a mixture of 1 mL Glubran 2 with 2 mL Lipiodol until complete obliteration of the pseudoaneurysm was obtained. The patient was hemodynamically stable at the end of the procedure and was discharged 6 days later in a good condition without active bleeding signs.

Differentiating Benign From Malignant Cystic Renal Masses: A Feasibility Study of Computed Tomography Texture-Based Machine Learning Algorithms.

The Bosniak classification attempts to predict the likelihood of renal cell carcinoma (RCC) among cystic renal masses but is subject to interobserver variability and often requires multiphase imaging. Artificial intelligence may provide a more objective assessment. We applied computed tomography texture-based machine learning algorithms to differentiate benign from malignant cystic renal masses. This is an institutional review board-approved, Health Insurance Portability and Accountability Act-compliant retrospective study of 147 patients (mean age, 62.4 years; range, 28-89 years; 94 men) with 144 cystic renal masses (93 benign, 51 RCC); 69 were pathology proven (51 RCC, 18 benign), and 75 were considered benign based on more than 4 years of stability at follow-up imaging. Using a single image from a contrast-enhanced abdominal computed tomography scan, mean, SD, mean value of positive pixels, entropy, skewness, and kurtosis radiomics features were extracted. Random forest, multivariate logistic regression, and support vector machine models were used to classify each mass as benign or malignant with 10-fold cross validation. Receiver operating characteristic curves assessed algorithm performance in the aggregated test data. For the detection of malignancy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve were 0.61, 0.87, 0.72, 0.80, and 0.79 for the random forest model; 0.59, 0.87, 0.71, 0.79, and 0.80 for the logistic regression model; and 0.55, 0.86, 0.68, 0.78, and 0.76 for the support vector machine model. Computed tomography texture-based machine learning algorithms show promise in differentiating benign from malignant cystic renal masses. Once validated, these may serve as an adjunct to radiologists' assessments.

Dynamic radiomics for predicting the efficacy of antiangiogenic therapy in colorectal liver metastases.

For patients with advanced colorectal liver metastases (CRLMs) receiving first-line anti-angiogenic therapy, an accurate, rapid and noninvasive indicator is urgently needed to predict its efficacy. In previous studies, dynamic radiomics predicted more accurately than conventional radiomics. Therefore, it is necessary to establish a dynamic radiomics efficacy prediction model for antiangiogenic therapy to provide more accurate guidance for clinical diagnosis and treatment decisions. In this study, we use dynamic radiomics feature extraction method that extracts static features using tomographic images of different sequences of the same patient and then quantifies them into new dynamic features for the prediction of treatmentefficacy. In this retrospective study, we collected 76 patients who were diagnosed with unresectable CRLM between June 2016 and June 2021 in the First Hospital of China Medical University. All patients received standard treatment regimen of bevacizumab combined with chemotherapy in the first-line treatment, and contrast-enhanced abdominal CT (CECT) scans were performed before treatment. Patients with multiple primary lesions as well as missing clinical or imaging information were excluded. Area Under Curve (AUC) and accuracy were used to evaluate model performance. Regions of interest (ROIs) were independently delineated by two radiologists to extract radiomics features. Three machine learning algorithms were used to construct two scores based on the best response and progression-free survival (PFS). For the task that predict the best response patients will achieve after treatment, by using ROC curve analysis, it can be seen that the relative change rate (RCR) feature performed best among all features and best in linear discriminantanalysis (AUC: 0.945 and accuracy: 0.855). In terms of predicting PFS, the Kaplan-Meier plots suggested that the score constructed using the RCR features could significantly distinguish patients with good response from those with poor response (Two-sided P<0.0001 for survival analysis). This study demonstrates that the application of dynamic radiomics features can better predict the efficacy of CRLM patients receiving antiangiogenic therapy compared with conventional radiomics features. It allows patients to have a more accurate assessment of the effect of medical treatment before receiving treatment, and this assessment method is noninvasive, rapid, and less expensive. Dynamic radiomics model provides stronger guidance for the selection of treatment options and precision medicine.

PS-R03-5: HYPOTENSIVE AND HYPERGLYCEMIC EFFECTS OF DIAZOXIDE IN A CASE OF INSULINOMA

Case report: We report the case of sporadic insulinoma in a 70-year-old female with breast cancer and hypertension treated by irbesartan 100 mg and benidipine 8 mg, who presented with a 1-month history of episodic tremulousness, diaphoresis, increased hunger, confusion and fainting. Initial laboratory investigations showed low blood glucose (21 mg/dL) and high blood insulin (107 μU/mL) levels. The hypoglycemic symptoms were relieved greatly by glucose administration and Whipple's triad for insulinoma was met. An abdominal contrast-enhanced computed tomography scan showed a 12 mm, small, well demarcated, heterogeneously enhancing lesion within the tail of pancreas without dilatation of pancreatic duct. The site also showed a well-defined accumulation of boundaries on PET-CT. Patient was diagnosed with insulinoma. Since Patient did not initially wish to undergo surgery, blood glucose control was performed by taking diazoxide 225 mg, gradually reduced to 50 mg. Before and after taking diazoxide, blood glucose increased from 75 ± 40 mg/dL to 124 ± 35 mg/dL significantly (p &lt; 0.05). On the other hand, blood pressure was significantly reduced from 141 ± 3/78 ± 3 mmHg to 126 ± 3/75 ± 3 mmHg. Benidipine was withdrawn to about 130/80 mmHg. Then, Patient changed her mind and underwent laparoscopic caudal pancreatic resection. Histopathological examination of the pancreatic mass confirmed neuroendocrine tumor (insulinoma). Patient had an uneventful recovery. Blood pressure re-increased above 140/90 mmHg and benidipine was resumed. Although diazoxide suppresses insulin secretion in the pancreas due to its KATP channel opening action and improves hypoglycemic attacks with insulinoma, it also acts on the KATP channel of vascular smooth muscle and show a hypotensive effect. It is important to pay close attention not only to blood glucose but also to blood pressure fluctuations when using diazoxide.

Changes in clinical and CT manifestations related to liver abscesses in patients with vs. without basic diabetes mellitus before and after CT-guided interventional therapy: An observational study

PurposeTo explore differences in the changes of clinical and CT manifestations related to liver abscess before and after CT-guided interventional therapy between patients with and without Diabetes Mellitus (DM). Materials and methodsFifty-eight consecutive patients with liver abscesses were retrospectively enrolled in this study. All patients underwent upper abdominal contrast-enhanced CT scans before and after CT-guided interventional therapy. They were divided into two groups including the DM group (n=30) and the Non-DM group (n=28) if the liver abscess occurred in patients with and without DM, respectively. The changes in the clinical and CT manifestations related to liver abscess after CT-guided interventional therapy in both groups were statistically analyzed. ResultsAfter CT-guided interventional therapy, the length of hospital stay, white blood cell recovery time and drainage tube removal time in the DM group were longer than in the Non-DM group (all p-values < 0.05). The incidence of postoperative complications in the DM group was higher than in the Non-DM group (p < 0.05). As shown on CT, the postoperative reduced percentage of maximum diameter of abscess cavity and the reduction rate of edema band surrounding the liver abscess in the DM group were smaller than in the Non-DM group (both p-values < 0.05). The time intervals of the previous characteristic changes on CT before and after interventional therapy in the DM group were longer than in the Non-DM group (all p-values < 0.05). ConclusionsThe liver abscesses patients with DM could not have a faster recovery and better therapeutic effect than those without DM after the CT-guided interventional therapy.

Automated CT pancreas segmentation for acute pancreatitis patients by combining a novel object detection approach and U-Net

Acute pancreatitis is an inflammatory disorder of the pancreas. Medical imaging, such as computed tomography (CT), has been widely used to detect volume changes in the pancreas for acute pancreatitis diagnosis. Many pancreas segmentation methods have been proposed but no methods for pancreas segmentation from acute pancreatitis patients. The segmentation of an inflamed pancreas is more challenging than the normal pancreas due to the following two reasons. 1) The inflamed pancreas invades surrounding organs and causes blurry boundaries. 2) The inflamed pancreas has higher shape, size, and location variability than the normal pancreas. To overcome these challenges, we propose an automated CT pancreas segmentation approach for acute pancreatitis patients by combining a novel object detection approach and U-Net. Our approach includes a detector and a segmenter. Specifically, we develop an FCN-guided region proposal network (RPN) detector to localize the pancreatitis regions. The detector first uses a fully convolutional network (FCN) to reduce the background interference of medical images and generates a fixed feature map containing the acute pancreatitis regions. Then the RPN is employed on the feature map to precisely localize the acute pancreatitis regions. After obtaining the location of pancreatitis, the U-Net segmenter is used on the cropped image according to the bounding box. The proposed approach is validated using a collected clinical dataset with 89 abdominal contrast-enhanced 3D CT scans from acute pancreatitis patients. Compared with other start-of-the-art approaches for normal pancreas segmentation, our method achieves better performance on both localization and segmentation in acute pancreatitis patients.

A spectrum of findings on computed tomography in paediatric abdominal and pelvic tumours in a Ghanaian teaching hospital.

To review the Computed Tomography( CT )features of pediatric oncological patients with abdominal and pelvic tumours and correlate these findings with their histopathological diagnosis. This was a retrospective cross-sectional facility-based study. This study was conducted in the Pediatric Oncology Unit and Radiology Department of the Korle Bu Teaching Hospital. Fifty-six pediatric oncology patients with contrast-enhanced abdominal and pelvic CT scans. The abdominal and pelvic CT scans findings, patient biodata, and histopathology reports of oncology patients over four years were reviewed. Simple descriptive statistics using frequency distribution, percentages, means, and standard deviation were used to describe the various variables and presented tables. The four commonest tumours were nephroblastoma, neuroblastoma, lymphoma, and hepatoblastoma. The mean age at diagnosis was 4.8 years, with a slightly higher male predominance. The majority of the tumours were extremely large at presentation. Overall, the CT - histopathology concordance was 79.2%. Abdominal and pelvic CT scans play an important role in the diagnostic workup of pediatric malignancies by ensuring early and accurate diagnosis of these tumours. None declared.

Spontaneous Left External Iliac Vein Rupture.

Spontaneous rupture of the Iliac Vein is very rare in practice. In over 90% of cases, the venous lesion is located on the left side. The exact etiology of this condition is unknown. Spontaneous injury of the iliac vein is thought to be favored by intense exercise, constipation, cough, labor, May-Thurner syndrome or pre-existing inflammatory changes in the venous wall are also implicated. We present the case of an 83-year-old woman who is brought to the Emergency Department for abdominal pain located in the left flank and in the left iliac fossa, which appeared after a medium physical exertion. After an emergency contrast-enhanced abdominal CT scan, the diagnosis of spontaneous rupture of the left external iliac vein is established. Surgery is performed with extreme urgency by retroperitoneal approach and due to the very precarious condition of the patient, venous ligation is done, wishing to perform a Palma-Dale venous bypass at a later time. Although a rare cause of spontaneous retroperitoneal hematoma, a non-traumatic rupture of the common or external iliac vein should be considered in patients in shock with massive retroperitoneal bleeding, accompanied by a high mortality rate.

Risk prediction of pancreatic cancer using AI analysis of pancreatic subregions in computed tomography images.

Early detection of Pancreatic Ductal Adenocarcinoma (PDAC) is complicated as PDAC remains asymptomatic until cancer advances to late stages when treatment is mostly ineffective. Stratifying the risk of developing PDAC can improve early detection as subsequent screening of high-risk individuals through specialized surveillance systems reduces the chance of misdiagnosis at the initial stage of cancer. Risk stratification is however challenging as PDAC lacks specific predictive biomarkers. Studies reported that the pancreas undergoes local morphological changes in response to underlying biological evolution associated with PDAC development. Accurate identification of these changes can help stratify the risk of PDAC. In this retrospective study, an extensive radiomic analysis of the precancerous pancreatic subregions was performed using abdominal Computed Tomography (CT) scans. The analysis was performed using 324 pancreatic subregions identified in 108 contrast-enhanced abdominal CT scans with equal proportion from healthy control, pre-diagnostic, and diagnostic groups. In a pairwise feature analysis, several textural features were found potentially predictive of PDAC. A machine learning classifier was then trained to perform risk prediction of PDAC by automatically classifying the CT scans into healthy control (low-risk) and pre-diagnostic (high-risk) classes and specifying the subregion(s) likely to develop a tumor. The proposed model was trained on CT scans from multiple phases. Whereas using 42 CT scans from the venous phase, model validation was performed which resulted in ~89.3% classification accuracy on average, with sensitivity and specificity reaching 86% and 93%, respectively, for predicting the development of PDAC (i.e., high-risk). To our knowledge, this is the first model that unveiled microlevel precancerous changes across pancreatic subregions and quantified the risk of developing PDAC. The model demonstrated improved prediction by 3.3% in comparison to the state-of-the-art method that considers the global (whole pancreas) features for PDAC prediction.

S3304 Acute Occlusive Mesenteric Ischemia From Venous and Aortic Thrombosis in a Patient with Hyperhomocysteinemia and Liver Cirrhosis

Introduction: Portal vein thrombosis (PVT) is a severe complication of liver cirrhosis and one of its major consequences include intestinal ischemia. Hyperhomocysteinemia (HHcy) has been suggested to be an independent risk factor for deep venous thrombosis, but limited data are available on the prevalence of HHcy in patients with PVT complicating liver cirrhosis. Several clinical studies have also demonstrated the role of HHcy in arterial and venous thrombosis. Case Description/Methods: We report a case of a 57 year old male with Liver Cirrhosis from Alcoholic Liver Disease, who presented at our ED with a two week history of dull periumbilical pain which worsened on the day of consult. Plain abdominal CT scan showed nonspecific small bowel enteritis. He was placed on general liquid diet and started on Ciprofloxacin and Metronidazole intravenously. However, on the third hospital day, he complained of sudden severe abdominal pain accompanied by abdominal distention, guarding, and direct and rebound tenderness on all quadrants. He had hypotension and on laboratory workup, had decreasing hemoglobin levels with elevated WBC count and lactate. Contrast-enhanced abdominal CT scan revealed portal and superior mesenteric vein thrombosis, bowel wall ischemia along the segment of the jejenum in the left hemiabdomen, and infrarenal abdominal aorta and ascending aorta thrombi. Emergency exploratory laparotomy was done with segmental jejunoileal resection and primary end-to-end anastomosis with intraoperative findings of gangrenous small bowels measuring 100 cm in length, with the rest of the proximal small bowels noted to be dilated and edematous. The patient was transferred to the intensive care unit post-operatively for closer monitoring; Heparin drip was started 24 hours post-surgery. Histopathology results showed extensive transmural infarction, hemorrhage, and necrosis on small bowel segments; organizing thrombi were seen on mesenteric vessels. The patient was worked-up for other causes of hypercoagulable states which showed elevated Homocysteine levels at 20.6 (NV: 5-12). Discussion: It is likely that HHcy may increase the risk of patients with liver cirrhosis to develop arterial and venous thrombosis considering the pivotal role the liver plays in the metabolism of sulphur amino acids and Hcy-related vitamin storage. Therefore, identification of this high-risk group may be important to plan prevention management, such as vitamin supplementation, other Hcy-lowering strategies, or long-term anticoagulation.

Segmentation of Pancreatic Subregions in Computed Tomography Images.

The accurate segmentation of pancreatic subregions (head, body, and tail) in CT images provides an opportunity to examine the local morphological and textural changes in the pancreas. Quantifying such changes aids in understanding the spatial heterogeneity of the pancreas and assists in the diagnosis and treatment planning of pancreatic cancer. Manual outlining of pancreatic subregions is tedious, time-consuming, and prone to subjective inconsistency. This paper presents a multistage anatomy-guided framework for accurate and automatic 3D segmentation of pancreatic subregions in CT images. Using the delineated pancreas, two soft-label maps were estimated for subregional segmentation—one by training a fully supervised naïve Bayes model that considers the length and volumetric proportions of each subregional structure based on their anatomical arrangement, and the other by using the conventional deep learning U-Net architecture for 3D segmentation. The U-Net model then estimates the joint probability of the two maps and performs optimal segmentation of subregions. Model performance was assessed using three datasets of contrast-enhanced abdominal CT scans: one public NIH dataset of the healthy pancreas, and two datasets D1 and D2 (one for each of pre-cancerous and cancerous pancreas). The model demonstrated excellent performance during the multifold cross-validation using the NIH dataset, and external validation using D1 and D2. To the best of our knowledge, this is the first automated model for the segmentation of pancreatic subregions in CT images. A dataset consisting of reference anatomical labels for subregions in all images of the NIH dataset is also established.

Evaluation of the Relationship between Fat Volume and Nephrolithiasis.

To examine the relation between perirenal fat volume, which is one of the visceral fat measurements, and kidney stones. 169 patients admitted to our clinic between January 2018 and May 2021 were included in the study. The patients were divided into 2 groups as Control Group and Unilateral Kidney Stone Group (88 patients with unilateral kidney stones). Contrast-enhanced abdominal computed tomography scans were used to measure perirenal fat volume and the results were transferred to workstations. The total perirenal fat volumes in the bilateral kidneys of patients were compared between the two groups. The perirenal fat volume in stone-bearing and non-stone bearing kidneys of patients were also compared. The total perirenal fat volume was higher in the Unilateral Kidney Stone Group than in the other groups and the perirenal fat volume of the patients in this group was higher in the stone bearing kidney (295.6±164.4cm3) than in the non-stone bearing kidney (273.1±179.6cm3). In the ROC analysis, it was concluded that total perirenal fat volume>387cm3 increased the risk of kidney stones. Presence of hypertension, presence of hyperlipidemia and total perirenal fat volume>387cm3 were found to be independent risk factors for the presence of kidney stones. Perirenal fat volume is higher in stone bearing kidneys compared to non-stone bearing kidneys. Therefore, stone formation in a kidney is directly related to the perirenal fat volume of that kidney. Also, total perirenal fat volume>387cm3 increases the risk of kidney stones independently of body mass index, and predicts it better.

Reduction of Peristalsis-Related Streak Artifacts on the Liver with Dual-Layer Spectral CT.

Background: Peristalsis-related streak artifacts on the liver compromise image quality and diagnostic accuracy. Purpose: To assess dual-layer spectral-detector computed tomography (CT) image reconstructions for reducing intestinal peristalsis-related streak artifacts on the liver. Methods: We retrospectively evaluated 220 contrast-enhanced abdominal dual-energy CT scans in 131 consecutive patients (mean age: 68 ± 10 years, 120 men) who underwent routine clinical dual-layer spectral-detector CT imaging (120 kVp, 40 keV, 200 keV, virtual non-contrast (VNC), iodine images). Two independent readers evaluated bowel peristalsis streak artifacts on the liver qualitatively on a five-point Likert scale (1 = none to 5 = severe) and quantitatively by depth of streak artifact extension into the liver and measurements of Hounsfield Unit and iodine concentration differences from normal liver. Artifact severity between image reconstructions were compared by Wilcoxon signed-rank and paired t-tests. Results: 12 scans were excluded due to missing spectral data, artifacts on the liver originating from metallic foreign materials, or oral contrast material. Streak artifacts on the liver were seen in 51/208 (25%) scans and involved the left lobe only in 49/51 (96%), the right lobe only in 0/51 (0%), and both lobes in 2/51 (4%) scans. Artifact frequency was lower in iodine than in 120 kVp images (scans 18/208 vs. 51/208, p < 0.001). Artifact severity was less in iodine than in 120 kVp images (median score 1 vs. 3, p < 0.001). Streak artifact extension into the liver was shorter in iodine than 120 kVp images (mean length 2 ± 4 vs. 12 ± 5 mm, p < 0.001). Hounsfield Unit and iodine concentration differed significantly between bright streak artifacts and normal liver in 120 kVp, 40 keV, 200 keV, and VNC images (p < 0.001, each), but not in iodine images (p = 0.23). Conclusion: Intestinal peristalsis-related streak artifacts commonly affect the left liver lobe at CT and can be substantially reduced by viewing iodine dual-energy CT image reconstructions.

Clinical Impacts of Juxtapapillary Duodenal Diverticulum Detected on Computed Tomography.

Diverticula are commonly observed in the duodenum. Duodenal Diverticulum (DD) usually does not give symptoms throughout life and is diagnosed by coincidence. However, it may present with different symptoms in patients. This study aims to evaluate the prevalence of DD and Juxtapapillary Duodenal Diverticulum (JDD) and its association with other possible pathologies and to determine its clinical impact by using Computed Tomography (CT). This retrospective observational study, which was taken consecutively between the years of 2013-2020, was evaluated in the Radiology Department. The total number of cases was 4850 (male-2440; female-2410). CT images were evaluated by two experienced radiologists at the workstation. DD and JDD prevalence and clinical findings in the hospital registry system were examined. The age of the patients included in the study ranged from 17 to 92 years (mean age 46.94±16.42). In patients with DD (female-130; male-101), mean age was 62.24 ± 12.69 (21-92). The prevalence of DD was 4.76% (n=231). The prevalence of JDD was 4.02% (n=195) and increased with age (p<0.01). The average diameter of the JDD was measured as 23.29±8.22 (9.5-55.3) mm. A significant positive correlation was found between age and DD diameter (p=0.039). DDs were found most commonly 84.42% (n=195) in the second segment of the duodenum as JDD. In patients with JDD, the mean diameter of choledochus and wirsung canal were 6.7 ± 2.4 (3-15.3) mm and 0.31 ± 0.1 (0.1-6.5) mm respectively. The choledochal diameter was correlated with the JDD size (p = 0.004). Cholelithiasis (n=56), choledocholithiasis (n=20), cholecystitis (n=52), diverticulitis (n=15), duodenitis (n=37), pancreatitis (n=5) and hiatal hernia (n=60) with JDD were observed. Periampullary carcinoma was detected in one patient. Our study shows that cholelithiasis, choledocholithiasis, cholecystitis, diverticulitis, duodenitis, pancreatitis may be associated with JDD. Therefore, in contrast-enhanced abdominal CT scans taken for various reasons, investigation of the presence and characteristics of JDD and detection of pathologies that may be associated with JDD are important for patients to benefit from early diagnosis and treatment opportunities and to take precautions against possible complications.

A53 A NOVEL PH-SENSITIVE OPIOID ANALOGUE PROVIDES SUSTAINED ANALGESIA DURING COLONIC INFLAMMATION AND LACKS COMMON SIDE EFFECTS

BackgroundOpioids provide effective pain relief during flares of inflammatory bowel disease but are limited by serious side effects. We showed that acute administration of a novel pH-sensitive opioid agonist, NFEPP, had potent analgesic effects in inflamed acidified colonic tissues without opioid typical side effects. However, the effects of repeated application of NFEPP during the course of an acute flare of colonic inflammation are unknown.AimsTo assess the analgesic and side effect profile resulting from repeated NFEPP applications during the course of acute colitis.MethodsAcute colitis in C57BL/6 mice was induced via 2.5% dextran sulfate sodium dissolved in drinking water for 5 days. Mice were then randomly group assigned to either vehicle, fentanyl or NFEPP. Drugs and vehicle were administered sc. BID for 5 days (0.4 mg/kg), with a final injection on Day 6 (Day 1–6). Visceral nociception was evaluated by performing visceromotor responses (VMRs) to colorectal distension at different time points during colitis. Side effects were assessed using 1) a combination of oral contrast-enhanced abdominal CT-scans (before/after treatment) and defecation assessments to analyze gastrointestinal transit and isometric tension recordings to evaluate colon motility 2) pulse oximeter measurements to reveal cardiorespiratory effects. Inflammation was assessed by histological scoring, myeloperoxidase activity assay and tissue pH measurement of colon samples.ResultsNFEPP decreased VMRs to colorectal distension over the entire period of acute DSS colitis (Day 6: 40.54%, p<0.001, reduction compared to baseline). However, strongest VMR inhibition was observed at Day 3 (66.7%, p<0.05), concordant with the peak of inflammation (MPO: 3.5 U/mg tissue, p<0.001; tissue Damage-Score: 3.0, p<0.001; tissue pH: ΔpH= -0.28, p=0.001, all compared to healthy control). Treatment with NFEPP did not delay gastrointestinal transit (GIT, p=0.37, compared to baseline) nor fecal output (p=0.45, compared to vehicle) whereas fentanyl decreased transit (GIT: p<0.05; fecal output: p<0.05). Colonic contractile responses evoked by electrical field stimulation were reduced in fentanyl treated mice compared to NFEPP (10 Hz: p<0.05). Fentanyl significantly reduced oxygen saturation (15 min: 85% SpO2, p<0.01) and caused a sustained reduction in heart rate at Day 2 (60 min: Δ BPM -91.8 from baseline, p=0.001) whereas NFEPP did not affect oxygen saturation (p=0.95) and revealed minor, transient effects on heart rate (15 min: Δ BPM -75.6, p<0.01) which recovered after 60 min.ConclusionsProlonged NFEPP administration effectively inhibits visceral nociception during acute colitis in a preclinical mouse model without altering gastrointestinal transit, colon motility and oxygen saturation.Funding AgenciesCCC

Tumor enhancement ratio on preoperative abdominal contrast-enhanced CT scan for predicting recurrence risk in stage II colon cancer.

The identification of high recurrence risk stage II colon cancer patients was critical to adjuvant chemotherapy decision. However, current definition of high-risk features remains inadequate. This study aimed to construct a model for predicting recurrence risk based on tumor enhancement ratio (TER) on abdominal contrast-enhanced CT scan. 282 stage II colon cancer patients were included and randomly divided into training and validation sets in the ratio of 7:3. TER was calculated using maximum tumor attenuation value in contrast-enhanced CT scan divided by the minimum. Kaplan-Meier survival analyses were adopted to evaluate the prognostic value of variables. A model based on TER was built to predict recurrence risk through the LASSO Cox model. The recurrence risk score of patients was calculated based on this model. The optimal cut-off value of TER was 1.83 derived from the time-dependent ROC (tdROC) curve. Patients with high-TER showed increasingly poorer disease-free survival (DFS) in both training (p < 0.001) and validation (p < 0.001) sets. A model was built based on TER demonstrated satisfactory performance to recurrence risk prediction (C-index: 0.784 in the training set and 0.725 in the validation set). Patients were regrouped into modified high-risk and non-high risk according to recurrence risk score (cut-off value: 1.75) and a significant DFS difference was observed (training set: p < 0.001; validation set: p < 0.001). TER can serve as a high-risk feature of stage II colon cancer. And a model based on TER provided a new approach to assess recurrence risk of stage II disease.

Radiological evaluation of response to treatment in hepatobiliary fascioliasis

PurposeIn this study, we aimed to evaluate the computed tomography (CT) findings of Fasciola hepatica infestations on initial and follow-up imagings after treatment, and also to describe the role of CT during diagnosis. MethodsIn this retrospective study, patients with a diagnosis of fascioliasis by clinical and laboratory examination who underwent initial and follow-up contrast-enhanced abdominal CT scans after treatment (a single oral dose of 10mg/kg Triclabendazole) were included. The CT scans were evaluated regarding liver and spleen sizes, portal and splenic vein diameters, involved hepatic segment numbers and involvement patterns, the presence of focal perihepatic hyperdensity, gallbladder wall thickening, dilatation of the intrahepatic biliary tract, periportal-right subdiaphragmatic lymphadenopathy, hepatic subcapsular and intra-abdominal bleeding, and perihepatic/intraabdominal free fluid. Initial (pre-treatment) and post-treatment CT scans (average 25 months after the treatment) were compared with for these features. ResultsA total of 36 patients with a mean age of 39.28±14.64 [15-83] years, were included in this study. After treatment, marked improvement in liver parenchymal involvement, biliary system findings, hepatomegaly-splenomegaly, periportal-peridiaphragmatic lymphadenopathy, and hepatic subcapsular hematoma were detected and focal perihepatic hyperdensity, free intraperitoneal fluid disappeared. ConclusionContrast-enhanced abdominal CT can be used in the diagnosis and post-treatment follow-up of fascioliasis. Awareness of intrahepatic/extrahepatic lesions and all the complications of fascioliasis can greatly aid the diagnosis and also evaluation of the response to treatment.

Diagnostic value of abdominal CT scan in ovarian tumors in Dr. Soetomo General Academic Hospital, Surabaya, Indonesia, from January 2017 to December 2018

HIGHLIGHTS1. Ovarian tumors diagnostic value has been determined using the tools on contrast-enhanced abdominal CT Scan2. The tools including primary finding like mass size, septation, solid component, and additional finding such as ascites, peritoneal implants, lymph node enlargement3. Most tumors were ovarian malignant tumors according to their histopathological results 4. Contrast-enhanced abdominal CT Scan of ovarian tumors evaluated by the tools gave better and more reliable diagnostic value than without using the toolsABSTRACTObjectives: The purpose of this study was to determine the diagnostic value of contrast-enhanced abdominal CT scan in ovarian tumors in Dr. Soetomo General Academic Hospital, Surabaya, Indonesia, to provide scientific and clinical benefits.Materials and Methods: Samples were taken retrospectively by contrast-enhanced abdominal CT scan raw data in Dr. Soetomo General Academic Hospital, Surabaya, Indonesia, from January 2017 to December 2018. Using inclusion and exclusion criteria, a total of 88 samples were obtained and reviewed blindly by Female Organ Division of Radiology Department, Faculty of Medicine Universitas Airlangga, and by using "tools" (primary and additional findings of modified ovarian tumors malignancy). The data were correlated with histopathological findings and analyzed by statistical tests and the results with and without "tools" were compared.Results: Samples were grouped by age, distributed with a range of 20 years and the group of 41-60 years had the highest age of ovarian tumor samples (46.6%) with 84.1% being ovarian malignant tumors according to their histopathological results. It was dominated by serous, mucinous and endometroid types with sensitivity of 93.3%, specificity of 64.3%, positive predictive value of 93.3% negative predictive value of 69.2%, and accuracy value of 89.8%. More reliable results were obtained by using “tools”.Conclusion: Contrast-enhanced abdominal CT scan of ovarian tumors in Dr. Soetomo General Academic Hospital, Surabaya, Indonesia, evaluated by “tools” still had a better and more reliable diagnostic value than without tools in determining policy steps in handling ovarian tumors with a note that more in-depth research on pitfalls is needed so it may enrich the characteristic findings in imaging.